Development of optical and electrochemical methods at the nano-scale for high-throughput biochemical sensing by Vince S. Siu Sc.B., Biological and Environmental Engineering, Cornell University, USA, 2007 Thesis Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy awarded jointly by the School of Engineering the Division of Biology and Medicine and the Center for Biomedical Engineering at Brown University Providence, RI May 2014 c Copyright 2014 by Vince S. Siu This dissertation by Vince S. Siu is accepted in its present form by the Biomedical Engineering Graduate Program, a joint program of the School of Engineering, the Division of Biology and Medicine and the Center for Biomedical Engineering as satisfying the dissertation requirement for the degree of Doctor of Philosophy Date . . . . . . . . . . . . . . . . . . . . . . ................................................ G. Tayhas R. Palmore, Ph.D., Advisor Recommended to the Graduate Council Date . . . . . . . . . . . . . . . . . . . . . . ................................................ Domenico Pacifici, Ph.D., Co–Advisor Date . . . . . . . . . . . . . . . . . . . . . . ................................................ Anubhav Tripathi, Ph.D., Reader Date . . . . . . . . . . . . . . . . . . . . . . ................................................ Gary Wessel, Ph.D., Reader Date . . . . . . . . . . . . . . . . . . . . . . ................................................ John C. MacDonald, Ph.D., External Reader Approved by the Graduate Council Date . . . . . . . . . . . . . . . . . . . . . . ................................................ Peter M. Weber Dean of the Graduate School iii The Vita of Vince S. Siu Vince S. Siu was born on September 20th, 1985 in Hong Kong, Hong Kong. She grew up in Toronto, Ontario and completed her Bachelor of Science in Biological and Environmental Engineering at Cornell University in 2007. She continued her grad- uate studies at Brown University, with a dissertation focused on the development of innovative electrochemical, optical and whole-cell engineered devices for analysis of biomolecules such as vitamin D metabolites and glucose. Nanostructured mate- rials (e.g. DNA, nano-grooves and slits) along with molecular biology and micro- fabrication techniques were used to create signal transducers and integrated microflu- idic devices for novel biosensing systems that have the potential to enable faster disease diagnosis and improve health-care decisions. She is currently a candidate for the degree of Doctor of Philosophy in biomedical engineering, which will be awarded at the May 2014 commencement. iv Acknowledgments This thesis is a highly collaborative creation that leaves me greatly indebted to a remarkable and wonderful group of individuals. First and foremost, I would like to thank my advisor, Dr. Tayhas Palmore, for her continuous support in my Ph.D. program. She showed me different ways to approach a research problem and offered encouragement and words of wisdom that helped me grow confidently both as a scientist and as an individual. I am grateful for her continual faith in me even when I was doubtful of my own abilities. Next, I would like to thank Dr. Domenico Pacifici, who taught me to see and describe the world with a more mathematical mind set. His exemplary optimistic disposition helped to foster a strong collaborative environment, and kept us all mo- tivated despite the trials and tribulations of research experiments and academic life. Besides my advisors, I would also like to thank the rest of my dissertation com- mittee, Dr. Anubhav Tripathi who always reminded me that there is a life to be lived while doing research, Dr. Gary Wessel for inspiring my interest in synthetic biology, and Dr. John C. Macdonald for invaluable suggestions and feedback to my thesis. I am also grateful for the help of Michael Jibitsky, Tony McCormick, Charlie Vickers, Christoph Schorl who manages the respective Microelectronics, Scanning Electron Mi- croscope, Machine Shop and CORE Facilities at Brown University. A special thank you also to the administrative staff Diane Felber, Peggy Mercurio, Richard Minogue and John Lee who without them I would not have had the parts needed to perform my experiments in a timely fashion. Many thanks to the former and current Palmore Research Group members: Dr. Sung-Yeol Kim, Dr. Steve Rhieu, Dr. Kwang-min Kim, Sujat Sen, Steven Ahn and Dan Liu for being the best multi-cultural brothers a Canadian-British sister can ask for; Daniel Ludwig, Andrea Rolong, Petros Perselis, Flora Ko, Chezev Matthew and Kelly Jin, for fruitful discussions and unforgettable memories. Also, thank you to the Pacifici Research Group members: Jing Feng, Pei Liu, Patrick Flanigan, Alec Roelke, Vihang Mehta, Kaan Gunay, Abigail Plummer, and Salvo Consentino for accepting v me as an honorary member of your lab. I wish you all the best of luck in your future endeavors. Thank you to all those who have been my guiding lights and sources of inspiration, my dear family and friends, teachers and those whose paths I was fortunate enough to cross. I consider myself extremely lucky to have my mother, Priscilla Siu-Tsang and late father, Clement Siu who through their love, support and sacrifices enabled me to further my education and pursue this degree. I am also thankful to my brother, Joran Siu, his wife, Doris Siu and their son, Lucas Siu for always providing encouragement and comic relief. I would like to also thank Dr. and Mrs. Codella for their support, advice and encouragement through these past few years, and for always being ready to provide me with much needed comfort food. A special thank you goes to my better half and best friend, Dr. Noel Codella, for his unwavering love and support through all the good, bad and mediocre times. Finally, I am grateful to my ferrety sidekicks, Cookie, Cream, CJ and NP who sleeps 18 hours a day while I write this thesis, climbing their cage from time to time to seek my attention when they think I might need a slight distraction. Thank you all from the bottom of my heart. vi Dedication I would like to dedicate this thesis to my mother, Priscilla Siu-Tsang and late father, Clement Wo-Tak Siu. Without their constant love, support and encouragement, this thesis would not exist. vii Contents Acknowledgments v Dedication vii 1 Introduction 1 1.1 Overview of biosensors . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Thesis overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Biochemical analytes . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.1 Clinical significance of vitamin D . . . . . . . . . . . . . . . . 4 1.3.2 Detection methods for 25(OH)D and 1α,25(OH)2 D3 . . . . . . 6 1.3.3 Clinical significance and detection of glucose . . . . . . . . . . 6 1.4 Electrochemical sensors . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4.1 Electrode reactions and electron transfer . . . . . . . . . . . . 8 1.4.2 Kinetics of electron transfer . . . . . . . . . . . . . . . . . . . 8 1.4.3 Mass transport . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.4.4 Electrochemical cell . . . . . . . . . . . . . . . . . . . . . . . . 10 1.4.5 Cyclic voltammetry (CV) . . . . . . . . . . . . . . . . . . . . 11 1.4.6 Electrochemical Impedance Spectroscopy (EIS) . . . . . . . . 13 1.5 Microbial intein-based sensors . . . . . . . . . . . . . . . . . . . . . . 15 1.5.1 Motivation and inspiration . . . . . . . . . . . . . . . . . . . . 15 1.5.2 Vitamin D receptor ligand binding domain (VDR-LBD) . . . . 17 1.5.3 Mycobacterium tuberculosis (Mtu) RecA Intein . . . . . . . . 19 1.5.4 Extein: Green fluorescent protein (GFP) . . . . . . . . . . . . 21 viii 1.6 Optical sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 1.6.1 Introduction to plasmonics . . . . . . . . . . . . . . . . . . . . 25 1.6.2 Coupling of surface plasmons . . . . . . . . . . . . . . . . . . 25 1.6.3 SPP skin depth and propagation length . . . . . . . . . . . . . 27 1.6.4 Sensing volume . . . . . . . . . . . . . . . . . . . . . . . . . . 28 1.7 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2 Direct electrochemistry of mouse cytochrome P450 27B1 in surfac- tant films 37 2.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.3 Experimental details . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.3.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 2.3.2 Expression and purification of CYP27B1 . . . . . . . . . . . . 41 2.3.3 Electrochemistry experiments . . . . . . . . . . . . . . . . . . 42 2.3.4 Film preparation . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 44 2.4.1 Direct electrochemistry of the CYP27B1/DDAB/EPG electrode 44 2.4.2 Determination of α and ks . . . . . . . . . . . . . . . . . . . . 44 2.4.3 Catalytic activity of immobilized CYP27B1 . . . . . . . . . . 47 2.4.4 The potential of the heme FeIII/FeII redox couple of CYP27B1 in DDAB/EPG films . . . . . . . . . . . . . . . . . . . . . . . 49 2.4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 2.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 3 Electrochemical detection of 1α,25-dihydroxyvitamin D3 by electro- chemical impedance spectroscopy 53 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 3.2 Experimental details . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.2.1 Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 3.2.2 Electrochemical set-up and instrumentation . . . . . . . . . . 55 ix 3.2.3 Electrode preparations . . . . . . . . . . . . . . . . . . . . . . 56 3.2.4 Electrochemical measurements . . . . . . . . . . . . . . . . . . 57 3.3 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 57 3.3.1 Electrochemical characterization of modified Au electrodes . . 57 3.3.2 Electrochemical detection of 1α,25(OH)2 D3 binding . . . . . . 60 3.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 3.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 3.6 Appendix: Calculation of a single monolayer of DMPC . . . . . . . . 67 4 Intein-mediated biocircuit for the detection of 1α,25-dihydroxyvitamin D3 69 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 4.2 Experimental details . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2.1 Reagents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2.2 Cell strains . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2.3 DNA plasmid construction . . . . . . . . . . . . . . . . . . . . 71 4.2.4 Protein expression and purification . . . . . . . . . . . . . . . 73 4.2.5 Crude lysate preparation . . . . . . . . . . . . . . . . . . . . . 75 4.2.6 Fluorimeter test for functional intein splicing activity . . . . . 75 4.2.7 Flow-activated cell sorter (FACS) analysis . . . . . . . . . . . 75 4.3 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 75 4.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 4.5 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 5 Nanoscale plasmonic interferometers for multi-spectral, high-throughput biochemical sensing 99 5.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.3 Experimental details . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 5.3.1 Fabrication, optimization and characterization of plasmonic in- terferometers . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 x 5.3.2 Optical set-up and spectral data acquisition . . . . . . . . . . 103 5.3.3 Fabrication of microfludic channel . . . . . . . . . . . . . . . . 105 5.4 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 106 5.4.1 SPP Interference model . . . . . . . . . . . . . . . . . . . . . 106 5.4.2 Detection of glucose using plasmonic interferometry. . . . . . . 120 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 5.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 6 A plasmonic cuvette: dye chemistry coupled to plasmonic interfer- ometry for glucose sensing 139 6.1 Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 6.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 6.3 Experimental Section . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 6.3.1 Reagents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 6.3.2 Fabrication and optical characterization of plasmonic interfer- ometers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 6.3.3 Spectrophotometric kinetic measurements . . . . . . . . . . . 146 6.3.4 Specificity test for glucose in artificial saliva . . . . . . . . . . 149 6.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . 149 6.4.1 Enhanced sensitivity of plasmonic interferometer when coupled to a dye chemistry assay . . . . . . . . . . . . . . . . . . . . . 149 6.4.2 Absorption properties of resorufin . . . . . . . . . . . . . . . . 152 6.4.3 Mathematical model of AR/GOx/Glucose assay . . . . . . . . 155 6.4.4 Determination of K1 . . . . . . . . . . . . . . . . . . . . . . . 156 6.4.5 Tuning the reaction time of the AR/GOx/Glucose assay . . . 162 6.4.6 Specificity test of glucose in artificial saliva . . . . . . . . . . . 169 6.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 6.6 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 6.7 Appendix: Guide to nomenclature . . . . . . . . . . . . . . . . . . . . 175 xi 7 Concluding remarks and future work 179 7.1 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 A Protocol: Expression, purification and fluorescence characterization of IntGFP and IntVDRGFP 185 A.1 Cell growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 A.2 Small scale purification of IntGFP, IntVDRGFP, IntGFP-pelB or IntVDR(118- 425,∆165-215)GFP . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186 A.2.1 Cell disruption . . . . . . . . . . . . . . . . . . . . . . . . . . 186 A.2.2 Aldrithiol treatment . . . . . . . . . . . . . . . . . . . . . . . 186 A.2.3 Column purification procedure . . . . . . . . . . . . . . . . . . 187 A.3 Determination of protein concentration . . . . . . . . . . . . . . . . . 188 A.4 Fluorimeter test for intein splicing assay . . . . . . . . . . . . . . . . 188 A.5 Buffer recipes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 B Performance comparison of plasmonic sensors. 190 xii List of Tables 1.1 Summary of intein-based biocircuit design . . . . . . . . . . . . . . . 17 6.1 Rate constants for the reactions in the AR/GOx/Glucose assay . . . 159 A.1 Plasmids encoding sensor proteins and corresponding antibiotic resis- tance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 B.1 Performance comparison between our plasmonic interferometer method and other conventional, plasmonic and microphotonics approaches. . . 191 xiii List of Figures 1.1 Examples of sources to obtain target analytes and components of a typical biosensor.1,2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Structural and biological properties of two vitamin D metabolites: 25- hydroxyvitamin D3 (25(OH)D3 ) and 1α,25-dihydrovitamin D3 (1α,25(OH)2 D3 ). The hydroxylation of inactive 25(OH)D3 to 1α,25(OH)2 D3 occurs in the kidney via the 1α-hydroxylase (CYP27B1) enzyme. 1α,25(OH)2 D3 is the natural ligand to the vitamin D receptor (VDR) and binds the VDR to regulate over 60 genes in nearly every tissue.3,7,8,9 . . . . . . 5 1.3 (a) Circuit of a three electrode electrochemical cell comprising of a reference electrode (RE), a working electrode (WE) and a counter (also known as an auxiliary) electrode (CE) all immersed in a supporting electrolyte. (b) Example of a typical electrochemical cell used in the experimental work of Chapters 2 and 3. . . . . . . . . . . . . . . . . . 11 1.4 (a) Triangular potential waveform of voltage as a function of time used in cyclic voltammetry. Working electrode potential is scanned from –0.2 to 0.6 V and back to –0.2 V in one cycle. All potentials are referenced to a Ag/AgCl electrode. (b) Cyclic voltammogram of a bare Au electrode in a 0.1 M KCl electrolyte (pH 7.0) containing 10 mM Fe(CN)64−/3− (1:1). Scan rate: 100 mV/s. . . . . . . . . . . . . . 12 1.5 (a) Randles equivalent circuit with parameters described in text. (b) Nyquist plot of impedance data for a bare Au electrode in a 0.1 M KCl electrolyte (pH 7.0) containing 10 mM Fe(CN)64−/3− (1:1). . . . . . . 14 xiv 1.6 Schematic of a generic DNA biocircuit comprising of an intein and extein elements that encode for a sensor protein for small molecule detection. A mini-intein without its homing endonuclease domain is depicted and often the ligand binding domain (LBD) of nuclear hor- mone receptors (NHR) is inserted into this region. The N- and C-extein fragments are nucleotides that together encode for a host sensor protein such as a green fluorescent protein. The primary translation product is known as the precursor protein. Post-translational splicing occurs at the splice junction that contains either a Cys, Ser or Thr residue. Splicing activity produces a ligated sensor protein and an excised intein. 16 1.7 (a) Members of the nuclear receptors form homo- or hetero-dimers and are classified in two groups based on their mechanism of action and sub- cellular distribution in the absence of a ligand. (b) Structure of highly conserved regions of function and sequence for nuclear hormone recep- tors (NHRs). Abbreviations: AF-1, AF-2 = Activiating Function-1/-2; DBD: DNA-binding domain; LBD: Ligand binding domain . . . . . . 19 1.8 Crystal structure of the vitamin D receptor ligand binding domain (VDR-LBD). PDB ID: 1DB1. The amino acid residues include 118-425 with a deletion of 50 residues between 165-215. The distance between the N- and C- termini of the VDR-LBD is ∼40.8 ˚ A. . . . . . . . . . . 20 1.9 Schematic representation of the four-step protein splicing pathway where the amino acid residues that participate in the chemical reaction must be either a hydroxyl- or thiol- containing residue (X = O or S). (Figure adapted from Ref. 51) . . . . . . . . . . . . . . . . . . . . . . . . . . 22 1.10 (a) The tertiary structure (β-barrel) of green fluorescent protein with its approximate dimensions. PDB ID: 2AWL (b) Three amino acids Ser65, Tyr66, and Gly67 undergoes an autocatalytic chromophore for- mation. (Adapted from Refs. 65, 68) . . . . . . . . . . . . . . . . . . 23 xv 1.11 Amino acid sequence comparison of three GFP variants used in con- struction of plasmids I – XI. Plasmid I contains EGFP (F64L, S65T), plasmids II and III contains GFP (F64L, S65T) and plasmids IV – XI contains wtGFP. The hexapeptide region encoded by amino acids 64 – 69 form the chromophore of a fluorescent GFP. . . . . . . . . . . . 24 1.12 The dispersion curve for a surface plasmon polariton (SPP) mode il- lustrates the momentum mismatch problem that must be overcome in order for light to couple to SPP modes. . . . . . . . . . . . . . . . . . 26 1.13 (a) Skin depth of SPPs as a function of wavelength on Ag/air (red line) and Ag/water (black line) interface. (b) Propagation length of SPP as a function of wavelength on Ag/air (red line) and Ag/water (black line) interface. . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.1 The structures of the (a) prosthetic heme-b group and (b) the hexa- coordinated iron center tethered via a thiolate linkage in the CYP protein. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 2.2 Catalytic cycle of cytochrome P450 (Photo courtesy of Dr. Steve Y. Rhieu; adapted and modified from Ref. 2) . . . . . . . . . . . . . . . 40 2.3 (a) In vivo electron transport chain for conversion of 25(OH)D3 into 1α,25(OH)2 D3 via co-factors such as NADPH, ADR and ADX. (b) An electrode replaces the in vivo electron transport chain. CYP27B1 enzymes are purified and immobilized onto the electrode and 25(OH)D3 is converted into its active form, 1α,25(OH)2 D3 electrochemically. . . 41 2.4 Spectral properties of the purified CYP27B1. (a) Absolute spectrum of purified CYP27B1 in 100 mM potassium phosphate, pH 7.4, 20% glycerol, 0.1% 3-[(3-Cholamidopropyl)dimethylammonio]-2-hydroxy-1- propanesulfonate, and 0.5 M NaCl was measured. (b) The concen- tration of purified CYP27B1 was determined from the reduced CO- difference spectrum (i.e., FeII·CO vs. FeII ) using a difference extinction coefficient at 446 and 490 nm of 446−490 = 91 mM−1 cm−1 . . . . . . . 42 xvi 2.5 The CYP27B1 monooxygenase activity was measured in a reconsti- tuted system consisting of the purified CYP27B1, ADR, ADX, and 25(OH)D3 in a final volume of 1 mL of working buffer. After incuba- tion at 37 ◦ C for 5 min, the reaction was initiated by adding NADPH at a final concentration of 1 mM. The reaction was terminated by adding 6 mL of methanol/dichloromethane (1:2, v/v). After extraction, the or- ganic phase was recovered and subjected to the HPLC analysis. HPLC profile of synthetic standards of 25(OH)D3 and 1α,25(OH)2D3, eluted at ∼8.5 min and ∼14.3 min, respectively (panel (a)). HPLC profile of the lipid extract from a CYP27B1 reconstituted assay incubated with 25(OH)D3 (panel (b)). . . . . . . . . . . . . . . . . . . . . . . . . . . 43 2.6 Cyclic voltammetry of CYP27B1 immobilized on a DDAB-modified EPG electrode. (a) The cyclic voltammogram was recorded in deoxy- genated 50 mM potassium phosphate buffer including 50 mM NaBr, pH 7.4, at a scan rate of 0.1 Vs−1 for the CYP27B1/DDAB/EPG (solid) and DDAB/EPG (dashed) electrodes. (b) The voltammetric peaks grow over the course of an hour (a-j: scanned every 5 min over a pe- riod of an hour). (c) Cyclic voltammograms of CYP27B1/DDAB/EPG electrodes at different scan rates (a-n: 0.03, 0.05, 0.075, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1 Vs−1 ). (d) The peak currents in- creased linearly as a function of scan rate up to 1 Vs−1 , indicating that CYP27B1 is confined to the surface of the electrode. Data points represent the mean of triplicate determinations ± S.D. . . . . . . . . 45 2.7 (a) Laviron plot: dependence of the anodic and cathodic peak poten- tials of a CYP27B1/DDAB/EPG electrode on the logarithm of the scan rates. (b) Linear segments of the Laviron plot showing the de- pendence of the peak potential (Ep ) on the logarithm of scan rates. Data points represent the mean of triplicate determinations ± S.D. . 46 xvii 2.8 Cyclic voltammetric responses of CYP27B1/DDAB/EPG electrodes in buffer saturated with argon (a) or dioxygen (c). Negative control (DDAB/EPG electrodes) revealed dioxygen reduction at more negative potentials (b). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 3.1 Schematic of the immobilization procedure starting with (a) bare Au electrode, (b) the supported lipid bilayer membrane (s-BLM): 1,2- dimyristoyl-sn-glycero-3-phosphocholine (DMPC), (c) immobilization of the human vitamin D receptor (hVDR) and (d) exposure of the sur- face modified electrode to 1α,25(OH)2 D3 . Fe(CN)64−/3− : 10 mM of ferro- and ferri- cyanide redox couple used in the working buffer solution. 55 3.2 Absorbance spectrum used to determine the concentration of a stock solution of 1α,25(OH)2 D3 in ethanol using the Beer-Lambert Law. . . 56 3.3 Cyclic voltammograms of a working electrode immersed in a 0.1 M KCl (pH 7.0) electrolyte containing 10 mM Fe(CN)64−/3− (1:1) – (a) Au; (b) DMPC/Au; (c) hVDR/DMPC/Au. Scan rate: 100 mV/s. Inset: CVs of (b) and (c) are expanded. . . . . . . . . . . . . . . . . . . . . 58 3.4 (a) Nyquist plot of impedance data at a bare Au (black squares) work- ing electrode immersed in 1 mL of 0.1 M KCl working buffer contain- ing 10 mM Fe(CN)64−/3− (1:1). Inset: Randles equivalent electrical circuit and is used to interpret impedance spectra generated by the capacitive (ic ) and faradaic (if ) currents. (b) Nyquist plot compares the impedance spectrum of three working electrodes: bare Au (black squares), DMPC/Au (red circles), and hVDR/DMPC/Au (blue trian- gles). Inset: Rct values are the average values obtained from seven independently prepared electrodes. Concentrations used for DMPC and hVDR were 2.2 mM and 0.38 µM, respectively. . . . . . . . . . . 59 xviii 3.5 (a) Nyquist plot of a hVDR/DMPC/Au electrode exposed to a solution containing 0 – 380 nM of 1α,25(OH)2 D3 dissolved in pure ethanol. (b) Corresponding Rct values of the impedance spectra in panel (a) as a function of 1α,25(OH)2 D3 concentration. . . . . . . . . . . . . . . . . 60 3.6 (a) Nyquist plot for the control experiment of pure ethanol exposed to hVDR/DMPC/Au electrode. (b) Corresponding Rct values of the impedance spectra in panel (a) as a function of ethanol concentration. 61 3.7 Calibration curve for detection of 1α,25(OH)2 D3 . The change in the charge transfer resistance (∆Rct ) was calculated from Eq. 3.1. The limit of detection for 1α,25(OH)2 D3 is 52 nM (22 ng/mL). . . . . . . 62 3.8 Nyquist plot showing the impedance spectra of (a) half a monolayer (45 µM); (b) one monolayer (91 µM); and (c) two monolayers (180 µM) of DMPC on a bare Au electrode. An impedance measurement of the DMPC/Au electrode was taken before (black squares) and after (red circles) removing and re-immersing the electrode back into the electrolyte. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 4.1 Schematic of the synthetic protein comprising of a vitamin D receptor (VDR, blue) embedded in a Mtu RecA intein (red) flanked by a split green fluorescent protein (GFP, green). Ligand binding will induce a conformational change in the intein, thus initiating a self-splicing mechanism that produces a dose-dependent fluorescence response via an intact GFP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.2 Step-by-step guide to basic molecular techniques involved in DNA plas- mid construction. Description for each step is described in the text and where appropriate a protocol is provided in Appendix A. . . . . . . . 73 4.3 Step-by-step guide to protein expression and purification for plasmids IV - X. Schematic shows the instructions for plasmid V: pIntVDR(108- 427)GFP. A detailed protocol for IntGFP or IntVDRGFP expression is included in Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . 74 xix 4.4 Construction of pET26b-EGFP used as a positive fluorescent control plasmid. (a) Schematic of plasmids involved to create Plasmid I. (b) Agarose gel to confirm the PCR amplification of enhanced green flu- orescent protein (EGFP) from pEGFP using primers P1 and P2 (720 bp). (c) Agarose gel to confirm successful ligation and transforma- tion of Plasmid III. Lane 1 = 1 kb DNA ladder; Lanes 2 - 7 = DNA from six successfully transformed colonies digested with NotI/NcoI. Multiple cloning site (MCS): 271 bp; Insert: 935 bp. (d) SDS-PAGE illustrating the successful expression of EGFP protein after induction for up to 6 h (26.2 kDa). (e) Western blot using anti-GFP to confirm protein band is our protein of interest. (f) Top to Bottom: Flow acti- vated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b-EGFP with/without 0.4 mM IPTG and/or with/without 1 µM estradiol (E2 ). Abbreviations: AmpR: Ampicillin resistance gene; KanR: Kanamycin resistance gene. . . . . 77 4.5 Construction of pET26b-IntERGFP used as a plasmid to confirm intein splicing activity. (a) Schematic of plasmids involved to create Plasmid II. (b) Agarose gel to confirm the PCR amplification of IntERGFP from p414-IntERGFP using primers P3 and P4 (1953 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid III. Lane 1 = 1 kb DNA ladder; Lanes 2 - 7 = DNA from six successfully transformed colonies digested with NotI/NcoI. Multiple cloning site (MCS): 271 bp; Insert: 2197 bp. (d) SDS-PAGE illustrating the successful expression of IntERGFP protein after 16 h induction with 0.4 mM IPTG (71.6 kDa). (e) Top to Bottom: Flow activated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b- IntERGFP with/without 0.4 mM IPTG and/or with/without 1 µM estradiol (E2 ). Abbreviation: Trp: Tryptophan. . . . . . . . . . . . . 79 xx 4.6 Construction of pET26b-IntVDR(108-427)GFP the biocircuit that en- codes the sensor protein. (a) Schematic of plasmids involved to create Plasmid III. (b) Agarose gel to confirm the digestion of ER-LBD with RsrII/NheI from pET26b-IntERGFP (744 bp) (c) Agarose gel to con- firm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 - 3: PCR amplification of VDR-LBD(108-427) (995 bp) from pN3-Flag-hVDR without and with primers P5 and P6, respectively. (d) SDS-PAGE illustrating the successful expression of sensor protein after induction for up to 12 h (82 kDa). (e) Top to Bottom: Flow acti- vated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b-IntVDR(108-427)GFP with/without 0.4 mM IPTG and/or with/without 1 µM 1α,25(OH)2 D3 . Abbrevia- tion: CMV: Cytomegalovirus promoter . . . . . . . . . . . . . . . . . 80 4.7 Amino acid sequence comparison of the RecA intein from the NIH pro- tein registry (GeneID:888371) which includes the homing endonuclease sequence and the RecA inteins that encodes the N- and C- fragments of p414-IntERGFP (received from Prof. David Liu) and pIntGFP (re- ceived from Prof. Henry Paulus). The latter two inteins have all or part of the homing endonculease region replaced by spacer sequences of different lengths. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.8 (a) Plasmid map for pIntGFP. Note: pelB sequence is not present on this plasmid. (b) SDS-PAGE showing the soluble, insoluble and purified fractions after a 4 h induction and expression of IntGFP (53 kDa). (c) The fluorescent intensity is measured for 75 µg/mL IntGFP with 1 mM TCEP as a function of wavelength. Excitation and emission wavelengths are 395 nm and 510 nm, respectively. (d) Fluorescent intensity measured as a function of time for 75 µg/mL IntGFP with and without 1 mM TCEP. The buffer composition is 20 mM sodium phosphate, pH 7.0, 0.5 M NaCl and 0.5 M L-arginine. . . . . . . . . . 82 xxi 4.9 Construction of pIntVDR(108-427)GFP – the biocircuit that encodes the sensor protein. (a) Schematic of plasmids involved to create Plas- mid V. (b) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = VDR-LBD(108-427) amplified by PCR from from pN3-Flag-hVDR using primers P5 and P6 (960 bp); Lanes 3 - 4 = IntGFP (1450 bp) and IntVDRGFP (2247 bp) amplified by PCR from pIntGFP and pIntVDRGFP using primers T7Fwd and T7Rev, respectively. (c) SDS-PAGE showing the soluble, insoluble and purified fractions after a 4 hr induction and expression of IntVDR(108- 427)GFP (85 kDa). (d) The fluorescent intensity is measured for 75 µg/mL IntVDR(108-427)GFP with 1 mM TCEP as a function of wave- length. Excitation and emission wavelengths are 395 nm and 510 nm, respectively. (e) Fluorescent intensity measured as a function of time for 75 µg/mL IntVDR(108-427)GFP with and without 1 mM TCEP. The buffer composition is 20 mM sodium phosphate, pH 7.0, 0.5 M NaCl and 0.5 M L-arginine. . . . . . . . . . . . . . . . . . . . . . . . 83 4.10 SDS-PAGE showing the spliced products after purified IntGFP and IntVDRGFP expressed from BL21(DE3) cells transformed with plas- mid IV and V, respectively. Samples of IntGFP and IntVDRGFP were kept with or without 1 mM TCEP and/or 1 µM 1α,25(OH)2 D3 . . . . 84 xxii 4.11 (a) Schematic representation illustrating the construction of plasmids VI - VIII which involves successive truncations of the VDR-LBD. The goal is to reduce the overall size of the sensor protein (i.e. IntVDR(108- 427)GFP) to be comparable to the size of the IntERGFP. (b) Agarose gel to confirm the successful construction and truncation of the plas- mids VI - VIII using site-directed mutagenesis and primers P9 - P14. Lanes 1 - 4 = same as Fig. 4.9(b). Lanes 5 - 7 = DNA amplified by PCR using primers T7Fwd and T7Rev on plasmids VI - VIII respec- tively. Expected sizes are: 2094 bp, 2058 bp and 2034 bp. The PCR plasmid controls without amplified product are present in the agarose gel on the right. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 4.12 Amino acid sequence comparison of the region between Int(N) and Int(C) for plasmids IV - VIII. Red: Intein regions; Blue: VDR-LBD of various lengths; Yellow: 6x-His tag. . . . . . . . . . . . . . . . . . . . 87 4.13 Fluorescent intensity as a function of wavelength reported for (a) BL21(DE3) cells only; (b) IntGFP; (c) IntVDR(108-427)GFP; (d) IntVDR(108- 427,∆165-215)GFP; (e) IntVDR(118-427,∆165-215)GFP; and (f) IntVDR(118- 425,∆165-215)GFP. All proteins are expressed with a 0.4 mM IPTG induction for 4 hours and the fluorescent measurements are made in crude lysate from the insoluble fraction. VD = 1 µM 1α,25(OH)2 D3 . 88 4.14 SDS-PAGE showing the soluble and insoluble fractions after IntGFP (53 kDa) has been expressed from BL21(DE3) cells transformed with plasmid IV. Induction conditions are T = 37 ◦ C or 20 ◦ C at a constant IPTG concentration of 0.4 mM. . . . . . . . . . . . . . . . . . . . . . 89 xxiii 4.15 (a) SDS-PAGE showing the soluble and insoluble fractions after Int- GFP has been expressed from BL21(DE3) cells transformed with plas- mid IV. Induction conditions are T = 30 ◦ C or 37 ◦ C and IPTG con- centration at 0.01 mM or 0.1 mM. Fluorescent intensity measured as a function of wavelength for the soluble fraction (T = 37 ◦C and IPTG concentration = 0.1 mM) at (b) pH 7.5, 1 mM TCEP; (c) pH 7.5, 0 mM TCEP; and (d) pH 7.0, 0 mM TCEP. (e) The fluorescent intensity is measured as a function of time for panels (b) – (d) at λ = 510 nm. 91 4.16 Construction of pET26b-IntGFP. (a) Schematic of plasmids involved to create Plasmid IX. (b) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = pET26b di- gested with NotI/EcoRI (5360 bp); Lane 3 = IntGFP amplified from pIntGFP by PCR using primers P17 and P18 (1383 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid IX. Lane 1 = 1 kb DNA ladder; Lanes 2 - 4 = DNA from three success- fully transformed colonies digested with NotI/EcoR. Lane 5: pET26b digested with NotI/EcoRI. . . . . . . . . . . . . . . . . . . . . . . . 92 4.17 (a) SDS-PAGE showing the soluble and insoluble fractions after Int- GFP has been expressed from BL21(DE3) cells transformed with plas- mid IX which contains the pelB sequence. Induction conditions are T = 37 ◦C or 20 ◦ C at a constant IPTG concentration of 0.4 mM. Fluorescent intensity measured as a function of wavelength for the (b) soluble fraction (T = 37 ◦ C) and (c) insoluble fraction (T = 37 ◦ C). (d) The fluorescent intensity is measured for the soluble and insoluble fractions collected from IntGFP expressed from plasmid IX (orange diamond and green triangle, respectively). For comparison, the fluo- rescent intensity measured for IntGFP expressed from plasmid IV in the insoluble fraction is also included (black square, blue triangle and red circle). All fluorescent intensity is measured at λ = 510 nm. . . . 93 xxiv 4.18 Construction of pET26b-IntVDR(118-425,∆165-215)GFP. (a) Schematic of plasmids involved to create Plasmid X. (b) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = pET26b digested with NotI/EcoRI (5360 bp); Lane 3 = Plasmid VIII digested with NotI/EcoRI (5466 bp, 2034 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid X. Lane 1 = 1 kb DNA ladder; Lanes 2 - 8 = DNA from seven successfully transformed colonies digested with NotI/EcoRI; Lane 9: pET26b di- gested with NotI/EcoRI. (d) SDS-PAGE of the soluble and insoluble fractions of the sensor protein induced at 0.4 mM IPTG for 4 h at 37 ◦ C. Red box (1) InteinVDR = 53 kDa; Red Box (2) GFP = 29 kDa. (e) Fluorescent intensity measured as a function of wavelength for the soluble fraction in panel (d) over 12 h. . . . . . . . . . . . . . . . . . 94 5.1 (a) SEM micrograph of a groove-slit-groove (GSG) plasmonic interfer- ometer with p1 = 0.57 µm and p2 = 1.85 µm. The separation distance between each groove and the slit defines one arm of the interferometer. The slit and groove widths are 100 nm and 200 nm, respectively. The depth of each groove is ∼20 nm. (b) Schematic of the working principle of a plasmonic interferometer. A collimated white light beam (λ = 400 – 800 nm) uniformly illuminates the structure. Diffractive scattering by the grooves converts the incident beam into counter-propagating SPPs. The total transmitted intensity (IT ) through the slit is the result of the three-beam interference at the slit position between the incident field amplitude (E0 ), the amplitudes of the propagating SPPs originating from the left groove (ESP P 1 ) and from the right side groove (ESP P 2 ). The interference conditions can be tuned by varying the length of the interferometer arms (p1 , p2 ) and the incident wavelength, λ. . . . . . 102 xxv 5.2 Scanning electron microscopy (SEM) images of two different types of plasmonic interferometers: (a) a groove-slit plasmonic interferometer with interferometer arm (groove-slit separation distance) p = 2.00 µm, (b) a groove-slit-groove plasmonic interferometer with p1 = 0.57 µm and p2 = 2.00 µm. The groove width is 200 nm, length is 10 µm and depth is ∼20 nm. The slit is 100 nm wide, 10 µm long and 300 nm deep.104 5.3 Optical path and experimental set-up to acquire the light intensity transmitted through the slit of each plasmonic interferometer . . . . . 