Functionalized Nanofiber Substrates for Nerve Regeneration

ELENA ALEKSANDROVNA SILANTYEVA

A Dissertation

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfillment

of the Requirements for the Degree

Doctor of Philosophy

Elena A. Silantyeva

May 2019 FUNCTIONALIZED NANOFIBER SUBSTRATES FOR NERVE REGENERATION

Elena Aleksandrovna Silantyeva

Dissertation

Approved: Accepted:

______Advisor Department Chair Dr. Matthew L. Becker Dr. Tianbo Liu

______Committee Member Dean of College Dr. Li Jia Dr. Ali Dhinojwala

______Committee Member Dean of the Graduate School Dr. Chrys Wesdemiotis Dr. Chand Midha

______Committee Member Date Dr. Darrell Reneker

______Committee Member Dr. Rebecca Willits

iii ABSTRACT

Peripheral nerve injuries are a significant clinical challenge due to the limited capacity of nerve tissue to regenerate.1 Recently, research has focused its attention on the polymer nanofiber substrates since they mimic ECM topography and can be functionalized with bioactive molecules to overcome the limitations of both naturally occurring proteins and synthetic polymers used in nerve tissue regeneration applications.

In the present work, we have developed poly(ԑ-caprolactone) (PCL) nanofiber substrates, modified with peptides to control the cellular activity. High molecular mass PCLs with a 4- dibenzocyclooctynol initiator was synthesized via ring-opening polymerization using magnesium 2,6-di-tert-butyl-4-methylphenoxide catalyst. The efficient chemical methods of nanofiber surface functionalization, such as strain-promoted azide-alkyne cycloaddition

(SPAAC), developed by the Becker Lab,2 and thiol-ene reaction were utilized to introduce biomolecules.

The dissertation is separated into four parts and demonstrates the combination of topographical cues and surface-tethered bioactive factors in effort to understand the optimal substrates for nerve regeneration or repair. We utilized the two most promising clinical approaches from our point of view for nerve tissue regeneration.

The first approach is the differentiation of stem cells in vitro, described in the first two parts. Substrates that facilitate the differentiation and support long term culture of mature neural cells would advance the field of regenerative medicine. First, we demonstrated that YIGSR-functionalized aligned nanofibers can be potentially used for stem cells neural differentiation in vitro. The commitment and maturity of mESCs on these

iv substrates were characterized using gene and protein expression. Then we compared influence of nanofiber topography and bioactive factors on neural differentiation of mESCs. These results highlight the influence of RGD binding versus topography in differentiation through high levels of glial fibrillary acidic protein expression.

The second approach is improving Schwann cell migration and is described in the last two parts. Improved Schwann cell response on functionalized nanofibers in vitro was demonstrated in our lab.3 In the present study, we examined RGD-functionalized fibers in vivo, on the rat sciatic nerve model and demonstrated enhancement of Schwann cell infiltration and functional outcomes. To further improve Schwann cell migration, we created nanofiber substrates with gradients of bioactive factors along the aligned fiber direction.

All the parts describe efforts to increase control over cellular activity (stem cell neural differentiation or Schwann cell migration) through combination of nanofiber topography and chemically tethered bioactive peptides. Each of these studies help to get an insight into optimal tissue engineering constructs for nerve regeneration.

v DEDICATION

I would like to dedicate this work to my sister Nataliya Silantyeva and my parents

Nina and Aleksandr, for their love and support.

vi ACKNOWLEDGEMENTS

During my PhD study I was lucky to meet nice people who improved me a scientist as well as a person. This work could not have been completed without the contribution of many individuals. First and foremost, I would like to express my gratitude to my advisor,

Dr. Matthew L. Becker, who inspires me to be creative and independent thinker, for giving me so many opportunities and always being supportive.

I would like to thank Dr. Willits and her students (Diana Philip, Wafaa Nasir,

Jacqueline Carpenter, Elham Malekzadeh, Galina Pylypiv and McKay Cavanaugh) for teaching me how to work in a collaborative environment, for all the advices and help with biological analysis and interpretation. The work of this dissertation would not be possible without the discussions and collaboration with Dr. Willits.

