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Viscoelastic Hydrazone Covalent Adaptable Networks to Study Chondrocyte Mechanobiology for

Cartilage Tissue Engineering

by

Benjamin McGlenn Richardson

B.A., Rensselaer Polytechnic Institute, 2015

M.S., University of Colorado Boulder, 2017

A thesis submitted to the

Faculty of the Graduate School of the

University of Colorado in partial fulfillment

of the requirement for a degree of

Doctor of Philosophy

Department of Chemical and Biological Engineering

2020

Thesis Committee

Adviser: Dr. Kristi S. Anseth

Dr. Stephanie J. Bryant

Dr. Virginia L. Ferguson

Dr. Jeffry W. Stansbury

Dr. Franck J. Vernerey

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Abstract

Richardson, Benjamin M. (Ph.D., Chemical Engineering)

Viscoelastic Hydrazone Covalent Adaptable Networks to Study Chondrocyte Mechanobiology for

Cartilage Tissue Engineering

Thesis directed by Professor Kristi S. Anseth

Symptomatic knee osteoarthritis is estimated to affect nearly 1 in 5 Americans over the age of 45.

Osteoarthritis patients often experience pain caused by damage to articular cartilage in load-bearing joints.

Matrix-assisted autologous chondrocyte transplantation (MACT) has emerged as a promising tissue engineering strategy to enhance the ability of chondrocytes to repair cartilage defects. This strategy often employs water-swollen polymer networks, known as hydrogels, as delivery vehicles to support chondrocytes and permit extracellular matrix (ECM) deposition. Hydrogels used for cartilage tissue engineering can be covalently crosslinked to withstand compressive forces experienced in articulating joints. However, traditional covalent crosslinks exhibit elastic responses to mechanical deformation and can limit ECM deposition to pericellular space. One potential strategy to improve regenerative outcomes of MACT is to incorporate viscoelastic properties, making hydrogels more similar to the viscoelastic ECM chondrocytes experience in vivo. However, few covalent hydrogels used for cartilage tissue engineering exhibit viscoelastic properties. Moreover, the effects of viscoelasticity (e.g., stress relaxation, creep compliance) on cartilage tissue engineering remain largely understudied.

Covalent adaptable networks (CANs) represent a rapidly growing class of polymers with reversible covalent crosslinks which potentially offer both robust mechanical support and viscoelastic network reorganization for cartilage tissue engineering. In this thesis, we aim to add to this growing body of research by examining the effects of mechanobiological cues on chondrocytes encapsulated in hydrazone CANs.

First, we sought to engineer hydrazone CANs with user-defined control over the viscoelastic properties by

ii leveraging differences in the equilibrium kinetics of -hydrazone and benzyl-hydrazone crosslinks.

Next, viscoelastic stress relaxation timescales of these networks are investigated to modulate ECM deposition by encapsulated chondrocytes. Then viscoelastic creep compliance is examined to temporally direct chondrocyte morphology during mechanical deformation. Finally, mechanobiological interactions between viscoelasticity and dynamic compression on chondrocytes in hydrazone CANs are studied using dynamic compression bioreactors to simulate biomechanical forces experienced within articulating joints.

Overall, this work lends insight about how viscoelastic material properties influence chondrocyte behavior in hydrazone CANs with the hope of informing the design of polymer matrices for cartilage tissue engineering to treat osteoarthritis in load-bearing joints.

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Acknowledgments

First and foremost, I would like to thank my thesis adviser Dr. Kristi Anseth. I remember meeting with you during my first semester at the University of Colorado and being blown away. I said to myself after that meeting, this woman is amazing how can I work with and learn from her. Your mentorship over the last five years, and the experience of being a member of your world-class research group has without a doubt been one of the richest learning experiences of my life. I am a better scientist and a better person through your dedicated efforts. I also want to thank my thesis committee Dr. Stephanie Bryant, Dr. Virginia

Ferguson, Dr. Jeff Stansbury, and Dr. Franck Vernerey and my collaborator Mark Randolph for the guidance you have provided during my time at the University of Colorado.

I would also like to thank the other members of the Anseth Research Group. Specifically, I would like to thank Dr. Kemal Arda Gűnay, Dr. Laura Macdougall, and Dr. Tobin Brown for mentoring me and helping Kristi shape my scientific identity. I would also like to thank my by graduate and undergraduate student collaborators, Cierra Walker, Mollie Maples, Daniel Wilcox, and Jack Hoye. I would also like to give a special thanks to my desk mate Ben Carberry for late night talks in the lab.

In addition to my professional life, I also need to thank my friends. I have had the privilege to know many special people during my life and the people I have met in Colorado are no exception. I want to name

Mike Hjortness, Katie Manduca, Jacob Fenster, Alex Delluva, Adrianne Blevins, Archish Muralidharan,

David Bull, Alexandra Morris, Lyle Bliss, Ben Coscia, Jenna Wagenblatt, the rest of my classmates and the LaCoix Bois. You have made my time here immensely more enjoyable and I am excited for many more adventures with you in the future. I also need to give special thanks to Bryce Manubay and James Gallant for being there for me at my best and at my worst. And to Grace Ramsey: thank you for supporting me.

Whether you were making sure I ate food while writing my thesis or just lending emotional support, your presence has been indispensable these last few weeks. Finally, I also want to thank my friends from back in Maine, my friends from New York, and all of the people I have met along the way that have made my life rich and fulfilling but are too numerous to list here.

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And finally, to my family. To my siblings Josh, Julia, and Karina: thank you for being there for me.

I am so unbelievably proud to be related to each of you and each of you give me valuable perspective on life, the world, and everything. To my mother and father: You have made me the person I am today more so than anyone else and I am eternally grateful. I couldn’t wish for parents who care more about me and I will never forget the sacrifices you made for me.

I am extremely grateful for the love and support that has enabled me to pursue this degree. Thank you.

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Table of Contents

Chapter 1 - Introduction ...... 1 1. Cartilage tissue engineering to treat osteoarthritis ...... 1 1.1. Articular cartilage structure and function ...... 1 1.1.1. Chondrocytes ...... 3 1.1.2. Extracellular matrix (ECM) ...... 4 1.1.3. Mechanical properties of articular cartilage ...... 5 1.2. Prevalence, symptoms and etiology of osteoarthritis ...... 6 1.3. Limitations of current osteoarthritis treatment strategies ...... 7 1.3.1. Joint arthroplasty ...... 8 1.3.2. Surgical intervention procedures ...... 8 1.3.3. Cell and matrix based treatments ...... 10 1.4. Polymer scaffold design considerations for MACT ...... 13 1.5. Dissertation approach ...... 21 1.6. References ...... 21

Chapter 2 - Background ...... 34 2. Dynamic covalent hydrogels as biomaterials to mimic the viscoelasticity of soft tissues ...... 34 2.1. Abstract ...... 34 2.2. Introduction ...... 34 2.3. Mechanical signatures of viscoelasticity ...... 37 2.4. Viscoelasticity of native tissues ...... 41 2.5. Viscoelastic networks with reversible crosslinks and their relaxation mechanisms ...... 45 2.6. Viscoelastic hydrogels with dynamic chemical bonds ...... 50 2.6.1. Diels-Alder reactions ...... 53 2.6.2. ...... 54 2.6.3. Boronates ...... 60 2.6.4. Adaptable sulfur chemistries ...... 63 2.7. Summary and Outlook ...... 70 2.8. References ...... 74

Chapter 3 - Objectives ...... 98 3. Overview ...... 98 3.1. The specific aims of this thesis ...... 99 3.2. References ...... 101

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Chapter 4 - Aim 1 ...... 104 4. Hydrazone covalent adaptable networks modulate extracellular matrix deposition for cartilage tissue engineering ...... 104 4.1. Abstract ...... 104 4.2. Introduction ...... 105 4.3. Materials and methods ...... 109 4.3.1. and macromer synthesis ...... 109 4.3.2. Macromer purification and characterization ...... 110 4.3.3. Hydrogel formation and rheological characterization ...... 110 4.3.4. Acellular swelling and mass loss behavior ...... 111 4.3.5. Chondrocyte isolation, encapsulation and cell culture ...... 111 4.3.6. Biochemical analysis of cell-laden hydrazone CANs ...... 112 4.3.7. Histological sectioning, staining and immunofluorescence ...... 113 4.3.8. Statistical analysis ...... 114 4.4. Results ...... 114 4.4.1. Hydrogel formation and shear moduli ...... 114 4.4.2. Two-element stretched exponential to model stress relaxation ...... 115 4.4.3. Alkyl and benzyl-hydrazone hydrogel formation and shear moduli ...... 117 4.4.4. Hydrogel formulations based on Flory-Stockmayer theory ...... 118 4.4.5. CANs with intermediate covalent adaptability enhance cellularity ...... 119 4.4.6. Interconnected sGAG matrix in viscoelastic CANs ...... 120 4.4.7. Significantly enhanced collagen deposition in viscoelastic CANs ...... 122 4.4.8. Average relaxation time and ECM deposition ...... 123 4.4.9. Articular cartilage specific ECM deposition ...... 125 4.5. Discussion ...... 126 4.6. Conclusion ...... 130 4.7. References ...... 131

Chapter 5 - Aim 2 ...... 136 5. Viscoelasticity of hydrazone crosslinked poly( glycol) hydrogels directs chondrocyte morphology during mechanical deformation ...... 136 5.1. Abstract ...... 136 5.2. Introduction ...... 137 5.3. Materials and Methods ...... 139 5.3.1. alkyl PEG aldehyde synthesis ...... 139

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5.3.2. benzyl PEG aldehyde synthesis ...... 140 5.3.3. PEG hydrazine synthesis ...... 140 5.3.4. Macromer purification and characterization ...... 141 5.3.5. Hydrogel formulation ...... 144 5.3.6. Shear rheometry and modeling ...... 144 5.3.7. Chondrocyte isolation and cell culture ...... 146 5.3.8. In situ deformation microscopy ...... 146 5.3.9. Histological sectioning and staining ...... 149 5.3.10. Quantitative real-time polymerase chain reaction (qRT-PCR) ...... 149 5.3.11. Statistics ...... 150 5.4. Results and Discussion...... 150 5.4.1. Viscoelastic alkl-hydrazone and elastic benzyl-hydrazone hydrogels ...... 150 5.4.2. Viscoelastic creep compliance influences chondrocyte morphology during deformation 152 5.4.3. Viscoelasticity alters biophysical cues over time during mechanical deformation ...... 155 5.4.4. Matrix deposition influences the transmission of biophysical cues ...... 158 5.5. Conclusion ...... 160 5.6. References ...... 161

Chapter 6 - Aim 3 ...... 167 6. Mechanobiological interactions between dynamic compression and viscoelasticity on chondrocytes in hydrazone covalent adaptable networks for cartilage tissue engineering ...... 167 6.1. Abstract ...... 167 6.2. Introduction ...... 168 6.3. Materials and methods ...... 171 6.3.1. Organic synthesis ...... 172 6.3.2. Chemical purification ...... 172 6.3.3. 1H-NMR spectroscopy ...... 173 6.3.4. Shear rheology ...... 173 6.3.5. Chondrocyte isolation, encapsulation and culture ...... 174 6.3.6. Quantitative polymerase chain reaction (qPCR) ...... 174 6.3.7. Biochemical assays ...... 175 6.3.8. Linear regression analysis ...... 176 6.3.9. Histological sectioning and staining ...... 176 6.3.10. Statistics ...... 176

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6.4. Results and discussion ...... 176 6.4.1. Formulation of hydrazone CANs with consistent shear moduli ...... 176 6.4.2. The dynamic viscoelastic properties of hydrazone CANs ...... 179 6.4.3. Hydrazone CANs maintain encapsulated chondrocyte populations during dynamic compression ...... 184 6.4.4. Viscoelasticity improves the expression of articular cartilage specific genes ...... 185 6.4.5. Viscoelasticity of hydrazone CANs influences the effects of dynamic mechanical compression on chondrocyte biosynthesis ...... 187 6.5. Conclusion ...... 192 6.6. Supporting Information ...... 193 6.7. References ...... 197

Chapter 7 - Conclusions and Recommendations ...... 205 7. Summary of Findings ...... 205 7.1. Implications ...... 206 7.2. Future Directions...... 208 7.2.1. Investigate chondrocyte response to a wide range of dynamic loading frequencies and compressive strains in hydrazone CANs ...... 208 7.2.2. Hydrazone CANs as bioinks for 3D bioprinting to promote shape-specific cartilage regeneration ...... 209 7.2.3. Investigate alternative cell sources for cartilage tissue engineering in hydrazone CANs 210 7.2.4. Hydrazone CANs to heal cartilage defects in a large animal model ...... 210 7.3. References ...... 211

Chapter 8 - Bibliography ...... 215 8. References by chapter ...... 215 8.1. Chapter 1 ...... 215 8.2. Chapter 2 ...... 228 8.3. Chapter 3 ...... 252 8.4. Chapter 4 ...... 255 8.5. Chapter 5 ...... 261 8.6. Chapter 6 ...... 266 8.7. Chapter 7 ...... 274

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List of Tables

Table 1.1 Advantages and disadvantages of naturally derived polymers for tissue engineering applications. Adapted with permission from Spicer et al. [117] copyright The Royal Society of Chemistry 2020...... 14

Table 1.2 Advantages and disadvantages of synthetically derived polymers for tissue engineering. Adapted with permission from Spicer et al. [117] copyright The Royal Society of Chemistry 2020...... 16

Table 5.1 Tabulated variables related to synthesis reactions and hydrogel formulation ...... 142

Table 5.2 Tabulated primers used for qRT-PCR ...... 149

Table 6.1 Primers used for qRT-PCR...... 175

Table 6.2 Viscoelastic properties and rates of chondrocyte matrix deposition for hydrazone CANs during free swelling and dynamic compression culture...... 189

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List of Figures

Figure 1.1 Diagram illustrating the structure and composition of articular cartilage. (a) Shows organization within the tissue with labels indicating distinct regions starting at the joint cavity (top) and ending at the underlying bone (bottom). (b) Inset shows the pericellular space with chondrocytes organized into chondrons. (c) The major molecular components of the ECM. (d) Inset shows the hierarchical structure of collagen from the polypeptide sequence to the fiber organization. (e) Inset shows the organization of brush- like aggrecan molecules. Adapted with permission from Baumann et al. [15] copyright Springer Nature Switzerland AG 2019...... 3

Figure 1.2 Illustration represents pathophysiological changes in a human knee joints during osteoarthritis. (a) A heathy human knee joints shows normal organization of bone, cartilage, tendons, and muscle. (b) Osteoarthritis is primarily characterized by severely worn and damaged articular cartilage tissue. The surrounding tissues can also experience deterioration or malformation contributing to the disease burden. Adapted with permission from Hunter et al. [58] copyright Massachusetts Medical Society 2015...... 7

Figure 1.3 Schematic illustrating two common surgical intervention techniques for treating osteoarthritis in load-bearing joints. (a) Mosaicplasty involves transplanting osteochondral plugs from one part of the joint to more critically located cartilage defects. (b) Microfracture involves perforating the knee joint to allow cells, growth factors, and nutrients from the underlying subchondral bone to reach the defect site. Adapted with permission from Dai et al. [77] copyright Springer Science + Business Media Singapore 2016...... 9

Figure 1.4 Schematic illustrating two common cell and matrix techniques for repairing articular cartilage in load-bearing joints. (a) Cartilage biopsies allow a patient’s chondrocytes to be isolated and expanded in vitro. (b) When chondrocytes are directly delivered to the defect site the treatment known as autologous chondrocyte implantation (ACI). When a supportive polymer matrix is added the technique known as matrix-assisted autologous chondrocyte transplantation (MACT). Adapted with permission from Dai et al. [77] copyright Springer Science + Business Media Singapore 2016...... 11

Figure 1.5 Tissue engineering and regenerative medicine represent multidisciplinary intersections of medicine, cell biology, materials chemistry, and polymer physics. (a) For regenerative medicine, cells are isolated from human patients in medical settings. Homogenous cell populations are created by cell biologists using cell sorting for specific tissue targets. Cells are then expanded in vitro before being

xi encapsulated within a hydrogel scaffold and implanted back into the patient. (b) Incorporating biochemical and biomechanical cues into hydrogel scaffolds allows for user-defined control over cell behavior for tissue engineering. Materials scientists are able to tailor hydrogel properties to study and direct cell-cell and cell- matrix interactions. This allows new materials to be developed to improve clinical outcomes for engineered tissues. Adapted with permission from DeForest et al. [116] copyright Annual Reviews 2012...... 13

Figure 1.6 Mechanical properties of traditionally elastic covalent crosslinks and viscoelastic dynamic covalent crosslinks. (a) -ene crosslink formation is an irreversible process locking polymer conformations in place and limiting energy dissipation. During mechanical testing this elastic behavior manifests as a linear stress–strain curve as well as frequency and strain independent moduli. (b) Conversely, equilibrium between forward and reverse reactions for hydrazone linkages lead to viscoelastic material properties. Dynamic covalent hydrogels demonstrate hysteresis, frequency dependent crossovers and shear- thinning behavior. Adapted with permission from Rosales et al. [135] copyright Springer Nature 2016. . 21

Figure 2.1 Complex cell-cell and cell-matrix interactions influence cell behavior in 3D environments. (a) Biochemical and biophysical cues in the extracellular matrix (ECM) influence cell behavior. Fig 2.1a adapted from Madlet al. [11] copyright 2018 Annual Review of Biomedical Engineering (b) Engineering the cellular microenvironment with dynamic materials can elicit spatiotemporal control over biophysical cues to direct cell fate. Fig 2.1b adapted from Ma et al. [30] copyright 2018 Wiley...... 37

Figure 2.2 Methods for characterizing viscoelasticity of soft materials (e.g., hydrogels, tissues). (a) The application of a step change is often used to measure dissipative (viscous) material behaviors. When a step strain γ0 is applied, stress relaxation is measured. Conversely, when a constant stress σ0 is applied to the material, a creep test measures the material deformation or creep compliance. (b) Cyclic measurements allow researchers to decouple elastic (in-phase) and viscous (out-of-phase) material responses in real time. Cyclic measurements are often used over a range of frequencies in order to obtain a frequency sweep spectra, which illustrate how a material will respond to mechanical stimuli as a function of application rate. (c) Particle tracking microrheology is a useful technique for investigating local as opposed to bulk changes in material properties. For example, microrheology allows researchers to study microenvironmental changes in viscoelastic properties due to cell-secreted proteases. Fig. 2.2c adapted from Schultz et al. [40] copyright 2015 the National Academy of Sciences of the United States of America. (d) Magnetic resonance elastography (MRE) uses magnetic resonance imaging (MRI) imaging with low-frequency vibrations to spatially map viscoelastic properties. Here, the elastic storage modulus (G’) and viscous loss modulus (G’’) are spatially resolved in a transverse section of human brain, demonstrating this technique’s ability to

xii generate visual representations of whole-tissue mechanical characteristics. Fig. 2.2d adapted from Weickenmeier et al. [47] copyright 2018 Elsevier. (e) Indentation measurements such as atomic force microscopy (AFM) allow nanoscale resolution of tissue mechanics. Here, articular cartilage shows different moduli for collagen fibrils and proteoglycans, illustrating higher-resolution information than is possible with other measurement techniques. Scale bars represent 2 μm. Fig. 2.2e adapted from Loparic et al. [50] copyright 2010 Elsevier. (f) Each technique is characterized by accessible timescales, illustrating that limitations of each technique typically require multiple approaches to fully understand complex viscoelastic behaviors of soft materials...... 40

Figure 2.3 Viscoelastic properties of native tissue. (a) Schematic illustrating the scale of soft tissue moduli. Fig. 2.3a Adapted from Discher et al. [65] copyright 2009 AAAS. (b) Stress relaxation profiles of soft tissues: adipose [66], liver [67], brain [68], lung [69], prostate [64], cervix [70], muscle [71], hematoma [63], and heart valve [72]. Early relaxation profiles are not shown when the test procedure did not use a step strain. (c) Technical setup and representative magnetic resonance elastography (MRE) images showing brain, liver, and femoral muscle tissue. (d) Changes in the viscoelastic power law behavior of brain, liver and skeletal muscle as a result of natural physiology or pathology from human MRE data. Fig. 2.3c-d adapted from Sack et al. [46] copyright 2013 Royal Society of Chemistry...... 45

Figure 2.4 Correlations between macroscale viscoelasticity and covalent bond dynamics. (a) Temperature dependent Diels-Alder/Retro-Diels-Alder reaction between furan and maleimide. (b) Viscoelastic frequency dependence is consistent with predicted values from kinetic analysis. Adapted from Adzima et al. [88] copyright 2008 American Chemical Society. (c) Polymer hydrogels based on reversible hydrazone bonds. (d) Engineering stress (σeng) graphed by extension ratio (λ) for different self-healing times, illustrating agreement between material behavior and acyl-hydrazone bond dynamics. Adapted from Liu et al. [90] copyright 2012 American Chemical Society. (e) Differences in reaction kinetics between phenylboronic acid derivatives in the presence of cis‐diols. (f) Varying the stoichiometric amounts of phenylboronic acid (PBA) to o-aminomethylphenylboronic acid (APBA) influences stress relaxation in boronate hydrogel networks. Figure adapted from Yesilyurt et al. [91] copyright 2017 Wiley...... 48

Figure 2.5 Addition and exchange mechanisms for dynamic covalent crosslinks. (a) Addition reactions (e.g., boronates) require breaking and reforming crosslinks, which results in kinetic dependence on the association and disassociation rate constants. (b) Equilibrium constants for addition reactions are strongly dependent on both temperature and concentrations. (c) In contrast, exchange reactions (e.g., ) result in bond rearrangement without crosslink cleavage. (d) For exchange reactions the

xiii reactants and products are the same. Therefore, the equilibrium constant is independent of temperature and the exchange rate is not influenced by concentrations of the reactive species...... 49

Figure 2.6 Cytocompatible dynamic covalent chemistries. Chemical reactions are grouped by reorganization mechanism; addition reactions, exchange reactions, and both mechanisms. (a) Diels-Alder [104,105,114–118,106–113] (b) Boronate [91,119,128–137,120,138–146,121–127] (c) [92,93,147–153] (d) Ally [154–163] (e) Schiff base [164,165,174,175,166–173] (f) Hydrazone [27,71,181–190,87,191–200,89,201–210,100,211,212,176–180] (g) [176,180,221,213–220] (h) [222,223,232–234,224–231]...... 53

Figure 2.7 Dynamic hydrazone hydrogels. a) Stress relaxation of dynamic hydrazone crosslinks allows motor neurons to extend axon bodies into the hydrogel. (i) Stress relaxation of alkyl-hydrazone crosslinks. (ii) Dynamic hydrazone equilibrium reaction responsible for network stress relaxation. (iii) Embryonic stem cell-derived motor neurons in PEG hydrazone hydrogels stained with Calcein (green) for live cells, and Ethidium Homodimer (red) for dead cells. Scale bar is 200 μm. (iv) Stress relaxation-mediated axon extension allows cellular forces to be calculated. Fig. 2.7a adapted from McKinnon et al. [100] copyright 2014 Royal Society of Chemistry. (b) Dynamic hydrazone crosslinks and network stress relaxation regulate cell spreading and focal adhesion of hMSCs in 3D. (i) Stress relaxation of dynamic hydrazone crosslinks promotes cell spreading. (ii) Comparison with static controls illustrates that dynamic covalent crosslinks allow cells to remodel their local microenvironment. (iii) Dynamic crosslinks lead to significant differences in cell morphology and the percentage of cells that form focal adhesions. Fig. 2.7b adapted from Lou et al. [198] copyright 2017 Elsevier. (c) Hydrazone crosslink dynamics tuned by introducing a small molecule catalyst to facilitate injectable delivery of human umbilical vein endothelial cells (HUVECs). (i) Temporal modulation of injectability is based on small molecule catalyst diffusion. (ii) High cell viability was observed post-injection in the presence of catalyst. (iii) Stress relaxation could be modulated in hydrazone hydrogels using both catalyst concentration and polymer content. (iv) The schematic represents the hydrazone reaction including the mechanism of catalysis. Fig. 2.7c adapted from Lou et al. [210] copyright 2018 Wiley. (d) Dynamic exchange of hydrazone crosslinks facilitates extrusion bioprinting of NIH T3T fibroblasts. (i) Shear-thinning hydrazone hydrogels allow 3D printing of self‐healing hydrazone bonds. (ii) Macroscopic view of 4‐layer 3D printed hydrazone lattices. (iii) Hydrazone hydrogel viscosity decreases with increasing shear rates to enable 3D printing. (iv) Live/dead staining within lattice filaments after extrusion verifies cytocompatability of the printing technique. Fig. 2.7d adapted from Wang et al. [238] copyright 2018 Wiley...... 59

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Figure 2.8 Dynamic boronate hydrogels. (a) Glucose-sensitive boronate hydrogels enable self-healing branched tubular channels for tissue engineering. (i) Rheological testing at high and low strain illustrates shear-thinning and self-healing of dynamic boronate crosslinks. (ii) Extruded cell-laden dynamic boronate hydrogels form sacrificial tubular structures surrounded by static hydrogel. (iii) Seeding vascular constructs with multiple cell types reveals morphological structures resembling neurovascular units (red fluorescence: endothelial cells, green fluorescence: neural stem cells. Fig. 2.8a adapted from Tseng et al. [140] copyright 2017 Elsevier. (b) Hybrid networks containing reversible boronate bonds and permanent crosslinks allow viscoelastic mechanotransduction to be isolated without degradation. (i) Schematic illustrating chemical structures of static strain-promoted azide- cycloaddition (SPAAC) crosslinks and dynamic boronate crosslinks. (ii) Stress relaxation increases subcellular location of YAP/TAZ. (iii) Stress relaxation also influences cell morphology and cell volume (orange: F-actin, blue: nucleus, magenta: YAP/TAZ) Scale bar represents 5 µm. Fig. 2.8b adapted from Tang et al. [131] copyright 2018 Wiley. (c) Dynamic boronate chemistry crosslinks enable self-healing and cell infiltration. (i) Schematic illustrating boronate equilibrium and an image of a self-healing hydrogel hang test. (ii) Rheological strain sweep shows rupture and self- healing of dynamic boronate hydrogels. (iii) Pulmonary fibroblasts (green: CCL151) and breast cancer cells (pink: MDAMB231) co-cultured in cut boronic acid-based hydrogels with cell infiltration quantified after self-healing. Fig. 2.8c adapted from Smithmyer et al. [139] copyright 2018 American Chemical Society. (d) Injectable hydrogels cross-linked by boronic acid-fructose complexation. (i) Schematic illustrates HA hydrogels with dynamic boronate crosslinks. (ii) Chemically distinct boronic acid derivatives result in user- defined control over frequency dependent viscoelasticity. The storage modulus (G’) and loss modulus (G’’) vary as a function of oscillation frequency, illustrating accessible regimes for injectable cell delivery. Fig. 2.8d adapted from Figueiredo et al. [127] copyright 2019 American Chemical Society...... 63

Figure 2.9 Dynamic hydrogels based on adaptable sulfur chemistries. (a) Mechanoresponsive PEG hydrogels with disulfide linkages can be functionalized through applied force. (i) Schematic illustrates force induced cleavage of disulfide crosslinks followed by Michael-type addition of an acceptor molecule. (ii) Mechanical testing shows stress–strain failure for disulfide crosslinks at various compression speeds. (iii) MSCs seeded on hydrogel-protein substrates with or without compression illustrating force dependent functionalization of hydrogels with adhesion proteins. Fig. 2.9a adapted from Lee et al. [234] copyright 2016 Royal Society of Chemistry. (b) Dynamic thioester crosslinks form wound sealants which rapidly dissolve by thioester exchange when exposed to small molecule . (i) Photographs show thioester hydrogels (green) adhered to human skin under torsion. (ii) Exposure to thiolate solutions causes exponential decay of thioester hydrogel moduli. (iii) Visualization of hydrogel sealant dissolution by thioester exchange in a cytocompatible solution of L‐cysteine methyl . Fig. 2.9b adapted from Ghobril

xv et al. [150] copyright 2013 Wiley. (c) Thioester exchange facilitates spreading, proliferation and migration of hMSCs in 3D scaffolds. (i) Chemical schematic shows thioester exchange reaction. (ii) hMSCs in viscoelastic thioester hydrogels proliferate significantly compared to static controls. (iii) Thioester-based hydrogels stress relax faster with excess thiol. (iv) Confocal fluorescence microscopy illustrates morphological differences between hMSCs in static non-thioester controls and dynamic excess thiol thioester hydrogels. Scale bars represent 100 μm Fig. 2.9c adapted from Brown et al. [92] copyright 2018 Elsevier. (d) Photo-induced exchange of allyl sulfide bonds enables the formation of intestinal organoid structures in 3D. (i) Chemical schematic shows light mediated exchange of an allyl sulfide crosslink with a free thiol to dynamically reduce hydrogel moduli. (ii) Intestinal organoid crypt structures are measured by distance from the colony body to the tip of the protrusion. (iii) Crypt length can be controlled by varying the extent of matrix softening by allyl sulfide exchange. (iv) Immunostaining verifies the presence of differentiated cell types commonly found in native intestine after allyl sulfide exchange mediated crypt formation (green: E‐cadherin, blue: DAPI, and red: Chromogranin A). Scale bar represents 100 μm. Fig. 2.9d adapted from Hushka et al. [161] copyright 2020 Wiley...... 69

Figure 2.10 Dynamic covalent chemistries to crosslink polymers for mimicking the viscoelasticity of native tissues. (a) Schematic summarizing how chemical kinetics and equilibrium reactions influence the rheological properties of the resulting hydrogels as well as the behavior of encapsulated cells. (b) Relative timeline for dynamic covalent chemistries, comparing bond reorganization timescales to illustrate relative rates of crosslink adaptation corresponding to more viscous or more elastic material behavior...... 74

Figure 4.1 Graphical abstract showing an artistic rendition of chondrocytes encapsulated in hydrazone covalent adaptable networks. Stable benzyl-hydrazone crosslinks are represented by solid lines and dynamic alkyl-hydrazone crosslinks are represented by viscoelastic Maxwell elements...... 105

Figure 4.2 Chemistry and hydrogel formulation. (a) Schematic representing chemical structures for the reaction of hydrazine with alkyl, a, and benzyl, b, aldehyde to from alkyl-hydrazone (aHz) and benzyl- hydrazone (bHz) bonds. (b) For an interconnected polymer network of bHz bonds to span the complete volume, the percentage of bHz bonds (pb) must be greater than the percolation threshold (pc) assuming ideal step-growth. 2D slices illustrate network connectivity for each experimental condition used for cell culture (88, 83, 78 and 0% aHz)...... 108

Figure 4.3 Cell viability post-encapsulation quantified by Live/Dead cytotoxicity assay using FIJI (ImageJ) with representative images taken on a confocal microscope. Chondrocyte viability was found to be

xvi approximately 80% in all three hydrazone hydrogel conditions used for cell culture experiments (88, 83, 75 and 0% aHz). For each condition 5 images were analyzed from two gels (n=2). Scale bars represent 50 µm...... 112

Figure 4.4 Rheological characterization of hydrazone hydrogels. Hydrazone hydrogels (5w/w%) formed by the stoichiometric reaction of 8-arm 20kD PEG-hydrazine with 8-arm 20kD alkyl or benzyl PEG- aldehyde. (a) Evolution of the shear storage (G’) and loss (G’’) modulus as a function of time during step- growth polymerization. (b) The final storage and loss modulus and (c) loss tangent (Tan(δ)=G’’/G’) for hydrogels with 100% alkyl-hydrazone (aHz) or 100% benzyl-hydrazone (bHz) crosslinks. In (a-c), bars represent mean ± standard deviation. Significance represents results of unpaired two-tailed t-tests (P < 0.05

= *) with Welch's correction. (d) Shear stress (σ/σo) as a function of time with solid lines representing model fits (Eq 1) for hydrazone hydrogels formulated with varied percentages of benzyl-hydrazone crosslinks

(e.g., 30% bHz ⇒ 70% aHz). Fitted values for the (e) relaxation time constants (τa and τb) and (f) stretching parameters (βa and βb) as a function of the hydrazone bond composition. Points represent fitted parameters ± 95% confidence bounds. (g) Average relaxation times (<τ>) calculated (Eq. 4.2) as a function of the percentage of bHz crosslinks in the hydrogel formulations calculated using fit parameters and 95% confidence bounds...... 116

Figure 4.5 Swelling and mass loss of acellular hydrogels. (a) Swollen mass (ms/mf) normalized by the mass at the time of formation (mf) for hydrogels with varied percentages of aHz crosslinks over time. (b) The percentage of initial polymer mass retained (%=md/m0x100%) and (c) the mass swelling ratio (q=md/ms) as a function of alkyl-hydrazone content; calculated using the dry mass (md) of constructs at the end of the 28- day experiment and the initial polymer mass of formulated hydrogels (m0). In each case four hydrogels were averaged for each condition (n=4) with significance representing 1-way or 2-way ANOVA or with Dunnett's multiple comparisons test. Significant differences with respect to the 0% aHz control are depicted with P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 118

Figure 4.6 Cellularity and proliferation. Quantification of the number of chondrocytes in hydrazone hydrogels over time as measured by dsDNA levels. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Dunnett's multiple comparisons test. Significant differences with respect to the 0% aHz control are depicted with P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 120

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Figure 4.7 sGAG content. (a) Brightfield microscopy images showing histological sections of cryosectioned constructs stained with Safranin O to visualize the spatial distribution of sGAGs deposited by chondrocytes after 28 days. sGAGs are represented by the red stained area with nuclei stained violet/black. Hydrazone hydrogels are labeled with the percentage of aHz crosslinks, and articular cartilage and acellular hydrogels are included as positive and negative controls, respectively. Scale bars represent 50 µm. (b) Graphical depiction of the total sGAG content as a function of time from a DMMB assay. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Dunnett's multiple comparisons test, showing differences with respect to the 0% aHz hydrogel, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** and with respect to the day 1 values, P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++...... 121

Figure 4.8 Collagen content. (a) Brightfield microscopy images showing histological sections stained with Masson’s Trichrome to show the spatial distribution of collagen deposited by chondrocytes after 28 days. Collagen is represented by blue stain area with nuclei stained violet/black. Hydrazone hydrogels are labeled with the percentage of aHz crosslinks, with an articular cartilage positive control and an acellular hydrogel negative control. Scale bars represent 50 µm. (b) The total collagen content as a function of time from a hydroxyproline assay. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Dunnett's multiple comparisons test. Differences with respect to the 0% aHz hydrogel are denoted by P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** and differences with respect to day 1 values are denoted by P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++...... 123

Figure 4.9 ECM deposition as a function of hydrogel average relaxation time. The mass of ECM produced by encapsulated chondrocytes at the final time point (day 28) with respect to the average relaxation time (<τ>) of hydrazone hydrogels. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Sidak's multiple comparisons test showing differences with respect to the 0% sHz control, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****, and with respect to the most adaptable 12% bHz condition, P < 0.05 = #, P < 0.01 = ##, P < 0.001 = ###, P < 0.0001 = ####...... 124

Figure 4.10 ECM Immunostaining. Immunohistochemical staining of chondrocyte laden-hydrazone hydrogels on day 28 to assess articular cartilage-specific ECM deposition. Images are maximum intensity projections of 30 μm sections imaged with a confocal microscope. Labels represent the percentage of aHz crosslinks, and porcine articular cartilage positive controls (+C). The first two rows show ECM specific to

xviii articular cartilage, collagen type II (red) and aggrecan (green). The second two rows show ECM indicative of chondrocyte dedifferentiation and fibrocartilage formation, collagen type X (red) and collagen type I (green). All images include a DAPI nuclear counterstain (blue) and scale bars represent 100 µm...... 126

Figure 4.11 Alternative normalization schemes. Graphs represent collagen (top) and sGAG (bottow) content normalized by lyophilized construct mass (left) and dsDNA content (right) for chondrocyte-laden hydrazone CANs over time. Four hydrogels were averaged for each condition (n=4)...... 130

Figure 5.1 Graphical abstract showing an artistic rendition of chondrocytes encapsulated in hydrazone covalent adaptable networks during deformation. Stable benzyl-hydrazone crosslinks are represented by purple hydrogels and dynamic alkyl-hydrazone crosslinks are represented by orange hydrogels...... 137