105 5.4 Simulated normalized per-slit transmitted intensity spectra for a two- arm plasmonic interferometer with two grooves at distances of p1 = 0.57 µm and p2 = 9.75 µm from the slit (black line), and a one-arm plasmonic interferometer with one groove p = 0.57 µm (red line). . . 108 5.5 (a) Spectra of light intensity transmitted through an isolated slit (red line) and through the slit of a GSG plasmonic interferometer with p1 =0.57 µm and p2=1.85 µm (black line) on a silver/air interface. (b) Normalized per-slit transmission spectrum for the same GSG plasmonic interferometer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 5.6 Simulated 2D color map of normalized light intensity transmitted through the slits of several plasmonic interferometers with p1 = 0.57 µm, as a function of groove-slit arm length p2 (horizontal axis) and wavelength λ (vertical axis). Also reported are typical plots obtained by horizontal or vertical cuts across the color map (indicated by grey boxes). . . . . 112 5.7 2D experimental color map of normalized to single-slit light intensity transmitted through the slits of several groove-slit plasmonic inter- ferometers, as a function of groove-slit distance p and wavelength λ (Ag/air interface). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 5.8 Color maps showing experimental (a)–(f) and simulated (g)–(l) nor- malized transmission spectra (wavelength in vertical axis) for GSG plasmonic interferometers with fixed p1 (400, 570, 740, 890, 1090, 1670 nm) and varying p2 (250 – 2000 nm, in steps of 25 nm). . . . . . . . . 114 xxvi 5.9 Wavelength dependence of the excitation efficiency β for SPPs gener- ated by diffractive scattering by a 200-nm-wide groove milled in Ag with air as the dielectric medium. Data points were determined from the experiments of the groove-slit plasmonic interferometer with vary- ing p (black dots). The red line is a fit of the experimentally determined data based on a least-square fitting method. . . . . . . . . . . . . . . 116 5.10 Simulated color maps showing normalized per-slit transmission spectra (wavelength in vertical axis) for groove-slit-groove plasmonic interfer- ometers with fixed p1 (400, 570, 740, 890, 1090, 1670 nm) and varying p2 (250 – 2000 nm, in steps of 25 nm), using white light illumination incident upon a Ag/air interface ((a)–(f)) and a Ag/water interface ((g)–(l)). The dielectric constant of water at various wavelengths was used to calculate (g)–(l). It is interesting to note that the increased refractive index of water determines the appearance of more peaks (compared to air) in the color maps for the very same devices. . . . . 117 5.11 Color maps showing a comparison between experimental and simulated transmission spectra (normalized to single slit) for groove-slit-groove plasmonic interferometers with varying p2 (between 8.00 – 9.70 µm) for Ag/air and Ag/water interfaces. . . . . . . . . . . . . . . . . . . . 118 xxvii 5.12 Color map shows simulated normalized transmission spectra (wave- length in vertical axis) for groove-slit-groove plasmonic interferometers with fixed p1 = 0.57 µm and varying p2 (0.25 – 10 µm, in steps of 25 nm), for a Ag/water interface. With larger p2 , there are more peaks and valleys in the spectra (vertical cuts), even for plasmonic interfer- ometer arms as long as 10 µm, which suggests that longer plasmonic interferometers have higher sensitivity. Due to absorption losses in the metal, the amplitude of the SPPs generated by longer plasmonic interferometers is attenuated, and as a result the constructive and de- structive interference effects are less pronounced. This explains the lower values of per-slit normalized transmission maxima observed at p2 = 10 µm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 5.13 Normalized per-slit transmitted intensity spectra for two GSG plas- monic interferometers with one arm length held constant at p1 = 0.57 µm and the other arm length held at p2 = 1.85 µm (black solid line) and 5.70 µm (red solid line), respectively. Dashed lines represent sim- ulated spectra for each of the two devices: p2 = 1.85 µm (black dashed line) and p2 = 5.70 µm (red dashed line). . . . . . . . . . . . . . . . . 121 5.14 (a) Normalized per-slit transmitted intensity spectra of a GSG device with p1 = 0.57 µm and p2 = 5.70 µm measured at various concentra- tions of glucose in water. (b) Relative intensity change as a function of wavelength (normalized to pure water) for the same device, at various concentrations of glucose in water. . . . . . . . . . . . . . . . . . . . . 123 5.15 Calibration curves for a plasmonic interferometer with p1 = 0.57 µm and p2 = 5.70 µm, used as a glucose sensor. (a) Measured (black solid squares) and simulated (black line) wavelength shifts as a func- tion of glucose concentration at 610 nm. (b) Measured (symbols) and simulated (lines) relative intensity change as a function of glucose con- centration measured at 590 nm (red circles and red line) and 610 nm (black squares and black line). The error bars are within the symbols. 124 xxviii 5.16 Refractive index as a function of glucose concentration (ρ), at a wave- length of 589 nm, 20 ◦ C. . . . . . . . . . . . . . . . . . . . . . . . . . 125 5.17 Performance comparison at 590 nm for four GSG plasmonic interferom- eters. Three of them have one arm length p1 , = 0.57 µm and different p2 : p2 = 1.85 µm (black squares), p2 = 5.70 µm (red rhombi) and p2 = 9.75 µm (green triangles). The fourth plasmonic interferometer has p1 = 5.70 µm and p2 = 9.75 µm (orange circles). The inset in (a) shows relative intensity change spectra as a function of wavelength for four different glucose concentrations: 10, 200, 4000 and 14000 mg/dL, where the wavelength shift and intensity change are clearly visible. The dashed lines are calibration curves obtained by least-square fittings of the scattered data points. (a) Wavelength shift versus glucose concen- tration for two devices with constant p2 = 9.75 µm and different p1 of 0.57 µm and 5.70 µm. (b) Relative intensity change versus glucose concentration for these two devices. (c) Wavelength shift versus glu- cose concentration for three devices with constant p1 = 0.57 µm and different p2 = 1.85, 5.70 and 9.75 µm. (d) Relative intensity change versus glucose concentration for these three devices. The error bars for relative intensity change are within the symbols. The grey boxes highlight the physiological range of glucose in saliva (light grey) and in serum (dark grey), respectively. . . . . . . . . . . . . . . . . . . . . 128 5.18 Color map reporting the simulated figure of merit (FOMI ) as a func- tion of glucose concentration and groove-slit distance p2 , for a fixed wavelength λ = 590 nm and groove-slit distance p1 = 0.57 µm. Plas- monic interferometers with longer p2 have a higher FOMI . However, for a given device, the FOMI decreases at higher concentrations, as experimentally observed. . . . . . . . . . . . . . . . . . . . . . . . . . 129 5.19 Color maps of simulated FOMI as a function of groove-slit distances p1 and p2 , for various glucose concentrations: 0.1, 5000, 14,300 mg/dL. 130 xxix 5.20 Plots of simulated FOMI versus glucose concentration for three differ- ent devices, at a fixed wavelength (λ = 590 nm). The plots show the complex non-linear functional dependence of FOMI . In particular, the blue line reports on the FOMI of a device that shows no significant change in transmitted intensity up to a concentration of 200 mg/dL. This evidences the importance of careful choice of p1 , p2 and λ for the optimization of device sensitivity in the concentration range of interest. 131 6.1 Overview of the plasmonic cuvette: plasmonic interferometry coupled to dye chemistry. (a) The Amplex Red/Glucose Oxidase/Glucose assay consumes glucose and produces resorufin in a 1:1 stoichiometric ratio via enzymatic reactions; (b) reaction 1 is the oxidation of β-D-glucose to D-gluconolactone by O2 to produce H2O2 , catalyzed by GOx; (c) reaction 2 is the oxidation Amplex Red (colorless) into resorufin (red), catalyzed by HRP; (D) reaction 3 is a side reaction with low yield that further oxidizes resorufin to an optically inactive product; (e) the effec- tive rate constants for the three reactions (K1, K2 and K3 ) were deter- mined by time-dependent kinetic studies of resorufin absorption using a UV-Vis cuvette; (f) the absorption cross-section (σ) and extinction coefficient () of resorufin as a function of wavelength; (g) schematic of the plasmonic cuvette; (h) sample data from the plasmonic cuvette: spectral absorption is correlated with resorufin concentration. . . . . 143 xxx 6.2 Spectral absorbance of stock concentrations for the commonly used reagents in this study: (a) glucose oxidase (GOx), (b) horseradish peroxidase (HRP) and (c) hydrogen peroxide (H2O2 ). The values for the extinction coefficient come from the literature;38−40 this is used in conjunction with the Beer-Lambert law to find the concentration (re- ported in each panel). In panels (a) and (b), the extinction coefficient is reported at the wavelength corresponding to maximum absorption. Glucose oxidase is stable for at least 24 h at room temperature; both GOx and HRP are stable at 4 ◦ C for at least two weeks. . . . . . . . 145 6.3 Surface re-usability test for a chip deposited with (a) 4-nm Ti followed by 300-nm Ag or (b) the same chip in part (a) with an additional 5-nm of Al2O3. Ten µL of 5 buffer solutions: (1) Buffer A: 50 mM sodium phosphate buffer (pH 7.4); (2) Buffer B: Buffer A with 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP, and 82.5 ± 0.7 nM GOx; (3) Buffer B with 5 µM D-(+)-Glucose; (4) Buffer B with 100 µM D-(+)-Glucose; (5) Buffer B with 250 µM D-(+)-Glucose; were drop-casted onto the surface of (a); allowed to sit for 30 min before thoroughly rinsed with copious amounts of water. This procedure was repeated for the same chip after Al2O3 deposition as seen in part (b). (c) Contact angle measurements were made using a goniometer with 5 µL droplet of water onto surface of (a) and (b). (d) The normalized per-slit transmitted intensity was measured in water for a GSG plasmonic interferometer coated with 5-nm of Al2O3 with p1 = 9.75 µm and p2 = 7.85 µm before and after exposure to AR/GOx/Glucose assay. . . . . . . . . . . . . . . . . . . 147 xxxi 6.4 The amount of spontaneous oxidation of AR/GOx/Glucose assay was determined by measuring the transmittance through the cuvette of a reaction mixture containing 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 82.5 ± 0.7 nM GOx dissolved in a 50 mM sodium phosphate buffer solution (pH 7.4) without glucose every 30 min for 10 h at λ = 571.7 nm. The percentage of spontaneous oxidation was calculated by setting the complete oxidation as the transmittance measured for the same reaction mixture reacted with 250 µM glucose to 100%. . . . . . . . . 148 6.5 Enhancing the sensitivity of a plasmonic interferometer with the dye assay. (a) Relative intensity change plotted as a function of wavelength for a groove-slit-groove (GSG) plasmonic interferometer with 250 ± 6 µM glucose in the presence (red solid line) or absence (blue dashed line) of the assay. Both spectra are normalized to a reaction mixture with 0 µM glucose (black solid line). (b) Calibration curves for the same GSG device used in part (a) as function of glucose concentration in the presence (red squares, λ = 571 nm) or absence (blue circles, λ = 628 nm) of the assay. . . . . . . . . . . . . . . . . . . . . . . . . . 151 6.6 (a) Spectra of the absorption coefficient, α, for four different concen- trations of resorufin in a 50 mM sodium phosphate buffer solution (pH 7.4) using a 0.2-cm path length cuvette. (b) Absorption coefficient as a function of the density of absorbing resorufin molecules (ρ) or the molar concentration of resorufin (c) at λ1 = 530 nm (blue circles), λ2 = 571 nm (red squares) and λ3 = 590 nm (purple triangles). This plot was obtained by taking a cross-section of the curves in panel (a) at λ1 , λ2 and λ3 . (c) The slope of a linear fit of curves in panel (b) represents the absorption cross-section of a resorufin molecule (σ) at a specified wavelength. This process was repeated for the entire range of wavelengths (450 nm < λ < 700 nm) in steps of 1 nm. . . . . . . . . 154 xxxii 6.7 Concentration of resorufin plotted as a function of time (symbols) in steps of 0.1 s, obtained from transmission measurements (at λmax = 571 nm). The solution contains 9.8 ± 0.2 µM resorufin and 8.8 ± 0.2 µM H2O2 , with either 0 nM, 5.5 ± 0.1 nM, 27.5 ± 0.6 nM, or 55 ± 1 nM HRP. The transmission data was plugged into Eq. 6.6 to find the concentration of resorufin. Experimental data points are reported every 5 s for clarity; the confidence band indicates the error for all data points. The measurements were repeated three times at each [HRP] value; the data in the figure shows the average value. The fits (solid lines) are obtained using a pseudo-first-order kinetics model (Eqs. 6.9 – 6.10) with K1 = 0 and K2 = 0. The best agreement between experimental data and the mathematical model corresponds to the case where [HRP] was 5.5 ± 0.1 nM. Therefore, this concentration of HRP was used for all other kinetic experiments in this study - K3 was found to be 56 ± 7 M−1 s−1 when averaged over the three trials at that particular concentration. . . . . . . . . . . . . . . . . . . . . . . . . . 157 xxxiii 6.8 (a) Concentration of resorufin plotted as a function of time (symbols) in steps of 0.1 s obtained from transmission measurements (at λmax = 571 nm). The solution contains 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP, and either 3.8 ± 0.1 µM, 7.8 ± 0.1 µM, or 15.5 ± 0.3 µM H2O2 . The transmission spectrum, along with Eq. 6.11, was used to find the concentration of resorufin. The measurements were repeated three times at each [H2O2 ] value; the data in the figure shows the average value. Experimental data points are reported every 5 s for clarity; the confidence band indicates the error for all data points. The fits (solid lines) are obtained using a pseudo-first-order kinetics model (Eqs. 6.7 – 6.10) with K1 = 0 and K3 = 56 ± 7 M−1 s−1 (as found in S3). (b) The average rate constant K2 was determined for three independent trials at each concentration of H2O2 (the error bars are within the data points). The mean value of all trials and concentrations is K2 = 135 ± 5 M−1 s−1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 6.9 Concentration profile of all six reactants in the AR/GOx/Glucose as- say simulated with (a) [G]t=0 = 30.2 ± 0.1 µM and (b) [G]t=0 = 210 ± 5 µM as functions of time. G = Glucose, O2 = Oxygen, H2O2 = Hydrogen Peroxide, AR = Amplex Red, R = Resorufin, OIP = Op- tically Inactive Product (c) Concentration profile of H2O2 production over time simulated at different initial glucose concentration ([G]t=0 ) conditions. Even when the initial concentration of glucose is high, the H2 O2 concentration never exceeds 10 µM. . . . . . . . . . . . . . . . 160 xxxiv 6.10 Spectral absorption of resorufin at different times after the reaction is initiated; each curve is normalized to its own maximum value. The insets show the raw absorption data. In both panels, the mixture con- tains 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP; (a) includes 82.5 ± 0.7 nM GOx and 50.0 ± 0.9 µM glucose (reactions 1, 2 and 3 occur); (b) in- cludes 27.1 ± 0.5 µM H2O2 (only reactions 2 and 3 occur). The curves within each panel are virtually identical at times, clearly demonstrat- ing that no other optically active product besides resorufin is being generated in the reactions. . . . . . . . . . . . . . . . . . . . . . . . . 161 6.11 (a) Intensity of light transmitted through the assay mixture plotted as a function of time at different concentrations of glucose. The transmit- tance through a cuvette (L = 0.2 cm) is monitored every 1 s for 2000 s at λmax = 571 nm; the data points are plotted in steps of 50 s for clarity (the confidence band interval is kept at 1 s). Each measurement is performed three times; the data shows the average of the three trials. (b) Concentration of resorufin plotted as a function of time using Eq. 6.11 (symbols). A non-linear first order kinetic model was used to fit the data (solid lines). (c) The mean value of three independent trials at each concentration of glucose is reported as K1 = 7.3 ± 0.3 M−1 s−1 . 163 xxxv 6.12 Effect of illumination intensity on the photo-oxidation of Amplex Red. (a) Three neutral density filters Filter A (22%), Filter B (7.6%) and Filter C (0.85%) - were used to attenuate the illumination intensity of the visible light source of the UV-Vis spectrophotometer. (b) The resorufin concentration was determined for a reaction mixture contain- ing 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 27 ± 0.5 µM H2O2 after 300 s in the dark (in grey) and after illumination every 0.1 s for 300 s. The illumination intensity was decreased with the use of neutral density filters. The experiments were repeated in triplicate. This data shows that the illumination intensity does not significantly affect the concentration of resorufin, which means that the photo-oxidation of Amplex Red is not occurring in the time scales of these experiments. 164 6.13 Relationship between assay time and GOx concentration for reaction 1. (a) Normalized concentration of resorufin plotted as functions of time at various GOx concentrations. The black arrow indicates the direction of decreasing reaction time. (b) Reaction time, t is plotted as a function of GOx concentration. . . . . . . . . . . . . . . . . . . . 165 6.14 (a) Relationship between K1 and concentration of GOx in reaction 1. The data points refer to experimental measurements of K1 performed in triplicate (average value reported). (b) Extracted K3 values as a function of HRP concentration indicates a linear dependence with a slope of K3 ’ = (1.45 ± 0.04) × 1010 M−2 s−1 . . . . . . . . . . . . . . . 167 6.15 Effects of artificial saliva on the AR/GOx/Glucose assay. The concen- tration of resorufin plotted as a function of time for reaction mixtures initiated with [G]t=0 = 13 ± 0.6 µM in either (1) artificial saliva diluted in 50 mM sodium phosphate buffer (1:6 v/v ratio, red circles) or (2) 50 mM sodium phosphate buffer (blue triangles). The control experiment is diluted artificial saliva with 0 µM glucose (black squares). . . . . . 168 xxxvi 7.1 (a) Schematic of the proposed integrated sensor for detection of glucose in saliva. (b) Image of a CCD camera unit currently under develop- ment. Also shown are the LCD panel, backlight source, and a dis- posable biochip; inset shows a detail of a gold biochip with integrated plasmonic interferometers placed on the CCD camera. (c) Illustrated step-by-step instructions that guides user with sample collection and use of the device. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182 xxxvii Chapter 1 Introduction 1.1 Overview of biosensors Over the last three decades, remarkable progress has been made in the development of biosensors and their applications in the areas of medical diagnostics, drug screening, food safety, and environmental protection. A biosensor is an analytical device that converts a biological response into a quantifiable signal. Figure 1.1 illustrates the main components of a typical biosensor starting with (a) the sources to obtain the target analyte of interest; (b) the target analyte which can include small molecules, proteins or cells with various size and shape; (c) the biorecognition element that bind specifically to the analyte; (d) the transducer element - the interface at which a transducer signal is produced upon a binding event between the analyte and the biorecognition element; and (e) the quantifiable signal that can be further amplified and processed to display the desired quantity. The scope of this dissertation is focused on the development of four different biosensors for medical diagnostics, with a specific focus on the detection of vita- min D in serum and glucose in saliva. Several different nanoscale biorecognition elements (e.g. DNA, receptors, enzymes and nano-grooves/slits) were coupled with electrochemical, microbial and optical transducers to offer improved and alternative methods to vitamin D and glucose detection. For all biosensors, the main performance characteristics for evaluation include 1 2 Figure 1.1: Examples of sources to obtain target analytes and components of a typical biosensor.1,2 the sensor’s sensitivity, selectivity, accuracy, repeatability, response time, limit of detection, dynamic range and multiplexing. Sensor sensitivity is the ratio of the change in the sensor output (i.e. current, resistance, fluorescence, wavelength or intensity) to the change in the analyte concentration. Selectivity describes the device’s ability to detect the target analyte within a complex mixture. Accuracy is the degree of closeness of the sensor’s measurements to the actual quantity value of the sample. Repeatibility refers to capability to reproduce the output give the same measurement condition. Response time is the amount of time required to acquire data, process and produce a quantifiable response. The limit of detection is the smallest amount of analyte that can be reliably detected. The dynamic range is the ratio between the largest measured concentration and the limit of detection. Multiplexing refers to the ability to detect two or more analytes of interest. The ideal characteristics of a practical sensor with clinical utility would include (1) high sensitivity and selectivity towards the target analyte; (2) is accurate and repeatable; (3) offers real-time and multiplexing capabilities; and (4) has a low limit of detection but a high dynamic range. For each sensor described in this thesis, several or all of the above performance characteristics were evaluated and the advantages highlighted in comparison to existing methods for vitamin D or glucose detection. 3 1.2 Thesis overview This thesis is made up of seven chapters describing the development of four biosensors for the specific detection of physiological levels of vitamin D metabolites in serum and glucose in saliva. Chapters 2 and 3 employ electrochemical methods to detect important vitamin D metabolites that support healthy teeth, bone and immune health. In Chapter 2, the inactive form of vitamin D, 25-hydroxyvitamin D3 (25(OH)D3 ), the most common circulating form of vitamin D is sensed amperometically using its cognate enzyme, CYP27B1 (1α-hydroxylase) expressed and purified from bacteria cells. The enzyme was embedded in a lipid film and immobilized onto an edge-plane graphite (EPG) elec- trode for electrochemical characterization. In Chapter 3, the active form of vitamin D, 1α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3 ) is selectively sensed via the vitamin D receptor immobilized in a lipid film on a gold electrode. The faradic impedance of these modified electrodes was measured in the presence of varying concentrations of 1α,25(OH)2 D3 using electrochemical impedance spectroscopy (EIS). Chapter 4 focuses on the design and assembly of a DNA biocircuit that encodes a sensor protein expressed within bacterial cells to produce a dose-dependent fluorescent response in the presence of 1α,25(OH)2 D3 . Expression of the sensor protein resulted in inclusion body formation, which are aggregates of improperly folded and inactive proteins. Different parameters including the length of the vitamin D receptor (VDR), induction conditions and addition of a pelB leader sequence are explored in attempt to express the sensor protein into the soluble fraction so that inclusion body formation can be minimized and splicing activity demonstrated. Chapters 5 and 6 highlight the development of a novel, high-throughput, optical plasmonic interferometer sensor for the real-time, sensitive and selective detection of glucose. Chapter 5 introduces the pioneering work of novel groove-slit-groove plasmonic interferometers and the characterization and optimization of their optical response. Chapter 6 describes the re-usability of the chip as well as the selectivity of glucose by coupling the plasmonic interferometers with the Amplex Red dye assay. 4 Chapter 7 provides some concluding remarks and potential future directions for each of the four sensors discussed in this dissertation. The remainder of Chapter 1 provides a brief explanation for the clinical signif- icance of vitamin D and glucose detection and covers some of the fundamentals of electrochemical, microbial and optical-based methods for biochemical sensing. 1.3 Biochemical analytes 1.3.1 Clinical significance of vitamin D Vitamin D3 is a fat-soluble, seco-steroid that plays a primary role in calcium home- ostasis and a secondary role in immune regulation, cellular differentiation and apoptosis.3 Its molecular structure closely aligns to that of other classic steroid hormones (e.g. estradiol (E2 ), tri-iodothyronine (T3 ) and thyroxine (T4 )). Several forms of vitamin D3 exist, with the two major forms being ergocalciferol (D2 ) and cholecalciferol (D3). The vitamin D2 is typically found in plants and can be obtained via dietary means. Vitamin D3 is produced photochemically in the skin from 7-dehydrocholesterol in the presence of UVB light (280 – 320 nm), then hydroxylated in the liver to be- come 25-hydroxyvitamin D3 (25(OH)D3), and further hydroxylated in the kidney by the enzyme cytochrome P450 27B1 (CYP27B1) to become α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3 ). Although 25(OH)D3 and 1α,25(OH)2 D3 can both be measured directly in blood, the measurement of 25(OH)D provides the best measure of vita- min D status. This is because the first hydroxylation step is unregulated and the second hydroxylation step is highly regulated, so a decrease in 1α,25(OH)2 D3 levels does not occur until an individual has significant deficiency. The 25(OH)D form also has a much longer serum half-life than 1α,25(OH)2 D3 (3 weeks vs. 4 – 6 hours),4 making 25(OH)D3 a better measure of one’s vitamin D nutritional status. The active 1α,25(OH)2 D3 acts like a steroid hormone and targets its cognate vitamin D receptor (VDR), which functions as a nuclear transcription factor that regulates the physio- logical responses of over 36 different cell types and the expression of as many as 500 5 Figure 1.2: Structural and biological properties of two vitamin D metabolites: 25- hydroxyvitamin D3 (25(OH)D3 ) and 1α,25-dihydrovitamin D3 (1α,25(OH)2 D3 ). The hydroxylation of inactive 25(OH)D3 to 1α,25(OH)2 D3 occurs in the kidney via the 1α- hydroxylase (CYP27B1) enzyme. 1α,25(OH)2 D3 is the natural ligand to the vitamin D receptor (VDR) and binds the VDR to regulate over 60 genes in nearly every tissue.3,7,8,9 of the ∼20,488 genes in the human genome.5,6 Figure 1.2 provides a comparison of the main structural and biological differences between 25(OH)D3 and 1α,25(OH)2 D3 . For the past few decades, the role of vitamin D3 as a vitamin and its contribution to good health has become the subject of heavy debate in the public health arena. Much of the debate has been fueled by the results of two studies published by the National Health and Nutrition Examination Survey (NHANES) population in 1994 and in 2004 indicating a near doubling in the number of subjects in the American population from 1994 to 2004 with insufficient levels of vitamin D.10 Some factors underlying this dramatic decrease in vitamin D insufficiency can be associated with a trend: 1) downward in milk consumption; 2) upward in sun protection and sun avoidance; and 3) upward in body mass index (BMI).11 Clinically, low vitamin D status is associated with a growing number of diseases including congestive heart failure,12 impaired absorption of intestinal calcium,13 as well as prostate, breast, and colon cancer.14 Additionally, severe vitamin D deficiency has long been associated with rickets in children and osteomalacia in adults.15 The U.S. Institute of Medicine of the National Academy of Sciences has set a daily rec- 6 ommended intake necessary to maintain vitamin D levels above that which rickets occurs. Efforts to fortify common foods (e.g., milk) has led to a decrease in the in- cidence of vitamin D-related bone diseases. The clinical importance of vitamin D makes it a compelling analyte to quantify rapidly and accurately. 1.3.2 Detection methods for 25(OH)D and 1α,25(OH)2D3 Many assays have been developed to measure the concentrations of vitamin D metabo- lites in blood. The gold standard is high-performance liquid chromatography (HPLC) coupled with UV detection or mass spectroscopy, but alternative methods such as competitive protein binding assays (CPBA) or competitive radioimmunoassays (RIA) do exist. HPLC is an accurate method for detecting 1α,25(OH)2 D3 as well as dif- ferentiating between the D2 versus D3 forms of 25(OH)D, however, this method re- quires expensive equipment, large sample volumes, extensive extraction procedures, and highly skilled technicians. CPBA and RIA assays require the use of an organic solvent to extract and purify the metabolite from its lipophilic vitamin D binding protein partner, which can lead to variable co-precipitation of the 25(OH)D analyte.4 Thus, presented in Chapters 2 − 4 of this dissertation is the development of two innovative electrochemical-based biosensors and a microbial intein-based biosensor for the measurement of 25(OH)D and 1α,25(OH)2 D3 in hopes to circumvent many of the aforementioned technical challenges. 1.3.3 Clinical significance and detection of glucose Diabetes mellitus (diabetes) affects over 347 million people worldwide is a metabolic disorder where excess blood glucose is not properly regulated by the pancreas.16 Dia- betes is controlled by adjusting the insulin level in a patient to properly regulate the blood glucose level. Insulin is either directly injected into the bloodstream (Type I) or oral medication is used to stimulate the pancreas to produce more insulin (Type II). Insulin therapy and self-monitoring using a blood glucose meter has allowed many to manage their condition and live long, healthy lives. However, patients are required 7 to check their blood glucose levels by pricking their fingers to obtain blood samples on average eight to fifteen times a day. Repeated injury to the fingers quickly leads to calloused fingertips in < 1 year of diagnosis, psychological aversion to pin-pricking, and inconvenience for dependent caretakers. The possibility to replace finger pricks with a non-invasive method shows promise to allow more frequent and accurate blood glucose monitoring, while avoiding chronic injuries to any part of the body. Chapters 5 and 6 present a novel plasmonic interferometer platform that offers an alternative, non-invasive, optical method for detecting glucose in saliva. As diabetes becomes more prevalent, it is our hope that this highly-sensitive and selective method can bring great improvement and comfort in diabetic care. 1.4 Electrochemical sensors There are three main categories of electrochemical biosensors. The first are am- perometric sensors where a voltage or a series of voltages are applied to a working electrode and the resulting current flow is measured. Example techniques include potential step voltammetry, linear sweep voltammetry (LSV) and cyclic voltammetry (CV). The second are potentiometric sensors that measure a voltage- rather than current-dependent output such as chronoamperometry (CA). The first two categories are based on dc theory which assumes that the frequency equals 0 Hz. Impedimet- ric sensors are the last group of electrochemical biosensors where a small-amplitude voltage perturbation is applied to an electrochemical cell and the current response is detected. A technique known as electrochemical impedance spectroscopy (EIS) mea- sures the impedance, Z – the ability of a circuit to resist the flow of electrical current and reveals important electrode properties such as its capacitance and charge-transfer kinetics.17 In Chapters 2 and 3, CV and EIS techniques are employed to characterize bilayer lipid films with embedded enzymes and receptor proteins. Both CV and EIS are widely used techniques for acquiring qualitative information about electrochemical reactions and can provide insight into the charge transfer processes of surface-modified 8 sensing electrodes. To better understand these two methods in greater detail, a few basic electrochemical concepts will be first introduced. 