I would like to thank Dr. Darrell Reneker for helping me with electrospinning and teaching me how to think ‘outside of the box’. I also want to thank my committee members

Dr. Li Jia, Dr. Chrys Wesdemiotis for their advice and constructive feedback to my research. I would like to thank Melissa Bowman, Jacqueline Clark and Marjorie Parrish for their help.

I would also like to expand a big thank you to all Becker group members for collaborative and friendly work environment.

A special thank you to Saranshu Singla, Fadi Haso and Selemon Bekele for helping me in studying for classes and cumulative exams. Ed Laughlin, Jack Gillespie and Bojie Wang for helping me and suggesting ideas.

Finally, I want to thank my family for the constant support.

vii LIST OF ABBREVIATIONS

ACS American Chemical Society ASCs Adipose-derived stem cells bFGF Basic fibroblast growth factor

BMSCs Bone marrow stromal cells

ε-CL ε-Caprolactone CuAAC Copper(I)-catalyzed azide-alkyne cycloaddition

DCM Dichloromethane DIBO 4-Dibenzocyclooctynol DMF N,N-Dimethylformamide DOSY Diffusion ordered spectroscopy DP Degree of polymerization

Đm Molecular mass distribution ECM Extracellular matrix

EPT Extensor postural thrust ESI Electrospray ionization GDNF Glial cell-derived neurotrophic factor

HFIP 1,1,1,3,3,3-hexafluoro-2-propanol HPLC High performance liquid chromatography mESCs Mouse embryonic stem cells

Mn Number average molecular mass

Mw Weight average molecular mass

viii MD% Percentage of motor deficit %MPE Percent maximal possible effect NGC Nerve guidance conduits

NGF Nerve growth factor

NIH National Institutes of Health NMR Nuclear magnetic resonance PBS Phosphate-buffered saline PCL Poly(ε-caprolactone)

PLGA Poly(lactic-co-glycolic acid)

PLLA Poly(L-lactide)

PNI Peripheral nerve injury qPCR Quantitative polymerase chain reaction RGMW Relative gastrocnemius muscle weight SC Schwann cell

SEC Size exclusion chromatography SEM Scanning electron microscopy SFI Sciatic functional index SPAAC Strain-promoted azide-alkyne cycloaddition