Figure 5.2 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-CHO. Oxidation of a) hydroxyl terminated PEG to b) alkyl=PEG aldehyde...... 140

Figure 5.3 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-Ar-CHO. HATU coupling of c) terminated PEG with formylbenzoic acid to form d) benzyl-PEG aldehyde...... 140

Figure 5.4 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-NH-NH2. HATU coupling of c) amine terminated PEG with tri-boc-hydrazinoacetic acid to form e) boc-PEG hydrazine and then deprotected with trifluoroacetic acid to produce f) PEG hydrazine...... 141

Figure 5.5 H-NMR spectroscopy verifying functionalization of 8-arm 10kD PEG macromers. (a)

Unmodified PEG-OH, δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-); (b) Functionalized PEG-CHO,

δ = 9.852-9.640 (s, H, -CHO), δ = 4.243-4.085 (s, 2H, -CH2-CHO), δ = 3.725-3.542 (m, 113.5H, -O-CH2-

CH2-O-); (c) Unmodified PEG-NH2 δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-); (d) Functionalized

PEG-Ar-CHO, δ = 10.024-10.119 (s, H, -CHO), δ = 8.037-7.894 (m, 4H, -C6H4-), δ = 3.725-3.542 (m,

113.5H, -O-CH2-CH2-O-); (e) Functionalized PEG-NBoc-NBoc2, δ = 3.860-3.819 (s, 2H, -NH-CO-CH2-),

δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-), δ = 1.581-1.509 (d, 18H, -OC(CH3)3), δ = 1.505-1.441 (d,

9H, -OC(CH3)3); (f) Functionalized PEG-NH-NH2, δ = 3.860-3.823 (s, 2H, -NH-CO-CH2-), δ = 3.725-

3.542 (m, 113.5H, -O-CH2-CH2-O-)...... 144

Figure 5.6 Schematic representation of the Kohlrausch–Williams–Watts stretched exponential function as an infinite series of Maxwell Elements in parallel...... 145

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Figure 5.7 Specially designed loading plate used for in situ deformation microscopy. a) Cuboidal hydrogels prior to loading showing the cover slide base with the microscope objective below. b) The loading plate viewed on a lab bench showing the mechanism. c) The microscope and environmental chamber used to image live cells during deformation...... 147

Figure 5.8 3D reconstructions showing chondrocytes before (left) and during (right) application of a physiologically relevant compressive strain. Imaris Software was used to combine z-stacks of confocal microscopy images into 3D renderings. The software was similarly used to identify and count chondrocytes. Scale bars represent 400 µm...... 148

Figure 5.9 The schematic above shows representative single chondrocytes at each time point during deformation. 2D cell masks were created from maximum intensity projections using Adobe Illustrator. A) Represents 0%, B) 22%, C) 100% and D) shows the experimental timeline for deformation experiments. Scale bar represents 10 µm...... 149

Figure 5.10 Rheological testing to investigate the viscoelastic/elastic material properties stemming from differences in chemical equilibria of dynamic hydrazone crosslinks. Off-stoichiometry (r = 0.8) hydrogels (~3wt%) were formed in situ between parallel plates using reactive 8-arm 10kD PEG macromers. a) Shear moduli were calculated G = [(G’)2 + (G’’)2]1/2 using plateau values (dG’/dt ≈ dG’’/dt ≈ 0) measured by time sweep during gelation in situ at 1% strain and 1 rad/s. b) Stress relaxation of a 10% strain monitored as a function of time. c) Creep compliance measured over time by the application of a constant 100 Pa stress. d) Loss tangents (tan(δ)) were calculated as the quotient of storage and loss moduli at 1% strain and 0.05 rad/s. e) Average relaxation times (<τ>) calculated based on the Kohlrausch–Williams–Watts stretched exponential function. f) Linear average creep rates (<1/η>) were fit to data excluding initial creep ringing. Data represent the average of measurements made in triplicate (n=3), with standard deviations where applicable. Significance represents the results of one-way ANOVA with Tukey’s multiple comparisons test showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 152

Figure 5.11 Viscoelastic creep compliance influences chondrocyte morphology during deformation. Viscoelastic alkyl-hydrazone hydrogels demonstrate both macroscopic and microscopic time-dependent material deformation. a) Schematic illustrating the experimental setup and hydrogel dimensions. b) Schematic illustrating how chondrocyte deformation index (X/Y) is measured. c) Chondrocytes stained with CellTrackerTM Orange and imaged in situ during deformation by confocal microscopy. Images represent maximum intensity projections illustrating changes in chondrocyte morphology over 10 hours of

xx compressive loading at 20% strain. Scale bar represents 30 µm. d) Correlation between microscopic chondrocyte deformation indexes and viscoelastic creep rates of hydrazone hydrogels after 10 hours of 20% strain. e) Macroscopic deformation indexes before and after loading. Significance represents one-way or two-way ANOVA with Tukey’s and Sidak’s multiple comparisons tests, P ≥ 0.05 = ns, P < 0.05 = *. .. 154

Figure 5.12 Viscoelastic and elastic hydrazone CANs impart biophysical cues to encapsulated chondrocytes differently over time during mechanical deformation. a), c), and e) show deformation indexes graphed over time. Grey regions represent 10 hours chondrocyte-laden hydrogels were subjected to a 20% uniaxial compressive strain. Data represent the mean and standard deviation of three hydrogels (n=3), where morphology data from 300 cells were averaged. Significance represents the results of two-way ANOVA with Dunnett’s multiple comparisons test showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****. b), d), and f) are schematics illustrating changes in chondrocyte morphology due to viscoelastic/elastic material properties to aid in the interpretation of deformation index data...... 157

Figure 5.13 Pericellular matrix deposition in viscoelastic hydrazone hydrogels influences the transmission of biophysical cues. Tissue engineering is a dynamic process and chondrocytes deposit extracellular matrix over time to influence the mechanics of their own microenvironments. a) Histological sections stained with Safranin O. sGAGs are represented by the red stain area with nuclei stained violet/black. Scale bars represent 20 µm. b) Quantification of normalized deformation index (X20% / Y20%) / (X0% / Y0%) after one week of culture illustrates differences in the transmission of a 20% strain to encapsulated chondrocytes. c) Estimation of the number of chondrocytes per hydrogel extrapolated from confocal microscopy data showing increased cell populations in the absence of percolating elastic networks of stable benzyl- hydrazone crosslinks. d) Relative expression of Col1 and Col2 after 6 hours of loading at 20% strain, normalized by GAPDH expression. The trend suggests that ECM disposition in viscoelastic CANs can help mitigate negative effects of static loading...... 160

Figure 6.1 In recent years, growing emphasis has been placed on understanding how matrix mechanics and mechanobiology can be used to design better biomaterials. Here, we use specially designed bioreactors to elucidate how viscoelasticity of hydrazone covalent adaptable networks influences the behavior of chondrocytes during physiologically relevant dynamic compression and our results lend insights for cartilage tissue engineering in load-bearing joints...... 168

Figure 6.2 Schematic illustration represents the experimental design for dynamic compression experiments. (a) The alkyl-hydrazone (green) crosslink equilibrium leads to more viscoelastic material

xxi properties (e.g., faster stress relaxation) than the more stable benzyl-hydrazone (purple) crosslinks. (b) The viscoelastic properties of hydrazone CANs are varied based on the molar percentage of alkyl-hydrazone and benzyl-hydrazone crosslinks. (c) Articular chondrocytes were encapsulated in hydrazone hydrogels and allowed three days to recover from isolation and encapsulation stresses. (d) On day 4, Chondrocyte-laden hydrazone hydrogels were transferred to dynamic compression bioreactors which were programed to apply a cyclic 15% strain at a rate of 1 Hz for one hour each day. Dynamically loaded hydrogels were compared to free swelling controls 3, 10, 17, 24 and 31 days after encapsulation...... 171

Figure 6.3 Gelation of alkyl-hydrazone and benzyl-hydrazone CANs. (a) Dynamic alkyl-hydrazone (green) crosslinks formed by reaction of alkyl-aldehyde (yellow) functionalized PEG with hydrazine (blue) functionalized PEG. (b) Stable benzyl-hydrazone (purple) crosslinks formed by the reaction of benzaldehyde (red) functionalized PEG with hydrazine (blue) functionalized PEG. (c) The final G∞ was

2 2 (1/2) statistically the same across all formulations. G∞ = [(G′) + (G′′) ] with plateau values (ΔG′/Δt ≈ ΔG′′/Δt ≈ 0) for each of the three hydrazone hydrogel conditions. (d) In situ gelation was monitored by a time sweep, showing shear storage (G’) and loss (G’’) moduli over time. (e) Gelation points for hydrazone CANs were measured at ω = 1 rad s-1 and γ = 1%. Gelation point is defined here as the time required to measure a storage modulus greater than the loss modulus (G’ > G’’), with an additional threshold of G’ ≥ 10 Pa to account for instrument error. Traces represent average measurements made in triplicate (n=3) with standard error where appropriate. Statistics represent the results of one-way ANOVA with Tukey's multiple comparisons test (MCT) showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 178

Figure 6.4 Shear rheometry was used to measure the viscoelastic responses of hydrazone CANs to step- changes. (a) Differences in viscoelastic stress relaxation between hydrazone CANs represented by variations in the normalized shear stress (σ/σmax) over time compared to model fits. (b) Average relaxation times (<τ>) represent the characteristic network reorganization timescales for each formulation. Stress relaxation data was fit with the Kohlrausch–Williams–Watts stretched exponential function (Equation 2) followed by integration to calculate the average relaxation times (Equation 3). (c) Hydrazone CANs relax different amounts of the initial stress over the course of 6 hours. (d) Differences in viscoelastic creep compliance (J) between hydrazone hydrogel formulations over time compared to model fits. (e) Linear average creep rates (<1/η>) as a function of hydrogel compositions. The creep compliance data were fit to (Equation 4), excluding initial creep ringing. (f) Hydrazone CANs were strained by different amounts over the course of 2 hour creep tests, and the final strain (γ) was plotted as a function of network composition. Traces represent average measurements made in triplicate (n=3) with standard error where appropriate.

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Statistics represent the results of one-way ANOVA with Tukey's MCT showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 181

Figure 6.5 SAOS rheometry to quantify frequency and strain dependent behavior of hydrazone CANs. (a) Frequency sweep spectra illustrate differences in the storage moduli (G’), loss moduli (G’’), and loss tangents (tan(δ) = G’’ / G’) as a function of angular frequency (ω) at constant strain (γ = 1%). (b) Differences between the low frequency loss tangents of hydrazone CANs (ω = 0.001 rad s-1). (c) Measurements of the high frequency loss tangents of hydrazone CANs were not significantly different (ω = 10 rad s-1). (d) Amplitude sweeps illustrate the shear-thinning behavior of hydrazone CANs. Data represent the storage moduli (G’), loss moduli (G’’), and loss tangent (tan(δ) = G’’ / G’) as a function of strain (γ) at constant angular frequency (ω = 1 rad s-1). (e) Each of the three hydrogel conditions showed similar strain-dependent crossovers (tan(δ) =1). (f) Quantification of the pre-strain modulus recovery illustrates that shear-thinning behavior is non-destructive. Percent recovery was calculated using the shear modulus after strain sweeps, expressed as a percentage of the shear modulus before strain sweeps as measured by time sweeps (ω = 1 rad s-1, γ = 1%). Traces represent average measurements made in triplicate (n=3) with standard error where appropriate. Statistics represent the results of one-way ANOVA with Tukey's MCT showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 183

Figure 6.6 Chondrocyte populations in free swelling (a) and dynamically loaded (b) hydrazone CANs over time. The number of chondrocytes per hydrogel formulation was calculated using a DNA assay and plotted as a function of time. Data from four CANs were averaged for each condition (n = 4) with standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** for differences between hydrogel conditions and Dunnett's MCT where P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++ for differences with respect to Day 3 levels within each hydrogel formulation...... 185

Figure 6.7 Relative mRNA expression of articular cartilage specific genes. Gene expression was investigated three days (Day 3) after encapsulation (a) and after one week (Day 10) of dynamic compression (b). Data represent expression of genes encoding for Collagen X, Collagen I, MMP13, Sox9, and Collagen II. Data from four hydrogels were averaged for each condition, excluding samples which did not provide reliable amounts of mRNA (n=2-4) showing mean and standard error. Data were double normalized first to GAPDH expression and then to the 0% condition. Statistical significance represents the results of two- way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****...... 187

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Figure 6.8 Interactive effects of mechanobiological cues on chondrocyte ECM deposition. Here blue represents collagen (a-b) and red shows sGAGs (c-d) in hydrazone CANs. Linear regression was used to calculate matrix production rates over the experimental time course showing collagen (a) and sGAG (c) deposition rates (µg day-1) during free swelling and dynamic compression culture. To frame these results in the context of viscoelasticity, data are graphed by the viscoelasticity represented by tan(δ) at 15% strain and 1 rad s-1. This represents the dynamically applied strain at a frequency relevant for cellular mechanosensing [79], which is useful for interpreting how viscoelasticity influences cell-matrix interactions in hydrazone CANs. Bright field microscopy was used to visualize 20 µm histological sections stained with (b) Masson’s Trichrome showing collagen (blue) and (d) Safranin O showing sGAGs (red) with cell nuclei (black/violet). Scale bars represent 15 µm. Data from four CANs were averaged for each condition (n = 4) with data representing mean values with standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** for differences between hydrogel conditions and Sidak's MCT where P ≥ 0.05 = ns, P < 0.05 = #, P < 0.01 = ##, P < 0.001 = ###, P < 0.0001 = #### for differences between dynamic compression and free swelling conditions...... 191

Figure S 6.1 Material response of alkyl-hydrazone and benzyl-hydrazone CANs to dynamic compressive loading. Acellular samples were subjected to unconfined compression in DPBS and the uniaxial force response was measured over time. The cycle was set to 20% strain and 1 Hz for one hour to investigate a physiologically relevant compression cycle. At the end of the hour the normalized force response was compared for fully alkyl-hydrazone and fully benzyl-hydrazone hydrogels showing non-significant differences between maximal force response cycles (n=3). Statistical significance represents the results of an unpaired t-test where P ≥ 0.05 = ns...... 193

Figure S 6.2 Relative mRNA expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) three days (Day 3) after encapsulation (a) and after one week (Day 10) of dynamic compression (b). These results verify that the house keeping gene is not affected by the viscoelasticity of hydrazone CANs. Data from four hydrogels were averaged for each condition, excluding samples which did not provide reliable amounts of mRNA (n=2-4) showing mean and standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns...... 194

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Figure S 6.3 Quantification of the biochemical collagen (a,b) and sGAG (c,d) content for free swelling controls and dynamic compression culture (1 hour day-1, ε = 15%, ν = 1 Hz). Quantification from hydroxyproline assay is reported assuming hydroxyproline accounts for 13.4% of the amino acid content of collagen in articular cartilage.[80] Quantification from DMMB assay was reported as chondroitin sulfate (ChS) equivalents per hydrogel. Data from four CANs were averaged for each condition (n = 4) with data representing the mean with standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** for differences between hydrogel conditions and Dunnett's MCT where P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++ for differences with respect to Day 3 levels within each hydrogel formulation...... 195

Figure S 6.4 Linear regression analysis for collagen (a-b) and sGAG (c-d) content for free swelling controls and dynamic compression culture. Linear regression was selected after comparing polynomials up to order 6 with extra sum-of-squares F tests where the simpler model is recommended unless P ≤ 0.05...... 196

Figure S 6.5 Quantification of construct Young’s moduli measured during compression. Average moduli of constructs subjected to dynamic compression (E Dynamic Compression) are represented normalized by their respective free swelling controls (E Free Swelling Control) over the experimental time course. Data from four CANs were averaged for each condition (n = 4) with data representing the mean with standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns...... 197

Figure 7.1 Macroscopic self-healing behavior of alkyl-hydrazone CANs may enable press-fitting for filling irregularly shaped cartilage defects...... 211

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Chapter 1 - Introduction

1. Cartilage tissue engineering to treat osteoarthritis

Articular cartilage in load-bearing joints provides low friction and shock absorbing surfaces that cushion junctions between bones [1]. Consequently, heathy articular cartilage is crucial for enabling pain- free mobility [2]. Articular cartilage tissue can become damaged by traumatic injuries or by wear-and-tear as we age [3]. Lack of vasculature and low regenerative activity of resident chondrocytes exacerbates this problem, causing cartilage to have diminished regenerative capacity compared to other tissues [4]. When articular cartilage becomes severely eroded or damaged this process is called osteoarthritis and it is often associated with debilitating pain [5]. In this way, osteoarthritis represents a barrier to well-being for over

30 million people in the United States [6]. Fortunately, cartilage tissue engineering has emerged as a promising strategy to treat osteoarthritis [7]. Cartilage tissue engineering relies on combinations of cells, polymer matrices, and promotive cues to regenerate damaged cartilage tissue [4].

The premise of this dissertation is to improve polymer matrices for treating osteoarthritis in load- bearing joints. The following sections provide background information about the composition, structure and function of articular cartilage tissue. Next the causes and symptoms of osteoarthritis are discussed. This is followed by an overview of the limitations of current treatment strategies to further motivate cartilage tissue engineering research. The final sections of this chapter provide information about important design criteria for cartilage tissue engineering and introduce the specific approach of this dissertation.

1.1. Articular cartilage structure and function

Articular cartilage is characterized by structural organization on multiple length scales (Fig. 1.1).

Macroscopically, human articular cartilage is typically a few millimeters thick [8], and can be subdivided into the superficial zone, the transitional zone, and the deep zone [9]. The tidemark separates articular cartilage from a layer of calcified cartilage which sits on top of the subchondral bone plate (Fig. 1.1a).

Articular cartilage is sparsely populated by a single cell type known as chondrocytes [9]. In articular

1 cartilage, chondrocytes and the surrounding pericellular matrix are called chondrons (Fig. 1.1b). The spatial distribution and morphology of chondrons vary between zones [10]. Chondrocytes are responsible for producing and maintaining the surrounding extracellular matrix (ECM), which is a dense hydrated network composed of collagen, proteoglycans, and small amounts of noncollagenous proteins and glycoproteins

(Fig. 1.1c) [11]. The composition and macromolecular structure of the ECM provides strength for withstanding forces in articulating joints [12]. Type II collagen is a fibrillar protein which is primarily responsible for the shape, mechanical structure and microarchitecture of articular cartilage (Fig. 1.1d) [9].

Proteoglycans (e.g., aggrecan) are responsible for retaining water molecules and lend compressive strength

(Fig. 1.1e) [13]. Aberrant remodeling of these ECM components can jeopardize the structural properties of articular cartilage contributing to the progression of osteoarthritis [14].

2

Figure 1.1 Diagram illustrating the structure and composition of articular cartilage. (a) Shows organization within the tissue with labels indicating distinct regions starting at the joint cavity (top) and ending at the underlying bone (bottom). (b) Inset shows the pericellular space with chondrocytes organized into chondrons. (c) The major molecular components of the ECM. (d) Inset shows the hierarchical structure of collagen from the polypeptide sequence to the fiber organization. (e) Inset shows the organization of brush- like aggrecan molecules. Adapted with permission from Baumann et al. [15] copyright Springer Nature

Switzerland AG 2019.

1.1.1. Chondrocytes

Chondrocytes account for a small percentage of articular cartilage by volume [16], and are largely homogeneous with respect to genetic and phenotypic markers [17]. Yet, this sparse cell population is

3 responsible for maintaining a delicate balance between anabolic and catabolic rates in order to preserve the structure and function of articular cartilage tissue [18]. During osteoarthritis, these processes can be dysregulated by cell-matrix interactions [19]. Differences in chondrocyte morphology have been shown to directly influence chondrocyte phenotype and have been implicated in the progression of osteoarthritis [20].

Understanding behavior of chondrocytes is important for achieving regeneration in vitro and the interactions of chondrocytes with their surrounding ECM present unique opportunities for controlling the behavior of chondrocytes for cartilage tissue engineering [21].

1.1.2. Extracellular matrix (ECM)

The largest component of the ECM is water, accounting for 65-80% of the mass of mature articular cartilage tissue [22]. The next largest component of the ECM are collagens, which make up 10-20% of the mass of articular cartilage tissue [22]. Collagens are composed of polypeptide chains with repeating glycine residues at every third position and other amino acids such as proline and hydroxyproline occupying the other positions (Fig. 1d) [23]. Hydroxyproline makes up approximately 1/8 of the amino acid content of collagens and can be detected by colorimetric assay [24,25]. Collagen polypeptide chains arrange themselves in left- handed helical conformations (< 1 nm diameter) [26]. Three of these strands associate in a right-handed alpha-helix to form procollagens which are converted to tropocollagen (1-2 nm diameter) [26].

Tropocollagen molecules are crosslinked forming fibrils (2-100 nm diameter) and eventually fibers (300-

500 nm diameter) [26]. In articular cartilage up to 90% of these collagen fibers are type II collagen. Collagen type II forms fibrillar networks which are organized into dense isotropic structures surrounding chondrocytes. Collagen II is critically important for healthy joint development and function, as studies have shown that dysregulation of the gene that codes for collagen II (COL2A1) can contribute to osteoarthritis

[27,28]. Small amounts of collagen types I, IV, V, VI, IX, and XI are also present in articular cartilage [9].

Some of these collagens are important for signal transduction and network stabilization [29]. However, expression of collagens other than type II in articular cartilage can also serve as disease markers. For

4 example, upregulation of type IV and type X are associated osteoarthritis [30,31]. Similarly, large quantities of type I collagen are characteristic of mechanically inferior fibrocartilage [32].

The final components of articular cartilage are proteoglycans (10-15% of the mass of cartilage tissue) and a small amount of non-collagenous proteins [9]. Proteoglycans are proteins that are heavily glycosylated.

Small proteoglycans like biglycan and decorin participate in ECM assembly and act as signaling molecules

[33,34]. Of the proteoglycans found in articular cartilage, aggrecan is the largest and the most abundant.

Aggrecan molecules are non-covalently attached to linear hyaluronic acid chains with stabilizing link proteins [35]. Sulfated glycosaminoglycans (sGAG) (e.g., chondroitin sulfate, keratan sulfate) protrude from the aggrecan core forming brush-like structures [35]. Electrostatic interactions between negatively charged residues, typically deprotonated carbocyclic acids and sulfates, help to retain water and enhance the compressive strength of articular cartilage [35]. Many non-collagenous proteins play niche roles within the ECM of articular cartilage [3]. Notably, lubricin is found at the outer boundary of articular cartilage and is primarily responsible for minimizing friction and lubricating the surface of the joint [36].

1.1.3. Mechanical properties of articular cartilage

Biomechanical factors influence the pathogenesis of osteoarthritis, and recent research emphasis on cellular mechanotransduction has illustrated the importance of biophysical cues and mechanical properties for cartilage tissue engineering [37]. The elastic stiffness, or more precisely the modulus, of articular cartilage varies significantly depending on the measurement technique and the donor cartilage

[38,39]. However, the Young’s modulus is typically estimated between 0.45 and 0.8 MPa [40]. Despite exhibiting highly elastic behavior, cartilage tissue also demonstrates viscous dissipation [41]. Articular cartilage shows time-dependent material properties such as stress relaxation and creep compliance which are indicative of the tissue’s ability to behave both solid-like and liquid-like [42]. These mechanical properties can influence the transmission of biophysical cues to chondrocytes [43] and cellular deformation has been implicated as part of the mechanobiology of osteoarthritis [44]. Advanced stages of osteoarthritis are characterized by tissue softening and faster stress relaxation, further illustrating the importance of both

5 modulus and viscoelasticity during disease progression [45]. Biophysical stimuli and cell-matrix interactions represent a promising avenue for improving cartilage tissue engineering strategies for treating osteoarthritis [46].

1.2. Prevalence, symptoms and etiology of osteoarthritis

In the United States, medical expenditures and lost earnings losses due to arthritis were recently estimated to be greater than $300 billion annually [47]. Osteoarthritis is the most common form of arthritis, affecting more than 30 million Americans [6], and this economic burden falls disproportionately on patients with osteoarthritis in load-bearing joints [48].

Osteoarthritis is defined by compromised structural integrity of articular cartilage, which typically results in pain and loss of function [49]. In healthy knee joints undamaged ligaments, bone, and articular cartilage work in concert to enable pain-free movement of the joint (Fig. 1.2a). In osteoarthritic knee joints, articular cartilage becomes severely eroded and this is often accompanied by ligament dysfunction [50], and osteophyte formation (Fig. 1.2b) [51]. These abnormities often lead to painful friction between bones, joint stiffness, swelling, and a loss of flexibility for afflicted patients [52]. Chondrocytes respond to articular cartilage damage by increasing synthesis of matrix molecules and proliferating [53]. However, the avascular, aneural, alymphatic, and hypocelluar nature of cartilage tissue present significant barriers for unassisted healing [54].

Osteoarthritic damage to articular cartilage has been attributed to a wide array of etiologies. For example, osteoarthritis can be considered idiopathic, post-traumatic, congenital, malpositional, postoperative, metabolic, or aseptic [49]. Several risk factors such as age, sex, obesity, prior injury, and prolonged exposure to excessive stress can increase the likelihood of developing osteoarthritis [55].

Unfortunately, there is no cure for osteoarthritis, but the symptoms can be managed and treated with varying degrees of success [56]. Many of these strategies involve pain mitigation and lifestyle changes to slow the

6 onset of the disease [57]. The next section discusses current osteoarthritis treatment strategies with emphasis on limitations preventing ubiquitous acceptance of a single treatment option.

Figure 1.2 Illustration represents pathophysiological changes in a human knee joints during osteoarthritis.

(a) A heathy human knee joints shows normal organization of bone, cartilage, tendons, and muscle. (b)

Osteoarthritis is primarily characterized by severely worn and damaged articular cartilage tissue. The surrounding tissues can also experience deterioration or malformation contributing to the disease burden.

Adapted with permission from Hunter et al. [58] copyright Massachusetts Medical Society 2015.

1.3. Limitations of current osteoarthritis treatment strategies

Treatment of osteoarthritis can take different forms depending on patient demographics, medical history, and economic considerations [59]. During early stages, patients can utilize non-steroidal anti- inflammatory drugs (NSAIDs) as these are inexpensive, provide pain relief, and mitigate swelling [60].

When these medications fail to provide adequate symptom relief, physicians sometimes administer

7 corticosteroids (e.g., cortisone) directly to the joint to ease pain and combat inflammation [61]. When conservative management strategies fail to alleviate symptoms, surgical procedures are typically recommended [62].

1.3.1. Joint arthroplasty

Joint arthroplasty involves the surgical removal and reconstruction of a joint, or part of a joint, with plastics [63], metals [64], and ceramics [65]. This is the most common form of treatment for severely worn and degraded articular cartilage in load-bearing joints [66]. Some patients experience restored motor function and reduced pain with prosthetic joints, however, extension strength and balance are generally reduced after total joint arthroplasty [67]. Prosthetic joints can similarly limit the type and duration of physical activity and wear over time [68]. As prosthetics wear they can create debris in the body and loosen causing instability [69]. Further, arthroplasty is highly invasive which carries the risk of surgical complications [70]. This danger is compounded over time, as corrective surgery rates double from 6% five years after the initial procedure to 12% after ten years [71]. These limitations prompted physicians and scientists to explore alternative treatment options for promoting the body’s natural ability to heal damaged articular cartilage rather than replace it [72].

1.3.2. Surgical intervention procedures

Arthroscopic debridement, mosaicplasty, and microfracture, are surgical procedures that are intended to promote natural functioning or partial healing of articular cartilage without reconstructing the joint with foreign materials [73]. Arthroscopic debridement refers to techniques which only remove diseased tissue [74]. Mosaicplasty involves transplanting cartilage from non-load-bearing areas of the joint to more critically located cartilage defects (Fig. 1.3a) [75]. And microfracture surgery is a process where the joint is perforated with channels that allow cells, growth factors, and nutrients from the underlying subchondral bone to promote new tissue formation (Fig 1.3b) [76].

8

Figure 1.3 Schematic illustrating two common surgical intervention techniques for treating osteoarthritis in load-bearing joints. (a) Mosaicplasty involves transplanting osteochondral plugs from one part of the joint to more critically located cartilage defects. (b) Microfracture involves perforating the knee joint to allow cells, growth factors, and nutrients from the underlying subchondral bone to reach the defect site.

Adapted with permission from Dai et al. [77] copyright Springer Science + Business Media Singapore

2016.

1.3.2.1. Arthroscopic debridement

Arthroscopic debridement techniques (e.g., chondroplasty, osteophyte excision, and meniscectomy) simply involve removing diseased tissues in order to improve the mechanical movement of the joint [74]. This is typically accomplished by reshaping cartilage and removing osteophytes to reduce friction and prevent further damage [78]. Unfortunately, these techniques rarely accomplish healing and are more often employed to slow the onset of osteoarthritis symptoms [79].

1.3.2.2. Mosaicplasty

Mosaicplasty is a procedure which reintroduces heathy cartilage to articular cartilage defects [80].

This process involves harvesting osteochondral plugs from non-load-bearing portions of the patient’s joint

9 and transplanting them at a more important defect area (Fig. 1.3a) [81]. However, integration failure [82] and donor site morbidity [83] present non-trivial risks for patients undergoing mosaicplasty.

1.3.2.3. Microfracture

Microfracture is a technique which aims to leverage the healing capacity of the underlying bone to generate new tissue [84]. This is achieved by perforating the cartilage with cylindrical channels which allow blood from the subchondral bone to transport nutrients, growth factors and mesenchymal stem cells

(MSCs), to the defect site to promote tissue formation (Fig. 1.3b) [85]. Microfracture surgery is popular among professional athletes because it is minimally invasive and affords athletes the ability to return to competition rapidly, often at near preinjury participation levels [86]. However, this technique is known to result in mechanically inferior fibrocartilage [87]. Microfracture surgeries have also demonstrated inconsistent clinical results and undesirable long-term patient outcomes, as thin fibrocartilage can rapidly wear down causing osteoarthritis symptoms to reemerge [88].

1.3.3. Cell and matrix based treatments

Multiple treatment strategies exist based on delivering cells and/or matrix molecules directly to an afflicted joint without surgery [89]. Hyaluronic acid is the most common matrix biomolecule delivered without cells, in a process known as viscosupplementation [90]. Conversely, when cartilage cells are delivered to a defect site the process is known as autologous chondrocyte implantation (ACI). This technique involves isolating and expanding chondrocytes in vitro (Fig 1.4a). New chondrocytes can then be delivered directly to a cartilage defect site to aid in the healing process (Fig. 1.4b). If a supportive polymer matrix is delivered along with the chondrocytes the technique is called matrix-assisted autologous chondrocyte transplantation (MACT) (Fig. 1.4b).

10

Figure 1.4 Schematic illustrating two common cell and matrix techniques for repairing articular cartilage in load-bearing joints. (a) Cartilage biopsies allow a patient’s chondrocytes to be isolated and expanded in vitro. (b) When chondrocytes are directly delivered to the defect site the treatment known as autologous chondrocyte implantation (ACI). When a supportive polymer matrix is added the technique known as matrix-assisted autologous chondrocyte transplantation (MACT). Adapted with permission from Dai et al.

[77] copyright Springer Science + Business Media Singapore 2016.

1.3.3.1. Viscosupplementation

Hyaluronic acid plays a key role in hydrating and lubricating the joint space in heathy articular cartilage [91]. Injectable delivery of hyaluronic acid has shown anti-inflammatory and chondroprotective benefits for osteoarthritis patients [90]. Viscosupplementation has also proven effective for reducing pain and preventing additional cartilage deterioration in articulating joints [92]. Unfortunately, these benefits are time-limited and require frequent administration to remain effective [93].

1.3.3.2. Autologous chondrocyte implantation (ACI)

Cell-only techniques take the opposite approach, delivering cells (e.g., chondrocytes [94], MSCs

[95]) to damaged cartilage tissue in articulating joints. ACI involves taking cartilage biopsies from patients

11 and digesting the ECM with enzymes to isolate chondrocytes [96]. Chondrocyte populations are then expanded in vitro (Fig 1.4a) [97], before being delivered back into the patient to aid the healing process

(Fig 1.4b) [98]. Some researchers have proposed allogenic [99] or xenogenic [100] strategies to avoid problems such as donor site morbidity [101] and reduced regenerative activity of aged chondrocytes [102].

Although the avascular and alymphatic qualities of cartilage enable a partially immune-privileged environment [103], severe immunologic responses and graft rejection are still possible, limiting widespread application [104].

Unfortunately, cell-only technologies are also plagued by technical problems such as inadequate cell retention [105], integration failure [106], and dedifferentiation of chondrocytes [107]. ACI techniques often employ a periosteal patch or a collagen membrane to help to retain cells and promote integration at the defect site, but this requires additional surgeries [108]. To address these limitations, cartilage tissue engineering has emerged as a strategy for improving ACI by delivering chondrocytes with supportive polymer scaffolds [109].

1.3.3.3. Matrix-assisted autologous chondrocyte transplantation (MACT)

Tissue engineering applies principles from biology and engineering to design functional substitutes for damaged tissues (Fig. 1.5) [110]. Clinically, cartilage tissue engineering strategies that rely on chondrocytes are known MACT [7]. The early stages of ACI and MACT are procedurally similar, requiring chondrocyte isolation and expansion in vitro (Fig. 1.4a). However, the two procedures diverge during reintroduction (Fig. 1.4b) [109]. For MACT, chondrocytes are reintroduced to the patient with a protective polymer matrix (Fig. 1.5a). These polymer matrices can be designed to provide supportive biochemical and biophysical cues (Fig. 1.5b) [111]. Despite promising initial studies, clinical data sets for MACT treatments are still limited [112]. Similarly, technical hurdles that require further research are illustrated by recent studies showing lower collagen content in engineered constructs compared to heathy articular cartilage tissue [113,114]. Much recent work in this area has focused on how materials science can be used to design advanced polymer matrices for influencing cell behavior to enhance regeneration [115].

12

Figure 1.5 Tissue engineering and regenerative medicine represent multidisciplinary intersections of medicine, cell biology, materials chemistry, and polymer physics. (a) For regenerative medicine, cells are isolated from human patients in medical settings. Homogenous cell populations are created by cell biologists using cell sorting for specific tissue targets. Cells are then expanded in vitro before being encapsulated within a hydrogel scaffold and implanted back into the patient. (b) Incorporating biochemical and biomechanical cues into hydrogel scaffolds allows for user-defined control over cell behavior for tissue engineering. Materials scientists are able to tailor hydrogel properties to study and direct cell-cell and cell- matrix interactions. This allows new materials to be developed to improve clinical outcomes for engineered tissues. Adapted with permission from DeForest et al. [116] copyright Annual Reviews 2012.

1.4. Polymer scaffold design considerations for MACT

Selection of an appropriate polymer backbone is a critical choice for MACT treatments [117].

Many synthetic and naturally derived polymers have been demonstrated in this context [118]. The derivation natural polymers from biological sources often makes them innately biocompatible and biodegradable [119,120]. Some of the most common natural polymers used for cartilage tissue engineering

13 include collagen [121], fibrin [122], hyaluronic acid [123], agarose [124], alginate [125], and chitosan

[126]. Table 1.1 below summarizes specific strengths and weaknesses of natural polymers commonly used for tissue engineering.

Table 1.1 Advantages and disadvantages of naturally derived polymers for tissue engineering applications.

Adapted with permission from Spicer et al. [117] copyright The Royal Society of Chemistry 2020.

Polymer Class Advantages Disadvantages

Collagen Proteinaceous • Adhesive and bioactive • Assembly sensitive to

modification

• Abundant and biodegradable • Contamination can lead to

immunogenicity

• Mimics native ECM • Mechanical stability lost during

processing

Gelatin Proteinaceous • Adhesive and bioactive • Mechanically weak

• Tolerant of functionalisation • Contamination can lead to

immunogenicity

• Abundant and biodegradable • Requires cross-linking

Silk Proteinaceous • High mechanical strength and • Slow gelation

elasticity

• Adhesive

14

Polymer Class Advantages Disadvantages

• Low immunogenicity

ELPs Proteinaceous • Thermoresponsive (LCST) • Low stability without cross-

linking

• Tunable structure and sequence

• Recombinant expression

Alginate Polysaccharide • Rapid gelation with divalent • Cation leaching leads to

cations dissolution

• Abundant • Non-biodegradable

• Ease of use for 3D printing • Poorly adhesive

• Reactive handles for

functionalisation

Chitosan Polysaccharide • Adhesive and antimicrobial • Poor solubility at neutral pH

• Abundant

• Low immunogenicity

HA Polysaccharide • Bioactive and biocompatible • Low stability without cross-

linking

15

Polymer Class Advantages Disadvantages

• Binds growth factors and • Rapidly degraded in vivo

cytokines

• Reactive handles for

functionalisation

Chondroitin Polysaccharide • Bioactive and biocompatible • Low stability without cross- sulfate linking

• Binds growth factors and • Rapidly degraded in vivo

cytokines

• Reactive handles for

functionalisation

Synthetically derived polymers typically have well-defined properties and are easy to modify [115].