1.4.1 Electrode reactions and electron transfer A typical electrode reaction involves the transfer of charge between the electrode surface to electroactive molecules in the interfacial region. These molecules may be redox active, meaning that the transfer of electrons causes a change in the oxidation state of the atoms involved in the chemical reaction. The general reaction describing the electron transfer between a reduced (R) and oxidized (O) species is described by Eq. 1.1: R  O + ne− (1.1) where n is the number of electrons transferred from the reduced species to the oxidized species. The main driving force of charge transfer between an electrode and an electroactive species is an externally applied dc voltage (in units of volts, V). A volt is the amount of energy measured in Joules (J) required to move charge measured in Coulombs (C). Metals are comprised of closely packed atoms with valence electrons in their crystal structure that carries a charge with a specific energy. When the applied voltage is low, it is thermodynamically unfavorable for the electron to move from the electrode to the species and no reduction will occur. By increasing the applied voltage and thereby increasing the energy of the electrons in the metal, electron transfer becomes more thermodynamically favored and the oxidized species is reduced.17 1.4.2 Kinetics of electron transfer In electrochemistry, Faraday’s law describes the amount of charge passed in an elec- trochemical experiment (Q) as a function of the number of moles of electroactive 9 species electrolyzed (N) (Eq. 1.2). Q = nF N (1.2) where n is the number of electrons (to reduce/oxide one molecular of analyte) and F is Faraday’s constant (F = 96,485 C/mol). By taking the differential form of this Law, we obtain Eq. 1.3: dQ dN = i = nF (1.3) dt dt which shows that the measurable current is directly proportional to the rate of electrolysis.18 The kinetics of electron transfer between the electrode and the electroactive species located in the interfacial region is influenced by the cell potential difference. However, another critical factor in maintaining electrolysis is the rate of mass transport of electrolyzed molecules between the interfacial region and the bulk electrolyte. In a majority of electrochemical experiments, mass transport is the rate limiting step and not electron transfer.17 1.4.3 Mass transport There are three types of mass transport: convection, migration and diffusion. Con- vection is the molecular motion imposed by the bulk motion of the electrolyte (i.e. stirring) and can be consider negligible when working in an unstirred environment. Migration is the molecular motion down an electric gradient and can be eliminated by using a supporting electrolyte with a high salt concentration to ensure low electri- cal resistance. Diffusion is the molecular motion down a concentration gradient and plays a significant role in electrolysis experiments since the reaction occurs only at the electrode surface.18 The Cottrell equation describes the change in electric current with respect to time and when the current measured is dependent on the rate at which the analyte diffuses 10 to the electrode surface, the system is said to be diffusion − controlled . The Cottrell equation is derived from Fick’s second law of diffusion and is described by Eq. 1.4: r D i = nF AC (1.4) πt where i is the current measured in Amps, A is the electrode area in cm2, C is the initial concentration of the reducible analyte in mol/cm3, D is the diffusion coefficient of the analyte in cm2/s and t is time in s. 1.4.4 Electrochemical cell A typical electrochemical experiment is carried out in an electrochemical cell with two or three electrodes, acting as electrical conductors, immersed in a supporting electrolyte solution. The energy source for driving an electrode reaction is an exter- nally applied dc voltage (in units of volts, V = Joule/Coulomb) resulting in a finite current with a magnitude related to the amount of redox chemical activity occurring at the electrodes. In a two-electrode cell, the working electrode (WE) is the site of electrolysis - the transfer of charge to and from an electroactive species under an applied potential. The counter electrode (CE) has a known potential and supplies a current to the WE to balance the charge added or removed in the redox reactions. A major short-coming of this method is the difficulty in maintaining a constant potential at either electrodes when a continuous current is passed, a phenomenon known as polarization. To overcome this issue, a third electrode, called a reference electrode (RE) is added to serve as a reference in measuring and controlling the potential of the WE and no current passes through it (Fig. 1.3(a)). Typical RE are ones with a stable poten- tial and a small temperature dependence on the applied potential such as saturated calomel electrode (SCE) or silver/silver chloride (Ag/AgCl). Thus, all electrochemical experiments described in Chapters 2 and 3 were per- formed in a three-electrode system (Fig. 1.3(b)) with a platinum mesh as the CE and a Ag/AgCl electrode as the RE. The materials chosen for the working electrode are 11 Figure 1.3: (a) Circuit of a three electrode electrochemical cell comprising of a ref- erence electrode (RE), a working electrode (WE) and a counter (also known as an auxiliary) electrode (CE) all immersed in a supporting electrolyte. (b) Example of a typical electrochemical cell used in the experimental work of Chapters 2 and 3. inert (e.g. edge-plane graphite or gold) to ensure that the chemical composition does not change while providing a surface upon which the electrode reaction can occur.17,19 1.4.5 Cyclic voltammetry (CV) Cyclic voltammetry (CV) is a powerful electroanalytical technique for determining the redox potentials of electroactive species in solution.17,20 In CV measurements, the voltage of the working electrode (WE) is swept between two values (E1 and E2 ) at a fixed scan rate (Fig. 1.4(a)) and the resulting current that flows is measured. The potential of working electrode is measured against a reference electrode (i.e. Ag/AgCl). Figure 1.4(b) shows a typical cyclic voltammogram for 10 mM ferro-/ferri-cyanide (Fe(CN)64−/3− ), a redox active molecule in a 0.1 M KCl (pH 7.0) electrolyte measured at a bare gold (Au) electrode. The single electron transfer reaction for this redox couple is described by Eq. 1.5. F e(CN)4− 3− 6  F e(CN)6 + e − (1.5) At an initial potential of E1 = –0.2 V, all the electroactive species is in its reduced state (i.e. Fe(CN)64− ). The potential is then swept in the positive direction towards 12 Figure 1.4: (a) Triangular potential waveform of voltage as a function of time used in cyclic voltammetry. Working electrode potential is scanned from –0.2 to 0.6 V and back to –0.2 V in one cycle. All potentials are referenced to a Ag/AgCl electrode. (b) Cyclic voltammogram of a bare Au electrode in a 0.1 M KCl electrolyte (pH 7.0) containing 10 mM Fe(CN)64−/3− (1:1). Scan rate: 100 mV/s. E2 = 0.6 V and the anodic current increases until the potential to sufficiently oxidize ferrocyanide to ferricyanide (i.e. Fe2+ → Fe3+ ) is reached (Eq. 1.2). The anodic current will continue to increase rapidly until the concentration of ferrocyanide near the electrode surface is depleted and the current will decay, resulting in the observable anodic peak current. The voltage is then swept in the negative direction back towards E1 where at a sufficiently negative potential, the ferricyanide that has accumulated near the electrode surface can now be reduced to ferrocyanide (i.e. Fe3+ → Fe2+ ). In a similar fashion, the cathodic current increases rapidly until all the ferricyanide near the electrode surface is depleted, resulting in a cathodic peak current. This cycling of potentials between E1 to E2 back to E1 and measuring the resulting current completes one cycle of a CV. Several important parameters of interest can be determined from the cyclic voltam- mogram. First, the anodic and cathodic peak currents (ipa and ipc ) can be extrapo- lated by taking the difference between the measured current and a baseline current (Fig. 1.4(b), green dotted line) at each respective anodic or cathodic peak potential (Epa and Epc ). For a reversible electrochemical reaction, the ratio between the peak currents (i.e. ipa/ipc ) should equal to one. Second, the mid-point potential or also 13 known as the formal reduction potential (E0 ) is centered between Epa and Epc for a reversible redox couple and is described by Eq. 1.6: Epa + Epc E0 = (1.6) 2 Third, the number of electrons (n) transferred in the electrochemical reaction can be determined by the separation between the peak potentials as described in Eqs. 1.7 and 1.8: 0.0592 ∆Ep = Epa + Epc ∼ (for a reversible reaction) (1.7) n 0.0592 ∆Ep = Epa + Epc > (for an irreversible reaction) (1.8) n Lastly, if the electron transfer process is diffusion-controlled, then the peak current should be proportional to the square root of the scan rate. When the peak current is directly proportional to the scan rate, the redox event is associated with other processes such as ligand binding or geometry change. An example of using CV to determine the kinetics of the first electron transfer is demonstrated in Chapter 2 for a CYP27B1 enzyme immobilized in a surfactant film. 1.4.6 Electrochemical Impedance Spectroscopy (EIS) Electrochemical impedance spectroscopy (EIS) is a powerful tool to study and char- acterize the electrochemical processes in electrode coatings with embedded biological material such as receptor proteins or antibodies. This technique involves applying a small-amplitude, alternating voltage (V) and measuring the resulting current (I) over a range of frequency values (10−3 – 105 Hz) and time (t). The total impedance of the system Z, measured in the units of ohms (Ω), is the ability of the circuit to resist the flow of electrical current and described by Eq. 1.9: V (t) V0 sin(ωt) V ZT (jω) = = = e−iφ (1.9) I(t) I0sin(ωt + φ) I 14 Figure 1.5: (a) Randles equivalent circuit with parameters described in text. (b) Nyquist plot of impedance data for a bare Au electrode in a 0.1 M KCl electrolyte (pH 7.0) containing 10 mM Fe(CN)64−/3− (1:1). where V0 and I0 are the maximum voltage and current amplitude, ω is the frequency in radians per second, t is the time in seconds and φ is the phase shift in radians.17,21,22 The complex impedance in Eq. 1.9 can also be expressed in terms of its real (Zreal ) and imaginary (Zim ) components: ZT (jω) =| Z | (cos φ − i sin φ) = Zreal (ω) − iZim (ω) (1.10) p The magnitude of the total impedance is defined as |Z| = (Zreal )2 + (Zim )2 and the phase angle is determined as φ = tan−1 (Zim /Zreal ). Impedance data are represented on either a Bode plot which plots log|Z| and φ vs. log(ω) or a Nyquist plot which plots Zreal vs. Zim at different ω values. To interpret the impedance data, an equivalent electrical circuit comprising of resistors and capacitors is used to model the factors such as the electron transfer kinetics, chemical reactions and diffusion that impede electron flow in an electrochemical cell. For the situation where an electrode is in contact with an electrolyte, the simplest equivalent circuit is the Randles circuit (Fig. 1.5(a)) which comprises of the ohmic solution resistance Rs , the charge transfer resistance, Rct , the double layer capaci- tance, Cdl and the Warbug impedance Zw . The current path of both the double-layer charging (ic ) and faradaic processes (if ) at the electrode interface are also described 15 by the circuit. In the Nyquist plot of a bare Au electrode shown in Fig. 1.5(b), the elements for Rs and Rct can be determined by the x-intercepts of the semi-circle. The double layer capacitance can be calculated from the frequency at the maximum of the semi-circle (ω = 1/(Rct Cdl ). In diffusion-controlled cases, the 45 ◦ line indicates the Warburg impedance which is governed by the mass transfer of ions to the interface from the bulk electrolyte solution.17,23 As observed in Chapter 3, the deposition of supporting lipid layers onto the electrode causes the interfacial/bulk impedance to be very large and the Warburg impedance is no longer observed. To provide a well-defined charge transfer resistance, Rct , a redox couple such as ferro-/ferri-cyanide (Fe(CN)63−/4− ) can be added to the electrolyte solution. When this couple is omitted, the Rct becomes very large and the capacitive (Cdl ) impedance behavior can be observed. The two components, Rct and Cdl depend on the insulating and dielectric features at the electrode/electrolyte interface, and therefore are highly sensitive to any binding event of an analyte on a surface-modified sensing electrode. Thus, impedance biosensors that monitor changes in Rct across a range of frequencies are termed faradaic biosensors while those that measure changes in Cdl at a fixed frequency are known as capacitive biosensors. Chapter 3 of this thesis discusses the development and characterization of a faradiac impedance biosensor for the detection of 1α,25(OH)2 D3 . 1.5 Microbial intein-based sensors 1.5.1 Motivation and inspiration Nuclear hormone receptors (NHRs) which are an important class of transcriptional regulatory proteins found in virtually every tissue of the human body. NHRs regulate many physiological processes including cell growth and death, reproduction, energy metabolism, embryogenesis and homeostasis.24,25 Well-studied receptors within this superfamily include the glucocortocoid receptor (GR), estrogen receptor (ER), thy- 16 roid hormone receptor (TR) and the vitamin D receptor (VDR). Malfunctions in these receptors have been correlated with various diseases such as breast cancer,26 thyroid-related cancer,27 and heart disease.28 Since the early 2000s, intein-based mi- Figure 1.6: Schematic of a generic DNA biocircuit comprising of an intein and extein elements that encode for a sensor protein for small molecule detection. A mini-intein without its homing endonuclease domain is depicted and often the ligand binding domain (LBD) of nuclear hormone receptors (NHR) is inserted into this region. The N- and C-extein fragments are nucleotides that together encode for a host sensor protein such as a green fluorescent protein. The primary translation product is known as the precursor protein. Post-translational splicing occurs at the splice junction that contains either a Cys, Ser or Thr residue. Splicing activity produces a ligated sensor protein and an excised intein. crobial sensors have been constructed to offer a fast, simple and inexpensive approach to small molecule sensing as well as a high-throughput screening method for ligand detection (see Table 1.1 for a summary of intein-based biocircuit design). Different combinations of intein and exteins were chosen but for the majority of the biocir- cuits designed with the LBD from ERα,29,30 ERβ,31 and TR32 , a Mtu RecA mini- intein33,34 was used (Fig. 1.6). Preliminary studies suggest that these microbes are capable of sensing estrogen and T3 ligands in micromolar concentrations,29,32,35 while for screening applications, the binding affinities and agonistic/antagonistic properties of small molecules within a chemical library can be determined.31 Liu et al. have 17 Table 1.1: Summary of intein-based biocircuit design Ligand Host N-Extein N-Intein Binding C-Intein C-Extein Organism Ref. Domain (LBD) ERα-LBD 30 DHFR* DHFR* Yeast (282-576) His6-N-EGFP N-Linker/C- C-EGFP 37 dnaE dnaE Mammalian (1-157) Linker* (158-238) FKBP VMA V MA FRB Bacteria 38 Mtu Mtu RecA GFP 39 GFP(3-128) Bacteria RecA(1-104) (367-440) (129-239) Mtu ER-LBD Mtu RecA KanR 29 KanR(1-118) Yeast RecA(1-94) (304-551) (383-440) (120-270) 29, Mtu ER-LBD Mtu RecA GFP Yeast, 36, GFP(1-107) RecA(1-94) (304-551) (383-440) (129-239) Mammalian 40 Bacteriophage Mtu TRβ-LBD Mtu RecA Bacteriophage 32 Bacteria T4 TS RecA(1-110) (203-461) (383-440) T4 TS Bacteriophage Mtu ERα-LBD Mtu RecA Bacteriophage 32 Bacteria T4 TS RecA(1-110) (301-553) (383-440) T4 TS Bacteriophage Mtu Mtu Bacteriophage 31 ERβ Bacteria T4 TS RecA(1-110) RecA(383-440) T4 TS Bacteriophage Mtu PPARγ-LBD Mtu RecA Bacteriophage 35 Bacteria T4 TS RecA(1-110) (110-383) (383-440) T4 TS Abbreviations: N-Linker = ASNNGNGRNG; C-Linker = GNNGGNNDV; CaM = Xenopus calmodulin; M13 = CaM-binding peptide derived from skeletal muscle myosin light-chain ki- nase; (E)GFP = Enhanced green fluorescent protein; FKBP = FK506-and rapamycin binding protein; FRB = FKBP-rapamycin binding; TS = Thymidylate Synthase; *DHFR = temperature sensitive yeast metabolic enzyme also demonstrated that the ERα-intein construct can cause osteoblast differentiation upon binding of 4-hydroxytamoxifen (4-HT).36 Given the success of previous intein- based biociruits with other NHR-LBD, Chapter 4 describes the construction and characterization of a similar biocircuit designed using the VDR-LBD for vitamin D sensing. 1.5.2 Vitamin D receptor ligand binding domain (VDR-LBD) The full-length vitamin D receptor (VDR) is a 48 kDa protein within the nuclear hor- mone receptor (NHR) superfamily and is regulated by its cognate ligand, 1α,25(OH)2 D3, to control calcium metabolism, immune modulation and cell proliferation and differentiation.5 There are two main groups of NHRs which are classified based on their mecha- nism of action and subcellular distribution in the absence of a ligand. Group I NHRs are bound to heat shock proteins (HSPs) naturally found in the cytoplasm. When 18 ligand binding occurs, the HSPs are dissociated from the NHRs, homo-dimerization of the NHR occurs, and the new complex is translocated into the nucleus. The DNA- binding domain (DBD) is then free to bind to hormone response element sequences (HREs), which are two-inverted hexanucleotide half-sites separated by a short vari- able nucleotide sequence (n = 0–6) that is specific to receptor dimerization. Group II NHRs, which includes the VDR, naturally reside in the nucleus, and the ligand must diffuse through the nuclear membrane to cause either homo- or hetero-dimerization and NHR-binding on direct repeats of HREs (Fig. 1.7(a)).41 Expression and purifica- tion of a functional VDR has been successfully demonstrated in bacteria,42,43 yeast44 and insect cells using baculovirus.45 All nuclear receptors, including the VDR, are comprised of multiple domains with conserved DNA sequences and function (Fig. 1.7(b)). At the N-terminus is the activating function-1 (AF-1) domain which initiates the ligand-independent functions of the receptor. Next, is the DNA-binding domain (DBD) which contains two C4-zinc fingers that facilitate DNA binding to specific HREs located upstream of the receptor’s targeted genes.24 The ligand binding domain (LBD) follows at the C-terminus of the receptor and forms a hydrophobic ligand binding pocket. The modularity of the DBD and LBD has enabled researchers such as Cham- bon et al. to swap the DBD of the ER with that from the GR. The result was that genes that were normally dependent on GR transactivation were now activated by the presence of estradiol, the natural ligand for the ER.46 The ability to swap different domains of the NHRs led to the hypothesis that an intein-based circuit is versatile by replacing the LBD region with a different NHR. The cDNA of the hVDR was cloned successfully in 1988,47 and the crystal structure of the LBD of the hVDR (amino acids 118-425,∆165–215) was first revealed in 2000 (Fig. 1.8). In order to crystallize the hVDR-LBD, 50 residues in a poorly conserved region connect- ing helices H1 to H3 was removed.48 This mutant hVDR-LBD was tested and shown to retain both its ligand binding and transactivation activities.48,49 In the design of the intein-based biocircuit in Chapter 4, several variants of the VDR-LBD was constructed including VDR(108-427), VDR(108-427,∆165-215), VDR(118-427,∆165- 19 Figure 1.7: (a) Members of the nuclear receptors form homo- or hetero-dimers and are classified in two groups based on their mechanism of action and subcellular distribu- tion in the absence of a ligand. (b) Structure of highly conserved regions of function and sequence for nuclear hormone receptors (NHRs). Abbreviations: AF-1, AF-2 = Activiating Function-1/-2; DBD: DNA-binding domain; LBD: Ligand binding domain 215) and VDR(118-425,∆165-215). 1.5.3 Mycobacterium tuberculosis (Mtu) RecA Intein Inteins (internal protein) are internal polypeptide sequences that participate in post- translational protein splicing caused by either a change in temperature or pH. Such sequences are generally found in mesophilic bacteria, yeast and thermophilic archaea. Protein splicing starts with the excision of an intein from a protein precursor (the primary translational product) followed by the subsequent ligation of the flanking N- and C- terminal fragments, also known as exteins (external protein), to form a mature host protein (Fig. 1.6). Intein-mediated protein splicing forms a native peptide bond between the ligated exteins, and this product determines the classification and functionality of specific intein sequences.50−52 As of April 15, 2009, there are 454 intein sequences listed in the New England Biolabs’ Intein Database (InBase) which can be accessed at: http://www.neb.com/neb/inteins.html.53 20 Figure 1.8: Crystal structure of the vitamin D receptor ligand binding domain (VDR- LBD). PDB ID: 1DB1. The amino acid residues include 118-425 with a deletion of 50 residues between 165-215. The distance between the N- and C- termini of the VDR-LBD is ∼40.8 ˚ A. Structurally, all inteins are coded by a set of amino acids with the residues at the amino and carboxy ends playing a critical role in its splicing activity. Embedded within the intein is an unrelated set of amino acids encoding a homing endonuclease that is involved in double-stranded DNA cleavage. Studies have shown that protein- splicing and the homing endonuclease functionalities occur at separate active sites and the intein active site residues do not block endonuclease function or vice versa.54 1.5.3.1 Intein splicing mechanism Protein splicing is an intramolecular process of the intein and requires no exogenous cofactors or sources of metabolic energy such as adenosine triphosphate (ATP). The information necessary for protein splicing is stored in highly conserved amino acid residues at both the N- and C-terminal splice junctions. Specifically, a hydroxyl- or thiol- containing residue (Ser, Thr or Cys) must be present at the position following 21 the two splice junctions and a His-Asn sequence is conserved at the C-terminus of the intein (Fig. 1.6).50 Any substitution will result in the abolishment of protein splicing activity52,54,55 The currently accepted mechanism of protein splicing involves four main steps (Fig. 1.9). First, the process is initiated by an attack of the nucleophilic hydroxyl or thiol group of the Ser, Thr or Cys residue. This produces a N/O or N/S acyl shift of the N-extein to that side chain. Second, in a transesterification reaction, the hydroxyl or thiol group of the first C-extein residue attacks the newly formed (thio)ester linkage to create a branched intermediate. Third, the intein is excised by peptide cleavage at the amide linkage, which is induced at the C-terminus of the intein through an Asn cyclization reaction. Lastly, a spontaneous rearrangement of the (thio)ester linkage between the spliced exteins forms a native peptide bond to make a reconstituted host protein.50,51,56 1.5.4 Extein: Green fluorescent protein (GFP) The exteins that flank the N- and C- terminus of the intein are two separate inac- tive components of a monomeric reporter protein that can reconstitute function upon successful splicing. These split reporter strategies includes the use of a variety of pro- teins and enzymes such as dihydrofolate reducatase (DHFR)57, β-galactosidase,58 β- lactamase,59 kanamycin,60 green fluorescent protein (GFP),61,39 or Renilla luciferase.37 The readout of the sensor will thus depend on the exteins selected and can include measuring the cell survival, absorbance, fluorescence or bioluminesecence. A split GFP was chosen as the exteins for this sensor. GFP is a fluorescent protein comprised of 238 amino acids and its DNA was first cloned in 1992.62 The ability to express GFP in microorganisms such as bacteria and yeast without the need of any co-factors from jellyfish to form its fluorescent structure has led to its widespread use in cell imaging and sensor applications.63,64 The wild-type GFP (wtGFP) absorbs blue light at 395 nm, with a minor peak at 475 nm; and emits green light at 509 nm.63,65 GFP is a highly stable protein, which may be a consequence of its three-dimensional 22 Figure 1.9: Schematic representation of the four-step protein splicing pathway where the amino acid residues that participate in the chemical reaction must be either a hydroxyl- or thiol- containing residue (X = O or S). (Figure adapted from Ref. 51) 23 Figure 1.10: (a) The tertiary structure (β-barrel) of green fluorescent protein with its approximate dimensions. PDB ID: 2AWL (b) Three amino acids Ser65, Tyr66, and Gly67 undergoes an autocatalytic chromophore formation. (Adapted from Refs. 65, 68) structure. Its structure consists of eleven beta strands that surround and protect the chromophore (a group of atoms responsible for the color of the GFP), which is located near the middle of the β-barrel. Several α-helices form the lid of the β-barrel and fur- ther protects the chromophore from fluorescence quenching agents such as acrylamide, halides and molecular oxygen (Fig. 1.10(a)).66 GFP is also thermostable and highly resistant to denaturation requiring treatment conditions of at least 6 M guanidine hy- drochloride at 90 ◦C or a pH of < 4.0 or > 12.0.67 The structure of the chromophore was first predicted by analysis of a hexapeptide with a primary sequence (Phe64-Ser- Tyr-Gly-Val-Gln69) obtained from proteolytic experiments of purified GFP. It was predicted that the internal Ser-Tyr-Gly sequence is post-translationally modified to a 4-(p-hydroxybenzylidene)-imidazolidin-5-one structure to form the GFP chromophore (Fig. 1.11(b)).67,69 The maturation of the chromophore begins by a rapid cyclization between Ser65 and Gly67 residues to form an imidazolin-5-one intermediate followed by a slower, rate-limiting oxygenation of the Tyr66 side chain by O2 .70 In Chapter 4, a total of 10 plasmids were constructed and can be grouped based on the GFP variant used. Plasmid I encodes for the enhanced green fluorescent protein (EGFP) obtained commercially from Clontech (Mountainview, CA) while plasmids II and III have a GFP variant obtained from p414-IntERGFP (donated by Dr. David Liu, 24 Figure 1.11: Amino acid sequence comparison of three GFP variants used in construc- tion of plasmids I – XI. Plasmid I contains EGFP (F64L, S65T), plasmids II and III contains GFP (F64L, S65T) and plasmids IV – XI contains wtGFP. The hexapeptide region encoded by amino acids 64 – 69 form the chromophore of a fluorescent GFP. Harvard University). Plasmids I – III have GFP variants with a double substitution (F64L and S65T) in the chromophore region. Plasmids IV – XI has a GFP variant equivalent to the wtGFP originally from pIntGFP (obtained from Dr. Henry Paulus, Boston Biomedical Research Institute). An amino acid sequence alignment of the three GFP variants is shown in Fig. 1.11. Certain mutations in the chromophore of the wtGFP affect the rate of chro- mophore formation as well as the spectral properties of the native protein. One advantageous mutation is the S65T, where a threonine is substituted for the serine at the 65th amino acid position. This mutation resolves the broad double excita- tion peaks of GFP at 395 nm and 475 nm to a single peak centered in the visible region.71 Furthermore, a GFP with a S65T substitution is more photostable compared to wtGFP.72 When the fluorescence intensity was investigated using the fluorescence- activated cell sorter (FACS) for a GFP with a double substitution of F64L and S65T (i.e. GFPmut1),73 the absorption maximum red-shifted by about 100 nm compared to wtGFP (i.e. 488 nm vs 395 nm). Excitation at 488 nm results in a 20-fold increase in the normalized fluorescent intensity compared to wtGFP excited at 395 nm.73 25 1.6 Optical sensors 1.6.1 Introduction to plasmonics Plasmonics is a rapidly evolving field of nanophotonics enabling the guiding and ma- nipulation of light in noble metal nanostructures smaller than the wavelength of the incident light.74,75 A plasmon is a collective oscillations of free electrons in a conduct- ing material. Interaction with light at optical frequencies causes the free electrons to oscillate collectively in resonance with the light wave. This resonant interaction be- tween the surface charge oscillation of the metal surface and the electromagnetic field of the light gives rise to surface plasmon polaritons (SPPs). SPPs are electromagnetic waves that propagate along the surface of a metal and the dielectric medium. Being confined at the metal surface, SPPs are very sensitive to any changes in the refractive index between the dielectric and metal interface. Owing to this property, SPPs have been extensively used to sense the presence of chemical and biological analytes.76−78 1.6.2 Coupling of surface plasmons A SPP is a transverse magnetic (TM) wave, where the magnetic vector is perpendic- ular to the propagation direction and parallel to the plane of the metal surface. The SPP dispersion relation can be derived from Maxwell’s equations to be: r ω 1 2 kx = (1.11) c 1 + 2 where kx is the frequency-dependent wavevector, ω is the angular frequency, c is the speed of light in vacuum, and 1 and 2 are dielectric functions of the metal and the dielectric material, respectively.79,80 Figure 1.12 illustrates the light wave in air (blue) and the SPP dispersion relation at a Ag/SiO2 interface (red). For a given frequency, ω (related to energy by E = ~ω), the SPP mode always lie beyond the light line and has a greater momentum (~kspp ) than a free space photon (~k0 ), thus SPPs cannot be excited with conventional free-space illumination. To overcome this momentum mismatch problem, SPPs can be excited using either a prism coupling in 26 Figure 1.12: The dispersion curve for a surface plasmon polariton (SPP) mode illus- trates the momentum mismatch problem that must be overcome in order for light to couple to SPP modes. the Krestchmann81 and Otto82 configuration or grating coupling83 methods. Given the resonant nature of surface plasmon excitation, prism- and grating coupling meth- ods are limited by bulky optics and in the number of wavelengths that can be used to sense the presence of a biochemical analyte. Therefore, the refractive index asso- ciated with the analyte can be measured only at a specific wavelength, thus strongly limiting the spectroscopic capabilities of any surface plasmon resonance(SPR)-based technique. Chapters 5 and 6 describes a novel method that uses nanoscale scatterers such as narrow grooves to excite surface plasmons at various wavelengths, eliminat- ing the bulky optics of conventional SPR-based plasmonic sensors. Sensitivity of the groove-slit-groove plasmonic interferometers can be enhanced by simply tuning the incident wavelength or varying the interferometer arm lengths. A performance comparison between our plasmonic interferometer method with other conventional plasmonic approaches is summarized in Appendix B, Table B.1. 27 Figure 1.13: (a) Skin depth of SPPs as a function of wavelength on Ag/air (red line) and Ag/water (black line) interface. (b) Propagation length of SPP as a function of wavelength on Ag/air (red line) and Ag/water (black line) interface. 1.6.3 SPP skin depth and propagation length The intensity of the surface plasmon decays with the square of the electric field and decreases exponentially in the direction perpendicular to the metal and dielectric interface. The skin depth, δ is the value at which the field amplitude falls to 1/e and determines the depth of the sensed volume of a plasmonic interferometer. Skin depth, δ is calculated at a specific wavelength, λ according to: λ 1r + 2 1/2 δ= ( ) (1.12) 2π 22 where 1r is the real part of the dielectric constant of the metal medium, and 2 is the dielectric constant of the dielectric medium above the metal. Figure 1.13(a) shows skin depth as a function of wavelength on Ag/air (red) and Ag/water (black) interfaces. As a SPP wave propagates along the metal surface, it loses energy to the 28 metal due to absorption. The intensity of SPPs propagating along a smooth surface also decreases exponentially because of ohmic losses in the metal. The propagation length L is the length at which the intensity decreases to 1/e: c 1r + 2 3/2 21r L= ( ) (1.13) ω 1r 2 1i where c is the speed of light, ω is the frequency at certain free-space wavelength, and 1i is the imaginary part of the dielectric constant of the metal medium.79 Figure 1.13(b) shows the propagation length spectra on Ag/air (red) and Ag/water (black) interfaces. 1.6.4 Sensing volume The sensing volume of a groove-slit-groove plasmonic interferometer can be calculated by assuming that the width is the sum of the two groove-slit distances, p1 and p2; the length is equal to 10 µm for all devices; and the height is equal to the skin depth at a specified wavelength. For example, the GSG device reported in Chapter 5 has a p1 = 0.57 µm and p2 = 9.75 µm, giving a total sensing width of 10.32 µm. 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Chapter 2 Direct electrochemistry of mouse cytochrome P450 27B1 in surfactant films 2.1 Abstract In this chapter, we report the first direct electrochemistry of cytochrome P450 27B1 (CYP27B1) immobilized on an edgeplane pyrolytic graphite (EPG) electrode coated with a film of didodecyldimethylammonium bromide (DDAB). Cyclic voltammetry (CV) in a deoxygenated solution revealed excellent electrochemical reversibility with an average midpoint potential of –180 ± 5 mV vs. Ag/AgCl and an apparent sur- face coverage of (7.0 ± 2.5) × 1013 molecules per cm2. The rate of heterogeneous electron transfer between CYP27B1 and the EPG electrode was determined to be 3.5 ± 0.6 s−1 . Upon addition of oxygen, a significant increase in cathodic current occurred, likely due to electrocatalytic reduction of dioxygen to peroxide and/or wa- ter by CYP27B1. Characterization of the electrochemical properties of CYP27B1 is an important first step toward developing a bioelectrochemical method for measuring vitamin D in serum. 37 38 2.2 Introduction Cytochrome P450 (CYPs) are a diverse group of enzymes that catalyze the oxidation of organic substrates including lipid and steroidal hormones and xenobiotic chemicals such as drugs and other toxic chemicals. Most CYPs participate in a mono-oxygenase reaction where one atom of the dioxygen is inserted into the organic substrate (RH) and the other atom is reduced to water as illustrated in Eq. 2.1:1 RH + O2 + NADP H + H + → ROH + H2 O + NADP + (2.1) Figure 2.1: The structures of the (a) prosthetic heme-b group and (b) the hexa- coordinated iron center tethered via a thiolate linkage in the CYP protein. The active site of CYPs contains a heme-b iron center tethered to the protein via a thiolate linkage derived from a highly conserved cysteine residue (Fig. 2.1). The mechanism by which CYPs are able to carry out the monooxygenase reaction has been investigated and a working model that describes the P450 catalytic cycle is represented in Fig. 2.2. In general, the P450 catalytic cycle proceeds as follows: (1) substrate (RH) binds to the active site of the enzyme close to the heme prosthetic group. The bound sub- strate causes a conformational change in the active site and results in the displace- ment of a water molecule and a change in the state of the ferric iron from low-spin to high-spin. The change in the electronic state increases the redox potential (E0 ) 39 of the heme group which favors electron transfer from NADPH via cytochrome P450 reductases such as FAD-containing adrenodoxin reductase (ADR); (2) the heme iron reduces to the ferrous (FeII ) state; (3) molecular oxygen binds covalently to the heme iron; (3a) addition of carbon monoxide (CO) yields the reduced state of the heme iron in complex with CO (FeII ·CO) with an absorption maximum at 450 nm; (4) a second electron is transferred via a ferredoxin protein such as adrenodoxin (ADX) to reduce the dioxygen adduct to a negatively charged peroxo group, which (5) can be protonated to yield a hydroperoxide complex, and (6) further protonated to yield a highly reactive FeIV -oxo intermediate; (7) the remaining oxygen atom bound to the heme iron is inserted into the carbon-hydrogen bond on the substrate to form the (8) product with an alcohol group (ROH) which is then released and the enzyme is regenerated to its original state. Also shown are the alternative routes (Fig. 2.2(A)- (C)) known as the peroxide shunt where the catalytic cycle can be completed without going through steps 4 - 8 resulting in no product formation.2 Recent research on the electrochemistry of cytochrome P450s has focused on eluci- dating their electron transport pathways and their development for use in biosensors and bioreactors.3−10 However, heterogeneous electron transfer is difficult to achieve in many oxidoreductases,9,10 especially with CYPs because membrane-bound enzymes exhibit a general instability when solubilized and the heme active-site is often buried within the protein. Much effort has been made to overcome the aforementioned issues. To date, coating an electrode surface with a surfactant film has been a suc- cessful method to facilitate direct electron transfer to heme-containing proteins such as myoglobin and CYP101.8,13,14 The stereoselective hydroxylation of 25-hydroxyvitamin D3 (25(OH)D3 ) is cat- alyzed by CYP27B1. This reaction results in the formation of 1α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3), the biologically active form of vitamin D3.15,16 The CYP27B1- catalyzed 1α-hydroxylation reaction required the uptake of two electrons from NADPH via an electron transport chain consisting of two proteins: ADR and ADX.16 Recently, mouse CYP27B1 has been overexpressed in Escherichia coli, purified, and biochemi- cally characterized.17 As such, the availability of recombinant CYP27B1 makes pos- 40 Figure 2.2: Catalytic cycle of cytochrome P450 (Photo courtesy of Dr. Steve Y. Rhieu; adapted and modified from Ref. 2) sible its electrochemical characterization (Fig. 2.3). In this chapter, we report the direct electrochemistry of recombinant mouse CYP27B1 immobilized on an edge-plane pyrolytic graphite (EPG) electrode coated with a thin didodecyldimethylammonium bromide (DDAB) film. The electrochemical characteri- zation of CYP27B1 presented in this chapter represents a first step toward measuring 25(OH)D3 electrochemically. 41 Figure 2.3: (a) In vivo electron transport chain for conversion of 25(OH)D3 into 1α,25(OH)2 D3 via co-factors such as NADPH, ADR and ADX. (b) An electrode replaces the in vivo electron transport chain. CYP27B1 enzymes are purified and immobilized onto the electrode and 25(OH)D3 is converted into its active form, 1α,25(OH)2 D3 electrochemically. 2.3 Experimental details 2.3.1 Materials The expression plasmids for mouse CYP27B1 (pKCHis-m1α) and GroEL/ES (pGro12) were kindly provided by Dr. T. Sakaki (Toyama Prefectural University, Japan). Syn- thetic 25(OH)D3 and 1α,25(OH)2 D3 were generous gifts from Dr. M.R. Uskokovi´c (Hoffmann-La-Roche, Nutley, NJ). The Amplex Red hydrogen peroxide/peroxidase assay kit was purchased from Invitrogen. Ni-NTA affinity resin was purchased from Qiagen, PD-10 columns from GE Healthcare, and centrifugal filter devices (Amicon Ultra-15 30,000 NMWL) from Millipore. DDAB was purchased from Aldrich. EPG disk electrodes were purchased from Pine Instrument Company. All solutions were prepared in water purified by a Milli-Q system providing 18.2 MΩ resistivity. All other chemicals were reagent grade and used as received. 