THF Tetrahydrofuran TLC Thin-layered chromatographic analysis

ix TABLE OF CONTENTS

LIST OF TABLES ...... xiii

LIST OF FIGURES ...... xiv

CHAPTER I. INTRODUCTION ...... 1

1.1. Peripheral nerve injury and its treatment ...... 1

1.2. Stem cell differentiation for nerve injury treatment ...... 4

1.3. Electrospun scaffolds for cell culture in nerve regeneration ...... 4

1.4. Touch-spinning ...... 6

1.5. Strain-Promoted Azide-Alkyne Cycloaddition (SPAAC) ...... 6

II. MATERIALS AND INSTRUMENTATION ...... 9

2.1. Materials ...... 9

2.2. Instrumentation ...... 10

III. ACCELERATED NEURAL DIFFERENTIATION OF MOUSE EMBRYONIC STEM

CELLS ON ALIGNED GYIGSR-FUNCTIONALIZED NANOFIBERS ...... 13

3.1. Abstract ...... 13

3.2. Introduction ...... 14

3.3. Experimental ...... 16

3.4. Results ...... 26

3.5. Discussion ...... 36

3.6. Conclusions ...... 42

3.7. Acknowledgement ...... 43

x IV. RGD-FUNCTIONALIZED NANOFIBERS INCREASE EARLY GFAP EXPRESSION

DURING NEURAL DIFFERENTIATION OF MOUSE EMBRYONIC STEM CELLS ...... 44

4.1. Abstract ...... 44

4.2. Introduction ...... 45

4.3. Experimental ...... 47

4.4. Results ...... 57

4.5. Discussion ...... 70

4.6. Conclusion ...... 76

4.7. Acknowledgement ...... 77

V. RGD-MODIFIED NANOFIBERS ENHANCE FUNCTIONAL OUTCOMES IN RATS

AFTER SCIATIC NERVE INJURY ...... 78

5.1. Abstract ...... 78

5.2. Introduction ...... 79

5.3. Experimental ...... 81

5.4. Results ...... 90

5.5. Discussion ...... 97

5.6. Acknowledgement ...... 100

VI. GRADIENT-MODIFIED ALLYL-POLY(Ԑ-CAPROLACTONE) ALIGNED

NANOFIBERS AS A PLATFORM FOR CELL MIGRATION ...... 102

6.1. Abstract ...... 102

6.2. Introduction ...... 102

6.3. Materials and methods ...... 104

6.4. Results ...... 109

6.5. Summary ...... 113

xi 6.6. Acknowledgements ...... 114

VII. CONCLUSION ...... 115

REFERENCES ...... 117

APPENDIX A-SUPPORTING FIGURES ...... 149

APPENDIX B-SUPPORTING SCHEMES AND TABLES ...... 170

xii LIST OF TABLES

Table Page Number

3.1. Primers used for real time qPCR with accession numbers, forward and reverse sequences...... 24

4.1. Summary of genes and their sequence utilized for gene analysis ...... 54

8.1. Optimal concentrations and efficiencies of primers used for real time qPCR...... 170

xiii LIST OF FIGURES

Figure Page Number

1.1. Strategies for improving existing hollow nerve guidance conduits. Adapted with permission from ref.1 Copyright Journal of the Royal Society Interface 2012...... 2

3.1. Nanofibers were fabricated by electrospinning from a solution of DIBO-terminated poly(ε-caprolactone) in HFIP (17% w/v) and a voltage of 15 kV. (A) Highly aligned nanofibers were collected on cover glasses in the gaps of metal collector plate. (B) Analysis of SEM images was performed to estimate topography of nanofibers. NIH ImageJ was used to estimate fiber diameter (ᴓ = 212 ± 63 nm) and alignment (DirectionalityTM plugin, average angle = 0 ± 6°). (C) Post-electrospinning modification with GYIGSR peptide via strain-promoted azide-alkyne cycloaddition. The concentration of peptide (17.3 ± 6.6 pmol/cm2) was measured using (D) UV– visible spectrophotometry by comparison of absorbance at 306 nm (peak corresponding to DIBO groups) before (red curve) and after (black curve) post- electrospinning modification based on calibration curve of DIBO in chloroform. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) ...... 28

3.2. Comparison of gene expression of D3 mESCs cultured on GYIGSR-functionalized aligned nanofibers and laminin-coated glass at day 1, 3,7 and 14. Expression of neural progenitor (Nes, Sox1, Pax6) and neuronal (Tubb3, Map2, Cdh2, Th, Gap43, Syp) as well as glial (Foxo4, Olig1, Gfap) gene markers demonstrated that aligned GYIGSR-functionalized nanofiber scaffolds have similar neuronal differentiation into neural lineage compared to laminin-coated glass. No significant differences were found between fibers and laminin glasses in most of the gene expression, with similar differentiation states at day 7 and day 14. Two exceptions of higher expression of neuronal genes on aligned GYIGSR fiber scaffolds at earlier time points were Sox1 at day 1 and Cdh2 at day 3 and day 7. ● indicates statistically significant difference (p < 0.05) in comparison to the previous time point for the same substrate, * indicates that gene expression on fibers is statistically significantly different (p < 0.05) than on laminin for the same time point...... 30