Some common synthetic materials used for cartilage tissue engineering include poly(lactic acid) (PLA) and poly(glycolic acid) (PGA) [127], poly(vinyl ) (PVA) [128], polydioxanone (PDS) [129], and poly(ethylene glycol) (PEG) [130]. Table 1.2 below summarizes the advantages and disadvantages of common synthetic materials used for tissue engineering.

Table 1.2 Advantages and disadvantages of synthetically derived polymers for tissue engineering. Adapted with permission from Spicer et al. [117] copyright The Royal Society of Chemistry 2020.

16

Polymer Class Advantages Disadvantages

PHEMA Polyvinyl • High mechanical strength • Non-degradable

• Generally biocompatible • Non-adhesive

• Easily derivatized • Potential calcification in vivo

• High monomer toxicity

PVA Polyvinyl • High elasticity • Non-degradable

• Variable deacetylation ratios • Non-adhesive

• High biocompatibility and

hydrophilicity

PNIPAM Polyvinyl • Temperature responsive (LCST) • Non-degradable

• Biocompatible • Non-adhesive

• Low immunogenicity • Monomer cyto- and neuro-toxic

• Gels have weak mechanical strength

PEG — • Versatile architecture and • Non-degradable

functionality

• ‘Blank slate’ scaffold • Non-adhesive

17

Polymer Class Advantages Disadvantages

• Modular gel properties • Evidence of immunogenicity in some

patients

PLA Polyester • Degradable by hydrolysis • Hydrolysis products may cause

inflammation

• Properties dependent on monomer • Physically cross-linked gels are weak

feedstock

PGA Polyester • Degradable by hydrolysis • Hydrolysis products may cause

inflammation

• Co-polymers with PLA give • Rapid breakdown in vivo

tunable properties

PCL Polyester • Degradable by hydrolysis • Physically cross-linked gels are weak

• Sensitive to degradation by lipase • Crystallinity may slow hydrolysis beyond

relevant timeframe

• Stable hydrogels over wide

concentration range

• Crystallinity provides mechanical

strength

18

This thesis is concerned with the use of PEG hydrogels as PEG is chemically and biologically inert

[131], easy to modify [132], and can maintain chondrocyte phenotype during 3D culture [133]. PEG hydrogels used for cartilage tissue engineering are often covalently crosslinked to provide mechanical strength for withstanding compressive loading in articulating joints [134]. However, these materials traditionally demonstrate purely elastic responses to deformation (Fig. 1.6a) despite the dynamic viscoelastic properties of native cartilage tissue [135]. Dense static covalent crosslinks have also been shown to limit ECM deposition by encapsulated chondrocytes [136]. Informed by the limitations above, we sought to explore a growing area of interest within the materials community: covalent adaptable networks (CANs) [137] as viscoelastic polymer matrices for cartilage tissue engineering. Reorganization of dynamic covalent crosslinks in these networks leads to non-linear mechanical properties (Fig. 1.6b) which can better mimic the biomechanical properties native cartilage tissue [138]. We hypothesized that adaptation of covalent crosslinks would enable chondrocytes to remodel their local microenvironment and enhance tissue regeneration without sacrificing robust structural support for MACT in load-bearing joints.

19

20

Figure 1.6 Mechanical properties of traditionally elastic covalent crosslinks and viscoelastic dynamic covalent crosslinks. (a) Thiol-ene crosslink formation is an irreversible process locking polymer conformations in place and limiting energy dissipation. During mechanical testing this elastic behavior manifests as a linear stress–strain curve as well as frequency and strain independent moduli. (b) Conversely, equilibrium between forward and reverse reactions for hydrazone linkages lead to viscoelastic material properties. Dynamic covalent hydrogels demonstrate hysteresis, frequency dependent crossovers and shear- thinning behavior. Adapted with permission from Rosales et al. [135] copyright Springer Nature 2016.

1.5. Dissertation approach

This dissertation focuses on how the viscoelastic properties of hydrazone CANs influence biophysical phenomena for cartilage tissue engineering. The goal of this work is to improve understanding of polymer matrices for MACT to treat osteoarthritis in load-bearing joints. The next section, Chapter II, provides background information about dynamic covalent hydrogels for mimicking the viscoelasticity of native tissues. Chapter III serves as an overview outlining three research hypotheses and the experimental investigations testing them. The first aim (Chapter IV) explores equilibrium differences between alky- hydrazone and benzyl-hydrazone crosslinks for developing model systems to better understand how stress relaxation of covalent crosslinks influences ECM deposition by encapsulated chondrocytes. The second aim (Chapter V) concerns phenotypic changes chondrocytes experience in viscoelastic and elastic hydrazone hydrogels when exposed to physiologically relevant mechanical deformation. The third and final aim (Chapter VI) examines the effects of dynamic compressive loading on viscoelastic hydrazone CANs in bioreactors to simulate the mechanical environment of articulating joints. The dissertation ends with

Chapter VII which synthesizes key takeaways and conclusions from the aforementioned research. This is accompanied by recommendations intended to inform further directions and aid the clinical translation of hydrazone PEG hydrogels as scaffolds for cartilage tissue engineering.

1.6. References

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Chapter 2 - Background

2. Dynamic covalent hydrogels as biomaterials to mimic the viscoelasticity of soft tissues

As appearing in Progress in Materials Science special 70th Anniversary Volume 2020

2.1. Abstract

The extracellular matrix (ECM) and its mechanical properties play an important role in regulating the cellular responses that occur during tissue regeneration, wound healing, and disease progression. A growing body of research, especially in the fields of mechanobiology and matrix biology, has been devoted to elucidating how the ECM mechanical environment, both in vitro and in vivo, influences cell fate and function. Synthetic materials that faithfully recapitulate key mechanical properties of native tissues provide an important means to understand the mechanisms by which cells sense and remodel their surrounding mechanical environments. However, tissue mechanics is inherently complex, exhibiting dependencies on many timescales. This review highlights recent progress in synthetic biomaterials, particularly polymer networks that capture critical aspects of the dynamic mechanical properties of soft tissues by exploiting dynamic covalent chemistries. Finally, future directions and opportunities in the development and application of viscoelastic biomaterials are discussed.

2.2. Introduction

The native extracellular microenvironment, typically referred to as the extracellular matrix (ECM), is an intricate and complex biomaterial containing a myriad of biochemical and biophysical cues. Cells receive signals from the ECM and this outside-in signaling influences cellular responses such as proliferation, migration, differentiation, and apoptosis [1]. Over the past several decades, synthetic biomaterials, especially polymer-based networks, have been widely employed as tissue mimics, providing robust platforms for culturing cells in two and three dimensions [2,3]. One particular class of networks, hydrogels, have proven particularly beneficial as they capture many key features of soft tissues, in part because of their high water content and porosity, as well as their tunable chemical and mechanical

34 properties. The design of hydrogels as synthetic ECM mimics is often informed by knowledge of the composition of the macromolecular constituents and the stiffness (or more precisely, the elastic modulus) of their native tissue counterparts. By changing the chemical and physical properties of hydrogel networks, biomaterials researchers are testing hypotheses related to regenerating tissues or understanding disease processes, and elucidating the mechanisms underlying cell-matrix interactions and mechanosensing [4].

This increasingly refined knowledge, in turn, improves design strategies for future synthetic biomaterials and has advanced the development of new materials to fulfill emerging needs.

This review focuses on recent advances in the development of polymer networks with controlled mechanical properties, especially viscoelastic hydrogels, and their biological applications. The mechanical properties of the ECM are increasingly appreciated as an important factor in regulating cell function and fate. In 2006, seminal studies by Discher and coworkers demonstrated that the underlying substratum elastic modulus dictated the differentiation of bone marrow derived human mesenchymal stem cells (MSCs) [5].

Using agarose hydrogels that closely matched the modulus of brain, muscle, and pre-calcified bone, MSCs preferentially differentiated down neurogenic, myogenic, and osteogenic pathways, respectively. Since then, a plethora of research and publications have further supported the notion that the mechanical properties of materials can directly control cell behavior [6]. For example, cell-cell interactions (e.g., cell- cell contacts [7,8], cell secreted factors [9,10], heterologous cell interactions [11,12]) and cell-matrix interactions such as matrix dimensionality [13,14], matrix degradability [15–17], adhesive ligand presentation [18,19], substrate modulus [20,21], network nano/micro-architecture (e.g., topography [22], fiber structure [23]), and spatial heterogeneity of chemical [24,25] and biophysical [26,27] cues, have all been shown to influence different aspects of cell interactions and, ultimately, cell function (Fig. 2.1a).

Despite this growing body of work, native tissue properties are more than a fixed scalar value, and a single modulus or stiffness measurement often oversimplifies the description of tissue mechanics.

Specifically, mechanical softening [28], stiffening [29], and other temporally dynamic matrix mechanics

[30] have been shown to influence cell behavior (Fig. 2.1b). Even at a constant matrix composition, many

35 tissues exhibit mechanical properties that are complex functions of time and length scales. For instance, several soft tissues show mechanical fingerprints of viscoelasticity, such as stress relaxation, creep, and hysteresis, all of which are dependent on the timescales of deformation. In addition, tissues can exhibit higher mechanical moduli at strains/stresses beyond a critical threshold, known as strain/stress stiffening.

Only recently has the biomaterials community started to systematically investigate how cells sense and respond to these types of complex mechanical properties [31–33]. Many non-intuitive results have emerged from these studies, and findings constantly challenge the existing understanding of cellular mechanosensing, while simultaneously revealing potential new strategies to control cell fate and function by materials engineering.

This review article begins with a brief overview of current research aimed at creating polymer networks, with a primary focus on water-swollen networks (i.e., hydrogels), that can recapitulate many of the time-dependent mechanical properties of native tissues. The mechanical properties of tissues are briefly introduced, especially in the context of motivating the development of new materials. Next, advances in dynamic covalent chemistries that can emulate tissue-like viscoelasticity are discussed, and specific examples are provided to illustrate cell responses when cultured on and/or within these synthetic and adaptable ECM-mimicking materials. Finally, the review ends by highlighting future directions where innovations in materials design might foster the development of new biomaterials for studying mechanobiology, matrix biology, and tissue engineering.

36

Figure 2.1 Complex cell-cell and cell-matrix interactions influence cell behavior in 3D environments. (a)

Biochemical and biophysical cues in the extracellular matrix (ECM) influence cell behavior. Fig 2.1a adapted from Madlet al. [11] copyright 2018 Annual Review of Biomedical Engineering (b) Engineering the cellular microenvironment with dynamic materials can elicit spatiotemporal control over biophysical cues to direct cell fate. Fig 2.1b adapted from Ma et al. [30] copyright 2018 Wiley.

2.3. Mechanical signatures of viscoelasticity

Viscoelasticity describes the ability of a material to simultaneously resist mechanical deformation under an applied load (solid-like behavior) and to dissipate energy (liquid-like behavior). The viscoelastic properties of polymers, and the hydrogels and soft tissues that are reviewed herein, often manifest as stress relaxation, creep and hysteresis, which can be revealed by a variety of mechanical measurement techniques.

Perhaps one of the most widely used approaches to measure viscoelasticity of soft materials is shear rheometry [34,35]. In this method, a hydrogel or tissue specimen is placed between two parallel plates or a cone-plate configuration and subject to simple deformation conditions that allow for facile computation of the material’s dynamic mechanical properties. These testing procedures can be either transient or cyclic. In

37 transient measurements (Fig. 2.2a), a step strain γ0 or stress σ0 is imposed onto the sample, and the resulting stress σ(t) or strain γ(t) is monitored as a function of time, which are known as stress relaxation and creep, respectively. In cyclic measurements (Fig. 2.2b), a sinusoidal strain γ(t) = γ0sin(ωt) is imposed onto the sample at varying frequencies, and the resulting stress σ(t) = σ0sin(ωt + δ) is measured, where the phase shift δ reflects the viscoelastic contribution. The stress-strain relationship is then decomposed into real and imaginary components to extract the storage modulus, G’(ω) and loss modulus, G”(ω), giving a frequency sweep spectrum.

While the aforementioned experimental techniques provide macroscopic or bulk mechanical information about materials, it is sometimes desirable to obtain local viscoelastic properties in a spatially defined manner. Mechanical characterization on a microscopic scale is particularly valuable for understanding correlations between ECM composition and its mechanics at the interface with cells. Current methods that permit local measurements of viscoelasticity (i.e., in the proximity of a cell cultured on or embedded within a material) include microrheology, indentation, and elastography. In microrheological measurements, tracer microparticles are embedded in the specimen, and the average motion of the particles under thermal fluctuations or external forces are used to infer the viscoelasticity of the surrounding microenvironment, based on the generalized Stokes-Einstein equation [36–39]. For example, Schultz et al.

[40] used particle tracking microrheology to study local changes caused by cell-secreted proteases (Fig.

2.2c), and used the logarithmic slope of the mean square displacement (α) as a measure of local viscoelasticity. Compared to conventional bulk rheological characterization, microrheology is useful for quantifying mechanical properties of cell-laden hydrogels, especially to understand changes in the material properties directly adjacent to the cells as they undergo dynamic cell-mediated remodeling (e.g., degradation or protein deposition) [40]. However, it remains challenging to apply this technique to characterize tissues, in part because of the difficulty in homogenously dispersing probe particles in dense tissue samples without damaging the ECM microenvironment. In addition, microrheology is typically

38 constrained to a narrow range of material moduli, further limiting the technique to very soft tissue mimics

(elastic modulus, E ~ 10-500 Pa) [41,42].

Elastography is an imaging technique that allows for completely non-invasive measurement of mechanical properties of tissues and is routinely performed in clinical settings to understand the states and changes of viscoelastic properties in patients. In an elastography experiment, shear waves are generated by ultrasound [43] or magnetic resonance [44], and the waves are measured after propagation through the material in order to infer spatial mechanical information about the specimen. Viscoelasticity is often presented as frequency sweep spectrum (with information averaged across the image area/volume) [45,46] or heat maps showing the elastic and viscous modulus components at a single frequency [47]. In this way, magnetic resonance elastography allows the elastic storage modulus (G’) and viscous loss modulus (G’’) to be resolved for an entire organ (e.g., human brain) (Fig. 2.2d) [47]. However, this technique is constrained by resolution in the millimeter range (macroscopic), which is suitable for large tissue scans, but unable to provide reliable information at the cellular level (microscopic) [48].

Indentation is another common technique to probe the mechanical environment of tissues and synthetic materials. By using an apparatus, such as an atomic force microscope or nano-indenter equipped with probes of well-defined sizes and shapes, one can apply a controlled load to a specimen across a small contact area rather than the whole sample. The resulting force-displacement response is then analyzed with mathematical models to extract parameters that represent the mechanical properties of the sample [49]. For example, nano-atomic force microscopy (AFM) measurements of articular cartilage show different moduli for collagen and proteoglycan components of the ECM (Fig. 2.2e) [50]. This nanoscale heterogeneity cannot be resolved by some of the other techniques mentioned above. It has been reported that the elastic modulus from indentation is typically at least an order of magnitude smaller than that measured by bulk tensile measurements, further suggesting important method-dependency of mechanical characterization results and illustrating the mechanical heterogeneity of native tissues [49]. On smaller length scales, on the order of µm, solvent migration becomes increasingly important for energy dissipation, a phenomenon

39 known as poroelastic relaxation [51,52]. It is thus important to distinguish viscoelastic relaxation from poroelastic relaxation.

In principle, the mechanical information from different testing procedures can be interconverted

[26]. In fact, this practice is routinely done to provide a combined mechanical spectra over a much broader time or frequency range that is otherwise difficult to obtain using a single experiment (Fig. 2.2f) [53–55].

For testing soft tissues or hydrogels, one should always perform experiments with extra precautions to avoid measurement artifacts that might result from instrument inertia, torque limits, interfacial slips, surface/edge effects, sample dehydration, and irregularity of the sample size [56,57]. Both transient and cyclic measurements can also be performed via compression and tension, which are advantageous for characterizing both linear and nonlinear mechanical properties, mechanical anisotropy, and deformation- induced changes in the structure-mechanics relationship in complex tissue or hydrogel samples [49].

Figure 2.2 Methods for characterizing viscoelasticity of soft materials (e.g., hydrogels, tissues). (a) The application of a step change is often used to measure dissipative (viscous) material behaviors. When a step

40 strain γ0 is applied, stress relaxation is measured. Conversely, when a constant stress σ0 is applied to the material, a creep test measures the material deformation or creep compliance. (b) Cyclic measurements allow researchers to decouple elastic (in-phase) and viscous (out-of-phase) material responses in real time.

Cyclic measurements are often used over a range of frequencies in order to obtain a frequency sweep spectra, which illustrate how a material will respond to mechanical stimuli as a function of application rate.

(c) Particle tracking microrheology is a useful technique for investigating local as opposed to bulk changes in material properties. For example, microrheology allows researchers to study microenvironmental changes in viscoelastic properties due to cell-secreted proteases. Fig. 2.2c adapted from Schultz et al. [40] copyright 2015 the National Academy of Sciences of the United States of America. (d) Magnetic resonance elastography (MRE) uses magnetic resonance imaging (MRI) imaging with low-frequency vibrations to spatially map viscoelastic properties. Here, the elastic storage modulus (G’) and viscous loss modulus (G’’) are spatially resolved in a transverse section of human brain, demonstrating this technique’s ability to generate visual representations of whole-tissue mechanical characteristics. Fig. 2.2d adapted from

Weickenmeier et al. [47] copyright 2018 Elsevier. (e) Indentation measurements such as atomic force microscopy (AFM) allow nanoscale resolution of tissue mechanics. Here, articular cartilage shows different moduli for collagen fibrils and proteoglycans, illustrating higher-resolution information than is possible with other measurement techniques. Scale bars represent 2 μm. Fig. 2.2e adapted from Loparic et al. [50] copyright 2010 Elsevier. (f) Each technique is characterized by accessible timescales, illustrating that limitations of each technique typically require multiple approaches to fully understand complex viscoelastic behaviors of soft materials.

2.4. Viscoelasticity of native tissues

Most tissues in our bodies contain specific cell types embedded within ECM that is organized in a spatially defined manner to form functional sub-units. In this way, the ECM provides not only the architectural framework for all tissues and organs, but its material properties impart critical biomechanical cues [58] that influence cell functions (e.g., proliferation, differentiation, and migration) [59]. In the body,

41 soft tissues and fluids exhibit an extremely wide range of moduli (E), from ~ 1 Pa for mucin to > 106 Pa for pre-calcified collagenous bone (Fig. 2.3a). As a result, many publications document the use of hydrogels with systematically varied Young’s moduli and document the importance of cellular matrix signaling and mechanosensing [5,28,29,60,61].

While variations in the Young’s moduli (E) of tissues have been long recognized, only recently have differences in the timescales of matrix viscoelasticity become broadly appreciated [62]. Substantial differences in both the rate and degree of stress relaxation are evident across various tissues (Fig. 2.3b). For example, liver tissue relaxes 50% of its stress within less than 1 s and can eventually relax over 90% of the total stress. In contrast, the relaxation of heart valves is considerably slower, on the order of hours, 103 s, and the maximum degree of stress relaxation is less than 30%. The structural basis responsible for the observed differences in viscoelasticity of various tissues remains poorly understood. It is also noteworthy that the relaxation profiles of many soft tissues are complex and cannot be described by a simple Maxwell model (i.e., a spring and dashpot in series) and its classical exponential decay function. One empirical approach to compare the relaxation time constant across different types of tissues is to look at the time at which 50% of the stress is relaxed (τ1/2) [32,63]. However, given the increasing knowledge that cells integrate mechanical signals over time in their decision making [31,60], this phenomenological approach omits important information, especially when tissue relaxation profiles span across a broad range of timescales. Furthermore, it should be noted that stress relaxation experiments do not always follow the same procedures, and the reported rise time and strain magnitude can vary substantially across laboratory measurements. These inconsistencies can limit the ability to compare data from different sources, yet this information is still quite valuable for the biomaterials and regenerative biology communities.

Characterizations of changes in the viscoelastic properties of tissues is also instrumental for further understanding physiological and pathological processes [47,64]. For example, magnetic resonance elastography of brain, liver, and muscle tissue (Fig. 2.3c) illustrate changes in viscoelasticity that lead to power law dependence as a result of the underlying (patho)physiology (Fig. 2.3d) [46]. Significantly, tissues

42 that become fibrotic upon injury or with disease are known to have a concomitant increase in their modulus

(elasticity), but these tissues also gradually lose their ability to dissipate energy (viscosity). Changes in both stiffness and energy dissipation are important in cell-matrix signaling. While existing studies have successfully documented and explained the effects of stiffness as it relates to many cellular and disease processes, the effect of viscoelasticity has only recently been explored.

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Figure 2.3 Viscoelastic properties of native tissue. (a) Schematic illustrating the scale of soft tissue moduli.

Fig. 2.3a Adapted from Discher et al. [65] copyright 2009 AAAS. (b) Stress relaxation profiles of soft tissues: adipose [66], liver [67], brain [68], lung [69], prostate [64], cervix [70], muscle [71], hematoma

[63], and heart valve [72]. Early relaxation profiles are not shown when the test procedure did not use a step strain. (c) Technical setup and representative magnetic resonance elastography (MRE) images showing brain, liver, and femoral muscle tissue. (d) Changes in the viscoelastic power law behavior of brain, liver and skeletal muscle as a result of natural physiology or pathology from human MRE data. Fig. 2.3c-d adapted from Sack et al. [46] copyright 2013 Royal Society of Chemistry.

2.5. Viscoelastic networks with reversible crosslinks and their relaxation mechanisms

A widely used strategy to prepare viscoelastic hydrogels is based on networks where reversible crosslinks form the network junctions. These dynamic bonds are based upon either reversible covalent chemical reactions or reversible supramolecular (physical) interactions. In both cases, the adaptable motifs can undergo numerous cycles of association and dissociation under thermal fluctuations and/or mild stimulus triggers, giving rise to viscoelastic network properties.

Many groups have contributed to theories explaining the molecular principles that govern the relaxation of reversible networks. In early work, Green and Tobolsky formulated theories that incorporated the impact of bond dissociation and re-association on network relaxation [73]. They arrived at the classic

Maxwell model, where the characteristic network relaxation time is the inverse of the reversible reaction rate. Although their assumption of equal forward and reverse reaction rates oversimplifies the physical picture, this work inspired connections between small molecule reaction kinetics and their influence on material relaxation timescales, bridging the gap between microscopic connectivity and macroscopic mechanics.

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Over the years, models and theories have refined the Green-Tobolsky model and added the influence of microscopic structure on network relaxation [74–77]. Amongst these, one of the most notable advancements was developed by Leibler, Semenov, Rubinstein and Colby [75,78–81]. Their theoretical framework is often referred to as the sticky Rouse theory for unentangled polymers and sticky reptation theory for entangled polymers. The authors modeled a network formed by linear polymers with multiple associative side groups regularly spaced along the backbone, which can undergo reversible dimerization.

By modifying the classic Rouse and reptation theories and applying scaling analysis, they developed many important predictions that were in good agreement with later experimental observations [82]. For example, network relaxation time is largely influenced by the lifetime of individual bonds, but increases with polymer concentration due to variations in the chain topology (known as bond lifetime renormalization).

In addition to the theoretical work mentioned above, several experimental studies have probed the connections between the kinetics of small molecule reactions and network relaxation rates. Seminal work by Yount et al. [83,84] measured the reverse reaction rate constants and equilibrium constants of pincer- complexes and characterized the dynamic mechanical properties of the resulting gels. The reverse rate constants were used to normalize the network viscosity and the shear rate, resulting in a master flow curve for gels with different types of pincer-pyridine complexes. This study provided the first experimental quantitative correlation between network relaxation and small-molecule reactions. Later, many studies on reversible networks based on chemically distinct motifs, such as coiled‐coil peptides [85], histidine-nickel complexes [86,87], Diels-Alder reactions [88], hydrazones [89,90], boronates [91] and thioesters [92,93] further validated the observations and conclusions by Yount et al [83,84]. These studies illustrate the strong correlation between macroscale measurements and bond dynamics in reversible networks. For example, temperature dependent crossover frequencies of Diels-Alder hydrogels are consistent with predicted values from small molecule kinetic studies (Fig. 2.4a-b) [88]. Similarly, acyl-hydrazone bond dynamics can be used to estimate self-healing times for reversibly crosslinked acyl-hydrazone hydrogels (Fig. 2.4c-d) [90].

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Finally, differences in equilibrium kinetics between phenylboronic acid derivatives are shown to influence stress relaxation times of boronate hydrogels (Fig. 2.4e-f) [91].

While these previous studies improved understanding of relaxation mechanisms in reversible networks, other factors should be considered for designing materials that capture the viscoelastic properties of soft tissues. First, almost all of the previous studies examined the network relaxation over a relatively narrow time period, and the conclusions rely on an implicit assumption that bond dissociation is the predominant, if not the only, relaxation mechanism. However, characterization of reversible networks necessarily occurs over multiple experimental timescales. On longer timescales, chain mobility becomes non-negligible, as motions of segment, chain and dynamic clusters can also lead to network relaxation

[55,94]. On shorter timescales, thermal fluctuation of network junctions or Rouse relaxation of single chains may introduce additional relaxation modes [95,96]. These material properties can be influential on cell behavior, as cells are known to integrate mechanical cues over time [97] and these neglected relaxation mechanisms may exert non-negligible influences on cell fate and function. Second, there remains a lack of quantitative correlation between bond dynamics and network relaxation [87]. Nonetheless, the knowledge gained in this set of theoretical and experimental studies can guide the rational design of reversible networks and their applications as self-healing materials [98,99] and cytocompatible hydrogels for regenerative medicine [71,100].

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Figure 2.4 Correlations between macroscale viscoelasticity and covalent bond dynamics. (a) Temperature dependent Diels-Alder/Retro-Diels-Alder reaction between furan and maleimide. (b) Viscoelastic frequency dependence is consistent with predicted values from kinetic analysis. Adapted from Adzima et al. [88] copyright 2008 American Chemical Society. (c) Polymer hydrogels based on reversible hydrazone bonds. (d) Engineering stress (σeng) graphed by extension ratio (λ) for different self-healing times, illustrating agreement between material behavior and acyl-hydrazone bond dynamics. Adapted from Liu et

48 al. [90] copyright 2012 American Chemical Society. (e) Differences in reaction kinetics between phenylboronic acid derivatives in the presence of cis‐diols. (f) Varying the stoichiometric amounts of phenylboronic acid (PBA) to o-aminomethylphenylboronic acid (APBA) influences stress relaxation in boronate hydrogel networks. Figure adapted from Yesilyurt et al. [91] copyright 2017 Wiley.

Figure 2.5 Addition and exchange mechanisms for dynamic covalent crosslinks. (a) Addition reactions

(e.g., boronates) require breaking and reforming crosslinks, which results in kinetic dependence on the association and disassociation rate constants. (b) Equilibrium constants for addition reactions are strongly dependent on both temperature and functional group concentrations. (c) In contrast, exchange reactions

(e.g., thioesters) result in bond rearrangement without crosslink cleavage. (d) For exchange reactions the

49 reactants and products are the same. Therefore, the equilibrium constant is independent of temperature and the exchange rate is not influenced by concentrations of the reactive species.

2.6. Viscoelastic hydrogels with dynamic chemical bonds

Much of the recent development of viscoelastic hydrogels has been inspired by work in the field of covalent adaptable networks (CANs) or dynamic chemical networks [101–103]. In CANs, the chemical reactions that form the network crosslinks are reversible in nature. On timescales longer than bond lifetimes, dynamics of network connectivity translate to time-dependent mechanical properties. For applications in the realm of tissue-mimetic materials or tissue engineering matrices, one must further consider environmental constraints. Typically, materials are used at physiological conditions (e.g., aqueous environments with cell culture components, pH 7.0−7.6, 37°C), and these conditions may cause undesirable side reactions during formation of adaptable bonds or limit adaptability itself because of the narrow operational pH and temperature window. Therefore, the types of adaptable bonds suitable to recapitulate the viscoelastic properties of many soft tissues in the body are limited, especially for tissue engineering applications that necessitate gelation conditions mild enough to occur in the presence of living cells.

Generally, dynamic covalent chemistries are separated into either reversible addition reactions

(e.g., Diels-Alder, Schiff base, hydrazone, oxime, boronate) or reversible exchange reactions (e.g., disulfide, ally sulfide, thioester) (Fig. 2.5) [75,80]. Both are influenced by chemical kinetics, but each has different temperature and concentration dependencies [101]. In the case of addition reactions (Fig. 2.5a), the equilibrium constant (Keq = k1/k-1) describes the relative rates of association (k1) and disassociation (k-

1). Importantly, these parameters are dependent on both temperature and the relative concentrations of each species (Fig. 2.5b). In contrast, the equilibrium constant for exchange reactions (Fig. 2.5c) is necessarily equal to one (Keq = 1), and the reorganization of the network is dependent only on the temperature and the kinetics of the exchange reaction (Fig. 2.5d). Although this may seem limiting, a variety of biomaterial applications require the maintenance of a local crosslink density during network reorganization in order to decouple the effects of modulus and viscoelasticity on cellular responses and tissue regeneration. Below,

50 several examples of addition and exchange reactions are discussed to illustrate selection criteria for adaptable covalent bonds that are compatible with cell culture conditions. This discussion is placed in the context of chemical and mechanical tunability for dynamic cell-instructive materials, and how new insights can be gained by controlling viscoelastic cell-material interactions.

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Figure 2.6 Cytocompatible dynamic covalent chemistries. Chemical reactions are grouped by reorganization mechanism; addition reactions, exchange reactions, and both mechanisms. (a) Diels-Alder

[104,105,114–118,106–113] (b) Boronate [91,119,128–137,120,138–146,121–127] (c) Thioester

[92,93,147–153] (d) Ally Sulfide [154–163] (e) Schiff base [164,165,174,175,166–173] (f) Hydrazone

[27,71,181–190,87,191–200,89,201–210,100,211,212,176–180] (g) Oxime [176,180,221,213–220] (h)

Disulfide [222,223,232–234,224–231].

2.6.1. Diels-Alder reactions

Diels-Alder cycloaddition reactions between dienes (R−CH=CH−CH=CH−R) and dienophiles

(R−CH=CH−R) represent one of the most well-established and characterized reversible covalent crosslinking strategies (Fig. 2.6a) [104]. In 2002, the dynamic nature of Diels-Alder crosslinks was illustrated by work from the Wuld group, illustrating thermal reversibility of furan-maleimide Diels-Alder polymer networks [105]. However, due to the largely stable nature of Diels-Alder bonds at physiological temperature (37°C) and pH (7.4), these networks have only recently been applied to applications involving cell encapsulation and tissue engineering [106]. Early studies focused on the thermal reversibility of Diels-

Alder crosslinks for modulating drug delivery to influence cell behavior [235–237], and subsequent research validated the reversible nature of Diels-alder and retro-Diels-Alder reactions under physiologically relevant conditions [107,108]. For example, fulvene-modified dextran was crosslinked with dicholromaleic-acid-modified poly(ethylene glycol) to form self-healing hydrogels with reversible Diels-

Alder linkages. Although cells were not encapsulated in these networks, NIH 3T3 fibroblasts remained viable when treated with the hydrogel precursor molecules [108]. Diels-Alder networks have also been combined with other dynamic covalent chemistries to form multifunctional double network hydrogels

[109,110,113]. In one example, a mixed oxime-Diels-Alder network was formulated as a synthetic alternative to Matrigel. These double network hydrogels were formulated to mimic aspects of a tumor microenvironment and test the efficacy of reversibly tethered anti-cancer agents [111].

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Recently, inverse electron demand Diels–Alder (IEDDA) reactions have emerged as particularly relevant for biomaterials due to rapid gelation kinetics at physiological pH and temperature as well as remarkable bioorthogonality [114]. The discovery of new phenyltetrazine derivatives and strained cycloalkenes has enabled rapid expansion of biological applications for IEDDA chemistries from bioprinting [115] to cell encapsulation [116]. For example, recent work illustrated the use of a dynamic

IEDDA reaction between norbornene and tetrazine to create injectable hydrogels for drug delivery [117].

In another recent example, Delplace et al. also used norbornene, but reacted with methylphenyltetrazine, to form methylcellulose hydrogels with moduli similar to that of brain tissue (1–3 kPa). Interestingly, the researchers incorporated degradable disulfide crosslinks in addition to IEDDA crosslinks showing survival and proliferation of neural progenitor cells for treating central nervous system injuries [118].

To date, Diels-Alder chemistries have been largely used for , drug delivery, and stabilization of double network hydrogels. Future opportunities exist to broaden the range of Diels-Alder reversibility and shorten long relaxation times for cell signaling under physiologically relevant conditions

[112].

2.6.2. Imines

Imines represent a family of dynamic covalent bonds with reversible carbon nitrogen double bonds

(R-C=N-R), which form by reactions between nucleophilic (R-NH2) and electrophilic carbonyl compounds (R-CHO-R). Although pioneering work studying such equilibria was completed in the 1960’s, biomedical application of these reactions has expanded rapidly in recent years [164,165], in part due to the compatibility of the forward (condensation) and reverse (hydrolysis) reactions with numerous biologics.

Both of these reactions occur readily in aqueous environments, producing or consuming water as the only byproduct. Many researchers have opted to control the chemical equilibrium of crosslinks by altering the identity of the reactive precursor species [176]. For example, when the nucleophile is a hydrazine (R-

NH-NH2) or (R-CH(O)-NH-NH2), the resulting imine bond is more specifically a hydrazone bond (R-NH-N=C-R). Similarly, when the nucleophile is an alkoxyamine (R-O-NH2) the resulting bond is

54 known as an oxime (R-O-N=C-R). The equilibrium of these reactions can be further tuned by modifying adjacent chemical moieties, resulting in even more specific subtypes. For example, a benzaldehyde can be used as the electrophile to form a benzoic imine, which increases the hydrolytic stability compared to aliphatic imines [177]. Interestingly, although the primary mode of reorganization in these networks is considered a natural equilibrium (i.e., addition reactions), reactive nucleophiles can also participate in transimination (i.e., exchange reactions) with imine bonds. These contributions can become particularly important in systems where there is a stoichiometric excess of the nucleophile or in the presence of nucleophilic small molecule catalysts [178].

2.6.2.1. Schiff Bases

Here, the term Schiff base is used where an imine bond cannot be more specifically classified as either a hydrazone or an oxime (Fig. 2.6e). These are typically the most reversible type of imine, exhibiting poor hydrolytic stability and fast stress relaxation [165]. When used for cell encapsulation and tissue engineering, these networks are often formed by modifying long natural polymer backbones, such as chitosan, hyaluronic acid and alginate [166–171,175]. In one recent study, Wei et al. [172] used dextran- chitosan hydrogels with dynamic Schiff base crosslinks to study how injection can influence cellular morphogenesis. These experiments lend insight for designing more effective polymer-based cell delivery systems. To date, much focus has been centered on the development of self-healing and injectable Schiff base hydrogels with shear-thinning properties. These hydrogels have been largely designed for application as tissue adhesives, while less focus has been placed on the time-dependent dissipative properties of these materials (e.g., stress relaxation, creep) [173,174].

2.6.2.2. Hydrazones

A hydrazone is a special class of imine formed upon reaction of a carbonyl, typically an aldehyde, with a hydrazine or hydrazide (Fig. 2.6f). These alpha nucleophiles are more reactive than standard amines, exhibiting enhanced bond stability and reversible adaptation on longer timescales [179]. Prior to application as viscoelastic materials for cell culture, hydrazones were extensively used for bioconjugation and acellular

55 materials synthesis [180–184]. The reaction between and / often proceed rapidly, without significant off-target reactions. For this reason, hydrazone formation reactions are sometimes listed as orthogonal bio-click reactions [185]. However, the on-and-off dynamics of adaptable hydrazone addition reactions can also lead to surface erosion or bulk degradation, resulting in concomitant mass loss and decreased moduli over time. Several strategies have been developed to minimize or completely suppress erosion, including introducing hydrolytically stable bonds (e.g., [186], benzyl- hydrazones [187]) above the percolation threshold [188,189] and increasing the functionality of the polymer backbone [71].

