Role of Mechanophenotype in Cell-Substrate Interactions by Manisha K. Shah B.S. University of California, San Diego, San Diego, CA 92093 Sc.M. Brown University, Providence, RI 02906 Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Engineering, a joint program in the Division of Biology and Medicine and the School of Engineering at Brown University Department of Molecular Pharmacology, Physiology, and Biotechnology and Center for Biomedical Engineering PROVIDENCE, RHODE ISLAND MAY 2018 ii © Copyright 2018 by Manisha K. Shah iii iii This dissertation by Manisha K. Shah is accepted in its present form by the Biomedical Engineering program, a joint program in the Division of Biology and Medicine and the Division of Engineering as satisfying the dissertation requirements for the degree of Doctor of Philosophy Date Eric Darling, PhD, Advisor Recommended to the Graduate Council Date Kareen Coulombe, PhD, Reader Date Jeffrey Morgan, PhD, Reader Date Ian Wong, PhD, Reader Date John Slater, PhD, External Reader Approved by the Graduate Council Date Andrew Campbell, Dean of the Graduate School iii Curriculum Vitae NAME Manisha K. Shah EDUCATION Brown University, Providence, RI Ph.D., Biomedical Engineering Advisor: Eric Darling, PhD Title of Dissertation: Role of Mechanophenotype in Cell – Substrate Interactions Expected: December 2017 Brown University, Providence, RI Sc.M., Biomedical Engineering, 2013 Advisor: Eric Darling, PhD Title of Dissertation: Characterization of Molecular and Mechanical Phenotypes of Freshly Isolated Lipoaspirate Cells University of California, San Diego, San Diego, CA B.S., Bioengineering (Biotechnology), 2009 PUBLICATIONS Shah MK, Garcia-Pak IH, Darling EM. Influence of inherent mechanophenotype on competitive adherence. Ann Biomed Eng. 2017 Apr 21. (Featured as Cover Art for print version of Journal: August 2017) Marble HD, Sutermaster BA, Kanthilal M, Fonseca VC, Darling EM. 2014. Gene expression-based enrichment of live cells from adipose tissue produces subpopulations with improved osteogenic potential. Stem Cell Res Ther. 2014 Oct 6; 5:145. Kanthilal M and Darling EM. Characterization of Mechanical and Regenerative Properties of Human, Adipose Stromal Cells. Cell Mol Bioeng. 2014 Aug 5; 7:585-597. iv CONFERENCE ABSTRACTS Shah MK, Leary EA, Morgan JR, Darling EM. (2018). Incorporation of Cell Mimicking Microparticles into a 3D Tumor Model of Melanoma. Conference abstract. Cellular and Molecular Bioengineering, Key Largo, FL, USA. Kanthilal M and Darling EM. (2016) Mechanophenotype influences cellular organization and morphology. Conference abstract. Biomedical Engineering Society Conference. Minneapolis, MN, USA. Kanthilal M, Pak I, Darling EM. (2015) Mechanophenotype influences cellular organization on mechanically and biologically engineered surfaces. Conference abstract. Tissue Engineering and Regenerative Medicine International Society, Boston, MA. González Cruz RD, Fonseca VC, Kanthilal M, Sadick JS, Darling EM. (2015). LMNA gene expression serves as a novel biomarker for characterizing mechanical phenotype. Conference abstract. Orthopaedic Research Society, Las Vegas, NV. Pak I, Kanthilal M, Darling EM. (2015) The role of cellular mechanical properties in microenvironment-dependent behavior. Conference abstract. Biophysical Society. Baltimore, MD. Darling EM, Labriola NR, González-Cruz RD, Kanthilal M, Sadick JS, Fonseca VC. (2015). The intersection of gene expression and mechanical phenotype. Conference abstract. Cellular and Molecular Bioengineering Conference. St. Thomas, USVI. Kanthilal M and Darling EM. (2013) Characterization of Molecular and Mechanical Phenotypes of Freshly Isolated Lipoaspirate Cells. Conference abstract. Biomedical Engineering Society Conference. Seattle, WA. LEADERSHIP AND TEACH EXPERIENCE 2013- Scientific Mentor to Undergraduate Students, Darling Lab, Brown University 2015 Teaching Assistant and Guest Lecturer, BIOL 1150 Stem Cell Engineering, Brown University 2014-2015 Summer at Brown Instructor. Providence, RI 2012 Teaching Assistant, BIOL 1120 Biomaterials, Brown University 2012 Outreach Volunteer, Nathan Bishop Middle School, Providence RI 2011- Brown Graduate Biomedical Engineering Society. Providence, RI President (2013-2014), Treasurer (2012-2013), Member (current). v TRAINING Laboratory: Primary cell/ stem cell isolation (adipose tissue and bone marrow), atomic force microscopy, fluorescence and confocal microscopy, high-content/ high-throughput imaging, mammalian cell culture (2D, suspension, and scaffold free - 3D cell culture) and transfection, bacterial cell culture and transformation, fluorescence activated cell sorting (FACS), biomaterials (polyacrylamide, PDMS, alginate), protein purification, cloning, chromatography (FPLC/ HPLC using AKTA systems), filtration, LAL Endotoxin Detection Assay, DNA extraction, SDS-PAGE, western blot, and big data Software: ImageJ, Photoshop, Illustrator, Imaris, FlowJo, SigmaPlot, GraphPad Prism, Excel, PowerPoint, Word, and MATLAB ADDITIONAL RESEARCH EXPERIENCE 2009-2011 Research Assistant II, Amunix Inc., Mountain View, CA Syracuse, NY 2008-2009 Undergraduate Researcher, Palsson Lab, UCSD, San Diego, CA 2008 Research Intern, Rangarajan Lab, Indian Institute of Science, Bangalore, India vi Acknowledgements First and foremost, I would like to thank my advisor, Eric Darling, for all the guidance, advice, and support over the last seven years. Thank you for your encouragement. Thank you for constantly challenging me to think critically and to always ask “Why.” Your mentorship has allowed me to grow into a more confident scientist, writer, and public speaker. Thank you for always having an open door for discussions on experiments, science, and the future. Thank you to my committee members, Jeffrey Morgan, Kareen Coulombe, Ian Wong, and John Slater. I truly appreciate all the feedback and support I have received from you over the years, and for encouraging me think outside the box. Thank you to the incredible administrative staff, past and present: Crystal Miller, Jess Bello, Melodie Vicenty, Tim Durning, Kris McCutcheon, Elly Peimer, Carol Folan, Cheryl Pariseau. You all have been so supportive of me during my time as a graduate student, answering my many questions, and hosting so many great MPPB events! My Labmates: past and present! I do not know what I would do without all of you! Moving so far away from home seven years ago was a huge step for me, and you all made that life change so much easier. You became my family away from home. Thank you for all the scientific discussions, help with troubleshooting the AFM and other experiments, Disney Fridays (sorry boys corner), post-its on my desk, lunch time conversations, and so much more! To Vera Fonseca: Thank you for being the best lab manager, aka lab mom, ever! You are incredibly patient and kind. Thank you for taking me under your wings and vii showing me the ways of the Darling Lab when I first arrived, and supporting me throughout my time here. Thank you to all the other residents of the BMC third floor! You have all contributed to my success at Brown, whether through lunch conversations, supplying me with reagents I needed, scientific advice, or just talking about all the Dramzzzz in our lives! You all have shaped this experience and made grad school so much more entertaining! To all the friends I have made here, thank you for being so encouraging, and, really, pillars of support through the years. I came to grad school for education, but gained so much more from the relationships I’ve built. I don’t know what I would have done without all the shenanigans with you guys. I will miss late nights at the GCB, grad student formals, ski trips, sheltering together during hurricanes/ winter storms, etc. I especially want to thank Molly Boutin and Michael Susienka for showing me the ways of the east coast, traveling with me, being a sounding board for both my scientific and non-scientific decisions, and so much more! To my amazing husband, Soham, thank you for your endless support, love, and encouragement. You’ve been a rock through my time here, and so understanding and patient, especially when I drag you to lab with me on your off days! Thank you for sharing your wonderful family, a family I now consider my own. I can’t wait to finally be able to see you for more than just a weekend, and to finally be done with long distance. I can’t wait to see what the future holds for us! And finally, my home and global family – I could not have done this without you. To my Parents – there aren’t enough ways to say Thank You for ALWAYS supporting me and having my back! You taught me to be ambitious, determined, and to always be the best viii version of myself. Thank you for being my biggest cheerleaders and the best role models anyone could ask for! To my sisters, Dipti and Anjali, thank you for never letting me miss out on a moment at home, whether through constant pictures, texts, snaps, or FaceTime. I truly appreciate all your visits over the last seven years, sending me food and care packages, going on mini-adventures with me to Maine, New York, the Cape, Iceland, and most importantly, exchanging new recipes to try out – because, of course, we love food! To my extended family, all over the world, my sisters, and my Mom and Dad, I know you’ve been asking me since Day 1: “When will you be done?” I can finally say, “I’m done!” ix Table of Contents Curriculum Vitae ............................................................................................................... iv Acknowledgements ........................................................................................................... vii Table of Contents ................................................................................................................ x List of Figures .................................................................................................................. xiii List of Tables .................................................................................................................... xv 1 Introduction ................................................................................................................. 1 1.1 Motivation/ Chapter Overview............................................................................. 1 1.2 Background and Significance............................................................................... 4 1.2.1 The Cellular Microenvironment and Mechanophenotype ............................ 4 1.2.2 Assessing Mechanophenotype using Atomic Force Microscopy ................. 6 1.2.3 Assessing heterogeneity of mechanophenotype of adipose derived stem cells 8 1.2.4 Mechanosensing of the microenvironment through integrins and cadherins 9 1.2.5 3D culture systems as tumor models .......................................................... 10 1.3 Closing Remarks ................................................................................................ 11 1.4 References .......................................................................................................... 13 2 Characterization of mechanical and regenerative properties of human, adipose stromal cells ...................................................................................................................... 19 2.1 Abstract .............................................................................................................. 20 2.2 Introduction ........................................................................................................ 21 2.3 Materials and Methods ....................................................................................... 23 2.3.1 SVF Isolation .............................................................................................. 23 2.3.2 Cell sorting .................................................................................................. 24 2.3.3 Mechanical Characterization of sorted SVF cells ....................................... 26 2.3.4 Multipotency assessment ............................................................................ 28 2.3.5 Statistical Analysis ...................................................................................... 29 2.4 Results ................................................................................................................ 30 2.4.1 Sorting of Cells in the SVF ......................................................................... 30 2.4.2 Characterization of Mechanical Properties of Cells in SVF ....................... 32 2.4.3 Differentiation of Cells in SVF ................................................................... 34 x 2.5 Discussion .......................................................................................................... 37 2.6 Acknowledgements ............................................................................................ 44 2.7 Ethical standards ................................................................................................ 44 2.8 References .......................................................................................................... 45 2.9 Supplemental Figure .......................................................................................... 52 3 Influence of inherent mechanophenotype on competitive cellular adherence .......... 53 3.1 Abstract .............................................................................................................. 54 3.2 Introduction ........................................................................................................ 55 3.3 Materials and Methods ....................................................................................... 57 3.3.1 Cell Culture ................................................................................................. 57 3.3.2 Development of Stable Cell Lines .............................................................. 58 3.3.3 Gel Fabrication and Functionalization ........................................................ 58 3.3.4 Atomic Force Microscopy .......................................................................... 59 3.3.5 Confirmation of Transfections Using Western Blot ................................... 61 3.3.6 Assessment of Actin Organization and Cellular Assembly ........................ 62 3.3.7 Statistical Analysis ...................................................................................... 63 3.4 Results ................................................................................................................ 63 3.4.1 Elastic Properties of PAAm Gels ................................................................ 63 3.4.2 Temporal Mechanophenotype Characterization of WI-38 Cells ................ 63 3.4.3 Transfection and Mechanical Characterization of WI-38 Cells ................. 65 3.4.4 Effect of Mechanophenotype on Cellular Organization ............................. 67 3.4.5 Confocal Imaging of Actin Cytoskeleton ................................................... 70 3.5 Discussion .......................................................................................................... 72 3.6 Author Contributions.......................................................................................... 79 3.7 Acknowledgments .............................................................................................. 79 3.8 Conflict of Interest ............................................................................................. 79 3.9 Data Accessibility .............................................................................................. 79 3.10 References .......................................................................................................... 80 3.11 Supplementary Text ........................................................................................... 85 3.11.1 ECM effects on cells from alternative lineages .......................................... 85 3.12 Supplemental Figures ......................................................................................... 87 xi 1 Integration of hyper-compliant microparticles into a 3D melanoma tumor model. .. 93 1.1 Abstract .............................................................................................................. 94 1.2 Introduction ........................................................................................................ 95 1.3 Methods .............................................................................................................. 96 1.3.1 Cell culture .................................................................................................. 96 1.3.2 Fabrication of MPs ...................................................................................... 97 1.3.3 Characterization of MPs and Cells ............................................................. 98 1.3.4 Spheroid seeding for 3 experiments............................................................ 98 1.3.5 Data Analysis in Imaris ............................................................................. 100 1.3.6 Rate of Penetration towards center of the spheroid .................................. 100 1.3.7 MP distance traveled and speed ................................................................ 101 1.3.8 Statistical Analysis .................................................................................... 101 1.4 Results .............................................................................................................. 101 1.4.1 Mechanical and Size Characterization of HEM-L158, NHF, A375 cells and MPs 101 1.4.2 Rate of Penetration of MPs towards center of Spheroids ......................... 102 1.4.3 Distance traveled and speed of MP within the spheroid ........................... 103 1.4.4 PS MP behavior in HEM and A375 spheroids ......................................... 105 1.4.5 Time lapse imaging of soft MP incorporation in A375 spheroids ............ 106 1.4.6 ECM deposition versus MP incorporation in extended study .................. 108 1.4.7 MP incorporation into NHF spheroids ...................................................... 108 1.5 Discussion ........................................................................................................ 109 1.6 Acknowledgements .......................................................................................... 112 1.7 References ........................................................................................................ 114 1.8 Supplemental Figure ........................................................................................ 118 2 Conclusion and Future Work................................................................................... 120 2.1 Chapter 2 .......................................................................................................... 120 2.2 Chapter 3 .......................................................................................................... 121 2.3 Chapter 4 .......................................................................................................... 122 2.4 Closing Remarks .............................................................................................. 124 2.5 References ........................................................................................................ 126 xii List of Figures Figure 2-1 Multi-color sorts of SVF cells based on protein expression using FACS....... 31 Figure 2-2 Biomechanical properties of the unsorted SVF and sorted cell types residing in adipose tissue for seven donors......................................................................................... 33 Figure 2-3 Adipogenic differentiation was assessed by ORO staining of intracellular lipids.................................................................................................................................. 35 Figure 2-4 Osteogenic differentiation was assessed by ARS staining of calcified matrix. ........................................................................................................................................... 36 Figure 2-5 While variability was observed, overall trends of biomechanical properties measured using AFM across the seven donors tested was conserved.. ............................ 52 Figure 3-1 Mechanical characterization of the cellular assemblies formed by WI-38 cells on compliant substrates over 5 days. ................................................................................ 64 Figure 3-2 Characterization of GFP, dnRhoA, and β-Actin cells.. ................................... 66 Figure 3-3 Effect of mechanophenotype on cellular assembly into nodules or plaques.. 68 Figure 3-4 Average mechanical properties, (a) Eelastic, (b) ER, (c) E0, and (d) µ, of GFP-, dnRhoA-, and β-Actin-transfected WI-38 cells after four days on 0.3, 0.5, and 1.4 kPa PAAm gels and glass coverslips (CS).. ............................................................................ 70 Figure 3-5 Nodules and plaques of GFP, dnRhoA, and β-Actin cells after 4 days of culture.. ............................................................................................................................. 71 Figure 3-6 Height changes correspond with cellular assembly of non-transfected WI-38 fibroblasts into nodules and plaques.. ............................................................................... 