3.3. Protein expression during differentiation on YIGSR-aligned fibers and laminin over 14 days. Displayed images are from the 3rd quartile of fluorescent intensity for each protein. Expression is noted as typical for pluripotent state (SSEA-1, POU5F1), neural progenitors (NES, SOX1) neural (TUBB3, MAP2, GAP43) and glial cells (GFAP, OLIG1, CNPase), scale bars = 100 mm. Images indicate similar neural xiv differentiation on (A) aligned GYIGSR-functionalized nanofiber scaffolds and (B) laminin glasses but with faster rates on fibers (earlier expression of NES, TUBB3, MAP2 and GAP43 on aligned fibers). ICC images were enhanced (+40% brightness, +20% contrast)...... 32

3.4. (A) ICC of neural marker TUBB3 at day 14 showed the primary effect of the fibers to guide spreading of neurites along the fiber direction, while (B)neurites on laminin- coated glass spread in all directions. Scale bars = 50 mm. (C) Orientation distribution of neurites on aligned fibers and on (D) laminin coated glass with Gaussian fitting. Average angle of neurite orientation on fibers relative to the fiber direction was found to be -2.8 ± 21.5° and 21.5 ± 43.5° and on laminin glass. The goodness of fit (r2) to the Gaussian curve (0.82 ± 0.14) was statistically increased on aligned fibers in comparison to laminin glass (0.48 ± 0.21). The width of the Gaussian peak at half its maximum intensity was more narrow for neurites on fibers (50.6°) than on laminin glass (102.5°), also demonstrating the alignment...... 34

4.1. (A) Analysis by DMF size exclusion chromatography confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 60,600 Da, Mw = 83,700 Da, ĐM = 1.38). Molecular mass was determined against polystyrene standards. (B, D) Nanofibers were fabricated by electrospinning from a solution of DIBO-terminated poly(ε-caprolactone) in HFIP (17% w/v) and a voltage of 15 kV. Cover glasses were placed on aluminum foil or in the gaps of metal collector plate for collecting of random or highly aligned nanofibers. (C, E) Analysis of SEM images was performed to estimate topography of nanofibers. NIH ImageJ was used to estimate fiber diameter (ᴓ = 212 ± 63 nm for aligned and 219 ± 36 nm for random fibers) and alignment (DirectionalityTM plugin, average angle = 0 ± 6° for aligned and -2 ± 111° random nanofiber scaffolds). (F) Post-electrospinning modification with GRGDS or GRGES peptides via strain-promoted azide-alkyne cycloaddition. The concentration of GRGDS or GRGES peptides was measured using UV–visible spectroscopy by comparison of absorbance at 306 nm (peak corresponding to DIBO groups) before (black curve) and after (green curve) post-electrospinning modification...... 58

4.2. Summary of neural precursor (A), glial (B, C), and neuronal (D-F) gene expression over 14 days of neural differentiation of mouse embryonic stem cells, on fibronectin coated surfaces and RGD functionalized aligned and random nanofibers. Gene expression is represented as log2 (fold change). Statistical differences are highlighted between groups with p<0.05 considered significant...... 62

4.3. Protein quantification of glial (A, C) and neuronal (B, D) proteins. Cells were considered positive for the respective protein if they possessed the appropriate protein morphology. Prior to morphology assessment, the images were thresholded according to the brightness and contrast settings of control images, which were samples stained with secondary antibodies and nuclei stain only. Protein positive cells were normalized to the total number of cells expressing at least one protein label, and expressed as a percentage. Data is represented as average of single and double labeled protein ± standard deviation of total labeled proteins. Double xv labeling of GFAP is noted with SOX1 (days 1 and 3) and OLIG1 (days 7 and 14); TUBB3 with SOX1; OLIG1 with GFAP; and MAP2 with GAP43. * represents statistical difference between respective topography timepoints and groups, with a p<0.05 considered significant...... 66

4.4. Glial (A) and neuronal (B) protein expression of mESCs for 14 days of neural differentiation. Images have been adjusted to control thresholds to highlight cells expressing positive markers and have been enhanced for display. At early time points, cells expressed GFAP, however more distinct glial morphology was seen at later time points. Similarly, neuronal expression was also found at early time points, however more distinct neurites were found at later time points of neural differentiation. Scale bar of 20 µm...... 68