Examples from the literature have broadly illustrated the use of hydrazone crosslinks for tissue engineering applications. More specifically, cytocompatible 3D encapsulation has been demonstrated with cells from bone [190,191], cartilage [192,193], muscle [100,194], and heart tissue [195,196]. Despite the well-established biological compatibility of hydrazone crosslinks, less emphasis was initially placed on how the viscoelastic behavior of hydrazone scaffolds can signal to cells [197–201]. However, McKinnon et al. developed adaptable hydrazone PEG hydrogels specifically to study the mechanobiological effects of viscoelastic network reorganization on cell behavior [71,89,100,187]. These hydrogels were used to study how viscoelasticity of dynamic hydrazone crosslinks could influence myoblast spreading in 3D [71] and calculate cellular forces associated with axon extension (Fig. 2.7a) [100]. Later Richardson et al. used the same PEG-hydrazone platform to study chondrocyte behavior for cartilage tissue engineering; showing that stress relaxation can modulate ECM deposition [187] and that creep compliance directs cell morphology during mechanical deformation [27]. In addition to PEG based hydrogels, naturally derived polysaccharides often contain 1,2-diols or carboxylic acids that can be modified to produce aldehyde moieties [202,203].

Notably, Lou et al. [198] developed hyaluronic acid-collagen interpenetrating networks and showed that stress relaxation of hydrazone crosslinks could be tuned to promote cell spreading, fiber remodeling, and focal adhesion formation (Fig. 2.7b). One should note that linear polysaccharides significantly differ from multi-arm PEGs in their ability to biochemically signal to cells [202,204]. Additionally, differences in

56 backbone architecture play an important role in controlling network connectivity, ultimately influencing the final material properties [87,205,212].

Interestingly, hydrazone kinetics can also be controlled by introducing external stimuli such as pH

[71,206], light [207], and catalysts [208] to tune the viscoelasticity of hydrazone materials. For example, exogenous addition of small molecule catalysts at low concentrations can dramatically influence the formation and cleavage of hydrazone bonds. Significantly, this control has been achieved in aqueous environments in the presence of cells [209]. Such catalysts have been used to temporally alter the viscoelasticity of injectable cell delivery systems, exhibiting time dependent network stabilization due to small molecule diffusion (Fig. 2.7c) [210,211]. In another noteworthy example, Wang et al. [238] developed dynamic hydrazone bioinks for 3D printing (Fig. 2.7d). In this case another stimulus, light, was employed to stabilize networks after extrusion by utilizing a secondary photo-crosslinking reaction.

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Figure 2.7 Dynamic hydrazone hydrogels. a) Stress relaxation of dynamic hydrazone crosslinks allows motor neurons to extend axon bodies into the hydrogel. (i) Stress relaxation of alkyl-hydrazone crosslinks.

(ii) Dynamic hydrazone equilibrium reaction responsible for network stress relaxation. (iii) Embryonic stem cell-derived motor neurons in PEG hydrazone hydrogels stained with Calcein (green) for live cells, and

Ethidium Homodimer (red) for dead cells. Scale bar is 200 μm. (iv) Stress relaxation-mediated axon extension allows cellular forces to be calculated. Fig. 2.7a adapted from McKinnon et al. [100] copyright

2014 Royal Society of Chemistry. (b) Dynamic hydrazone crosslinks and network stress relaxation regulate cell spreading and focal adhesion of hMSCs in 3D. (i) Stress relaxation of dynamic hydrazone crosslinks promotes cell spreading. (ii) Comparison with static controls illustrates that dynamic covalent crosslinks allow cells to remodel their local microenvironment. (iii) Dynamic crosslinks lead to significant differences in cell morphology and the percentage of cells that form focal adhesions. Fig. 2.7b adapted from Lou et al.

[198] copyright 2017 Elsevier. (c) Hydrazone crosslink dynamics tuned by introducing a small molecule catalyst to facilitate injectable delivery of human umbilical vein endothelial cells (HUVECs). (i) Temporal modulation of injectability is based on small molecule catalyst diffusion. (ii) High cell viability was observed post-injection in the presence of catalyst. (iii) Stress relaxation could be modulated in hydrazone hydrogels using both catalyst concentration and polymer content. (iv) The schematic represents the hydrazone reaction including the mechanism of catalysis. Fig. 2.7c adapted from Lou et al. [210] copyright

2018 Wiley. (d) Dynamic exchange of hydrazone crosslinks facilitates extrusion bioprinting of NIH T3T fibroblasts. (i) Shear-thinning hydrazone hydrogels allow 3D printing of self‐healing hydrazone bonds. (ii)

Macroscopic view of 4‐layer 3D printed hydrazone lattices. (iii) Hydrazone hydrogel viscosity decreases with increasing shear rates to enable 3D printing. (iv) Live/dead staining within lattice filaments after extrusion verifies cytocompatability of the printing technique. Fig. 2.7d adapted from Wang et al. [238] copyright 2018 Wiley.

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2.6.2.3. Oximes

Oximes are generally considered to be the most stable and least dynamic imine [213] used for cell encapsulation and tissue engineering (Fig. 2.6g) [214]. Despite conventional wisdom, recent studies have proposed significant viscoelastic behavior, such as self-healing, for oxime networks under certain conditions [215]. For example, Sánchez-Morán et al. [216] designed oxime-alginate hydrogels exhibiting average stress relaxation times from several hours up to one day. Additionally, examples from the literature demonstrate the usefulness of oxime-crosslinked materials for tissue adhesives [217], injectable cell delivery [218,219] and bioprinting [220]. Work by Zander et al. [221] may partially explain the discrepancy between the hydrolytic stability of oxime bonds [176,180] and the viscoelasticity of oxime networks. This study showed that pH and salt concentrations can both influence the efficiency of oxime network formation, suggesting that formation kinetics may play an important role in the viscoelasticity of oxime hydrogels.

2.6.3. Boronates

Boronic , or boronates (R-B-(OR)2), are often formed by addition reactions between boronic acids (R-B(OH)2) and cis-1,2-diols (R-CH(OH)-CH(OH)-R) or cis-1,3-diols (R-CH(OH)-CH2-CH(OH)-R)

(Fig. 2.6b). Reversible boronate bonds are well-known for their responsive properties [119], especially with respect to saccharide concentration [120,121] and solution pH [122,123]. Boronate-based hydrogels exhibit dynamic mechanical properties, including shear-thinning [124,125], self-healing [123,126], and frequency- dependent viscoelasticity [91,127,128]. Boronate-based hydrogels exhibit fast relaxation timescales, often on the order of seconds [91,129–131] which can be attributed to rapid bond dynamics [130–133]. Fast material relaxation timescales make boronate-based materials uniquely suited to mimic soft tissues that show fast relaxation behavior, such as adipose [66], liver [67], and brain [68].

Boronate materials have been used as glucose sensors and controlled release devices [119,122,134–136], as well as tissue engineering cell culture platforms [119,129,137–139]. Tseng et al. [140] developed glucose-sensitive self-healing hydrogels as sacrificial materials to fabricate vascularized constructs (Fig.

2.8a), combining the two applications. However, dynamic boronate crosslinks present unique challenges

60 for regenerative medicine applications. First, the formation of boronates requires a pH above the pKa of boronic acid (typically 1-3 pH units above physiological pH 7.4) [141,142]. Thus, strategies have focused on lowering the pKa of boronic acids by intramolecular coordination with /nitrogen or by introducing electron withdrawing groups [122]. However, the synthesis and purification of boronic acid small molecules are notoriously difficult, and have limited widespread application in the materials research community [142,143]. In addition, cell culture media often contains free saccharides (mM range) that may drive boronate equilibrium towards dissociation, and glycoproteins on the cell surface can further disrupt material crosslinking [144]. In fact, boronate hydrogel degradation in the presence of cells is well documented [124,138,145], although this phenomena is advantageous in some settings (e.g., cell capture and release).

To circumvent the confounding effects of hydrogel degradation, Tang et al. [131] designed fast relaxing boronate hydrogels that exhibit long term stability by incorporating a small fraction of non- dynamic crosslinks (Fig. 2.8b) [131]. Human MSCs encapsulated in these viscoelastic boronate hydrogels showed YAP/TAZ nuclear localization, suggesting that dynamic covalent crosslinks can influence mechanotransduction in 3D hydrogels [131,146]. Smithmyer et al. [139] leveraged similar rapid boronate crosslink dynamics to study how self-healing influences cell infiltration during dynamic co-culture (Fig.

2.8c). Researchers were able to quantify the average distance pulmonary fibroblasts and breast cancer cells traveled across the healing interface, drawing conclusions relevant to cancer disease progression.

Importantly, the behavior of boronate hydrogels depends strongly on the chemical structure of the boronic acid species. For example, Figueiredo et al. [127] developed several chemically distinct boronate crosslinks to allow user-defined control over scaffold viscoelasticity for injectable cell delivery (Fig. 2.8d).

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Figure 2.8 Dynamic boronate hydrogels. (a) Glucose-sensitive boronate hydrogels enable self-healing branched tubular channels for tissue engineering. (i) Rheological testing at high and low strain illustrates shear-thinning and self-healing of dynamic boronate crosslinks. (ii) Extruded cell-laden dynamic boronate hydrogels form sacrificial tubular structures surrounded by static hydrogel. (iii) Seeding vascular constructs with multiple cell types reveals morphological structures resembling neurovascular units (red fluorescence: endothelial cells, green fluorescence: neural stem cells. Fig. 2.8a adapted from Tseng et al. [140] copyright

2017 Elsevier. (b) Hybrid networks containing reversible boronate bonds and permanent crosslinks allow viscoelastic mechanotransduction to be isolated without degradation. (i) Schematic illustrating chemical structures of static strain-promoted azide-alkyne cycloaddition (SPAAC) crosslinks and dynamic boronate crosslinks. (ii) Stress relaxation increases subcellular location of YAP/TAZ. (iii) Stress relaxation also influences cell morphology and cell volume (orange: F-actin, blue: nucleus, magenta: YAP/TAZ) Scale bar represents 5 µm. Fig. 2.8b adapted from Tang et al. [131] copyright 2018 Wiley. (c) Dynamic boronate chemistry crosslinks enable self-healing and cell infiltration. (i) Schematic illustrating boronate equilibrium and an image of a self-healing hydrogel hang test. (ii) Rheological strain sweep shows rupture and self- healing of dynamic boronate hydrogels. (iii) Pulmonary fibroblasts (green: CCL151) and breast cancer cells

(pink: MDAMB231) co-cultured in cut boronic acid-based hydrogels with cell infiltration quantified after self-healing. Fig. 2.8c adapted from Smithmyer et al. [139] copyright 2018 American Chemical Society.

(d) Injectable hydrogels cross-linked by boronic acid-fructose complexation. (i) Schematic illustrates HA hydrogels with dynamic boronate crosslinks. (ii) Chemically distinct boronic acid derivatives result in user- defined control over frequency dependent viscoelasticity. The storage modulus (G’) and loss modulus (G’’) vary as a function of oscillation frequency, illustrating accessible regimes for injectable cell delivery. Fig.

2.8d adapted from Figueiredo et al. [127] copyright 2019 American Chemical Society.

2.6.4. Adaptable sulfur chemistries

Reactions with sulfur functionalities have long been used for designing self-healing polymers

[239]; however, recent advances have greatly expanded the applicability of dynamic sulfur chemistries for

63 cell and tissue engineering [240]. These systems are often associated with phototunable properties making them exceptionally valuable for studying the spatiotemporal influence of matrix viscoelasticity on cell function [157,230,241]. The dynamic nature of these chemistries is also influenced by external stimuli such as pH and potentials, further expanding the accessible experimental space, but also potentially limiting biomedical application in vivo [94,152].

2.6.4.1.

Protein folding relies heavily on disulfide (R-S-S-R) bonds formed between cysteine residues

[222,223]. These disulfide bonds (Fig. 2.6h) can be reduced under physiological conditions driving dynamic addition reactions [224–226]. Disulfide-crosslinked hydrogels demonstrate dynamic material properties in addition to rapid gelation conditions suitable for biomedical applications [227–229]. For example, disulfide networks typically exhibit relatively fast relaxation kinetics (faster than hydrazones but slower than boronates) in the presence of UV light and photoinitiator [242]. Characteristic timescales for these exchange reactions are typically on the order of minutes [230]. Bermejo-Velasco et al. [231] demonstrated that electron-withdrawing groups influence the protonation state of thiols, ultimately influencing disulfide formation. Researchers further studied these reaction kinetics and demonstrated how polymerization and cell-directed degradation can be tuned to influence the mechanical properties of disulfide hydrogels crosslinked under physiological conditions. In another example, Lee et al. [234] used mechanoresponsive disulfide crosslinks to pattern hydrogels with proteins during mechanical compression (Fig. 2.9a). In this way, the researchers were able to mimic force-induced bond rupture that occurs in viscoelastic tissues to control cell behavior on 2D substrates.

Much of the work using dynamic disulfide hydrogels has focused on swelling and degradation associated with network reorganization [232]. More viscoelastic characterization will be critical to better understand how disulfide networks can be controlled for studying cell behavior. An important caveat is that disulfide crosslinking strategies may be susceptible to side reactions with proteins in vivo. This could

64 hamper user-directed control over the mechanical properties or adversely influence long term network stability [222,233].

2.6.4.2. Thioesters

Recently, thiol-thioester exchange, or transthioesterification has emerged as a viable strategy for controlling hydrogel viscoelasticity (Fig. 2.6c). At a pH greater than the pKa of thiols, thiolate anions (R-

S-) are able to attack thioesters (R-CH(O)-S-R), generating new thioester bonds and releasing thiols [147].

In the presence of free thiols at mM concentrations, rate constants for this exchange reaction are in the range of 10-4 to 10-2 s-1 [93]. This rate suggests that the transthioesterification reaction is significantly slower than the cleavage reaction of boronates, but faster than that of hydrazones. While reversible transthioesterification has long been recognized as the basis for native chemical ligation, its application to form materials relevant for cell encapsulation and biomaterial applications was not demonstrated until recently [148–151].

Early work by Ghobril et al. [150] applied dynamic thioester exchange to develop novel dissolvable hydrogel sealants for wound closure (Fig. 2.9b). Researchers created thioester crosslinked hydrogels by native chemical ligation that were able to adhere strongly to human skin even during torsional stress. Upon exposure to thiolate solutions, thiol-thioester exchange rapidly reduced the sealant modulus allowing the wound closure to be completely washed (~30 minutes) from the skin. While this early example illustrated the biomedical applicability of thioester exchange, the viscoelastic behavior of thioester hydrogels was not used to control encapsulated cell behavior until very recently. In 2019, Brown et al. [92] photo-polymerized thioester PEG hydrogels with relaxation time constants from 104 to 106 s under physiological conditions

(Fig. 2.9c). Hydrogels with these adaptable thioester bonds supported proliferation of encapsulated MSCs and allowed them to spread in three dimensions. Subsequently, a similar hydrogel platform was also used to study mechanotransduction in thioester hydrogels. Researchers showed that photo-induced viscoelasticity can increase YAP/TAZ nuclear localization [152]. More interestingly, cell readouts reverted

65 back to elastic control levels when the viscoelasticity was “switched-off.” These types of experiments are providing useful information to researchers seeking to understand how cells respond to dynamic changes in substrate viscoelasticity (e.g., as occurs during fibrosis) [153].

2.6.4.3. Allyl sulfides

Ally sulfide (R-S-CH2-C(CH2)-CH2-S-R’) network reorganization (Fig. 2.6d) is achieved by introducing radicals which participate in addition-fragmentation chain transfer resulting in photoinduced plasticity and stress relaxation [154]. In contrast with the other dynamic covalent chemistries discussed thus far, materials with allyl sulfide crosslinks are primarily elastic and depend on free radicals (typically photoinitiated) to exhibit dissipative (i.e., viscous) behavior, such as stress relaxation and creep. However, the stimuli dependent viscoelasticity of allyl sulfide materials renders them suitable for studying cellular response to dynamic changes in viscoelasticity [155,156]. Early work with mammalian cells leveraged the dynamic nature of allyl sulfide crosslinks to modulate the presentation of biochemical cues [157,158].

Hydrogels with allyl sulfide crosslinks have also been adapted as biomaterials where dynamic photo- induced network exchange allows experimenters to study time dependent cell responses to viscoelastic changes in their microenvironments [159–161].

Finally, complete degradation of ally sulfide networks is achievable by introducing monothiols into the solution, which rapidly (< 30 s) exchange with network crosslinks. This exchange rapidly alters the mechanical properties of the hydrogel and circumvents light attenuation limitations when erosion/degradation occurs [159]. For example, Brown et al. [159] demonstrated complete dissolution of 1 cm thick hydrogel sample in ~ 1 min using cytocompatible photochemistry conditions. Similarly, by incorporating a tethered photoinitiator, the viscoelastic properties of hydrogel networks can be altered in a spatiotemporally controlled fashion. Viscoelastic timescales of allyl sulfide networks range from tens of seconds to a few minutes [159,241]. Researchers observed that MSC protrusions retract in response to photo-induced viscoelasticity, implying that individual cell spreading can be controlled in a user-defined

66 manner [160]. In addition, ally sulfide-crosslinked PEG hydrogels have been reported as a substitute for

Matrigel to passage intestinal organoids [163] and direct crypt formation [161]. Hydrogels for organoid expansion and differentiation represent an area of growing interest within the biomaterials community, and methods to form high fidelity organoids are necessary to enable new drug screening techniques [162]. In one example, researchers varied the relaxation of matrix forces to control crypt formation in intestinal organoids (Fig. 2.9d) [161]. Further, Yavitt et al. [163] studied how the structure, specifically pKa, of small molecule thiols influences photodegradation to optimize degradation of allyl sulfide hydrogels for organoid passaging. Collectively, these studies lend better understanding as to mechanical dependencies central to producing reproducible organoids for clinical applications.

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Figure 2.9 Dynamic hydrogels based on adaptable sulfur chemistries. (a) Mechanoresponsive PEG hydrogels with disulfide linkages can be functionalized through applied force. (i) Schematic illustrates force induced cleavage of disulfide crosslinks followed by Michael-type addition of an acceptor molecule. (ii)

Mechanical testing shows stress–strain failure for disulfide crosslinks at various compression speeds. (iii)

MSCs seeded on hydrogel-protein substrates with or without compression illustrating force dependent functionalization of hydrogels with adhesion proteins. Fig. 2.9a adapted from Lee et al. [234] copyright

2016 Royal Society of Chemistry. (b) Dynamic thioester crosslinks form wound sealants which rapidly dissolve by thioester exchange when exposed to small molecule thiols. (i) Photographs show thioester hydrogels (green) adhered to human skin under torsion. (ii) Exposure to thiolate solutions causes exponential decay of thioester hydrogel moduli. (iii) Visualization of hydrogel sealant dissolution by thioester exchange in a cytocompatible solution of L‐cysteine methyl ester. Fig. 2.9b adapted from Ghobril et al. [150] copyright 2013 Wiley. (c) Thioester exchange facilitates spreading, proliferation and migration of hMSCs in 3D scaffolds. (i) Chemical schematic shows thioester exchange reaction. (ii) hMSCs in viscoelastic thioester hydrogels proliferate significantly compared to static controls. (iii) Thioester-based hydrogels stress relax faster with excess thiol. (iv) Confocal fluorescence microscopy illustrates morphological differences between hMSCs in static non-thioester controls and dynamic excess thiol thioester hydrogels. Scale bars represent 100 μm Fig. 2.9c adapted from Brown et al. [92] copyright 2018

Elsevier. (d) Photo-induced exchange of allyl sulfide bonds enables the formation of intestinal organoid structures in 3D. (i) Chemical schematic shows light mediated exchange of an allyl sulfide crosslink with a free thiol to dynamically reduce hydrogel moduli. (ii) Intestinal organoid crypt structures are measured by distance from the colony body to the tip of the protrusion. (iii) Crypt length can be controlled by varying the extent of matrix softening by allyl sulfide exchange. (iv) Immunostaining verifies the presence of differentiated cell types commonly found in native intestine after allyl sulfide exchange mediated crypt formation (green: E‐cadherin, blue: DAPI, and red: Chromogranin A). Scale bar represents 100 μm. Fig.

2.9d adapted from Hushka et al. [161] copyright 2020 Wiley.

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2.7. Summary and Outlook

Research into controlling the properties and chemistry of biomaterials has rapidly expanded over the last few decades, advancing the understanding of cell-material interactions and outside-in signaling.

The field has shifted from identifying materials with pre-engineered properties to serve as tissue replacements to considering dynamic materials whose temporally evolving properties are capable of directing cell behavior [243]. As the chemistry and structure of biomaterial scaffolds become increasingly advanced [244], synthetic hydrogels are often used to simulate biophysical cues of native tissues [245].

These soft material networks allow one to control how cells interact with their extracellular environment

(Fig. 2.10a), and a growing body of evidence shows that cells respond to time-dependent viscoelastic properties [246]. Indeed, recent discoveries have shown that the behavior of cells in elastic and viscoelastic networks can vary in unintuitive ways. For example, both higher elastic moduli (i.e., more solid-like properties) [247] and viscous stress relaxation (i.e., more liquid-like behavior) [32] can promote osteogenic differentiation of MSCs. By further studying how mechanical stimuli influence cell behavior, researchers will be able to advance the design of cell-based biomedical treatments.

To this end, a diverse array of dynamic covalent crosslinks (Fig. 2.6) have been introduced into polymer networks [248]. The resulting covalent adaptable networks exhibit a wide range of viscoelastic properties that relax over various timescales (Fig. 2.10b) and are useful for a variety of cell and tissue engineering applications. User-defined control over dissipative material properties has been combined with real-time cell tracking and 3D visualization of cell-material interactions in vitro [92]. Studies to date have demonstrated differences in integrin clustering [198], cellar morphology [27], mechanotransduction [131], matrix remodeling [100], and infiltration [139] as a result of viscoelastic material properties. Dynamic covalent hydrogels provide benefits for a host of biomedical applications, including minimally invasive injectable cell delivery systems [127,210], wound healing matrices [150], scaffolds for tissue regeneration

[140,187], bioinks for 3D printing [238], and platforms for organoid culture [161,163].

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Further advances in dynamic covalent material chemistries are required to broaden the application of these biomaterials for personalized medicine. Personalized biomaterials could be tailored to differences in tissue matrix properties that result from patient age, sex, and disease progression [249]. Studying viscoelastic timescales of native tissues can help to inform the design of viscoelastic scaffolds by providing reference points and relative trends for viscoelastic mechanobiology. However, it is worth noting that tuning viscoelastic properties to control cell behavior in vitro may not simply require matching the biomechanical properties of native tissues. For example, matching the stiffness of a given tissue does not guarantee optimal regeneration in vitro, especially for stiff tissues such as bone and cartilage where highly crosslinked materials can limit cellular activity and matrix production [58]. This should not detract from important findings such as the fact that greater substrate moduli are beneficial for maintaining osteogenic phenotypes

[250]. Rather, it emphasizes the intricate nature of the extracellular microenvironment and the need for optimization of complex and even potentially contradictory biophysical cues. Future research should focus on understanding how the time-dependent material properties of tissues evolve during development and disease progression (Fig. 2.3d), specifically with respect to local cell function. These characteristics would help identify critical timescales for how material properties influence intracellular signaling and further guide the design of new dynamic covalent polymers. Inspiration may be drawn from decellularized matrices and how their composition and structure might provide guidance in material designs to achieve tissue- specific behaviors and benefits [102].

While many synthetic biomaterials are highly tunable, several of their properties are coupled and not independently controlled. For example, swelling, mechanics, degradation, and rearrangement of crosslinks in adaptable materials are highly interdependent. Further, each of these interrelated material properties ultimately affect cell behavior [251]. To address aspects of this issue, fabrication methods are integrating dual or double network chemistries and developing theoretical models to better predict how network structure influences final material properties. Future research directions could focus on isolating complex multimodal time-dependent behavior in hydrogels with heterogeneous dynamic covalent

71 crosslinks. One might then optimize and tune formulations to achieve multiple material properties, such as final moduli, viscoelasticity, and degradation profiles. This would enable customizable smart-materials with precisely tuned behavior for multiple types of cells [252]. One challenge in this field may involve standardizing methods to characterize the properties of viscoelastic biomaterials, especially in the presence of cells and in a local manner. In biomaterial applications, cells and tissue can introduce local forces, spatially varied degradation, and heterogeneous tissue deposition. Further, cells can influence network dynamics and interact with materials very differently in two dimensions versus three dimensions [253].

Notably, methods used to quantify the mechanical properties of soft materials can vary significantly and standardized methods would allow for better comparison and commercialization of these materials.

Perhaps, methods to study the kinetics of small molecules used as network crosslinks will also provide further insights into viscoelastic material reorganization rates [254], especially across multiple classes of reversible chemistries.

As the field of dynamic covalent hydrogels and their implementation as biomaterials continues to mature, a host of impactful applications are on the horizon. These improvements may take many forms, such as culturing cells on scaffolds with biophysical cues to reduce reliance on costly soluble growth factors

[255] or using tissue-mimetic substrates to rescue the regenerative properties of stem cells during expansion

[256]. In particular, synthetic viscoelastic tissue mimics are interesting candidates for 3D printed scaffolds and are beginning to find application for additive manufacturing of tissue engineering materials [257–259].

One could imagine several different dynamic covalent “inks” which would allow multiscale features of organs to be printed with different moduli and varied viscoelastic properties. Several recent studies have shown promising preliminary results by 3D printing dynamic dual network hydrogels [220,238,260]. Other emerging applications include organ-on-a-chip technologies [261] and organoid cultures [262]. Here, viscoelastic materials based on dynamic covalent chemistries provide ECM mimics that afford more reproducible cultures, which are useful for drug screening applications.

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Knowledge of dynamic covalent polymers has grown drastically since the 1940’s when Tobolsky et al. published work illustrating how chemical reactions can induce polymer viscoelasticity [263,264].

New understandings of molecular reactivity and mechanistic principles illustrate the rapid development and diverse applications of covalent adaptable networks [265]. Despite the fast pace of research, the application of dynamic covalent polymers in the biomaterials community is relatively new, and numerous opportunities abound for designing novel systems that can mimic the dynamic properties of tissues for biomedical applications [266].

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Figure 2.10 Dynamic covalent chemistries to crosslink polymers for mimicking the viscoelasticity of native tissues. (a) Schematic summarizing how chemical kinetics and equilibrium reactions influence the rheological properties of the resulting hydrogels as well as the behavior of encapsulated cells. (b) Relative timeline for dynamic covalent chemistries, comparing bond reorganization timescales to illustrate relative rates of crosslink adaptation corresponding to more viscous or more elastic material behavior.

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Chapter 3 - Objectives

3. Overview

Heathy articular cartilage is crucial for enabling pain-free mobility [1]; however, articular cartilage is often damaged by traumatic injuries or wear-and-tear with age [2]. Lack of vasculature and the low regenerative activity of resident chondrocytes limit the repair of cartilage relative to other types of tissues

[3]. Continued degeneration can lead to osteoarthritis, often causing pain [4]. Osteoarthritis affects over 30 million people in the United States [5].

Cartilage tissue engineering has emerged as a promising strategy for treating osteoarthritis in load- bearing joints [6]. Methods typically rely on delivering combinations of cells, polymer matrices, and/or promotive cues to regenerate damaged cartilage [3]. As one example, matrix-assisted autologous chondrocyte transplantation (MACT) is a clinically relevant cartilage tissue engineering procedure that relies on the delivery of patient-derived cells embedded in biomaterial scaffolds [7]. Scaffolds used for

MACT must be able to withstand biomechanical forces in articulating, load-bearing joints [8], and hydrogels are often employed. To impart structural integrity and improve mechanical properties, many of the hydrogels used for cartilage tissue engineering are covalently crosslinked [9]. However, densely crosslinked hydrogels can also impede the ability of chondrocytes to remodel their local microenvironment

[10] and deposit a collagen-rich extracellular matrix (ECM) [11]. In addition, most covalent crosslinked hydrogels exhibit linear elastic responses to mechanical deformation [12], but native cartilage tissue has time-dependent viscoelastic properties [13]. As a result, there has been a growing interest in dynamic covalent chemistries [14] and covalent adaptable networks [15] for tissue engineering applications, as these materials have a wide range of non-linear mechanical properties that match those of many soft tissues [16].

This thesis focuses on dynamic hydrazone crosslinked networks that are suitable for forming hydrogels in aqueous environments under physiological conditions [17]. Small molecule kinetic

98 experiments have verified that chemical equilibria between the forward and reverse reactions are the primary mechanism driving viscoelastic rearrangement of covalent crosslinks in hydrazone hydrogels [18].

Further, recent work from our group established the application of hydrazone crosslinked poly(ethylene glycol) (PEG) hydrogels as cytocompatible platforms for studying viscoelastic mechanobiology of myoblasts (C2C12s) [19] and embryonic stem cell-derived motor neurons (ESMNs) [20]. Building on these studies, this thesis now aims to elucidate the mechanobiological effects of hydrazone CANs and their viscoelastic properties on chondrocyte behavior (e.g., phenotype, proliferation, matrix deposition) for cartilage tissue engineering. The global objective is to inform the design of polymer matrices for matrix- assisted autologous chondrocyte transplantation (MACT) that could improve the treatment of osteoarthritis in load-bearing joints.

3.1. The specific aims of this thesis

1. Investigate how stress relaxation of hydrazone CANs influences ECM deposition and proliferation

of encapsulated chondrocytes

2. Understand how viscoelastic creep rates of hydrazone CANs alter chondrocyte morphology over

time during mechanical deformation

3. Evaluate the mechanobiological interactions between dynamic compression and viscoelasticity on

chondrocytes encapsulated in hydrazone CANs

Aim 1 focuses on engineering hydrazone poly(ethylene glycol) hydrogels with tunable viscoelasticity and stress relaxation, and correlating these properties to chondrocyte ECM deposition (Chapter 4). Freshly isolated porcine chondrocytes are encapsulated in hydrogels designed to have relaxation times that vary from hours to weeks by changing the molar percentages of alkyl-hydrazone and benzyl-hydrazone crosslinks in the network. Chondrocyte proliferation and secretory properties are measured as a function of the network adaptability by quantifying the amount of DNA, sulfated glycosaminoglycans (sGAGs), and collagen in the chondrocyte-laden hydrazone CANs over the course of 4 weeks. The spatial distribution of deposited ECM molecules is further visualized by histological and immunohistochemical staining

99

(aggrecan, collagen I, II, and X) to assess the development of neocartilaginous tissue. Then, by studying differences in the hydrazone linker equilibria and hydrogel swelling equilibria, we sought to investigate the influence of average relaxation times on regenerative outcomes. In general, the extracellular matrix deposition show biphasic trends as a function of the average relaxation time. Ultimately, these experiments are designed to interrogate the role of adaptable alkyl-hydrazone crosslinks on overall cellularity and matrix deposition, but a percolating network of more stable benzyl-hydrazone bonds is required to maintain scaffold integrity with time and form the highest quality neocartilaginous tissue.

Beyond studying their secretory properties, deformation of articular chondrocytes and their surrounding matrix occurs in vivo. The resulting morphological changes are thought to influence multiple mechanotransduction pathways related to osteoarthritis in load-bearing joints. Using our materials design considerations (Aim 2), we next formulated alkyl-hydrazone and benzyl-hydrazone hydrogels with different viscoelastic creep compliance to study how chondrocyte morphology might be influenced by mechanical deformation in hydrazone CANs (Chapter 5). Real time confocal microscopy is used to track morphology of encapsulated chondrocytes during the application of a physiologically relevant strain.

Beyond measuring changes in cell shape with time, pericellular matrix deposition (histology), proliferation

(imaging), and gene expression (qt-PCR) are also investigated. We sought to determine if chondrocytes are able to exert forces on their surrounding matrix over time, specifically hydrazone CANS, and if dissipative phenomena (i.e., creep compliance, stress relaxation) would allow chondrocytes to adapt their morphology and corresponding properties. In particular, we posited that viscoelasticity might lead to differences in the pericellular distribution of ECM molecules, such as sGAGs, and differentially alter mechanosensing by chondrocytes. We further studied the influence of viscoelastic creep on pericellular matrix deposition, proliferation, and articular cartilage specific gene expression.

Articular chondrocytes experience dynamic compression in vivo, which has motivated the design of bioreactors that allow for the application of cyclic compressive strain to elucidate the specific influence of loading on chondrocytes and cartilage tissue regeneration. These experimental systems can prove especially

100 beneficial when evaluating various scaffolds for MACT and the influence of the scaffold properties on chondrocyte behavior during mechanical compression. Experiments in Aim 3 are designed to investigate these mechanobiological interactions, between viscoelasticity and mechanical compression in hydrazone

CANs (Chapter 6). First, we leveraged key findings from Aims 1 and 2 to identify experimental conditions suitable for studying chondrocyte-laden hydrazone CANs during long-term culture in dynamic compression bioreactors. Once identified, small amplitude oscillatory shear (SAOS) rheometry is used to quantify the viscoelastic properties of the selected CANS. For these same material systems, changes in chondrocyte gene expression are measured as a function of the viscoelastic properties. Biosynthesis rates of cartilage specific ECM molecules, sGAG and type II collagen. Both biochemical assays are used for quantitation and histological staining to visualize the spatial distribution of the ECM. We aim to understand the role of viscoelasticity and mechanical compression on chondrocyte gene expression and rates of extracellular matrix deposition.. Collectively, these experiments should help identify specific dynamic hydrazone CAN formulations that could prove beneficial as scaffolds to promote cartilage matrix deposition and address current limitations in MACT for treating osteoarthritis in load-bearing joints. Finally, these results should deepen the understanding of mechanobiological factors that influence chondrocyte matrix signaling and ultimately, cartilage tissue engineering.

Chapter 7 summarizes the key findings and conclusions, while also recommending future research directions in hydrazone (and other) CANs to advance the fundamental understanding of cell-matrix mechanosignaling and their application as scaffolds for MACT to treat osteoarthritis in load-bearing joints.

3.2. References

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[2] Roughley PJ. Articular cartilage and changes in arthritis noncollagenous proteins and proteoglycans in the extracellular matrix of cartilage. Arthritis Res 2001;3:342–7. https://doi.org/10.1186/ar326.

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[3] Hunziker EB. Articular cartilage repair: basic science and clinical progress. A review of the current status and prospects. Osteoarthr Cartil 2001;10:432–63. https://doi.org/10.1053/joca.2002.0801.

[4] Altman R, Asch E, Bloch D, Bole G, Borenstein D, Brandt K, et al. Development of criteria for the classification and reporting of osteoarthritis: Classification of osteoarthritis of the knee. Arthritis Rheum 1986. https://doi.org/10.1002/art.1780290816.

[5] Cisternas MG, Murphy L, Sacks JJ, Solomon DH, Pasta DJ, Helmick CG. Alternative Methods for Defining Osteoarthritis and the Impact on Estimating Prevalence in a US Population-Based Survey. vol. 68. NIH Public Access; 2016. https://doi.org/10.1002/acr.22721.

[6] Kon E, Verdonk P, Condello V, Delcogliano M, Dhollander A, Filardo G, et al. Matrix-assisted autologous chondrocyte transplantation for the repair of cartilage defects of the knee: systematic clinical data review and study quality analysis. Bone Joint Res 2009;37:1565–665. https://doi.org/10.1177/0363546509351649.

[7] Kon E, Filardo G, Di Matteo B, Perdisa F, Marcacci M. Matrix assisted autologous chondrocyte transplantation for cartilage treatment: A systematic review. Bone Joint Res 2013;2:18–25. https://doi.org/10.1302/2046-3758.22.2000092.

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[10] Nicodemus GD, Skaalure SC, Bryant SJ. Gel structure has an impact on pericellular and extracellular matrix deposition, which subsequently alters metabolic activities in chondrocyte-laden PEG hydrogels. Acta Biomater 2011;7:492–504. https://doi.org/10.1016/J.ACTBIO.2010.08.021.