87 Figure 3-7 Effect of substrate stiffness for (a) MG-63 cells and (b) SH-SY5Y cells on fibronectin, laminin, and collagen-1 functionalized PAAm gels ...................................... 89 Figure 3-8 Average mechanical properties of (a-d) MG-63 and (d-f) SH-SY5Y cells after two days on glass CS or PAAm gels coated with FN, LN, or COL-1.. .......................... 90 Figure 3-9 Height changes correspond with cellular assembly of transfected cell types into nodules and plaques for (a) GFP, (b) dnRhoA, and (c) β-Actin cells.. ..................... 91 xiii Figure 4-1Characterization of cell and MPs.. ................................................................. 102 Figure 4-2 Assessment of MP penetration towards the center of the spheroid. ............. 103 Figure 4-3 Assessment of MP distance traveled within HEM and A375 spheroids. ...... 104 Figure 4-4 Assessment of incorporation of PS MPs within HEM and A375 spheroids..105 Figure 4-5 Confocal 3D projections of integration of a soft MP into an A375 spheroid at 44-minute intervals. ........................................................................................................ 107 Figure 4-6 Pilot HEM and A375 spheroid histology. ..................................................... 108 Figure 4-7 Assessment of incorporation of soft, stiff and PS MPs within control NHF spheroid ........................................................................................................................... 118 Figure 4-8 Confocal 3D projections at last time point of HEM, A375, and NHF spheroids with MP integrated. ......................................................................................................... 119 xiv List of Tables Table 2.1 Summary of antibody combinations used for FACS. ...... Error! Bookmark not defined.5 Table 3.1 Number of samples tested corresponding to (a) WI-38 cell mechanics over four days on glass ................................................................................................................... 922 xv Chapter 1 1 Introduction 1.1 Motivation/ Chapter Overview Cellular mechanophenotype is defined as the elastic and viscoelastic properties of a cell, and is commonly characterized by atomic force microscopy (AFM). Assessment of a cell’s mechanophenotype in the larger context of its microenvironment can add to increased understanding of biological phenomena such a cellular organization, proliferation, shape, motility, and differentiation. Here, we aim to (1) characterize the mechanical properties and differentiation potential of cells present in human lipoaspirate, (2) examine the influence of inherent mechanophenotype on cell-cell-substrate organization, and (3) assess incorporation of compliant microparticles into cancer vs. normal spheroids. Chapter 2 characterized the mechanical and regenerative properties of human, adipose stromal cells. The stromal vascular fraction (SVF) of human adipose tissue is a heterogeneous population with component cell types that may or may not contribute to its regenerative potential. The goal of this study was to characterize mechanical properties and differentiation potential of component cell types present in the SVF. Using fluorescence- 1 activated cell sorting, the SVF was sorted for four major cell types: adipose-derived stem cells (ASCs), endothelial cells (EC), pre-adipocytes, and smooth muscle cells (SMCs). Cellular mechanophenotype and adipogenic/osteogenic differentiation potential of the unsorted SVF and sorted subpopulations was characterized. Cells populating the SVF exhibited a range of mechanical properties, with ECs, ASCs, pre-adipocytes, and unsorted SVF cells being significantly more compliant than SMCs. Lineage-specific metabolite production was most robust in SVF cells, followed by ASCs, with the other cell types showing little or no potential, suggesting the unsorted populations may benefit from a paracrine response that is lacking once the cells are sorted into more uniform cell populations. This study takes the first step in defining the mechanophenotype of the cells present in the SVF for future mechanics-based sorting platforms, in hopes of eliminating the need for culturing. Chapter 3 determined the influence of inherent mechanophenotype on competitive cellular adherence. Understanding the role of mechanophenotype in competitive cell adherence to other cells versus underlying substrates can inform such processes as tissue development, cancer progression, and wound healing. The goal of this study was to (1) investigate the stability of inherent cellular mechanophenotype with respect to time and compliance of the underlying substrate and (2) determine whether mechanophenotype can influence cellular adhesion and assembly when cells are grown on gels of known, physiologic elasticity. Human lung fibroblasts were mechanically characterized over four days of culture on collagen 1-coated polyacrylamide gels to assess if, and when, mechanophenotype reached equilibrium. Stably transfected fibroblasts with distinct mechanophenotypes were grown on substrates of different stiffnesses. Changes in cellular 2 mechanical properties and organizational phenotypes were assessed in relation to the mechanophenotype of the cell. The ability of cells to aggregate or spread individually depends not only on cell type, extracellular matrix ligands, and substrate stiffness, but also on inherent mechanophenotype. This suggests that inherent mechanophenotype plays a role as a competing surface during microenvironment mechanosensing and subsequent cell-cell-substrate organization. Chapter 4 assessed the integration of hyper-compliant microparticles into a 3D melanoma tumor model. Multicellular 3D-spheroids provide a physiologically relevant platform to study the microenvironment of tumors and potential therapeutic applications, such as microparticle-based drug delivery. The goal of this study was to investigate the incorporation/ penetration of compliant polyacrylamide microparticles (MPs), into either cancerous or healthy human cell spheroids. Incorporation of MPs (stiffness: 0.1 and 9 kPa; diameter: 10-30 µm) into spheroids (diameter ~100 µm) was tracked over 24 hours. Soft MPs penetrated towards the center significantly more in melanoma spheroids compared to normal spheroids. Mature spheroids from both cell types were able to recognize and integrate MPs. While many tumor models exist to study drug delivery and efficacy, uptake and incorporation of cell-sized MPs into established spheroids/tissues or tumors has been difficult. The ability of hyper-compliant MPs to successfully penetrate 3D tumor models encapsulated by extracellular matrix provides a novel platform for potential delivery of drugs and other therapeutics into tumor cores. The goal of this thesis was to provide a better understanding of the role of mechanical properties of both cells and substrates, and how the responses of these mechanical interactions could be used. Chapter 6 summarizes these main conclusions from 3 the work completed in this thesis. Additionally, future directions and alternate experiments are proposed. 1.2 Background and Significance 1.2.1 The Cellular Microenvironment and Mechanophenotype The cellular microenvironment is a delicate combination of numerous elements, including soluble and insoluble signaling molecules, physical stimuli, and cell-matrix and cell-cell interactions. Previous studies have demonstrated how the extracellular environment drastically shapes cell behaviors; however internal cellular properties can be equally important to understanding the reaction of a cell. Cellular properties such as gene and protein expression are frequently considered the gold standard for defining a cell. However the under-studied property of mechanophenotype, defined by the mechanical properties of a cell and acts as a secondary descriptor/reporter of molecular changes, can be equally important [8, 11, 12, 14, 30]. Cells generate specific phenotypic responses based on extracellular mechanical triggers, such as surface rigidity, sheer forces, and stretching through cell-cell and cell-substrate contacts, as well as intracellular mechanochemical reactions [17]. Furthermore, mechanical differences in cellular morphologies/phenotype and tissue stiffness are representative of normal versus diseased states [11, 17]. Recently, mechanophenotype has come into the forefront as a viable biomarker and descriptor of a cell’s function and fate [11]. Defined by a cell’s elastic and viscoelastic properties, cellular mechanophenotype relative to substrate stiffness can inform processes such as tissue development, cancer progression, and wound healing. Often, population- wide mechanical properties are considered, but recent studies show that single cells need 4 to be investigated to define appropriate correlations between mechanics and traditional biomarkers [3, 8, 23]. Mechanophenotype is a promising label-free biomarker that could be used to sort cells of interest, once the role of mechanical properties is better described [8, 11]. A model system to understand the interplay between the extracellular microenvironment and intracellular mechanophenotype is a cancer tumor. It is thought that tumors stiffen over time due to increased deposition of extracellular matrix (ECM), but can have softer inner cores that have greater cell density and limited ECM [34]. Divergent from the stiffening of the ECM, a hallmark of metastasis is concurrent softening of individual cells. This phenomenon is linked to increased cellular motility and invasiveness, allowing the cancer cells to squeeze through small spaces and extravasate into vasculature for metastasis [6, 36]. A theory behind this characteristic is the loss of mechanosensitivitiy of cancer cells, which leads to substrate stiffness having limited negative effects on migration, proliferation, and survival compared to normal cell counterparts [6, 25, 36]. While cancer displays the most obvious role and descriptions for mechanophenotype, many other tissue systems follow similar principles. For example, myoblasts cultured on polyacrylamide (PA) gels of stiffness ranging from 1 kPa to 17 kPa, coated with stripes of collagen, displayed the ability to spread on all the gels, but only developed striations on 8-12 kPa PA gels, mimicking normal muscle tissue stiffness [13]. Similarly, hepatocytes maintain their differentiated states on extremely compliant Matrigel substrates, but when activated, drastically alter morphologies, and change into stellate hepatic cells on stiff substrates, such as tissue culture plastic [16]. Normal hepatocytes naturally form aggregates in healthy tissue (Young's modulus < 600 Pa [37]) to maintain 5 their hepatic network, but changes in conditions, such as liver disease (Young's modulus > 20 kPa [37]), lead to the breakdown of this network, a stiffer extracellular matrix, and increased stellate cells [17]. Another example of the importance of ECM properties and cell type-specific response is neuron growth on Matrigel-coated PA gels, where cells are healthy and form extensions as expected [15]. Contrastingly, activated glial cells, primarily found in nervous system scar tissue, were unable to survive on the low stiffness substrates [15]. While it has been recognized that substrate stiffness is essential to successful implants and tissue-engineered constructs, and different cell types display varying reactions to these environments [17, 37]. there is a significant missing link. Specifically, there is a gap in scientific understanding of the effect of inherent cellular mechanophenotypes on the success of implantable polymers and the role of mechanophenotypic changes due injury or disease. 1.2.2 Assessing Mechanophenotype using Atomic Force Microscopy Understanding how whole-cell mechanophenotype affects cellular behavior and interaction within the microenvironment is important for directing cellular assembly in regenerating tissues. Atomic force microscopy (AFM) is a common technique used to assess cellular elastic and viscoelastic properties [9, 10, 19, 23]. This technique involves (1) bringing a cantilever with known spring constant in contact with a cell or sample of interest, (2) reflecting a laser off the tip of the cantilever and onto a photo-sensitive detector, (3) indenting into the sample by moving the cantilever in the z-direction using a piezoelectric motor, and (4) measuring the movement of the laser to determine the 6 deflection of the cantilever. Using this method, five mechanical parameters can be quantified: elastic modulus (Eelastic), instantaneous modulus (E0), relaxed modulus (ER), apparent viscosity (µ), and height (h) [10]. Briefly, Eelastic is the measure of a cell’s resistance to deformation; a more compliant cell has a lower Eelastic. E0 is the initial resistance to deformation, and ER denotes the stiffness of the cell at equilibrium. Lastly, µ represents the deformation of a cell over the 30 second stress application. E0 and ER represent viscoelastic properties that better describe the time-dependent characteristics of a cell. A modified Hertz model (Eq. 1) is used to define the elastic modulus, Eelastic, where F is the applied force, δ is the indentation, R is the relative radius the bead at the tip of the cantilever that comes in contact with the cell (Eq. 2), and υ is the Poisson’s ratio, assumed to be 0.5 for incompressible materials [9]. C is a thin-layer correction factor relating indentation depth, tip radius, and sample thickness. The relative radius is described as the contact point between the probe tip and the cell, where h is the height of the cell. The parameters ER (Eq. 3), E0 (Eq. 4), and µ (Eq. 5) can be determined using a thin-layer, stress relaxation model of a viscoelastic solid, where τσ and τε are the relaxation times under constant load and deformation, respectively [9]. 4𝑅𝑅 1⁄2 𝐸𝐸𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 1 1 𝐹𝐹(δ) = δ3⁄2 𝐶𝐶 (1) 𝑅𝑅 = (𝑅𝑅 + ℎ� )−1 (2) 3(1−υ2 ) 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 2 3⁄2 4𝑅𝑅 1⁄2 δ0 𝐸𝐸𝑅𝑅 τσ − τε τσ − τε 𝐹𝐹(𝑡𝑡) = (1 + 𝑒𝑒 −𝑡𝑡⁄τε ) (3) 𝐸𝐸0 = 𝐸𝐸𝑅𝑅 (1 + ) (4) 3(1−υ) τε τε µ = 𝐸𝐸𝑅𝑅 (τσ − τε ) (5) 7 1.2.3 Assessing heterogeneity of mechanophenotype of adipose derived stem cells Adipose tissue is a promising source of mesenchymal stem cells for regenerative applications because of its abundance, high stem cell-yields, relatively non-invasive surgeries for isolation, and ability to be used autologously [20, 38]. The stem cell population derived from adipose tissue, known as adipose derived stem cells (ASCs), has the ability to differentiate along mesodermal lineages, and others such as epithelial and neuronal.[2, 31] The tissue is also easily obtained from the numerous liposuction surgeries performed annually. While this is an extremely useful cell source for regenerative therapies, groups studying ASCs have varying definitions for the cell population [32]. Some studies use the entire cell population isolated from adipose tissue, more commonly known as the stromal vascular fraction (SVF). Other groups use a subgroup of the SVF isolated based on surface markers. Lastly, others use passaging as a purification method to yield their final ASC population. Major limitations, such as inherent variation in physical and molecular phenotypes, temporal changes in surface markers [28]. and lack of specific antibodies for ASCs, exist across all current isolation procedures and consequently restrict translational and clinical applications [4]. Previous work in our lab has shown mechanophenotype to be a marker for lineage-specific differentiation, with compliant cells expressing increased adipogenic markers, while less compliant cells exhibiting a tendency towards osteogenic differentiation [19]. Assessing the heterogeneity within the cell types present in the SVF, 8 with respect to mechanophenotype, could be the first step to defining population with specific differentiation potentials. 1.2.4 Mechanosensing of the microenvironment through integrins and cadherins Integrins are transmembrane proteins that facilitate cell-cell and cell-ECM interactions. They have two distinct components, α- and β- subunits, which allow for binding specificity and mechanosignal transduction [33]. Furthermore, integrins permit bidirectional cell signaling by regulating binding to the ECM intracellularly and transmitting signals from the ECM into the cell [18, 35]. These signals not only regulate cytoplasmic kinases, growth factor receptors, and ion channels, but also control the organization of the intracellular actin cytoskeleton for regulation over cellular activities such as adhesion, proliferation, cell shape, motility, gene expression, and differentiation [18, 35]. Specifically, integrins’ mechanosensing abilities facilitate cells to preferentially migrate to areas of increase stiffness, or durotaxis. Cadherins are also transmembrane proteins that facilitate cell-cell adhesions and bind cells within tissues [5]. They form cell layers and assemblies and are the adhesive mechanism for tissue-specific structures. Cadherins are directly linked to the actin cytoskeleton as well, through coupling proteins, such as β-catenin, α-catenin, and vinculin [35]. Both integrins and cadherins act as points of adhesion for cells and as sensors of physical cues [27]. These cues control RhoA activity, a small GTPase that regulates various cellular structure and functions, including actin cytoskeletal organization, cell motility, cell division, and tissue repair [24]. The RhoA pathway is directly involved in the regulation 9 of actin polymerization and stabilization. Actin is a protein that is functional when it forms microfilaments and provides basic structure to cells. It is essential for many cellular processes including cell motility, cell division, cell signaling, establishing and maintaining cell adhesion sites, and cell shape [27]. The actin cytoskeleton plays a prominent role in cellular force generation during cell-matrix adhesion. In vitro studies controlling various ECM components, including substrate stiffness and spatial distribution of ECM ligands revealed that cells grown on compliant substrates do not form actin stress fibers, while cells cultured on stiff substrates form stress fibers and focal adhesions [29]. These extrasensory proteins, cadherins and integrins, provide cues to cells for maintenance of cellular and tissue structure, and signals cells to sense and respond to changes in their microenvironments. While both cadherins and integrins function similarly and activate many of the same signaling pathways, they act as junctions in an interdependent adhesive network, where modulation of one component influences the adhesive function and signaling activities of other elements in the network [35]. 1.2.5 3D culture systems as tumor models Recently, 3D culture systems have been widely used to gain greater clinical relevance for in vitro experiments [1]. Specifically, three-dimensional (3D), multi-cell spheroids recapitulate many characteristics of in vivo avascular tumors, such as cellular heterogeneity and organization, changes in gene expression levels and proliferation in different parts of the spheroid, natural extracellular matrix deposition, and increased cell- cell and cell-matrix interactions [7, 21, 26]. Additionally, these models create oxygen and nutrient gradients, as well as the hallmark layers of avascular regions within a tumor: the 10 proliferation zone at the surface, followed by the senescent zone, and finally the necrotic zone in the core of the tumor [7, 26]. Of particular interest, deposition of ECM creates a barrier to entry for drugs, nanoparticles, microparticles, etc., which limits treatment options in vivo. The ability to successfully penetrate these 3D tumor models would allow for uniform delivery of drugs throughout a spheroid in vitro, or a tumor in vivo. 1.3 Closing Remarks The role of inherent mechanophenotype in varying microenvironments has not been well characterized, but this is an important consideration for tissue engineered constructs, cancer progression, and wound healing applications. This work provides greater understanding of inherent mechanophenotype properties of heterogeneous cell populations as well as cellular organization in relation to cellular mechanophenotype. Prior to our work, the regenerative properties of SVF cells, a clinically relevant cell population, with resident cell-types of varying mechanophenotype, had not been investigated. Defining these parameters and providing a direct link between cell mechanics and differentiation will give insight into uses of label-free and alternative biomarkers for sorting cells of interest [11, 22]. While defining the mechanophenotype of cell-types is important, our next step was to understand how this parameter played a role in interactions with neighboring surfaces. When combining cells with specific tissue engineered constructs, it may be necessary to consider not only the extracellular components, such as the biomaterial and other soluble factors, but also inherent cellular properties, such as mechanophenotype and cell adhesion mechanisms. Ideally, defining this link can give rise to more effective implantable polymers that provide a natural mechanical barrier from attachment of unwanted cells 11 and/or allowing development of specific cell-cell or cell-substrate interactions. Mechanophenotype is an often-overlooked cellular property that can provide insight into many different tissue states, including those in homeostasis or undergoing various pathologies. 12 1.4 References 1. 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Lab on a Chip. 11(5): p. 912-920, 2011. 