2.3.2 Expression and purification of CYP27B1 Mouse CYP27B1 with a C-terminal tetra-histidine tag was co-expressed with molec- ular chaperonins GroEL/ES in Escherichia coli and purified as described previously 42 Figure 2.4: Spectral properties of the purified CYP27B1. (a) Absolute spectrum of purified CYP27B1 in 100 mM potassium phosphate, pH 7.4, 20% glycerol, 0.1% 3-[(3- Cholamidopropyl)dimethylammonio]-2-hydroxy-1-propanesulfonate, and 0.5 M NaCl was measured. (b) The concentration of purified CYP27B1 was determined from the reduced CO-difference spectrum (i.e., FeII·CO vs. FeII) using a difference extinction coefficient at 446 and 490 nm of 446−490 = 91 mM−1 cm−1 . with minor modifications.17 After purification, protein samples that yielded an ab- sorbance ratio (A417/A280 ) greater than 1.0 were collected and concentrated (Fig. 2.4). SDS-PAGE (Fig. 2.4(a), inset) and an enzyme reconstitution assay were per- formed to confirm enzyme purity and activity, respectively. The enzymatic product, 1α,25(OH)2 D3 , was confirmed by high performance liquid chromatography (HPLC) against synthetic standards (Fig. 2.5). Aliquots of protein were flash-frozen in liquid nitrogen and stored at –80 ◦ C. 2.3.3 Electrochemistry experiments A three-neck round-bottom flask was utilized as the electrochemical cell containing an EPG disk (working, geometric area, A = 0.126 cm2 ), a platinum gauze (counter), and a Ag/AgCl (reference, 0.197 V vs. NHE). All potentials in this study were reported with reference to Ag/AgCl. An EG&G Potentiostat/Galvanostat (model 263A) was used for cyclic voltammetry (CV) experiments. All CV experiments were performed at room temperature (22 ± 1 ◦C) with 4 mL of 50 mM potassium phosphate buffer (pH 7.4) containing 50 mM NaBr. Prior to performing CV, the working solution was 43 Figure 2.5: The CYP27B1 monooxygenase activity was measured in a reconstituted system consisting of the purified CYP27B1, ADR, ADX, and 25(OH)D3 in a final volume of 1 mL of working buffer. After incubation at 37 ◦ C for 5 min, the reaction was initiated by adding NADPH at a final concentration of 1 mM. The reaction was terminated by adding 6 mL of methanol/dichloromethane (1:2, v/v). After extraction, the organic phase was recovered and subjected to the HPLC analysis. HPLC profile of synthetic standards of 25(OH)D3 and 1α,25(OH)2 D3 , eluted at ∼8.5 min and ∼14.3 min, respectively (panel (a)). HPLC profile of the lipid extract from a CYP27B1 reconstituted assay incubated with 25(OH)D3 (panel (b)). fully deoxygenated (< 1.5 ppm) by purging with argon for at least 30 min. An argon atmosphere also was maintained over the solution throughout the experiments. 2.3.4 Film preparation DDAB films were fabricated as described previously for CYP101 with minor modifications.8 A freshly polished EPG disk electrode was coated with 15 µL of 10 mM DDAB in chloroform, which was evaporated at room temperature for 1 h. The DDAB-modified EPG electrodes were placed into 5 µL of 40 µM purified CYP27B1 for 1 h at 4 ◦ C. The resulting CYP27B1/DDAB/EPG electrodes were dried under a stream of nitrogen prior to the experiments. 44 2.4 Results and discussion 2.4.1 Direct electrochemistry of the CYP27B1/DDAB/EPG electrode The cyclic voltammogram shown in Fig. 2.6(a) demonstrates the electrochemical re- versibility of CYP27B1 immobilized on the DDAB/EPG electrode. No voltammetric peaks were observed in the absence of enzyme. CYP27B1 showed an average mid- point potential of –180 mV with a standard deviation of ± 5 mV across three different electrodes. The voltammetric peaks grew over the course of an hour (Fig. 2.6(b)), suggesting reorganization of the enzyme within the film and/or changes in the de- gree of hydration of the film.18 The relationship between peak current and scan rate was linear up to 1 Vs−1 (Fig. 2.6(d)). This property is indicative of a thin film of electroactive species that is not under diffusion control as stated in Laviron theory. By integrating the oxidative and reductive peaks in the CV and applying Faraday’s law, the apparent surface coverage of electroactive CYP27B1 was calculated to be (7.0 ± 2.5) × 1013 molecules per cm2 , suggesting multiple layers of CYP27B1 were electroactive. This amount of enzyme corresponds to ∼7% of the deposited enzyme. The oxidative and reductive peaks had approximately equal areas indicating only a single electron was transferred reversibly to the heme center and no oxygen reduction took place. The small standard deviation in the midpoint potential, apparent surface coverage of electroactive species, and the peak current demonstrate that electrode preparation was highly reproducible. 2.4.2 Determination of α and ks The electron-transfer coefficient (α) and the rate constant (ks ) were obtained from empirically fitted Laviron equations.19 Irreversible electrochemistry (i.e., peak sepa- ration >200/n mV, taking n = 1) occurred when the scan rate exceeded 1.5 Vs−1 (Fig. 2.7(a)). Using Laviron’s approach for diffusionless thin-layer voltammetry, the cathodic (Epc ) and anodic (Epa) peak positions at various scan rates (υ) are expressed 45 Figure 2.6: Cyclic voltammetry of CYP27B1 immobilized on a DDAB-modified EPG electrode. (a) The cyclic voltammogram was recorded in deoxygenated 50 mM potas- sium phosphate buffer including 50 mM NaBr, pH 7.4, at a scan rate of 0.1 Vs−1 for the CYP27B1/DDAB/EPG (solid) and DDAB/EPG (dashed) electrodes. (b) The voltammetric peaks grow over the course of an hour (a-j: scanned every 5 min over a period of an hour). (c) Cyclic voltammograms of CYP27B1/DDAB/EPG electrodes at different scan rates (a-n: 0.03, 0.05, 0.075, 0.1, 0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1 Vs−1 ). (d) The peak currents increased linearly as a function of scan rate up to 1 Vs−1 , indicating that CYP27B1 is confined to the surface of the electrode. Data points represent the mean of triplicate determinations ± S.D. 46 Figure 2.7: (a) Laviron plot: dependence of the anodic and cathodic peak potentials of a CYP27B1/DDAB/EPG electrode on the logarithm of the scan rates. (b) Linear segments of the Laviron plot showing the dependence of the peak potential (Ep ) on the logarithm of scan rates. Data points represent the mean of triplicate determinations ± S.D. 47 as Eq. (2.2) and (2.3):   ◦0RT αnF RT Epc = E − ln − ln υ (2.2) αnF RT ks αnF   ◦0 RT (1 − α)nF RT Epa = E + ln − ln υ (2.3) (1 − α)nF RT ks (1 − α)nF where E ◦0 is the formal potential, and R, T , F , and n are the universal gas constant, absolute temperature, Faraday’s constant, number of moles of electrons transferred, respectively. The value of α can be determined from Eq. (2.4) by using the slopes from the linear plots of Epa and Epc vs. ln υ: RT (1 − α)nF δpa α= = (2.4) RT RT δpa − δpc + (1 − α)nF αnF where δpa and δpc are the slopes of linear region of the plot (Fig. 2.7(b)) when the difference of Epa and Epc (∆Ep) is greater than 200 mV. The value of ks can be determined by using Eq. (2.5):   RT nF ∆Ep log(ks ) = α log(1 − α) + (1 − α) log α − log − α(1 − α) (2.5) nF υ 2.3RT The resulting electron transfer coefficient and rate constant for heterogeneous electron transfer were determined to be 0.4 and 3.5 ± 0.6 s−1 , respectively. 2.4.3 Catalytic activity of immobilized CYP27B1 When the solution was saturated with dioxygen, a large increase in cathodic current was observed along with a disappearance of the anodic peak (Fig. 2.8). One source of this cathodic current reflects the enzymatic reduction of dioxygen to hydrogen per- oxide (i.e., the formation of an FeII − O2 complex followed by a second one-electron reduction to yield an iron-peroxo species).20 The formation of hydrogen peroxide was confirmed by using the Amplex Red hydrogen peroxide/peroxidase assay kit. The re- 48 Figure 2.8: Cyclic voltammetric responses of CYP27B1/DDAB/EPG electrodes in buffer saturated with argon (a) or dioxygen (c). Negative control (DDAB/EPG elec- trodes) revealed dioxygen reduction at more negative potentials (b). duction of dioxygen by DDAB/EPG electrodes occurred at more negative potentials, indicating that CYP27B1 significantly lowered the overpotential required for dioxy- gen reduction. The electrocatalytic reduction of the generated peroxide to water also may contribute to the observed catalytic current (i.e., the formation of an O=FeIV complex followed by two electron reduction with diprotonation to yield water).9 Af- ter addition of catalase to the solution, a noticeable increase in cathodic current was observed, suggesting that the reduction of generated peroxide by CYP27B1 to water is slower than that of dioxygen to peroxide. Electrolysis reactions were performed at –0.6 V in oxygenated solutions in the presence of 25(OH)D3 , however, no product formation was observed. It is possible that the active site of CYP27B1 is blocked by DDAB, a phenomenon that has been observed for other CYPs in surfactant films.6,22 49 2.4.4 The potential of the heme FeIII /FeII redox couple of CYP27B1 in DDAB/EPG films The measured midpoint potential of CYP27B1 in this study is considerably more positive to the redox potentials of CYPs reported previously.5,22 This shift in potential may be a consequence of the DDAB film. For example, it has been observed that the measured redox potential of the heme group shifts to more positive values (100 – 300 mV) when CYP101 is embedded within DDAB films6,10 compared to values obtained in solution.3,23 One possible explanation for the observed shift in redox potential is electrostatic repulsion between ferric heme and DDAB head groups (both are cationic), which destabilizes the ferric state and shifts the equilibrium towards the ferrous state. Consequently, the potential of the ferric/ferrous redox couple shifts to a more positive value according to the Nernst equation. Furthermore, the Born equation24 implies that the electrostatic free energy (∆G = nF ∆E) of the heme group changes because of local differences in the dielectric constant of the hydrophobic tails of DDAB compared to the polar environment of the bulk electrolyte. Such effects have been discussed in the literature for other heme-containing enzymes.25,26 2.4.5 Conclusion Recombinant mouse CYP27B1 immobilized on a DDAB-modified EPG electrode was characterized electrochemically in both deoxygenated and oxygenated solutions. The redox potential of CYP27B1 was determined to be –180 ± 5 mV and its heteroge- neous electron transfer rate was 3.5 ± 0.6 s−1 . With the growing clinical importance of vitamin D, there is a need for a rapid and inexpensive method for quantifying serum levels of 25(OH)D3 . 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Interaction of horse heart cytochrome c with lipid bi- layer membranes: Effects on redox potentials. J. Bioenerg. Biomembr., 29:211, 1997. Chapter 3 Electrochemical detection of 1α,25-dihydroxyvitamin D3 by electrochemical impedance spectroscopy 3.1 Introduction Chronic kidney disease (CKD) is a condition of kidney damage or decreased renal function, accompanied with a decreased level of 1-alpha-25-dihydroxyvitamin D3 , (1α,25(OH)2 D3 ).1 A reduced circulating level of 1α,25(OH)2 D3 contributes to sec- ondary hyperparathyroidism and parathyroid gland hyperplasia. Since 1α,25(OH)2 D3 is generated from its inactive vitamin D precursor, 25-hydroxyvitamin D3 by 1α- hydroxlase expressed in the kidney, the severity of a patient with CKD is directly re- lated to the circulating levels of 1α,25(OH)2 D3 . The physiological levels of 1α,25(OH)2 D3 in a normal patient is 48 - 156 nM, with a half-life of 4 - 6 hours.2 To address the lack of rapid 1α,25(OH)2 D3 measurement tools, we describe the fabrication and characteriza- tion of a sensitive, selective and label-free biosensor based on faradic electrochemical impedance spectroscopy (EIS).3−5 53 54 Since the early 1960s, supported bilayer lipid membrane (s-BLMs) have been used as experimental models to mimic natural biomembranes6−11 and served as an excellent matrix for immobilizing receptor proteins while retaining their functional properties.12−16 The detection of 1α,25(OH)2 D3 is achieved by the immobilization of a 48-kDa full-length vitamin D receptor (VDR) protein into 1,2-dimyristoyl-sn-glycero- 3-phosphocholine (DMPC), a s-BLM that self-assembles onto a gold electrode. DMPC is a small molecule with a polar head group and two hydrophobic tails. In solution, the polar head group is attracted to the gold surface via electrostatic interaction and the hydrophobic tails aligned to form a lipid bilayer on the surface of the electrode. The selectivity of the sensing electrode comes from the specific binding of vitamin D receptor (VDR) to 1α,25(OH)2 D3 (KD = 0.1 nM). The interfacial prop- erties of each layer of the modified electrode was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) in the presence of a ferro- /ferri-cyanide (Fe(CN)64−/3− ) redox probe (Fig. 3.1). A simple equivalent circuit model is used to fit impedance spectral data, where the resistance to charge trans- fer, Rct , can be correlated to varying concentrations of 1α,25(OH)2 D3 present in the electrolyte. The response time of the sensor is < 10 min and a detection limit of 52 nM has been achieved. Future work will focus on the reproducibility and selectivity of the sensing electrode. 3.2 Experimental details 3.2.1 Materials 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC, >99% purity) was purchased from Avanti Polar Lipids, Inc. (Alabaster, AL). Recombinant human vitamin D re- ceptor (hVDR, 250 pmol/vial) was obtained from Thermo Scientific (Rockford, IL) and synthetic 1α,25(OH)2 D3 was a generous gift from Dr. Satyanarayana Reddy. Potassium ferricyanide(III) (K3 Fe(CN)6) and potassium hexacyanoferrate(II) trihy- drate (K4Fe(CN)6 · 3H2O) were purchased from Sigma (St. Louis, MO). Gold working 55 Figure 3.1: Schematic of the immobilization procedure starting with (a) bare Au electrode, (b) the supported lipid bilayer membrane (s-BLM): 1,2-dimyristoyl-sn- glycero-3-phosphocholine (DMPC), (c) immobilization of the human vitamin D re- ceptor (hVDR) and (d) exposure of the surface modified electrode to 1α,25(OH)2 D3 . Fe(CN)64−/3− : 10 mM of ferro- and ferri- cyanide redox couple used in the working buffer solution. electrodes were purchased from CH Instruments, Inc. (Austin, TX). All solutions were prepared in water purified by a Milli-Q system with 18.2 MΩ cm resistivity at 25 ◦C. The hVDR was stored at –80 ◦ C in 2 µL aliquots (1.9 pmol/µL) and freshly prepared by adding 8 µL of 1× phosphate buffer saline (PBS, pH 7.4) on ice. The concentration of 1α,25(OH)2 D3 dissolved in pure ethanol was determined spectrophotometrically at λ = 264 nm using a molar extinction coefficient of 264nm = 1.80 × 104 L mol−1 cm−1 and stored at –20 ◦ C (Fig. 3.2).17 All other chemicals were of analytical grade and used without further purification. 3.2.2 Electrochemical set-up and instrumentation A three-electrode system was used in a single cell compartment to perform all elec- trochemical measurements: the working electrode was a gold disk (Au, d = 2 mm), the counter electrode was a platinum mesh, and the reference electrode was Ag/AgCl (+0.197 V vs. NHE). All potentials reported were referenced to Ag/AgCl. Cyclic voltammetry (CV) was performed using an EG&G Potentiostat/Galvanostat (Model 273A, Princeton Applied Research, Oak Ridge, TN) and electrochemical impedance spectroscopy (EIS) measurements were made with a Frequency Response Analyzer 56 Figure 3.2: Absorbance spectrum used to determine the concentration of a stock solution of 1α,25(OH)2 D3 in ethanol using the Beer-Lambert Law. (Model 1255A, Solartron Analytical, Hampshire, UK). 3.2.3 Electrode preparations Bare Au electrodes were cleaned by polishing repeatedly with 1.0, 0.3 and 0.05 µm alumina slurry then followed by successive sonication in ethanol and deionized water each for 5 min. After polishing, the Au electrodes were immersed in a Pirahna mixture with 3:1 concentrated sulfuric acid to 30 %(w/v) hydrogen peroxide. Electrodes were rinsed with copious amounts of deionized water before further electrochemical characterization. Twenty microliters of DMPC (1.5 mg/mL) was dissolved in 1 mL chloroform then drop-casted onto a clean Au electrode and allowed to evaporate at room temperature for 10 min. The DMPC/Au electrodes were immersed in 0.1 M KCl (pH 7.0) for 10 min to re-orient the lipid layer and allowed to dry. Then, 5 µL of hVDR stock (0.38 µM) was gently dropped on top of the DMPC/Au electrode for 12 h at 4 ◦ C in an enclosed wet environment to prevent dehydration of the film. The resulting hVDR/DMPC/Au surface-modified sensing electrodes were allowed to dry at room temperature prior to subsequent electrochemical characterization. 57 3.2.4 Electrochemical measurements CV and EIS experiments were performed in 1 mL of 0.1 M KCl (pH 7.0) containing 10 mM K3Fe(CN)6/K4 Fe(CN)6 (1:1). For CV, the working electrode potential was cycled between –0.2 mV to +0.6 mV at a scan rate of 100 mV/s. EIS measurements were performed over a frequency range between 10−3 – 105 Hz with the electrode poised at 0.230 mV using an AC amplitude of 5 mV rms, for two cycles. Prior to performing each CV or impedance measurement, the working electrolyte was purged thoroughly with N2 for 15 min and a blanket of N2 was maintained over the solution throughout the experiments. 3.3 Results and discussion 3.3.1 Electrochemical characterization of modified Au elec- trodes Cyclic voltammetry is a valuable technique to monitor the packing structure and electron transfer kinetics of surface-modified electrodes.18 Figure 3.3 shows a cyclic voltammogram for a bare Au electrode, a DMPC/Au and a hVDR/DMPC/Au mod- ified electrode in a 0.1 M KCl electrolyte with a 10 mM Fe(CN)64−/3− (1:1) redox couple. A set of well-defined redox peaks is observed in the case of the bare Au electrode, which is characteristic of the high electron transfer kinetics to and from the electrode surface to the redox couple in the interfacial region (Fig. 3.3, black solid line). Across seven freshly prepared Au electrodes, a peak-to-peak separation (∆Ep ) of 119 ± 10.3 mV and an average midpoint potential (Ep1/2) of 238 ± 6.5 mV was observed. Deposition of 2.2 mM 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) bilayer lipid film onto a bare Au electrode surface led to a suppression of the anodic and cathode peak currents, suggesting that the lipid film has coated the entire electrode surface and acts as an inert layer blocking the diffusion of Fe(CN)64−/3− toward the electrode surface (Fig. 3.3, red dashed line). Incorporation of the human vitamin D receptor (hVDR) into the hydrophobic tails of the DMPC film resulted in 58 a slight increase in the anodic and cathodic peak currents, which suggests that hVDR increased the permeability of the lipid film and facilitated improved electron transfer kinetics (Fig. 3.3, blue dotted line). Next, Figure 3.4 reports Nyquist plots of the real, Figure 3.3: Cyclic voltammograms of a working electrode immersed in a 0.1 M KCl (pH 7.0) electrolyte containing 10 mM Fe(CN)64−/3− (1:1) – (a) Au; (b) DMPC/Au; (c) hVDR/DMPC/Au. Scan rate: 100 mV/s. Inset: CVs of (b) and (c) are expanded. Zreal , and imaginary Zim components of the complex impedance at different stages of the Au electrode preparation. The impedance data was fitted to the Randles equiva- lent circuit which is comprised of the following parameters: the electrolyte resistance (Rs ), the double-layer capacitance (Cdl ), the charge transfer resistance (Rct ) and the Warburg impedance (Zw ) (Fig. 3.4(a), inset). The x-intercepts of the semi-circle fit can provide information about the values for Rs and Rct . The value for Cdl can be calculated from the frequency at the maximum of the semi-circle (ω = 1/(Rct Cdl ). The Warburg impedance, Zw represents a diffusion-controlled process and is observed as the straight-line regime at a 45◦ in the impedance spectra at the bare Au electrode (Fig. 3.4(a)). At the bare Au electrode, the Rct value was 0.36 ± 0.06 kΩ which suggests the Au acts as a good conductor and that electron transfer between the electrode surface with Fe(CN)64−/3− is kinetically facile. For a DMPC/Au electrode, the Rct value increases by two order of magnitude to 80.4 ± 43.5 kΩ and correlates 59 Figure 3.4: (a) Nyquist plot of impedance data at a bare Au (black squares) work- ing electrode immersed in 1 mL of 0.1 M KCl working buffer containing 10 mM Fe(CN)64−/3− (1:1). Inset: Randles equivalent electrical circuit and is used to inter- pret impedance spectra generated by the capacitive (ic ) and faradaic (if ) currents. (b) Nyquist plot compares the impedance spectrum of three working electrodes: bare Au (black squares), DMPC/Au (red circles), and hVDR/DMPC/Au (blue triangles). Inset: Rct values are the average values obtained from seven independently prepared electrodes. Concentrations used for DMPC and hVDR were 2.2 mM and 0.38 µM, respectively. well with the CV data in Fig. 3.3 (red) to confirm that the deposition of DMPC is ef- fective in blocking the electron transfer of Fe(CN)64−/3− to the electrode surface (Fig. 3.4(b), red circles). The immobilization of the hVDR into the DMPC/Au modified electrode decreases the Rct to 48.0 ± 14.6 kΩ, which suggest greater permeability in the DMPC film. The improved electron transfer kinetics observed may be attributed to an increased electrostatic attraction from the positive surface charge of the hVDR with the negatively charged redox probe in the electrolyte (Fig. 3.4(b), blue trian- gles). Both DMPC/Au and hVDR/DMPC/Au modified electrodes exhibit sluggish electron transfer kinetics and thus the Warburg impedance is not observed at low frequencies and can be considered negligible.18,19 A summary of the Rct values for an average of seven independently prepared electrodes is shown in the inset of Fig. 3.4(b). 60 Figure 3.5: (a) Nyquist plot of a hVDR/DMPC/Au electrode exposed to a solution containing 0 – 380 nM of 1α,25(OH)2 D3 dissolved in pure ethanol. (b) Corresponding Rct values of the impedance spectra in panel (a) as a function of 1α,25(OH)2 D3 concentration. 3.3.2 Electrochemical detection of 1α,25(OH)2D3 binding The interaction of 1α,25(OH)2 D3 with the hVDR/DMPC/Au surface-modified sens- ing electrode was investigated in situ with EIS. Figure 3.5(a) reports a Nyquist plot showing the impedance data measured after exposure of the sensing electrode to 26 – 338 nM of 1α,25(OH)2 D3 in pure ethanol. The Rct values, determined by the semi-circle diameters, increase as the concentration of 1α,25(OH)2 D3 increases (Fig. 3.5(b)). A linear region is observed between 52 – 260 nM 1α,25(OH)2 D3 , and the slope of the linear fit is 0.14 kΩ / nM. The increased Rct can be attributed to two major factors: (1) 1α,25(OH)2 D3 has a strong affinity to the hVDR (Kd = 5.2 × 10−11 M),20 and the binding event can lead to greater mass accumulation at the elec- trode surface, thus further blocking electron transfer between the electrode and the electrolyte in the interfacial region; (2) the binding of 1α,25(OH)2 D3 to the hVDR may induce a conformational change in the receptor causing the hVDR/DMPC film to form a more impermeable membrane at the electrode surface. To improve solu- bility of 1α,25(OH)2 D3 , the ligand was distributed into the bulk electrolyte solution using ethanol as a vehicle. The concentration of ethanol added as a function of the concentration of 1α,25(OH)2 D3 is shown on the top axis of Fig. 3.5(b). At 380 nM 61 Figure 3.6: (a) Nyquist plot for the control experiment of pure ethanol exposed to hVDR/DMPC/Au electrode. (b) Corresponding Rct values of the impedance spectra in panel (a) as a function of ethanol concentration. 1α,25(OH)2 D3 , a total of 222.3 µM of ethanol was added to the electrolyte. Thus, it is important to investigate the non-specific impedance response of pure ethanol when ex- posed to a hVDR/DMPC/Au modified sensing electrode. Figure 3.6(a) shows Nyquist plots of a hVDR/DMPC/Au electrode in the presence of pure ethanol between 0 – 651 µM. Figure 3.6(b) reports the decreasing trend of Rct values with increasing ethanol concentration, which is opposite to that observed with 1α,25(OH)2 D3 (Fig. 3.5(b)). A linear fit of the Rct values reported in Fig. 3.6(b) gives a slope of –0.007 kΩ/nM, suggesting there is minimal effect on the total impedance with the addition of ethanol. A calibration curve of the hVDR/DMPC/Au modified electrode can be determined from calculating the change in the charge transfer resistance, ∆Rct as defined by Eq. 3.1: ∆Rct = ∆Rct,(V DR−V D) − ∆Rct,(V DR) (3.1) where ∆Rct,(V DR−V D) is the electron transfer resistance when 1α,25(OH)2 D3 binds to the hVDR and ∆Rct,(V DR) is the value of the electron transfer resistance of the starting hVDR/DMPC/Au electrode. Figure 3.7 shows the change in electron trans- fer resistance, ∆Rct at a hDVR/DMPC/Au electrode after binding of 1α,25(OH)2 D3 62 Figure 3.7: Calibration curve for detection of 1α,25(OH)2 D3 . The change in the charge transfer resistance (∆Rct ) was calculated from Eq. 3.1. The limit of detection for 1α,25(OH)2 D3 is 52 nM (22 ng/mL). in concentration ranges of 26 – 338 nM. The modified electrode exhibits a sigmoidal calibration curve with an acceptable linear response between concentrations of 52 – 260 nM which yielded a linear regression equation: ∆Rct = 0.14 [1α,25(OH)2 D3 ] – 9.2 (R2 = 0.986). The detection limit of this particular sensor is 52 nM (22 ng/mL) which falls within the range reported by other affinity-based, faradaic impedance biosensors.15,21,22 The stability of DMPC/Au electrodes were evaluated by a dip test where an initial impedance spectrum was measured for a modified electrode im- mersed in the electrolyte solution (Fig. 3.8, black squares) and re-measured after the electrode was removed and re-immersed into the electrolyte (Fig. 3.8, red cir- cles). Figure 8 shows the dip test results performed on three electrodes prepared with half a monolayer (45 µM); one monolayer (91 µM); and two monolayers (180 µM) of DMPC (see the Appendix for the calculation of one monolayer of DMPC). Since the DMPC is not covalently attached onto the Au electrode, there is a large variation between the two impedance spectra which could have resulted from human error as the electrode is re-immersed into the electrolyte. In all the experiments reported thus far, 2.2 mM DMPC was used to form the lipid layer. This concen- 63 Figure 3.8: Nyquist plot showing the impedance spectra of (a) half a monolayer (45 µM); (b) one monolayer (91 µM); and (c) two monolayers (180 µM) of DMPC on a bare Au electrode. An impedance measurement of the DMPC/Au electrode was taken before (black squares) and after (red circles) removing and re-immersing the electrode back into the electrolyte. tration is equivalent to ∼24 monolayers on the electrode (see Appendix at the end of the chapter for the calculation) and the instability of the film can be observed by the large variances in the Rct values during the preparation of the DMPC/Au and hVDR/DMPC/Au electrodes (Fig. 3.4(b), inset). From a practical standpoint, other lipid films such as self-assembled monolayers (SAMs)23−25 or a combination of phospholipids/alkanethiols26,27 which can covalently attached to Au via a sulfide link- age may be a more reproducible, stable and promising alternative for immobilizing receptors for impedance sensing. 3.4 Conclusion This study investigated the feasibility of using a supported lipid bilayer membrane, (i.e. DMPC) to immobilized the human vitamin D receptor (hVDR) for detection of 1α,25(OH)2 D3 . At each step of the fabrication of the electrode, a steady-state impedance spectrum was obtained and effects on the charge transfer resistance, Rct was determined. Deposition of the lipid layer impeded electron transfer between the Fe(CN)64−/3− redox couple and the electrode surface at the interfacial region but addition of the hVDR made the lipid film more permeable to charge transfer. The 64 lowest detection limit achieved with the hVDR/DMPC/Au surface-modified sensing electrode was 52 nM 1α,25(OH)2 D3 . Compared to conventional approaches of detect- ing 1α,25(OH)2 D3 via the hVDR, electrochemical impedance spectroscopy provides a more convenient, time-saving and cell-culture free alternative. Issues related to the stability and reproducibility of the lipid film and methods to lower the detection limit will be the subject of future studies. 3.5 References 1. S. Masuda, and G. Jones. Promise of vitamin D analogues in the treatment of hyperproliferative conditions. Mol. Cancer Ther., 5:797, 2006. 2. R. Bouillon, G. Carmeliet, L. Verlinden, E. van Etten, A. Verstuf, H. F. Luderer, L. Lieben, C. Mathieu, and M. Demay. Vitamin D and human health: Lessons from vitamin D receptor null mice. Endocr. Rev., 29:726, 2008. 3. E. Katz, and I. Willner. Probing biomolecular interactions at conductive and semiconductive surfaces by impedance spectroscopy: routes to impedimetric immunosensors, DNA-sensors, and enzymes biosensors. Electroanalysis, 15:913, 2003. 4. I. O. KOwino, and O. A. Sadik. Impedance spectroscopy: A powerful tool for rapid biomolecular screening and cell culture monitoring. Electroanalysis, 17:2101, 2005. 5. F. Lisdat, and D. Schfer. The use of electrochemical impedance spectroscopy for biosensing. Anal. Bioanal. Chem., 391:1555, 2008. 6. L. Wang, X.-P. Hou, A. Ottova, and H. T. Tien. Receptor-ligand interactions in a reconstituted bilayer lipid membrane. Echem. Commun., 2:287, 2000. 7. H. T. Tien, and A. L. Ottova. Supported planar lipid bilayers (s-BLMs) as electrochemical biosensors. Electrochim. Acta, 43:3587, 1998. 65 8. C. Steinem, A. Janshoff, W.-P. Ulrich, M. Sieber, and H.-J. Galla. Impedance analysis of supported lipid bilayer membranes: a scrutiny of different prepara- tion techniques. Biochim. Biophys. Acta, 1279:169, 1996. 9. M. Stelzel, G. Weissmller, and E. Sackmann. On the application of supported bilayers as receptive layers for biosensors with electrical detection. J. Phys. Chem., 97:2974, 1993. 10. H. T. Tien, and A. L. Ottova. The lipid bilayer concept and its experimental realization: from soap bubbles, kitchen sink, to bilayer lipid membranes. J. Membrane Sci., 189:83, 2001. 11. M. Montal, and P. Mueller. Formation of bimolecular membranes from lipid monolayers and a study of their electrical properties. Proc. Nat. Acad. Sci. USA, 69:3561, 1972. 12. W. Xia, Y. Li, Y. Wan, T. Chen, J. Wei, Y. Lin and S. Xu. Electrochemical biosensor for estrogenic substance using lipid bilayers modified by Au nanopar- ticles. Biosens. Bioelectron., 25:2253, 2010. 13. J.-H. Yoon, K.-S. Lee, J. Yang, M.-S. Won, and Y.-B. Shim. Electron transfer kinetics and morphology of cytochrome c at the biomimetic phospholipid layers. J. Electroanal. Chem., 644:36, 2010. 14. Y. Liu, and W. Wei. Detection of cytochrome c at biocompatible nanostructure Au-lipid bilayer-modified electrode. Anal. Sci., 24:1431, 2008. 15. F. Darain, D. S. Park, J. S. Park, and Y. B. Shim. Development of an im- munosensor for the detection of vitellogenin using impedance spectroscopy. Biosens. Bioelectron., 19:1245, 2004. 16. Z. Wu, B. Wang, Z. Cheng, X. Yang, S. Dong, and E. Wang. A facile approach to immobilize protein for biosensor: self-assembled supported bilayer lipid mem- branes on glassy carbon electrode. Biosens. Bioelectron., 16:47, 2001. 66 17. E. Uchida, N. Kagawa, T. Sakaki, N. Urushino, N. Sawada, M. Kamakura, M. Ohta, S. Kato, and K. Inouye. Purification and characterization of mouse CYP27B1 overproduced by an Escherichia coli system coexpressing molecular chaperonins GroEL/ES. Biochem. Biophys. Res. Commun., 323:505, 2004. 18. A. J. Bard, and L. R. Faulkner. Electrochemical methods: Fundamentals and applications. John Wiley & Sons, New York, 2001. 19. S. J. Ding, B. W. Chang, C. C. Wu, M. F. Lai, and H. C. Chang. Electro- chemical evaluation of avidinbiotin interaction on self-assembled gold electrodes. Electrochim. Acta, 50:3660, 2005. 20. A. R. Baker, D. P. McDonnell, M. Hughes, T. M. Crisp, D. J. Mangelsdorf, M. R. Haussler, J. W. Pike, J. Shine, and B. W. OMalley. Cloning and expression of full-length cDNA encoding human vitamin D receptor. Proc. Natl. Acad. Sci. USA, 85:3294, 1988. 21. H. Cai, T. M.-H. Lee, and I. M. Hsing. Label-free protein recognition using an aptamer-based impedance measurement assay. Sens. Actuators B., 114:433, 2006. 22. D. K. Xu, D. W. Xu, X. B. Yu, Z. H. Liu, W. He, and Z. Q. Ma. Label-free electrochemical detection for aptamer-based array electrodes. Anal. Chem. 77:5107, 2005. 23. M. D. Porter, T. B. Bright, D. L. Allara, and C. E. D. Chidsey. Spontaneously organized molecular assemblies: 4. Structural characterization of n-alkyl thiol monolayers on gold by optical ellipsometry, infrared spectroscopy, and electro- chemistry. J. Am. Chem. Soc., 109:3559, 1987. 24. C. D. Bain, E. B. Troughton, Y.-T. Tao, J. Evall, G. M. Whitesides, and R. G. Nuzzo. Formation of monolayer films by the spontaneous assembly of organic thiols from solution onto gold. J. Am. Chem. Soc., 111:321, 1989. 67 25. R. Subramanian, and V. Lakshminarayanan. A study of kinetics of adsorption of alkanethiols on gold using electrochemical impedance spectroscopy. Elec- trochim. Acta., 45:4501, 2000. 26. A. L. Plant. Self-assembled phospholipid/alkanethiol biomimetic bilayers on gold. Langmuir, 9:2764, 1993. 27. M. B. Smith, J. Tong, J. Genzer, D. Fischer, and P. K. Kilpatrick. Effects of synthetic amphilphilic a-helical peptides on the electrochemical and structural properties of supported hybrid bilayers on gold. Langmuir, 22:1919, 2006. 3.6 Appendix: Calculation of a single monolayer of DMPC A monolayer of DMPC is calculated as follows: Diameter of entire electrode (include telfon casing) = 0.6 cm Area of entire electrode = Aelectrode = πr2 = 0.283 cm2 Assume 1 molecule of DMPC has a trigonal pyramidal structure, the area of 1 molecule of DMPC, ADM P C is described by: p ADM P C = (s(s − a)(s − b)(s − c)) (3.2) where s = (a + b + c)/2 and a, b, c are the side lengths of the trigonal pyramid. Atomic radius of a nitrogen (N) atom = 65 pm Atomic radius of a methyl (CH3 ) group = 2.3 ˚ A a = 2.44 ˚ A; b = 2.47 ˚ A; c = 2.42 ˚ A; s = 3.67 ˚ A 68 Thus, the area of one DMPC monolayer is: 2 2 ADM P C = 2.6˚ A × 10−16 cm2 /1˚ A = 2.58 × 10−16 cm2 (3.3) Number of moles of DMPC to form 1 monolayer: nDM P C = Aelectrode /ADM P C = 1.8 × 10−9 mol (3.4) Concentration of DMPC to form 1 monolayer (assume 20 µL chloroform) = 91 µM Thus, 2.2 mM DMPC lipid film used throughout this study is roughly equivalent to ∼24 monolayers. Chapter 4 Intein-mediated biocircuit for the detection of 1α,25-dihydroxyvitamin D3 4.1 Introduction The aim of this research is to build a DNA biocircuit to encode a synthetic pro- tein designed to signal the presence of a specific small molecule within a milieu of other molecules. This synthetic protein contains three elements: a human vi- tamin D receptor (VDR), a Mycobacterium tuberculosis (Mtu) RecA intein and a green fluorescent protein (GFP). VDR was chosen for its selectivity to vitamin D metabolites (i.e., 25-hydroxyvitamin D (25(OH)D) and 1α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3 ), which are important small molecules that play a fundamental role in calcium homeostasis, immune regulation, as well as cellular differentiation and apoptosis.1 Currently, vitamin D metabolites are detected by high performance liq- uid chromatography (HPLC), a method that requires sophisticated equipment and personnel to perform. Development of alternative approaches to measure medically relevant metabolites is an important goal in reducing health care costs. Our syn- thetic protein is one such alternative approach as it is designed to bind a vitamin D 69 70 metabolite in the VDR that subsequently activates the intein, which splices together two fragments of GFP to yield a functionally fluorescent GFP (Fig. 4.1). Another potential application of this synthetic protein is its use to identify novel compounds that can modulate the transcriptional activation of genes regulated by the hVDR. Discovery of agonistic or antagonistic small molecules that binds to the hVDR can lead to the development of effective therapeutics for various diseases in- cluding alopecia, chronic kidney disease and several forms of cancer. Current drug screening platforms such as cell-based transactivation assays for detecting vitamin D ligands2−4 are limited by long incubation times and variable results depending on the assay conditions. Therefore, this synthetic protein can provide a low-cost alternative for vitamin D metabolite detection with the added capability to serve as a high-throughput, first-line screening tool for identifying target molecules to the hVDR. Figure 4.1: Schematic of the synthetic protein comprising of a vitamin D receptor (VDR, blue) embedded in a Mtu RecA intein (red) flanked by a split green fluores- cent protein (GFP, green). Ligand binding will induce a conformational change in the intein, thus initiating a self-splicing mechanism that produces a dose-dependent fluorescence response via an intact GFP. 71 4.2 Experimental details 4.2.1 Reagents Restriction enzymes, Q5 DNA Polymerase, and T4 DNA ligase were purchased from New England Biolabs (NEB, Ipswich, MA). GoTaq Flexi DNA Polymerase was pur- chased from Promega. Oligonucleotides were ordered from Integrated DNA Tech- nologies (IDT-DNA, Coralville, IA). 