[11] Bryant SJ, Anseth KS. Hydrogel properties influence ECM production by chondrocytes photoencapsulated in poly(ethylene glycol) hydrogels. J Biomed Mater Res 2002;59:63–72. https://doi.org/10.1002/jbm.1217.

[12] Roberts JJ, Earnshaw A, Ferguson VL, Bryant SJ. Comparative study of the viscoelastic mechanical behavior of agarose and poly(ethylene glycol) hydrogels. J Biomed Mater Res Part B Appl Biomater 2011;99B:158–69. https://doi.org/10.1002/jbm.b.31883.

[13] Spirt AA, Mak AF, Wassell RP. Nonlinear viscoelastic properties of articular cartilage in shear. J Orthop Res 1989;7:43–9. https://doi.org/10.1002/jor.1100070107.

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[14] Rowan SJ, Cantrill SJ, Cousins GRL, Sanders JKM, Stoddart JF. Dynamic covalent chemistry. Angew Chem Int Ed Engl 2002;41:898–952. https://doi.org/10.1002/1521- 3773(20020315)41:6<898::AID-ANIE898>3.0.CO;2-E.

[15] Mcbride MK, Worrell BT, Brown T, Cox LM, Sowan N, Wang C, et al. Enabling Applications of Covalent Adaptable Networks. Annu Rev Chem Biomol Eng 2019;10:175–98. https://doi.org/10.1146/annurev-chembioeng.

[16] Rosales AM, Anseth KS. The design of reversible hydrogels to capture extracellular matrix dynamics. Nat Publ Gr 2016;1:1–16. https://doi.org/10.1038/natrevmats.2015.12.

[17] Kölmel DK, Kool ET, Kö DK, Kool ET, Kölmel DK, Kool ET. Oximes and Hydrazones in Bioconjugation: Mechanism and Catalysis. Chem Rev 2017;117:10358–76. https://doi.org/10.1021/acs.chemrev.7b00090.

[18] McKinnon DD, Domaille DW, Cha JN, Anseth KS. Bis-Aliphatic Hydrazone-Linked Hydrogels Form Most Rapidly at Physiological pH: Identifying the Origin of Hydrogel Properties with Small Molecule Kinetic Studies. Chem Mater 2014;26:2382–7. https://doi.org/10.1021/cm5007789.

[19] McKinnon DD, Domaille DW, Cha JN, Anseth KS. Biophysically defined and cytocompatible covalently adaptable networks as viscoelastic 3d cell culture systems. Adv Mater 2014;26:865–72. https://doi.org/10.1002/adma.201303680.

[20] McKinnon DD, Domaille DW, Brown TE, Kyburz KA, Kiyotake E, Cha JN, et al. Measuring cellular forces using bis-aliphatic hydrazone crosslinked stress-relaxing hydrogels. Soft Matter 2014;10:9230–6. https://doi.org/10.1039/c4sm01365d.

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Chapter 4 - Aim 1

4. Hydrazone covalent adaptable networks modulate extracellular matrix deposition for cartilage tissue engineering

As appearing in Acta Biomaterialia 2019

4.1. Abstract

Cartilage tissue engineering strategies often rely on hydrogels with fixed covalent crosslinks for chondrocyte encapsulation, yet the resulting material properties are largely elastic and can impede matrix deposition. To address this limitation, hydrazone crosslinked poly(ethylene glycol) hydrogels were formulated to achieve tunable viscoelastic properties and to study how chondrocyte proliferation and matrix deposition vary with the time-dependent material properties of covalent adaptable networks. Hydrazone equilibrium differences were leveraged to produce average stress relaxation times from hours (4.01 × 103 s) to months (2.78 × 106 s) by varying the percentage of alkyl-hydrazone (aHz) and benzyl-hydrazone (bHz) crosslinks. Swelling behavior and degradation associated with adaptability were characterized to quantify temporal network changes that can influence the behavior of encapsulated chondrocytes. After four weeks, mass swelling ratios varied from 36 ± 3 to 17 ± 0.4 and polymer retention ranged from 46 ± 4% to 92 ± 5%, with higher aHz content leading to loss of network connectivity with time. Hydrogels were formulated near the Flory-Stockmayer bHz percolation threshold (17% bHz) to investigate chondrocyte response to distinct levels of covalent architecture adaptability. Four weeks post-encapsulation, formulations with average relaxation times of 3 days (2.6 × 105s) revealed increased cellularity and an interconnected articular cartilage-specific matrix. Chondrocytes embedded in this adaptable formulation (78% aHz) deposited

190 ± 30% more collagen and 140 ± 20% more sulfated glycosaminoglycans compared to the 0% aHz control, which constrained matrix deposition to pericellular space. Collectively, these findings indicate that incorporating highly adaptable aHz crosslinks enhanced regenerative outcomes. However, connected

104 networks containing more stable bHz bonds were required to achieve the highest quality neocartilaginous tissue.

Figure 4.1 Graphical abstract showing an artistic rendition of chondrocytes encapsulated in hydrazone covalent adaptable networks. Stable benzyl-hydrazone crosslinks are represented by solid lines and dynamic alkyl-hydrazone crosslinks are represented by viscoelastic Maxwell elements.

4.2. Introduction

Millions of patients suffer debilitating pain from osteoarthritis caused by damage to articular cartilage in load-bearing joints [1]. Osteoarthritic degeneration of articular cartilage is exacerbated by poor innate healing capabilities, stemming from lack of vasculature and the low regenerative activity of resident chondrocytes [2]. Matrix-assisted autologous chondrocyte transplantation (MACT) has emerged as a promising tissue engineering strategy to enhance the ability of chondrocytes to repair critically sized cartilage defects [3]. This strategy often employs water-swollen polymer networks (hydrogels) as delivery vehicles to support chondrocytes and permit extracellular matrix (ECM) deposition [4]. Hydrogels used for cartilage tissue engineering are frequently covalently crosslinked to withstand compressive forces experienced in articulating joints, but this also renders them largely elastic in their response to mechanical forces. Densely crosslinked hydrogels and fixed elastic crosslinks have been linked to low rates of

105 chondrocyte proliferation, as well as ECM deposition restricted to pericellular space [5]. This could help explain why MACT remains an ancillary clinical treatment for osteoarthritis and why robust articular cartilage regeneration remains elusive [6,7].

To improve regenerative outcomes of MACT strategies, scaffolds used for articular cartilage regeneration can be designed to incorporate viscoelastic mechanical characteristics, making them more similar to native cartilage than fixed elastic hydrogels [8]. Biomechanical analysis of freshly isolated cartilage reveals viscoelastic behavior, such as stress relaxation and creep. However, few covalent hydrogels used as chondrocyte scaffolds exhibit stress relaxation and creep in response to mechanical deformation [9,10]. Moreover, the effects of viscous dissipation (e.g., stress relaxation) on cartilage regeneration remain largely understudied compared to the relationship between elastic stiffness and chondrocyte behavior (e.g., differentiation, proliferation, and matrix deposition) [11–13].

Most hydrogels that exhibit both viscous and elastic behavior (i.e., viscoelasticity) have relied on the physical or ionic association of naturally derived polymers, such as collagen, hyaluronic acid or alginate

[14]. The current study was motivated, in part, by seminal work using ionically crosslinked calcium-alginate hydrogels to investigate the effects of stress relaxation on cell behavior. Faster stress relaxation was shown to influence morphology, proliferation, differentiation, and secretory properties of mesenchymal stem cells

(MSCs) [15–17]. More recently, Lee et al. demonstrated increased ECM deposition by chondrocytes when stress relaxation times of calcium-alginate hydrogels were tuned from 2 hours to 1 minute [18]. While calcium-alginate hydrogels provide many benefits as biomaterial scaffolds, divalent metal ion crosslinking strategies (e.g., calcium-alginate crosslinks) can be disrupted by monovalent cation exchange in physiological environments, possibly limiting in vivo application within articulating joints [19].

Biologically derived hydrogels (e.g., collagen, hyaluronic acid, matrigel, and calcium-alginate) can also suffer batch-to-batch variability and present biochemical cues, confounding the effects of viscoelastic mechanical properties on chondrocyte secretory properties and tissue regeneration [20–23].

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Synthetic networks crosslinked with covalent adaptable bonds offer a complementary approach for cartilage tissue engineering and provide specific benefits. Ultimately, association interactions result in moduli that are much lower than those of equivalent networks that are covalently crosslinked [24]. In addition, covalent adaptable networks (CANs) are able to reorganize network connectivity to relieve local stresses, such as those caused by cell proliferation and the secretion of matrix molecules [25]. Despite these advantages, CANs have only recently begun to be explored as scaffolds for cell encapsulation and tissue engineering.[26,27] Prior research from our group has demonstrated that hydrazone CANs are able to be used for encapsulation of primary cells, due to mild formation conditions without catalyst [28,29].

Hydrazone bonds (R-HC=NH-NH-R) are formed by nucleophilic attack on a carbonyl electrophile followed by condensation (Fig. 4.2a) [30]. Hydrazone bonds (Hz) are susceptible to hydrolysis under physiologically relevant conditions (pH and temperature), regenerating the original nucleophile (Nu) and electrophile (El)

- and rendering the process reversible ([El]+[Nu]⇌[Hz]) [31]. Chemical equilibria (Keq=k1/k1=[Hz][Nu]

1[El]-1) of hydrazone bonds govern network reorganization. This effect has been illustrated by small molecule kinetic studies that demonstrate close agreement between forward (k1) and reverse (k-1) rate constants and the mechanical properties of PEG CANs [32].

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Figure 4.2 Chemistry and hydrogel formulation. (a) Schematic representing chemical structures for the reaction of hydrazine with alkyl, a, and benzyl, b, aldehyde to from alkyl-hydrazone (aHz) and benzyl- hydrazone (bHz) bonds. (b) For an interconnected polymer network of bHz bonds to span the complete volume, the percentage of bHz bonds (pb) must be greater than the percolation threshold (pc) assuming ideal step-growth. 2D slices illustrate network connectivity for each experimental condition used for cell culture

(88, 83, 78 and 0% aHz).

Boehnke and coworkers used similar synthetic PEG hydrogels to culture mouse MSCs, demonstrating controlled degradation from 1 to 7 days by varying the ratio of hydrazone to oxime crosslinks

[33]. Degradable hydrazone hydrogels were also used in a subcutaneous mouse model, showing ectopic

ECM deposition by chondrocytes encapsulated within scaffolds formed by reacting adipic dihydrazide-

108 modified poly(L-glutamic acid) with aldehyde-modified poly(L-glutamic acid) [34]. More recently, hydrazone crosslinked elastin-like protein-hyaluronic acid hydrogels were used to illustrate the biochemical effects of hyaluronic acid, showing upregulation of chondrocyte specific genes with increasing hyaluronic acid concentration [35]. These studies demonstrate the versatile nature of hydrazone crosslinks, but the effects of distinct hydrazone equilibria and the resulting viscoelastic properties have yet to be studied in the context of cartilage tissue engineering.

Herein, we synthesized and characterized a range of hydrogel formulations crosslinked with hydrazone bonds as viscoelastic scaffolds to study the effects of covalent crosslink adaptability on chondrocyte functions for cartilage tissue engineering. Freshly isolated porcine chondrocytes were encapsulated in hydrogels that were designed to have average stress relaxation times varying from hours to months by changing the relative percentage of alkyl-hydrazone (aHz) and benzyl-hydrazone (bHz) crosslinks (Fig. 4.2b). Chondrocyte proliferation and secretory properties were investigated as a function of hydrogel adaptability by monitoring the total collagen content, the sulfated glycosaminoglycan (sGAG) content, and the amount of double stranded DNA (dsDNA) in chondrocyte-laden CANs over the course of

4 weeks. The spatial distribution of deposited ECM molecules was also visualized by histological (sGAGs, total collagen) and immunohistochemical staining (aggrecan, collagen I, II and X) to assess the development of neocartilaginous tissue.

4.3. Materials and methods

4.3.1. Hydrazine and aldehyde macromer synthesis

All chemicals and solvents were analytical grade and acquired from commercial sources unless otherwise described. Alkyl PEG-aldehyde was synthesized by Dess-Martin oxidation of 8-arm PEG-OH

(Mn ~ 20,000 g/mol) as previously described [36]. Briefly, PEG was dissolved with Dess-Martin periodinane (1.5 equiv. w.r.t. -OH groups) in minimal amount of dichloromethane (DCM) containing catalytic H2O. The reaction was allowed to proceed for 3 hours at room temperature (23°C). PEG-hydrazine

109 and PEG-benzaldehyde were synthesized by HATU (1-[Bis(dimethylamino)methylene]-1H-1,2,3- triazolo[4,5-b]pyridinium3-oxidhexafluorophosphate) coupling to 8-arm PEG-NH2 (Mn ~ 20,000 g/mol)

[37]. For each respective synthesis, either tri-boc-hydrazinoacetic acid or 4-formylbenzoic acid (2.2 equiv. w.r.t -NH2 groups) were activated with HATU (2.0 equiv. w.r.t -NH2 groups) and 4-methylmorpholine (5.0 equiv. w.r.t -NH2 groups) in dimethylformamide (DMF) under argon for 10 minutes. In parallel, PEG amine was dissolved in DMF containing 4-methylmorpholine (5.0 equiv. w.r.t -NH2 groups). The two solutions were mixed and the reactions were allowed to proceed overnight under argon at room temperature. Boc(tert- butyloxycarbonyl)-protected PEG-hydrazine was precipitated dropwise in cold (4°C) diethyl (Et2O), then dissolved in a 50:50 mixture of triflouroacetic acid (TFA) and DCM. The deprotection reaction was allowed to proceed in a vented flask for 3 hours prior to purification.

4.3.2. Macromer purification and characterization

Crude reaction mixtures were concentrated under reduced pressure and subsequently precipitated dropwise in cold Et2O. Samples were centrifuged, decanted, and washed 3x with Et2O before drying en vacuo. Dry products were dissolved in deionized H2O and dialyzed in regenerated cellulose membranes

(Spectra/Por) with a molecular weight cut-off of 8,000 g/mol for 48 hours at 4°. Polymers were then

1 lyophilized and stored at -20°C. H NMR spectra (Bruker AV-III, 400 MHz, CDCL3) were used to evaluate functionalization of PEG macromers by integrating the functional or protecting group peaks normalized to

PEG protons. In each case the functionality was found to be ≥ 90%. Boc-PEG-NH-NH2 δ=3.79-3.41 (m,

227H, -O-CH2-CH2-O-), δ=1.57-1.42 (m, 27H, -O-C(CH3)3); PEG-NH-NH2 δ=3.77-3.54 (m, 227H, -O-

CH2-CH2-O-); PEG-Ar-CHO δ=10.34-9.81 (s, H, CHO), δ=8.12-7.83 (m, 4H, -C6H4-), δ=4.09-3.15 (m,

227H, -O-CH2-CH2-O-); PEG-CHO δ=9.81-9.58 (s, H, CHO); δ=4.25-4.08 (s, 2H, -CH2-CHO), δ=3.90-

3.23 (m, 227H, -O-CH2-CH2-O-).

4.3.3. Hydrogel formation and rheological characterization

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Functionalized PEGs were dissolved in phosphate buffered saline (PBS) and neutralized to pH 7.0

(10 w/w%). Hydrogels were formed with 5w/w% final polymer content on stoichiometry. In situ rheology was performed using parallel plates on a temperature-controlled Peltier plate (TA Instruments DH-R3).

Shear rheology was performed at an angular frequency of 1 rad/s, which has been previously shown to be relevant for cell behavior [38]. aHz and bHz hydrogel formation was monitored by time sweep at 1% strain and 25°C. For stress relaxation experiments, a 10% shear strain was applied over a 10-second ramp at 37°C.

Experimental conditions were formulated with aHz/bHz molar percentages of 100, 90, 80, 70, 60, 50, 30 and 0%. The experiment length (12 hours) was dictated by the amount of time for the 100% aHz condition to completely relax the applied stress. Mineral oil was applied to the air-hydrogel interface to prevent evaporation during experimentation. Theoretical models were fit using the curve fit application in

MATLAB reporting 95% confidence intervals on fit parameters.

4.3.4. Acellular swelling and mass loss behavior

Hydrogels (75 μL, 5 w/w%) were prepared off-stoichiometry (r=[El]/[Nu]=0.8) with aHz/bHz molar percentages of 100, 87.5, 75, 50, 25 and 0% with the same initial polymer mass (m0). Hydrogels were swollen in chondrocyte growth media for 28 days. The wet mass (ms) was measured every 7 days and normalized by the mass at the time of formation (mf). After 28 days, hydrogels were frozen in liquid nitrogen (LN2), lyophilized and weighed (md) to calculate the polymer retention (%retention = m0/md x

100%) and equilibrium mass swelling ratios (q=ms/md).

4.3.5. Chondrocyte isolation, encapsulation and cell culture

Primary chondrocytes were isolated from femoral condyles and the patellar groove of Yorkshire swine stifle joints (n=6) as detailed previously [39]. Freshly isolated porcine chondrocytes were encapsulated within 40 μL hydrazone hydrogels formed in 1 mL syringe barrels at ~50 million cells/mL, as this density has been shown to produce high quality neotissue for in vitro encapsulation studies [40]. For chondrocyte encapsulation, three covalent adaptable formulations (88, 83, and 78 mol% aHz, 5 w/w%)

111 were selected and compared to a primarily elastic and slow-relaxing 0% aHz control. Hydrogels were formulated off-stoichiometry (r = [El]/[Nu] = 0.8, 5 w/w%) to minimize potential cytotoxicity from pendant aldehyde groups. Cell viability was assessed by Live/Dead assay (Invitrogen) immediately after encapsulation to verify that the encapsulation process was cytocompatible (Fig. 4.3). Chondrocyte-hydrogel constructs were cultured in chondrocyte growth medium composed of high-glucose DMEM (Gibco) containing 10% fetal bovine serum (Gibco), 1% penicillin-streptomycin and fungizone (Gibco, Invitrogen),

50 mg/mL L-ascorbate-2-phosphate (Sigma-Aldrich), 40 mg/mL L-proline (Sigma-Aldrich), 100 mg/mL non-essential amino acids (Gibco), 100 mg/mL HEPES buffer (Sigma-Aldrich) and 50 mg/mL gentamicin

(Invitrogen). Medium was changed every other day, and cell-hydrogel constructs were maintained with 5%

CO2 at 37°C.

Figure 4.3 Cell viability post-encapsulation quantified by Live/Dead cytotoxicity assay using FIJI (ImageJ) with representative images taken on a confocal microscope. Chondrocyte viability was found to be approximately 80% in all three hydrazone hydrogel conditions used for cell culture experiments (88, 83, 75 and 0% aHz). For each condition 5 images were analyzed from two gels (n=2). Scale bars represent 50 µm.

4.3.6. Biochemical analysis of cell-laden hydrazone CANs

Cell-laden hydrogels (n=4) were removed from culture conditions 1, 7, 14, 21 and 28 days post- encapsulation, snap frozen in LN2 and stored at -70°C prior to analysis. Samples were then lyophilized before being added to digestion buffer composed of 125 μg/mL papain (Worthington Biochemical) and 10

112 mM cysteine (Sigma Aldrich). Samples were homogenized for 10 minutes with 5-mm steel beads shaking at 30 Hz (Qiagen TissueLyser). Digestion was allowed to proceed overnight at 60°C. Samples from each digest solution were hydrolyzed with an equal volume of 12 M HCl for 3 hours at 120°C. Total collagen content was analyzed by a hydroxyproline assay, where hydroxyproline was assumed to make up 13.4% of the amino acid content of collagen [41,42]. Remaining digest solutions were centrifuged and the supernatant was used for a DMMB assay, with results reported as chondroitin sulfate (ChS) equivalents. Supernatant was also used to quantify cell number using dsDNA from a PicoGreen assay (Life Technologies) assuming each chondrocyte accounts for 7.7 pg of dsDNA [43].

4.3.7. Histological sectioning, staining and immunofluorescence

On day 28, constructs were fixed for 1 hour at room temperature in 4% paraformaldehyde.

Hydrogels were rinsed with DPBS and then soaked in a 30% sucrose solution overnight at 4°C. Hydrogels were transferred to molds, embedded in optimal cutting temperature (OCT) compound and slowly frozen to -70°C overnight. Slides were prepared with 30-μm sections cut with a Leica Cryostat CM1850. Sections were stained with Safranin-O and Masson's Trichrome using a Leica Autostainer-XL. Cover slides were applied with Permount (Fisher) and slides were imaged by bright field microscopy with a Nikon TE-2000 inverted microscope. For immunofluorescence staining, cell-hydrogel samples were harvested on day 28 and fixed in 10% formalin for 1 hour at room temperature. Hydrogels were frozen and cryosectioned as described above. Frozen sections were stored at -70°C. Antigen retrieval was performed on thawed slides with Retrievagen (BD Biosciences). For collagen II and aggrecan immunostaining, samples were treated with C-ABC (100 mU/mL, Sigma) and keratanase (50 mU/mL, Sigma) for 1 hour at 37°C followed by hyaluronidase (2000 U/mL, Sigma) pretreatment under the same conditions. For collagen I and collagen X staining, samples were pretreated with pepsin (1 mg/mL, ~ 4000 U, pH 2.0, Sigma) for 1 hour at 37°C.

Samples were permeabilized with 0.25 w/w% TritonX-100 and then blocked with 1 w/w% bovine serum albumin (BSA) for 1 hour at room temperature. Samples were then incubated with rabbit polyclonal antibodies for collagen type II or collagen X (1:200, Abcam) as well as mouse monoclonal antibodies for

113 aggrecan or collagen I (1:200, Abcam) in 1% BSA overnight at 4°C. Samples were incubated with secondary antibodies, AlexaFluor-555 donkey-anti-mouse and AlexaFluor-647 goat-anti-rabbit (1:200,

Abcam), in 1% BSA for 12 hours in a dark humidified chamber at 4°C. Samples were counterstained with

DAPI for 30 minutes at room temperature in the dark. Coverslips were mounted onto slides with

Fluoromount (Sigma) and sealed with nail polish. Stained samples were stored in the dark at 4°C until imaging. All samples were processed at the same time to minimize sample-to-sample variation. Images were taken on a Zeiss LSM710 scanning confocal microscope using identical acquisition settings and post- processing for all samples.

4.3.8. Statistical analysis

Unless otherwise noted, graphical representations and error bars represent the mean ± standard deviations. Individual differences between sample means were analyzed by unpaired two-tailed t-tests with

Welch's correction. Standard thresholds for significance were used throughout (e.g., P < 0.05 = *, P < 0.01

= **, P < 0.001 = ***, P < 0.0001 = ****). Comparisons of three or more independent groups were analyzed by ordinary 1-way or 2-way ANOVA with Dunnett’s or Sidak’s multiple comparison tests. Statistical analyses were performed with GraphPad Prism 6 software.

4.4. Results

4.4.1. Hydrogel formation and shear moduli

To create hydrazone CANs with varied adaptability, three distinct 8-arm PEG macromers (Mn ~

20,000 g/mol) were synthesized with complementary reactive groups. Hydrazone hydrogels were formed by reacting nucleophilic PEG-hydrazine with two different electrophilic PEG-aldehydes (alkyl and benzyl).

Hydrazone hydrogels were compared by monitoring step-growth polymerization at the same macromer concentrations (Fig. 4.4a). Non-significant differences between storage moduli (G’) shown in Fig. 4.4b resulted in similar complex shear moduli (G*aHz = 20.3 ± 0.3 kPa vs. G*bHz = 20.4 ± 0.1 kPa). In contrast, the final loss moduli (G’’) were significantly different, resulting in differences between loss tangents

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(Tan(δ)) depicted in Fig. 4.4c. These findings indicate that aHz and bHz equilibria can be leveraged to crosslink hydrogels resulting in viscoelastic differences, without requiring differences in polymer content or elastic stiffness.

4.4.2. Two-element stretched exponential to model stress relaxation

To more thoroughly investigate the viscoelastic differences between aHz and bHz hydrogels, we performed stress relaxation experiments by shear rheology (Fig. 4.4d). The composition was graduated from 100% aHz crosslinks (i.e. 100% bHz crosslinks) to 0% aHz crosslinks in order to investigate intermediate levels of covalent adaptability. This resulted in precise incremental control over the stress relaxation characteristics of hydrazone hydrogels. Normalized stress relaxation data was fit with a two- element Kohlrausch-Williams-Watts function (Eq. 4.1).

Equation 4.1

σ t βa t βb = Xa exp (‐ ( ) ) + Xb exp (‐ ( ) ) Eq. 4.1 σ0 τa τb

In is equation, the two elements are stretched exponential terms where the pre-exponential factors represent the mole fractions (X) of either alkyl (a) or benzyl (b) hydrazone crosslinks. Similarly, the relaxation time constants (τ) are characteristic of the reorganization of each type of covalent bond, with stretching parameters (β) to account for heterogeneity in relaxation behavior. The model fit parameters with

95% confidence intervals are shown in Fig. 4.4e and Fig. 4.4f showing time constants and stretching parameters, respectively. The bHz relaxation time constants increased drastically with the percentage of bHz crosslinks, unlike the aHz relaxation time constants which remained relatively constant. bHz crosslinks also showed a constant level of highly heterogeneous stress relaxation behavior, likely due to larger contributions from alternative rearrangement mechanisms (e.g., transimination) compared to the aHz crosslinks, which remained dominated by rapid hydrolysis and reformation [44]. We next derived the equation for average relaxation time (<τ>) by integrating the model over its entire domain (t=0 to t=∞) (Eq.

4.2).

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Equation 4.2

X τ 1 X τ 1 〈τ〉 = a a Γ ( ) + b b Γ ( ) Eq. 4.2 βa βa βb βb

Using fit parameters from stress relaxation data, single value outputs were calculated for each hydrogel formulation to illustrate the wide range of accessible viscoelastic properties (Fig. 4.4g). This resulted in hydrazone hydrogel average relaxation times spanning three orders of magnitude (<τ0%> ≈ 4 x

3 6 10 s to <τ100%> ≈ 3 x 10 s) corresponding to a range from roughly one hour to one month.

Figure 4.4 Rheological characterization of hydrazone hydrogels. Hydrazone hydrogels (5w/w%) formed by the stoichiometric reaction of 8-arm 20kD PEG-hydrazine with 8-arm 20kD alkyl or benzyl PEG- aldehyde. (a) Evolution of the shear storage (G’) and loss (G’’) modulus as a function of time during step-

116 growth polymerization. (b) The final storage and loss modulus and (c) loss tangent (Tan(δ)=G’’/G’) for hydrogels with 100% alkyl-hydrazone (aHz) or 100% benzyl-hydrazone (bHz) crosslinks. In (a-c), bars represent mean ± standard deviation. Significance represents results of unpaired two-tailed t-tests (P < 0.05

= *) with Welch's correction. (d) Shear stress (σ/σo) as a function of time with solid lines representing model fits (Eq 1) for hydrazone hydrogels formulated with varied percentages of benzyl-hydrazone crosslinks

(e.g., 30% bHz ⇒ 70% aHz). Fitted values for the (e) relaxation time constants (τa and τb) and (f) stretching parameters (βa and βb) as a function of the hydrazone bond composition. Points represent fitted parameters

± 95% confidence bounds. (g) Average relaxation times (<τ>) calculated (Eq. 4.2) as a function of the percentage of bHz crosslinks in the hydrogel formulations calculated using fit parameters and 95% confidence bounds.

4.4.3. Alkyl and benzyl-hydrazone hydrogel formation and shear moduli

Swelling experiments were performed for the length of the intended cell culture experiments to understand any temporal network changes or mass loss that may be associated with the adaptability of the hydrazone crosslinks. The swollen mass was measured every 7 days (Fig. 4.5a). The two most adaptable hydrazone CANs (100 and 87.5% aHz) demonstrated increased swollen masses at early time points (days

1, 7, and 14). All other conditions (75, 50, 25 and 0% aHz) maintained constant swollen masses for the duration of the experiment. After the final time point, acellular hydrogels were lyophilized and the dry mass was used to calculate polymer retention. The hydrogels composed primarily of aHz crosslinks (100, 85.5, and 75% aHz) showed reduced polymer content when compared with 0% aHz hydrogels (Fig. 4.5b).

Similarly, on day 28, mass swelling ratios were calculated to illustrate changes observed over the course of the experiment (Fig. 4.5c). Again, the conditions with the highest percentages of aHz crosslinks demonstrated significant differences when compared to the 0% aHz hydrogels.

117

Figure 4.5 Swelling and mass loss of acellular hydrogels. (a) Swollen mass (ms/mf) normalized by the mass at the time of formation (mf) for hydrogels with varied percentages of aHz crosslinks over time. (b) The percentage of initial polymer mass retained (%=md/m0x100%) and (c) the mass swelling ratio (q=md/ms) as a function of alkyl-hydrazone content; calculated using the dry mass (md) of constructs at the end of the 28- day experiment and the initial polymer mass of formulated hydrogels (m0). In each case four hydrogels were averaged for each condition (n=4) with significance representing 1-way or 2-way ANOVA or with

Dunnett's multiple comparisons test. Significant differences with respect to the 0% aHz control are depicted with P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****.

4.4.4. Hydrogel formulations based on Flory-Stockmayer theory

Formulations used for chondrocyte cell culture were designed based on Flory-Stockmayer theory

(Eq. 4.3) to create hydrogels with varied adaptability using two hydrazone equilibrium reactions (Fig. 4.2a)

[45].

Equation 4.3

118

1 pc = Eq. 4.3 √r(fNu‐1)(fEl‐1)

The percolation threshold (pc) for step-growth polymerization off-stoichiometry, represents the minimum conversion required for hydrogel formation. Where fNu and fEl are the number of nucleophilic or electrophilic groups on each PEG macromer and r is the stoichiometric ratio (r = [El]/[Nu]). For cell culture, hydrogels were designed with the electrophilic species as the limiting reagent (r ≤ 1). Assuming ideal network formation, the fraction of bHz crosslinks (pb) must be greater than pc for slow-relaxing bHz bonds to span the dimensions of the hydrogel (Fig. 4.2b). For 8-arm macromers 0.17 (17% bHz) is the calculated percolation threshold. We were particularly interested in studying chondrocyte behavior in viscoelastic adaptable networks above and below this threshold to test the effects of distinct levels of adaptability near this critical point. For this reason, 88, 83 and 78% aHz crosslinks, as well as a 0% aHz control, were used for further experiments with chondrocyte-laden hydrogels. These hydrogels are expected to produce

4 4 5 approximate average relaxation times of <τ88%> ≈ 4.7 x 10 s, <τ83%> ≈ 6.3 x 10 s, <τ78%> ≈ 2.6 x 10 s, and

6 <τ0% > ≈ 2.8 x 10 s based on the aforementioned results of rheological stress relaxation experiments.

4.4.5. CANs with intermediate covalent adaptability enhance cellularity

The dsDNA content of hydrazone hydrogels was assayed over the course of 28 days to characterize overall cellularity and proliferation with respect to covalent adaptability (Fig. 4.6). The cellularity of hydrazone hydrogels increased initially in the most adaptable hydrogels (88% aHz), but over time was surpassed by conditions at intermediate levels of covalent adaptability (83 and 78% aHz). The 78% aHz hydrogels demonstrated nearly two-fold increase (1.68 ± 0.19) in the number of chondrocytes between day

1 and day 28. Conversely, chondrocyte populations were reduced in the 0% aHz hydrogels and demonstrated consistently lower cell populations over the time course of the experiment, despite the same initial seeding densities (day 0). These findings imply that dense networks of primarily elastic, fixed bHz crosslinks hinder chondrocyte proliferation and significantly reduce cellularity over extended culture times.

119

However, cellularity can be rescued in hydrazone hydrogels by substituting a significant fraction of the bHz crosslinks with highly adaptable aHz crosslinks. Most interestingly, once the percentage of aHz crosslinks becomes ≥88% the network fails to retain proliferating cells and the cellularity of the resulting neotissue declines.

Figure 4.6 Cellularity and proliferation. Quantification of the number of chondrocytes in hydrazone hydrogels over time as measured by dsDNA levels. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Dunnett's multiple comparisons test. Significant differences with respect to the 0% aHz control are depicted with P < 0.05 = *, P < 0.01 = **, P < 0.001 =

***, P < 0.0001 = ****.

4.4.6. Interconnected sGAG matrix in viscoelastic CANs

Histological sectioning and staining with Safranin O was used to visualize the spatial distribution of sGAGs in hydrazone CANs after 28 days of chondrocyte cell culture. Representative images are shown in Fig. 4.7a, revealing maximal sGAG deposition in CANs formulated just above the percolation threshold for bHz crosslinks (88% aHz). This is illustrated by comparison with the more diffuse, lighter sGAG

120 staining in the 88 and 83% aHz hydrogels. Consistent with prior results using non-adaptable hydrogels, the slow-adapting 0% aHz hydrogels demonstrated sGAG deposition primarily in pericellular space with small dense stain areas observed around chondrocytes. Acellular hydrogels and articular cartilage sections were also stained for comparison, helping to highlight differences in neotissue quality across hydrazone formulations. To complement this qualitative analysis, sGAG secretion as a function of time was quantified by a DMMB assay (Fig. 4.7b). sGAG content increased with time in all four hydrazone hydrogel conditions.

Notably, sGAG deposition by encapsulated chondrocytes in the 78% aHz hydrogels was significantly higher than all other hydrogel formulations at the final time point. In contrast, the most adaptable 88% aHz hydrogels showed reduced sGAG content after 28 days. These findings are consistent with previous work studying degradation in non-adaptable hydrogels, but also suggests that adaptable covalent bonds can be tuned to support matrix deposition without requiring irreversible degradation of crosslinks [46].

Figure 4.7 sGAG content. (a) Brightfield microscopy images showing histological sections of cryosectioned constructs stained with Safranin O to visualize the spatial distribution of sGAGs deposited by chondrocytes after 28 days. sGAGs are represented by the red stained area with nuclei stained

121 violet/black. Hydrazone hydrogels are labeled with the percentage of aHz crosslinks, and articular cartilage and acellular hydrogels are included as positive and negative controls, respectively. Scale bars represent 50

µm. (b) Graphical depiction of the total sGAG content as a function of time from a DMMB assay. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with

Dunnett's multiple comparisons test, showing differences with respect to the 0% aHz hydrogel, P < 0.05 =

*, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** and with respect to the day 1 values, P < 0.05 = +, P

< 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++.

4.4.7. Significantly enhanced collagen deposition in viscoelastic CANs

Masson’s trichrome staining was performed to assess the development of collagen matrix by chondrocytes encapsulated within hydrazone CANs after 28 days (Fig. 4.8a). Chondrocytes formed robust and interconnected collagen networks in the 78% aHz hydrogels with collagen staining that spanned large clusters of cells. This condition most closely resembled native articular cartilage compared to other experimental conditions (88, 83 and 0% aHz). The primarily elastic 0% aHz hydrogels with very slow relaxation times showed only pericellular ECM deposition, with staining isolated to the immediate vicinity of the chondrocytes. The 0% aHz control also demonstrated limited scaffold replacement, maintaining large areas closely resembling acellular hydrogels. Biochemical analysis revealed even larger differences in the collagen content than was observed for sGAGs (Fig. 4.8b). In particular, the 78% aHz hydrogels resulted in significantly more collagen deposition by encapsulated chondrocytes, nearly 1 mg after 28 days, or almost twice as much as the 0% aHz hydrogels.

122

Figure 4.8 Collagen content. (a) Brightfield microscopy images showing histological sections stained with

Masson’s Trichrome to show the spatial distribution of collagen deposited by chondrocytes after 28 days.

Collagen is represented by blue stain area with nuclei stained violet/black. Hydrazone hydrogels are labeled with the percentage of aHz crosslinks, with an articular cartilage positive control and an acellular hydrogel negative control. Scale bars represent 50 µm. (b) The total collagen content as a function of time from a hydroxyproline assay. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Dunnett's multiple comparisons test. Differences with respect to the 0% aHz hydrogel are denoted by P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** and differences with respect to day 1 values are denoted by P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 =

++++.

4.4.8. Average relaxation time and ECM deposition

To more closely examine the relationship between the viscoelastic properties of hydrazone CANs and the secretory properties of encapsulated chondrocytes, the amount of collagen and sGAGs deposited

123 after 28 days was plotted as a function of average relaxation time (Fig. 4.9). This analysis reveals information about the timescales of network adaptation that may be important for chondrocyte processes.