15 23. Kanthilal, M. and Darling, E.M., Characterization of Mechanical and Regenerative Properties of Human, Adipose Stromal Cells. Cellular and Molecular Bioengineering. 7(4): p. 585-597, 2014. 24. Kloc M., L.X.C., & Rafik M. Ghobrial, RhoA Cytoskeletal Pathway to Transplantation. Journal of Immunology and Clinical Research. 2(1): p. 1012, 2014. 25. Lin, H.H., Lin, H.K., Lin, I.H., Chiou, Y.W., Chen, H.W., Liu, C.Y., Harn, H.I., Chiu, W.T., Wang, Y.K., Shen, M.R., and Tang, M.J., Mechanical phenotype of cancer cells: cell softening and loss of stiffness sensing. Oncotarget. 6(25): p. 20946-58, 2015. 26. Lovitt, C.J., Shelper, T.B., and Avery, V.M., Advanced cell culture techniques for cancer drug discovery. Biology (Basel). 3(2): p. 345-67, 2014. 27. Marjoram, R.J., Lessey, E.C., and Burridge, K., Regulation of RhoA activity by adhesion molecules and mechanotransduction. Curr Mol Med. 14(2): p. 199-208, 2014. 28. Mitchell, J.B., McIntosh, K., Zvonic, S., Garrett, S., Floyd, Z.E., Kloster, A., Di Halvorsen, Y., Storms, R.W., Goh, B., Kilroy, G., Wu, X., and Gimble, J.M., Immunophenotype of human adipose-derived cells: temporal changes in stromal- associated and stem cell-associated markers. Stem Cells. 24(2): p. 376-85, 2006. 29. Schwarz, U.S. and Gardel, M.L., United we stand: integrating the actin cytoskeleton and cell-matrix adhesions in cellular mechanotransduction. J Cell Sci. 125(Pt 13): p. 3051-60, 2012. 16 30. Solon, J., Levental, I., Sengupta, K., Georges, P.C., and Janmey, P.A., Fibroblast adaptation and stiffness matching to soft elastic substrates. Biophys J. 93(12): p. 4453-61, 2007. 31. Strem, B.M., Jordan, M.C., Kim, J.K., Yang, J.Q., Anderson, C.D., Daniels, E.J., Hedrick, M.H., Roos, K.P., Schreiber, R.E., Fraser, J.K., and MacLellan, W.R., Adipose tissue-derived stem cells enhance cardiac function following surgically- induced myocardial infarction. Circulation. 112(17): p. U330-U330, 2005. 32. Strioga, M., Viswanathan, S., Darinskas, A., Slaby, O., and Michalek, J., Same or Not the Same? Comparison of Adipose Tissue-Derived Versus Bone Marrow- Derived Mesenchymal Stem and Stromal Cells. Stem Cells and Development. 21(14): p. 2724-2752, 2012. 33. Vicente-Manzanares, M., Choi, C.K., and Horwitz, A.R., Integrins in cell migration--the actin connection. J Cell Sci. 122(Pt 2): p. 199-206, 2009. 34. Wang, X., Wang, J., Liu, Y., Zong, H., Che, X., Zheng, W., Chen, F., Zhu, Z., Yang, D., and Song, X., Alterations in mechanical properties are associated with prostate cancer progression. Med Oncol. 31(3): p. 876, 2014. 35. Weber, G.F., Bjerke, M.A., and DeSimone, D.W., Integrins and cadherins join forces to form adhesive networks. J Cell Sci. 124(Pt 8): p. 1183-93, 2011. 36. Weder, G., Hendriks-Balk, M.C., Smajda, R., Rimoldi, D., Liley, M., Heinzelmann, H., Meister, A., and Mariotti, A., Increased plasticity of the stiffness of melanoma cells correlates with their acquisition of metastatic properties. Nanomedicine. 10(1): p. 141-8, 2014. 17 37. Wells, R.G., The role of matrix stiffness in regulating cell behavior. Hepatology. 47(4): p. 1394-400, 2008. 38. Zuk, P.A., Zhu, M., Mizuno, H., Huang, J., Futrell, J.W., Katz, A.J., Benhaim, P., Lorenz, H.P., and Hedrick, M.H., Multilineage cells from human adipose tissue: Implications for cell-based therapies. Tissue Engineering. 7(2): p. 211-228, 2001. 18 Chapter 2 2 Characterization of mechanical and regenerative properties of human, adipose stromal cells Cellular and Molecular Bioengineering. 2014 Aug 5; 7:585-597. doi: 10.1007/s12195-014-0350-y Manisha Kanthilal1,2 and Eric M. Darling1,2,3,4 1 Center for Biomedical Engineering, Brown University, Providence, RI 02912 2 Department of Molecular Pharmacology, Physiology, & Biotechnology, Brown University, Providence, RI 02912 3 Department of Orthopaedics, Brown University, Providence, RI 02903 4 School of Engineering, Brown University, Providence, RI 02912 Abbreviated title Characterization of human, adipose stromal cells 19 2.1 Abstract The stromal vascular fraction (SVF) of human adipose tissue is a heterogeneous population, with component cell types that may or may not contribute to its regenerative potential. Recent findings indicate that single-cell mechanical biomarkers are characteristic of cell type and can be used comparably to gene and protein expressions to identify cell populations. In this study, we characterized mechanical properties and differentiation potential of cell types present in the SVF. Fluorescence-activated cell sorting was used to isolate four distinct populations based on surface markers: endothelial cells (EC), adipose- derived stem cells (ASCs), pre-adipocytes, and smooth muscle cells (SMC). Atomic force microscopy was used to mechanically characterize sorted cell populations and unsorted SVF. Differentiation capabilities of sorted and unsorted populations were evaluated by quantifying lipid production and calcified matrix deposition. Cells populating the SVF exhibited a range of mechanical properties, with ECs, ASCs, pre-adipocytes, and unsorted SVF cells being significantly more compliant than SMCs. Lineage-specific metabolite production was most robust in SVF cells, followed by ASCs, with the other cell types showing little or no potential, suggesting the unsorted populations may benefit from a paracrine response that is lacking once the cells are sorted into more uniform cell populations. Key terms adipose-derived stem cell; stromal vascular fraction; atomic force microscope; cell mechanics; differentiation; human lipoaspirate; mechanical biomarkers 20 2.2 Introduction Adipose tissue is a promising source of mesenchymal stem cells (MSCs) for regenerative therapies and tissue engineering applications due to its abundance, relatively non-invasive surgical procedures, and high cell yields [17, 42]. The tissue is readily available from liposuction surgeries as waste tissue, known as lipoaspirate. These adipose- derived stem cells (ASCs) can be used autologously with limited negative immune response and have the ability to differentiate along mesodermal lineages as well as other lineages such as epithelial, endothelial, and neuronal [1, 33]. A major limitation in utilizing ASCs in clinical applications is the lack of a clear set of parameters that define the stem cell population, compounded by limited research in this area as well as contradicting studies. Some researchers use the entire unpurified cell population from the lipoaspirate, called the stromal vascular fraction (SVF), while others purify the SVF to acquire a more specific and pure ASC population [34]. The SVF is a heterogeneous population that includes multipotent stem cells, smooth muscle cells, endothelial cells, and other circulating cell types such as red and white blood cells and hematopoietic stem cells [14, 41]. Current ASC enrichment techniques include monolayer expansion and surface marker-based sorting. Cultured ASCs grown in monolayers are defined by their ability to adhere to plastic surfaces and fast proliferation rates, but this method is not ideal for clinical applications since expanding cell numbers to therapeutically relevant numbers can take weeks. However, this technique works well for enrichment because any non-adherent cell types (e.g., circulating red and white blood cells) are washed away, and the higher proliferation rate of ASCs helps them take over the culture with time. It should also be 21 noted that ASCs in vitro are not immortal and eventually undergo senescence, lower proliferation rates, and decreased differentiation potential [2, 22]. Fluorescence-activated cell sorting (FACS) using surface makers is another technique utilized to sort ASCs. While arguably the gold standard approach, FACS-based enrichment of ASCs can be problematic since surface markers for mesenchymal stem cells are constantly changing with passage, overlap with other cell populations present in adipose tissue, and often lead to low cell yields since everything but the specified combination of markers are eliminated [17, 26, 27]. Recent findings from our lab and others indicate that single-cell mechanical biomarkers can be used to distinguish among diverse cell populations, disease states, and tissue sources, in a manner similar to gene and protein expression profiles [6-8, 15, 36]. These characteristics are strongly influenced by the cell’s physiological and structural functions. Specifically, mechanical properties are dependent on cytoskeletal make-up and the level of actin organization [25]. Studies using atomic force microscopy (AFM) for single-cell analysis have shown that mechanical biomarkers can indicate cell type, predict differentiation potential of stem cells, and reflect cytoskeletal reorganization [6, 15, 39]. Maintaining ASCs in a truly undifferentiated state in culture is challenging since the cells can be affected by many factors, including plating densities, protein coatings on culture dishes, substrate stiffness, and growth media compositions [2]. To eliminate the need for culturing, it would be beneficial to develop a method for immediate ASC enrichment following SVF isolation. Since mechanics play an important role in cell properties and correlate with lineage-specific differentiation potentials, our long-term hypothesis is that a mechanics-based approach may be beneficial [15, 36]. However, to 22 determine the feasibility of such a technique, the mechanical properties of the cell types present in the SVF must first be defined. The goal of this study was to characterize mechanical properties and differentiation potential of component cell types present in the SVF. This was accomplished by sorting non-expanded, human SVF cells into four different populations classified as ASCs, endothelial cells (ECs), smooth muscle cells (SMCs), and pre-adipocytes, followed by characterization of elastic and viscoelastic properties for each of the sorted populations and unsorted SVF cells using AFM. Differentiation potential of the sorted cell types and the unsorted SVF was assessed based on lipid production for adipogenesis and calcified matrix deposition for osteogenesis. 2.3 Materials and Methods 2.3.1 SVF Isolation Human adipose tissue was obtained as lipoaspirate from collaborators at Rhode Island Hospital following an approved protocol (IRB Registration #0000396, 00004624; CMTT/PROJ: 210312). Samples were originally from the abdomen or outer thigh regions, harvested via liposuction from seven female donors with a prior diagnosis of breast cancer (mean age 51; range 34-62 years). Approximately 250 mL of adipose tissue was processed from each donor. Lipoaspirate was processed according to published methods with minor modifications [12]. Briefly, to isolate the SVF, samples were washed 5-7 times with equal volumes of warm phosphate buffered saline (PBS) to remove blood and tumescent fluid. The tissue was then digested with equal volumes of a collagenase solution (0.1% (wt/vol) 23 collagenase, 1% (vol/vol) Bovine Serum Albumin (BSA, Invitrogen) (Fraction V) and 2 mM calcium chloride) in PBS for 1 hour on a shaker at 37°C. Following incubation, the digested tissue was centrifuged at room temperature at 300g for 5 minutes. The supernatant containing lipids and mature, buoyant adipocytes was aspirated. The remaining pellet was resuspended and washed in stromal medium (DMEM/F-12, 10% Fetal Bovine Serum (FBS, Zen-Bio), and 1% antibiotic/antimycotic (A/A)). The resuspended cells were filtered sequentially through 100 µm and 70 µm filters, followed by a 10 minute incubation in red blood cell lysis buffer (155 mM ammonium chloride, 10 mM potassium carbonate and 0.1 mM EDTA). After centrifugation at 400g for 5 minutes, the isolated cells, identified as the SVF, were washed once in stromal media before freezing them in 80% FBS, 10% stromal media, and 10% dimethyl sulfoxide (DMSO) at -80°C in an isopropyl alcohol insulated container, and subsequently stored in liquid nitrogen. 2.3.2 Cell sorting SVF samples were sorted by FACS into constituent cell types according to their surface markers. SVF cells from each donor were thawed rapidly in a 37°C water bath and transferred to 10 mL of warm stem cell expansion media (DMEM/F-12, 10% FBS, 5 ng/ml human epidermal growth factor, 1 ng/ml recombinant human fibroblastic growth factor, basic, 0.25 ng/ml transforming growth factor-β1, and 1% A/A) [12]. All growth factors were purchased from R&D systems. Cells were counted with a hemocytometer and viability determined using Trypan Blue (viability was typically >60%, consistent with other studies [27]). Cells were washed twice in ice-cold wash buffer (1x PBS, 1% bovine serum albumin (BSA)), resuspended in 24 cold blocking buffer (1x PBS, 3% BSA), and incubated for 10 minutes on ice. Following a wash, 150,000 cells in 100 µl were aliquoted into separate tubes for negative and single color controls. The remaining cells were aliquoted for multi-antibody stains and sorting. Pre-conjugated antibodies against the following antigens were used from BD Pharmingen at recommended concentrations: CD34-FITC (#560942), CD31-PE (#560983), CD45-PE- Cy5 (#560974), CD36-PerCP-Cy5.5 (#561536), CD146-PerCP-Cy5.5 (#562134). The combination of antibodies used to sort each cell type is described in Table 1 [4, 13, 24, 26, 27, 37, 38]. The cells were incubated with antibodies on ice for 20 minutes in the dark, followed by rinsing with ice-cold wash buffer. The sort was performed on a FACSAria IIu, and data were analyzed using FlowJo (Tree Star Inc.). Sorted cells were collected into tubes containing expansion medium with 20% FBS. 100,000 sorted cells were plated on glass cover slips in 50 x 9 mm, non-tissue culture treated dishes (BD Falcon) and allowed to adhere to the glass surface for 45 minutes prior to mechanical testing. Table 2.1 Summary of antibody combinations used for FACS. Cell Type Positive Markers Negative Markers ASC CD34 CD45, CD31 Endothelial Cell (EC) CD34, CD31 --- Smooth Muscle Cell (SMC) CD146 CD31 Pre-adipocytes CD36 CD31 For the purposes of clarity, this manuscript refers to sorted cell populations by “Cell Type” rather than their surface marker designation. However, it is possible that some cells 25 exhibiting the stated surface antigens may or may not truly be that cell type (e.g., CD34+/CD45-/CD31- may not exclusively be ASCs). The CD36+/CD31- cell population were classified as pre-adipocytes since mature adipocytes were eliminated during the cell isolation process described earlier, and CD36 expression is present upon activation of adipogenic differentiation [13]. 2.3.3 Mechanical Characterization of sorted SVF cells Single-cell mechanical testing was performed using an atomic force microscope (AFM, MFP-3D-Bio, Asylum Research, Santa Barbara, CA) based on previously published techniques, with minor modifications [6, 7, 15]. Briefly, spherically tipped cantilevers were made by adhering 5 µm diameter, borosilicate glass beads to the end of tipless, silicon nitride cantilevers (Bruker Corporation, MLCT-O10, k~0.03 N/m). Cantilever spring constants (average, calibrated value of 0.027 N/m) were calculated based on the power spectral density of the thermal noise fluctuations prior to each experiment [21]. These cantilevers were used to mechanically probe single cells over their perinuclear region for elastic indentation and viscoelastic stress relaxation tests. An approach velocity of 10 µm/s was used, with a 30 s relaxation period. Trigger forces ranged between 0.75- 1.5 nN, which limited indentations to <10% strain based on the height of the cell. All tests were done at room temperature Once sorted, each cell type was allowed to adhere to a glass surface for approximately 45 minutes. At this time, the cell’s spherical morphology was confirmed visually by phase contrast microscopy. Cells were mechanically characterized within 1.5 hours of adhering to the surface, such that a rounded cell shape existed but no movement 26 occurred during the testing procedure. Five mechanical parameters were quantified: elastic modulus (Eelastic), instantaneous modulus (E0), relaxed modulus (ER), apparent viscosity (µ), and height (h). Briefly, Eelastic is the measure of a cell’s resistance to deformation; a more compliant cell has a lower Eelastic. E0 is the initial resistance to deformation, and ER denotes the stiffness of the cell at equilibrium for a stress relaxation test. Lastly, µ represents the deformation resistance of the cell over time; a higher viscosity indicates slower deformation or flow under a given load. A Hertz model appropriate for spherical indentations (Eq. 1) was used to determine the elastic modulus, Eelastic [10]: 4𝑅𝑅 1⁄2 𝐸𝐸𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝐹𝐹(δ) = δ3⁄2 𝐶𝐶, (1) 3(1−υ2 ) where F is the applied force, δ is the indentation, R is the relative radius (Eq. 2), and υ is the Poisson’s ratio, assumed to be 0.5 for incompressible materials. C is a thin-layer correction factor relating indentation depth, tip radius, and sample thickness [10]. The relative radius accounts for the curvature of the probe tip and cell at the point of contact: 1 1 𝑅𝑅 = (𝑅𝑅 + ℎ� )−1 , (2) 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 2 where h is the height of the cell. The relaxed modulus (ER, Eq. 3), instantaneous modulus (E0, Eq. 4), and apparent viscosity (µ, Eq. 5) were determined using a thin-layer, stress relaxation model of a standard linear solid, where τσ and τε are the relaxation times under constant load and deformation, respectively [7, 8]. 3⁄2 4𝑅𝑅 1⁄2 δ0 𝐸𝐸𝑅𝑅 τσ − τε 𝐹𝐹(𝑡𝑡) = (1 + 𝑒𝑒 −𝑡𝑡⁄τε ) (3) 3(1−υ) τε τσ − τε 𝐸𝐸0 = 𝐸𝐸𝑅𝑅 (1 + τε ) (4) µ = 𝐸𝐸𝑅𝑅 (τσ − τε ). (5) 27 2.3.4 Multipotency assessment To determine the multipotency of the unsorted SVF and sorted ASCs, the cell populations were differentiated along adipogenic and osteogenic lineages. Isolated pre- adipocytes, SMCs, and ECs were terminally differentiated or lineage-committed cell types. To determine if these cell types had trans-differentiation capabilities, the pre-adipocytes, SMCs, and ECs were also introduced to adipogenic and osteogenic induction factors. 2.3.4.1 Adipogenic Differentiation Cells from a representative donor were used to evaluate the multipotency of individual cell types in freshly isolated SVF. Frozen cells were thawed and sorted using the markers defined in Table 1. Each sorted cell type was seeded in a 96-well plate at a density of 2,000-8,000 cells per well and allowed to grow for 5-7 days before inducing adipogenic differentiation. Unsorted SVF cells were differentiated concurrently as well. All cells were incubated for 14 days in either adipogenic medium (DMEM/F-12, 10% FBS, 10 µM insulin, 1 µM dexamethasone, 0.25 mM isobutyl-1-methylxanthine, 200 µM indomethacin (Sigma-Aldrich) and 1% A/A) or control medium (DMEM/F-12, 10% FBS, 1% A/A) [40]. After 14 days of culture, cells were fixed with 10% formalin, and differentiation was visualized with Oil Red O staining (ORO, Sigma-Aldrich) to assess lipid accumulation in induced and control samples. Images were analyzed with a custom MATLAB program using the built-in Image Processing Toolbox to detect and measure lipid droplet size. Lipid size was used as a metric to assess adipogenesis since positive differentiation is characterized by an increase in intracellular lipids, specifically large droplets. The percentage of cells in each sample exhibiting a rounded morphology was 28 manually calculated (confluent, monolayer cultures were considered to be 0% rounded and 100% spread based on visual observation). ORO dye was eluted from each sample and measured at 500 nm using a spectrophotometer to obtain quantitative, optical density values. Lastly, cell nuclei were stained with 4’,6-diamino-2-phenylindole (DAPI, Thermo Fisher Scientific), counted, and used to normalize optical densities on a per-cell basis [5]. 2.3.4.2 Osteogenic Differentiation For osteogenic differentiation, SVF cells were thawed, sorted, and plated as for adipogenesis. Sorted ASCs, ECs, SMCs, pre-adipocytes, and unsorted SVF cells were incubated for 21 days in either osteogenic medium (DMEM/HG, 10% FBS, 10 mM β- glycerophosphate, 0.15 mM ascorbate-2-phosphate, 10 nM dexamethasone, and 1% A/A) or control medium [18]. After 21 days of culture, cells were fixed with 10% formalin, and differentiation was visualized with Alizarin Red S staining (ARS, Sigma-Aldrich) to assess calcified matrix deposition in induced and control samples. As with adipogenesis, the percentage of cells exhibiting spread versus rounded morphologies was quantified. After imaging the wells, the ARS dye was eluted from each sample and measured at 540 nm using a spectrophotometer for quantification. Lastly, cell nuclei were stained with DAPI, counted, and used to normalize optical density measurements on a per-cell basis [5]. 2.3.5 Statistical Analysis All statistical analysis was performed in SigmaPlot 12.3 (Systat Software Inc.). Data throughout study are presented as arithmetic mean ± standard deviation (SD). Mechanical data collected from each of the four, cell type populations were not normal, 29 according to the Shapiro-Wilk test. Non-parametric analysis was performed using a Kruskal-Wallis analysis of variance (ANOVA) on ranks, followed by Dunn’s test for multiple comparisons with a significance of p < 0.05. Height data collected for the cell types was found to be normal using the Shapiro-Wilk test and was analyzed using a one- way ANOVA, followed by a Fisher LSD post-hoc test with a significance of p < 0.05. Student’s t-tests were performed for differentiation data to compare induced and control conditions within cell types. A two-way ANOVA, followed by a Duncan's Multiple Range post-hoc test was performed to compare osteogenic differentiation between the unsorted SVF and four, individual sorted cell types. 