25-dihydroxyvitamin D3 (25(OH)D3 ) was pur- chased from EMBO Life Sciences and 1α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3 ) was kindly provided by Dr. Satyanarayana Reddy and were dissolved in absolute ethanol and stored at –20 ◦ C. The concentration of vitamin D metabolites are deter- mined using extinction coefficient 264nm = 1.8 × 104 M−1cm−1 .5 4.2.2 Cell strains E. coli strain Top10, XL1 Blue and BL21(DE3) were used for subcloning, site-directed mutagenesis and protein expression respectively. The genotype of BL21(DE3) is F ompT gal dcm lon hsdSB (rB− mB− ) λ(DE3 [lacI lacUV5-T7 gene 1 ind1 sam7 nin5]). 4.2.3 DNA plasmid construction Ten plasmids were constructed using standard molecular cloning procedures. Figure 4.2 illustrates a simplified guide to traditional molecular biology techniques for DNA plasmid construction. A brief explanation for each step is provided below: 1. Transformation: is the process of incorporating DNA into competent cells either by electroporation or heat shock. For all plasmids constructed, chemically competent cells were prepared using CaCl2 and transformed with DNA by the heat shock method. 2. Grow single colonies: Agar plates made with Luria-Broth (LB) were made with the appropriate antibiotic to screen transformed cells that contain the plasmid with the corresponding antibiotic resistance marker. 72 3. DNA purification: Purification of DNA is achieved by using a Qiagen mini- prep kit after the DNA is amplified by growing transformed cells in a 6 mL overnight culture of LB plus the appropriate antibiotic. 4. DNA sequence: All DNA samples were sent to Genewiz Inc. (South Plain- field, NJ) for sequencing. 5. Polymerase chain reaction (PCR): is a technique to amplify a region of DNA (i.e. 106 copies) from a plasmid using specific forward and reverse primers (or short pieces of DNA). 6. Restriction enzyme digest: is a method to cut DNA at specific sequences (typically 6 base pairs) using bacterially derived restriction enzymes. 7. Gel electrophoresis: is a technique to separate DNA fragments based on size. Gels are prepared by dissolving 0.8 - 1.0 %(w/v) agarose into 1x TAE buffer. 8. DNA ligation: is the process of stitching two pieces of DNA fragments together using a T4 DNA ligase enzyme. To assemble plasmids I - X, fragments of DNA were amplified using polymerase chain reaction (PCR) or digested using restriction enzymes. Here is a more detailed description, as an example, for the construction of Plasmid V: The pIntGFP6−8 which encodes the intein-GFP was kindly donated by Dr. Henry Paulus. The ligand- binding domain (LBD) of the human vitamin D receptor (VDR), residues 108-427, was amplified by polymerase chain reaction (PCR) using forward primer P7 (5’- AGC CTA GGG GTC TGA AGC GGA A-3’) and reverse primer P8 (5’-CCA CCG CGG GAG ATC TCA TT-3’) on plasmid pN3x-Flag-hVDR (generously provided by Dr. James Fleet) containing the full length human VDR. The amplified VDR-LBD was digested with AvrII/SacII and ligated into a similarly digested pIntGFP vector at the linker region between the N- and C- intein sequences. The final VDR sensor protein, IntVDR(108-427)GFP, consists of the following components: (i) the GFP residues 1-128 with a E125V substitution, (ii) the N-terminal of the RecA intein residues 73 Figure 4.2: Step-by-step guide to basic molecular techniques involved in DNA plasmid construction. Description for each step is described in the text and where appropriate a protocol is provided in Appendix A. 1-104, (iii) the VDR-LBD residues 108-427, (iv) the C-terminal of the RecA intein residues 367-440, and (v) the GFP residues 129-239 with a I129C substitution. The sequences QPRRFDGFGDVGH6ARG (containing a 6x histidine tag for purification purposes) and RGGMKQVLGASRLRRD were used as linkers between the N-intein and VDR-LBD and between the VDR-LBD and C-intein fragments, respectively. 4.2.4 Protein expression and purification Figure 4.3 illustrates a step-by-step guide to the expression and purification of the sensor proteins encoded by plasmids IV - X. A single colony of transformed E. coli BL21(DE3) cells with the desired plasmid were grown in 6 mL Luria-broth (LB) supplemented with 100 g/mL ampicillin (Amp) or 35 µg/mL kanamycin (Kan) at 37 ◦ C for 14 h. One mL of the overnight culture was added to a 100 mL LB-Amp or LB-Kan culture and grown to a density (A600nm ) of 0.5. Protein expression was induced with 0.4 mM isopropyl β-D-thiogalactoside (IPTG) and allowed to grow for an additional 4 h at 37 ◦ C. Cells were harvested by centrifugation at 4000 rpm for 10 min and resuspended in 3 mL lysis buffer A (20 mM sodium phosphate buffer, 74 pH 7.5, 0.5 M NaCl). Cells were then passed through a French Press twice, and the pellet obtained by centrifugation at 16,000 rpm for 20 min was resuspended in buffer B (buffer A with 8 M urea at pH 7.9) once, centrifuged then resuspended in buffer B supplemented with 2 mM aldrithiol-4’. The aldrithiol-4’ addition helps to cap all the free thiols from cysteine residues and after centrifugation at 16,000 rpm for 20 min, the insoluble material is removed and the inclusion bodies are extracted. The solubilized inclusion bodies were loaded on a Ni-NTA column (GE Healthcare) and equilibrated with 5 column volumes of buffer B. The column was washed and fractions collected with buffer B with increasing imidazole concentration at 10 mM, 50 mM, 100 mM and 200 mM. The His-tagged sensor protein was eluted in the fractions containing 50 mM imidazole. The purified sensor protein in 8 M urea was renatured by an ∼8-fold dilution into buffer C (buffer A supplemented with 0.5 M L-arginine, pH 7.0). L-arginine is added to buffer C to help prevent protein aggregation. To visualize the protein collected in each fraction, a SDS-PAGE was performed using precast 10 - 20 % gradient Tris-glycine gels (Life Technologies) and a EZ-Run protein ladder. The gels were quick-stained with Coomassie Blue. Figure 4.3: Step-by-step guide to protein expression and purification for plasmids IV - X. Schematic shows the instructions for plasmid V: pIntVDR(108-427)GFP. A detailed protocol for IntGFP or IntVDRGFP expression is included in Appendix A. 75 4.2.5 Crude lysate preparation This procedure is a simplification to the above purification protocol. Cultures (25 mL) were used and after protein expression, the cells were harvested and resuspended in 3 mL buffer A as described previously. Cells were sonicated using 50 % maximum power output for 24 s with a 0.5 s pulse applied. The cells that were pelleted by centrifugation at 4000 rpm for 10 min were resuspended with 150 µL solubilization buffer B. Cells were centrifuge at 13,000 rpm for 5 minutes and the supernatant discarded. The insoluble fraction was resuspended in 1.5 mL dilution buffer C and the protein concentration of each sample determined using the bicinchoninic acid (BCA) protein assay kit (Thermo Scientific Pierce, Rockford, IL). Proteins were diluted using buffer C to a concentration of 75 µg/mL and aliquots were stored at –20 ◦ C. 4.2.6 Fluorimeter test for functional intein splicing activity A Cary Eclipse fluorescence spectrophotometer (Agilent Technologies, Chesterfield, MO) was used to detect the fluorescence of GFP using a quartz cuvette with a path length of 10 mm. The excitation wavelength was 395 nm and the emission spectrum was scanned between 450 and 600 nm. Both excitation and emission bandwidths were set to 5 nm. 4.2.7 Flow-activated cell sorter (FACS) analysis Protein splicing and fluorescence was detected in intact whole cells after protein in- duction and expression using the FACS Calibur (Becton Dickinson, NJ). Cells were harvested and centrifuged at 4000 rpm for 20 min. The pellet was resuspended in 3 mL 1x phosphate buffer solution prior to flowing through the FACS detector. 4.3 Results and discussion A total of ten plasmids (I - X) was constructed in this study. For each plasmid, a panel of figures showing a schematic for the construction of the plasmid, agarose gels 76 confirming the size of DNA fragments and SDS-PAGE gels to show protein expres- sion is provided. Protein splicing was monitored and reported by either FACS or fluorescence measurements. As a starting point to assemble the biocircuit which encodes the intVDRGFP sen- sor protein (Fig. 4.1), the plasmid p414-IntERGFP9 was received from Prof. David Liu (Harvard University). This yeast plasmid encodes for a intein-based sensor pro- tein with an estrogen receptor (ER) ligand binding domain (LBD) under an inducible Gal1 promoter. Since both the ER and VDR share similar structures and can be ex- pressed well in both bacteria and yeast cells, the goal of this study was to create an intein-VDR-GFP biocircuit for in vivo expression in bacterial cells. To achieve this goal, a high expression plasmid, pET26b which has a bacterial T7 promoter was se- lected as the backbone chassis for engineering the biocircuit for protein expression in BL21(DE3) bacterial cells. Plasmids I - III were created by using traditional molecular biology methods to assemble the gene of interest into the multiple cloning site (MCS) of the pET26b (Fig. 4.4(a), pink). Plasmid I was assembled to serve as a positive con- trol plasmid that encodes for an intact, functional enhanced green fluorescent protein (EGFP). Successful construction and expression of the EGFP is demonstrated in Fig. 4.4(b) - (d). The fluorescence of EGFP is detected using FACS and when cells trans- formed with pET26b-EGFP was induced with 0.4 mM isopropyl β-D-thiogalactoside (IPTG), a > 300-fold increase in fluorescence was observed compared to cells with- out plasmid (Fig. 4.4(f), panels (1) and (4)). Interestingly, uninduced cells with pET26b-EGFP also exhibited a 50-fold increase compared to cells without plasmid, suggesting that the T7 promoter may be leaky and protein expression occurs without the presence of the inducer (Fig. 4.4(f), panels (1) and (2)). Plasmids II and III were assembled from p414-IntERGFP to test the intERGFP and intVDRGFP sensor proteins in bacteria cells (Figs. 4.5 and 4.6). Although the construction of both plasmids and protein expression were successful, fluorescence analysis using FACS did not result in any observable fluorescence in the presence of the receptor’s natural ligands (i.e. estradiol, E2 and 1α,25-dihydroxyvitamin D3 (1α,25(OH)2 D3 ) respectively). The sensor proteins may not splice due to a failure in 77 Figure 4.4: Construction of pET26b-EGFP used as a positive fluorescent control plasmid. (a) Schematic of plasmids involved to create Plasmid I. (b) Agarose gel to confirm the PCR amplification of enhanced green fluorescent protein (EGFP) from pEGFP using primers P1 and P2 (720 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid III. Lane 1 = 1 kb DNA ladder; Lanes 2 - 7 = DNA from six successfully transformed colonies digested with NotI/NcoI. Multiple cloning site (MCS): 271 bp; Insert: 935 bp. (d) SDS-PAGE illustrating the successful expression of EGFP protein after induction for up to 6 h (26.2 kDa). (e) Western blot using anti-GFP to confirm protein band is our protein of interest. (f) Top to Bottom: Flow activated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b-EGFP with/without 0.4 mM IPTG and/or with/without 1 µM estradiol (E2 ). Abbreviations: AmpR: Ampicillin resistance gene; KanR: Kanamycin resistance gene. 78 the intein or the binding of the ligand to the receptor. Looking closer at the amino acid sequence of the intein, several amino acid mutations were observed between RecA intein from p414-IntERGFP and that from the National Institute of Health’s protein registry (Gene ID: 888371) (Fig. 4.7). These mutations may abolish the ability of the intein to splice. It is also possible that ligand binding did not occur since the ligand is lipophilic and was dissolved in 100 % ethanol prior to addition to the cells. The high ethanol concentration can cause a loss of fluorescence of any spliced GFP as well as cell death. To investigate the two potential factors that affect the production of a functional spliced GFP, namely intein splicing and ligand binding separately, plasmid IV (pInt- GFP) was obtained from Dr. Henry Paulus (Boston Biomedical Research Institute). pIntGFP consists of an intein-based circuit with split GFP exteins but without any receptor LBD. A protein sequence comparison of the intein from this plasmid was compared to that from the NIH protein registry and found that there were no amino acid mutations. The IntGFP protein was expressed successfully and purified from the insoluble fraction (Fig. 4.8(b)). Fluorescence emission at λ = 510 nm indicated intein splicing occurred in the presence of 1 mM tris (2-carboxyethyl)phosphine (TCEP), a reducing agent to help break apart the disulfide bonds (Fig. 4.8(c) – (d)). With a functional IntGFP biocircuit, plasmid V was constructed by the addition of the VDR-LBD (amino acids: 108-427) into the spacer region between the N- and C- intein fragments of pIntGFP. Construction and expression of the IntVDRGFP was successful and splicing was again triggered by the presence of 1 mM TCEP (Fig. 4.9). Splicing activity of both IntGFP (53.2 kDa) and IntVDRGFP (82 kDa) was confirmed by an SDS-PAGE gel with the excised Intein (24 kDa) or InteinVDR (53 kDa) and spliced GFP (29 kDa) indicated in the red boxes (Fig. 4.10). Although splicing was observed from both biocircuits in plasmid IV and V, there were two main issues. First, expression of the sensor protein (both IntGFP and IntV- DRGFP) resulted in inclusion body formation, which are aggregates of improperly folded (i.e., inactive) proteins. This is a common problem faced in the expression of synthetic proteins and our target synthetic protein is no exception.10,11 In order to 79 Figure 4.5: Construction of pET26b-IntERGFP used as a plasmid to confirm in- tein splicing activity. (a) Schematic of plasmids involved to create Plasmid II. (b) Agarose gel to confirm the PCR amplification of IntERGFP from p414-IntERGFP using primers P3 and P4 (1953 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid III. Lane 1 = 1 kb DNA ladder; Lanes 2 - 7 = DNA from six successfully transformed colonies digested with NotI/NcoI. Multiple cloning site (MCS): 271 bp; Insert: 2197 bp. (d) SDS-PAGE illustrating the successful expression of IntERGFP protein after 16 h induction with 0.4 mM IPTG (71.6 kDa). (e) Top to Bottom: Flow activated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b-IntERGFP with/without 0.4 mM IPTG and/or with/without 1 µM estradiol (E2 ). Abbreviation: Trp: Tryptophan. 80 Figure 4.6: Construction of pET26b-IntVDR(108-427)GFP the biocircuit that en- codes the sensor protein. (a) Schematic of plasmids involved to create Plasmid III. (b) Agarose gel to confirm the digestion of ER-LBD with RsrII/NheI from pET26b- IntERGFP (744 bp) (c) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 - 3: PCR amplification of VDR-LBD(108-427) (995 bp) from pN3-Flag-hVDR without and with primers P5 and P6, respectively. (d) SDS-PAGE illustrating the successful expression of sensor protein after induction for up to 12 h (82 kDa). (e) Top to Bottom: Flow activated cell sorter (FACS) analysis for BL21(DE3) bacterial cells with no plasmid; BL21(DE3) + pET26b-IntVDR(108- 427)GFP with/without 0.4 mM IPTG and/or with/without 1 µM 1α,25(OH)2 D3 . Abbreviation: CMV: Cytomegalovirus promoter 81 Figure 4.7: Amino acid sequence comparison of the RecA intein from the NIH protein registry (GeneID:888371) which includes the homing endonuclease sequence and the RecA inteins that encodes the N- and C- fragments of p414-IntERGFP (received from Prof. David Liu) and pIntGFP (received from Prof. Henry Paulus). The latter two inteins have all or part of the homing endonculease region replaced by spacer sequences of different lengths. 82 Figure 4.8: (a) Plasmid map for pIntGFP. Note: pelB sequence is not present on this plasmid. (b) SDS-PAGE showing the soluble, insoluble and purified fractions after a 4 h induction and expression of IntGFP (53 kDa). (c) The fluorescent intensity is measured for 75 µg/mL IntGFP with 1 mM TCEP as a function of wavelength. Excitation and emission wavelengths are 395 nm and 510 nm, respectively. (d) Flu- orescent intensity measured as a function of time for 75 µg/mL IntGFP with and without 1 mM TCEP. The buffer composition is 20 mM sodium phosphate, pH 7.0, 0.5 M NaCl and 0.5 M L-arginine. 83 Figure 4.9: Construction of pIntVDR(108-427)GFP – the biocircuit that encodes the sensor protein. (a) Schematic of plasmids involved to create Plasmid V. (b) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = VDR-LBD(108-427) amplified by PCR from from pN3-Flag-hVDR using primers P5 and P6 (960 bp); Lanes 3 - 4 = IntGFP (1450 bp) and IntVDRGFP (2247 bp) amplified by PCR from pIntGFP and pIntVDRGFP using primers T7Fwd and T7Rev, respectively. (c) SDS-PAGE showing the soluble, insoluble and purified fractions after a 4 hr induction and expression of IntVDR(108-427)GFP (85 kDa). (d) The fluorescent intensity is measured for 75 µg/mL IntVDR(108-427)GFP with 1 mM TCEP as a function of wavelength. Excitation and emission wavelengths are 395 nm and 510 nm, respectively. (e) Fluorescent intensity measured as a function of time for 75 µg/mL IntVDR(108-427)GFP with and without 1 mM TCEP. The buffer composition is 20 mM sodium phosphate, pH 7.0, 0.5 M NaCl and 0.5 M L-arginine. 84 Figure 4.10: SDS-PAGE showing the spliced products after purified IntGFP and IntVDRGFP expressed from BL21(DE3) cells transformed with plasmid IV and V, respectively. Samples of IntGFP and IntVDRGFP were kept with or without 1 mM TCEP and/or 1 µM 1α,25(OH)2 D3 . test for splicing activity, the sensor protein had to be first extracted and renatured, converting what would have been a simple, in vivo biosensor to a cumbersome in vitro system. Second, intein splicing occurs only in the presence of 1 mM TCEP, when ideally, the trigger should be a vitamin D metabolite. TCEP appears to be a necessary trigger as long as the sensor protein is expressed as inclusion bodies which will require disulfide cleavage for the protein to renature and fold properly. Disulfide cleavage into two free thiols/ cysteines is also necessary for intein splicing to occur (Fig. 1.9). Thus, we hypothesize that if the sensor protein can be stably expressed in the soluble fraction, then both of the aforementioned problems can be addressed. In order to achieve expression of the sensor protein into the soluble fraction, we explored four different parameters to minimize the formation of inclusion bodies and demonstrate splicing activity, keeping in mind that the optimized outcome may be achieved through one or a combination of these factors. The parameters investigated include: (1) the length of the VDR-LBD; (2) induction temperature; (3) concentration of IPTG; and (4) addition of a pelB DNA sequence, which sends expressed proteins 85 Figure 4.11: (a) Schematic representation illustrating the construction of plasmids VI - VIII which involves successive truncations of the VDR-LBD. The goal is to reduce the overall size of the sensor protein (i.e. IntVDR(108-427)GFP) to be comparable to the size of the IntERGFP. (b) Agarose gel to confirm the successful construction and truncation of the plasmids VI - VIII using site-directed mutagenesis and primers P9 - P14. Lanes 1 - 4 = same as Fig. 4.9(b). Lanes 5 - 7 = DNA amplified by PCR using primers T7Fwd and T7Rev on plasmids VI - VIII respectively. Expected sizes are: 2094 bp, 2058 bp and 2034 bp. The PCR plasmid controls without amplified product are present in the agarose gel on the right. 86 into the periplasmic space of the bacterium. The first parameter studied was the effect of the length of the VDR-LBD. The size of IntVDRGFP is almost 100 amino acids longer than that of IntERGFP ex- pressed from p414-IntERGFP9 (Fig. 4.11(a)). When looking at the stability index of the two proteins, based on their amino acid composition, IntERGFP was stable while IntVDRGFP was statistically unstable in a test tube. This may be due to the added length of the VDR-LBD and a higher concentration of the certain dipeptides known to cause protein instability.12 The crystal structure of the VDR-LBD revealed the removal of a flexible loop region encoded by amino acids 165-215 in order for successful crystallization to be achieved. The removal of this region had been shown to not affect the ligand binding activity of the VDR-LBD.13 Furthermore, the average distance between the N- to C- termini of the ERα-LBD14,15 crystal structure is 24.5 ˚ A while for the VDR-LBD the distance is 40.8 ˚ A (Fig. 1.8). Taking all this together, we assumed that the instability of the VDR-LBD(108-427) may be due to its length and assembled three additional plasmids (plasmid VI - VIII) with sequential trun- cations of the VDR-LBD using the QuikChange II site-directed mutagenesis system (Stratagene).16,17 Three sets of forward and reverse primers were designed (P9 – P14) and used in three sequential rounds of site-directed mutagenesis. The sequential set of deletions generated the following sensor proteins: (1) IntVDR(118-427)GFP; (2) IntVDR(118-427,∆165-215)GFP; and (3) IntVDR(118-425,∆165-215)GFP. The suc- cessful construction of the three plasmids is demonstrated in Fig. 4.11(b) and the amino acid sequence of the region between the N- and C-intein fragments is provided in Fig. 4.12. Figure 4.13 shows the fluorescent measurements performed on the expressed sensor proteins encoded by biocircuits on plasmids IV - VIII. Truncation of the VDR-LBD did not result in expression of the sensor proteins into the soluble fraction. In order to simplify the protein purification protocol, the crude lysate (i.e. sensor protein is not purified) of the insoluble fraction was examined for fluorescence output. Fig- ure 4.13(a) shows BL21(DE3) cells with no plasmid and thus no fluorescence was measured in all conditions tested. Figure 4.13(b) and (c) measures the fluorescent 87 Figure 4.12: Amino acid sequence comparison of the region between Int(N) and Int(C) for plasmids IV - VIII. Red: Intein regions; Blue: VDR-LBD of various lengths; Yellow: 6x-His tag. 88 Figure 4.13: Fluorescent intensity as a function of wavelength reported for (a) BL21(DE3) cells only; (b) IntGFP; (c) IntVDR(108-427)GFP; (d) IntVDR(108- 427,∆165-215)GFP; (e) IntVDR(118-427,∆165-215)GFP; and (f) IntVDR(118- 425,∆165-215)GFP. All proteins are expressed with a 0.4 mM IPTG induction for 4 hours and the fluorescent measurements are made in crude lysate from the insolu- ble fraction. VD = 1 µM 1α,25(OH)2 D3 intensity for expressed IntGFP (from plasmid IV) and IntVDR(108-427)GFP (from plasmid V), respectively, in the crude lysate under different expression conditions. Both a drop in the pH (red line) and the addition of 1 mM TCEP (blue line) resulted in an observable GFP, with a peak emission at 510 nm. Splicing activity is inconclu- sive for the addition of 1 µM 1α,25(OH)2 D3 (green line) since there is a large amount of background self-splicing observed. When comparing the sensor proteins of the IntVDRGFP with the different VDR-LBD truncations expressed from cells trans- formed with plasmids V VIII (Fig. 4.13(d)–(f)), IntVDR(118-425,∆165-215)GFP exhibited the most similar fluorescent intensity profile as the control IntGFP case (Fig. 4.13(f) vs. (b), respectively). Interestingly, this VDR-LBD truncation has the same amino acid sequence as the reported cystal structure for the receptor’s LBD.13 Since the truncation of the VDR-LBD did not result in a soluble version of the sensor protein, the next parameter investigated was the effect of induction temper- 89 Figure 4.14: SDS-PAGE showing the soluble and insoluble fractions after IntGFP (53 kDa) has been expressed from BL21(DE3) cells transformed with plasmid IV. Induction conditions are T = 37 ◦ C or 20 ◦ C at a constant IPTG concentration of 0.4 mM. ature on inclusion body formation. To simplify the sensor protein construct, these experiments were performed using plasmid IV which encodes for the IntGFP synthetic protein. Figure 4.14 shows an SDS-PAGE for the soluble and insoluble fractions har- vested from cells with pIntGFP expressed at of T = 37 ◦C and 20 ◦ C. Temperature alone reveals that the expression of IntGFP remained in the insoluble fraction. Next, the effects of IPTG concentration (0.01 mM or 0.1 mM) was investigated for cells with pIntGFP at T = 30 ◦ C or 37 ◦ C (Fig. 4.15(a)). The expected IntGFP size is 53.2 kDa which appears to be expressed in the insoluble fraction at T = 30 ◦ C and concentration of IPTG at 0.01 mM. However, in the case where T = 37 ◦C and IPTG concentration is 0.1 mM , the band at 53 kDa is faint in the insoluble fraction. If IntGFP is not expressed in the insoluble, then perhaps it may be expressed in the soluble fraction, but in too small of a quantity to be detectable by the SDS-PAGE. Thus, fluorescent measurements were performed using the soluble fraction of T = 37 ◦ C and concentration of IPTG at 0.1 mM. In the presence of 1 mM TCEP, there is a substantial increase at λ = 475 nm (Fig. 4.15(b)). Without TCEP and at two different pH, the crude lysate of this soluble fraction did not exhibit much spectral increase over a period of 5 h (Fig. 4.15(c) - (e)). When GFP is excited at 395 nm, 90 over time, it is known that a photo-isomerization effect occurs where a decrease in the 395 nm excitation peak is observed and correlated to a reciprocal increase in the 475 nm excitation band.18,19 When a mature chromophore is present, then a 510 nm fluorescence emission is observed (Fig. 1.10). The data presented in Fig. 4.15(b) - (e) suggests that GFP is present in the soluble fraction tested due to the spectral increase at 475 nm. However, it is possible that the chromophore is not folded properly within the crude lysate and thus no fluorescene emission is detected at 510 nm. The last parameter investigated was the addition of a pelB sequence to the expres- sion plasmid. This was achieved by using PCR amplification of the IntGFP region from pIntGFP and inserting the DNA fragment into the pET26b (used previously in the construction of plasmids I - III) to create plasmid IX (Fig. 4.16). Expres- sion of IntGFP-pelB from plasmid IX at T = 37 ◦ C and 20 ◦ C at 0.4 mM IPTG revealed a loss of the 53.2 kDa band in the insoluble fractions (Fig. 4.17(a)). How- ever, this band was not observed in the soluble fraction either. What was observed were two strongly visible bands that correspond well with the spliced products of IntGFP whi are GFP (29 kDa) and Intein (24 kDa). This observation suggests that the intGFP was expressed in the periplasmic space, but due to the naturally reducing environment of this cellular compartment, the sensor protein may have undergone self-splicing. To confirm this hypothesis, fluorescence measurements were monitored for both the soluble and insoluble fractions from the induction condition (T = 37 ◦ C and IPTG concentration = 0.4 mM)(Figs. 4.17(b) - (c) respectively). Figure 4.17(d) shows a fluorescent intensity measured at λ = 510 nm plotted as a function of time for both IntGFP and IntGFP-pelB expressed at T = 37 ◦ C. Without TCEP added, the soluble fraction of IntGFP-pelB shows an increased rate of fluorescence (Fig. 4.17(d), orange), which supports that self-splicing is occurring. Plasmid X is the last plasmid created and consists of the IntVDR(118-425,∆165- 215)GFP biocircuit inserted into pET26b (Fig. 4.18). We hypothesized that while self-splicing was observed for IntGFP-pelB, the addition of the VDR-LBD in between the N- and C-intein fragments may slow down the rate of self-splicing. Expression of IntVDR(118-425,∆165-215)GFP (82 kDa) was observed in the soluble fraction, how- 91 Figure 4.15: (a) SDS-PAGE showing the soluble and insoluble fractions after IntGFP has been expressed from BL21(DE3) cells transformed with plasmid IV. Induction conditions are T = 30 ◦ C or 37 ◦ C and IPTG concentration at 0.01 mM or 0.1 mM. Fluorescent intensity measured as a function of wavelength for the soluble fraction (T = 37 ◦ C and IPTG concentration = 0.1 mM) at (b) pH 7.5, 1 mM TCEP; (c) pH 7.5, 0 mM TCEP; and (d) pH 7.0, 0 mM TCEP. (e) The fluorescent intensity is measured as a function of time for panels (b) – (d) at λ = 510 nm. 92 Figure 4.16: Construction of pET26b-IntGFP. (a) Schematic of plasmids involved to create Plasmid IX. (b) Agarose gel to confirm size of the following DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = pET26b digested with NotI/EcoRI (5360 bp); Lane 3 = IntGFP amplified from pIntGFP by PCR using primers P17 and P18 (1383 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid IX. Lane 1 = 1 kb DNA ladder; Lanes 2 - 4 = DNA from three successfully transformed colonies digested with NotI/EcoR. Lane 5: pET26b digested with NotI/EcoRI. 93 Figure 4.17: (a) SDS-PAGE showing the soluble and insoluble fractions after IntGFP has been expressed from BL21(DE3) cells transformed with plasmid IX which con- tains the pelB sequence. Induction conditions are T = 37 ◦ C or 20 ◦ C at a constant IPTG concentration of 0.4 mM. Fluorescent intensity measured as a function of wave- length for the (b) soluble fraction (T = 37 ◦C) and (c) insoluble fraction (T = 37 ◦ C). (d) The fluorescent intensity is measured for the soluble and insoluble fractions collected from IntGFP expressed from plasmid IX (orange diamond and green tri- angle, respectively). For comparison, the fluorescent intensity measured for IntGFP expressed from plasmid IV in the insoluble fraction is also included (black square, blue triangle and red circle). All fluorescent intensity is measured at λ = 510 nm. 94 Figure 4.18: Construction of pET26b-IntVDR(118-425,∆165-215)GFP. (a) Schematic of plasmids involved to create Plasmid X. (b) Agarose gel to confirm size of the fol- lowing DNA fragments: Lane 1 = 1 kb DNA ladder; Lane 2 = pET26b digested with NotI/EcoRI (5360 bp); Lane 3 = Plasmid VIII digested with NotI/EcoRI (5466 bp, 2034 bp). (c) Agarose gel to confirm successful ligation and transformation of Plasmid X. Lane 1 = 1 kb DNA ladder; Lanes 2 - 8 = DNA from seven successfully transformed colonies digested with NotI/EcoRI; Lane 9: pET26b digested with NotI/EcoRI. (d) SDS-PAGE of the soluble and insoluble fractions of the sensor protein induced at 0.4 mM IPTG for 4 h at 37 ◦C. Red box (1) InteinVDR = 53 kDa; Red Box (2) GFP = 29 kDa. (e) Fluorescent intensity measured as a function of wavelength for the soluble fraction in panel (d) over 12 h. ever, the sensor protein self-splice into InteinVDR (53 kDa) and GFP (29 kDa) (Fig. 4.18(d)). Interestingly, under the same induction conditions and with a pelB sequence present, expression of IntVDR(108-427)GFP (from Plasmid III) and IntVDR(118- 425,∆165-215)GFP (from Plasmid X) was observed in the soluble fraction, but the former as an intact protein while the latter self-spliced (Fig. 4.5(d) and Fig. 4.18(d)). This finding further suggests that the point mutations found in the intein region may have abolished splicing activity for sensor proteins expressed from Plasmids II and III. 95 4.4 Conclusion In conclusion, a total of ten plasmids were designed and assembled successfully over the course of this project. The overall goal is to construct an intein-based biocircuit that encodes for a sensor protein that can be expressed to produce a dose-dependent fluorescent response in the presence of vitamin D metabolites. Due to the shared sim- ilarities and modularity of nuclear hormone receptors (NHRs), the most straightfor- ward approach was to swap the estrogen receptor ligand binding domain (ER-LBD) from p414IntERGFP with that of the vitamin D receptor ligand binding domain (VDR-LBD). This resulted in the work and fabrication of plasmids I - III. Despite the successful construction of the IntVDR(108-427)GFP biocircuit, intein splicing of the green fluorescent protein (GFP) was not observed, which may be attributed to several point mutations within the DNA and protein sequence of the intein. Plasmids V - X were subsequently assembled from pIntGFP (Plasmid IV) after first demonstrating functional intein splicing of the sensor protein, IntGFP (which lacks any NHR-LBDs) in the presence of a small trigger molecule, TCEP. The prob- lem encountered with the synthetic proteins encoded by Plasmids IV and V was that protein expression led to the formation of inclusion bodies, which are protein aggre- gates that are insoluble and inactive. Extraction, purification and renaturation of synthetic protein from inclusion bodies is cumbersome, lengthy and impractical for real-time biosensing. Thus, different parameters including the length of the VDR- LBD (Plasmids VI - VIII), incubation conditions (i.e., temperature, T and concentra- tion of added inducer (IPTG)), and addition of a pelB leader sequence (Plasmids IX - X) were explored in attempt to express the synthetic proteins in the soluble fraction and thereby minimizing inclusion body formation. The sensor protein, IntVDR(118-425,∆165-215)GFP with a shortened VDR-LBD and encoded by Plasmid VIII resulted in a similar intein splicing activity profile as the control protein, IntGFP. However, the protein remained in the insoluble fraction. Temperature alone also did not affect the expression of the sensor protein into the soluble fraction. When the concentration of IPTG was reduced, fluorescence mea- 96 surements of the crude lysate suggested self-splicing may be present in forming a detectable immature GFP chromophore. Addition of the pelB sequence appears to be the most successful method for driving the protein expression into the soluble frac- tion, however, due to the natural reducing environment of the periplasmic space, self- splicing of the intein was observed without any trigger molecules present (i.e., TCEP or vitamin D metabolite). Further studies to stabilize the IntVDR(118-425,∆165- 215)GFP-pelB expressed from Plasmid X in the soluble fraction will be necessary. These studies may include a systemic study on the effect of pH on the self-splicing activity of the intein or to perform a directed evolution process to evolve and control a sensor protein that splices only in the presence of 25(OH)D3 or 1α,25(OH)2 D3 . 4.5 References 1. A. W. Norman. From vitamin D to hormone D: fundamentals of the vitamin D endocrine system essential for good health. Am. J. Clin. Nutr., 88:491S, 2008. 2. PolarScreenT M Vitamin D Receptor Competitive Assay kit instructions. Invit- rogen Corp.: Carlsbad, CA, 2006. 3. LanthaScreen TR-FRET Vitamin D Receptor Coactivator Assay kit instruc- tions. Invitrogen Corp.: Carlsbad, CA, 2007. 4. GeneBLAzer VDR Cell-Based Assay kit instructions. Invitrogen Corp.: Carls- bad, CA, 2007. 5. E. Uchida, N. Kagawa, T. Sakaki, N. Urushino, N. Sawada,M. Kamakura, M. Ohta, S. Kato, and K. Inouye. Purification and characterization of mouse CYP27B1 overproduced by an Escherichia coli system coexpressing molecular chaperonins GroEL/ES. Biochem. Biophys. Res. Commun., 323:505, 2004. 6. J. P. Gangopadhyay, S. Jiang, and H. Paulus. An in vitro screening system for protein splicing inhibitors based on green fluorescent protein as an indicator. Anal. Chem., 75:2456, 2003. 97 7. K. Shingledecker, S. Jiang, and H. Paulus. Molecular dissection of the My- cobacterium tuberculosis RecA intein: design of a minimal intein and of a trans- splicing system involving two intein fragments. Gene, 207:187, 1998. 8. J. P. Gangopadhyay, S. Jiang, P. V. Berkel, and H. Paulus. In vitro splicing of erythropoietin by the Mycobacterium tuberculosis RecA intein without substi- tuting amino acids at the splice junctions. Biochim. Biophys. Acta, 1619:193, 2003. 9. A. R. Buskirk, Y.-C. Ong, Z. J. Gartner, and D. R. Liu. Directed evolution of ligand dependence: small-molecule-activated protein splicing. Proc. Natl. Acad. Sci. USA, 101:10505, 2004. 10. G. Georgiou, and P. Valax. Expression of correctly folded proteins in Es- cherichia coli. Curr. Opin. Biotech., 7:190, 1996. 11. R. Rudolph, and H. Lilie. In vitro folding of inclusion body proteins. FASEB J., 10:49, 1996. 12. K. Guruprasad, B. V. B. Reddy, and M. W. Pandit. Correlation between stabil- ity of a protein and its dipeptide composition: a novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Eng., 4:155, 1990. 