4.5. Neurite extension tracings. TUBB3 from day 7 on (A) aligned and (B) random nanofibers were used for (B, E) neurite tracings and (C, F) directionality measurements. (B) The aligned traces were rotated to orient the aligned fibers (from phase image) at 0°, and directionality of these neurite traces was measured. Gaussian fit (the red curve) was applied to measure neurite orientation. Scale bar of 50 µm...... 69

5.1. Electrospinning setup for aligned nanofibers: solution of DIBO-terminated poly(ԑ- caprolactone) in HFIP (17% w/v) was placed in syringe, and a voltage of 15 kV was applied to form aligned nanofibers in the gaps of metal collector. (b) Analysis of SEM images was performed to estimate topography of nanofibers. (c) Distribution of fiber diameters (average diameter ᴓ = 112 ± 35 nm) was calculated using NIH ImageJ198 (d) Aligned nanofibers were collected in the gaps of collector by tweezers to form yarns. (e) Yarns were functionalized with GRGDS peptide, cut into 13 mm stripes and placed inside 17 mm silicone tube in a way that 2 mm space is left on each sides of the tube. For the non-functionalized fiber group samples were placed in the tube without functionalization. (f) SEM of the cross-section of silicone tube with fiber yarns inside was cut at 45°...... 83

6.1. Polymer 1H-NMR overlay of allyl-PCL with 5%, 14% and 23% of allyl functionality. Peaks at the characteristic ‘b’, ‘c’ and ‘d’ resonances confirmed successful incorporation of allyl functionality in polymer chains. The molar ratio of the incorporated allyl groups in the afforded polymers were calculated from the characteristic ‘d’ resonances in blue from allyl-ε-CL comonomer, and the ‘e’ resonances in grey from ε-CL comonomer...... 107

6.2. Top: photomicrograph of aligned fibers with fluorescently labeled FITC-PEG-SH gradient along the fiber direction patterned via thiol-ene reaction using a quadratic gradient photomask. Images were taken with exposures 0.5 s and intensity was enhanced (+40% brightness). Scale bar is 100 µm. Bottom: corresponding graph of the increasing concentration gradient of immobilized FITC-PEG-SH (red circles). Graph of photomask pattern (black circles). The concentration of FITC-PEG-SH along the fiber direction had the same trend as greyscale intensity of the photomask used for thiol-ene reaction...... 111 xvi 6.3. Graph of the increasing concentration gradient of immobilized FITC-PEG-SH measured at 550 nm endpoint emission (red squares). Graph of photomask pattern (black squares). The concentration of FITC-PEG-SH along the fiber direction had the same trend as greyscale intensity of the photomask used for thiol-ene reaction...... 112

1 3 7.1. H NMR of 4-dibenzocyclooctynol (DIBO) (300 MHz, CDCl3, 303 K): δ = 7.75 (d, JH-H 3 = 7.8 Hz, 1H, aromatics), 7.54 – 7.28 (m, 7H, aromatics), 4.64 (dd, JH-H = 3.2, 2.5, 3 3 1H, CHOH), 3.11 (dd, JH-H = 14.7, 2.1 Hz, 1H, CH2), 2.94 (dd, JH-H = 14.7, 3.6 Hz, 1H, CH2), 2.14 (s, 1H, OH) ppm. DIBO was synthesized in accordance with the literature and was used as an initiator for ring-opening polymerization of ε- caprolactone...... 149

1 7.2. H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after polymerization (peaks a, c and d at δ = 5.56, 3.10 and 2.93 ppm correspond to protons from DIBO)...... 150

7.3. (A) Analysis by DMF size exclusion chromatography confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 60,600 Da, Mw = 83,700 Da, ĐM = 1.38). Molecular mass was determined against PS standards. (B) UV-visible spectra of DIBO-terminated poly(ԑ-caprolactone) in chloroform confirms survival of DIBO group after polymerization: absorbance peak at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO...... 150