2.4 Results 2.4.1 Sorting of Cells in the SVF SVF cells were sorted via FACS into four distinct populations based on previously reported surface marker characteristics [23, 32, 38]. Either two- or three- color labeling was used to define each of the cell types. On average, ~75% of the entire cell population was used in downstream gating schemes to eliminate debris, dead cells, and cell aggregates based on the forward and side scatter plot (Figure 1A). Single CD marker controls were first run for CD34, CD31, CD45, CD146, and CD36 to determine expression levels of each within the SVF (Figure 1B-F). When double- and triple-stained SVF cells were sorted into four distinct populations, noticeable variation was observed in percentage of each cell types among the seven donors (Figure 1G-K). Overall, the largest fraction of cells in the SVF were ASCs, followed by ECs, pre-adipocytes, and SMCs (Figure 1L). 30 Figure 2-1 Multi-color sorts of SVF cells based on protein expression using FACS. (A) Distribution of cells, plotted as forward (cell size) vs. side scatter (granularity). The population within the gate "Cells" represented ~75% of total events and was used for downstream gating strategies for dot plots and histograms. (B-F) Cells were analyzed for expression of CD34-FITC, CD31-PE, CD45-PE-Cy5, CD36-PerCP-Cy5.5, and CD146- PerCP-Cy5.5. Each histogram plot depicts a control, unstained, SVF population in red and a stained SVF population in blue. Percent positive cells are shown. (G-I) Three-color FACS was used to sort SVF samples for ASCs (CD34+/CD31-/CD45-, green) and ECs (CD34+/CD31+, red). (J-K) Double-color analysis was used to sort SVF samples for SMCs (CD146+/CD31-, blue) and pre-adipocytes (CD36+/CD31-, yellow). (L) Mean ± SD of each sorted cell type across the seven donors. 31 2.4.2 Characterization of Mechanical Properties of Cells in SVF Following cell sorting, the mechanical properties of four adherent cell types in the SVF were measured using AFM. Testing was also conducted on the unsorted SVF from each donor. Five parameters were measured to obtain a complete panel of elastic and viscoelastic properties. 109 ECs, 135 ASCs, 129 pre-adipocytes, 110 SMCs, and 105 unsorted, SVF cells were tested in total from all seven donors in approximately equal proportions. As expected, different cell types that reside within adipose tissue exhibited a range of mechanical properties. The results indicated that cell populations in adipose tissue vary in compliance, apparent viscosity, and height (Figure 2). SMCs exhibited Eelastic, ER, and E0 values three times that of ASCs, ECs, and pre-adipocytes. While the apparent viscosity (µ) exhibited large variability regardless of cell type, as has been observed before [6], a statistically significant difference did exist between ECs and SMCs, with the latter being twice as viscous as the former (p < 0.05). Furthermore, SMCs were 10-15% smaller in height than ASCs, ECs, and pre-adipocytes (Figure 2 Inset, p < 0.05). Pre-adipocytes were also about 6% smaller than ECs. SVF cells showed similar mechanical properties to pre-adipocytes, ECs, and ASCs. By using the percentage splits determined from FACS among the cell populations, we can calculate a composite elastic modulus for all cells present in the SVF, 0.8 kPa. This is approximately the same as the measured value of 0.7 kPa for unsorted SVF cells. Variability in mechanical properties among the seven donors was noticeable; however, the overall trend for Eelastic, E0, ER, µ, and cell height among the cell types was consistent (Supplemental Figure 1). Eelastic was determined by fitting a modified, Hertz model to the initial indentation response of individual cells (Figure 2B). 32 The viscoelastic parameters, E0, ER, and µ, were extracted using the 30 second relaxation phase of the single-cell test (Figure 2C). Figure 2-2 Biomechanical properties of the unsorted SVF and sorted cell types residing in adipose tissue for seven donors. (A) Mean ± SD of each of the elastic and viscoelastic properties of the four cell types are shown (*p<0.05, † p<0.05 as determined by Kruskal- Wallis ANOVA on ranks, followed by Dunn’s test for multiple comparisons). On average, SMCs displayed Eelastic, E0, and ER values three times those of ASCs, ECs, and pre- adipocytes. SMCs also exhibited µ values twice that of ECs. (Inset) Cell heights showed that SMCs were also significantly shorter than ECs, ASCs, pre-adipocytes, and unsorted SVF cells. Average height ± SD for each cell type is shown (Unmatched letters are 33 significant from each other, p < 0.05); determined by a one-way ANOVA and Fisher LSD post hoc test. Overall, SMCs were less compliant and smaller than the other sorted cell types. Mechanical properties of SVF cells were representative of its component cells. (B, C) Representative, individual cells from the unsorted SVF and sorted cell populations illustrate the mechanical trends of the overall population, with SMCs portraying a less compliant phenotype than other cell types for elastic and viscoelastic tests. 2.4.3 Differentiation of Cells in SVF To compare the multilineage differentiation potential of the four sorted populations and the unsorted SVF, isolated cells were induced for adipogenesis and osteogenesis. Qualitatively, a clear difference was observed between induced SVF and ASC samples over their respective controls, with adipogenic conditions resulting in large lipid droplets forming in the cells compared to uniformly distributed, small, intracellular lipid droplets (Figure 3A). When comparing optical densities of eluted ORO stain of induced versus control wells as a whole, only the SVF and ASCs exhibited lipid production, with the controls displaying higher optical densities than induced wells (p<0.05, Figure 3B). To account for differences due to cell numbers, the optical densities for ORO stain were normalized to 10,000 cells per well for further interpretation (Figure 3C). Based on this measure, induced ASCs produced significantly more lipids than controls (p < 0.05), and while increased lipid production was visually observed in induced SVF cells than controls, the difference did not reach a level of statistical significance (p = 0.112). Differences in lipid production were not observed between induced and control cells for ECs, pre- adipocytes, and SMCs. Quantitative analysis of mean lipid area between induced and control samples showed a clear difference existed for SVF cells and ASCs (p<0.001, Figure 3D) but not for other cell types. 34 Figure 2-3 Adipogenic differentiation was assessed by ORO staining of intracellular lipids. (A) Adipogenically induced samples are shown on the top row, with corresponding controls depicted on the bottom row (Scale bar = 200 µm). (B) Optical densities corresponding to eluted ORO stain indicated no significant lipid production occurred in induced samples over controls on a per sample basis. (C) When normalized to the number of cells in each sample, more robust lipid production was observed in sorted ASCs than unsorted SVF cells, ECs, pre-adipocytes, and SMCs (* p < 0.05). (D) Mean lipid droplet size measurements showed induced SVF cells and ASCs produced significantly larger lipids over control cells, which produced smaller, uniformly distributed lipids throughout the samples (* p < 0.05). Data are presented as Mean ± SD. Student’s t-test determined statistical significance. For osteogenesis, qualitatively, a noticeable difference was only observed in induced SVF samples over controls, with osteogenic conditions resulting in significant calcified matrix deposition (Figure 4A). The optical densities for ARS stain corresponding to matrix production were also compared for induced versus control wells on a per well and per cell basis. Only the induced, unsorted SVF cells produced significantly more calcified matrix over its control condition (p<0.05, Figure 4B-C). The induced, unsorted 35 SVF cells also produced significantly more calcified matrix than the four induced, sorted cell types (p<0.001). Figure 2-4 Osteogenic differentiation was assessed by ARS staining of calcified matrix. (A) Osteogenically induced samples are shown on the top row, with corresponding controls depicted on the bottom row (Scale bar = 200 µm). (B) Optical densities corresponding to the eluted ARS stain indicated a robust osteogenic response in SVF cells compared to purified, component cell types (* p < 0.05). (C) When normalized to the number of cells in each sample, more robust calcified matrix deposition was observed in the unsorted SVF cells than sorted ASCs, ECs, pre-adipocytes, and SMCs (* p < 0.05). Data are presented as Mean ± SD. Student’s t-test determined statistical significance. It was also visually observed that few of the SMCs or pre-adipocytes spread, produced lipid, or deposited any matrix. SVF cells undergoing osteogenesis and adipogenesis presented a spread morphology. ASCs undergoing osteogenesis were spread, 36 but for adipogenesis, 47 ± 18% presented a rounded morphology. Regardless of differentiation condition, ECs presented a primarily rounded morphology (adipogenesis: 99 ± 1%; osteogenesis: 78 ± 31%). All SMCs and pre-adipocytes presented only a rounded morphology. The viability of the SVF cells and sorted cell types was tested after plating and prior to differentiation, with >60% being alive. Despite having a rounded morphology, SMCs and pre-adipocytes remained adhered to the culture surface throughout differentiation, which included multiple medium changes. 2.5 Discussion The results of this study indicate that the human SVF is heterogeneous, with subpopulations exhibiting differences in mechanical properties, a range of surface marker expression, and variations in differentiation potential. Overall, significant differences in elastic and viscoelastic properties were observed when comparing unsorted SVF, ASCs, ECs, and pre-adipocytes to SMCs. Dramatic differences in lineage-specific metabolite production between ASCs and unsorted SVF cells suggest that surface marker-based sorting may eliminate supportive cell types necessary for robust differentiation, especially for osteogenesis. The study identified significant differences in mechanical properties between major cell types residing in adipose tissue, which is a first step towards mechanics-based enrichment of specific populations within the SVF. These properties could also provide insight on mechanical differences between terminally differentiated cell types and cells in a progenitor state. Cells were mechanically characterized in a spherical morphology to assess their properties with minimal contribution to mechanics from their 37 microenvironment. Therefore, the properties identified can be translated more easily to a suspension state suitable for high-throughput cell sorting techniques, while limiting the influence various morphologies of spread cells have on measured properties. Furthermore, in the spherical morphology, all cells have nominally the same shape in the same conditions, providing a means to compare across cell types. Importantly, it has been previously shown that cells exhibit distinct mechanical biomarkers in the spherical morphology [15]. By allowing the cells to adhere to glass coverslips for only 45 minutes, the cells do not have enough time for substantial cytoskeletal reorganization, including formation of large actin filament bundles, and mechanical properties obtained can be more confidently related to their suspended state mechanics [7, 8]. Microfluidics-based platforms can be used to sort these cells based on their elastic properties and deformation through multiple methods, most of which capitalize on fluid shear forces and inertial focusing [11, 16, 20, 31]. The ability to sort on such a platform would also eliminate the need to immunolabel cells prior to FACS. While properties obtained through AFM will not fully translate to cells in suspension, these data still provide a comparable starting point, as shown by studies comparing micropipette aspiration, where cells are completely in suspension, to AFM testing, where cells are slightly adhered to a surface [8]. For comparison, a previously reported elastic modulus for ECs determined using micropipette aspiration is approximately 0.5 kPa, while the AFM technique used in this study calculated Eelastic as 0.7 kPa [19]. Similarly, pre-adipocytes had an Eelastic of 0.8 kPa, as reported in this study, which is similar to the previously determined 0.9 kPa, also calculated on spherical cells using AFM [6]. To our knowledge, micropipette aspiration studies have not been performed on SMCs, so a valid comparison of elastic moduli in their 38 spherical state cannot be made. Variations are possibly due to differing techniques, conditions used from study to study, and differences in the tissue and donor source of each cell type. The SVF isolated from lipoaspirate was also confirmed to be a heterogeneous population with relation to their cells' surface marker profile. The sorted populations analyzed in this study accounted for ~70% of the entire SVF, and although not investigated as part of this study, we hypothesize the remaining ~30% of the SVF primarily contains a CD45+ hematopoietic lineage population based on previously published studies [24, 26]. The cellular composition of the SVF, as defined by percentage of the whole cell population, varied from donor to donor. The range for ASCs spanned from 18% to 61%, ECs 5% to 31%, pre-adipocytes 2% to 10%, and SMCs 1% to 4%. Other groups using similar surface marker profiles also reported a high degree of variability among donors [24, 26, 27, 38]. The surface marker profile for the “cell types” selected for these studies was designed to be broad to include progenitor cells that more definitive profiles would eliminate. However, as mentioned, it is likely that a fraction of cells within each group are not actually of the specified lineage, which inserts some noise into the system. Furthermore, expected surface markers are not always present since they have been shown to change with cell cycle, which could result in the possible elimination of progenitors, emphasizing the need for an alternative means to identify cell phenotype, such as cellular mechanical biomarkers [9, 29]. Tissue source and donor medical history should also be considered as potential sources of variability in cellular properties. While all donors in this study had a prior diagnosis of breast cancer, lipoaspirate was harvested from non-cancerous sites, limiting 39 the potential impact of the disease on observed cellular phenotypes. Our reported mechanical properties and proportions of each cell type within the SVF were similar to those seen in previously published studies with healthy donors [6, 19, 24, 26, 27, 38]. Regardless of health status, cells from the non-discarded tissue were used clinically for reconstructive purposes with good success, indicating these cells are a viable option for regenerative therapies. Based on previous studies, it was expected that the sorted ASC population would have a more significant adipogenic differentiation response compared to the unsorted SVF [23]. When considering the normalized optical density of ORO stain, only the sorted ASCs produced significantly more intracellular lipids compared to control media. However, to account for the large, mature lipid production visible in the induced SVF and ASCs, mean lipid size was determined as an alternative metric for lipid quantification. Both induced SVF cells and ASCs produced lipids over twice the size of lipids formed in control media (p < 0.001), a response not observed in other cell types. While Li et al. did not observe the same response of increased large lipid production from the unsorted SVF, the adipogenic potential of ASCs, defined in the present study as CD34+/CD31-/CD45-, was found to be comparable. The differences in the studies could be due to differing adipogenic induction media used, tissue harvest methods of abdominoplasty instead of liposuction, and donor to donor variability. The higher adipogenic potential of ASCs and the unsorted SVF could be due to an inherently higher expression of adipocyte markers such as peroxisome proliferator-activated receptor-γ and fatty acid binding protein-4 [23]. Both the unsorted SVF and sorted ASCs could therefore be viable options for soft tissue regeneration such as fat reconstruction. 40 The unsorted SVF cells deposited seven times more calcified matrix in induced versus control media. Conversely, the four, sorted populations showed no significant matrix deposition. This finding is also similar to Li et al., who qualitatively showed that cultured, unsorted cells differentiated better than purified, component populations [23]. Additional studies comparing osteogenic differentiation of CD34+ and CD34- populations concluded similar results, showing that the CD34+ population (describing ASCs) did not differentiate as well as CD34- populations [35]. Further study and analysis of the interaction and signaling among other cell types in the SVF, such as endothelial cells and the CD45+ populations, is necessary to fully understand the overall osteogenic potential of unsorted cells. Purification of the SVF based on surface marker profiles may not be ideal for regenerative therapies since cells never exist in the body in a completely pure form. Supportive cell types or cells from other tissues in the local microenvironment could play a role in the proper function of the cells to effect repair [3, 28]. In a study on bone marrow transplantation, Nilsson et al. determined a purified bone marrow stem cell population had lower engraftment than unsorted bone marrow cells, further suggesting the existence of a "non-stem cell facilitator population" [28]. Alternative characteristics like mechanical biomarkers encompass many aspects of the cell and can serve as a secondary characteristic for gene and protein expressions. Other options such as selecting cells based on physical, electrical, or gene expression characteristics may also provide a broader swathe of cell types that will lessen the possibility of "over purification." Alternatively, finding the proper combination of completely pure cell types could allow for highly controlled regenerative 41 procedures since many cells in SVF are already committed to a terminally differentiated state. Culturing conditions were kept consistent across cell types isolated from SVF to allow for comparative analysis. The apparent lack of growth for ECs, SMCs, and pre- adipocytes could be due partially to these culture conditions, although these cells did attach to the surface and remain adhered for the 2-3 weeks of differentiation. Customizing the culture environment for each cell type could produce different results at the expense of a uniform experiment (e.g., surface coating stimulates EC growth and maintenance [30]). It would be expected that that these terminally differentiated and lineage-committed cells should not change even when placed in a lineage-inducing environment. The lack of growth of these cell types support this. Increasing cell density could be beneficial for acquiring a differentiation response due to a larger concentration of paracrine signaling. The goal of this assay was to determine whether significant levels of "trans-differentiation" existed within the sorted cell populations, and the data suggest that this was not the case. While only one representative donor was used to evaluate the differentiation potential of component cell types within SVF, findings were consistent with previously published data using multiple donors [23, 35]. While surface markers alone may not be conclusive for isolating cell populations with robust differentiation potential, the addition of mechanical biomarkers may facilitate enrichment of a therapeutically beneficial cell source. In the current study, lack of adipogenic and osteogenic responses from CD146+ and CD36+ cells indicate they would contribute little to the differentiation response of the overall SVF population. However, it would be interesting to assess differentiation potential of specific combinations of cell 42 types necessary to elicit optimal, regenerative responses. The addition of mechanical biomarkers to this sorting scheme could better refine populations with overlapping and transient surface marker profiles. Previous findings also suggest the cellular mechanical properties may indicate the synthetic potential of a cell and not just its differentiation potential [15]. The dramatic difference in cellular mechanical properties between SMCs and other cell types could provide a means to identify and potentially exclude this cell type. However, researchers should bear in mind that removing integral cell types might actually degrade the regenerative response of a heterogeneous cell population. In the SVF of lipoaspirate, significant variation is present in the mechanical properties of resident cells. Further experiments will be necessary to assess the effectiveness of the combined use of surface markers and mechanical biomarkers via microfluidics and mechanics-based, high- throughput platforms to determine an ideal range of properties for enriched, differentiation- capable cell populations. 