13. N. Rochel, J. M. Wurtz, A. Mitschler, B. Klaholz, and D. Moras. The crystal structure of the nuclear receptor for vitamin D bound to its natural ligand. Mol. Cell., 5:173, 2000. 14. A. M. Brzozowski, A. C. W. Pike, Z. Dauter, R. E. Hubbard, T. Bonn, L. Engstrom, ˙ G. L. Greene, J. A. Gustafsson, and M. Carlquist. Molecular basis of agonism and antagonism in the oestrogen receptor. Nature, 389:753, 1997. 15. A. K. Shiau, D. Barstad, P. M. Loria, L. Cheng, P. J. Kushner, D. A. Agard, and G. L. Greene. The structural basis of estrogen receptor/coactivator recognition and the antagonism of this interaction by tamoxifen. Cell, 95:927, 1998. 98 16. W. Wang, and B. A. Malcolm. Two-stage PCR protocol allowing introduction of multiple mutations, deletions and insertions using QuikChange site-directed mutagenesis. BioTechniques, 26:680, 1992. 17. QuikChange Site-Directed Mutagenesis Kit Product Manual, Stratagene, 2007. 18. F. Yang, L. G. Moss, and G. N. Phillips Jr. The molecular structure of green fluorescent protein. Nat. Biotechnol., 14:1246, 1996. 19. A. Cubitt, R. Heim, S. Adams, A. Boyd, L. Gross, and R. Tsien. Understanding, improving and using green fluorescent proteins. TIBS., 20:448, 1995. Chapter 5 Nanoscale plasmonic interferometers for multi-spectral, high-throughput biochemical sensing 5.1 Abstract In this chapter, we report the design, fabrication and characterization of novel bio- chemical sensors consisting of nanoscale grooves and slits milled in a metal film to form two-arm, three-beam, planar plasmonic interferometers. By integrating thou- sands of plasmonic interferometers per square millimeter with a microfluidic system, we demonstrate a sensor able to detect physiological concentrations of glucose in wa- ter over a broad wavelength range (400 – 800 nm). A wavelength sensitivity between 370 – 630 nm/RIU (RIU, Refractive Index Units), a relative intensity change be- tween ∼103 – ∼106 %/RIU, and a resolution of ∼3 × 10−7 in refractive index change were experimentally measured using typical sensing volumes as low as 20 femtoliters (fL). These results show that multispectral plasmonic interferometry is a promising approach for the development of high-throughput, real-time and extremely compact 99 100 biochemical sensors. 5.2 Introduction The past several decades have seen a rapidly growing interest in the field of biolog- ical and chemical sensing. Many optical methods have been developed, based on fiber optics,1,2 Mach-Zehnder interferometry,3 ring resonators,4 surface enhanced Ra- man scattering (SERS),5−10 and surface plasmon resonance (SPR).11,12 Among the various techniques, SPR has been one of the most successful in the development of biochemical sensors in the last 30 years. It is known that by using metal-dielectric nano-structures (such as grooves, slits and holes)13−15 or a prism,16−19 light at optical frequencies can be efficiently coupled to surface plasmon polaritons (SPPs).20−27 SPPs are electromagnetic waves coupled to oscillations of free electrons in a metal charac- terized both by maximum field amplitudes at the metal surface and by wavelengths much shorter than that of the incident light. Being confined at the metal surface, SPPs can be very sensitive to changes in the dielectric properties of the materials they propagate through. With this ideal property, SPPs have been used extensively to sense the presence of biological and chemical analytes in real time.28−42 Typical SPR implementations rely on a prism or metallic grating (such as groove, slit and hole arrays) to couple the incident beam into propagating SPPs, using light in- cident at a wavelength-specific angle. Also widely used are localized surface plasmon resonances (L-SPRs) in metal nanoparticles producing resonant scattering and ex- tinction at specific frequencies.43−45 Given the resonant nature of the SPP excitation, practical implementations of SPR-based sensing schemes are limited in the number and range of wavelengths that can be used to sense the presence of analytes.28−42 thus further limiting their spectroscopic capabilities. In this chapter, we develop a nanoscale plasmonic interferometer consisting of two grooves flanking a slit in a silver film. The two grooves scatter a normally incident white light beam into multi-frequency SPPs, counter-propagating at the metal/dielectric interface. The field amplitudes of the two SPP waves interfere with 101 the incident field at the slit location, thus causing a modulation in the light intensity transmitted through the slit. The transmitted intensity depends on wavelength, re- fractive index, and it can also be tuned by simply varying the groove-slit separation distances (i.e. the lengths of the two interferometer arms). Since SPPs are strongly confined at the metal/dielectric interface, a far-field measurement of the light inten- sity transmitted through the slit carries information about the near-field interaction of the SPPs with the dielectric material, useful to determine the refractive index of unknown chemical analytes and their concentration in solution, only a few tens or hundreds of nanometers above the metal surface. Furthermore, SPPs can be gen- erated at multiple frequencies simultaneously using the same groove and incoupling angle, thus enabling operation of the plasmonic interferometer even at frequencies far from the metal resonance, and extraction of the analyte dispersion relation in a broad wavelength range. Hence, plasmonic interferometers offer a novel scheme for SPP excitation and refractive index detection using SPP interference, retaining real-time and label-free sensing capabilities of existing technologies. In this paper, we present on the design, fabrication, and characterization of plasmonic interferometers using glucose as a model analyte to assess their sensing capabilities. 5.3 Experimental details 5.3.1 Fabrication, optimization and characterization of plas- monic interferometers Plasmonic interferometers consisting of groove-slit (GS) and groove-slit-groove (GSG) structures were fabricated in a metal film. Figure 5.1(a) shows a scanning electron microscopy (SEM) image of a representative GSG plasmonic interferometer consist- ing of a 100-nm-wide, 300-nm-deep, 10-µm-long slit flanked by two 200-nm-wide, ∼20-nm-deep and 10-µm-long grooves as determined by top-view SEM images seen in Fig. 5.2. Using electron beam evaporation, a 4-nm thick titanium adhesion layer was first deposited onto previously cleaned quartz slides, followed by a 300-nm-thick 102 Figure 5.1: (a) SEM micrograph of a groove-slit-groove (GSG) plasmonic interfer- ometer with p1 = 0.57 µm and p2 = 1.85 µm. The separation distance between each groove and the slit defines one arm of the interferometer. The slit and groove widths are 100 nm and 200 nm, respectively. The depth of each groove is ∼20 nm. (b) Schematic of the working principle of a plasmonic interferometer. A collimated white light beam (λ = 400 – 800 nm) uniformly illuminates the structure. Diffractive scattering by the grooves converts the incident beam into counter-propagating SPPs. The total transmitted intensity (IT ) through the slit is the result of the three-beam interference at the slit position between the incident field amplitude (E0 ), the ampli- tudes of the propagating SPPs originating from the left groove (ESP P 1 ) and from the right side groove (ESP P 2 ). The interference conditions can be tuned by varying the length of the interferometer arms (p1 , p2 ) and the incident wavelength, λ. 103 silver layer. Silver was chosen because it supports SPPs that can propagate for several tens of micrometers without significant attenuation, allowing fabrication of plasmonic interferometers with arm length ranging between ∼200 nm – 20 µm. Plasmonic in- terferometers were then fabricated using focused ion beam (FIB) milling, with a typical Ga-ion beam current of 200 pA and an accelerating voltage of 30 kV. By using a custom made scripting routine able to automatically move the sample stage, adjust beam focus and stigmatism at each sample location, and etch the devices with specified width, length and interferometer arm length, more than 1,000 plasmonic in- terferometers can be milled in less than two hours, over an area of ∼1 mm2. Several columns of GSG devices were milled according to various combinations of interferom- eter arm lengths with p1 (left groove-slit separation distance) held constant to 0.4, 0.57, 0.74, 0.89, 1.09, 1.67 and 5.70 µm, respectively for each column, and p2 (right slit-groove distance) varying from 0.25 to 10 µm increasing in steps of 25 nm. The in- terferometer arm lengths have been chosen based on optimized sensitivity and sensor response as simulated using the model developed in the following. For comparison, a single column of GS devices was also milled on the same chip along with a column of identical single-slit devices to serve as a reference for normalization of the raw transmitted intensity spectra measured for GS and GSG plasmonic interferometers. 5.3.2 Optical set-up and spectral data acquisition The spectral dependence of light intensity transmitted through the slit of each plas- monic interferometer was measured using a modified inverted microscope (Nikon Ti Eclipse) coupled to a spectrograph and a CCD camera (Fig. 5.3). A 100 W broadband halogen light source was aligned to the optical axis of the inverted microscope. For the experiment, both the field and aperture diaphragms of the microscope condenser lens were closed to achieve a collimated light beam, normally incident upon the top of the sample surface, as schematically shown in Fig. 5.1(b). The actual power incident on the sample measured by a calibrated photo diode was only 7 µW (integrated over the full wavelength range), uniform over a spot with diameter of ∼0.3 mm, leading to a power density of only 10−2 W/cm2 . The low power density and continuous flow of 104 Figure 5.2: Scanning electron microscopy (SEM) images of two different types of plas- monic interferometers: (a) a groove-slit plasmonic interferometer with interferometer arm (groove-slit separation distance) p = 2.00 µm, (b) a groove-slit-groove plasmonic interferometer with p1 = 0.57 µm and p2 = 2.00 µm. The groove width is 200 nm, length is 10 µm and depth is ∼20 nm. The slit is 100 nm wide, 10 µm long and 300 nm deep. 105 Figure 5.3: Optical path and experimental set-up to acquire the light intensity trans- mitted through the slit of each plasmonic interferometer water employed during the sensing experiment allowed the temperature of the device to be held constant throughout the experiment. The far-field light intensity trans- mitted through the slit of each plasmonic interferometer was then collected by a 40× objective lens with numerical aperture NA = 0.6, dispersed using a single-grating monochromator and detected with a charge-coupled device (CCD) camera. Spectral resolution of our set-up was ∼0.4 nm; the number of counts and acquired spectra per experiment were adjusted to ensure a statistical error of < 0.1% in the measured transmitted intensity. 5.3.3 Fabrication of microfludic channel A 1” by 1” quartz master was created by patterning SU-8 negative photoresist (Mi- croChem Corporation, Newton, MA) into a rectangular microchannel with dimensions of 2-cm long × 1-cm wide × 70-µm high. Polydimethylsiloxane (PDMS) pre-polymer and a curing agent (SYLGARD 184 Silicone Elastomer Kit, Dow Corning, Midland, 106 MI) were mixed in a 10:1 mass ratio, degassed using a vacuum desiccator, and cured against the master at 70 ◦ C for 5 h. The PDMS was peeled from the master and inlet and outlet holes were punched using a 1.2 mm hole puncher (Harris Uni-core, Ted Pella Inc.). A custom holder was created to securely sandwich the PDMS on top of the patterned quartz substrate with an array of plasmonic interferometers while allowing perfect allocation in the automated microscope stage slot. 5.4 Results and discussion 5.4.1 SPP Interference model An SPP interference model was developed to predict the optical response for the plasmonic interferometer, extending reported models dealing with groove diffraction and SPP interference.13−15,46−50 As shown in Fig. 5.1(b), light incident upon the left-side groove generates SPPs propagating toward the slit. At the slit location, and for each frequency, the SPP (with complex amplitude ESP P 1 ) will interfere with the coherent incident beam (E0 ). Light incident on the right groove also excites an SPP with amplitude ESP P 2 , traveling along the metal surface and interfering with the incident beam and the other SPP wave at the slit location. Though the slit can also generate SPPs, these are mainly scattered back in free space by out-of-plane scattering once they reach the neighboring grooves. Therefore, slit-generated SPPs do not contribute significantly to the transmitted intensity through the same slit. Accordingly, for this model, only the SPPs originating from the two grooves will be considered. This assumption is verified by the excellent agreement between simulated and experimental results. The resulting total transmitted intensity through the slit of a GSG two-arm plasmonic interferometer is given by: IT =| ET |2= IS | 1 + β1eiφ1 + β2 eiφ2 |2 (5.1) where IS is the light intensity transmitted through an isolated slit with identical width and length; subscripts 1 and 2 denote the SPP contributions originating from 107 the left and right groove, respectively; β1,2 accounts for the effective efficiency of SPP excitation via diffractive scattering by each groove, and φ1,2 is the total phase shift of the SPP including a complex phase accounting for propagation and absorption in the metal and dielectric material, and a scattering phase accrued by the SPP upon excitation by each groove, given by: 2π φ1,2 = p1,2 (nspp ∓ nd sinθ) + φG1,2 (5.2) λ where λ is the free-space wavelength of the incident beam, p1,2 is the groove-slit distance, θ is the angle between the incident light beam and the normal to the sample surface (θ = 0 in this paper), nSP P is the complex refractive index of the SPP given by nspp = [m d /(m + d )],20 where m is the complex dielectric constant of the metal and d is the complex dielectric constant of the material above the metal, nd is the refractive index of the dielectric material, and φ1,2 is an additional phase shift due to the initial scattering by the groove. Clearly, the SPP propagative phase is affected by several tunable parameters, such as the incident wavelength (λ), the distance between the slit and the grooves (p1,2 ), and the refractive index of the dielectric material, nd = d 1/2. If the two grooves are identical and the dielectric material on top of each is the same, then the SPP excitation efficiencies and scattering phases at each groove are the same, i.e. β = β1 = β2 and φ = φ1 = φ2 . The transmitted intensity through the slit (normalized to the light intensity transmitted through an isolated slit) then becomes: IT =| 1 + β{ei[p1(kspp−k sin θ)+φG ] + ei[p2 (kspp +k sin θ)+φG ] } |2 (5.3) IS where kspp = 2πnspp /λ and k = 2πnd /λ. As a result of the interference process between the SPP waves and the incident beam, the light intensity transmitted through the slit can be either enhanced or suppressed, depending on whether constructive or destructive interference occurs. In comparison, light transmitted through the slit of a plasmonic interferometer consisting of only one groove-slit pair will be the result of a two-beam interference (SPPs from the two grooves plus the incident beam), which 108 Figure 5.4: Simulated normalized per-slit transmitted intensity spectra for a two-arm plasmonic interferometer with two grooves at distances of p1 = 0.57 µm and p2 = 9.75 µm from the slit (black line), and a one-arm plasmonic interferometer with one groove p = 0.57 µm (red line). would result in reduced beatings and constructive/destructive interference effects. Figure 5.4 shows simulated light intensity transmitted through the slit of a groove- slit-groove (black line) and a groove-slit (red line) plasmonic interferometer on a Ag/water interface. These two plasmonic interferometers share a constant groove- slit distance equal to 0.57 µm, which causes the envelope profile (red line) in their normalized transmission spectra. The GSG plasmonic interferometer has a greater number and sharper maxima and minima due to the three-beam interference (i.e. incident beam and two counter-propagating SPPs interfering at the slit location) caused by the addition of an extra groove that defines a second arm in the plasmonic interferometer. The GSG plasmonic interferometers clearly show better sensitivity with smaller full width half maxima (FWHM) when compared to GS devices and were chosen accordingly for the sensing experiments. To verify our model, the plasmonic interferometers were illuminated using a col- 109 limated, broadband light source normally incident upon the sample surface. Figure 5.5(a) shows representative spectra of light intensity transmitted through an isolated nano-slit (red line) and through the nano-slit of a GSG plasmonic interferometer with arm lengths p1 = 0.57 µm and p2 = 1.85 µm (black line). By dividing the light inten- sity transmitted through the slit of the GSG plasmonic interferometer (Fig. 5.5(a), black line) by that of an identical isolated slit used as a reference (Fig. 5.5(a), red line), a normalized per-slit transmitted intensity spectrum can be obtained, as reported in Fig. 5.5(b) (solid line). Compared to an isolated slit, the light intensity transmit- ted through any given GSG plasmonic interferometer can be enhanced or suppressed depending upon the incident wavelength. The observed intensity modulation in the normalized transmission spectrum for a GSG device results from interference (at the slit location) between the two counter-propagating SPPs originating from in-plane diffractive scattering of light at the two grooves, and the incident beam. The slit in between the two grooves effectively acts as a spatial mixer of the three field ampli- tudes (incidence beam plus the two SPP waves generated by diffractive scattering). The light intensity transmitted through the slit contains information of the relative phase difference and amplitude of the different beams. Figure 5.5(b) also reports the simulated normalized per-slit transmission through the slit of the GSG plasmonic interferometer (dashed line) using the model developed above. The agreement be- tween experimental and simulated normalized per-slit transmission spectra verifies our hypothesis that transmission maxima and minima are the result of constructive or destructive interference between SPPs and incident beam at the slit location for various wavelengths. The results in Fig. 5.5(b) also demonstrate that SPPs can be efficiently generated at multiple wavelengths simultaneously by using a single groove to scatter the incident beam, using the same angle of incidence (normal to the sam- ple surface in this case). This is a novel capability not possible in previous SPR techniques based on prism- and grating-coupling approaches where SPP can only be generated at a specific wavelength and/or angle of incidence (which depends upon the incident wavelength).28−42 Figure 5.6 shows a simulated color map of normalized per-slit light intensity trans- 110 Figure 5.5: (a) Spectra of light intensity transmitted through an isolated slit (red line) and through the slit of a GSG plasmonic interferometer with p1 =0.57 µm and p2 =1.85 µm (black line) on a silver/air interface. (b) Normalized per-slit transmission spectrum for the same GSG plasmonic interferometer. 111 mitted through the slit of a series of plasmonic interferometers in air, at a given p1 = 0.57 µm and varying p2 = 0.25 – 2.0 µm (in steps of 25 nm), as a function of wavelength (400 – 800 nm). To construct this color map, normalized transmission spectra or wavelength profiles (vertical grey box in Fig. 5.6) for plasmonic interfer- ometers with varying p1 and p2 were stacked according to increasing p2. The color of each point in the map corresponds to the simulated normalized transmitted intensity, i.e. IT (p1 , p2 , λ)/IS , for a plasmonic interferometer with a specific combination of slit-groove separation distances (p1, p2 ) and wavelength (λ). The color bar reported in Fig. 5.6 shows the scale for normalized transmitted intensity, with 1 represent- ing the intensity transmitted through an isolated reference slit. From this map, a horizontal cut (for example at 600 nm, as indicated by the horizontal grey box in Fig. 5.6) can reveal an intensity profile as a function of arm-length p2 , for a given incident wavelength. According to Eq. 5.3, the difference between intensity maxima and minima can be shown to be proportional to the SPP excitation efficiency from the groove. Therefore, such horizontal cuts in the experimental color maps are useful in determining the SPP excitation efficiency at various wavelengths. A similar color map of experimental transmission spectra for GS devices normalized to single slit is shown in Fig. 5.7 as a function of wavelength, λ and groove-slit distance, p. In order to further validate this model, additional plasmonic interferometers were fabricated and the experimental (Fig. 5.8(a)–(f)) and simulated (Fig. 5.8(g)–(l)) color maps were compared (Ag/air interface). It is worth noting that Fig. 5.8(h) and 5.6 represent the same intensity map. The excellent agreement between experiment and simulation strongly supports the SPP interference model, thus providing for full control and tunability of the light transmission as a function of any of the three parameters: p1 , p2 and λ. In addition, a fit of the experimental data using the SPP interference model allows the determination of the effective SPP excitation efficiency (β) as a function of wavelength. This parameter, β can be obtained using a simpler interference model that reflects a GS device. The interference effect between the incident beam and the surface plasmon polaritons (SPPs) generated by the groove in a groove-slit plasmonic interferometer simplifies Eq. 5.3 to give the following 112 Figure 5.6: Simulated 2D color map of normalized light intensity transmitted through the slits of several plasmonic interferometers with p1 = 0.57 µm, as a function of groove-slit arm length p2 (horizontal axis) and wavelength λ (vertical axis). Also reported are typical plots obtained by horizontal or vertical cuts across the color map (indicated by grey boxes). 113 Figure 5.7: 2D experimental color map of normalized to single-slit light intensity transmitted through the slits of several groove-slit plasmonic interferometers, as a function of groove-slit distance p and wavelength λ (Ag/air interface). 114 Figure 5.8: Color maps showing experimental (a)–(f) and simulated (g)–(l) normal- ized transmission spectra (wavelength in vertical axis) for GSG plasmonic interfer- ometers with fixed p1 (400, 570, 740, 890, 1090, 1670 nm) and varying p2 (250 – 2000 nm, in steps of 25 nm). 115 expression for the normalized transmitted intensity: IT =| 1 + βeiφ |2 (5.4) I0 where β is the SPP excitation efficiency for the groove (defined as the ratio between the in-plane scattered SPP field amplitude and the incident field), which is related to the geometry of the groove (such as depth and width); φ is the phase shift of the SPP, dependent on the free-space wavelength, angle of incidence, groove-slit distance, scattering phase, and material properties (dielectric constants), all of which are known parameters. By taking a horizontal cut in Fig. 5.7 at a certain wavelength, the normalized transmitted intensity as a function of groove-slit distance can be obtained. Upon fitting the transmitted data, the effective excitation efficiency β at that specific wavelength is determined and represented by a single black dot in Fig. 5.9. By fitting the β values determined at wavelengths increasing in steps of 25 nm with the least- square method, the relationship between effective excitation efficiency and wavelength is obtained as: β = 128.2/λ, with λ in nm, which has not been previously reported in literature. In particular, β is ∼0.3 at 460 nm and it decreases to ∼0.15 at 760 nm. In principle, this technique described can be employed to determine β at any wavelength, for any groove width, depth and length, or metal/dielectric combination. Additional color maps of transmitted intensity normalized to single slit for Ag/air and Ag/water interfaces were simulated for GS devices and GSG devices with p2 extending to 10 µm, using the well-know dielectric constant for silver and water (Figs. 5.10, 5.11 and 5.12). Since the phase and amplitude of an SPP wave can be affected by any chemical analytes encountered along its optical path due to an induced refractive index change, useful information about the kind and quantity of the analytes can be retrieved from the interference process. In other words, by measuring the far-field light intensity transmitted through the slit as a function of wavelength and monitoring the change caused by the presence of analytes in the near field, it is possible to estimate the amount and identity of the adsorbed chemical species. 116 Figure 5.9: Wavelength dependence of the excitation efficiency β for SPPs generated by diffractive scattering by a 200-nm-wide groove milled in Ag with air as the dielec- tric medium. Data points were determined from the experiments of the groove-slit plasmonic interferometer with varying p (black dots). The red line is a fit of the experimentally determined data based on a least-square fitting method. 117 Figure 5.10: Simulated color maps showing normalized per-slit transmission spectra (wavelength in vertical axis) for groove-slit-groove plasmonic interferometers with fixed p1 (400, 570, 740, 890, 1090, 1670 nm) and varying p2 (250 – 2000 nm, in steps of 25 nm), using white light illumination incident upon a Ag/air interface ((a)– (f)) and a Ag/water interface ((g)–(l)). The dielectric constant of water at various wavelengths was used to calculate (g)–(l). It is interesting to note that the increased refractive index of water determines the appearance of more peaks (compared to air) in the color maps for the very same devices. 118 Figure 5.11: Color maps showing a comparison between experimental and simulated transmission spectra (normalized to single slit) for groove-slit-groove plasmonic in- terferometers with varying p2 (between 8.00 – 9.70 µm) for Ag/air and Ag/water interfaces. 119 Figure 5.12: Color map shows simulated normalized transmission spectra (wavelength in vertical axis) for groove-slit-groove plasmonic interferometers with fixed p1 = 0.57 µm and varying p2 (0.25 – 10 µm, in steps of 25 nm), for a Ag/water interface. With larger p2 , there are more peaks and valleys in the spectra (vertical cuts), even for plas- monic interferometer arms as long as 10 µm, which suggests that longer plasmonic interferometers have higher sensitivity. Due to absorption losses in the metal, the am- plitude of the SPPs generated by longer plasmonic interferometers is attenuated, and as a result the constructive and destructive interference effects are less pronounced. This explains the lower values of per-slit normalized transmission maxima observed at p2 = 10 µm. 120 5.4.2 Detection of glucose using plasmonic interferometry. To illustrate the feasibility of our sensing scheme, thousands of plasmonic interfer- ometers were patterned onto a single biochip equipped with a polydimethylsilox- ane (PDMS) microchannel. Various concentration of glucose solutions in water were flowed into and out of the microfluidic channel at a constant rate of 150 µL/min using two micro-syringe pumps, and the transmitted light intensity was monitored for each plasmonic interferometer. The continuous flow together with the extremely low power density allowed the temperature of the device to be held constant through- out the sensing experiment. Glucose was chosen as a model analyte for our sensing experiments given that over 346 million people worldwide are affected by diabetes mellitus,51 a chronic metabolic disorder that results from excessive glucose levels in the bloodstream generally due to insulin deficiency. Complications of diabetes include an increased risk of cardiovascular disease, chronic renal failure or retinal damage, all of which can be reduced by frequent monitoring and controlling of blood glucose levels. It would be ideal to find alternative methods able to sense even lower glucose concentrations, potentially allowing the use of saliva for non-invasive glucose sensing and real-time monitoring. Figure 5.13 shows the experimental (solid lines) and simulated (dashed lines) nor- malized transmitted intensity spectra for two plasmonic interferometers with constant p1 = 0.57 µm and different p2 lengths: 1.85 µm (black lines) and 5.70 µm (red lines). From this figure, a greater number of intensity maxima and minima can be observed by increasing p2 , resulting in more wavelengths at which constructive and destructive interference occurs. The increase in the number of peaks (and valleys) for plasmonic interferometers with longer p2 is clearly demonstrated in the color map provided in Fig. 5.12. These results suggest that the device sensitivity can be improved at various wavelengths by simply increasing the groove-slit separation distance. This distance is only limited by the ohmic and scattering losses of SPPs, which in general reduce the SPP propagation length (Fig. 1.13), and by the spatial and temporal degree of coher- ence between the SPPs and the incident beam, needed to determine the interference 121 Figure 5.13: Normalized per-slit transmitted intensity spectra for two GSG plasmonic interferometers with one arm length held constant at p1 = 0.57 µm and the other arm length held at p2 = 1.85 µm (black solid line) and 5.70 µm (red solid line), respectively. Dashed lines represent simulated spectra for each of the two devices: p2 = 1.85 µm (black dashed line) and p2 = 5.70 µm (red dashed line). effect. Based on results shown in Fig. 5.13, the device with p1 = 0.57 µm and p2 = 5.70 µm was chosen to perform the glucose sensing experiment. Figure 5.14(a) illustrates the normalized per-slit transmitted intensity spectra of this device, measured as a function of wavelength for increasing concentrations of an aqueous glucose solution. A wavelength shift (∆λ) is observed at all incident wavelengths. Increasing glucose concentration enhances the refractive index of water (the dielectric material), and results in a red-shifted interference spectrum. In contrast to existing approaches that use a single excitation (resonant) wavelength, plasmonic interferometers operate over a broad spectral range, enabling spectroscopic detection of the refractive index of chemical analytes as a function of wavelength. Thus, plasmonic interferometers allow for fingerprinting of any biochemical analytes, without resorting to labeling or surface functionalization with specific linkers. By correlating the wavelength shift with a known concentration, a calibration curve can be generated for each device, and 122 at various wavelengths simultaneously. Figure 5.14(b) shows the relative intensity change (∆I/I0) for the same device as in Fig. 5.14(a), described by Eq. 5.5: ∆I (Iglucose − Iwater ) = × 100% (5.5) I0 Iwater where Iglucose is the transmitted light intensity through the slit of a plasmonic interfer- ometer at a specific glucose concentration, and I0 = Iwater is the reference transmitted intensity through the slit of the same interferometer in pure water (i.e. zero glucose concentration). It is interesting to observe that some wavelengths do not show any significant change in transmitted light intensity, forming nodes that are characteris- tic of a specific interferometer. For this particular plasmonic interferometer with p1 = 0.57 µm and p2 = 5.70 µm), the maximum relative intensity change is achieved at an incident wavelength of 610 nm, with measured values up to 40 %. In sum- mary, by monitoring the ∆λ and ∆I/I0 at all wavelengths, glucose sensing over broad wavelength and concentration ranges is feasible. In Fig. 5.15, the performance of the same device was analyzed by plotting the experimental and simulated values for ∆λ and ∆I/I0 as a function of glucose con- centration. The experimental (symbols) and simulated (solid line) ∆λ at a center wavelength of 610 nm and ∆I/I0 at 590 nm (red line and circles) and at 610 nm (black line and squares) are reported in Figs. 5.15 (a) and (b), respectively. The sim- ulated curves are in excellent agreement with the experimental data. ∆λ and ∆I/I0 show significant variation as a function of glucose concentration, and can therefore be used to infer the concentration of glucose in solution. Furthermore, as shown in Fig. 5.14(b), it is evident that at close but different wavelengths, the device response can be remarkably different, with higher sensitivity observed at 610 nm. Figure 5.17 shows a sensing performance comparison at 590 nm for four devices, three of which have a constant p1 = 0.57 µm and varying p2 = 1.85, 5.70, 9.75 µm, and the fourth with p1 = 5.70 µm and p2 = 9.75 µm. Panels (a) and (c) in Fig. 5.17 describe the wavelength shift while panels (b) and (d) report the relative intensity change as a function of glucose concentrations, spanning five orders of magnitude, 123 Figure 5.14: (a) Normalized per-slit transmitted intensity spectra of a GSG device with p1 = 0.57 µm and p2 = 5.70 µm measured at various concentrations of glucose in water. (b) Relative intensity change as a function of wavelength (normalized to pure water) for the same device, at various concentrations of glucose in water. 124 Figure 5.15: Calibration curves for a plasmonic interferometer with p1 = 0.57 µm and p2 = 5.70 µm, used as a glucose sensor. (a) Measured (black solid squares) and simulated (black line) wavelength shifts as a function of glucose concentration at 610 nm. (b) Measured (symbols) and simulated (lines) relative intensity change as a function of glucose concentration measured at 590 nm (red circles and red line) and 610 nm (black squares and black line). The error bars are within the symbols. 