The most significant ECM deposition was observed in the 78% aHz hydrogels, which were formulated with average relaxation times of approximately 3 days (2.6 x 105 s). This observation lends insight for chondrocyte metabolic processes and matrix synthesis rates. For example, relaxation time scales on the order of 12 hours (4.6 x 104 s) were too fast for chondrocytes to effectively generate neotissue, perhaps due to changes in mechanosensing, diffusion and mass loss. On the other hand, relaxation timescales of about

1 month (2.8 x 106 s) were too slow, clearly limiting matrix deposition to pericellular regions and reducing overall cellularity. These differences were further dependent on the size of the matrix molecules, with collagen having a stronger dependence on average relaxation time than sGAGs.

Figure 4.9 ECM deposition as a function of hydrogel average relaxation time. The mass of ECM produced by encapsulated chondrocytes at the final time point (day 28) with respect to the average relaxation time

(<τ>) of hydrazone hydrogels. Four hydrogels were averaged for each condition (n=4) with significance representing 2-way ANOVA with Sidak's multiple comparisons test showing differences with respect to

124 the 0% sHz control, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****, and with respect to the most adaptable 12% bHz condition, P < 0.05 = #, P < 0.01 = ##, P < 0.001 = ###, P < 0.0001 = ####.

4.4.9. Articular cartilage specific ECM deposition

Immunohistochemistry verified that the deposited ECM was articular cartilage-specific. Hydrazone

CANs showed large amounts of collagen II and aggrecans, two primary components of articular cartilage

(Fig. 4.10). The distribution was consistent with results for total collagen and sGAGs, showing more interconnected collagen II and more aggrecan-rich matrix in hydrogels formulated to have intermediate levels of adaptability (83 and 78% aHz). Staining for collagen I revealed some limited fibrocartilaginous character across all hydrazone hydrogel formulations. Similarly, small amounts of hypertrophic collagen X were observed in all hydrazone hydrogels; however, qualitatively both collagen type I and type X were minimal in hydrazone CANs (Fig. 4.10) compared to deep zone cartilage (+C).

125

Figure 4.10 ECM Immunostaining. Immunohistochemical staining of chondrocyte laden-hydrazone hydrogels on day 28 to assess articular cartilage-specific ECM deposition. Images are maximum intensity projections of 30 μm sections imaged with a confocal microscope. Labels represent the percentage of aHz crosslinks, and porcine articular cartilage positive controls (+C). The first two rows show ECM specific to articular cartilage, collagen type II (red) and aggrecan (green). The second two rows show ECM indicative of chondrocyte dedifferentiation and fibrocartilage formation, collagen type X (red) and collagen type I

(green). All images include a DAPI nuclear counterstain (blue) and scale bars represent 100 µm.

4.5. Discussion

Arthritis-attributable medical expenditures and earnings losses in the United States alone were recently estimated to be greater than $300 billion annually [47]. This financial burden falls disproportionately on people who suffer advanced symptomatic osteoarthritis in load-bearing joints. In this work, we investigated the use of hydrazone CANs that are able to provide mechanical strength for MACT in load bearing joints though covalent linkages that are able to break, adapt, and reform, demonstrating viscoelastic properties and allowing improved ECM deposition by encapsulated chondrocytes. The highest performing constructs were identified using Flory-Stockmayer theory to formulate hydrogels above the percolation threshold for slowly adapting bHz crosslinks (17% bHz), while maximizing the percentage of highly adaptable aHz crosslinks. The material properties of the resulting scaffolds were able to maintain cellularity, retain deposited neotissue, and preserve scaffold integrity simultaneously, something that is difficult to achieve with classically degradable hydrogels.

The material properties of hydrazone CANs are dominated by equilibrium kinetics, particularly

aHz -4 -1 bHz differences in reverse reaction rates of aHz and bHz formation (k-1 = (2.8 ± 0.6) x 10 s vs. k-1 = (8.7

± 0.3) x 10-6 s-1) [28]. Kinetic differences in crosslink equilibrium manifested as significant differences in viscoelastic properties. Importantly, hydrogels were formed at the same polymer content (w/w%) and resulted in similar initial storage moduli (G’), allowing differences in covalent adaptability to be studied by tuning the percentage of aHz and bHz crosslinks. For cell encapsulation experiments, we selected

126 formulations maintaining large percentages (≥78%) of fast adapting aHz crosslinks near the Flory-

Stockmayer percolation threshold for slow adapting bHz crosslinks. We hypothesized that this regime

(12%-22% bHz) would be most interesting for cartilage tissue engineering applications. We assumed that a relatively small percentage of bHz crosslinks could maintain the overall structural integrity of the hydrogel, while maximizing crosslink adaptation to facilitate cellular activity and the distribution of cell- secreted ECM. As discussed later, the results of ECM deposition by encapsulated chondrocytes supports this hypothesis, showing large differences within this narrow compositional space, as well as significantly increased ECM with respect to 0% aHz controls.

Prior to encapsulation studies, it was important to characterize temporal changes in network architecture resulting from differences in covalent adaptability. After 28 days, hydrazone hydrogels demonstrated swelling ratios from approximately 20 to 40, corresponding to 97.5 to 95% water content.

Although higher than typically observed in native cartilage tissue (~80%), high water content in synthetic polymer scaffolds has been previously linked to improved cellular viability [48]. In addition, higher water content can help facilitate transport within networks for exogenous delivery of biochemical factors, such as small molecules and growth factors to promote regenerative behavior of encapsulated chondrocytes. Of equal interest, we wanted to understand the extent to which unbound PEG macromers would be released from hydrazone hydrogels over time. When the aHz content was high, the rate of hydrolysis of the aHz bonds was faster than the adaptable reformation, thus resulting in significant polymer loss for hydrogels composed almost entirely of aHz crosslinks. This highlights the need to balance the bHz content relative to the aHz content, especially with respect to tissue engineering applications. Specifically, bHz crosslinks help to maintain bulk material properties and structural integrity, while the aHz crosslinks create microenvironments that can respond to local forces generated by cells when they proliferate and secrete matrix molecules during tissue regeneration.

After seeding chondrocytes in CANs with varied adaptability, we sought to better understand how stress relaxation of these materials would influence the proliferation and matrix deposition. While

127 proliferation was not directly investigated, the cellularity of constructs was quantified over the course of 28 days. Due to the low metabolic activity of chondrocytes, the differences observed in cell density were relatively narrowly distributed, with hydrazone hydrogels demonstrating less than a single doubling over the course of 4 weeks. However, cell density did increase more significantly at intermediate levels of covalent adaptability. To further support these observations, it would be interesting to directly measure chondrocyte proliferation and track survival as a function of network adaptability, especially in the presence of mitogens or when stimulated by co-culture with MSCs [40]. In this work, a balance between fast and slow relaxing crosslinks was required for long term survival and proliferation of chondrocytes while maintaining cells within the confines of the scaffold. Average relaxation times between 6.3 x 104 s and 2.6 x 105 s facilitated increased chondrocyte populations, implying that this range may be particularly relevant for survival and proliferation of chondrocytes during in vitro cell culture. Increased cellularity in adaptable constructs correlated strongly with enhanced matrix deposition (Fig. 4.11), implying that proliferation is one of the primary mechanisms by which adaptable networks improve regenerative outcomes. We next studied how matrix components were spatially distributed as a function of the relaxation properties to better understand chondrocyte behavior within CANs, showing that ECM deposition was biphasic as a function of the hydrazone covalent adaptability. The formulation that formed neotissue most closely resembling native articular cartilage had an average relaxation time of 2.6 x 105 s, suggesting a link to chondrocyte timescales for ECM deposition and material properties that change on the order of days. Work focused on measuring local mechanical properties (e.g., microrheology) could provide further insight for how changes in mechanics of the cellular microenvironment alter chondrocyte phenotype and secretory properties, especially compared to the bulk rheological measurements conducted here.

Immunofluorescence was used to verify that chondrocytes in hydrazone CANs secreted articular cartilage-specific matrix molecules. Chondrocytes encapsulated in all of the hydrazone hydrogel formulations demonstrated relatively low levels of collagen I and collagen X deposition. In contrast, other clinical treatments currently used to repair articular cartilage, such as microfracture surgery, result in

128 primarily type I collagen, indicative of mechanically inferior fibrocartilage formation [49]. Similarly, the development of hypertrophic collagen type X typically precedes neotissue mineralization and osteoarthritic phenotypes [50]. Rather than displaying these markers of dedifferentiation, chondrocytes in hydrazone

CANs deposited primarily collagen type II found in healthy articular cartilage.

After only 4 weeks, the large amount of ECM deposited by encapsulated chondrocytes in these hydrazone hydrogels compared well to previously published literature. The hydrazone condition composed of 78% aHz crosslinks produced 140 ± 20 μg collagen / mg dry construct weight (Fig. 4.11). This value falls well within the range for ECM deposition by chondrocytes previously cultured within degradable PEG hydrogels (hydrolytically and enzymatically) as well as chondrocytes in naturally derived polymer networks such as hyaluronic acid and calcium-alginate hydrogels (~50-300 μg collagen / mg dry construct weight) [18,35,40,50,51]. This result is particularly promising considering that this study did not use juvenile chondrocytes, which produce more ECM than older chondrocytes from animals that have been alive for several months. This further encourages the use of CANs for MACT where chondrocytes are often isolated form elderly patients.

Alternatively, these CANs could be used to investigate the influence of non-linear scaffold mechanics on differentiation of MSCs for cartilage tissue engineering. This could augment the clinical significance of CANs for MACT due to higher availability and expansion potential of MSCs [52]. CANs also exhibit self-healing and injectable behaviors uniquely suited to clinical challenges facing cartilage tissue engineering and MACT [53]. For example, irregular defects could be press fit with self-healing CANs and invasive surgery requirements could be circumvented by injectable delivery schemes [54,55]. To simulate application in articulating joints, cell-laden hydrazone constructs could be cultured in a bioreactor to examine the effects of confined mechanical loading in vitro. Furthermore, hydrazone crosslinks have been previously used for in vivo studies suggesting facile translation for future animal studies [34,56]. Based on the results of this work, we postulate that covalent equilibria of hydrazone hydrogels could be tuned to

129 provide mechanical support for encapsulated cells in load bearing joints, while adaptable crosslinks allow for improved proliferation, matrix deposition and cellular remodeling.

Figure 4.11 Alternative normalization schemes. Graphs represent collagen (top) and sGAG (bottow) content normalized by lyophilized construct mass (left) and dsDNA content (right) for chondrocyte-laden hydrazone CANs over time. Four hydrogels were averaged for each condition (n=4).

4.6. Conclusion

We demonstrated the use of synthetic hydrazone CANs with tunable viscoelastic properties that modulate behavior of encapsulated chondrocytes. Incorporation of highly adaptable aHz crosslinks improved cellularity by a factor of two over four weeks and enhanced regenerative outcomes such as proliferation and ECM deposition with respect to the 0% aHz control. However, weakly percolating networks of slowly relaxing bHz crosslinks were also required to achieve the highest quality neocartilaginous tissue and maintain scaffold integrity. The reported results reveal covalent networks with relaxation timescales applicable for cartilage tissue engineering (6.3 x 104 - 2.6 x 105s) and provide insight

130 for how chondrocytes respond to differences in covalent network adaptability. Dense chondrocyte populations and interconnected neotissue observed in hydrazone CANs with average relaxation times of ~3 days suggests that this timescale is particularly relevant for chondrocyte behavior in CANs. Additionally, these results point to cellularity and reorganization timescales as determinant factors for development of neocartilaginous tissue in viscoelastic scaffolds. Chondrocytes in these adaptable hydrogels produced significantly more collagen (190 ± 30%) and sGAGs (140 ± 20%) than chondrocytes in predominantly elastic hydrogels with slow average relaxation times of ~1 month. Adaptable hydrazone hydrogels also yielded largely articular cartilage-specific type II collagen and aggrecan deposition, supporting future use of CANs as scaffolds to improve cartilage tissue engineering outcomes for MACT.

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Chapter 5 - Aim 2

5. Viscoelasticity of hydrazone crosslinked poly(ethylene glycol) hydrogels directs chondrocyte morphology during mechanical deformation

As appearing in Biomaterials Science 2020

5.1. Abstract

Chondrocyte deformation influences disease progression and tissue regeneration in load-bearing joints. In this work, we found that viscoelasticity of dynamic covalent crosslinks temporally modulates the biophysical transmission of physiologically relevant compressive strains to encapsulated chondrocytes.

Chondrocytes in viscoelastic alky-hydrazone hydrogels demonstrated (91.4 ± 4.5%) recovery of native rounded morphologies during mechanical deformation, whereas primarily elastic benzyl-hydrazone hydrogels significantly limited morphological recovery (21.2 ± 1.4%).

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Figure 5.1 Graphical abstract showing an artistic rendition of chondrocytes encapsulated in hydrazone covalent adaptable networks during deformation. Stable benzyl-hydrazone crosslinks are represented by purple hydrogels and dynamic alkyl-hydrazone crosslinks are represented by orange hydrogels.

5.2. Introduction

Symptomatic knee osteoarthritis is estimated to affect nearly 1 in 5 Americans over the age of 45 [1]. These patients experience chronic pain caused by damage to articular cartilage in load- bearing joints [2]. Degeneration of articular cartilage during the onset of osteoarthritis is typically compounded by the avascular structure and the limited regenerative capacity of resident chondrocytes [3]. Fortunately, tissue engineering strategies such as matrix-assisted autologous chondrocyte transplantation (MACT) have been developed to augment chondrocyte’s natural ability to regenerate during disease progression [4]. This strategy involves using water-swollen polymer networks, to support chondrocyte growth, enhance their regenerative capacity and deliver cells to the defect site [5]. To withstand compressive forces experienced in articulating joints, hydrogels developed for cartilage tissue engineering are often covalently crosslinked. However, traditional covalent crosslinks lead to an elastic response to mechanical deformation. In addition, non-

137 degradable covalent crosslinks can limit chondrocyte proliferation and extracellular matrix (ECM) deposition [6]. These limitations may suggest an explanation for why MACT remains an uncommon clinical treatment relative to microfracture [7].

To improve regenerative outcomes of MACT, hydrogels can be designed with viscoelastic properties, making them more similar to the ECM chondrocytes experience in vivo [8,9]. More specifically, freshly isolated cartilage tissue demonstrates viscoelastic matrix properties, such as stress relaxation and creep in addition to poroelastic interstitial fluid flow [10]. While covalently crosslinked hydrogels used as chondrocyte matrices allow for robust tuning of the elastic modulus of the material, they do not demonstrate time dependent material properties during mechanical deformation and permanent crosslinks can inhibit tissue regeneration [11]. Few cartilage regeneration studies have investigated how viscous dissipation (e.g., stress relaxation and material creep) influence chondrocyte deformation by comparison with the more well-studied effects of elastic stiffness [12,13]. Furthermore, many previously studied viscoelastic networks rely on electrostatic interactions (e.g., calcium-alginate) or entanglement (e.g., collagen) resulting in lower moduli than analogous covalently crosslinked hydrogels potentially limiting their ability to withstand compressive loading in articulating joints [8]. As a complement to existing hydrogels used for chondrocyte encapsulation, covalent adaptable networks (CANs) are a rapidly growing class of biomaterials [14]. When synthesized from water soluble precursors under physiological conditions, reversible covalent crosslinks offer both robust mechanical support and viscoelastic network reorganization uniquely suited for cartilage tissue engineering in compression bioreactors

(in vitro) or in load bearing joints (in vivo) [15].

In recent work, dynamic covalent chemistries (e.g., Diels-Alder reactions, Schiff bases, hydrazones, oximes and boronate esters) have been applied as CAN scaffolds for cell encapsulation and tissue engineering [16,17]. Related to this study, hydrazone CANs in particular can be used to encapsulate primary cells due to mild formation conditions (pH 7.0, 25°C) without a catalyst

138

[18,19]. Hydrazone bonds (R-HC=NH-NH-R) are formed when a nucleophilic hydrazine or hydrazide attacks a carbonyl electrophile in a condensation reaction, producing water as the only byproduct [20]. These hydrazone bonds are also susceptible to hydrolysis, rendering the process reversible [21]. Natural chemical equilibria, or the balance between these forward and reverse reactions is responsible for the viscoelastic network reorganization of hydrazone CANs. For example, adjacent electron withdrawing groups (e.g., rings) can be used to stabilize hydrazone bonds [21]. The increased hydrolytic stability of benzyl-hydrazone bonds relative to alkyl-hydrazone bonds (i.e. smaller reverse rate constant) leads to slower covalent crosslink adaptation and more elastic (i.e. less viscoelastic) material behavior [18]. This phenomena has been verified by small molecule kinetic studies showing that rate constants measured by small molecule kinetic studies can be used to understand the viscoelastic material properties of hydrazone CANs

[22]. The dynamic nature of hydrazone crosslinks makes them especially attractive as extracellular matrix mimics for tissue engineering [23,24].

5.3. Materials and Methods

All chemicals and solvents were analytical grade and acquired from commercial sources unless otherwise described. Multi-arm polyethylene glycol (PEG) precursors were purchased from JenKem

Technology USA.

5.3.1. alkyl PEG aldehyde synthesis

Alkyl-PEG-aldehyde was synthesized by Dess-Martin Oxidation of 8-arm PEG-OH (Mn

∼10,000 g/mol) as previously described (Fig. 5.2) [25]. Briefly, PEG was dissolved with Dess-Martin

Periodinane (1.5 equiv. w.r.t. OH groups) in a minimal amount of dichloromethane (DCM) containing catalytic H2O. The reaction was allowed to proceed for 3 h at room temperature. (23 °C)

139

Figure 5.2 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-CHO. Oxidation of a) hydroxyl terminated PEG to b) alkyl=PEG aldehyde.

5.3.2. benzyl PEG aldehyde synthesis

Benzyl-PEG-aldehyde was synthesized by HATU (1-[Bis(dimethylamino)methylene]-1H-1,2,3- triazolo[4,5-b]pyridinium3-oxidhexafluorophosphate) coupling to PEG-NH2 (Fig 5.3) [26]. Briefly, 4- formylbenzoic acid (2.2 equiv. w.r.t NH2 groups) was activated with HATU (2.0 equiv. w.r.t NH2 groups) and 4-methylmorpholine (5.0 equiv. w.r.t NH2 groups) in dimethylformamide (DMF) under argon for

10 min. In parallel, PEG-NH2 was dissolved in DMF containing 4-methylmorpholine (5.0 equiv. w.r.t NH2 groups). The two solutions were mixed and the reactions were allowed to proceed overnight under argon at room temperature. (23 °C)

Figure 5.3 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-Ar-CHO. HATU coupling of c) amine terminated PEG with formylbenzoic acid to form d) benzyl-PEG aldehyde.

5.3.3. PEG hydrazine synthesis

140

Hydrazine-PEG was synthesized by HATU coupling to PEG-NH2 as described above using Tri- boc-hydrazinoacetic acid (Fig. 5.4). Boc (tert-butyloxycarbonyl) protected hydrazine-PEG was precipitated dropwise in cold (4 °C) diethyl ether (Et2O), then dissolved in a 50:50 mixture of trifluoroacetic acid in

DCM. The deprotection reaction was allowed to proceed in a vented flask for 3 h prior to purification.

Figure 5.4 Reaction schematic showing organic synthesis scheme for 8a-PEG(TP)-10kD-NH-NH2. HATU coupling of c) amine terminated PEG with tri-boc-hydrazinoacetic acid to form e) boc-PEG hydrazine and then deprotected with trifluoroacetic acid to produce f) PEG hydrazine.

5.3.4. Macromer purification and characterization

Crude reaction mixtures were concentrated under reduced pressure, precipitated dropwise in cold

Et2O, centrifuged, and decanted. The products were washed similarly 3x and dried en vacuo. The products were then dissolved in deionized H2O and dialyzed in regenerated cellulose membranes (Spectra/Por) with molecular weight cut-off of 8,000 g/mol for 96 h at 4 °C. Polymer solutions were then lyophilized, and

1 stored dry at −20 °C. H-NMR spectroscopy (Bruker AV-III, CDCL3, 400 MHz) was used to evaluate the functional efficiency of the oxidation and coupling reactions. (Fig. 5.5) In each case the functionality was found to be >80%. (Table 5.1) Integrations were normalized by the setting PEG peaks to 113.5 as this represents the average number of PEG protons in a single polymer arm (for 8 arm 10 kD macromers). Under this normalization scheme, functional peak integrations should correspond to the number of protons within

141 each functional unit. Therefore, the average percent functionalization for each macromer was calculated by dividing normalized functional peak integrations by the number of protons that should be present in each functional unit. (Eq. 5.1)

Equation 5.1

∑ funtional peak integrations % functionalization = *100% Eq. 5.1 # protons in functional unit

Table 5.1 Tabulated variables related to synthesis reactions and hydrogel formulation

Designation hydrazine alkyl-aldehyde benzyl-aldehyde

Macromer structure PEG-NH-NH2 PEG-CHO PEG-Ar-CHO

Nucelophile (Nu) or electrophile (El) Nu El El

PEG, MW (g/mol) 10000 10000 10000

# of arms / PEG macromer 8 8 8

Functional Group MW (g/mol) 71 -2.0 130

Approximate functionalization (%) 88% 82% 93%

Estimated macromer functionality (fx) 7.0 6.6 7.4

Percolation threshold (pc) N/A (excess reagent) 0.19 0.18

4 3 3 Functionalized PEG, MW (g/mol) 1.05 x 10 9.99 x 10 1.10 x 10

142

143

Figure 5.5 H-NMR spectroscopy verifying functionalization of 8-arm 10kD PEG macromers. (a)

Unmodified PEG-OH, δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-); (b) Functionalized PEG-CHO,

δ = 9.852-9.640 (s, H, -CHO), δ = 4.243-4.085 (s, 2H, -CH2-CHO), δ = 3.725-3.542 (m, 113.5H, -O-CH2-

CH2-O-); (c) Unmodified PEG-NH2 δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-); (d) Functionalized

PEG-Ar-CHO, δ = 10.024-10.119 (s, H, -CHO), δ = 8.037-7.894 (m, 4H, -C6H4-), δ = 3.725-3.542 (m,

113.5H, -O-CH2-CH2-O-); (e) Functionalized PEG-NBoc-NBoc2, δ = 3.860-3.819 (s, 2H, -NH-CO-CH2-),

δ = 3.725-3.542 (m, 113.5H, -O-CH2-CH2-O-), δ = 1.581-1.509 (d, 18H, -OC(CH3)3), δ = 1.505-1.441 (d,

9H, -OC(CH3)3); (f) Functionalized PEG-NH-NH2, δ = 3.860-3.823 (s, 2H, -NH-CO-CH2-), δ = 3.725-

3.542 (m, 113.5H, -O-CH2-CH2-O-).

5.3.5. Hydrogel formulation

Functionalized PEG macromers were dissolved in buffered saline (DPBS Gibco) and neutralized.

(pH 7.2) Stock solutions were aliquoted for storage at -70°C prior to experimentation. Hydrogels were formed off stoichiometry (r = [El]/[Nu] = 0.8) to minimize the free aldehyde concentrations (~3wt%).

Percolation thresholds were determined using Flory-Stockmayer theory (Eq. 5.2), where fx represents the average number of reactive functional groups per macromer. (Table 5.2)

Equation 5.2

1 pc = Eq. 5.2 √r(fNu‐1)(fEl‐1)

5.3.6. Shear rheometry and modeling

Rheological experimentation was performed between temperature controlled parallel plates on a controlled-stress rheometer. (TA Instruments DH-R3) Hydrogels were formed in situ with a mineral oil ring applied to the air-hydrogel interface to prevent evaporation during experimentation. Characteristic relaxation times (τ) represent the quotient of the spring constant (E) and viscosity (η) for a Maxwell

Element, represented by a spring and dashpot in series. (Eq. 5.3) In this work, the Kohlrausch-Williams-

144

Watts model was used to describe viscoelastic behavior and is represented by an infinite series of Maxwell

Elements in parallel. (Fig. 5.6) Normalized stress relaxation data was fit with the Kohlrausch-Williams-

Watts function. (Eq. 5.4) In this equation, relaxation time constants (τ) are characteristic of the reorganization of covalent bonds and stretching parameters (β) account for heterogeneous relaxation events

[27].

Equation 5.3

τ = η/E Eq. 5.3

Figure 5.6 Schematic representation of the Kohlrausch–Williams–Watts stretched exponential function as an infinite series of Maxwell Elements in parallel.

Equation 5.4

σ t β = exp (‐ ( ) ) Eq. 5.4 σ0 τ

Average relaxation times 〈τ〉 represent the distribution of relaxation modes for the Kohlrausch-

Williams-Watts function. (Eq. 5.5) Average relaxation times were calculated by integrating the stretched exponential model over its entire domain (t = 0 to t = infinity).

Equation 5.5

145

τ 1 〈τ〉 = Γ ( ) Eq. 5.5 β β

Average linear creep rates (1/<η>) represent inverse viscosities and are characteristic of material deformation rates. (Eq. 5.6) This parameter can be found as the slope of the line describing the creep compliance (J) as a function of time, excluding initial creep ringing.

Equation 5.6

t J‐J = Eq. 5.6 0 〈η〉

5.3.7. Chondrocyte isolation and cell culture

Primary chondrocytes were isolated from the stifle joints and the femoral patellar groove of

Yorkshire swine as detailed previously [28]. Freshly isolated chondrocytes were frozen in 90% fetal bovine

6 serum (FBS) with 10% dimethyl (DMSO) at 2 x 10 cells/mL and stored in LN2 prior to use for experimentation. One week before encapsulation, chondrocytes were thawed and seeded onto T-75 tissue culture flasks. Expanded cell populations were encapsulated after reaching 80% confluence without passaging (P0). Chondrocytes were stained with CellTrackerTM Orange and encapsulated at 5 x 106 cells / mL. Hydrogels (50 µl) were formed in rectangular molds (4x4x3 mm) for 30 minutes prior to submersion in chondrocyte growth medium. Medium was composed of high-glucose DMEM (Gibco) supplemented with 10% FBS (Gibco), 1% penicillin-streptomycin-fungizone (Gibco, Invitrogen), 50 mg/mL L-ascorbate-

2-phosphate (Sigma-Aldrich), 40 mg/mL L-proline (Sigma- Aldrich), 100 mg/mL non-essential amino acid

(NEAA) (Gibco), 100 mg/mL HEPES buffer (Sigma-Aldrich) and 50 mg/mL gentamicin (Invitrogen).

Medium was changed every other day and hydrogels were maintained at 37 °C and 5% CO2.

5.3.8. In situ deformation microscopy

146

Figure 5.7 Specially designed loading plate used for in situ deformation microscopy. a) Cuboidal hydrogels prior to loading showing the cover slide base with the microscope objective below. b) The loading plate viewed on a lab bench showing the mechanism. c) The microscope and environmental chamber used to image live cells during deformation.

Cuboidal hydrogel constructs were loaded into a specially designed microscope mounted loading plate. Confocal images were acquired on a Nikon A1R laser scanning confocal microscope (40x objective) fitted with an environmental chamber to maintain humidity at 37°C and 5% CO2. (Fig. 5.7) Image processing and analysis were completed using ImageJ (NIH) or Imaris (Oxford Instruments) for intensity thresholding, edge exclusion, counting and measurement (Fig. 5.8). Data are shown as representative analysis from Z-stack maximum intensity projections, unless otherwise noted. Chondrocyte recovery is defined as the percentage of the initial deformation recovered by chondrocytes during 10 hours of static loading. (Eq. 5.7) The timeline for the in situ deformation experiments was defined by setting unstrained

(0% strain) conditions as t = 0 hour, the initial deformed time point (20% strain) as t = 1 hour, and the final deformed time point (20% strain) as t = 11 hour. (Fig. 5.9) Reported values represent error propagation of standard deviations from three hydrogel (n=3) hydrogel replicates.

147

Figure 5.8 3D reconstructions showing chondrocytes before (left) and during (right) application of a physiologically relevant compressive strain. Imaris Software was used to combine z-stacks of confocal microscopy images into 3D renderings. The software was similarly used to identify and count chondrocytes.

Scale bars represent 400 µm.

Equation 5.7

0 hour 11 hour X̅ X̅ [( ) ‐ ( ) ] Y 0% strain Y 20% strain % recovery = 0 hour 1 hour *100% Eq. 5.7 X̅ X̅ [( ) ‐ ( ) ] Y 0% strain Y 20% strain

148

Figure 5.9 The schematic above shows representative single chondrocytes at each time point during deformation. 2D cell masks were created from maximum intensity projections using Adobe Illustrator. A)

Represents 0%, B) 22%, C) 100% and D) shows the experimental timeline for deformation experiments.

Scale bar represents 10 µm.

5.3.9. Histological sectioning and staining

One week after encapsulation, chondrocyte-hydrogel constructs were fixed for 30 minutes at room temperature in 10% formalin. Hydrogels were rinsed in DPBS for 45 minutes then incubated in optimal cutting temperature (OCT) compound (Tissue-Tek) overnight at 4°C. Samples were transferred to molds with fresh OCT and snap frozen in LN2 prior to storage at -70°C. Slides were prepared with 20 μm hydrogel sections (Leica Cryostat CM1850). Sections were stained with Safranin-O (Leica Autostainer-XL) and cover slides were applied with Permount (Fisher) to preserve staining. Slides were imaged by bright field microscopy on a Nikon TE-2000 inverted microscope (100x objective).

5.3.10. Quantitative real-time polymerase chain reaction (qRT-PCR)

qRT‐PCR was used to quantify the mRNA expression levels for collagen type I (COL1A1) and collagen type II (COL2A1) relative to the reference gene GAPDH. Chondrocytes were cultured in hydrazone CANs for one week then subjected to 6 hours of uniaxial compressive loading (20%) after which samples were homogenized for 3 minutes with 5-mm steel beads shaking at 30 Hz (Qiagen TissueLyser).

RNA was then isolated using a RNeasy Micro Kit (Qiagen). RNA quantity and purity were measured via spectrophotometry (ND‐1000, NanoDrop). cDNA was synthesized from total RNA using the iScript

Synthesis kit (Bio‐Rad) and quantified via qRT‐PCR using SYBR Green reagents (Bio‐Rad) on an iCycler

(Bio‐Rad). Relative expression levels of Col1 and Col2 were quantified using the delta delta Cq method by normalizing to GAPDH for three replicates per condition [29]. Primer sequences are listed in Table 5.2.

Table 5.2 Tabulated primers used for qRT-PCR

149

Gene Forward primer (5′–3′) Reverse primer (5′–3′)

GAPDH ACACTCACTCTTCTACCTTTG CAAATTCATTGTCGTACCAG

COL1A1 GGGCAAGACAGTGATTGAATACA GGATGGAGGGAGTTTACAGGAA

COL2A1 CCTCAAGAAAGCCCTGCTCA CCCCACTTACCGGTGTGTTT

5.3.11. Statistics

Unless otherwise noted, graphical representations and error bars represent the mean ± standard deviations. Standard thresholds for significance were used throughout (e.g., P < 0.05 = *, P < 0.01 = **,

P < 0.001 = ***, P < 0.0001 = ****). Comparisons of three or more independent groups were analyzed by ordinary 1-way or 2-way ANOVA with multiple comparison tests. Statistical analyses were performed with

GraphPad Prism 8 software.

5.4. Results and Discussion

5.4.1. Viscoelastic alkl-hydrazone and elastic benzyl-hydrazone hydrogels

In this work, poly(ethylene glycol) (PEG) macromers were functionalized with nucleophilic hydrazines and electrophilic aldehydes. PEG is an attractive material because it is biologically inert and easy to modify. These characteristics minimize non-specific protein interactions and circumvent biochemical cues from naturally derived polymers which could confound studies aiming to elucidate biophysical effects of viscoelasticity [30]. The average functionalization of each type of PEG macromer was estimated (Table 5.1) using integrations for distinct functional groups normalized by PEG protons.

(Fig. 5.5) In each case the functionalization was found to be >80%. Reactive components were mixed off- stoichiometry (r = 0.8) to engineer hydrogels with user defined control over the viscoelastic properties by varying the molar percentages of alkyl-hydrazone and benzyl-hydrazone dynamic covalent crosslinks.

Three hydrogel formulations were tested by shear rheology to investigate the accessible range of

150 viscoelastic properties. (Fig. 5.10) Formulations represent a viscoelastic 100% alkyl-hydrazone (0% benzyl-hydrazone) an elastic 0% alkyl-hydrazone (100% benzyl-hydrazone) as well as an optimized mixed condition, 78% alkyl-hydrazone (22% benzyl-hydrazone) [31]. These hydrogel formulations were selected to yield a similar shear moduli (G) and remove stiffness as a confounding variable. (Fig. 5.10a) This is an important characteristic to control, as crosslinking density has been previously shown to influence chondrocyte morphology during deformation [32]. Hydrogel stiffness was selected to approximate the stiffness of encapsulated chondrocytes [33]. Importantly, despite matched stiffness, these hydrogels maintained differences in loss tangents tan(δ) = G’’/G’, illustrating differences in the viscous and elastic contributions to the shear modulus. (Fig. 5.10d)

Viscoelastic properties were measured through stress relaxation and creep tests to investigate how equilibrium differences of hydrazone crosslinks alter the scaffold response to deformation. Stress relaxation tests (Fig. 5.10b) were comparable with previous results, exhibiting average relaxation times (Fig. 5.10e) from (7.20 ± 1.1 1) x 103 s to (1.42 ± 0.06) x 106 s based on the Kohlrausch–Williams–Watts stretched exponential function [31]. (Eq. 5.4 & 5.5) More interestingly, these networks also exhibited material deformation, or creep, in response to a constant shear stress. (Fig. 5.10c) These differences were quantified by linear fitting, (Eq. 5.6) excluding creep ring artifacts and illustrating significant differences from (5.19

± 0.54) x 10-7 Pa-1s-1 to (9.59 ± 2.78) x 10-9 Pa-1s-1. (Fig. 5.10f) This treatment is consistent with the physical representation of the stretched exponential used to model stress relaxation and would be representative of an aggregate creep rate due to an infinite series of Maxwell elements in parallel (Fig. 5.6) [34]. Importantly, all three formulations result in non-significantly different shear moduli, which is directly proportional to the crosslink density [35]. Additionally, the average functionalization and polymer content are approximately equal between formulations. Therefore it is reasonable to assume that any differences in crosslinking efficiency are negligible and that differences in viscoelasticity can be attributed to bond dynamics of alkyl-hydrazone and benzyl-hydrazone crosslinks.

151

Figure 5.10 Rheological testing to investigate the viscoelastic/elastic material properties stemming from differences in chemical equilibria of dynamic hydrazone crosslinks. Off-stoichiometry (r = 0.8) hydrogels

(~3wt%) were formed in situ between parallel plates using reactive 8-arm 10kD PEG macromers. a) Shear moduli were calculated G = [(G’)2 + (G’’)2]1/2 using plateau values (dG’/dt ≈ dG’’/dt ≈ 0) measured by time sweep during gelation in situ at 1% strain and 1 rad/s. b) Stress relaxation of a 10% strain monitored as a function of time. c) Creep compliance measured over time by the application of a constant 100 Pa stress. d) Loss tangents (tan(δ)) were calculated as the quotient of storage and loss moduli at 1% strain and 0.05 rad/s. e) Average relaxation times (<τ>) calculated based on the Kohlrausch–Williams–Watts stretched exponential function. f) Linear average creep rates (<1/η>) were fit to data excluding initial creep ringing.

Data represent the average of measurements made in triplicate (n=3), with standard deviations where applicable. Significance represents the results of one-way ANOVA with Tukey’s multiple comparisons test showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****.

5.4.2. Viscoelastic creep compliance influences chondrocyte morphology during deformation

152

Armed with a better understanding of how these hydrogels respond to mechanical deformation, we sought to examine how differences in viscoelastic properties of hydrazone CANs would influence the morphology of encapsulated chondrocytes during mechanical deformation (Fig. 5.11). To accomplish this, porcine chondrocytes were stained with CellTrackerTM Orange, encapsulated in cuboid hydrogels, and imaged in situ by confocal microscopy (Fig. 5.11a). Representative maximum intensity projections of single chondrocytes exposed to a 20% uniaxial compressive strain illustrate changes in chondrocyte morphology over 10 hours due to viscoelasticity (Fig. 5.11c). These qualitative changes in chondrocyte morphology were then quantified by measuring the cell deformation index [36]. The deformation index (Fig. 5.11b &

Fig. 5.11d) was calculated as the quotient of the cell dimension parallel to the axis of compression (X) and the cell dimension perpendicular to the axis of compression (Y) [37]. Previously, we have observed that a

20% macroscopic strain corresponded to X/Y = 0.8 ± 0.1 in PEG hydrogels with low crosslinking densities, which is higher than would be expected (X/Y = 0.67) assuming cell volume remains constant [38,39].