43 2.6 Acknowledgements The authors would like to thank Dr. Paul Liu from Rhode Island Hospital for lipoaspirate, and Nicholas R. Labriola for assistance with AFM and development of the MATLAB program for lipid size analysis. This work was supported by awards from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR063642), National Institute of General Medical Sciences (P20GM104937), and National Science Foundation (CAREER Award, CBET1253189). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or National Science Foundation. 2.7 Ethical standards All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5), and approved by Rhode Island Hospital's Institutional Review Board. Informed consent was obtained from all patients providing waste tissue in this study. No animal studies were carried out by the authors for this article. 44 2.8 References 1. Baer, P.C., Adipose-derived stem cells and their potential to differentiate into the epithelial lineage. Stem Cells Dev. 20(10): p. 1805-16, 2011. 2. Baer, P.C. and Geiger, H., Adipose-derived mesenchymal stromal/stem cells: tissue localization, characterization, and heterogeneity. 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Zhu, Y., Liu, T., Song, K., Fan, X., Ma, X., and Cui, Z., Adipose-derived stem cell: a better stem cell than BMSC. Cell Biochem Funct. 26(6): p. 664-75, 2008. 50 42. Zuk, P.A., Zhu, M., Mizuno, H., Huang, J., Futrell, J.W., Katz, A.J., Benhaim, P., Lorenz, H.P., and Hedrick, M.H., Multilineage cells from human adipose tissue: implications for cell-based therapies. Tissue Eng. 7(2): p. 211-28, 2001. 51 2.9 Supplemental Figure Figure 2-5 While variability was observed, overall trends of biomechanical properties measured using AFM across the seven donors tested was conserved. The unsorted SVF cells, ECs, ASCs, and pre-adipocytes, on average, were more compliant and viscous compared to SMCs for the (A) elastic modulus, (B) relaxed modulus, (C) instantaneous modulus, and (D) apparent viscosity. (E) SMCs were observed to be smaller in cell height across all donors compared to the unsorted SVF, ECs, ASCs, and pre-adipocytes. 52 Chapter 3 3 Influence of inherent mechanophenotype on competitive cellular adherence Annals of Biomedical Engineering 2017 Apr 21; 45: 2036. doi: 10.1007/s10439-017-1841-5 Manisha K. Shah1, Iris H. Garcia-Pak1, Eric M. Darling1, 2, 3, 4 1 Center for Biomedical Engineering, Brown University, Rhode Island, USA 2 Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Rhode Island, USA 3 Department of Orthopaedics, Brown University, Rhode Island, USA 4 School of Engineering, Brown University, Rhode Island, USA Abbreviated title: Mechanophenotype and competitive adherence 53 3.1 Abstract Understanding the role of mechanophenotype in competitive adherence of cells to other cells versus underlying substrates can inform such processes as tissue development, cancer progression, and wound healing. This study investigated how mechanophenotype, defined by whole-cell, elastic/viscoelastic properties for the perinuclear region, and cellular assembly are intertwined through the mechanosensing process. Atomic force microscopy was used to characterize the temporal elastic/viscoelastic properties of individual and assembled fibroblasts grown on substrates with elastic moduli above, below, or similar to whole-cell mechanophenotypes measured for three, genetically modified cell lines. All cells were at their most compliant immediately after plating but transitioned to distinct, stiffer mechanophenotypes by Day 1 after acclimation. This mechanical state, and cellular assembly/morphology, did not change significantly over the following three days of testing, regardless of substrate compliance or cellular organization (multi-cell nodules/plaques or single cells). Interestingly, cells formed 3D nodules when attached to substrates with elastic moduli less than their own but spread readily on substrates with moduli equal to or greater than their own, suggesting a preference to adhere to the stiffest surface sensed (substrate or cell). This suggests that inherent mechanophenotype plays a role as a competing surface during microenvironment mechanosensing and subsequent cell-cell-substrate organization. Keywords mechanosensing, atomic force microscopy, nodule, plaque, elastic/ viscoelastic properties, cellular assembly 54 3.2 Introduction Mechanophenotype, which can be characterized using whole-cell, elastic and viscoelastic properties, has emerged as a viable biomarker and descriptor of cellular function and fate [6-8, 33]. Changes in cellular mechanophenotype have been observed in different cell states, such as stem cell pluripotency/differentiation, cancer invasion, and cytoskeletal disruption or rearrangement [6, 9, 15, 20]. Cells generate specific phenotypic responses to stimulatory factors in the cellular microenvironment, including an intricate combination of soluble and insoluble signaling molecules, physical stimuli, and cell-matrix and cell-cell interactions [3, 19]. Previous studies have demonstrated how the extracellular environment drastically shapes cell behaviors. However, intrinsic properties of the cell, specifically mechanophenotype, have typically been overlooked but are invariably important to cell function (e.g., proliferation, self-renewal, differentiation, apoptosis, etc.) [10, 11, 31]. We hypothesize that mechanophenotype will play a role in how a cell responds to its physical microenvironment, influencing the process of multicellular organization when in the presence of physiologically compliant surfaces. Cellular assembly, defined by 2D and/or 3D cellular organization, is influenced by interactions between cells and substrates as well as between cells and other cells. While substantial effort over the past decade has been devoted towards understanding the effects of substrate compliance on cell behavior, the role of cellular mechanophenotype in cell- cell and cell-substrate interactions is not clearly understood [12, 23]. Cells typically display a more rounded morphology and tend to aggregate on softer substrates, whereas cells attach and spread to a greater extent on stiffer substrates, with the latter also being dependent on the type and density of extracellular matrix (ECM) ligand coating [14, 23]. Cellular 55 mechanosensing of the microenvironment is linked to inherent mechanophenotype through cytoskeletal components, including focal adhesions, integrins, and cadherins [28, 32, 35]. Studies by Guo et al. and Gilchrist et al. both report formation of tissue-like aggregates on compliant substrates, observed across a range of cell types that included fibroblasts, epithelial cells, and nucleus pulposus cells, postulating that cells gain the most tension from cell-cell interactions compared to cell-substrate interactions [14, 16, 24]. The adhesion complexes formed through focal adhesions, integrins, and cadherins begin with actin polymerization and organization, followed by activation of myosin-II contractility that allows cells to migrate to regions of higher stiffness [16, 21, 24]. While this concept, known as durotaxis, has been extensively studied to understand the role of underlying substrates in cellular migration and adherence, little has been done in relation to cell-cell interactions. Understanding mechanophenotype in the context of cellular assembly could give rise to more effective tissue-specific constructs where appropriate cell-cell and cell-substrate interactions can develop. The goal of this study was to (1) investigate the stability of inherent cellular mechanophenotype with respect to time and the compliance of the underlying substrate and (2) determine whether mechanophenotype can influence cellular adhesion and assembly when cells are grown on gels of known, physiologic elasticity. Human lung fibroblasts were mechanically characterized using atomic force microscopy (AFM) during four days of culture on collagen 1 (COL 1)-coated polyacrylamide (PAAm) gels to assess if and when mechanophenotype reached a state of equilibrium. Fibroblasts were transfected with three plasmids to create mechanically distinct cell lines: (1) GFP (control plasmid), (2) dnRhoA (to disrupt cytoskeletal regulation) and (3) β-Actin (to increase actin 56 synthesis). The behavior of these stably transfected cell lines was then investigated when cells were grown on gels with stiffness above, below, and matching their whole-cell, elastic moduli. Changes in cellular mechanical properties and organizational phenotypes were assessed in relation to the mechanophenotype of the cell. We hypothesized that cells would maintain an inherent, internal mechanophenotype regardless of substrate stiffness. Additionally, cells would spread and attach more readily on substrates with elastic moduli equal to or greater than their own and that cells would compete to find and adhere to the stiffest surface sensed (substrate or cell). 3.3 Materials and Methods 3.3.1 Cell Culture WI-38 VA-13 subline 2RA (WI-38, human lung fibroblasts, purchased from ATCC, #CCL-75.1) were expanded and maintained in phenol red-free MEM (CellGro, Corning) supplemented with 10% (volume/volume, v/v) FBS (Calsson Labs, lot #08142019 and #08152003), 1% (v/v) penicillin/streptomycin (Hyclone, GE Healthcare), 2 mM Glutamax (Hyclone, GE Healthcare), and 1 mM sodium pyruvate (Thermo Fisher Scientific). Cells were maintained in humidified incubators at 37º C, 5% CO2 and passaged at 60-80% confluence using 0.25% trypsin-EDTA (Hyclone, GE Healthcare). MG-63 (osteosarcoma) and SH-SY5Y (neuroblastoma) cell lines were also used to confirm cell- cell-substrate assemblies and mechanical properties. The methodology and results for these additional experiments involving MG-63 and SH-SY5Y cells is shown in electronic supplementary text. 57 3.3.2 Development of Stable Cell Lines WI-38 cells were plated in 96 well plates at 25,000 cells/well. After 24 hours, cells were transfected using NanoJuiceTM Transfection Reagent (Novagen) according to product literature. Cells were transfected with one of three plasmids: pAcGFP1-Actin (β-Actin, #632453, Clontech), pcDNA3-EGFP-RhoA-T19N (dnRhoA, a gift from Gary Bokoch, #12967, Addgene), and pEmGFP-N1 (GFP, a gift from L. E. O. Darling, Wellesley College). Once cells reached 80-90% confluence post-transfection, cells were trypsinized and re-plated at low densities in 6-well plates in WI-38 culture media supplemented with 400 µg/mL Geneticin. After 4-7 days, when positively transfected colonies were visible (based on GFP fluorescence), 3-5 colonies were picked and expanded under antibiotic conditions. Colonies were grown and developed into stable cell lines in the presence of antibiotics. 3.3.3 Gel Fabrication and Functionalization Polyacrylamide (PAAm) gels of three different stiffnesses were fabricated to be lower than, equal to, or greater than the stiffness of the transfected cell lines (0.3, 0.5, 1.4 kPa). Mechanical properties of the gels were modulated by using 3% acrylamide (#161- 0140, Bio-Rad) with varying concentrations of bis-acrylamide (0.05, 0.07, and 0.2%, #161- 0142, Bio-Rad) in phosphate buffered saline based on previously published protocols [34]. Gels were polymerized using 10% (weight/volume, w/v) ammonium persulfate (#BP179, Thermo Fisher Scientific) and 1.5% (v/v) tetramethylethylenediamine (#BP150, Thermo Fisher Scientific). 60 µl of the final PAAm solution was placed between a hydrophilic glass coverslip prepared using 0.5% (v/v) 3-aminopropyl-trimethoxysilane (#313251000, Acros 58 Organics) and 0.5% (v/v) glutaraldehyde (#A17876, Alfa Aesar) and a hydrophobic glass slide prepared using 0.5% acetic acid (#A38-212, Thermo Fisher Scientific) and 2.5% (tridecafluoro-1,1,2,2-tetrahydrooctyl)trichlorosilane (#SIT8174, Gelest Inc.) in hexane (#H292, Thermo Fisher Scientific). An additional slide was used to provide a base, with three glass coverslips creating a spacer that held the solution apart to yield a flat gel with a standardized thickness. After polymerization (~10 minutes), the gels were soaked in PBS for at least one hour before functionalization. Gels were functionalized by UV-photoactivation of a heterobifunctional cross linker, sulfo-SANPAH (#13414, CovaChem), followed by overnight incubation at 4º C in 100 µg/ml solution of collagen type 1 (COL-1, #08-115, Lot #2373345, Millipore) [34]. Prior to cell seeding, the gels are washed twice with sterile water and incubated for 10 minutes in 100% ethanol for sterilization. Gels were then rinsed and allowed to equilibrate in base medium, MEM, prior to seeding cells. 3.3.4 Atomic Force Microscopy 3.3.4.1 Mechanical Characterization of Cells Non-transfected and transfected WI-38 cells were mechanically characterized using AFM to characterize differences in mechanophenotype. Briefly, single-cell elastic and viscoelastic tests were performed using an AFM based on our previously published techniques, with minor modifications [7, 8, 15]. Four mechanical parameters were quantified using AFM: elastic modulus (Eelastic), instantaneous modulus (E0), relaxed modulus (ER), and apparent viscosity (µ). Eelastic is the measure of a cell’s resistance to deformation; a more compliant cell has a lower Eelastic. E0 is the initial resistance to 59 deformation, and ER denotes the stiffness of the cell at equilibrium. Lastly, µ represents the resistance to flow of a cell when a specific stress is applied. Spherically tipped cantilevers were made by adhering 5 µm borosilicate beads to the end of silicon nitride, triangular cantilevers (Bruker Corporation, MLCT-O10, k~0.03 N/m). The AFM was calibrated prior to each experiment by calculating cantilever spring constants based on the power spectral density of the thermal noise fluctuations. Indentation and stress relaxation tests were performed on the perinuclear region of single cells or the center of cell aggregates, with an approach velocity of 10 µm/sec and a 30 second relaxation period. Trigger forces ranged between 0.6 - 1.5 nN to limit indentations to <15% strain based on the height of the cell. All AFM testing was performed at room temperature. Cell and nodule/plaque heights were determined by using the AFM to measure the difference in initial contact location of the cell compared to a reference contact location on the substrate. Three, separate experiments were performed to characterize the mechanophenotype of transfected and non-transfected cells. The first experiment investigated whether mechanophenotype would change over time on a compliant gel. Non-transfected WI-38 cells were grown on COL-1-coated coverslips and PAAm gels for 5 days. Cells were tested on Day 0 in a spherical morphology (~30 minutes after seeding) and after 1, 2, 3, and 4 days in the nodule/plaque assemblies that formed. The second experiment investigated differences in mechanical properties among GFP-, dnRhoA-, and β-Actin-transfected WI- 38 cells. Cells were allowed to adhere to a glass coverslip for 48 hours prior to elastic and viscoelastic testing to determine their mechanophenotype in a spread morphology. The third experiment investigated mechanophenotype and assembly behavior of the mechanically distinct cell types when grown on compliant PAAm gels tuned to precise 60 elasticities. GFP, dnRhoA, and β-Actin cells and cell assemblies grown on COL-1-coated gels or coverslips were mechanically characterized 96 hours after plating. Number of samples tested for each experiment are shown in Supplementary Table 1. 3.3.4.2 Mechanical Characterization of PAAm Gels Gels were also characterized using AFM. Briefly, a 4x4 array of indentation sites in 3 distinct locations, for 3 gels per stiffness were collected. As described above, spherically tipped cantilevers were used to indent gel substrates with an indentation rate of 10 µm/sec. The resulting force-indentation curves were fit to the Hertz contact model for spherical indentation of a flat surface. Trigger forces ranged between 1.0 and 1.75 nN to maintain indentations ranging from 0.5 to 1.5 µm. 3.3.5 Confirmation of Transfections Using Western Blot Protein levels of GFP, dnRhoA, and β-Actin were assessed using Western Blot, following previously described protocols [27]. Briefly, 5 µg of protein were separated on pre-cast SDS-PAGE gels (Bio-Rad) and transferred onto Immobilon IP membranes (Millipore) before probing for GFP (1:2500, Abcam, #ab6556), RhoA (1:500, #MA1-134, Thermo Fisher Scientific), β-Actin (1:2500, #ab170325, Abcam), and GAPDH (1:50,000, #PA1-9046, Thermo Fisher Scientific). Primary antibodies were detected using IRDye 800CW goat anti-mouse (#925-332210), IRDye 680RD donkey anti-rabbit (#925-68073), or IRDye 800CW donkey anti-goat (#926-32214) secondary antibodies (1:15,000, LI- COR). Blots were visualized on an Odyssey Infrared Imaging System (LI-COR). Blots 61 were stripped with NewBlot PVDF Stripping Buffer (LI-COR) and reprobed once to allow for detection of all four proteins on the same blot. 3.3.6 Assessment of Actin Organization and Cellular Assembly Transfected WI-38 cells were seeded on the three fabricated PAAm gels at a density of 20,000 cells/gel within a 24 well plate (1 gel/well). Three, separate iterations of the experiment were run, with a total of 7-8 gels per condition. After 96 hours of culture, the cells were fixed with 10% formalin, permeabilized with a 0.1% solution of Triton X-100, and blocked with 3% bovine serum albumin. Cells were then stained with phalloidin (#A22287, Molecular Probes, Thermo Fisher) for actin filaments and 4',6-diamino-2- phenylindole (DAPI, Thermo Fisher) for nuclei. Nine to sixteen images were captured per gel using a 10x objective on the Cytation 3 cell imager (Biotek Instruments Inc.), and cellular assembly was described as either multi-cellular nodules/plaques or single cells/monolayers (Fig. 1a). Nodule frequency was quantified per field of view (FOV) as a function of cell and gel stiffness using a custom ImageJ (NIH) macro and confirmed by hand counting. Brightness and contrast were uniformly adjusted across entire images to show morphology. Confocal imaging of cellular organization was performed using a Zeiss LSM 510 Meta Confocal Laser Scanning Microscope built on an Axiovert 200M inverted microscope with ZEN 2 software (Carl Zeiss MicroImaging). All images were taken using the 40x objective with 1.05 µm slices. DAPI was visualized using a 405-nm diode laser, and phalloidin was visualized with a 633-nm Helium-Neon laser. 62 3.3.7 Statistical Analysis All statistical analysis was performed using SigmaPlot 12.5 (Systat Software Inc.). All data are represented as arithmetic mean ± standard deviation (SD). Cellular mechanical and height data collected using AFM were non-normal, according to the Shapiro-Wilk test. Non-parametric analysis was performed on all data using a Kruskal-Wallis analysis of variance (ANOVA) on ranks, followed by Dunn’s test for multiple comparisons with a significance of p < 0.05. Nodule frequency data were normalized by logarithmic transform. Significant differences between cell type and PAAm gel stiffness were assessed using a two-factor ANOVA, followed by a Holm-Sidak post-hoc test for multiple comparisons using significance of p < 0.05. 3.4 Results 3.4.1 Elastic Properties of PAAm Gels COL-1-coated PAAm gels were fabricated to exhibit elasticities lower, equal to, or greater than those exhibited by transfected WI-38 cells (0.47 ± 0.21 kPa). Resultant gels exhibited elastic moduli of 0.3 ± 0.02 kPa, 0.5 ± 0.04 kPa, and 1.4 ± 0.1 kPa, as measured by AFM. 3.4.2 Temporal Mechanophenotype Characterization of WI-38 Cells To determine if there was a time component involved in defining cellular mechanophenotype, mechanical properties of non-transfected WI-38 cells were measured across four days while cultured on 0.3, 0.5, and 1.4 kPa gels and glass coverslips (CS). Four parameters, Eelastic, ER, E0, and µ, were measured to obtain a panel of elastic and viscoelastic properties for individual cells exhibiting a spherical morphology on Day 0 63 (about 30 minutes after seeding) or assemblies of cells in nodule (defined as multi-cellular aggregates) or plaque (defined as flattened versions of nodules) morphologies from Days 1-4 (Fig. 1). Individual cells on glass CS were also tested over the same period. Average Eelastic increased from ~0.2 kPa to ~0.5 kPa between Day 0 and Days 1-4 (Fig. 1a). From Days 1-4, cells and nodules/plaques typically exhibited Eelastic ranging from 0.4-0.6 kPa, regardless of cellular assembly or substrate stiffness (p > 0.05). As with the elastic modulus, ER, E0, and µ varied on Day 0 based on substrate stiffness but stabilized to a consistent, stiffer mechanophenotype on Days 1-4 (p > 0.05, Fig. 1b-d). In general, WI-38 cells in nodule formation on 0.3 and 0.5 kPa gels were significantly taller than their corresponding plaques formed on 1.4 kPa gels for each day (Supplementary Fig. 1). Individual WI-38 cells on glass CS were significantly shorter than nodules or plaques on gels. Figure 3-1 Mechanical characterization of the cellular assemblies formed by WI-38 cells on compliant substrates over 5 days. (a) Different cellular assemblies formed when cells were cultured on compliant gels. Nodules represent three-dimensional cellular aggregates. 