125 Figure 5.16: Refractive index as a function of glucose concentration (ρ), at a wave- length of 589 nm, 20 ◦C. which correspond to a total refractive index change of only ∆n = 0.02. The grey boxes in Fig. 5.17(b) highlight the physiological concentration ranges of glucose in saliva (lighter grey area) and serum (darker grey area), respectively. Typical physiological concentrations range between 0.36 – 4.3 mg/dL in saliva and 50 – 144 mg/dL in serum.52 The inset to Fig. 5.16(a) shows representative relative intensity change spectra for a device with p1 = 0.57 µm and p2 = 9.75 µm measured at four glucose concentrations. By monitoring the changes in the experimental spectra taken at different glucose concentrations, scattered data of ∆λ and ∆I/I0 can be obtained, as plotted in Fig. 5.17 for a wavelength of 590 nm. Comparing panels (a) and (b), it is observed that at low glucose concentrations (0.1 – 500 mg/dL), ∆λ does not show a significant change, while ∆I/I0 is a more reliable parameter for detection of glucose. At higher glucose concentrations (500 – 14,000 mg/dL) both ∆λ and ∆I/I0 can be used to detect the presence of glucose and quantify its concentration. The dashed lines are calibration curves obtained by least-square fittings of the scattered experimental data points. Clearly, the proposed plasmonic interferometers are able to sense the lowest glucose concentrations typically found in saliva. At all concentrations, ∆I/I0 seems to outperforms ∆λ. 126 In order to better quantify the device sensitivity, figures of merit can be calculated as the slopes of the calibration lines obtained by fitting ∆λ and ∆I/I0 data as a function of concentration. At a specific glucose concentration (ρ), the refractive index of the solution can be calculated by the second order polynomial described in Eq. 5.6:53 n = 1.333000 + 1.42382 × 10−6 ρ − 5.19903 × 10−13 ρ (5.6) Figure 5.16 illustrates the refractive index as a function of glucose concentration, ρ in units of mg/dL, at a wavelength of 589 nm at 20 ◦C. The index of pure water is 1.3330 at 20 ◦ C, and the data was fitted with Eq. 5.6. By dividing the wavelength shift ∆λ by the difference in the refractive index (∆n) between two glucose solutions, we can define a figure of merit relative to the wavelength shift (FOMλ) at each given concentration, i.e.: ∆λ F OMλ = lim (5.7) ∆n→0 ∆n Similarly, dividing the difference in the relative intensity change ∆I/I0 by ∆n, the figure of merit relative to the intensity change (FOMI ) can be derived, at each con- centration: ∆ II0 F OMλ = lim (5.8) ∆n→0 ∆n The device with p1 = 0.57 µm and p2 = 9.75 µm (green triangles) shows a FOMI of ∼166,000 %/RIU in the glucose concentration range typically found in saliva (0.2 – 8 mg/dL) and ∼10,000 %/RIU in the concentration range typically found in blood serum (40 – 400 mg/dL). For the device with longer p1 = 5.70 µm (orange circles), the measured FOMI is even higher, reaching ∼884,000 %/RIU and ∼17,000 %/RIU in the glucose concentration ranges for saliva and serum, respectively. This device is able to detect a refractive index change as low as 3 × 10−7 RIU. Experimentally, the relative intensity change is found to be a better figure of merit for detection of low 127 glucose concentrations. The data suggest that at the lowest glucose concentrations, adsorption of glucose molecules directly onto the metal surface of the plasmonic inter- ferometer determines an increased glucose concentration right at the device surface and higher FOMI than those simulated using a uniform glucose concentration in so- lution. Functionalization of the sample surface with linkers specific to glucose can further increase the device sensitivity and specificity. At higher glucose concentra- tions (500 – 14000 mg/dL), FOMλ is between 370 – 630 nm/RIU for the three devices (Fig. 5.17(c)). The device with p1 = 0.57 µm and p2 = 9.75 µm, shows a decrease in FOMI from ∼16,000 %/RIU (Fig. 5.17(b)) to ∼1,000 %/RIU (Fig. 5.17(d)), in agreement with the trend observed in the simulations, showing that plasmonic interferometers optimized for detection of low refractive index changes are indeed characterized by higher figures of merit at lower glucose concentrations (Figs. 5.18, 5.19 and 5.20). The measured figures of merit are at least one order of magnitude greater than those reported in recently published papers,54−60 opening up the possi- bility to use plasmonic interferometers for detection of low concentrations of clinically relevant molecules. Moreover, the typical sensing volume of a plasmonic interferome- ter is only 20 fL, which corresponds to a sensed mass of 0.02 fg or ∼67,000 molecules (see Section 1.4.1 for calculation of sensing volume). If desired, sensing specificity can be achieved for multiple analytes by functionalizing the surface with antibodies that have high affinity to specific analytes. 5.5 Conclusion In conclusion, we reported the design, fabrication and characterization of a novel plasmonic sensor consisting of a nano-slit flanked by two nano-grooves with varying separation distances to define compact two-arm, three-beam interferometers. Light intensity transmitted through the slit carries information about the refractive index change determined by the analyte in the near field, as sampled by two multi-frequency counter-propagating SPPs interfering with the incident beam at the slit location. A theoretical model was developed to predict the optical response and sensitivities of 128 Figure 5.17: Performance comparison at 590 nm for four GSG plasmonic interferom- eters. Three of them have one arm length p1 , = 0.57 µm and different p2 : p2 = 1.85 µm (black squares), p2 = 5.70 µm (red rhombi) and p2 = 9.75 µm (green triangles). The fourth plasmonic interferometer has p1 = 5.70 µm and p2 = 9.75 µm (orange circles). The inset in (a) shows relative intensity change spectra as a function of wavelength for four different glucose concentrations: 10, 200, 4000 and 14000 mg/dL, where the wavelength shift and intensity change are clearly visible. The dashed lines are calibration curves obtained by least-square fittings of the scattered data points. (a) Wavelength shift versus glucose concentration for two devices with constant p2 = 9.75 µm and different p1 of 0.57 µm and 5.70 µm. (b) Relative intensity change versus glucose concentration for these two devices. (c) Wavelength shift versus glu- cose concentration for three devices with constant p1 = 0.57 µm and different p2 = 1.85, 5.70 and 9.75 µm. (d) Relative intensity change versus glucose concentration for these three devices. The error bars for relative intensity change are within the symbols. The grey boxes highlight the physiological range of glucose in saliva (light grey) and in serum (dark grey), respectively. 129 Figure 5.18: Color map reporting the simulated figure of merit (FOMI ) as a function of glucose concentration and groove-slit distance p2 , for a fixed wavelength λ = 590 nm and groove-slit distance p1 = 0.57 µm. Plasmonic interferometers with longer p2 have a higher FOMI . However, for a given device, the FOMI decreases at higher concentrations, as experimentally observed. 130 Figure 5.19: Color maps of simulated FOMI as a function of groove-slit distances p1 and p2 , for various glucose concentrations: 0.1, 5000, 14,300 mg/dL. 131 Figure 5.20: Plots of simulated FOMI versus glucose concentration for three different devices, at a fixed wavelength (λ = 590 nm). The plots show the complex non-linear functional dependence of FOMI . In particular, the blue line reports on the FOMI of a device that shows no significant change in transmitted intensity up to a concentration of 200 mg/dL. This evidences the importance of careful choice of p1 , p2 and λ for the optimization of device sensitivity in the concentration range of interest. 132 plasmonic interferometers with varying arm lengths and wavelength. This model was validated experimentally and it allows extraction of useful physical parameters, such as the SPP excitation efficiency by diffractive scattering from a groove, and the refrac- tive index of the dielectric material through which the SPPs propagate. To illustrate the potential of plasmonic interferometers for biochemical sensing, a proof-of-concept sensor chip was fabricated, consisting of thousands of plasmonic interferometers per square millimeter to detect glucose concentrations in aqueous solutions. The best sensor was able to detect glucose over a wide concentration range from 0.1 – 14,000 mg/dL, using a sensing volume of only 20 fL, covering a refractive index change of 0.02. Wavelength sensitivities from ∼ 370 – 630 nm/RIU and relative intensity changes from ∼103 – ∼106 %/RIU were experimentally demonstrated, with a res- olution of ∼3 × 10−7 RIU. These results show that plasmonic interferometry is a promising approach for the development of high-throughput, extremely compact bio- chemical sensors amenable to large scale integration on-chip, and able to provide (for example) a non-invasive technique for measuring glucose using saliva, where typical concentrations are between 0.36 – 4.0 mg/dL, a range amply covered by plasmonic interferometers. 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In this chapter, the synergistic advantage of combining plasmonic interferometry with an enzyme- driven dye assay yields an optical sensor capable of detecting glucose in saliva with high sensitivity and selectivity. The sensor, coined a plasmonic cuvette, is built around a groove-slit-groove (GSG) plasmonic interferometer coupled to the Amplex Red/Glucose Oxidase/Glucose (AR/GOx/Glucose) assay. This device is both highly sensitive, with a measured intensity change of 1.7 × 105 % / M (i.e. one order of magnitude more sensitive than without assay) and selective for glucose in picoliter samples, across the physiological range of glucose found in human saliva (20 – 240 µM). Since GSG plasmonic interferometry enables spectroscopic fingerprinting of a sample and the AR/GOx/Glucose assay is selective for glucose, the detection of glu- cose is possible within a complex mixture of proteins, small molecules, and salts 139 140 typically found in samples of saliva or serum. To make the device feasible for real- time glucose monitoring in saliva, the underlying reactions of the assay were studied in detail and fitted using a rate equation model. The effective rate constants were determined and used to tune the reaction time and expand the detection range of the assay. The results reported suggest that by varying the dye assay used, a plas- monic cuvette provides a general, real-time approach to sensing low concentrations of a selective molecular target within a very small volume of biological fluid. 6.2 Introduction Diabetes mellitus is a chronic metabolic disorder that affects over 347 million people worldwide.1 Although there are many causes for diabetes, the primary symptom of this disease is excessive glucose levels in the blood. The long-term complications asso- ciated with diabetes include cardiovascular disease, chronic renal failure, and diabetic retinopathy, all of which can be reduced significantly by controlling blood glucose lev- els using a blood glucose meter (BGM). Traditional BGMs employ bio-electrochemical schemes that use glucose oxidase (GOx) or glucose dehydrogenase (GDH) immobilized on the surface of a disposable electrode.2 These monitoring schemes are non-toxic and have high selectivity; however, the detection limit of commercial BGMs is ∼2.8 mM (50 mg/dL),3 which prevents their use in fluids such as tears or saliva (i.e., do not require invasive extraction) and are characterized by glucose concentrations that are typically 50 – 100× lower than what is found in blood. Over the past decade, extensive research has focused on optical, rather than elec- trochemical methods, with the goal of reducing the limit of detection and achiev- ing non-invasive sensing.4−12 Optical non-invasive detection schemes assume a direct correlation between the glucose levels found in blood and other bodily fluids; this correlation is well established for interstitial fluids13 and saliva.14,15 Saliva is a partic- ularly attractive candidate for non-invasive glucose sensing since it is almost always present and easy to acquire (unlike tears). These optical biosensors can be further im- proved by employing metal nanoparticles or planar metal films with nano-corrugations 141 in order to favorably manipulate the light.16−21 Example techniques include surface plasmon resonance (SPR),22,23 grating couplers,24 and plasmonic interferometers.25,26 In all these techniques, incident light is coupled to surface plasmon polaritons (SPPs) which are electromagnetic waves supported by electron density fluctuations in no- ble metals (e.g., silver and gold).27 SPPs are generated from localized sources (e.g. grooves) and propagate outward to interfere with each other and produce local field intensity minima and maxima. SPPs are highly sensitive to changes in the refrac- tive index of the dielectric material, a property useful in developing ultra-sensitive, compact and real-time biosensors. In this chapter, we demonstrate a plasmonic cuvette obtained by coupling a groove-slit-groove (GSG) plasmonic interferometer to an Amplex Red/Glucose Oxi- dase/Glucose (AR/GOx/Glucose) dye assay that adds selectivity for glucose detec- tion, and further enhances its sensitivity by one order of magnitude. The resulting sensor offers real-time sensitivity toward glucose in extremely small sensing volumes (i.e., ≤ 12 pL), and exhibits glucose selectivity in complex mixtures such as a 50 mM sodium phosphate buffer solution and artificial saliva over the physiological range of glucose concentration in saliva (20 – 240 µM).28 These results demonstrate the via- bility of measuring the concentration of glucose in saliva, which is a complex mixture of proteins, salts, and urea.29 The plasmonic cuvette offers several advantages over a traditional UV-Visible (UV-Vis) cuvette. First, the sensed volume in a plasmonic cuvette is 12 pL (compared to ≤ 240 µL for the UV-Vis cuvette); this advantage reduces the amount of sample and reagents required by seven orders of magnitude. Second, the plasmonic cuvette can be integrated with a microfluidic channel to achieve more uniform mixing than what is normally possible in a UV-Vis cuvette. Third, the plasmonic cuvette has a very short effective path length (< 20 µm) compared to a UV-Vis cuvette. This shorter path length allows the response of the system to remain linear over a wider range of concentrations and avoids the necessity to either dilute the solution or reduce the path length of the UV-Vis cuvette at higher analyte concentrations. We also report a detailed study of the enzyme kinetics involved in the AR/GOx/Glucose 142 assay: the effective rate constants are found and used to tune the reaction time and range of applicability of the assay to cover the physiological range of glucose in saliva. Figure 6.1(a) provides an overview of the assay reactions with details of each en- zymatic reaction shown in Figs. 6.1(b) through 6.1(d). Reaction 1 (Fig. 6.1(b)) describes the oxidation of β-D-glucose to D-gluconolactone by oxygen catalyzed by GOx to yield H2O2 as a product.30 The H2O2 generated in Reaction 1 is utilized by horseradish peroxidase (HRP) to oxidize Amplex Red (AR), a colorless, non- fluorescent compound, to resorufin, a red, fluorescent compound (Reaction 2, Fig. 6.1(c)).31−33 Reaction 3 (Fig. 6.1(d)) is a much slower, H2O2 -limited side reaction that further oxidizes resorufin into an optically inactive product (OIP), thought to be a complex polymer.30,33,34 Reactions 1 and 2 are commonly used to detect glucose in a wide variety of applications, such as determining glucose consumption by cancerous cells to better understand tumorigenesis,35 or quantifying starch and glucose concen- trations in food.36 In these applications, the fluorescence properties of resorufin are preferred because of the high signal-to-noise ratio (Fig. 6.1(e)). By contrast, this work employs the absorption properties of resorufin in order to evaluate the optical transmission response of the plasmonic cuvette (Fig. 6.1(f)). The foundation of the plasmonic cuvette, a GSG plasmonic interferometer, is shown in Fig. 6.1(g). When light of wavelength λ is incident upon a groove, an SPP mode is generated and prop- agates through the sample solution toward the center slit, which is a distance p away from the groove (also known as the arm length). The counter propagating SPP waves from the two grooves interfere constructively or destructively at the slit depending on p, λ, and the refractive index of the dielectric resting on top of the metal (n). The output spectrum will be a convolution of the incident light and the net SPP field - changes in the intensity or shifts in the wavelength of the output spectrum provide information about the concentration and types of analytes present (Fig. 6.1(h)). 143 Figure 6.1: Overview of the plasmonic cuvette: plasmonic interferometry coupled to dye chemistry. (a) The Amplex Red/Glucose Oxidase/Glucose assay consumes glucose and produces resorufin in a 1:1 stoichiometric ratio via enzymatic reactions; (b) reaction 1 is the oxidation of β-D-glucose to D-gluconolactone by O2 to produce H2O2 , catalyzed by GOx; (c) reaction 2 is the oxidation Amplex Red (colorless) into resorufin (red), catalyzed by HRP; (D) reaction 3 is a side reaction with low yield that further oxidizes resorufin to an optically inactive product; (e) the effective rate constants for the three reactions (K1 , K2 and K3) were determined by time- dependent kinetic studies of resorufin absorption using a UV-Vis cuvette; (f) the absorption cross-section (σ) and extinction coefficient () of resorufin as a function of wavelength; (g) schematic of the plasmonic cuvette; (h) sample data from the plasmonic cuvette: spectral absorption is correlated with resorufin concentration. 144 6.3 Experimental Section 6.3.1 Reagents 10-Acetyl-3,7-dihydroxyphenoxazine (Amplex Red, or AR) and 7-Hydroxy-3H-phenoxazin- 3-one sodium salt (resorufin sodium salt) were purchased from Invitrogen (Carls- bad, CA). A stock solution of 19.5 mM AR and 4.5 mM resorufin sodium salt was prepared in anhydrous dimethylsulfoxide (DMSO), aliquoted and stored at –20 ◦C. Horseradish peroxidase (HRP) from Armoracia rusticana (253 purpurogallin U/mg, P-8375, EC1.11.1.7), glucose oxidase (GOx) from Aspergillus niger (100 kU/mg, G7141, EC1.1.3.4), D-(+)-Glucose and urea were purchased from Sigma (St. Louis, MO). Stock concentrations of HRP (10 U/mL) and GOx (1 U/mL) were deter- mined spectrophotometrically using molar extinction coefficients 403nm = 102,000 M−1 cm−1,37 and 280nm = 267,200 M−1 cm−1 ,38 respectively (Figs. 6.2(a) – 6.2(b)). A stock solution of 0.5 mM D-(+)-Glucose was prepared and subsequently allowed to stand for 1 h to complete the mutarotation reaction. The concentration of hydrogen peroxide (35% w/w H2O2 from Acros Organics) was determined spectrophotometri- cally at λ = 240 nm using a molar extinction coefficient of 240nm = 43.6 M−1 cm−1 (Fig. 6.2(c)).39 Initial reaction mixtures of the AR/GOx/Glucose assay were pre- pared at ambient temperature and consisted of 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 82.5 ± 0.7 nM GOx dissolved in a 50 mM sodium phosphate buffer solution (pH 7.4) unless otherwise stated. The enzyme stock solutions were thawed and diluted immediately prior to measurement. 6.3.2 Fabrication and optical characterization of plasmonic interferometers An array of groove-slit-groove (GSG) plasmonic interferometers with arm lengths p1 = 7.00 µm and p2 = 9.75 µm (as well as single slit devices for normalization purposes) were fabricated on a 300-nm-thick Ag film deposited on top of a 1” by 1” quartz slide using focused ion beam (FIB) milling. A 5-nm-thick, optically transparent 145 Figure 6.2: Spectral absorbance of stock concentrations for the commonly used reagents in this study: (a) glucose oxidase (GOx), (b) horseradish peroxidase (HRP) and (c) hydrogen peroxide (H2O2 ). The values for the extinction coefficient come from the literature;38−40 this is used in conjunction with the Beer-Lambert law to find the concentration (reported in each panel). In panels (a) and (b), the extinc- tion coefficient is reported at the wavelength corresponding to maximum absorption. Glucose oxidase is stable for at least 24 h at room temperature; both GOx and HRP are stable at 4 ◦C for at least two weeks. 146 layer of Al2O3 was deposited on top of the milled films using atomic layer deposition to prevent the silver from oxidizing. This layer of Al2O3 made the surface more hydrophilic compared to plain Ag as demonstrated by a 20◦ difference in contact angle measurements (Fig. 6.3(c)). The re-usability of the chip was demonstrated by measuring the spectral transmitted intensity response of water before and after exposure to the AR/GOx/Glucose assay. The similarities in both the peak intensity and position of the before (black line) and after (red line) exposure of the surface to the assay supports the re-usability of the chip (Fig. 6.3(d)). A collimated beam of white light (λ = 400 – 800 nm) illuminates the plasmonic interferometer at normal incidence. A 40× objective lens (numerical aperture = 0.6) was used to collect the transmitted light, which is then dispersed by a single-grating spectrograph and detected by a charge-coupled device (CCD) camera. The spectral resolution of the optical setup was ∼0.4 nm; the number of counts at each wavelength and number of acquired spectra per experiment were adjusted to ensure a statistical error < 0.1% in the measured transmitted intensity. An initial reaction mixture of the AR/GOx/Glucose assay was reacted with various concentrations of glucose (0 - 250 µM) in the dark for 50 min to allow the reaction to go to full completion. The reacted solution was then delivered to the plasmonic interferometer via a polydimethylsiloxane (PDMS) microfluidic channel (2-cm long × 1-cm wide × 70-µm high) using a syringe pump at a flow rate of 150 µL/min. 6.3.3 Spectrophotometric kinetic measurements All spectroscopic measurements were performed with a dual-beam UV-Visible Cary 500 Spectrophotometer (Agilent Technologies, Chesterfield, MO) using a quartz cu- vette with a path length of L = 0.2 cm. The same initial reaction mixture that was used with the plasmonic interferometers was used for both the optical characterization of resorufin and kinetic experiments. For the optical characterization of resorufin, the reaction mixture was initiated with 100 µL of glucose at a concentration of 10.0 ± 0.4 µM, 25 ± 1 µM, 50 ± 2 µM or 100 ± 4 µM, reacted for 50 min in the dark; the transmittance was measured for 147 Figure 6.3: Surface re-usability test for a chip deposited with (a) 4-nm Ti followed by 300-nm Ag or (b) the same chip in part (a) with an additional 5-nm of Al2O3. Ten µL of 5 buffer solutions: (1) Buffer A: 50 mM sodium phosphate buffer (pH 7.4); (2) Buffer B: Buffer A with 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP, and 82.5 ± 0.7 nM GOx; (3) Buffer B with 5 µM D-(+)-Glucose; (4) Buffer B with 100 µM D-(+)- Glucose; (5) Buffer B with 250 µM D-(+)-Glucose; were drop-casted onto the surface of (a); allowed to sit for 30 min before thoroughly rinsed with copious amounts of water. This procedure was repeated for the same chip after Al2O3 deposition as seen in part (b). (c) Contact angle measurements were made using a goniometer with 5 µL droplet of water onto surface of (a) and (b). (d) The normalized per-slit transmitted intensity was measured in water for a GSG plasmonic interferometer coated with 5-nm of Al2O3 with p1 = 9.75 µm and p2 = 7.85 µm before and after exposure to AR/GOx/Glucose assay. 148 Figure 6.4: The amount of spontaneous oxidation of AR/GOx/Glucose assay was determined by measuring the transmittance through the cuvette of a reaction mixture containing 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 82.5 ± 0.7 nM GOx dissolved in a 50 mM sodium phosphate buffer solution (pH 7.4) without glucose every 30 min for 10 h at λ = 571.7 nm. The percentage of spontaneous oxidation was calculated by setting the complete oxidation as the transmittance measured for the same reaction mixture reacted with 250 µM glucose to 100%. incident wavelengths between 450 and 700 nm. The amount of spontaneous oxidation of AR to resorufin over a 10 h period was found to be almost negligible (Fig. 6.4). For the kinetic experiments, the reaction was initiated with the addition of various concentrations of H2O2 or glucose (both in 100 µL solutions). The reaction was monitored at the wavelength where resorufin exhibits maximum absorption (λmax = 571 nm) in 0.1- or 1-s intervals. All experiments were performed in triplicate at standard temperature (25 ◦ C) and pressure (760 mm Hg); the concentration of dissolved oxygen ([O2]) was assumed to be constant and equal to 261 µM (calculated using Henry’s law).40 All samples were illuminated with a 50 W tungsten light source; the intensity was measured with a calibrated photodiode and found to be 75 µW cm−2. 149 6.3.4 Specificity test for glucose in artificial saliva Modified Fusayama artificial saliva (MFAS) was prepared to determine the selectivity for glucose in the AR/GOx/Glucose assay. This mixture contains NaCl (6.8 mM), KCl (5.4 mM), CaCl2 ·2H2 O (5.4 mM), NaH2PO4 ·H2O (5.0 mM), KSCN (3.1 mM), Na2 S·9H2O (6.9 µM) and urea (16.7 mM) at a pH of 7.4.41 A 600-µL solution for measuring glucose concentration was prepared by mixing an initial reaction mixture of the AR/GOx/Glucose assay with 100 µL of MFAS containing 100 µM glucose. Diluting the MFAS solution by 7× increases the solubility of urea and the salts found in the mixture, while still allowing the assay reactions to occur. Control experiments used the same reaction mixture initiated with either 100 µL of the modified Fusayama artificial saliva without glucose or 100 µL of 50 mM sodium phosphate buffer with 100 µM glucose. The transmitted light intensity was measured every 1 s for 2000 s for each reaction and each condition was studied in triplicate. 6.4 Results and Discussion 6.4.1 Enhanced sensitivity of plasmonic interferometer when coupled to a dye chemistry assay Both the plasmonic and UV-Vis cuvettes rely on the same figure of merit to quantify sensitivity, which itself depends on the ability of the solution to absorb incident light. The relevant figure of merit is the relative intensity change (∆I/I0), defined as ∆I (Iglucose − Iwater ) = × 100% (6.1) I0 Iwater where Iglucose is the transmitted light intensity through the slit of the plasmonic interferometer at a non-zero glucose concentration; I 0 corresponds to the absence of glucose. Figure 6.5(a) shows the relative intensity change as a function of wavelength when the assay is present (red solid line) or absent (blue dashed line); the initial glucose concentration is [G]t=0 = 250 ± 6 µM in both cases. The AR/GOx/Glucose 150 assay produces 1 mol of resorufin for every mol of glucose consumed. Consequently, any change in light intensity corresponds directly to a change in glucose concentration - this figure clearly shows that the assay is effective in increasing the sensitivity of the device. In this device, two distinct optical processes are occurring: direct absorption of the incident light (characterized by the absorption cross-section curve in Fig. 6.1(f)) and absorption by the groove-generated surface plasmon polaritons (SPPs). In this regard, the spectrum can be divided into three distinct regions. At shorter wavelengths (450 nm < λ < 510 nm), the direct absorption of light by resorufin is low enough that the two processes can be resolved. The pronounced peaks in this region of the spectrum can be attributed to interference between counter-propagating SPP waves; the shift in peak position as well as the intensity change can be correlated to a refractive index change.26 At wavelengths between 510 nm and 590 nm, resorufin is strongly absorbing; thus, bulk absorption dominates over plasmonic interference and absorption. The presence of this peak, which closely resembles the shape of the absorption spectrum of resorufin, ensures the device is selective towards glucose and can be attributed to the high specificity of GOx to glucose in the assay. At λmax = 571 nm, the relative intensity change is at a maximum and goes from – 2.8 % (without assay) to – 41.7 % (with assay). At wavelengths above 590 nm, resorufin does not absorb light, so any relative intensity change must be due solely to changes in the SPPs propagation and interference behavior, which depends on the refractive index of the solution. This observation suggests that differences in the two spectra are a result of the enzymes and resorufin altering the refractive index of the solution. In theory, any wavelength in this spectrum could be used for detection, but the best sensitivity is achieved at λmax . Note that Fig. 6.1(h) displays the same with assay data, but over a range of glucose concentrations between 0 to 250 µM, demonstrating the expanded range of applicability provided by the coupling of dye chemistry with plasmonic interferometry. Figure 6.5(b) shows the relative intensity change as a function of glucose concen- tration with and without the assay present. When the assay is absent (blue circles), the calibration curve yields a sensitivity of 0.2 × 105 % / M: when the assay is present 151 Figure 6.5: Enhancing the sensitivity of a plasmonic interferometer with the dye assay. (a) Relative intensity change plotted as a function of wavelength for a groove- slit-groove (GSG) plasmonic interferometer with 250 ± 6 µM glucose in the presence (red solid line) or absence (blue dashed line) of the assay. Both spectra are normalized to a reaction mixture with 0 µM glucose (black solid line). (b) Calibration curves for the same GSG device used in part (a) as function of glucose concentration in the presence (red squares, λ = 571 nm) or absence (blue circles, λ = 628 nm) of the assay. 152 (red squares), a linear fit of the data yields a sensitivity of 1.7 × 105 % / M; , which corresponds to an 8.5× increase (N.B.: the sensitivity is defined as the absolute value of the slope of the linear fit). The measurements were performed on the same plas- monic interferometer, but the detection wavelengths were chosen as λ = 571 nm (with assay) and λ = 628 nm (without assay) to maximize the sensitivity of the device in each case. For comparison, the sensitivity of our previously reported GSG plasmonic interferometer - with p1 = 5.70 µm and p2 = 9.75 µm, λ = 590 nm, no assay present - yielded a sensitivity of 0.4 × 105 % / M.26 The data presented here demonstrates that not only can the assay be used with different plasmonic interferometers (i.e., different arm lengths, p) to detect glucose, but that the sensitivity and selectivity of the device is significantly enhanced by the presence of the assay. 6.4.2 Absorption properties of resorufin Since the absorption properties of resorufin (produced in the AR/GOx/Glucose assay) affect the output signal of the plasmonic interferometer, the optical properties of resorufin were measured for the purpose of using this information to optimize the performance of the plasmonic cuvette. Figure 6.6(a) shows the absorption coefficient of resorufin as a function of wavelength at various concentrations of glucose in the buffer solution. The absorption coefficient, a in units of cm−1, is a measure of how much incident light is absorbed as it propagates through the solution. The formula that describes this absorption is −loge (T ) α= (6.2) L where T is transmittance (defined as the intensity of transmitted light, IT , divided by the reference intensity, Iref ) and L is the path length of the cuvette in cm. Note that the curve peaks at λ = 571 nm, which corresponds to the maximum absorption wavelength of resorufin. Figure 6.6(b) presents the same data as Fig. 6.6(a), but the horizontal axis is plotted as density, ρ (linearly correlated to concentration, c - Appendix: Guide to nomenclature); the three curves shown correspond to three 153 different incident wavelengths. This is used to obtain the absorption cross-section (σ) of the optically active molecule (here, resorufin), which is defined as the slope of the line in Fig. 6.6(b): α σ= (6.3) ρ The absorption cross-section has units of cm2 and represents the effective cross- sectional area of a resorufin molecule when light is incident upon it. The absorption cross-section can be defined at all wavelengths by performing the linear fit (Fig. 6.6(b) shows a few example wavelengths). Although σ does not depend on the concentration of the absorbing species, it will depend on the nature and composition of the buffer solution. Shown in Fig. 6.6(c) is a plot of σ as a function of wavelength on the left vertical axis. The extinction coefficient () of resorufin is plotted on the right axis and is related to σ by loge (10)c σ= = (3.824 × 10−21 mol) (6.4) ρ where c and ρ are the molar concentration and the density of the absorbing cen- ter, respectively. The extinction coefficient is a measure of how strongly resorufin molecules absorb incident light. The incident wavelength chosen for this work was λmax 571 nm where σ 571nm = (2.05 ± 0.08) × 10−16 cm2 and 571nm = (5.4 ± 0.2) × 104 M−1 cm−1 (compared to the literature value of 571nm = (5.4 ± 0.4) × 104 M−1 cm−1).31,42 The accuracy of the 571nm value reported here confirms the validity of this method to obtain σ and  at other wavelengths. Figure 6.6(c) expands the range of applicable wavelengths for resorufin detection. This method can be generalized for deriving the absorption properties for any optically active molecule - once the absorp- tion cross-section and extinction coefficient have been found, the optimal wavelength can be selected to use with the sensor. Additionally, because every molecule has its own unique σ and  wavelength dependence and the plasmonic cuvette is capable of multiplex sensing, two or more optically active biochemical analytes that are present 154 Figure 6.6: (a) Spectra of the absorption coefficient, α, for four different concen- trations of resorufin in a 50 mM sodium phosphate buffer solution (pH 7.4) using a 0.2-cm path length cuvette. (b) Absorption coefficient as a function of the density of absorbing resorufin molecules (ρ) or the molar concentration of resorufin (c) at λ1 = 530 nm (blue circles), λ2 = 571 nm (red squares) and λ3 = 590 nm (purple triangles). This plot was obtained by taking a cross-section of the curves in panel (a) at λ1 , λ2 and λ3 . (c) The slope of a linear fit of curves in panel (b) represents the absorption cross-section of a resorufin molecule (σ) at a specified wavelength. This process was repeated for the entire range of wavelengths (450 nm < λ < 700 nm) in steps of 1 nm. 155 on the chip could be identified and the corresponding concentrations determined si- multaneously. 6.4.3 Mathematical model of AR/GOx/Glucose assay The AR/GOx/Glucose assay typically requires an incubation time of 30 min for the reactions to proceed to completion.42 The incubation time needs to be shortened significantly if the plasmonic cuvette is to be used as a real-time sensor for glucose. Efforts have been made to characterize the factors that affect the incubation time of the coupled GOx- and HRP-dependent reactions.43 A study by Nakajima et al. reduced the incubation time to 4.8 s by photochemically arranging the HRP and GOx molecules in a specific pattern inside a microfluidic PDMS channel.44 Because all the reagents are simultaneously present in solution in a plasmonic cuvette sample, the best approach is to increase the rates of the three reactions (Figs. 6.1(b) – (d), corresponding to rate constants K1, K2 , and K3, respectively). The values for these rate constants can be obtained by fitting the change in the concentration of resorufin as the reaction progresses. Using first-order kinetics, a model for the time-dependent 156 concentrations can be established with the following rate equations: d[G] = −K1 [O2 ][G] (6.5) dt d[O2 ] = 0 (6.6) dt d[H2 O2 ] = K1 [O2][G] − K2 [H2 O2 ][AR] − K3 [H2 O2 ][R] (6.7) dt d[AR] = −K2 [H2 O2 ][AR] (6.8) dt d[R] = K2 [H2O2 ][AR] − K3 [H2 O2 ][R] (6.9) dt d[OIP ] = K3 [H2O2 ][R] (6.10) dt where G is glucose, AR is Amplex Red, R is resorufin, and OIP is the optically inactive product generated in reaction 3. This non-linear system of differential equations was solved numerically to fit the experimental data, with the initial concentrations of the six reagents as initial parameters and the rate constants as fitting parameters. The concentration of resorufin, [R]t was found by measuring the transmittance (T) and using the following formula (see Appendix: Guide to nomenclature for the derivation of α): −log10 (T ) [R]t = (6.11) L where  is the extinction coefficient of resorufin and L is the path length of the cuvette. 6.4.4 Determination of K1 To obtain the experimental concentration of resorufin as a function of time, the trans- mittance was monitored for reaction mixtures in a 50 mM sodium phosphate buffer 157 Figure 6.7: Concentration of resorufin plotted as a function of time (symbols) in steps of 0.1 s, obtained from transmission measurements (at λmax = 571 nm). The solution contains 9.8 ± 0.2 µM resorufin and 8.8 ± 0.2 µM H2 O2, with either 0 nM, 5.5 ± 0.1 nM, 27.5 ± 0.6 nM, or 55 ± 1 nM HRP. The transmission data was plugged into Eq. 6.6 to find the concentration of resorufin. Experimental data points are reported every 5 s for clarity; the confidence band indicates the error for all data points. The measurements were repeated three times at each [HRP] value; the data in the figure shows the average value. The fits (solid lines) are obtained using a pseudo-first-order kinetics model (Eqs. 6.9 – 6.10) with K1 = 0 and K2 = 0. The best agreement between experimental data and the mathematical model corresponds to the case where [HRP] was 5.5 ± 0.1 nM. Therefore, this concentration of HRP was used for all other kinetic experiments in this study - K3 was found to be 56 ± 7 M−1 s−1 when averaged over the three trials at that particular concentration. (pH 7.4) with 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 82.5 ± 0.7 nM GOx. The concentration of glucose was varied between 0 – 210 µM. The initial concentration of Amplex Red was set to 280 µM for two reasons: (i) to ensure a 1:1 stoichiometric ratio between AR and glucose while allowing the initial concentration of glucose to vary across the entire physiological range of glucose in human saliva (ii) to prevent precipitation of AR (i.e. the solubility limit of AR is 300 µM in the aqueous buffer solution used here).31 Although it is possible to solve for K1 , K2 , and K3 simultaneously, using too many fitting parameters at once (including [G]t=0) could lead to large errors. To simplify 158 Figure 6.8: (a) Concentration of resorufin plotted as a function of time (symbols) in steps of 0.1 s obtained from transmission measurements (at λmax = 571 nm). The solution contains 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP, and either 3.8 ± 0.1 µM, 7.8 ± 0.1 µM, or 15.5 ± 0.3 µM H2O2 . The transmission spectrum, along with Eq. 6.11, was used to find the concentration of resorufin. The measurements were repeated three times at each [H2O2 ] value; the data in the figure shows the average value. Experimental data points are reported every 5 s for clarity; the confidence band indicates the error for all data points. The fits (solid lines) are obtained using a pseudo-first-order kinetics model (Eqs. 6.7 – 6.10) with K1 = 0 and K3 = 56 ± 7 M−1 s−1 (as found in S3). (b) The average rate constant K2 was determined for three independent trials at each concentration of H2 O2 (the error bars are within the data points). The mean value of all trials and concentrations is K2 = 135 ± 5 M−1 s−1 . 