Initially, this was observed in all three conditions, with unstrained deformation indices close to 1.0 followed by cellular deformation to approximately 0.8 immediately after application of a 20% compressive strain

(Fig. 5.9). However, after 10 hours of applied strain, the morphologies of chondrocytes in the highly viscoelastic 100% alkyl hydrazone hydrogels and the primarily elastic 0% alkyl hydrazone hydrogels diverge significantly. During 10 hours of deformation at 20% strain, chondrocytes encapsulated in the viscoelastic 100% adaptable hydrogels recovered their unstrained rounded morphologies. (X/Y = 0.97 ±

0.03) Whereas, chondrocytes in the elastic 0% adaptable hydrogels largely retained deformed ellipsoidal morphologies (X/Y = 0.86 ± 0.05).

For the morphology of an encapsulated chondrocyte to change within these 3D hydrogel matrices, the network crosslinks must be able to transmit strain to the cellular level. Similarly, for a chondrocyte to recover a rounded morphology while under deformation, the cell must exert a stress on the network and the crosslinks must rearrange or creep to allow the cell to change shape [40]. Therefore, it follows that creep compliance would be the viscoelastic behavior driving changes in chondrocyte morphology in hydrazone

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CANs during mechanical deformation. Graphing the cellular deformation index after 10 hours of deformation by the linear creep rate reveals a linear correlation, which is consistent with the rheological understanding that the material must creep to allow the cell morphology to change (Fig 5.11d). This cellular observation is particularly interesting in comparison with the macroscopic dimensions of the hydrogels before and after 10 hours of deformation at 20% strain (Fig 5.11e). The viscoelastic 100% hydrogel macroscopically creeped to adopt the deformed shape even after the load was removed. In contrast, the 0% hydrogels elastically retained similar dimensions before and after strain removal. As expected, the hybrid

78% condition exhibited behavior between the two extremes fitting the intermediate creep rate measured by shear rheology. Notably, the trend for bulk hydrogel deformation (Lx/Ly) after strain removal was inverse of the cellular deformation (X/Y) during deformation, illustrating consistent creep compliance behavior at both the microscopic and macroscopic length scales.

Figure 5.11 Viscoelastic creep compliance influences chondrocyte morphology during deformation.

Viscoelastic alkyl-hydrazone hydrogels demonstrate both macroscopic and microscopic time-dependent material deformation. a) Schematic illustrating the experimental setup and hydrogel dimensions. b)

Schematic illustrating how chondrocyte deformation index (X/Y) is measured. c) Chondrocytes stained

154 with CellTrackerTM Orange and imaged in situ during deformation by confocal microscopy. Images represent maximum intensity projections illustrating changes in chondrocyte morphology over 10 hours of compressive loading at 20% strain. Scale bar represents 30 µm. d) Correlation between microscopic chondrocyte deformation indexes and viscoelastic creep rates of hydrazone hydrogels after 10 hours of 20% strain. e) Macroscopic deformation indexes before and after loading. Significance represents one-way or two-way ANOVA with Tukey’s and Sidak’s multiple comparisons tests, P ≥ 0.05 = ns, P < 0.05 = *.

5.4.3. Viscoelasticity alters biophysical cues over time during mechanical deformation

To further investigate the biophysical transmission of mechanical strain to encapsulated chondrocytes, we sought to track morphology changes over time. This allowed us to map the influence of viscoelasticity on cell-matrix interactions in hydrazone CANs. (Fig. 5.12) Chondrocytes in the most adaptable 100% condition rapidly regained rounded morphologies, becoming non-significantly different from the unstrained chondrocytes after only 5 hours. (Fig. 5.12a & 5.12b) Material testing by shear rheology indicates that after 5 hours the network should have been able to relax >80% of an applied strain. This implies that a large fraction of the pericellular crosslinks must rearrange in order to influence chondrocyte morphology in hydrazone CANs. Furthermore, chondrocytes encapsulated in the viscoelastic 100% CAN hydrogels continued to approach their initial spherical morphologies over the course of the experiment, eventually showing 91.4 ± 4.5% recovery (Eq. 5.7). This phenomena is consistent with that observed in viscoelastic alginate hydrogels, where chondrocytes experience a decrease in cellular strain over time in low polymer content ionically crosslinked hydrogels [41].

Similarly, the 78% condition demonstrated viscoelastic recovery, albeit over a much slower time scale. Chondrocyte morphologies became less significantly different from the initial unstrained state over the course of the deformation period (Fig. 5.12c & 5.12d). This is also consistent with the theoretical framework, as 22% benzyl-hydrazone crosslinks (78% alkyl-hydrazone) is above the Flory-Stockmayer percolation threshold. Meaning the hybrid hydrogels are composed of an interconnected network with both alkyl-hydrazone and benzyl-hydrazone crosslinks spanning the dimensions of the hydrogel (Eq. 5.2) [42].

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Therefore, the behavior of chondrocytes in the 78% condition can be understood to be influenced by competing elastic and viscoelastic crosslinks. The result of this is partial recovery of the rounded morphology during deformation, followed by full elastic recovery in the wake of strain removal.

Importantly, this shows that incorporating a relatively small percentage of benzyl-hydrazone crosslinks (22 mol %) can significantly impact network reorganization which in turn influences cellular morphology during deformation (e.g., 32.7 ± 1.7% recovery).

In accordance with prior results, the 0% hydrogels behaved as ideal elastic solids, maintaining statistically significant chondrocyte deformation over the entire 10 hour strain period. Chondrocytes in the

0% condition showed limited recovery during deformation, (21.2 ± 1.4%) followed by instantaneous recovery when the 20% strain was removed (Fig. 5.12e & 5.12f). We had postulated that this would be the case due to the short experimental time relative to the average relaxation time for 0% networks (104 s <<

106 s). The elastic response of the 0% hydrogels is also consistent with previously published literature showing similar elastic recovery during unloading in agarose hydrogels [43]. Taken together, these findings expand our understanding of how chondrocyte morphology is altered by mechanical deformation in viscoelastic scaffolds and further elucidates how dynamic covalent crosslinks can be used to modulate the cellular response. This information may be relevant for cartilage tissue engineering applications, considering the well-established relationship between chondrocyte morphology and phenotype [44].

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Figure 5.12 Viscoelastic and elastic hydrazone CANs impart biophysical cues to encapsulated chondrocytes differently over time during mechanical deformation. a), c), and e) show deformation indexes graphed over time. Grey regions represent 10 hours chondrocyte-laden hydrogels were subjected to a 20% uniaxial compressive strain. Data represent the mean and standard deviation of three hydrogels (n=3), where morphology data from 300 cells were averaged. Significance represents the results of two-way ANOVA with Dunnett’s multiple comparisons test showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 =

***, P < 0.0001 = ****. b), d), and f) are schematics illustrating changes in chondrocyte morphology due to viscoelastic/elastic material properties to aid in the interpretation of deformation index data.

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5.4.4. Matrix deposition influences the transmission of biophysical cues

To put the aforementioned findings into greater context for cartilage tissue engineering, we then explored how nascent ECM protein deposition over the first week of culture can influence the transmission of compressive strains within CAN networks (Fig. 5.13). We observe that chondrocytes rapidly begin to synthesize ECM molecules in these hydrogel constructs, potentially influencing the local presentation of biomechanical cues [45]. Here, CAN-chondrocyte hydrogels were cultured at 37°C with 5% CO2 in chondrocyte growth medium for 1 week. Representative histology sections stained for sulfated glycosaminoglycans (sGAGs) show variations in the spatial distribution of deposited matrix as a function of viscoelastic creep (Fig. 5.13a). In the most adaptable hydrogels, (100%) cell secreted sGAGs were distributed a larger distance from the chondrocytes, which was similarly observed in the 78% CANs.

Interestingly, many cells in the fully adaptable 100% viscoelastic CANs appeared in lacunae often with more than one chondrocyte. In contrast, the elastic hydrogels (0%) constrained deposited sGAGs with sharply defined boarders at the hydrogel-neotissue interface [31]. For cartilage tissue engineering, scaffolds must act in concert with the kinetics of tissue growth to allow neotissue percolation, ultimately replacing the scaffold with ECM [46]. In this respect, adaptablility of the viscoelastic CANs (100% and 78%) allows for a greater degree of cell-secreted matrix integration. This suggests that viscoelastic creep of dynamic covalent crosslinks could be a viable mechanism for improving cartilage tissue engineering without compromising mechanical properties of tissue engineering matrices.

To interpret how differences in pericellular matrix deposition might influence chondrocyte behavior, chondrocyte-laden hydrogels were similarly subjected to a compressive strain and imaged before

(0% strain) and during deformation (20% strain). Deformation index was normalized to better represent the transmission of compressive strain in different conditions by accounting for minor deviations in unstrained chondrocyte morphology during extended culture. The results show that pericellular matrix deposition reduced cellular deformation in viscoelastic CANs, implying that chondrocytes can remodel the cellular microenvironment in a way that protects chondrocytes from compressive strains (Fig. 5.13b). This

158 pericellular matrix-mediated strain protection has been examined extensively by Knight et al. where hyaluronidase treatment was used to degrade sGAGs, restoring the magnitude of chondrocyte deformation at day three to that of day one [39,47]. In this work, the effect was more significant in the 78% hydrogels than the most viscoelastic 100% hydrogels despite more matrix deposition in the latter case. We hypothesized that this observation may be the result of enhanced proliferation in the highly adaptable 100% hydrogels that complicates the analysis. To test this, we assumed a uniform cell distribution and calculated the approximate number of chondrocytes in each hydrogel (Fig. 5.13c) using 3D reconstructions from confocal microscopy images (Fig. 5.8) We found that both networks containing percolating benzyl- hydrazone crosslinks (78% & 0%) showed similar chondrocyte densities relative to initial seeding density

(5 x 106 cells/mL) which implies that little or no proliferation was possible in these networks after only one week. In contrast, the total number of chondrocytes roughly doubled in highly viscoelastic 0% hydrogels, despite variable results between hydrogel replicates (P ≤ 0.1).

To further gauge the implications of viscoelastic differences for cartilage tissue engineering, 1- week samples were collected after 6 hours of deformation at 20% strain and analyzed for expression of chondrocyte-specific markers using qPCR. We investigated the relative expression ratio of collagen type I

(Col1) to collagen type II (Col2) as an established metric for quantifying chondrocyte dedifferentiation

[48]. More specifically, native chondrocytes express primarily Col2 in healthy articulating joints, whereas the expression of Col1 is indicative of bias towards a fibrochondrocyte phenotype and the formation of mechanically inferior fibrocartilage [49]. The data shows an interesting trend towards an increase in the ratio of Col1:Col2 expression in highly elastic 0% hydrogels, showing almost and order of magnitude increase compared to the viscoelastic 100% and 78% CANs. These results suggest that viscoelasticity and adaptability of the hydrazone CANs may help to ameliorate the detrimental effects of static deformation on chondrocyte gene expression (Fig. 5.13d) [50]. This mechanism has been previously proposed by

Nicodemus & Bryant to explain observed changes in chondrocyte gene expression during dynamic cyclic compression in bioreactor cultures [51]. Future work in this space could investigate physiologically relevant

159 deformation regimes during extended cell culture in bioreactors to build on the fundamental understanding established here.

Figure 5.13 Pericellular matrix deposition in viscoelastic hydrazone hydrogels influences the transmission of biophysical cues. Tissue engineering is a dynamic process and chondrocytes deposit extracellular matrix over time to influence the mechanics of their own microenvironments. a) Histological sections stained with

Safranin O. sGAGs are represented by the red stain area with nuclei stained violet/black. Scale bars represent 20 µm. b) Quantification of normalized deformation index (X20% / Y20%) / (X0% / Y0%) after one week of culture illustrates differences in the transmission of a 20% strain to encapsulated chondrocytes. c) Estimation of the number of chondrocytes per hydrogel extrapolated from confocal microscopy data showing increased cell populations in the absence of percolating elastic networks of stable benzyl- hydrazone crosslinks. d) Relative expression of Col1 and Col2 after 6 hours of loading at 20% strain, normalized by GAPDH expression. The trend suggests that ECM disposition in viscoelastic CANs can help mitigate negative effects of static loading.

5.5. Conclusion

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Joint movement causes deformation of articular chondrocytes and their surrounding matrix in vivo, and the morphology changes associated with these events have implications for cartilage tissue engineering

[52]. In this work, we establish hydrazone crosslinked PEG hydrogels for studying the effects of viscoelastic rearrangement of covalent crosslinks on chondrocyte function during mechanical deformation. Using in situ deformation microscopy, we found that the morphology of encapsulated chondrocytes could be controlled by altering adaptation rates of covalent crosslinks during the application of a physiologically relevant strain. Significantly, these experiments show that chondrocytes are able to exert forces on their surrounding matrix over time, and that dissipative phenomena (i.e., creep compliance & stress relaxation) allow chondrocytes to regain native rounded morphologies under static loads in hydrazone CANs.

Viscoelasticity also led to differences in the pericellular distribution of sGAGs after one week, differentially interrupting the biophysical transmission of compressive strain to encapsulated chondrocytes. Finally, viscoelastic creep and pericellular matrix deposition may reduce some of the detrimental effects of static deformation by enabling proliferation and improving the relative expression of collagen type II to collagen type I. These findings provide a basis to inform future work using dynamic covalent chemistries to design next generation biomaterials for studying and controlling chondrocyte behavior for cartilage tissue engineering.

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Chapter 6 - Aim 3

6. Mechanobiological interactions between dynamic compression and viscoelasticity on chondrocytes in hydrazone covalent adaptable networks for cartilage tissue engineering

Appearing as submitted to Advanced Healthcare Materials 2020

6.1. Abstract

Mechanobiological cues influence chondrocyte biosynthesis and are often used in tissue engineering applications to improve the repair of articular cartilage in load-bearing joints. In this work, we explore the effects of an applied dynamic compression on chondrocytes encapsulated in viscoelastic hydrazone covalent adaptable networks (CANs). Here, hydrazone CANs exhibit viscoelastic loss tangents ranging from (9.03 ± 0.01) 10-4 to (1.67 ± 0.09) 10-3 based on the molar percentages of alkyl-hydrazone and benzyl-hydrazone crosslinks. Chondrocytes in viscoelastic and elastic hydrazone CANs respond differently to physiologically relevant, dynamic compressive strain. Viscoelastic hydrazone networks improve articular cartilage specific gene expression, showing lower COL10A1 and MMP13 expression relative to elastic controls. Interestingly, dynamic compression improves matrix biosynthesis in elastic benzyl- hydrazone controls but reduces biosynthesis in viscoelastic alkyl-hydrazone CANs. Additionally, intermediate levels of viscoelastic adaptability demonstrate the highest levels of matrix biosynthesis in hydrazone CANs, demonstrating on average 70 ± 4 µg of sulfated glycosaminoglycans per day and 31 ± 3

µg of collagen per day over one month in dynamic compression bioreactors. Collectively, the results herein demonstrate the role of matrix adaptability and viscoelasticity on chondrocytes in hydrazone CANs during dynamic compression, which may prove useful for tissue engineering applications in load-bearing joints.

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Figure 6.1 In recent years, growing emphasis has been placed on understanding how matrix mechanics and mechanobiology can be used to design better biomaterials. Here, we use specially designed bioreactors to elucidate how viscoelasticity of hydrazone covalent adaptable networks influences the behavior of chondrocytes during physiologically relevant dynamic compression and our results lend insights for cartilage tissue engineering in load-bearing joints.

6.2. Introduction

Osteoarthritis is a painful condition where articular cartilage becomes severely degenerated [1].

Unfortunately, osteoarthritis affects more than 30 million people in the United States [2]. Additionally, arthritis-associated medical expenditures and loss of earnings in the United States are estimated to be >$300 billion annually [3]. Osteoarthritis is the most common form of arthritis [2], and this economic burden is borne disproportionately by patients with osteoarthritis in load-bearing joints [4].

Because of the need for reparative treatments prior to the onset of osteoarthritis, cartilage tissue engineering has emerged as one promising strategy to address these problems [5]. Cartilage tissue engineering strives to help regenerate damaged cartilage using cells, polymer matrices, and promotive cues

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[6]. In articulating joints, chondrocytes receive biomechanical cues in the form of dynamic compression

[7], which can increase chondrocyte biosynthesis [8], when applied at physiologically relevant strains and frequencies [9]. In this way, dynamic compression bioreactors have been used to mimic the native cartilage environment and stimulate chondrocytes for cartilage tissue engineering in vitro. Efforts by tissue engineers to leverage this effect for cartilage tissue engineering have been comprehensively reviewed by Anderson and Johnstone [10]. Briefly, dynamic mechanical compression has been shown to influence chondrocyte anabolic and catabolic activities [11], gene expression [12], secretory properties [13], nitric oxide production [14], proliferation [15], calcium signaling [16], and the bulk mechanical properties of engineered tissues [17]. Further, the material properties of hydrogel scaffolds (e.g., incorporation of cell adhesive ligands [18], crosslinking density [19], network microarchitecture [20], energy dissipation [21]) also influence chondrocyte responses to mechanical compression. These effects have been shown in the context of osteoarthritis, where dynamic compression can improve biosynthesis by chondrocytes isolated from patients with osteoarthritis [22].

Hydrogel scaffolds used for cartilage tissue engineering in load-bearing joints must provide mechanical strength for withstanding biomechanical forces in articulating joints [23]. Many of the hydrogels used for cartilage tissue engineering are covalently crosslinked to provide resistance to compression in articulating joints [24]. Unfortunately, covalent bonds can limit cellular remodeling [25], and confine extracellular matrix (ECM) deposition to the pericellular space [26]. While covalent hydrogels exhibit tailorable elastic mechanical properties,[27] native articular cartilage is viscoelastic [28]. Covalent adaptable networks (CANs) [29]. are a growing area of interest within the biomaterials community, as these networks can adapt and dynamically reorganize in response to mechanical stresses and strains [30]. The reversibility of network crosslinks imparts viscoelastic material properties [31], which can capture aspects of the mechanical properties of native tissues [32]. As one example, hydrazone CANs are well-suited for biological applications where the reversibility of the crosslinks occurs under physiological conditions (pH

7.4, 37°C) [33]. McKinnon et al. developed viscoelastic hydrazone crosslinked poly(ethylene glycol) (PEG)

169 hydrogels to study C2C12 myoblasts and ES-derived motor neurons [34,35]. Following this work, hydrazone crosslinked hyaluronic acid-based hydrogels have also been developed as viscoelastic cell culture platforms [36,37]. More recently, we used viscoelastic hydrazone CANs to encapsulate chondrocytes and study matrix deposition as a function of the network chemistry. We found that stress relaxation influenced ECM deposition [38], and that creep compliance impacts chondrocyte morphology during mechanical deformation [39].

Understanding how mechanobiological cues influence chondrocyte behavior is critical for improving cartilage tissue engineering strategies [40]. In this work, we sought to investigate mechanobiological interactions between viscoelastic matrix properties during mechanical compression using hydrazone CANs (Fig. 6.2). We formulated hydrazone PEG hydrogels with alkyl-hydrazone and benzyl-hydrazone crosslinks (Fig. 6.2a) and quantified differences in their viscoelastic properties using small amplitude oscillatory shear (SAOS) rheometry (Fig. 6.2b). Chondrocytes encapsulated in these networks (Fig. 6.2c) were subjected to long-term culture in dynamic compression bioreactors designed to simulate mechanical stimuli experienced in articulating joints (Fig. 6.2d). Gene expression was quantified by quantitative polymerase chain reaction (qPCR) to study how viscoelasticity and mechanical compression influence articular cartilage specific gene expression. Rates of biosynthesis were measured by quantifying the deposition of sulfated glycosaminoglycans (sGAGs) and collagen over time during dynamic compression. Histological sectioning and staining analysis was employed to visualize the spatial distribution of these molecules. This study further validates the application of hydrazone CANs for cartilage tissue engineering and lends insight about how mechanobiological factors can affect chondrocytes and their matrix synthesis to improve cartilage tissue engineering.

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Figure 6.2 Schematic illustration represents the experimental design for dynamic compression experiments. (a) The alkyl-hydrazone (green) crosslink equilibrium leads to more viscoelastic material properties (e.g., faster stress relaxation) than the more stable benzyl-hydrazone (purple) crosslinks. (b) The viscoelastic properties of hydrazone CANs are varied based on the molar percentage of alkyl-hydrazone and benzyl-hydrazone crosslinks. (c) Articular chondrocytes were encapsulated in hydrazone hydrogels and allowed three days to recover from isolation and encapsulation stresses. (d) On day 4, Chondrocyte-laden hydrazone hydrogels were transferred to dynamic compression bioreactors which were programed to apply a cyclic 15% strain at a rate of 1 Hz for one hour each day. Dynamically loaded hydrogels were compared to free swelling controls 3, 10, 17, 24 and 31 days after encapsulation.

6.3. Materials and methods

171

Chemicals and solvents used in this work were analytical grade and acquired from commercial sources unless otherwise described.

6.3.1. Organic synthesis

Chemicals and solvents used in this work were analytical grade and acquired from commercial sources unless otherwise described. PEG-hydrazine was synthesized by HATU (1-

[Bis(dimethylamino)methylene]-1H-1,2,3-triazolo[4,5-b]pyridinium3-oxidhexafluorophosphate) coupling to form an amid bond using amine terminated PEG macromers (8 arm, 10 kDa) and tert- butyloxycarbonyl(boc)-protected hydrazinoacetic acid as previously described [41]. Frist, tri-boc- hydrazinoacetic acid (2.2 mol eq. / R-NH2) was reacted with HATU (2.0 mol eq. / R-NH2) and 4- methylmorpholine (5.0 mol eq. / R-NH2) in dimethylformamide (DMF) under argon for 10 minutes. In parallel, PEG amine was deprotonated with 4-methylmorpholine (5.0 mol eq. / R-NH2) in DMF. The two solutions were combined and the reaction was allowed to proceed overnight under argon at room temperature (23°C). Boc-protected PEG-hydrazine was then precipitated dropwise in cold (4°C) diethyl ether (Et2O) and dried in vacuo, before being dissolved in a 50:50 mixture of trifluoracetic acid (TFA) and dichloromethane (DCM). The deprotection reaction was allowed to proceed in a vented flask for 3 hours prior to purification. PEG-benzaldehyde was similarly synthesized using HATU reagent with PEG amine and 4-formylbenzoic acid as described above, excluding the deprotection reaction. Alkyl-PEG-aldehyde was synthesized using Dess-Martin Periodinane (DMP) to oxidize hydroxyl terminated PEG macromers

[42]. Hydroxyl PEG (8 arm, 10 kDa) was dissolved with DMP (1.5 equiv. mol eq. / R-OH) in DMF containing catalytic dissolved water. The reaction was allowed to proceed for 3 hours at room temperature

(23°C) prior to purification.

6.3.2. Chemical purification

Crude reaction products were concentrated under reduced pressure, precipitated dropwise in cold diethyl ether (Et2O), centrifuged, and decanted. PEG products were washed in this way three times and

172 dried in vacuo. Functionalized PEGs were then dissolved in deionized water and dialyzed in regenerated cellulose membranes (Spectra/Por MWCO 8,000 kDa) for 48 hours at room temperature (23°C). Polymer solutions were then lyophilized and dissolved in phosphate buffered saline (PBS). Each stock solution was carefully neutralized (pH = 7.0 ± 0.02) as small variations in pH can strongly influence hydrazone kinetics

[43].

6.3.3. 1H-NMR spectroscopy

Proton NMR spectroscopy was used to estimate PEG macromer functionalization (Bruker AV-III,

CDCL3, 400 MHz). In each case, PEG chains were ≥ 80% functionalized with the intended products of the oxidation and coupling reactions. Functionalization was calculated by normalizing proton peak integrations to PEG protons in a single polymer arm (113.5 H). Under this normalization scheme, functional group integrations correspond to the protons within each functional unit. The average functionalization for each macromer was then calculated by dividing normalized functional peak integrations by the number of protons in each functional unit. Unmodified PEG-OH, δ = 3.73-3.54 (m, 113.5H). Functionalized PEG-

CHO, δ = 9.85-9.64 (s, H), δ = 4.24-4.09 (s, 2H), δ = 3.73-3.54 (m, 113.5H). Unmodified PEG-NH2,

δ = 3.73-3.54 (m, 113.5H). Functionalized PEG-Ar-CHO, δ = 10.12-10.02 (s, H), δ = 8.04-7.90 (m, 4H),

δ = 3.73-3.54 (m, 113.5H). Functionalized PEG-NBoc-NBoc2, δ = 3.86-3.82 (s, 2H), δ = 3.73-3.54 (m,

113.5H), δ = 1.58-1.51 (d, 18H), δ = 1.51-1.44 (d, 9H). Functionalized PEG-NH-NH2, δ = 3.86-3.82 (s, 2H),

δ = 3.73-3.54 (m, 113.5H).

6.3.4. Shear rheology

Hydrazone CANs were formed in situ between temperature-controlled Peltier plates (TA Instruments

DH-R3). CANs were formulated to match conditions for cell culture, off-stoichiometry (r = [El] / [Nu] =

0.8) at 5.1, 5.3 and 5.5 w/v% to compensate for differences in macromer functionalization. Experimental conditions were informed by previous work indicating that a percolating network of benzyl-hydrazone bonds are required to maintain scaffold integrity and promote optimal neotissue development in hydrazone

173 covalent adaptable networks [38]. Mineral oil was applied to the hydrogel-air-instrument interface to prevent evaporative artifacts. Gelation was monitored by time sweep at 1 rad s-1, 1% strain, and 25°C.

Gelation point was defined as the time for the instrument to register a storage modulus greater than the loss modulus with G’ ≥ 10 Pa to account for instrument limitations. For stress relaxation experiments, a 10% shear strain (γ) was applied and the shear stress (σ) was measured as a function of time. For creep experiments, a 100 Pa stress was constantly applied and the creep compliance (J) was measured as a function of time. Frequency sweeps were measured at 1% strain, and strain sweeps were performed at 1 rad s-1. Modulus recovery is defined here as the quotient of the shear modules (G) modulus before and after shear-thinning expressed as a percentage of the initial modulus. MATLAB was used to fit rheology data.

Normalized shear stress was fit to a two-element Kohlrausch-Williams-Watts function (Equation 2) to account for heterogeneities such as addition and exchange reaction mechanisms [44].

6.3.5. Chondrocyte isolation, encapsulation and culture

Porcine chondrocytes were obtained by digesting cartilage from the femoral condyles and the patellar groove of Yorkshire swine stifle joints (n=8) [45]. Primary chondrocytes were encapsulated at ~20 million cells per mL in cylindrical hydrazone CANs (D =5 mm, H = 3 mm) as this seeding density has been previously shown to resolve differences in matrix deposition during dynamic compression culture [17].

Chondrocytes were given 3 days under free swelling conditions to recover from digestion/encapsulation stresses prior to dynamic compression culture. Chondrocyte-laden CANs were cultured in chondrocyte growth medium containing high-glucose DMEM (Gibco) supplemented with 10% fetal bovine serum

(Gibco), 1% penicillin-streptomycin-fungizone (Gibco, Invitrogen), 50 mg mL-1 L-ascorbate-2-phosphate

(Sigma-Aldrich), 40 mg mL-1 L-proline (Sigma-Aldrich), 100 mg mL-1 non-essential amino acids (Gibco),

100 mg mL-1 HEPES buffer (Sigma-Aldrich) and 50 mg mL-1 gentamicin (Invitrogen).

6.3.6. Quantitative polymerase chain reaction (qPCR)

174

RNA was isolated by first mechanically homogenizing samples in RLT lysis buffer (Qiagen 79216) for 3 minutes with 5-mm steel beads shaking at 30 Hz (Qiagen TissueLyser). RNA was isolated from the homogenized samples using the RNeasy Mini Kit (Qiagen 74106). The quantity and purity of RNA were measured via spectrophotometry (ND‐1000, NanoDrop). cDNA was synthesized from total RNA using the iScript Synthesis kit (Bio‐Rad 1708841) and quantified via qRT‐PCR using SYBR Green reagents (Bio‐

Rad 1708884) on an iCycler (Bio‐Rad). Relative expression levels were quantified using the ΔΔCq method by normalizing to GAPDH with forward and reverse primer sequences listed in Table 6.1 [46].

Table 6.1 Primers used for qRT-PCR.

Gene Forward primer (5′–3′) Reverse primer (5′–3′) GAPDH ACACTCACTCTTCTACCTTTG CAAATTCATTGTCGTACCAG COL1A1 GGGCAAGACAGTGATTGAATACA GGATGGAGGGAGTTTACAGGAA

COL2A1 CCTCAAGAAAGCCCTGCTCA CCCCACTTACCGGTGTGTTT MMP13 TCATGCTTTTCCTCCCGGAC GGGTCCTTGGAGTGGTCAAG SOX9 CACATCTCTCCCAACGCCAT GTTGGTGGACCCTGGGATTG COLX GCTGGTAGGACACCAACTCC CAAAAGGGCTGTTTGTGGCA

6.3.7. Biochemical assays

Hydrogels were flash frozen in liquid nitrogen, lyophilized and then homogenized in digestion buffer by shaking for 10 minutes with 5-mm steel beads at 30 Hz (Qiagen TissueLyser). Homogenized samples were further enzymatically digested in a solution of 125 μg mL-1 papain (Worthington Biochemical) supplemented with 10 mM cysteine (Sigma Aldrich) overnight at 65°C. Sample solutions were centrifuged and the supernatant was used for dimethylmethylene blue (DMMB) assay and PicoGreen (Life

Technologies) assay to quantify sGAG content [47], and the cell number [48], respectively. A portion of each digest solution was hydrolyzed with an equal volume of 12 M hydrochloric acid for 15 hours at 120°C.

Total collagen content was then estimated by hydroxyproline assay [49].

175

6.3.8. Linear regression analysis

Four hydrogel replicates (n=4) were analyzed from five time points (3, 10, 17, 24, and 31 days after encapsulation) to calculate matrix deposition rates for each experimental condition. Linear regression was used to extract linear matrix deposition rates. Linear regression was selected as most appropriate for interpreting chondrocyte behavior after comparing polynomials up to order 6 with extra sum-of-squares F tests where the simpler model is recommended unless the P values are less than 0.05.

6.3.9. Histological sectioning and staining

Chondrocyte-hydrogel constructs were fixed at room temperature (23°C) for 30 minutes in 10% formalin. CANs were rinsed in DPBS (Gibco) for 30 minutes before incubation at 4°C in optimal cutting temperature (OCT) compound (Tissue-Tek) overnight. Samples were transferred to cryomolds with fresh

OCT and flash frozen in liquid nitrogen. 20 μm sections (Leica Cryostat CM1850) were stained with

Masson’s Trichrome for collagen and Safranin-O for sGAGs (Leica Autostainer-XL). Cover slides were applied with Permount (Fisher). And slides were imaged by bright field microscopy (Nikon TE-2000).

6.3.10. Statistics

Traces represent averages of measurements made in triplicate (n=3). Bar graphs show mean values

± standard error. Standard significance thresholds were used to define statistical differences (e.g.,

P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****). Comparisons of three or more independent groups were analyzed by ordinary 1-way or 2-way ANOVA with multiple comparison tests as noted.

Statistical analysis was performed with GraphPad Prism 8 software.

6.4. Results and discussion

6.4.1. Formulation of hydrazone CANs with consistent shear moduli

The alkyl-hydrazone and benzyl-hydrazone crosslinks have different forward (k1) and reverse (k-1) reaction rates, and this leads to differences in the chemical equilibria and the rates of crosslink

176 reorganization in co-poly(alkyl-benzyl-hydrazone) CANs (Fig. 6.3) [43]. By varying the molar ratio of alkyl-hydrazone (Fig. 6.3a) to benzyl-hydrazone (Fig. 6.3b) crosslinks, the viscoelastic properties of the resulting hydrogels can be tuned in a user-defined manner [38]. To form hydrazone hydrogels, we synthesized 8-arm tripentaerythritol PEG macromers (Mn ~ 10 kDa) with reactive hydrazine, alkyl- aldehyde, and benzaldehyde end groups. Three CAN formulations were designed to achieve a range of viscoelastic properties, based on Flory-Stockmayer percolation theory (Eq. 6.1) [50]. Here the percolation threshold (pc) represents the fraction of crosslinks required to form a percolating network, which depends on the stoichiometric ratio (r = [Nu] / [El]) and the functionality (f) of each type of reactive macromer. The most viscoelastic condition (green) was designed with 78%:22% alkyl-hydrazone to benzyl-hydrazone crosslinks, accounting for network non-idealities and ensuring that all three conditions contained a percolating network of stable benzyl-hydrazone crosslinks which provide stability for long term cell culture experiments. The most elastic condition was formulated with 0%:100% alkyl-hydrazone to benzyl- hydrazone) crosslinks (purple), and a mixed condition, composed of 61%:39% alkyl-hydrazone to benzyl- hydrazone crosslinks (blue), was included to further probe the experimental space.

Equation 6.1

1 pc = Eq. 6.1 √r(fNu‐1)(fEl‐1)

Hydrogels were formulated to minimize differences (Fig. 6.3c) in the final shear moduli (G∞) and isolate the effects of viscoelastic crosslink rearrangement from the overall crosslinking density [19,51].

Gelation was monitored by time sweeps, measuring the shear storage (G’) and loss (G’’) moduli as a function of time after mixing hydrazine and aldehyde functionalized PEGs. Data illustrate characteristic step-growth polymerizations of hydrazone CANs (Fig. 6.3d). The gelation point is defined here as the time required to measure a storage modulus greater than the loss modulus (G’ > G’’), with an additional threshold of G’ ≥ 10 Pa to account for instrument error. The gelation point was delayed for the elastic 0% CANs relative to the other two conditions, containing alkyl-hydrazone crosslinks (39% and 78%), due to the

177 slower kinetics of formation of benzyl-hydrazone bonds at neutral pH (Fig. 6.3e) [52]. However, all three conditions consistently formed gels within two minutes of mixing precursor solutions, illustrating gelation timescales relevant for cell encapsulation.

Figure 6.3 Gelation of alkyl-hydrazone and benzyl-hydrazone CANs. (a) Dynamic alkyl-hydrazone (green) crosslinks formed by reaction of alkyl-aldehyde (yellow) functionalized PEG with hydrazine (blue) functionalized PEG. (b) Stable benzyl-hydrazone (purple) crosslinks formed by the reaction of benzaldehyde (red) functionalized PEG with hydrazine (blue) functionalized PEG. (c) The final G∞ was

2 2 (1/2) statistically the same across all formulations. G∞ = [(G′) + (G′′) ] with plateau values (ΔG′/Δt ≈

ΔG′′/Δt ≈ 0) for each of the three hydrazone hydrogel conditions. (d) In situ gelation was monitored by a time sweep, showing shear storage (G’) and loss (G’’) moduli over time. (e) Gelation points for hydrazone

CANs were measured at ω = 1 rad s-1 and γ = 1%. Gelation point is defined here as the time required to measure a storage modulus greater than the loss modulus (G’ > G’’), with an additional threshold of G’ ≥

10 Pa to account for instrument error. Traces represent average measurements made in triplicate (n=3) with standard error where appropriate. Statistics represent the results of one-way ANOVA with Tukey's multiple

178 comparisons test (MCT) showing P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***,

P < 0.0001 = ****.

6.4.2. The dynamic viscoelastic properties of hydrazone CANs

Viscoelasticity is defined as a materials tendency to elastically resist mechanical deformation while also dissipating energy [53]. Transient step-change rheometry was used to quantify differences in the viscoelastic behavior of the 78%, 39% and 0% alkyl-hydrazone CANs (Fig. 6.4). First, stress relaxation was measured as a function of time (t) (Fig. 6.4a). Normalized shear stress (σ/σmax) was fit to a two element stretched exponential model (Eq. 6.2) to estimate time constants (τ) and stretching parameters (β) for alkyl

(a) and benzyl (b) hydrazone crosslinks as a function of their molar composition (X).