64 Plaques represent a flattened version of the nodules. And lastly, single cells represent a variety of morphologies demonstrated by non-assembling cells, present at early time points for all substrates and at later time points on substrates with elasticities stiffer than the mechanophenotype of the cell. Average mechanical properties, (b) Eelastic, (c) ER, (d) E0, and (e) µ, of single and assembled WI-38 cells over four days across PAAm gels and glass coverslips (CS). In general, cells tested on Day 0, about 30 minutes after seeding, showed the most variation due to substrate stiffness for all four mechanical properties. WI-38 cells maintained their mechanophenotype from Day 1 onwards, regardless of organizational morphology and substrate stiffness. At later time points, cells only formed plaques on the 1.4 kPa gel, which exhibited mechanical properties similar to the nodules formed on other gels and single cells on glass CS. Data shown as mean ± s.d., with statistical significance determined using Kruskal-Wallis ANOVA on ranks within each day, followed by a Dunn’s post-hoc analysis (* p < 0.05). #, Only single cells were present for this condition, instead of nodules/plaques. +, Individual cells in spherical morphologies were tested on Day 0 for all substrates. 3.4.3 Transfection and Mechanical Characterization of WI-38 Cells Successful transfections of WI-38 cells with GFP, dnRhoA, or β-Actin plasmids were visualized by green fluorescence from the GFP reporter (Fig. 2a). Western blots confirmed successful incorporation of plasmid DNA and subsequent expression of GFP- fused proteins based on the presence of higher molecular weight bands for all modified groups (Fig. 2b). Eelastic of the three transfected cell lines was mechanically characterized after two days on glass coverslips using AFM (Fig. 2c). β-Actin cells were ~30% more compliant than GFP cells (p < 0.05), while dnRhoA cells were ~60% stiffer (p < 0.05). dnRhoA cells were ~130% stiffer than β-Actin cells (p < 0.05). 65 Figure 3-2 Characterization of GFP, dnRhoA, and β-Actin cells. (a) Stably transfected cell lines exhibited uniform GFP expression. Scale bar = 50 µm. (b) Expression of fusion proteins was confirmed via Western blot analysis. (c) Each cell line was mechanically characterized when adhered to glass coverslips for two days, with results showing higher (dnRhoA) and lower (β-actin) elastic moduli in comparison to the control, GFP-transfected 66 cells. Data shown as mean ± s.d., with statistical significance determined using Kruskal- Wallis ANOVA on ranks, followed by a Dunn’s post-hoc analysis (* p < 0.05). 3.4.4 Effect of Mechanophenotype on Cellular Organization Two, distinct, organizational phenotypes, multi-cellular nodules/plaques versus single cells/monolayers, were visible across all cell lines and across gels regardless of their stiffness. DAPI and phalloidin staining provided more detail on these particular cell arrangements (Fig. 3). Qualitatively, GFP and dnRhoA cells primarily formed nodules on 0.3 and 0.5 kPa gels, elastic moduli that were equal to or less than that measured for either cell type (Fig. 3a). Interestingly, β-Actin cells displayed the lowest nodule frequency per FOV compared to the other two cell types across all three gel stiffnesses (p < 0.05, Fig. 3b). While not statistically significant, β-Actin cells tended to form fewer nodules on the 0.3 kPa gels than either GFP or dnRhoA cells (50-55% fewer, p = 0.07 for both comparisons). β-Actin cells also formed significantly fewer nodules than dnRhoA cells on 0.5 kPa (60% fewer, p = 0.01) and 1.4 kPa (71% fewer, p = 0.02) gels. Similar trends were observed between β-Actin and GFP cells on 0.5 kPa (53% fewer, p = 0.15) and 1.4 kPa (62% fewer, p = 0.13) gels. For all cell types investigated, nodule frequency on the 1.4 kPa gels was significantly less than on 0.3 and 0.5 kPa gels (p < 0.05). Similar observations were made for cell types spanning across other lineages (Supplementary Fig. 2-3). 67 Figure 3-3 Effect of mechanophenotype on cellular assembly into nodules or plaques. (a) Representative images of transfected WI-38 cells on PAAm gels (nuclei: blue, actin filaments: red; scale bar: 200 µm). (b) Abundant nodule formation occurred on gels that were more compliant than the inherent mechanophenotype of cells in the noted cell line. Nodule frequency per field of view (FOV) shown as mean ± s.d. (* p < 0.05, as determined by a two-factor ANOVA between cell type and gel stiffness on logarithmically transformed data, followed by Holm-Sidak post-hoc analysis). 68 Mechanophenotype of GFP, dnRhoA, and β-Actin Cells on Compliant Gels The behavior of mechanically distinct, stably transfected cell lines was then observed when grown on substrates with stiffness above, below, and equal to the elastic modulus of the cell. Mechanical properties of cells from the four cell lines grown on COL- 1-coated 0.3, 0.5, 1.4 kPa gels and glass CS were measured at a single time point, Day 4. The mechanophenotype of cells in nodule or plaque morphologies was recorded for each of the cell types. Interestingly, no differences in Eelastic, ER, E0, or µ (Fig. 4a-d) were observed among nodules and plaques formed by GFP, dnRhoA, or β-Actin cells on the gels (p > 0.05). Additionally, no differences in mechanical properties were observed between nodules or plaques on gels and individual cells on glass CS (Fig. 4 and electronic supplementary material, table S1c). While the heights of individual cells compared to nodules and plaques varied due to increased cell numbers (Supplementary Fig. 4), this did not affect cellular mechanophenotype. 69 Figure 3-4 Average mechanical properties, (a) Eelastic, (b) ER, (c) E0, and (d) µ, of GFP-, dnRhoA-, and β-Actin-transfected WI-38 cells after four days on 0.3, 0.5, and 1.4 kPa PAAm gels and glass coverslips (CS). In general, cells displayed similar mechanical properties, regardless of organizational morphology (nodule vs. plaque vs. single cells) and substrate stiffness. Data shown as mean ± s.d., with statistical significance determined using Kruskal-Wallis ANOVA on ranks for each mechanical parameter within each cell line, followed by a Dunn’s post-hoc analysis (* p < 0.05). 3.4.5 Confocal Imaging of Actin Cytoskeleton Confocal z-stacks of DAPI- and phalloidin-stained cells were taken 96 hours after culture on gels of designated stiffness (Fig. 5). Qualitatively, nodules formed by GFP cells on 0.3 kPa and 0.5 kPa gels showed more centralized actin cytoskeleton that became more diffuse and less visible towards the edges of the nodule. On the 1.4 kPa gel, GFP cells primarily formed plaques that displayed a highly structured network of actin filaments. dnRhoA cells on 0.3 kPa gels displayed minimally structured actin cytoskeleton, instead presenting punctate actin structures throughout the cytoplasm. Similar to GFP cells, 70 dnRhoA on 0.5 and 1.4 kPa gels had a centralized actin cytoskeleton where cells were in contact with other cells and had minimal interaction with the underlying compliant gel. β- Actin cells cultured on 0.3 kPa gels showed diffuse phalloidin staining throughout the cytoplasm and minimal structured cytoskeleton. Conversely, on 0.5 and 1.4 kPa gels, which were stiffer than β-Actin cells, cells displayed organized actin fibers. Unlike other cell types, β-Actin cells were able to adhere to gels as single cells and completely spread out. Figure 3-5 Nodules and plaques of GFP, dnRhoA, and β-Actin cells after 4 days of culture. Confocal projections revealed differences in actin bundle formation (nuclei: blue, actin 71 filaments: red; scale bars: 20 µm) on gels, especially as cells transitioned from nodule to plaque formations on PAAm gels greater than the mechanophenotype of the adhered cells. 3.5 Discussion Results from this study indicate that inherent mechanophenotype influences cellular assembly when grown on substrates exhibiting elasticities similar to the cells themselves. Cells maintained a characteristic, perinuclear, whole-cell mechanophenotype on all substrates, regardless of their stiffness, and across all group morphologies and assemblies formed by the cells. Non-transfected WI-38 cells reached a stable mechanical state one day after plating and maintained this mechanophenotype throughout the remaining three days of the experiment. Mechanically distinct GFP-, dnRhoA-, and β- Actin-transfected cells also displayed inherent, whole-cell mechanical signatures that appeared to be largely decoupled from the external microenvironment. Additionally, the results from this study indicate that cells have the ability to mechanosense their environment and selectively adhere and spread on whatever material, PAAm substrate or neighboring cells, that is stiffer than their inherent mechanophenotype. The most compliant cell type in the study exhibited the least amount of nodule formation across all three gels, suggesting a preference to adhere to the stiffer substrate than soft, neighboring cells. Furthermore, for all cell types, significantly greater nodule formation was observed on 0.3 and 0.5 kPa PAAm gels compared to 1.4 kPa gels, where cells were able to spread and develop a more structured actin cytoskeleton. The inherent mechanophenotype of WI-38 cells varied during initial attachment to a substrate but remained largely stable over time. The different cellular assemblies observed throughout the study also formed within the first day, indicating that cells could 72 react quickly to their microenvironment. Since the mechanical properties of WI-38 cells did not change over time, comparisons among the transfected cell lines were made at a single time point. Mechanically distinct, transfected WI-38 cell lines also maintained their inherent, whole-cell mechanophenotypes on substrates of varying stiffness. These results are supported by other studies that have also observed a stable, inherent mechanophenotype despite changes to the cellular microenvironment. Poh et al. showed that embryonic stem cells did not increase their apical cell stiffness on substrates of varying stiffness, while basal traction forces did increase at the interface of cell-substrate interactions on PAAm gels ranging from 0.35 to 8 kPa [25]. Jagielska et al. observed that oligodendrocyte progenitor cells were more compliant than differentiated oligodendrocytes. However, both progenitor and differentiated cell stiffnesses were independent of PAAm gel elasticity, ranging from 0.1 to 70 kPa [18]. It is important to note that Jagielska’s study observed changes in cell survival, proliferation, migration, and other biological factors that were independent of cellular mechanophenotype, emphasizing that this parameter is not solely a secondary indicator of normal cell functions [18]. Contrary to our results, other studies have suggested that mechanophenotype is a more malleable characteristic that changes to match the elasticity of whatever surface the cell is attached to [18, 25, 29-31]. However, these experiments differ substantially in the mechanical testing techniques used (AFM using sharp pyramidal tips over the cytoplasm/cytoskeleton rather than spherical beads over the perinuclear region), range of PAAm gel stiffness examined (0.5 - 40 kPa, many- fold higher than WI-38 mechanophenotype), and cell type investigated (e.g., fibroblasts vs. glioma cells vs. endothelial cells). The current study focused on whole-cell properties to provide an average measure of mechanical properties associated with a cell, rather than 73 nanometer-sized, point tests that can vary widely depending on what underlying cellular component is contacted. Gel elasticity was also limited to only those stiffnesses immediately higher and lower to the cells used in the work, rather than including elasticities orders of magnitude greater. In this way, the work narrowly focuses on studying competitive adherence, due to elasticity, of cells on a soft surface. This study identified that mechanophenotype plays a role in cellular assembly on mechanically-varied substrates, which could be a key factor to consider in tissue formation and development. A clear transition in organizational phenotype was observed across all three WI-38-transfected cell lines tested. GFP (Eelastic ~ 0.55 kPa), and dnRhoA (Eelastic ~ 0.87 kPa) cell lines exhibited significantly more nodule formation on 0.3 kPa and 0.5 kPa gels, with cells preferentially adhering to each other over the softer gel. Comparatively, β- Actin cells (Eelastic ~ 0.37 kPa) readily adhered and spread on the softer gels, even maintaining single-cell morphologies rather than multi-cell assemblies. These findings confirmed our hypothesis that cells would competitively bind with the stiffest substrate they sense, whether that is a surface or neighboring cell. Confocal imaging provided further insight into the differences in the actin cytoskeleton network developed in the various types of cellular assemblies. The integrated cytoskeletal network that existed across multiple cells can form through cadherins in cell- cell adhesions, which facilitate cell layers and assemblies within tissues and are the adhesive mechanism for tissue-specific structures [4, 36]. Cadherins also direct actin assembly through coupling proteins, such as β-catenin, α-catenin, and vinculin [36]. Previous studies with similar observations in cellular assembly attribute this behavior to cells maximizing their mechanical input from the microenvironment [16]. Gilchrist et al. 74 observed nucleus pulposus cells (Eelastic ~0.35 ± 0.20 kPa) preferred to aggregate (the typical cellular arrangement in vivo) on 0.10 and 0.22 kPa PAAm gels, yet spread out and form an ordered actin cytoskeleton on 0.72 kPa gels [14]. These phenomena may be explained by differences in expression of Rho pathway components and their link to myosin-II associated contractility [16]. These proteins help cells sense their environment by regulating formation of focal adhesions (integrins) and by mediating cell-cell interactions (cadherins). Therefore, cellular mechanophenotype, in combination with substrate compliance, can influence mechanosensing of the microenvironment and, ultimately, tissue formation. This study strived to create a controlled system to test the effect of mechanophenotype on the various cellular assemblies by creating stable cell lines. These stable transfections minimized variation due to genetic differences and provided a more consistent phenotype compared to commonly used pharmacologic treatments, such as cytochlasin D (inhibitor of actin polymerization), blebbistatin (myosin II inhibitor), or Y- 27632 (ROCK inhibitor). By transfecting a common background cell type with cytoskeleton-related genes, dnRhoA or β-Actin, two mechanically distinct cell lines were developed, with a GFP-transfected cell line serving as a control. Transfection with the dominant negative RhoA (point mutation T19N) created the stiffest cell type, while transfection with β-Actin created the most compliant cell type. While there were visible changes in morphologies of these two cell types, their changes in mechanical properties were contrary to what would be expected. dnRhoA cells were transfected with a mutated, non-functional version of RhoA that inhibits activation of Rho kinase and downstream actin assembly but displayed typical cell spreading behaviors, as observed previously [13]. 75 In the current work, dnRhoA-GFP-transfected cells maintained their endogenous RhoA (as identified by western blot expression levels), in addition to the mutated RhoA, with mechanophenotype stiffening as a response. β-Actin-transfected cells visibly incorporated β-Actin-GFP into their actin fibers; however, much diffuse, β-Actin remained in the cytoplasm as well. While previous studies indicate a ~5-10% increase in overall actin expression is to be expected, a corresponding increase in whole-cell stiffness was not observed in the current study [5, 10]. To our knowledge, researchers using the dnRhoA- GFP or β-Actin-GFP transfections have only investigated changes in cell morphology, differentiation potential, actin organization, and protein content, while whole-cell mechanical properties were not assessed [5, 10, 13, 22]. While the mechanisms behind gene-specific mechanophenotype responses are not within the scope of this study, we hypothesize the apparent contradiction may be due to alternative feedback mechanisms through components of the Rho pathway. The activation of Rho kinase may occur through secondary mechanisms (instead of by RhoA), which would lead to continued stabilization of actin, development of stress fibers, and whole-cell stiffening [2]. Comparatively, while overexpression of β-Actin leads to increased monomeric actin (visualized by the diffuse green fluorescence in the cytoplasm, Fig. 2a), this may not be completely translated into filamentous F-actin that makes up stress fibers and correlates with cell stiffness. Additionally, the β-Actin-GFP fusion protein has been shown to inhibit various actin binding proteins and myosin-II interactions in protozoa which could lead to dysfunction of the actin structure, and thus, a more compliant cell [1, 17]. While the current study used COL-1 as a substrate coating for all conditions, it is likely that ECM ligands will play an important role in cellular assembly by restricting 76 integrin binding for cell types of more varied backgrounds. Supplementary experiments explored this hypothesis by investigating how cells from multiple lineages responded to fibronectin (FN) and laminin (LN), in addition to COL-1. MG-63 (osteosarcoma, Eelastic = 1.3 ± 0.5 kPa) and SH-SY5Y (neuroblastoma, Eelastic = 0.3 ± 0.1 kPa) cells were grown on PAAm gels coated in the different proteins. While a ligand-dependent adhesion response was observed (Supplementary Fig. 2), cellular mechanophenotype was still maintained across gels (Supplementary Fig. 3). Protein coatings had a modulatory effect on cellular mechanosensing as well, likely due to disparate integrin binding interactions. MG-63 cells spread more on COL-1, even on soft gels. Highly compliant SH-SY5Y cells spread and exhibited the same morphologies on all three gel stiffnesses, which were greater than or equal to the ~0.3 kPa elastic modulus of SH-SY5Y cells. Notably, binding affinity was weak on soft, LN- and FN-coated gels. Additionally, SH-SY5Y cell morphologies are inherently cell density dependent, aggregating when seeded at lower cell densities or spreading and forming monolayers at higher densities (Supplementary Fig. 2b, c) [26]. These results suggest that inherent mechanophenotype influences cellular assembly across multiple types of cells, but are only one factor since other environmental conditions like protein ligands can exert influences of their own. Single-cell mechanical properties exhibit large variations. If biological phenotype is not a concern, cell populations can be chosen that are mechanically distinct (e.g., MG- 63 and SH-SY5Y). While stable transfections of a common background cell type created mechanically distinct cell populations in the current study, the induced stiffening or softening were not extensive enough to completely separate their mechanophenotype distributions. Therefore, cell assembly responses on the various substrates were more 77 heterogeneous. Cells exhibiting a “soft” mechanophenotype were inevitably present in small proportions in the “stiffer” cell type groups and vice versa. Regardless, sufficient separation in average mechanophenotype was achieved to discern generalized cell assembly behaviors. Complete knockdown of genes, promoters, or modulation of other elements that have a more dramatic effect on the whole-cell properties may provide even clearer evidence of what is reported here. Whole-cell mechanophenotype affects critical functions, including proliferation, differentiation, motility, shape, and multi-cell assembly [9]. Therefore, understanding how mechanophenotype influences cell behavior in relation to the local, mechanical microenvironment is vital to directing successful cellular organization in regenerating tissues. The ability of cells to aggregate or spread individually depends not only on cell type, extracellular matrix ligands, and substrate stiffness, but also importantly on inherent mechanophenotype [14, 37]. These findings can provide insight into future studies on tissue engineered constructs as well as the pathological progression of injuries and disease based on combined data from mechanical changes in extracellular matrix and cellular properties. 78 3.6 Author Contributions M.K.S. and E.M.D. designed the study, analyzed data, and wrote the manuscript. M.K.S. performed all AFM experiments and all experiments with non-transfected and transfected WI-38 cells lines. I.H.G.-P performed MG-63 and SH-SY5Y cellular assembly experiments. All authors gave final approval for publication. 3.7 Acknowledgments The authors would like to thank Louise E. O. Darling for the GFP plasmids and Jessica S. Sadick and Vera Fonseca for help with western blots. This work was supported by awards from the National Institute of Health (R01 AR063642, P20 GM104937) and the National Science Foundation (CAREER CBET 1253189). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or National Institutes of Health 3.8 Conflict of Interest Manisha K. Shah, Iris H. Garcia-Pak, and Eric M. 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Wang, J.H. and Lin, J.S., Cell traction force and measurement methods. Biomech Model Mechanobiol. 6(6): p. 361-71, 2007. 36. Weber, G.F., Bjerke, M.A., and DeSimone, D.W., Integrins and cadherins join forces to form adhesive networks. J Cell Sci. 124(Pt 8): p. 1183-93, 2011. 37. Yeung, T., Georges, P.C., Flanagan, L.A., Marg, B., Ortiz, M., Funaki, M., Zahir, N., Ming, W., Weaver, V., and Janmey, P.A., Effects of substrate stiffness on cell morphology, cytoskeletal structure, and adhesion. Cell Motil Cytoskeleton. 60(1): p. 24-34, 2005. 