159 Table 6.1: Rate constants for the reactions in the AR/GOx/Glucose assay Rate Constant (M−1 s−1 ) Enzyme Concentrations Mean Value K1 HRP: 5.5 nM; GOx: 82.5 nM 7.3 ± 0.3 K2 HRP: 5.5 nM 135 ± 5 K3 HRP: 5.5 nM 56 ± 7 Data taken at 25 ◦ C in 50 mM sodium phosphate buffer (pH 7.4), [AR]t=0 = 280 ± 6 µM, [HRP] = 5.5 ± 0.1 nM, [GOx] = 82.5 ± 0.7 nM, and [G]t=0 = 0 – 200 µM. the calculations, the system was solved using a bottom-up approach: reaction 3 was studied by itself to obtain a value for K3 ; using this value, reactions 2 and 3 were run to obtain K2 (Figs. 6.7 and 6.8 for the kinetic analysis; see Table 6.1 for the values). However, when solving the full system of reactions for K1, K3 was set to zero. This assumption is supported by the fact that reaction 3 is slower than reaction 2 (K3 < K2 ) and that reaction 3 will occur only after there is a buildup of H2O2 in the reaction mixture. Zhou et al. demonstrated that a decrease in resorufin concentration (i.e., the initiation of reaction 3 to generate OIP) is observed only when the ratio of solution concentrations of H2O2 to AR is 2:1.31 In the full assay, the initial concentrations of resorufin and H2O2 always start at zero. Using the model to simulate the concentration of all six reagents as a function of time, the concentration of H2O2 never exceeds 10 µM (Fig. 6.9) when the highest initial concentration of glucose (210 µM) was used. This concentration of H2 O2 is significantly lower than that of AR in solution. To confirm that resorufin is the only optically active molecule in the buffer solu- tion, the spectral absorption (defined as A = 1 - T in the case of negligible reflection) was measured at different times and normalized to the absorption curve after the system reached saturation. The absorption spectrum does not change over the course of the experiment, thus confirming that other optically active products were not gen- erated (Fig. 6.10). This observation gives further credence to setting K3 = 0 when solving for K1. If K3 was not zero, then resorufin would undergo further oxidation to OIP, which would change the absorption profile of the reaction over time. Shown in Fig. 6.11(a) are transmittance curves plotted as a function of time for several different initial concentrations of glucose. Figure 6.11(b) plots the converted 160 Figure 6.9: Concentration profile of all six reactants in the AR/GOx/Glucose assay simulated with (a) [G]t=0 = 30.2 ± 0.1 µM and (b) [G]t=0 = 210 ± 5 µM as functions of time. G = Glucose, O2 = Oxygen, H2O2 = Hydrogen Peroxide, AR = Amplex Red, R = Resorufin, OIP = Optically Inactive Product (c) Concentration profile of H2O2 production over time simulated at different initial glucose concentration ([G]t=0) conditions. Even when the initial concentration of glucose is high, the H2O2 concentration never exceeds 10 µM. 161 Figure 6.10: Spectral absorption of resorufin at different times after the reaction is initiated; each curve is normalized to its own maximum value. The insets show the raw absorption data. In both panels, the mixture contains 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP; (a) includes 82.5 ± 0.7 nM GOx and 50.0 ± 0.9 µM glucose (reactions 1, 2 and 3 occur); (b) includes 27.1 ± 0.5 µM H2O2 (only reactions 2 and 3 occur). The curves within each panel are virtually identical at times, clearly demonstrating that no other optically active product besides resorufin is being generated in the reactions. 162 transmittance data to resorufin concentration over time using Eq. 6.11. Although [G]t=0 was measured a priori, this quantity was used as a variable parameter in the fitting code; the numbers reported in the figure refer to these fits. In all cases, the fitted value matches the concentration of resorufin at saturation, confirming the accuracy of the model. For each value of [G]t=0, a fitted value for K1 and [G]t=0 was found. The weighted average of all K1 data yields K1 = 7.3 ± 0.3 M−1 s−1 (Fig. 6.11(c)). The fitted curves show an excellent correlation to the experimental data, with a small discrepancy occurring when [[G]t=0 > 114 µM at long reaction times. There are two possible explanations for this discrepancy between the model and experiment. First, there may be local regions of depleted oxygen, which can be prevented by bub- bling oxygen into the buffer solution prior to experimentation. Second, Amplex Red may be photo-oxidized to resorufin.45−47 Three neutral density filters with different attenuation factors were used to reduce incident intensity. No significant change was observed in the measured concentration of resorufin (Fig. 6.12), thus eliminating this possibility. 6.4.5 Tuning the reaction time of the AR/GOx/Glucose as- say When applying the plasmonic cuvette to real-time glucose sensing, there are three time-dependent steps that must be considered: (i) the reaction time of the AR/GOx/Glucose assay (30 – 50 min); (ii) the flow time required to deliver the reacted solution to the surface of the sensor (∼10 s); and (iii) the data acquisition time (∼60 s). Since the reaction time of the assay is the longest, this property was investigated further and reduced by increasing the GOx concentration of reaction 1; this reaction had the smallest rate constant and therefore, was the rate-limiting step in the assay (Table 6.1). Figure 6.13(a) reports the concentration of resorufin measured as a function of time for various concentrations of GOx; each curve is normalized by its own saturation 163 Figure 6.11: (a) Intensity of light transmitted through the assay mixture plotted as a function of time at different concentrations of glucose. The transmittance through a cuvette (L = 0.2 cm) is monitored every 1 s for 2000 s at λmax = 571 nm; the data points are plotted in steps of 50 s for clarity (the confidence band interval is kept at 1 s). Each measurement is performed three times; the data shows the average of the three trials. (b) Concentration of resorufin plotted as a function of time using Eq. 6.11 (symbols). A non-linear first order kinetic model was used to fit the data (solid lines). (c) The mean value of three independent trials at each concentration of glucose is reported as K1 = 7.3 ± 0.3 M−1 s−1 . 164 Figure 6.12: Effect of illumination intensity on the photo-oxidation of Amplex Red. (a) Three neutral density filters Filter A (22%), Filter B (7.6%) and Filter C (0.85%) - were used to attenuate the illumination intensity of the visible light source of the UV-Vis spectrophotometer. (b) The resorufin concentration was determined for a reaction mixture containing 280 ± 6 µM AR, 5.5 ± 0.1 nM HRP and 27 ± 0.5 µM H2O2 after 300 s in the dark (in grey) and after illumination every 0.1 s for 300 s. The illumination intensity was decreased with the use of neutral density filters. The experiments were repeated in triplicate. This data shows that the illumination intensity does not significantly affect the concentration of resorufin, which means that the photo-oxidation of Amplex Red is not occurring in the time scales of these experiments. 165 Figure 6.13: Relationship between assay time and GOx concentration for reaction 1. (a) Normalized concentration of resorufin plotted as functions of time at various GOx concentrations. The black arrow indicates the direction of decreasing reaction time. (b) Reaction time, t is plotted as a function of GOx concentration. 166 value. As expected, increasing [GOx] makes the reaction run faster, but the effect saturates as [GOx] increases. To quantify this effect, Fig. 6.13(b) plots the reaction time (t, defined as the time it takes for [R]t to reach 63.2% of its saturation value) as a function of [GOx]. For example, increasing [GOx] by a factor of 10 (from 82.5 ± 0.7 nM to 825 ± 7 nM) shortens the reaction time from 583.5 s to 136.5 s, a factor of 4.3×. A non-linear dependence between K1 and [GOx] is observed when the data from each concentration of GOx was fitted for a new K1 value, with K2 and K3 unchanged. The data was fitted against the curve: C1[GOx] K1 = (6.12) C2 + [GOx] where C1 and C2 are fitting parameters. It was found that C1 = 48.5 ± 4.2 M−1 s−1 and C2 = (4.5 ± 0.9) × 10−7 M. Although this curve resembles the functional form of the Michaelis-Menten curve, it needs to be emphasized that Michaelis-Menten model is used to find the relationship between product generation rate (i.e., velocity v) as a function of substrate concentration ([S]) Instead, Eq. 6.12 is being used to determine the reaction rate (K1 ) as a function of enzyme concentration ([GOx]).48 The Michaelis-Menten model is not directly applicable to this data, because one of the foundational assumptions - that the initial substrate concentration is much greater than the concentration of enzyme - is not applicable here. In this system, the initial concentration of substrate (i.e., glucose) is at most only two orders of magnitude higher than the enzyme concentration [GOx] with [G] rapidly declining as it is converted into product. The non-linear behavior may be caused by aggregation of enzyme at higher concentrations, thus reducing the amount of active sites available to react with glucose (Fig. 6.14(a)). At the other extreme, when reaction 1 occurs very quickly, reaction 2 takes over as the rate-limiting step in the overall array. A similar experiment was performed for reaction 3. The value for K3 was found as a function of [HRP] by fitting the experimental data to Eqs. 6.9 – 6.10 with K2 = 0. The relationship between K3 and the concentration of HRP was found to be linear, with a slope of K3 ’ = (1.45 ± 0.04) × 1010 M−2 s−1 (Fig. 6.14(b)). 167 Figure 6.14: (a) Relationship between K1 and concentration of GOx in reaction 1. The data points refer to experimental measurements of K1 performed in triplicate (average value reported). (b) Extracted K3 values as a function of HRP concentration indicates a linear dependence with a slope of K3 ’ = (1.45 ± 0.04) × 1010 M−2 s−1 . 168 Figure 6.15: Effects of artificial saliva on the AR/GOx/Glucose assay. The concen- tration of resorufin plotted as a function of time for reaction mixtures initiated with [G]t=0 = 13 ± 0.6 µM in either (1) artificial saliva diluted in 50 mM sodium phos- phate buffer (1:6 v/v ratio, red circles) or (2) 50 mM sodium phosphate buffer (blue triangles). The control experiment is diluted artificial saliva with 0 µM glucose (black squares). 169 6.4.6 Specificity test of glucose in artificial saliva Although the plasmonic cuvette demonstrated high selectivity for glucose in a 50 mM sodium phosphate buffer solution, clinical samples of saliva are more complex and include a mixture of glycoproteins, enzymes, urea and electrolytes.29 The following experiments were performed in modified Fusayama artificial saliva (MFAS), which differs from actual saliva by the absence of large (> 12 kDa) proteins and enzymes (e.g., immunoglobin and α-Amylase, respectively). MFAS contains 16.7 mM of urea; in contrast, the concentration of urea in actual saliva is typically 2 – 3 mM. Figure 6.15 shows the production of resorufin over time using the AR/GOx/Glucose assay in MFAS to demonstrate the selectivity of glucose in a complex mixture and in 50 mM sodium phosphate buffer solution as a control. The black squares correspond to the experiment in MFAS (diluted 7× to increase the solubility of the urea and salts in the mixture) without glucose; as expected, the reaction to produce resorufin does not occur. When glucose is included in the reaction mixture, the assay proceeds normally (red circles). Since the composition of MFAS is different than that of 50 mM sodium phosphate buffer solution, the value of 571nm for MFAS was found to be (4.6 ± 0.2) × 104 M−1 cm−1. To quantify the difference between MFAS and the buffer solution, the experiment was repeated with the same [G]t=0 value in buffer solution (blue triangles). The two curves are quite similar: at the saturation time (t = 1855 s) the difference between the two curves is 7.4 %. Nothing in the MFAS solution should reacts with resorufin; thus, the discrepancy between the two curves can be attributed to a change in the overall kinetics of the assay, causing resorufin to be generated at a faster rate in MFAS. A kinetic analysis of the AR/GOx/Glucose assay in complex mixtures such as human saliva at different pH and temperatures will be reported elsewhere. 6.5 Conclusion In conclusion, this work introduces our plasmonic cuvette: a device that couples an enzyme-driven dye assay to plasmonic interferometry to produce a highly sensitive 170 real-time glucose sensor. The sensitivity was found to be 1.7 × 105 % / M within the physiological range of glucose in saliva (20 – 240 µM). This high sensitivity can be attributed to the strongly absorbing properties of resorufin, which absorbs optical and plasmonic signals to produce a unique spectral fingerprint. This optical signature was measured across a wide spectrum of wavelengths. Next, the reaction rate constants that underlie the assay were determined by fitting a first-order non-linear kinetic model to the experimental data. Knowledge of the kinetic constants led to altering the enzyme concentrations in reaction 1, which reduced significantly the time required for the assay reaction. Finally, the plasmonic cuvette was tested with artificial saliva to demonstrate the selective detection of glucose in a complex mixture of urea and salts. Not only does this report demonstrate the first step towards a sensitive and selective sensor for glucose in saliva, but the methodology can be applied to a plasmonic cuvette utilizing other dye assays and sensing schemes and will be the subject of future studies. 6.6 References 1. World Health Organization Fact Sheet, 312, 2013. 2. J. Wang. Electrochemical Glucose Biosensors. Chem. Rev., 108:814, 2008. 3. T. Cornelius, H. Pohlmeier, T. Behnke, V. Schmid, M. Grenningloh, T. Forst, and A. Pftzner. Accuracy evaluation of five blood glucose monitoring systems obtained from the pharmacy: A European multicenter study with 453 subjects. Diabetes Technol. Ther., 14:330, 2012. 4. 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Enzymatic activ- ity of surface-immobilized horseradish peroxidase confined to micrometer- to nanometer-scale structures in nanocapillary array membranes. Analyst, 134:851, 2009. 48. A. L. Lehninger, D. L. Nelson, and M. M. Cox. Lehninger principles of bio- chemistry, 4th ed.W.H. Freeman, New York, 2005. 6.7 Appendix: Guide to nomenclature The plasmonic cuvette merges two disparate fields into one device: dye chemistry and plasmonics. Because of the various conventions and standards that exist in the realms of chemistry and physics, it is important to be clear with the notation in this manuscript. There are two equivalent conventions for discussing the amount of molecules in a solution. Concentration c, in units of moles / volume (called a molar, M), is typically used by chemists. Density ρ is typically used by physicists, and is expressed in 176 (length)−3 . The conversion factor from one to the other is ρ = c × NA (6.13) where NA is Avogadro’s constant (NA = 6.022 × 1023 mol−1 ). For both cuvettes mentioned in this report (plasmonic and UV-Vis), the quantity that the system measures directly is the spectral transmittance, defined as IT T = (6.14) Iref where IT is intensity transmitted through the device and Iref is the reference incident intensity. Under the assumption that no reflection occurs, the law of conservation of energy states that A = 1−T (6.15) where A is called the absorption. The Beer-Lambert law defines a closely related quantity, the absorbance (sometimes called absorptance) Ab: Ab = −log10 (T ) (6.16) A is typically used by physicists, whereas Ab is typically used by chemists. Although they both share the property of 0 < A, Ab < 1, they are mathematically distinct. Next, the absorption coefficient σ is defined. This quantity, in units of (length)−1, depends on the intrinsic properties of the absorbing molecule and its concentration in the solution. The first principles definition is −loge (T ) T = e−αL → α = (6.17) L where L is the path length of the cuvette (in cm). This expression appears in both physics and chemistry. However, it is often useful to define a quantity that can help quantify absorption and absorbance, but does not depend on the concentration of a 177 species with a solution (that is, it is purely an intrinsic property of the molecule). Once again, physics and chemistry diverge on this point. Chemists prefer to use the extinction coefficient  (also known as the molar absorptivity), which is defined as Ab = (6.18) cL and is expressed in (molar)−1 (length)−1. Physicists prefer to use the absorption cross-section σ (in units of (length)2), which is defined as α σ= (6.19) ρ There is a linear relationship between  and σ; either of these can be used to relate the time- and wavelength transmission to the measured concentration or density of the optically-active resorufin species. To obtain this relationship, plug Eq. 6.18 into Eq. 6.16: cL = −log10 (T ) → c = [R]t = −log10 (T )L (6.20) This is Eq. 6.11 in the main text; the notation [ ]t refers to the time-dependent concentration of the species in the bracket. Next, plug in the definition of T from Eq. 6.17: −log10(e−αL ) αlog10 (e) c= = (6.21) L  Plug in the definition of α from Eq. 6.19: −σρlog10(e) c= (6.22)  Recall that logx (y) = 1/(logy (x)); re-arranging Eq. 6.22 gives loge (10)c σ= (6.23) ρ 178 This is Eq. 6.4 as discussed in Chapter 6. Finally, plug in Eq. 6.13 to obtain the expression loge (10) σ= = (3.824 × 10−21 mol) (6.24) NA Chapter 7 Concluding remarks and future work Much effort has been dedicated towards the development of innovative electrochem- ical and optical-based biosensors for the detection of small molecules in biological fluids. Both types of sensors have matured into a number of commercial instruments ranging from portable blood glucose meters to larger bench-top SPR instruments (e.g., Biacore) and are ideal analytical methods for monitoring interfacial reactions at a solid-liquid interface. Electrochemical and optical-based sensors offer numer- ous benefits including miniaturization, fast response times and high sensitivity. By identifying the appropriate surface chemistries, modifications to the bio-recognition element (i.e., enzyme, protein or antibody) and patterning new nano-corrugations (i.e., groove or slit configurations) to excite surface plasmons, further improvements can be made to improve the sensitivity, selectivity and stability of the sensing sur- faces over time. An added benefit to optical-based biosensors is the capability for non-invasive sampling, which is a desired parameter to improve patient compliance and comfort, disease management leading to better prognostic outcomes. This dissertation explores a variety of nano-scale methods to develop four different electrochemical or optical-based biosensors for vitamin D and glucose detection. In Chapters 2 and 3, we explored the use of different surface chemistries and bilayer lipid films to immobilize the CYP27B1 and vitamin D receptor (VDR) onto the sens- 179 180 ing electrodes. In Chapter 2, we were able to successfully immobilize the CYP27B1 into the didodecyldimethylammonium bromide (DDAB) surfactant film as confirmed by the direct electron transfer observed in the cyclic voltammograms. However, we discovered that the DDAB may have blocked the active site of CYP27B1 from binding to 25(OH)D3 and thereby impedes successful catalytic activity from being observed. To circumvent this problem, CYP27B1 may be incorporated into nano-discs1 , a self- assembled system that has been demonstrated to show the functional incorporation of other membrane bound CYP450 proteins including CYP2B42 and CYP3A43 . In Chapter 3, the successful incorporation of VDR into a bilipid layer film was able to detect concentrations of 1α,25(OH)2 D3 down to 52 nM. To further improve the limit of detection, conductive nanoparticles can be incorporated into the lipid films to further enhance the signal-to-noise ratio. The use of alternative surface chemistries such as n-alkanethiols4,5 to form SAM layers directly on gold or silver surfaces can also be used to ensure that the VDR protein is covalently attached in the proper orientation to the metal surface. In Chapter 4, a microbial biosensor was developed by designing and assembling a DNA-based biocircuit with a vitamin D receptor ligand binding domain (VDR-LBD) embedded within an intein that is flanked by a split green fluorescent protein. This biocircuit encoded a synthetic protein that was expressed as inclusion bodies within the cell. Progress was made to modify the biocircuit for expression into the soluble fraction, and thereby minimize the formation of inclusion bodies. Insertion of a pelB leader sequence allowed the sensor protein to be expressed in the soluble fraction, however, additional experiments will be necessary to evolve and control the biocircuit to splice conditionally in the presence of vitamin D metabolites. In the larger context of synthetic biology, further experiments can also be per- formed by modifying the different components of the biocircuit. The current Mtu RecA intein may be replaced with the faster splicing inteins such as Ssp DnaE intein6 or the Npu DnaE intein7. The VDR-LBD may be swapped with other nuclear hor- mone or orphan receptors so that the biocircuit can be used as a first line screening tool for identifying agonistic or antagonistic ligands that bind to the receptors. The 181 green fluorescent protein (GFP) split exteins system may also be replaced with other reporter proteins such as a split kanamycin or protease to cleave lipid films. As fur- ther inteins are discovered and split exteins systems are made, the potential for a variety of clever intein-based sensing applications will emerge. In Chapter 5, we introduced the novel groove-slit-groove (GSG) configuration for surface plasmon polariton (SPP) generation. We fabricated and characterized the transmitted light intensity response for a GSG plasmonic interferometer experimen- tally and confirmed the experimental data with a simulated model. Glucose was used as model analyte to demonstrate the feasibility of the GSG plasmonic sensor to detect small changes in refractive index; the sensor has wavelength sensitivity between 370 – 650 nm/RIU (RIU, Refractive Index Units), a relative intensity change between ∼103 – 106 %/RIU and a resolution of ∼3 × 10−7 in refractive index change. To make the sensitive GSG plasmonic interferometer more practical for real-time detection of glucose in saliva, the selectivity for glucose in a complex mixture was investigated in Chapter 6. The plasmonic interferometer was coupled to the Am- plex Red/Glucose Oxidase/Glucose (AR/GOx/Glucose) dye assay which offers high selectively to β-D-Glucose via the enzyme glucose oxidase (GOx). The Amplex Red to resorufin dye system is one of many suitable chromogenic dye assays that can be coupled successfully with the plasmonic interferometers. To choose a suitable dye to couple with the plasmonic interferometer for glucose detection in saliva, several factors should be considered: (1) the pH of saliva can vary between 2.5 – 7.5, thus the dye should be stable within that pH range; (2) a single reagent dye versus a dichromogen system will make the reagent composition simpler; (3) easily soluble in water; and (4) a higher extinction coefficient will improve sensitivity and detection range of the sensor. Finally, it is also important when selecting the arm lengths (i.e., p1 and p2 ) of the groove-slit-groove plasmonic interferometer to choose a device with a spectral minimum at the same peak absorption wavelength of the dye to achieve maximum sensitivity. Lastly, while the plasmonic interferometer shows great promise as a next-generation ultra-sensitive, high-throughput sensor for biochemical sensing, two practical consid- 182 Figure 7.1: (a) Schematic of the proposed integrated sensor for detection of glucose in saliva. (b) Image of a CCD camera unit currently under development. Also shown are the LCD panel, backlight source, and a disposable biochip; inset shows a detail of a gold biochip with integrated plasmonic interferometers placed on the CCD camera. (c) Illustrated step-by-step instructions that guides user with sample collection and use of the device. erations will need to be addressed for application as a point-of-care device. First, is the reduction of costs to fabricate the plasmonic interferometer. Nanoimprint lithog- raphy (NIL)8 may be a cheaper, alternative method to focus ion beam (FIB) for milling the concurrent pattern of desired nano-structures over a large uniform area. Second, is the miniaturization of the current optical- and experimental setup (Fig. 5.3) to a portable, hand-held device. A preliminary prototype design for a handheld glucose monitor may consist of an optical meter, a biochip milled with the plas- monic interferometers, a control solution and a saliva collection tube (Fig. 7.1(a)). A graphical illustration of instructions to operate the prototype device is shown in Fig. 183 7.1(b). In the field of biosensor research, proper design in the miniaturization and integra- tion of various functionalities (i.e., small reaction volumes and large sensor densities) is appealing but often limited in resources such as power, portability and costs. Thus, it is important to take into consideration the required sensor metrics during the re- search and development process of the sensor, and determine how to achieve these metrics with the minimum use of available resources. Many of the fabrication and characterization techniques discussed in the scope of this thesis can be extended to other biorecognition elements specific to other clinically relevant analytes. The molec- ular biology techniques described can be utilized to modify proteins to offer greater control in orienting the molecules on the sensing surface (e.g., addition of a sulfur moiety to better attach a protein onto a gold surface). Point mutations can also be introduced in the protein sequence that increases the binding affinity of that element to the analyte of interest and thereby improving the overall selectivity of the sensor. The micro- and nanofabrication techniques presented such as focus ion beam milling and electro-deposition of metal can be utilized to generate novel geometries of nano- corrugations that may achieve a sensor with even greater sensitivity than previously reported. Finally, by taking advantage that excitation of surface plasmons inherently require a metal film, the coupling of electrochemistry with plasmonic interferome- try may offer a new, simultaneous approach to study interfacial molecular binding processes. By drawing upon the techniques of interdisciplinary fields, the sensor in development will have a higher potential to become a successful disruptive innovation advancing both the fields of fundamental research and medical diagnostics. 7.1 References 1. I. G. Denisov, and S. G. Sligar. Cytochromes P450 in nanodiscs. Biochim. Biophys. Acta, 1814:223, 2011. 2. T. H. Bayburt, J. W. Carlson, and S. G. Sligar. Single molecule height mea- surements on a membrane protein in nanometer-scale phospholipid bilayer disks. 184 Langmuir, 16:5993, 2000. 3. A. Nath, P. K. Koo, E. Rhoades, and W. M. Atkins. Allosteric Effects on substrate dissociation from cytochrome P450 3A4 in Nanodiscs observed by ensemble and single-molecule fluorescence spectroscopy. J. Am. Chem. Soc., 130:15746, 2008. 4. C. D. Bain, E. B. Troughton, Y.-T. Tao, J. Evall, G. M. Whitesides, and R. G. Nuzzo. Formation of monolayer films by spontaneous assembly of organic thiols from solution onto gold. J. Am. Chem. Soc., 111:321, 1989. 5. J. P. Folkers, P. E. Laibinis, and G. M. Whitesides. Self-assembled monolayers of alkanethiols on gold: Comparisons of monolayers containing mixtures of short- and long-chain constituents with CH3 and CH2 OH terminal groups. Langmuir, 8:1330, 1992. 6. J. H. Appleby-Tagoe, I. V. Thiel, Y. Wang, Y. Wang, H. D. Mootz, and X.-Q. Liu. Highly efficient and more general cis- and trans- splicing inteins through sequential directed evolution. J. Biol. Chem., 286:34440, 2011. 7. J. Zettler, V. Sch¨ utz, and H. D. Mootz. The naturally split Npu DnaE intein ex- hibits an extraordinarily high rate in the protein trans-splicing reaction. FEBS Lett., 583:909, 2009. 8. S. Y. Chou, P. R. Krauss, and P. J. Renstrom. Imprint lithography with 25- nanometer resolution. Science, 272:85, 1996. Appendix A Protocol: Expression, purification and fluorescence characterization of IntGFP and IntVDRGFP This protocol was modified from the one that was originally received from Dr. Henry Paulus. This protocol was used to express and purify proteins from Plasmids IV, V, IX and X described in Chapter 4. Table A.1: Plasmids encoding sensor proteins and corresponding antibiotic resistance Plasmid Sensor Protein Antibiotic Resistance IV IntGFP AmpR V IntVDRGFP AmpR IX IntGFP-pelB KanR X IntVDR(118-425,∆165-215)GFP KanR A.1 Cell growth 1. Incubate 4 mL culture of Escherichia coli BL21 transformed with pIntGFP are grown at 37 ◦ C in LB supplemented with appropriate antibiotic (100 µg/mL Amp or 35 µg/mL Kan, see Table B.1) for 12 h. (3 × 1 mL 100 mL LB culture, 1 mL for glycerol stock) 185 186 2. Add 1 mL overnight to 100 mL culture of LB supplemented with appropriate antibiotic. 3. At a culture density (A600nm) of 0.5 (∼2-3 h), the cultures are induced with 0.4 mM IPTG (400 µL of 100 mM IPTG stock) and allowed to grow for another 4 h at 37 ◦ C. 4. Cells are harvested by centrifugation at 4,000 rpm for 20 min in weighted 50 ml centrifuge tubes. 5. Resuspend the pellets in 6 mL of Buffer A each. 6. Centrifuge at 4,000 rpm in Sorvall, weigh the tube to get the weight of cells, and stored in –80 ◦C freezer (for long-term); –20 ◦C (for purification the next day). A.2 Small scale purification of IntGFP, IntVDRGFP, IntGFP-pelB or IntVDR(118-425,∆165-215)GFP A.2.1 Cell disruption 1. Resuspend cells in 6 mL of Buffer A, using 4 ml Buffer A per gram of cells 2. Disrupt by passing through a French pressure cell 3. Centrifuge at 16,000 g for 20 min and collect the pellet A.2.2 Aldrithiol treatment 1. Resuspend in Buffer B using (4 mL buffer B/g of cells) to extract the inclusion bodies and centrifuge at 16,000g for 20 min to remove insoluble material. 2. Add 2 mM Aldrithiol-4’, (4.4 mg per 10 mL and store at 4 ◦C) 187 3. Centrifuge at 16,000 g for 20 min to remove insoluble material and yield solu- bilized inclusion bodies. 4. Save small sample for measuring protein concentration using Coomassie Plus reagent and use the remainder for purification on a 5 mL HiTrap chealtor col- umn. A.2.3 Column purification procedure (Use 2 mL/min flow rate with a 5 mL plastic BD syringe) Wash 1 mL HiTrap Chelator columns as follows: 1. 25 mL H2 O (Flow: 2 mL/min) 2. (10 mL of 0.1 M NiSO4) when need to recharge 3. 10 mL of H2O and 25 ml of Buffer B (Flow: 2 mL/min) 4. Apply sample in Buffer B (Collect eluate) (Flow: 1 mL/min) 5. 25 mL Buffer B (Collect eluate) (Flow: 2 mL/min) 6. 25 mL Buffer B + 10 mM imidazole (Collect eluate) (Flow: 2 mL/min) 7. 20 mL Buffer B + 50 mM imidazole (Collect 2 mL fractions) (Flow: 2 mL/min) 8. 10 mL Buffer B + 100 mM imidazole (Collect 2 mL fractions) (Flow: 2 mL/min) 9. 10 mL Buffer B + 200 mM imidazole (Collect 2 mL fractions) (Flow: 2 mL/min) 10. 20 mL water wash Essentially all activity elutes at 50 mM imidazole. Combine active fractions and store at 4 ◦C. Protein splicing activity is stable for at least 2 months. 188 A.3 Determination of protein concentration 1. Set up the BCA assay (Pierce) according to manufacturer’s instructions and incubate at 37 ◦ C for 45 minutes. 2. Perform absorbance scan from 540 - 590 nm at 1 nm/s. Peak absorbance should be observed at λ = 562 nm. 3. Dilute expressed protein to 75 µ/mL using dilution Buffer C. The 0.5 M L- arginine in Buffer C serves to prevent protein aggregation. 4. Make aliquots of 475 µL leaving 25 µL for addition of TCEP, EtOH or ligand to make a final concentration of 75 µg/mL. 5. Store at –20 ◦ C. Use within 2 days after dilution buffer has been added. A.4 Fluorimeter test for intein splicing assay 1. Using the Cary Eclipse fluorimeter, set the λex = 395 nm and scan emission from 450 - 600 nm. Monitor GFP emission wavelength at 510 nm as a function of time. 2. Zero instrument in air (i.e., no cuvette or sample). 3. Scan sample containing 475 µL of diluted purified protein supplemented with 25 µL of TCEP, EtOH or ligand. Protein splicing is initiated by the addition of TCEP to 1 mM to reduce the 4-thiopyridine adduct of the Cys residues. A.5 Buffer recipes 1. Buffer A: 20 mM sodium phosphate, pH 7.5, 0.5 M NaCl 2. Buffer B: 20 mM sodium phosphate, pH 7.9, 0.5 M NaCl, 8 M urea. This is prepared by adding 48 g of urea (enzyme grade) to 50 ml of double- strength Buffer A and adjusting volume to 100 mL with H2O. 189 3. Buffer C: 20 mM sodium phosphate, pH 7.0, 0.5 M NaCl, and 0.5 M arginine (2.0 M arginine, pH 7.0, is prepared by dissolving 211 g L-arginine hydrochloride in 300 mL H2O, adjusting pH to 7.0 with NaOH, and adjusting volume to 500 mL) Appendix B Performance comparison of plasmonic sensors. 190 Table B.1: Performance comparison between our plasmonic interferometer method and other conventional, plasmonic and microphotonics approaches. Wavelength FOMλ = FOMI = Sensed Device Sensor Resolution Ref. Technique Range ∆λ/∆n (∆I/I0 )/∆n Volume Size Density (RIU) (nm) (nm/RIU) (%/RIU) (fL or µm3 ) (µm2 ) (mm−2 ) Groove-slit-groove Broadband 3 × 10 −7 32,200 105,000 20 100 10,000 1 p1 = 0.57 µm; p2 = 9.75 µm (350 – 1700 nm) Prism-coupled SPR Single (928 nm) 8.6 × 10−5 9,950 2,900 1.5 × 107 2.8 × 107 0.04 2 Grating-coupled SPR Single (632.8 nm) 1.5 × 10−6 N/A N/A N/A N/A N/A 3 Imaging SPR 4,5 Single (800 nm) > 3 × 10−5 N/A 3,000 3 × 105 7.8 × 108 16 (SPRimagerII) Optical Fibers Single (650 nm) N/A 3,600 1,200 4.1 × 106 > 6 × 106 < 0.2 6 Nanoparticles Single (897 nm) N/A 405 2,100 N/A 5 × 105 2 7 Nanohole Array Single (606 nm) N/A 333 N/A 71.3 400 2,500 8 Nanoslit Array Single (697 nm) N/A 600 5,900 N/A 10,000 100 9 Two-Slit Single (870 nm) 4.4 × 10 −6 4,550 N/A 1784 3,900 250 10 Ultra high-Q Single 11 Single (681.5 nm) N/A N/A N/A 502 15 microtoroid Molecule Mach-Zehnder 12 Single (830 nm) 2.5 × 10−6 N/A N/A 2 × 105 1.3 × 106 0.74 Interferometer References: 1. J. Feng, V. S. Siu, A. 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Ghenuche, A. Haghiri-Gosnet, D. Decanini, J. Chen, J. Pelouard, and S. Collin. λ3 /1000 Plasmonic nanocavities for biosensing fabricated by soft UV nanoimprint lithography. Nano Lett., 11:3557, 2011. 8. A. Leebeeck, L. K. S. Kumar, V. Lange, D. Sinton, R. Gordon, and A. Brolo. On-chip surface-based detection with nanohole arrays. Anal. Chem., 79:4094, 2007. 9. K. Lee, and P. Wei. Enhancing surface plasmon detection using ultrasmall nanoslits and a multispectral integration method. Small, 6:1900, 2010. 10. X. Wu, J. Zhang, J. Chen, C. Zhao, and Q. Gong. Refractive index sensor based on surface-plasmon interference. Opt Lett., 34:392, 2009. 11. A. M. Armani, R. P. Kulkarni, S. E. Fraser, R. C. Flagan, and K. J. Vahala. Label-free, Single-molecule detection with optical microcavities. Science, 317:783, 2007. 191 12. J. Lillie, M. Thomas, N. M. Jokerst, S. Ralph, K. A. Dennis, and C. Henderson. 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