Equation 6.2

σ t βa t βb = Xa exp (‐ ( ) ) + Xb exp (‐ ( ) ) Eq. 6.2 σ0 τa τb

Average relaxation times (<τ>) were then calculated (Eq. 6.3) as characteristic relaxation timescales for each of the three hydrazone CAN formulations (Fig. 6.4b) [54].

Equation 6.3

X τ 1 X τ 1 〈τ〉 = a a Γ ( ) + b b Γ ( ) Eq. 6.3 βa βa βb βb

The average relaxation time for the most elastic 0% condition was statistically different from the two viscoelastic conditions (39%, 78%). The percentage of the maximum stress relaxed over a six hour period was also quantified to further illustrate differences in viscoelastic stress relaxation (Fig. 6.4c). The

78%, 39% and 0% alkyl-hydrazone CANs relaxed 89 ± 0.36%, 69 ± 1.3%, and 28 ± 7.5% of the initial stress, respectively. Next, the creep compliance (J) was measured over time (Fig. 6.4d), and the average creep compliance rate (1/<η>) for each network was calculated by subtracting the immediate elastic compliance response (J0) (Eq. 6.4).

179

Equation 6.4

t J‐J = Eq. 6.4 0 〈η〉

The results closely corresponded to differences observed during stress relaxation experiments. The viscoelastic conditions exhibited statistically significant creep compliance behavior relative to the elastic

0% condition (Fig. 6.4e). The 78%, 39% and 0% CANs also demonstrated different levels of physical deformation in response to the constant shear stress, corresponding to 5.20 ± 0.33%, 2.46 ± 0.31%, and

0.44 ± 1.48% strain (γ), respectively (Fig. 6.4f).

Native articular cartilage also demonstrates viscoelastic creep compliance and stress relaxation

[55]; however, cartilage explants typically have viscoelastic timescales on the order of 100 -1800 s [56].

These timescales are much faster than the timescales reported here for our hydrazone CANs. While these specific hydrazone CAN formulations are not biomimetic [57], incorporating time-dependent material properties, such as stress relaxation and creep, can still be valuable for controlling chondrocyte behavior for in vitro cartilage tissue engineering [58]. Cartilage tissue engineering is a complex process, which does not necessarily require matching the exact properties of the native tissue. For example, after Engler et al. discovered that matrix elasticity can direct stem cell lineage specification, early mechanobiological research focused on elastic moduli [59]. However, attempting to match the high elastic modulus of articular cartilage can inhibit the regenerative behavior of chondrocytes when encapsulated in non-degradable 3D hydrogels

[60], often impeding integration with the surrounding tissue [61]. Such discrepancies illustrate the need for materials platforms to better recapitulate the extracellular microenvironment, and further optimize viscoelastic mechanobiological cues specific for chondrocytes and cartilage tissue engineering. Hydrazone

CANs offer one well-defined viscoelastic platform to study chondrocyte behavior for these purposes.

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Figure 6.4 Shear rheometry was used to measure the viscoelastic responses of hydrazone CANs to step- changes. (a) Differences in viscoelastic stress relaxation between hydrazone CANs represented by variations in the normalized shear stress (σ/σmax) over time compared to model fits. (b) Average relaxation times (<τ>) represent the characteristic network reorganization timescales for each formulation. Stress relaxation data was fit with the Kohlrausch–Williams–Watts stretched exponential function (Equation 2) followed by integration to calculate the average relaxation times (Equation 3). (c) Hydrazone CANs relax different amounts of the initial stress over the course of 6 hours. (d) Differences in viscoelastic creep compliance (J) between hydrazone hydrogel formulations over time compared to model fits. (e) Linear average creep rates (<1/η>) as a function of hydrogel compositions. The creep compliance data were fit to

(Equation 4), excluding initial creep ringing. (f) Hydrazone CANs were strained by different amounts over the course of 2 hour creep tests, and the final strain (γ) was plotted as a function of network composition.

Traces represent average measurements made in triplicate (n=3) with standard error where appropriate.

181

Statistics represent the results of one-way ANOVA with Tukey's MCT showing P ≥ 0.05 = ns, P < 0.05 = *,

P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****.

To further characterize the viscoelastic properties of hydrazone CANs, SAOS rheology was used to measure the storage (G’) and loss moduli (G’’) as a function of frequency (ω) and amplitude (γ) (Fig. 6.5).

Here, the loss tangent (tan(δ) = G’’ / G’) is used to quantify the relative contributions of viscous and elastic behaviors, where higher loss tangents reflect greater viscoelasticity. Hydrazone CANs have higher loss tangents with decreasing angular frequency (Fig. 6.5a), which suggests that hydrazone CANs behave more viscously over long timescales and more elastically over short timescales. For example, at high frequencies

(ω = 10 rad s-1), the loss tangents were not significantly different and very small (< 2.0 x 10-3), indicating that these hydrazone CAN formulations may be approximated as ideal elastic solids during rapid deformation (Fig. 6.5c). These results are useful for cartilage tissue engineering in load-bearing joints where hydrogel scaffolds must withstand rapid compressive forces from walking, running, and jumping [62]. To confirm this assumption, acellular 100% alkyl-hydrazone and 100% benzyl-hydrazone (i.e. 0% alkyl- hydrazone) CANs were subjected to a physiologically relevant dynamic compression cycle (20% strain, 1

Hz, 1 hour) and the uniaxial force response was measured over time (Fig. 6.S1). These tests showed relatively small declines in the final force response for both conditions, further suggesting that both alkyl- hydrazone and benzyl-hydrazone CANs respond elastically during rapid deformation. Importantly, this is not the case for shear rheology at low frequencies (ω = 0.001 rad s-1), where each of the three hydrazone

CANs were significantly different from each other (Fig. 6.5b). This property may also be beneficial for cartilage tissue engineering, as cellular processes such as matrix deposition occur over long timescales, which correspond to small frequencies [63].

All three of the hydrazone CAN formulations investigated in this work demonstrated strain-dependent behavior (Fig. 6.5d). At low strains, the storage (G’) and loss moduli (G’’) were constant. However, as the strain exceeded a critical threshold, the storage modulus declined and the loss modulus rose, resulting in strain-dependent crossovers (tan(δ) = 1). The crossover points were not significantly different between

182 conditions, occurring between 200% and 300% strain (Fig. 6.5e). Time sweeps were performed after the strain sweeps to ensure that the disassociation of dynamic hydrazone crosslinks was responsible for this shear-thinning behavior. All three conditions showed full recovery of the pre-strain moduli, illustrating that the shear-thinning behavior was non-destructive (Fig. 6.5f) and not the result of breaking PEG chains. These results could be particularly relevant for enabling minimally invasive injectable delivery of chondrocytes for cartilage tissue engineering [64], or may prove useful for 3D bioprinting [65], and additive manufacturing [66].

Figure 6.5 SAOS rheometry to quantify frequency and strain dependent behavior of hydrazone CANs. (a)

Frequency sweep spectra illustrate differences in the storage moduli (G’), loss moduli (G’’), and loss tangents (tan(δ) = G’’ / G’) as a function of angular frequency (ω) at constant strain (γ = 1%). (b) Differences between the low frequency loss tangents of hydrazone CANs (ω = 0.001 rad s-1). (c) Measurements of the high frequency loss tangents of hydrazone CANs were not significantly different (ω = 10 rad s-1). (d)

Amplitude sweeps illustrate the shear-thinning behavior of hydrazone CANs. Data represent the storage moduli (G’), loss moduli (G’’), and loss tangent (tan(δ) = G’’ / G’) as a function of strain (γ) at constant

183 angular frequency (ω = 1 rad s-1). (e) Each of the three hydrogel conditions showed similar strain-dependent crossovers (tan(δ) =1). (f) Quantification of the pre-strain modulus recovery illustrates that shear-thinning behavior is non-destructive. Percent recovery was calculated using the shear modulus after strain sweeps, expressed as a percentage of the shear modulus before strain sweeps as measured by time sweeps (ω = 1 rad s-1, γ = 1%). Traces represent average measurements made in triplicate (n=3) with standard error where appropriate. Statistics represent the results of one-way ANOVA with Tukey's MCT showing P ≥ 0.05 = ns,

P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = ****.

6.4.3. Hydrazone CANs maintain encapsulated chondrocyte populations during dynamic compression

After characterizing the viscoelastic properties of the hydrazone CANs, we next sought to verify if these formulations would maintain chondrocytes during physiologically relevant compression. Primary porcine chondrocytes were encapsulated at ~20 million cells per milliliter in hydrazone CANs (D = 5 mm, t= 3 mm) [17]. Chondrocyte-laden hydrazone CANs were loaded into custom-built dynamic compression bioreactors four days after encapsulation (Day 4) [14]. Briefly, bioreactors were controlled by a programed sinusoidal waveform, precisely raising and lowering a platform equipped with permeable pins.

Chondrocyte-laden hydrazone CANs (78%, 39%, and 0% alkyl-hydrazone crosslinks) were immersed in culture medium within 24-well plates on top of permeable well inserts. The compression regime was selected to be physiologically relevant, with daily cyclic compression for 1 hour at 1 Hz and 15% strain [9].

Compressive regiments were separated into two primary modes simulating activity and rest. The active mode was designed to simulate walking by applying a cyclic 15% unconfined compressive strain [67], once a second (1 Hz), based on average walking speed and gait size [68]. Average daily step estimates translate to approximately two hours of walking per day [69]. To simulate reduced activity during patient recovery, this was reduced to 1 hour per day [70]. We exposed chondrocyte-laden hydrazone CANs to this cycle for

4 weeks [67].

184

To track changes in chondrocyte populations over time during dynamic compression, the total number of chondrocytes in each hydrogel was quantified (Fig. 6.6) with a DNA assay. The initial seeding density was kept constant between the hydrazone formulations. The chondrocyte populations were generally similar in both the free-swelling controls (Fig. 6.6a) and during dynamic compression culture (Fig. 6.6b) over the entire experimental time course. These results suggest that the dynamic compression regime did not adversely affect chondrocyte survival or proliferation in hydrazone CANs.

Figure 6.6 Chondrocyte populations in free swelling (a) and dynamically loaded (b) hydrazone CANs over time. The number of chondrocytes per hydrogel formulation was calculated using a DNA assay and plotted as a function of time. Data from four CANs were averaged for each condition (n = 4) with standard error.

Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns,

P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***, P < 0.0001 = **** for differences between hydrogel conditions and Dunnett's MCT where P < 0.05 = +, P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++ for differences with respect to Day 3 levels within each hydrogel formulation.

6.4.4. Viscoelasticity improves the expression of articular cartilage specific genes

185

Compressive mechanical stimuli are often associated with positive changes in chondrogenic gene expression [12]. To test this phenomena in hydrazone CANs, gene expression of Collagen X (COL10A1),

Collagen I (COL1A1), Matrix Metalloproteiase 13 (MMP13), SRY-box Transcription Factor 9 (SOX9), and Collagen II (COL2A1) were investigated by qPCR (Fig. 6.7). Relative mRNA expression was double normalized first by the house keeping gene glyceraldehyde-3-phosphate dehydrogenase (GAPDH) (Fig.

6.S2) then by the 0% elastic control.

First, we examined the relative gene expression three days after encapsulation and before dynamic compression to establish baseline differences between hydrazone CANs with varied viscoelastic properties

(Fig. 6.7a). We found that COL10A1 and MMP13 were significantly downregulated in the viscoelastic

39% and 78% hydrogels relative to the 0% elastic control. These data suggest that viscoelasticity may help maintain the articular phenotype as COL10A1 and MMP13 are markers of chondrocyte hypertrophy, and their upregulation is often associated with osteoarthritis [71,72]. This finding is also consistent with prior literature where mechanical confinement in less viscoelastic microenvironments resulted in upregulation of

MMP13 [58]. Additionally, polymeric scaffolds with higher energy dissipation have been previously shown to improve expression of chondrogenic markers [21].

Next, we sought to investigate if dynamic compression influences chondrocyte gene expression in viscoelastic hydrazone CANs (Fig. 6.7b). After one week of dynamic compression (Day 10), chondrocytes encapsulated in the viscoelastic hydrogels (39%, 78%) showed even more significantly reduced COL10A1 expression relative to the 0% condition. However, dynamic compression reduced differences in MMP13 expression, which has also been observed by others [73]. Dynamic compression also seemed to down- regulate COL2A1 expression and up-regulated COL1A1. Taken together, these data suggest that viscoelasticity is beneficial for maintaining chondrocyte phenotype during free swelling culture, however, the effect of dynamic compression on chondrocyte gene expression in viscoelastic hydrazone CANs remains unclear.

186

Figure 6.7 Relative mRNA expression of articular cartilage specific genes. Gene expression was investigated three days (Day 3) after encapsulation (a) and after one week (Day 10) of dynamic compression

(b). Data represent expression of genes encoding for Collagen X, Collagen I, MMP13, Sox9, and Collagen

II. Data from four hydrogels were averaged for each condition, excluding samples which did not provide reliable amounts of mRNA (n=2-4) showing mean and standard error. Data were double normalized first to GAPDH expression and then to the 0% condition. Statistical significance represents the results of two- way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***,

P < 0.0001 = ****.

6.4.5. Viscoelasticity of hydrazone CANs influences the effects of dynamic mechanical compression on chondrocyte biosynthesis

While scaffolds used for cartilage tissue engineering must provide mechanical support to resist physiological compression [74], the embedded chondrocytes must also be able to deposit ECM in order to

187 replace the scaffold with neocartilaginous tissue [75]. Here, we investigated ECM deposition by encapsulated chondrocytes to gauge whether hydrazone CANs would facilitate uniform cartilaginous matrix secretion during dynamic compression.

Collagens are fibrillar proteins which are primarily responsible for the shape and microarchitecture of articular cartilage [76]. sGAGs are a major component of proteoglycans, like aggrecan, which are responsible for retaining water and providing compressive strength [77]. Biochemical assays and histological staining were used to study the deposition of these two key cartilage matrix molecules and assess the development of neocartilaginous tissue over time (Fig. 6.8). The effects of dynamic compression are often more pronounced at later time points, as it takes weeks for neotissue to develop within hydrogel networks [8]. We observed significant differences in both collagen and sGAG content between viscoelastic and elastic formulations (Fig. 6.S3) after four weeks of bioreactor culture [38,58]. We also observed increased matrix in the 39% alkyl-hydrazone condition with intermediate levels of crosslink adaptation during both free swelling and dynamic compression culture.

To better understand biosynthesis by chondrocytes in hydrazone CANs, linear regression analysis

(Fig. 6.S4) was performed to extract the rates of collagen (Fig. 6.8a) and sGAG (Fig. 6.8c) deposition over the experimental time course. Strikingly, we observed reversed effects from dynamic compression in viscoelastic and elastic hydrazone CANs (Table 6.2). Dynamic compression improved matrix biosynthesis in elastic 0% alkyl-hydrazone hydrogels, showing 127 ± 16% collagen deposition and 117 ± 22% sGAG deposition relative to free swelling controls. This effect was reversed for the viscoelastic 78% alkyl- hydrazone hydrogels, where dynamic mechanical compression reduced collagen deposition rates to 71 ±

12% and sGAG deposition rates to 75 ± 16% of free swelling levels. In 78% alkyl-hydrazone CANs, these differences resulted in a statistically significant reduction in collagen matrix production during dynamic compression. A similar phenomenon has been observed previously where degradation improved the deposition of collagen and sGAGs in (un)loaded constructs but not during dynamic compression [67].

However, we do not expect degradation to be the main factor in these networks as all three conditions (78%,

188

39%, and 0%) contain benzyl-hydrazone crosslinks well above the percolation threshold. To confirm this hypothesis, we measured compressive Young’s moduli for each condition over time (Fig. 6.S5). The moduli of chondrocyte-laden constructs subjected to dynamic compression were normalized by their respective free swelling controls. These data show that dynamic compression slightly increases the compressive modulus in all three conditions, although differences were not significant. These results imply that dynamic loading did not cause excessive degradation in the most viscoelastic 78% condition and cannot account for reduced matrix deposition rates. Further, this finding supports load-inhibition rather than transport phenomena as the primary mechanism behind matrix reduction in the 78% hydrogels during dynamic compression. Interestingly, we also observed decreased matrix synthesis rates during dynamic compression for the intermediate 39% condition. However, this effect was less pronounced, showing 93 ± 10% and 86

± 14% of free swelling sGAG and collagen deposition rates during dynamic compression. These results match expectations, as both the effect of matrix mechanics [38], and dynamic compression [17], are typically more pronounced for collagens than sGAGs due the kinetics of matrix synthesis as well as diffusion and assembly considerations [78].

Table 6.2 Viscoelastic properties and rates of chondrocyte matrix deposition for hydrazone CANs during free swelling and dynamic compression culture.

Loss tangent Free swelling control Dynamic compression [tan(δ)] [µg day-1] [µg day-1] γ = 15% Collagen sGAG Collagen sGAG ω = 1 rad s-1

78% (1.67 ± 0.09) 10-3 43 ± 3 52 ± 5 30 ± 3 47 ± 7

39% (1.21 ± 0.14) 10-3 36 ± 4 75 ± 6 31 ± 3 70 ± 4

0% (9.03 ± 0.05) 10-4 20 ± 2 38 ± 6 25 ± 3 45 ± 8

The spatial distribution of collagen (Masson’s Trichrome, Fig. 6.8b) and sGAGs (Safranin O, Fig.

6.8d) were also investigated qualitatively by histological sectioning and staining at the final time point (Day

189

31) but the differences between conditions were subtle, albeit consistent with the results from biochemical assays. Importantly, during both free swelling and dynamic compression culture the intermediate 39% condition with moderately viscoelastic properties demonstrated significantly higher sGAG deposition rates than either extreme. This condition also demonstrated robust collagen deposition surpassed only by the free swelling 78% condition. This effect has been previously observed in hydrazone CANs [38], and these results further suggest that a balance between dynamic alkyl-hydrazone crosslinks and stable benzyl- hydrazone crosslinks is most applicable for cartilage tissue engineering.

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Figure 6.8 Interactive effects of mechanobiological cues on chondrocyte ECM deposition. Here blue represents collagen (a-b) and red shows sGAGs (c-d) in hydrazone CANs. Linear regression was used to calculate matrix production rates over the experimental time course showing collagen (a) and sGAG (c) deposition rates (µg day-1) during free swelling and dynamic compression culture. To frame these results in the context of viscoelasticity, data are graphed by the viscoelasticity represented by tan(δ) at 15% strain and 1 rad s-1. This represents the dynamically applied strain at a frequency relevant for cellular

191 mechanosensing [79], which is useful for interpreting how viscoelasticity influences cell-matrix interactions in hydrazone CANs. Bright field microscopy was used to visualize 20 µm histological sections stained with (b) Masson’s Trichrome showing collagen (blue) and (d) Safranin O showing sGAGs (red) with cell nuclei (black/violet). Scale bars represent 15 µm. Data from four CANs were averaged for each condition (n = 4) with data representing mean values with standard error. Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **,

P < 0.001 = ***, P < 0.0001 = **** for differences between hydrogel conditions and Sidak's MCT where P

≥ 0.05 = ns, P < 0.05 = #, P < 0.01 = ##, P < 0.001 = ###, P < 0.0001 = #### for differences between dynamic compression and free swelling conditions.

6.5. Conclusion

Hydrazone covalent adaptable networks (CANs) were synthesized with varied viscoelastic properties

(e.g., stress relaxation, creep compliance, frequency dependence, and shear-thinning) by tuning the molar ratio of alkyl-hydrazone to benzyl-hydrazone crosslinks in PEG hydrogels. Incorporation of adaptable alkyl-hydrazone crosslinks led to significantly reduced expression of hypertrophy markers (COL10A1 and

MMP13). These results suggest that viscoelasticity in hydrazone CANs may be beneficial for maintaining articular cartilage specific phenotypes for cartilage tissue engineering.

We also found that viscoelasticity of hydrazone CANs altered how dynamic mechanical compression influenced rates of matrix deposition by encapsulated chondrocytes. Specifically, dynamic compression improved rates of sGAG and collagen biosynthesis in the elastic benzyl-hydrazone controls (0% alkyl- hydrazone), however, dynamic compression reduced rates of extracellular matrix deposition in viscoelastic

78% and 39% alkyl-hydrazone CANs. Interestingly, sGAG (70 ± 4 µg day-1) and collagen (31 ± 3 µg day-

1) deposition rates were only slightly reduced in the 39% alkyl-hydrazone CANs. This resulted in biphasic behavior with respect to viscoelasticity which further illustrates that intermediate levels of adaptable viscoelasticity may be the most beneficial for cartilage tissue engineering in hydrazone CANs. These results provide insight for how mechanobiological cues influence chondrocytes in hydrazone CANs. Additionally,

192 these experiments support the use of dynamic hydrazone CANs as advanced materials which could provide robust mechanical strength and adaptable viscoelastic properties that are well-suited for cartilage tissue engineering in load-bearing joints.

6.6. Supporting Information

Figure S 6.1 Material response of alkyl-hydrazone and benzyl-hydrazone CANs to dynamic compressive loading. Acellular samples were subjected to unconfined compression in DPBS and the uniaxial force response was measured over time. The cycle was set to 20% strain and 1 Hz for one hour to investigate a physiologically relevant compression cycle. At the end of the hour the normalized force response was compared for fully alkyl-hydrazone and fully benzyl-hydrazone hydrogels showing non-significant differences between maximal force response cycles (n=3). Statistical significance represents the results of an unpaired t-test where P ≥ 0.05 = ns.

193

Figure S 6.2 Relative mRNA expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) three days (Day 3) after encapsulation (a) and after one week (Day 10) of dynamic compression (b). These results verify that the house keeping gene is not affected by the viscoelasticity of hydrazone CANs. Data from four hydrogels were averaged for each condition, excluding samples which did not provide reliable amounts of mRNA (n=2-4) showing mean and standard error. Statistical significance represents the results of two-way

ANOVA with Tukey's MCT where P ≥ 0.05 = ns.

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Figure S 6.3 Quantification of the biochemical collagen (a,b) and sGAG (c,d) content for free swelling controls and dynamic compression culture (1 hour day-1, ε = 15%, ν = 1 Hz). Quantification from hydroxyproline assay is reported assuming hydroxyproline accounts for 13.4% of the amino acid content of collagen in articular cartilage.[80] Quantification from DMMB assay was reported as chondroitin sulfate

(ChS) equivalents per hydrogel. Data from four CANs were averaged for each condition (n = 4) with data representing the mean with standard error. Statistical significance represents the results of two-way

ANOVA with Tukey's MCT where P ≥ 0.05 = ns, P < 0.05 = *, P < 0.01 = **, P < 0.001 = ***,

P < 0.0001 = **** for differences between hydrogel conditions and Dunnett's MCT where P < 0.05 = +,

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P < 0.01 = ++, P < 0.001 = +++, P < 0.0001 = ++++ for differences with respect to Day 3 levels within each hydrogel formulation.

Figure S 6.4 Linear regression analysis for collagen (a-b) and sGAG (c-d) content for free swelling controls and dynamic compression culture. Linear regression was selected after comparing polynomials up to order

6 with extra sum-of-squares F tests where the simpler model is recommended unless P ≤ 0.05.

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Figure S 6.5 Quantification of construct Young’s moduli measured during compression. Average moduli of constructs subjected to dynamic compression (E Dynamic Compression) are represented normalized by their respective free swelling controls (E Free Swelling Control) over the experimental time course. Data from four

CANs were averaged for each condition (n = 4) with data representing the mean with standard error.

Statistical significance represents the results of two-way ANOVA with Tukey's MCT where P ≥ 0.05 = ns.

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Chapter 7 - Conclusions and Recommendations

7. Summary of Findings

The goal of this thesis was to demonstrate how the viscoelastic properties of hydrazone covalent adaptable networks (CANs) may be used to influence encapsulated chondrocytes for cartilage tissue engineering applications. In pursuit of this main objective, hydrazone CANs were synthesized with varied viscoelastic properties using dynamic alkyl-hydrazone and stable benzyl-hydrazone crosslinks, and experiments were designed to study how stress relaxation timescales of hydrazone CANs influences extracellular matrix (ECM) deposition by encapsulated chondrocytes (Chapter 4). Hydrazone CANs with fast relaxing alkyl-hydrazone crosslinks improved cellularity and enhanced ECM deposition with respect to very slowly relaxing benzyl-hydrazone controls. However, to achieve the highest quality neocartilaginous tissue and maintain scaffold integrity, weakly percolating networks of more stable benzyl- hydrazone crosslinks were also required. Finally, relaxation timescales (~3 days) in hydrazone CANs were identified that enabled the deposition of articular cartilage specific matrix molecules. These experiments provide fundamental knowledge as to how chondrocytes respond to differences in hydrazone crosslink adaptability and lend insight as to how viscoelastic stress relaxation of CANs may be beneficial for cartilage tissue engineering.

Building on these findings, we next sought to investigate the morphological effects of creep compliance on chondrocytes encapsulated in hydrazone CANs during mechanical compression (Chapter

5). By altering the rates of adaptation of crosslinks in hydrazone CANs, differences in chondrocyte morphology were quantified over time using in situ deformation microscopy. Results showed that chondrocytes encapsulated in hydrazone CANs returned to their native rounded morphologies during the application of compressive strain, and this correlated to the viscoelastic creep compliance. Additionally, pericellular ECM deposition was influenced by the viscoelastic properties of the hydrazone CANs. We

205 posited that ECM deposition reduces the biophysical transmission of compressive strain to encapsulated chondrocytes. Importantly, we found that matrix deposition and viscoelastic creep compliance improved the relative expression of cartilage-specific matrix molecules, namely the ratio of collagen type II to collagen type I. Collectively, these finding suggest that the viscoelasticity of hydrazone CANs influences how chondrocytes respond to deformation, and may circumvent some of the detrimental effects of sustained loading.

Our next objective focused on investigating how viscoelasticity of hydrazone CANs might influence chondrocyte biosynthesis during physiologically relevant dynamic compression (Chapter 6). To study this, chondrocyte-laden hydrazone CANs were loaded into dynamic compression bioreactors, and a cyclic compression regime was used to simulate compression experienced by chondrocytes in articulating joints.

The viscoelasticity of the hydrazone CANs altered how mechanical compression influenced chondrocyte gene expression and rates of ECM deposition. Specifically, viscoelasticity improved articular cartilage specific gene expression, showing down regulation of the hypertrophic markers COL10A1 and MMP13.

We also found that viscoelasticity of hydrazone CANs altered how dynamic mechanical compression influenced rates of matrix deposition by encapsulated chondrocytes. Together, these results may help to inform the design of polymer matrices for cartilage tissue engineering and help to better understand the role of matrix properties and adaptability on chondrocyte behavior in vivo.

7.1. Implications

In recent years, growing emphasis has been placed on the role of matrix mechanics and viscoelastic mechanobiology to design advanced biomaterials for cell and tissue engineering [1]. The biomaterials applications of CANs have expanded rapidly in recent years, leveraging the dynamic reversibility of covalent crosslinks to control cell behavior [2]. The hydrazone CANs engineered in Chapter 4 provide a well-defined viscoelastic cell culture platform for studying the effects of mechanobiological cues on encapsulated chondrocytes. These poly(ethylene glycol) (PEG)-based hydrogels offer chemically and biologically inert properties [3] and are capable of maintaining chondrocyte phenotype during 3D culture

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[4]. Additionally, by modifying PEG macromers with reactive hydrazine, alkyl-aldehyde, and benzaldehyde moieties, hydrazone CANs were formulated with user-defined control over their viscoelastic properties based on the molar percentages of alkyl-hydrazone and benzyl-hydrazone crosslinks. This material system was developed and exploited to understand how viscoelastic material properties, such as stress relaxation, may influence chondrocyte behavior. While other viscoelastic cell culture platforms have been used to study chondrocyte behavior (e.g., calcium-alginate hydrogels) [5], these hydrazone CANs offer a complementary approach with tailorable moduli and relaxation kinetics. Additionally, Chapter 4 demonstrates how adaptation of covalent crosslinks can be used to enable ECM deposition by encapsulated chondrocytes.

Covalent crosslinks provide mechanical strength for cartilage tissue engineering applications in load- bearing joints [6], and these hydrazone CANs were further employed to elucidate how mechanical deformation affects chondrocyte behavior (Chapter 5). In situ imaging of chondrocyte-laden hydrogels revealed that viscoelasticity directly impacts chondrocyte morphology, matrix secretion, proliferation, and gene expression during deformation. These findings may have important implications, as each of the aforementioned readouts are known to impact osteoarthritis [7] and tissue regeneration [8]. In addition, continued investigations with hydrazones and other CANs may help improve the design of advanced scaffolds for cartilage tissue engineering in load-bearing joints.

Combining the findings from Chapters 4 and 5, we next sought to understand how dynamic compression, chondrocyte deformation, and viscoelastic covalent adaptability influence chondrocyte gene expression, matrix deposition and neocartilaginous tissue evolution (Chapter 6). Medical treatments often fail during clinical trials despite promising early research [9], and it is prudent to test the efficacy of new biomaterial technologies thoroughly in vitro before attempting to move in vivo. Here, dynamic compression bioreactors were used to simulate physiologically relevant mechanical stimuli. Incorporation of adaptable alkyl-hydrazone crosslinks led to significantly reduced expression of hypertrophic gene expression markers. These results suggest that viscoelasticity in hydrazone CANs may be beneficial for maintaining

207 articular cartilage specific phenotypes for cartilage tissue engineering. Viscoelasticity of hydrazone CANs also altered how dynamic mechanical compression influenced rates of matrix deposition by encapsulated chondrocytes. Specifically, dynamic compression improved rates of biosynthesis in the elastic controls, however, dynamic compression reduced rates of extracellular matrix deposition in viscoelastic hydrazone

CANs. Interestingly, matrix deposition rates were only slightly reduced in hydrazone CANs with intermediate levels of adaptable viscoelasticity which further suggests that a balance between adaptable alkyl-hydrazone and stable benzyl-hydrazone crosslinks may be most beneficial for cartilage tissue engineering.

Collectively, these revelations could help identify biomaterial cell-carriers (e.g., viscoelastic

CANs) that would be most beneficial for matrix-assisted autologous chondrocyte transplantation (MACT) to treat osteoarthritis [10]. Taken together, this thesis research has contributed to a better understanding as to how viscoelastic matrix cues provided by hydrazone CANs influence chondrocyte morphology, gene expression, proliferation, secretory properties, and the development of neocartilaginous matrix, all of which are important to promote tissue regeneration.

7.2. Future Directions

7.2.1. Investigate chondrocyte response to a wide range of dynamic loading frequencies and compressive strains in hydrazone CANs

This thesis focused on understanding how the viscoelastic properties of hydrazone CANs influence the behavior of encapsulated chondrocytes. In experiments related to Aim 3 (Chapter 6), chondrocyte-laden hydrazone CANs were subjected to a single physiologically relevant dynamic compression regime. The results provided insights into the complex interplay between cell-deformation, gene expression, and matrix synthesis when the surrounding matrix microenvironment can relax applied stresses. In particular, the results revealed how chondrocytes in hydrazone CANs responded to a cyclic 15% strain applied at 1 Hz for one hour each day. However, chondrocytes in vivo experience varied dynamic compressive stimuli over a

208 range of strains, frequencies, and durations [11]. Indeed the viscoelastic properties of hydrazone CANs studied in this thesis illustrate how different material properties of hydrazone CANs can influence chondrocytes as a function of strain, frequency, and deformation timescales.

To better understand how the material properties of hydrazone CANs influence chondrocytes for cartilage tissue engineering, future work might examine a wider range of dynamic stimuli. For example, given the viscoelastic properties of hydrazone CANs, one might examine 0.003 Hz, 0.03 Hz, 0.3 Hz, and 3

Hz to further elucidate how chondrocytes experience dynamic stimuli in hydrazone CANs [12]. Similarly, a broader range of dynamic strains of 5%, 10%, 20% and 30% might be appropriate to probe the physiologically relevant experimental space and expand scientific understanding of hydrazone CANs for cartilage tissue engineering [13,14]. Lastly, the loading cycle could be tuned (e.g., multiple cycles per day, cycles longer than 1 hour) to simulate sustained exercise. Such experiments could potentially lend insights about how the viscoelastic properties of hydrazone CANs may alleviate cellular stresses associated with sustained loading, which can contribute to osteoarthritis disease progression in load-bearing joints.

7.2.2. Hydrazone CANs as bioinks for 3D bioprinting to promote shape-specific cartilage regeneration

The dynamic viscoelastic properties of hydrazone CANs make them interesting candidates for additive manufacturing strategies to fabricate shape-specific cartilage. For example, Wang et al. demonstrated the use of dynamic hydrazone crosslinked hyaluronic acid hydrogels for extrusion bioprinting with fibroblast cells [15]. Future studies could apply the PEG-hydrazone CAN platform used in this thesis to develop chondrocyte-laden hydrazone CAN bioinks, which would allow filling of cartilage defects with shape-specific hydrogel matrices. The rheological characterization in this thesis may provide useful information for tailoring the viscoelastic properties of hydrazone CANs for this application. Additionally, microrheology could be employed to provide further insights about how the local properties differ from the bulk properties [16]. Future work might also focus on synthesizing PEG macromers with other hydrazines and aldehydes beyond the alkyl and benzyl derivatives studied here, in this manner a wider range of

209 reversible hydrazone kinetics could be achieved. This may be particularly useful when tailoring hydrazone

CANs for 3D printing [17]. Alternatively, small molecule catalysts could be used to influence the kinetics of the hydrazone CANs, and these have been widely reported in the literature for other applications [17].

For 3D printing, a cytocompatible small molecule catalyst could be used to temporally modulate the shear- thinning behavior of hydrazone CANs, resulting in more viscous behavior during printing and more elastic behavior after printing due to catalyst diffusion [18].

7.2.3. Investigate alternative cell sources for cartilage tissue engineering in hydrazone CANs

The scope of this thesis was limited to studying primary chondrocytes in hydrazone CANs.

However, donor sources can be limited and monolayer expansion can result in dedifferentiation [19]. To address these concerns, undifferentiated progenitor cell types can be used as alternatives for cartilage tissue engineering. For example, mesenchymal stem cells, or medicinal signaling cells, (MSCs) [20], adipose- derived stem cells (ADSCs) [21], and induced pluripotent stem cells (iPSCs) [22] are attractive candidates due to their relative abundance and chondrogenic potential. Studying the differentiation of these progenitor cells within hydrazone CANs as a function of the viscoelasticity could be done alone or in conjunction with other cell types. Such studies may yield interesting information about how different cells respond to mechanobiological cues and likely broaden the applicability of hydrazone CANs for cartilage tissue engineering.

7.2.4. Hydrazone CANs to heal cartilage defects in a large animal model

Ultimately, this work was intended to provide information about how hydrazone CANs influence chondrocyte behavior to improve polymer matrices for cartilage tissue engineering. However, this thesis explored these phenomena in vitro, and the experiments undertaken as part of this work did not involve transplantation in vivo. Future experiments could leverage the findings of this work and design matrices for animal models to further test the efficacy of hydrazone CANs for cartilage tissue engineering. A large animal (e.g., porcine) model would be beneficial for approximating the biomechanical forces experienced

210 in a human knee joint [23]. For these studies, hydrazone CANs could be formulated based on the optimized conditions identified in Chapter 4 and Chapter 6 with intermediate levels of covalent crosslink adaptation and moderately viscoelastic material properties. Additionally, the shear-thinning properties of hydrazone

CANs discussed in Chapter 6 could prove useful for injectable delivery of chondrocyte-laden hydrazone

CANs to an animal’s joint cavity. Alternatively, the creep compliance behavior studied in Chapter 5 could facilitate the design of a press-fitting chondrocyte delivery system that could fill irregularly shaped cartilage defects.

Figure 7.1 Macroscopic self-healing behavior of alkyl-hydrazone CANs may enable press-fitting for filling irregularly shaped cartilage defects.

While this thesis provided extensive new knowledge about chondrocyte-matrix signaling, especially in response to viscoelastic properties, there are many opportunities to build on the studies discussed above.

With sustained efforts and additional pre-clinical studies, hydrazones and other CANs could serve an unmet clinical need for advanced biomaterial platforms to improve cartilage tissue engineering-based osteoarthritis treatments.

7.3. References

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