84 3.11 Supplementary Text 3.11.1 ECM effects on cells from alternative lineages 3.11.1.1 Materials and Methods Cell Culture: MG-63 (osteosarcoma, #CRL-1427, ATCC) cells were expanded and maintained in phenol red-free MEM supplemented with 10% FBS, 1% penicillin/streptomycin, 100 mM Glutamax, and 100 mM sodium pyruvate. SH-SY5Y (neuroblastoma, #CRL-2266, ATCC) cells were expanded and maintained in high-glucose DMEM (Hyclone, GE-Healthcare), 10% FBS, 1% penicillin/streptomycin, and 1% Glutamax. Cells were maintained in humidified incubators at 37ºC, 5% CO2 and passaged at 60-80% confluence using 0.25% trypsin-EDTA (Hyclone, GE Healthcare). PAAm Gel Fabrication: PAAm gels of three stiffnesses were fabricated using different ratios of acrylamide:bis-acrylamide: 3%:0.06%, 7%:0.03%, and 10%:0.1%. Gels were made to be lower than, equal to, or greater than the stiffness of MG-63 and SH-SY5Y cells (0.3, 2, and 12 kPa). The protocol for gel fabrication is as described in Section 3.3.3 Gel Fabrication and Functionalization. Gels were coated overnight with 20 µg/ml laminin (LN, #354239, BD Biosciences), 100 µg/ml collagen-1 (COL-1, #08-115, Millipore), or 10 µg/ml fibronectin (FN, #33016015, ThermoFisher). Assessment of Actin Organization and Cellular Assembly: MG-63 and SH-SY5Y cells were seeded and assessed for cellular assemblies as described in Section 3.3.6 Assessment of Actin Organization and Cellular Assembly. 85 Atomic Force Microscopy: Both MG-63 and SH-SY5Y cells were mechanically characterised as described in Section 3.3.4.1 Mechanical Characterization of Cells. Individual cells were tested on gels and glass CS two days after seeding. Gels were also characterized as described in Section 3.3.4.2 Mechanical Characterization of PAAm Gels. 86 3.12 Supplemental Figures Figure 3-6 Height changes correspond with cellular assembly of non-transfected WI-38 fibroblasts into nodules and plaques. (a) Minimal differences in cell heights existed across spherical cells on gels and glass CS on Day 0. In general, the nodules that existed on (b) Day 1, (c) Day 2, (d) Day 3, and (e) Day 4 on 0.3 kPa and 0.5 kPa gels were significantly taller than the plaques that existed on 1.4 kPa gels and single cells on glass CS. Heights shown as mean ± s.d., with statistical significance determined using Kruskal-Wallis ANOVA on ranks within each cell line, followed by a Dunn’s post-hoc analysis (* p < 0.05). #, nodules/plaques did not exist for this condition, only single cells. 87 88 Figure 3-7 Effect of substrate stiffness for (a) MG-63 cells and (b) SH-SY5Y cells on fibronectin, laminin, and collagen-1 functionalized PAAm gels, as shown with DAPI (nuclei: blue) and phalloidin (actin: red) staining. Control cultures were plated on (c) untreated, glass coverslips. MG-63 cells, which displayed a mechanophenotype equivalent to the 2 kPa gel, formed more nodules on gels with compliance less than the elastic modulus of the cell. SH-SY5Y cells, with a mechanophenotype equivalent to the softest gels, did not display any organizational transition on the different substrate compliances, possibly because all PA gels were stiffer than the cells. Increased actin organization was visible in spread MG-63 cells compared to cells in nodules. Scale bar: 200 µm. Inset scale: 80 µm x 80 µm. 89 Figure 3-8 Average mechanical properties of (a-d) MG-63 and (d-f) SH-SY5Y cells after two days on glass CS (MG-63: n = 20; SH-Y5Y: n = 15) or PAAm gels (MG-63: n = 44- 79; SH-Y5Y: n = 22-28) coated with FN, LN, or COL-1. In general, individual cells displayed similar mechanical properties regardless of gel stiffness. Both MG-63 and SH- SY5Y cells cultured on gels exhibited a more compliant mechanophenotype than cells cultured on much stiffer, untreated glass coverslips. Data shown as mean ± s.d., with statistical significance determined using Kruskal-Wallis ANOVA on ranks for each mechanical parameter within each cell line and ligand coating, followed by a Dunn’s post- hoc analysis (* p < 0.05). COL-1: collagen-1, LN: laminin, FN: fibronectin. 90 Figure 3-9 Height changes correspond with cellular assembly of transfected cell types into nodules and plaques for (a) GFP, (b) dnRhoA, and (c) β-Actin cells. Data shown as mean ± s.d., with statistical significance determined using Kruskal-Wallis ANOVA on ranks within each cell line, followed by a Dunn’s post-hoc analysis (* p < 0.05). 91 Supplementary Table 1. Table 3.1 Number of samples tested corresponding to (a) WI-38 cell mechanics over four days on glass, (b) GFP-, dnRhoA-, and β-Actin-transfected cell mechanics at two days on glass coverslips, and (c) transfected cell mechanics on PAAm gels and glass coverslips (CS) at four days. a) Sample sizes for WI-38 cells/nodules/plaques tested over four days for each substrate to assess elastic and viscoelastic properties (#, no nodules/plaques present). Gel Stiffness Day 0 Day 1 Day 2 Day 3 Day 4 (kPa) 0.3 48 15 45 32 53 0.5 56 20 39 56 49 1.4 53 # 40 40 55 CS 57 25 30 43 40 b) Sample sizes for transfected WI-38 cells tested to assess average elastic moduli. GFP dnRhoA β-Actin 61 58 57 c) Sample sizes for GFP-, dnRhoA-, and β-Actin-transfected cells/nodules/plaques tested for each substrate to assess elastic and viscoelastic properties. Gel Stiffness GFP dnRhoA β-Actin (kPa) 0.3 40 35 10 0.5 41 39 11 1.4 38 39 50 CS 20 7 18 92 Chapter 3 4 Integration of hyper-compliant microparticles into a 3D melanoma tumor model. Manisha K. Shah1, Elizabeth A. Leary1, Eric M. Darling1, 2, 3, 4 1 Center for Biomedical Engineering, Brown University, Rhode Island, USA 2 Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Rhode Island, USA 3 Department of Orthopaedics, Brown University, Rhode Island, USA 4 School of Engineering, Brown University, Rhode Island, USA 93 4.1 Abstract Multicellular spheroids provide a physiologically relevant platform to study the microenvironment of tumors and therapeutic applications, such as microparticle-based drug delivery. The goal of this study was to investigate the incorporation/ penetration of compliant polyacrylamide microparticles (MPs), into either cancerous or healthy human cell spheroids. Incorporation of collagen-I-coated MPs (stiffness: 0.1 and 9 kPa; diameter: 10-30 µm) into spheroids (diameter ~100 µm) was tracked over 20-22 hours. Soft MPs penetrated towards the center significantly more in melanoma spheroids compared to normal spheroids. Mature spheroids from both cell types were able to recognize and integrate MPs. While many tumor models exist to study drug delivery and efficacy, the study of uptake and incorporation of cell-sized MP into established spheroids/tissues or tumors has been limited. The ability of hyper-compliant MPs to successfully penetrate 3D tumor models encapsulated by extracellular matrix provides a novel platform for potential delivery of drugs and other therapeutics into tumor cores. 94 4.2 Introduction Mechanical properties of cells and the substrates they interact with are important parameters to take into account for drug delivery vehicles [3, 25, 26]. Engineered, drug- loaded microparticles (MP) and nanoparticles (NPs) are currently being investigated for delivery of specific molecules or signaling cues in vitro and in vivo [1-3, 25]. Some properties to consider for fabrication of microparticles include chemical and physical characteristics, such as drug loading/ release parameters, degradation rates, shape, and size.[2, 18] Recently, mechanical properties of these MPs have become another important variable to control bio-availability and bio-distribution within tissues, especially in vivo [3]. To study efficacy and efficiency of drug delivery properties of MPs in tissues, 3D multi-cell spheroids are being used as an in vitro model [9, 22]. Typically the first tests with MPs as deliver vehicles have been performed in 2D, with only a single layer of cells as a barrier to entry for the particles or the use of trans-well systems to solely assess drug or metabolite release characteristics of MPs, making this technique less clinically-relevant. Alternatively, MPs incorporated into spheroids as a co-culture have shown promise to provide more in vivo-like conditions. However, incorporation of MPs, specifically post- spheroid formation into mature tissues with developed extracellular matrix (ECM), has not been well studied. Furthermore, when particles are administered intravascularly, some key barriers exist, including clearance by the liver and spleen, extravasation out of vasculature, and further penetration into tissue of interest [4]. Recent literature shows different strategies allowing for increased particle penetration into spheroids in vitro and tissues in 95 vivo, including use of particle coatings, such as collagenase [13], altering particle geometry and size [6, 25], and elasticity [3]. To understand if, and how, MPs could penetrate into ECM-rich spheroids, the skin and melanoma were used as tissues of interest. Normal melanocytes sit on a bed of fibroblasts in vivo. When the melanocytes change from a benign to a cancerous state, they start to proliferate, expand into the layer of fibroblasts, and make their way into vasculature to metastasize [15, 17]. The goal of this study was to investigate the incorporation/ penetration of compliant polyacrylamide microparticles (MPs), into either mature, cancerous or healthy human cell spheroids. Incorporation of compliant MPs into spheroids was tracked over 20-22 hours using a high-content, high-throughput confocal imaging system. Total MP distance traveled within the spheroid and rate of MP penetration towards the center of the spheroids were measured. Additionally, ECM deposition by the cells in the spheroid and ability of MPs to penetrate into mature spheroids was visualized over 4 weeks. 4.3 Methods 4.3.1 Cell culture A375 (malignant melanoma, a gift from Dr. Elena Oancea, Brown University) and NHFs (Normal human fibroblasts (a gift from Dr. Jeffrey Morgan, Brown University), derived from neonatal human foreskins were expanded in high glucose DMEM (DMEM- HG, HyClone), 10% FBS (HyClone), and 1% penicillin/streptomycin (P/S, HyClone). Cells were passaged at ~80% confluence using 0.25% trypsin-EDTA (HyClone, GE Healthare). Experiments used NHFs at P7–9. HEM-L158 (HEM, Human epidermal 96 melanocytes, a gift from Dr. Elena Oancea), were expanded in Medium 254 (M254500, Gibco), 1% Human melanocyte growth supplement-2 (S0165, Gibco), and 1% P/S. HEM- L158 cells were subcultured at 60-80% confluence using 0.05% Trypsin-EDTA (25300054, Gibco), followed by neutralization with Trypsin Neutralizer Solution (R002100, Gibco). All cells were maintained in humidified incubators at 37°C, 5% CO2. Main comparisons for the study were performed based on HEM and A375 spheroids, with supplemental information on NHFs as an alternative control. 4.3.2 Fabrication of MPs Polyacrylamide MP fabrication was accomplished through inverse emulsion polymerization protocol as previously described, with minor modifications.[18] Mechanically distinct MPs were created with either 4% acrylamide (Bio-Rad, Hercules, CA): 0.05% bis- acrylamide (Bio-Rad) or 8 % acrylamide: 0.3% bis-acrylamide solutions. MPs were visualized using a blue highlighter dye (Sharpie) with emission at 647 nm wavelength. MPs were functionalized by UV-photoactivation of a heterobifunctional cross linker, sulfo- SANPAH (#13414, CovaChem), followed by overnight incubation at 4 ºC in 100 µg/mL solution of collagen type 1 (COL-1, #08-115, Lot #2373345, Millipore). 10 µm polystyrene (PS) MPs were also used for experiments. PS MPs were coated with COL-1 overnight through adsorption. 10 µm Polystyrene (PS) MPs (F8831, Molecular Probes, Fisher Scientific) were used as an “ultra-stiff” control. PS MPs were incubated overnight at 4 ºC in 100 µg/mL solution of COL-1 for coating through adsorption. 97 4.3.3 Characterization of MPs and Cells The elastic modulus of the MPs and the 3 cell lines were characterized with a MFP- 3D-Bio atomic force microscope (AFM, Asylum research, Santa Barbara, CA) [10, 11]. Spherically tipped cantilevers were made by adhering 5 µm polystyrene beads to the end of silicon nitride, triangular cantilevers (Bruker Corporation, MLCT-O10, k ~ 0.03 N/m). MPs and cells were allowed to attach to glass coverslips for 30 minutes prior to testing in spherical morphologies using established techniques. 4.3.4 Spheroid seeding for 3 experiments 4.3.4.1 Seeding spheroids and their assessment using the Opera PhenixTM A custom mold with a series of 4 rows by 8 columns of pegs was fabricated with 4 conical-shaped microposts atop individual pegs to fit into a single well of a 96-well plate (Greiner bio-one, #655891). To create non-adherent hydrogels, 90 µL of sterile 2% weight/volume molten agarose (Fisher Scientific) in phosphate buffered saline was pipetted into each well, followed by placing the mold into the wells. Hydrogels were allowed to solidify for 15 minutes before removing the mold, followed by overnight equilibration in 150 µL of DMEM-HG or Medium 254 base media supplemented 1% P/S. HEM-L158 and NHF spheroids were seeded at 400 cells/well in a 20 µL of media (100 cells/ spheroid), while A375 spheroids were seeded at 200 cells/ well (50 cells/ spheroid). 30 minutes after seeding cells, each well was flooded with 150 µL of growth media. Media were change every other day. After a 7-day maturation period, 40 “soft,” “stiff,” or polystyrene (PS) MPs in a 20 µL solution were added to each well in sterile phosphate buffered saline supplemented with 98 1% P/S (v/v) and 10 µg/mL Wheat Germ Agglutinin, Alexa Fluor 488 Conjugate (WGA, W11261, Molecular Probes, Thermo Fisher Scientific). Twenty minutes after adding the MPs, the wells were flooded with 150 µL of cell type-specific growth media. Each well was imaged using an Opera PhenixTM High Content Screening System (PerkinElmer, Waltham, MA) over 20-22 hours at either 34.5, 44, or 46 minute time intervals, and 10 - 12.5 µm z-stacks using a 20X water objective with 2 excitation lasers: 488 nm for WGA and 640 nm for red dye-stained MPs. 4.3.4.2 Spheroids for 4 week longitudinal study Spheroids for 4 week longitudinal experiments were seeded in microwells fabricated using 2% agarose (as described above) using 3D Petri Dish® molds (24-96- Small, Microtissues Inc.). Microwells were cured for 15 minutes at room temperature, transferred to a 24-well plate, and equilibrated in 1% P/S, DMEM-HG overnight. HEM- L158 and NHF cells were seeded at 9,600 cells/well (100 cells/ spheroid), and A375 cells were seeded at 4,800 cells/ well (50 cells/spheroid). Soft and stiff MPs were added after different maturation periods: 1, 2, 3, and 4 weeks. 48 hours after adding MPs at each time point, spheroids were fixed overnight in 4% paraformaldehyde. Following fixation, agarose microwells containing the spheroids were transferred to 100% ethanol. After overnight dehydration, the agarose trough area of the micromolds were back-filled with 2% molten agarose to keep the spheroids in place. The samples were then embedded in paraffin, sectioned in 7 µm slices, and stained with hematoxylin and eosin (H&E) to visualize cells and ECM. 99 4.3.5 Data Analysis in Imaris Time-lapse, confocal z-slice images obtained using the Opera Phenix were analyzed using Imaris (BitPlane, Belfast, UK). Confocal slices were rendered as 3D projections, and the “Cell Detection” and “Surface Detection” modules within the software were used to identify and track spheroid and relative MP position, respectively, in the x,y,z plane. Initial MP interaction with the spheroid was identified as time “0.” Spheroid volumes were computed using the “Cell Detection module” to determine average radii 3 3 𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉𝑉. using the following equation: 𝑟𝑟 = �4 𝜋𝜋 , where r is the radius. MP position from there onwards was tracked using the spheroid center as a reference point. Spheroids with no MPs being incorporated, or greater than 2 MPs incorporated within were not used for analysis. 4.3.6 Rate of Penetration towards center of the spheroid To determine if there were differences in MP incorporation based on MP stiffness in normal versus cancerous cell types, MP position relative to the center of the spheroids were tracked. The rate of entry towards the center of the spheroid was determined by calculating the distance of the MP from the center of the spheroid at every time point using the distance formula: AB = �(x2 − x1 )2 + (y2 − 𝑦𝑦1 )2 + (z2 − z1 )2 , where AB represent the distance between the MP and the center of the spheroid, (x1,y1,z1) is the center of the spheroid, and (x2, y2, z2) is the position of the MP. Slopes were calculated using linear regression analyses for MP movement within each spheroid. A best fit line was then fit to the data for each condition to trace average MP position relative to center of the spheroid at each time point. 100 4.3.7 MP distance traveled and speed To calculate total distance traveled by MPs, spheroid movement at each time point was also taken into account. Once relative MP movement was determined at each time point, the distance formula was used to determine total distance traveled. Since the track of MP distance traveled over time was fairly linear, a linear regression analysis was performed for each condition and fit with a best fit line. 4.3.8 Statistical Analysis All statistical analyses were performed using GraphPad Prism 7 (GraphPad Software, Inc). A one-way ANOVA was run on cell elastic modulus data, with a Tukey’s post hoc analysis. Linear regression analyses were performed to assess differences in rate of penetration to the center of the spheroid and total distance traveled by MP, followed by a two-way ANOVA comparing cell type vs. MP stiffness, and a Tukey’s post hoc analysis. To compare PS data, two-tailed t-tests were performed. All NHF data was compared using a one-way ANOVA, followed by a Tukey post hoc analysis. For all statistical analyses, significance was achieved at p < 0.05. 4.4 Results 4.4.1 Mechanical and Size Characterization of HEM-L158, NHF, A375 cells and MPs HEM (normal melanocyte) and A375 (malignant melanoma) cells tested in the spherical morphology had an elastic modulus of approximately two and three times that of NHF cells, respectively (p < 0.05, Figure 1A), while the height of all three cell types was approximately 15 µm (Figure 1B). MPs were fabricated at ~110 Pa and 9.3 kPa, and 101 classified as “soft” and “stiff,” respectively (Figure 1C). While PS MPs were not mechanically characterized within this study, they have been previously measured by other groups to be 2 – 8 GPa [14]. Soft and stiff MPs ranged in size from 15-30 µm (Figure 1D), while PS MPs were 10 µm. Figure 4-1Characterization of cell and MPs. (A-B) Mechanical and heights of the three cell types of interest were characterized using AFM. (C-D) MPs were fabricated an order of magnitude below and above average cells stiffness and in the range of cell size. 4.4.2 Rate of Penetration of MPs towards center of Spheroids Successful incorporation of COL-1 coated soft and stiff MPs was observed in both HEM and A375 spheroids after one week of maturation (Figure 2, Supplemental Figure 2). However, rate of soft MP penetration was approximately twice as fast in A375 spheroids compared to HEM spheroids (p < 0.05, Figure 2B). Rate of penetration of stiff MPs was approximately three times as fast in A375 spheroids compared to HEM spheroids, however 102 due to the great variation in rate this was not significant (p = 0.5, Figure 2B). Overall, when comparing the two factors, there was a significant difference in behavior between both cell types and MP stiffness (p < 0.05). Figure 4-2 Assessment of MP penetration towards the center of the spheroid. (A-B) Graphical depiction of average MP position over time. Data shown as linear regression of slopes with 95% prediction intervals of soft and stiff MP penetration (HEM/soft: n=13, HEM/stiff: n=7, A375/soft: n=16, A375/stiff: n=6). (C) Soft MPs were integrated towards the center of A375 spheroids faster compared to HEM spheroids. Data shown as mean ± S.D., with statistical significance determined using a two-way ANOVA within cell-type and MP stiffness, followed by a Tukey’s post hoc analysis (*p<0.05). 4.4.3 Distance traveled and speed of MP within the spheroid Total MP distance traveled was calculated to understand how erratic or directed MP movement was within spheroids. Distance traveled by soft MPs was about twice as far in A375 spheroids compared to HEM spheroids over the 20-22 hour MP tracking period 103 (p < 0.05, Figure 3A-B), while no significant difference was observed with the stiff MPs. When comparing MP movement per minute, soft MPs were approximately 1.7 times faster in A375 spheroids compared to HEM spheroids (p < 0.05, Figure 3C), while no difference in stiff MP speed was observed. Overall the cell type factor, comparing A375 and HEM spheroids, were significantly different (p < 0.05, Figure 3C). Figure 4-3 Assessment of MP distance traveled within HEM and A375 spheroids. (A-B) Graphical depiction of average MP distance traveled over time. Data shown as linear regression of slopes with 95% prediction intervals of soft and stiff MP penetration. (C) Overall speed of soft MPs was greater in A375 spheroids compared to HEM spheroids. Stiff MP speed was similar in both spheroids. Data shown as mean ± S.D., with statistical significance determined using a two-way ANOVA within cell-type and MP stiffness, followed by a Tukey’s post hoc analysis (*p<0.05). 104 4.4.4 PS MP behavior in HEM and A375 spheroids Since much stiffer MPs, such as PS MPs, are more common in the field, the next step was to assess if any differences were observed in their behavior in our spheroid systems (Figure 4). The “ultra-stiff” PS MPs did now show any difference in rate of penetration towards the center of the spheroids between the two cell types (Figure 4A-B). Corroborating these results, no difference was observed in PS MP speed or total distance traveled within HEM or A375 spheroids (Figure 4C-D). Figure 4-4 Assessment of incorporation of PS MPs within HEM and A375 spheroids. (A- B) PS MP penetration towarads the center were not significantly different in HEM or A375 spheroids, when comparing velocity or linear regression analyses of MP position (HEM/PS: n=7; A375/PS: n=10. (C-D) Overall speed of PS MPs was the same in spheroids of both cell types as shown by slopes and MP location over time. Data shown as linear regression of slopes with 95% prediction intervals of soft and stiff MP penetration. Data 105 shown as mean ± S.D., with statistical significance determined using a two-tailed t-test (*p<0.05). 4.4.5 Time lapse imaging of soft MP incorporation in A375 spheroids 3D projections of confocal z-slices were taken of soft MPs (stained red) incorporating into A375 spheroids (stained with WGA) over 22 hours at 44-minute intervals (Figure 5). The soft MP begins outside the spheroid, as shown in Image 0 (9 hours and 32 minutes). However, in Image 1 (10 hours and 16 minutes), the MP is well integrated into the spheroid. The soft MP can be seen shuttled through the spheroid and being deformed as it is moved between cells. Spheroids were also observed to reorganize over the 13-hour period shown. 106 Figure 4-5 Confocal 3D projections of integration of a soft MP into an A375 spheroid at 44-minute intervals (MP: red, cell membrane/spheroid: green; scale bar = 50 µm; rainbow bar = time progression). Confocal 3D projections Soft MP first interacts with and integrates into the spheroid between hour 9 and 10 of imaging, and continues to be displaced in the 107 spheroid through hour 22. Images with the MP outside and not interacting with the spheroid were not included in the figure. 4.4.6 ECM deposition versus MP incorporation in extended study Preliminary H&E staining of HEM spheroids at week 1 (Figure 6A) and week 4 (Figure 6B), two days after adding MPs to the spheroids, show both matrix deposition, increased melanin production over time, and concurrent MP incorporation. A375 spheroids after 1-week maturation period were not as solid as the HEM spheroids, making it difficult to definitively approximate location of the MP (Figure 6C). Figure 4-6 Pilot HEM and A375 spheroid histology. (A) After a 1-week maturation period, histology exhibited a pocket within the spheroid that could be the location of an MP. (B) HEM spheroid maturated for 4 weeks prior to adding MPs exhibit matrix and melanin deposition, and pocket within the spheroid representing MP location. (C) A375 spheroids maturated for 1 week prior to adding MPs. A375 spheroids were not as cohesive as HEM spheroids, making it difficult to confirm MP position. (black arrow = MP location; white arrow: potential MP location/ needs to be confirmed; scale bar = 100 µm) 4.4.7 MP incorporation into NHF spheroids NHFs were used as a secondary control cell type in this study, and showed no difference in soft, stiff, or PS MP penetration, speed, or distance traveled (Supplemental Figure 1, Supplemental Figure 2). 108 4.5 Discussion Results from this study indicated that material mechanical properties influence cell- substrate interactions in melanoma spheroids and can be important for ECM-rich spheroid penetration. Malignant melanoma (A375) spheroids exhibited a greater propensity to incorporate and move around soft MPs (Eelastic ~ 110 Pa) compared to normal melanocyte (HEM) spheroids. Conversely, no difference was observed between incorporation of stiff MPs (Eelastic ~ 9.3 kPa) or PS MPs in melanoma or cancer spheroids. Lastly, all COL-1 coated MPs (soft, stiff, PS) were capable of penetrating mature spheroids through established ECM. Soft MPs penetrated and were internalized to a greater degree in the melanoma spheroids compared to normal cell spheroids. Interestingly, the soft MPs were an order of magnitude more compliant than the cell types used. Typically, in 2D, it is understood that normal cell types have a greater affinity to migrate towards stiffer substrates, known as durotaxis [21]. However, cancer cell types have been shown to lose their stiffness sensing ability as they start to metastasize, and will not abide by typical durotaxis theories [8, 20]. Compared to healthy cell types, cancer cells have exhibited increased motility on compliant substrates (300 Pa), while also being more susceptible to chemotherapeutics on these substrates [19]. Additionally, tumors stiffen as increased matrix deposition occurs and concurrent softening of cells make the cells more motile. This is linked to the cancer cells’ ability to intravasate into blood vessels and metastasize [29]. These previously established theories support our findings that soft MPs had greater displacement within melanoma spheroids compared to healthy melanocyte spheroids. 109 Since particles that are orders of magnitude stiffer than cells are typically used for drug delivery, we used PS MPs as a control to assess any differences between the cancerous and normal cell types. No differences were observed between HEM and A375 cells, but the ultra-stiff MP control showed similar behaviors to the stiff MPs, with less overall MP distance traveled. Qualitatively, once cells attached to the stiff and PS MPs, some spheroids would break off into satellite spheroids (data not shown). An explanation for this could be due to cells stabilizing their focal adhesions and attachment to the MPs due to the substrates’ increased stiffness [12, 30], instead of passing them on through the spheroid. This study identified that mechanical properties of MPs allow for divergent behaviors in melanoma versus normal spheroids, and differences in MP size did not prevent incorporation. Compliant MPs used in this study allow for deformation by cellular forces, while stiff and PS MPs exhibited limited or no deformation. This characteristic could play an important role for in vivo biodistribution and bioavailability. Particle sizes studied in literature range from nanometers up to hundreds of micrometers. Nanometer-sized particles (NPs) used in vitro have shown internalization into individual cells through phagocytosis or endocytosis, while in vivo these NPs tend to have short circulation times and end up accumulating in the spleen, lung and kidneys [3, 25]. Alternatively, MPs that mimic cell size have been shown to interact well with cells in vitro when cells and MPs are combined as co-cultures [2]. However, penetration into tissues and ability to circulate in vivo is limited due to size. Based on our results, the addition of compliance as a material property could bridge the gap between current NP and MP studies because it provides a route for particle incorporation. 110 Although the present study showed successful MP penetration into established tumors models, a limitation is the MP size range of 15-30 µm. Based on literature, decreasing the size of the current MPs to mimic blood cell size of 5-7 µm could allow for increased circulation time allowing for margination and extravasation from blood vessels into tissues [3, 25]. It can further be argued that instead of the internalization of a particle into a cell, as seen with particles < 5 µm in diameter [1, 4, 5, 7, 25], the ability of an MP to be moved around and spread throughout a spheroid would allow for increased, consistent drug delivery. While signaling molecules and matrix metalloprotease expression were beyond the scope this study, the incorporation of COL-1 coated MPs could be due to MP participation in the collagen degradation and cell migration mechanism. The role of cadherins and integrins in normal melanocytes versus melanoma is a growing field. Specifically, normal melanocytes express E-cadherins to maintain communication with neighboring keratinocytes, which help downregulate expression of the αvβ3 integrin, an integrin linked to progress of cancer and other disease [15]. However in melanoma, E-cadherin is downregulated, with concurrent upregulation of N-cadherin, αvβ3, αIIβ3, and α4β1 to allow melanoma cells to communicate with underlying fibroblasts and eventually endothelial cells to enter vasculature [15, 17, 27, 28]. In particular, αvβ3 is a promiscuous integrin, with the ability to bind to a range of ligands and upregulate expression of MMP-1 and activation of MMP-2, which degrades collagen matrix and promotes melanoma cell migration [23, 24]. As the collagen matrix is broken down by MMPs, expression of αvβ3 allows for continued binding to this nonfibrillar or denatured collagen [16]. Combined, this could 111 explain differences observed in the degree of soft MP integration and reorganization within melanoma versus melanocyte spheroids. The built-in modules in Imaris allowed tracking of relative MP and spheroid position. While spheroid movement was tracked in the x,y,z direction to account for whole spheroid movement compared to MP movement, we were unable to account for spheroid rotation. Another limitation of the study is the inability to track individual cells within the spheroid interacting with the MPs. An alternate method could be to use pre-stain cells different colored cell membrane dyes, in conjunction with smaller z-slices and shorter time intervals, to maintain visualization of the cells through the course of the experiment. This study is among the first to visualize MP penetration into developed, mature spheroids, and further confirm material compliance as a key factor. This property not only allowed for initial incorporation into the spheroid, but also increased displacement of the MP within melanoma spheroids. Future work to improve on MP coating to target specific tissues or exchanging polymers to be biodegradable could allow for more effective, targeted therapies. Ultimately, this study helps inform the development of novel, therapeutically-relevant MPs for drug delivery within cancer, and potentially a range of other pathologies. 4.6 Acknowledgements The authors would like to thank Elena Oancea for discussions on melanoma and the Center for Predictive Biology for use of the Opera PhenixTM. Thank you to Benjamin Wilks, Kali Manning, and Jeffrey Morgan for guidance with making spheroids and further analysis. Thank you to Vera Fonseca for help with staining spheroids, and Jessica Sadick, Rafael Gonzalez-Cruz, and Nicholas Labriola for useful discussions on data analysis. This 112 work was supported by awards from the National Institute of Health (R01 AR063642, P20 GM104937) and the National Science Foundation (CAREER CBET 1253189). The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation or National Institutes of Health 113 4.7 References 1. 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Sen Gupta, A., Role of particle size, shape, and stiffness in design of intravascular drug delivery systems: insights from computations, experiments, and nature. Wiley Interdiscip Rev Nanomed Nanobiotechnol. 8(2): p. 255-70, 2016. 26. Shah, M.K., Garcia-Pak, I.H., and Darling, E.M., Influence of Inherent Mechanophenotype on Competitive Cellular Adherence. Ann Biomed Eng. 45(8): p. 2036-2047, 2017. 27. Trikha, M., Timar, J., Lundy, S.K., Szekeres, K., Cai, Y., Porter, A.T., and Honn, K.V., The high affinity alphaIIb beta3 integrin is involved in invasion of human melanoma cells. Cancer Res. 57(12): p. 2522-8, 1997. 28. van der Flier, A. and Sonnenberg, A., Function and interactions of integrins. Cell Tissue Res. 305(3): p. 285-98, 2001. 29. Weder, G., Hendriks-Balk, M.C., Smajda, R., Rimoldi, D., Liley, M., Heinzelmann, H., Meister, A., and Mariotti, A., Increased plasticity of the stiffness of melanoma cells correlates with their acquisition of metastatic properties. Nanomedicine. 10(1): p. 141-8, 2014. 30. Yeung, T., Georges, P.C., Flanagan, L.A., Marg, B., Ortiz, M., Funaki, M., Zahir, N., Ming, W., Weaver, V., and Janmey, P.A., Effects of substrate stiffness on cell morphology, cytoskeletal structure, and adhesion. Cell Motil Cytoskeleton. 60(1): p. 24-34, 2005. 117 4.8 Supplemental Figure Figure 4-7 Assessment of incorporation of soft, stiff and PS MPs within control NHF spheroids. (A-B) MP penetration towarads the center were not significantly different in NHF spheroids, when comparing velocity or linear regression analyses of MP position (soft: n=6; stiff: n=6; PS: n=7). (C-D) Overall speed of MPs was the same in spheroids of both cell types as shown by slopes and MP location over time. Data shown as linear regression of slopes with 95% prediction intervals of soft and stiff MP penetration. Data shown as mean ± S.D., with statistical significance determined using a one-way ANOVA comparing MP stiffness., followed by a Tukey’s post hoc analysis (*p<0.05). 118 Figure 4-8 Confocal 3D projections at last time point of HEM, A375, and NHF spheroids with MP integrated (MP: red, cell membrane/spheroid: green; scale bar = 50 µm; rainbow bar = time progression). 119 Chapter 5 5 Conclusion and Future Work Mechanophenotype is a descriptor of cellular fate and function. The work in this thesis confirmed that mechanophenotype should be considered as an important parameter for cell and tissue engineering purposes. The first part of this thesis described the regenerative and mechanical heterogeneity of cells residing within the stromal vascular fraction (SVF) of adipose tissue, relating the role of cell type to mechanophenotype. Next, we described how cellular mechanophenotype influences mechanosensing and subsequent cell-cell-substrate organization, specifically using mechanophenotype as a descriptor for competitive adherence of cells to neighboring surfaces (i.e., cell or collagen-1 coated gels). Lastly, we assessed incorporation of compliant microparticles (MP) into normal and cancerous spheroids. 5.1 Chapter 2 Chapter two assessed the mechanical heterogeneity and regenerative potential of cell types populating the SVF of adipose tissue. Adipose tissue is made up a range of cell types, including mesenchymal stem cells, endothelial cells, smooth muscle cells, adipocytes, and other cell types contained within the vasculature [4, 18]. Many of the resident cell types exhibited similar mechanophenotype: endothelial cells, pre-adipocytes, 120 and ASCs. However, smooth muscle cells exhibited a much stiffer mechanophenotype, which may suggest their role in adipose tissue in providing structure to the blood vessels they line.[12] When assessing regenerative potential, the unsorted SVF yielded the greatest potential for adipogenic and osteogenic metabolite production, followed by the sorted ASCs. Endothelial cells, pre-adipocytes, and smooth muscle cells showed little metabolite production on their own. This suggested that the unsorted population may benefit from paracrine signaling from the other cell types present. This study took the first step in defining the mechanophenotype of the resident cell types within adipose tissue. Some other applications of this technique could be in understanding cancer tumors and their surrounding healthy tissue, and the role that both intracellular and extracellular mechanical properties play within a tumor prior to metastasis. 5.2 Chapter 3 Chapter three investigated the influence of mechanophenotype on competitive adherence of cells, either to an underlying substrate or a neighboring cell. The use of transfected cells provided a controlled system to understand the role mechanophenotype plays showing that cells preferentially adhered to the stiffest surface they could sense. While this hypothesis was only tested in a mature, differentiated cell type (fibroblasts), different results could be expected in primary cells or other epithelial cell type with natural cell-cell adhesion tendencies. While our theory could hold for mature, terminally differentiated cell types, stem cells, progenitor cells, and cancer cells may react differently due to their inherent plasticity. Additionally, use of stable transfections allowed for endogenous protein expression to be maintained, which led to some overlap in 121 mechanophenotype of the cells used in this study. To test if the conservation of endogenous protein expression plays a role, completely silencing or over-expressing proteins through use of siRNA or plasmid transfection, respectively, would provide more compelling results. Furthermore, use of the GFP reporter can also disrupt cellular machinery [5], so elimination of this reporter would provide fewer confounding variables when studying mechanophenotype. Additionally, this study reported findings that were divergent from the field, indicating that mechanophenotype of cells on compliant substrates maintained their mechanical properties instead of adapting to underlying substrates. This may be compounded by varying cadherin and integrin profiles that adhere to different extracellular matrix protein coatings [7, 15]. Cadherins and integrins are the main adhesive components in tissues and facilitate cell-cell and cell-substrate interactions, respectively [6, 8, 17]. To better understand the mechanisms behind these cell-substrate interactions, blocking of either specific cadherins or integrins could give light to specific components involved in competitive adherence of cells. In addition, performing western blots or ELISAs on proteins involved in the cadherin-integrin mechanism within the Rho/ROCK pathway, as well as those involved in motility, mechanosensing, and cytoskeletal structure could further clarify their role in cell-cell-substrate organization and exhibition of a specific mechanophenotype. 5.3 Chapter 4 Chapter four investigated the incorporation of collagen-1-coated “soft” and “stiff” MPs into mature melanoma and healthy melanocyte spheroids. While both MPs were easily 122 incorporated into the spheroids of both cell types, soft MPs were shuttled faster towards the center and traveled the most within the melanoma spheroids. Since particle penetration through deposited extracellular matrix has been limited, it was surprising to see the hyper- compliant MPs being easily shuttled around within the spheroid. There are many theoretical explanations for these results that could be further investigated. For example, only 2 cell types were extensively assessed in this study: A375, a malignant melanoma cell line, and HEM, a normal melanocyte primary cell type. It would be interesting to assess differences within other conditions: (1) cell lines vs. primary cell types since many molecular and physical changes occur in vitro [9, 10], (2) other melanoma cell lines, (3) other cancer pathologies, and (4) stem cells. MP penetration into spheroids based on elasticity creates an interesting platform to study a range of different parameters, including particle deformation and mechanisms for incorporation in vitro. First, the soft MPs were significantly deformed by the cells as they were moved through the spheroid. The ability to deform is a hallmark of many cell types in the body, especially those that extravasate/intravasate through blood vessels and into tissues [2, 14]. Further comparisons between the MPs and these cell types may allow for the better understanding of cellular forces exhibited in mature tissues. Second, altering the coating on the MPs could provide more insight into the interplay between integrins, cadherins, and extracellular matrix (ECM). While the MPs are passively pushed around within the spheroid with the collagen-1 coating (an ECM protein), would this change with a cadherin coating, where the cells identify the MP as another cell? Recently, cell membrane extracts have been used as surface coatings, potentially increasing the chances of targeting specific cell types or tissues [16]. Lastly, once the size of these particles can 123 be limited to 5 - 10 µm in diameter, it would be interesting to visualize the behavior of these MPs in vivo, with the expectation of increasing their bioavailability and biodistribution compared to current alternatives. Lastly, the MPs used in this study were fabricated using polyacrylamide. While this polymer was perfect for initial studies because they are easily mechanically tunable and can be coated with a range of proteins, polyacrylamide does not degrade and is not currently FDA approved [11, 13]. Additionally, when looking at drug loading/ release kinetics, polyacrylamide has a large burst release and extremely limited long-term release properties. A solution to continue using polyacrylamide as the main component, the MPs can be loaded with slow-releasing nanoparticles, using the MPs as a carrier in vivo. Alternatively, another polymer with similar mechanical properties, but that is biodegradable, biocompatible, and already FDA approved, could be used, such as polyethylene glycol (PEG), collagen, alginate, or poly(lactic-co-glycolic acid) (PLGA) [1- 3, 14]. 5.4 Closing Remarks The goal of this thesis was to elucidate the importance of mechanical properties of both cells and the substrates with which they interact. This is evident in the studies depicted here, from defining the mechanophenotype of individual resident cells within a tissue, to elucidating the influence mechanophenotype play in competitive adherence between cells and substrates, and lastly assessing the role of material elasticity in a more clinically relevant system of melanoma versus melanocyte spheroids. 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