7.4. (A) Distribution of fiber diameters (average diameter ᴓ = 219 ± 36) was calculated using NIH ImageJ.108 (B) DirectionalityTM plugin109 was used to estimate alignment of the scaffolds and Fityk 0.9.8 was used to fit Gaussian function (red curve) and calculate average angle as peak of fitting.110 Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1. Average angle was calculated to be 0 ± 6°, and goodness of fitting of Gaussian curve calculated by DirectionalityTM plugin was high (0.91 ± 0.06, average ± standard deviation)...... 151

7.5. ESI spectra and structure of N3-GYIGSR peptide confirms successful synthesis of N3- GYIGSR peptide, m/z for [M + Na]+ = 813.4 Da...... 151

7.6. Gene expression of pluripotency marker Pou5f1 on GYIGSR-functionalized aligned nanofibers and laminin-coated glasses shows that cells were pushed to differentiation...... 152

7.7. Representative images of flow cytometry indicating the purity of pluripotent D3 mouse embryonic stem cell population before seeding...... 152

7.8. SEM images of fibers A) before and B) after modification with peptide did not show differences in the fiber structure...... 153

7.9. Phase images of mESCs cultured on fibers and laminin coated glass...... 153 xvii 1 111 3 7.10. H NMR spectra of 6-azidohexanoic acid (300 MHz, CDCl3): δ = 3.28 (t, JH-H = 3 6.8 Hz, 2 H), 2.38 (t, JH-H = 7.3 Hz, 2 H), 1.74 – 1.52 (m, 4 H), 1.50 – 1.36 (m, 2 H) ppm. 6-azidohexanoic acid was synthesized according to literature111. Sodium azide (3.0 g, 15.4 mmol) was added to solution of 6-bromohexanoic acid (4.5 g, 7.7 mmol) in N,N-dimethylformamide (15 mL) and the mixture was heated at 85 °C for 3 h. The crude reaction mixture was diluted in methylene chloride, and this solution washed with 0.1 N aq. HCl. The organic layer was dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure to give 6-azidohexanoic acid (2.7 g, 74%) as an oil...... 154

1 7.11. H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after polymerization (peaks a, c and d at δ = 5.56, 3.10 and 2.93 ppm correspond to protons from DIBO)...... 155

7.12. UV-visible spectra of DIBO-terminated poly(ԑ-caprolactone) in chloroform confirms survival of DIBO group after polymerization: absorbance peak at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO...... 155

7.13. DirectionalityTM plugin109 was used to estimate alignment of the (A) aligned and (B) random fiber scaffolds. Fityk 0.9.8 was used to fit Gaussian function (red curve) and calculate average angle as peak of fitting110. Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1. Average angle was calculated to be 0 ± 6° for aligned and -2 ± 111° for random fibers. Goodness of fitting of Gaussian curve calculated by DirectionalityTM plugin was high for aligned fibers (0.91 ± 0.06) and low for random fibers 0.41 ± 0.2, average ± standard deviation)...... 156

7.14. Distribution of fiber diameters for (A) aligned and (B) random nanofibers was calculated using NIH ImageJ.108 (average diameter ᴓ = 212 ± 63 nm and 219 ± 36 nm accordingly)...... 156

7.15. ESI spectra and structure of N3-GRGDS peptide confirms successful synthesis of peptide, m/z for [M]+ = 630.01 Da ...... 157

7.16. ESI spectra and structure of N3-GRGES peptide confirms successful synthesis of peptide, m/z for [M]+ = 644.27 Da...... 158

7.17. For gene expression, the cell number was insufficient to fully evaluate. The example here is for Gfap on aligned and random nanofibers functionalized with high (8.4 ± 3.8 pmol/cm2 and 24.7 ± 8.4 pmol/cm2 respectively) and low (1.5 ± 0.2 pmol/cm2 and 2.5 ± 1.4 pmol/cm2 respectively) concentrations of GRGES, and low (1.9 ± 1.5 pmol/cm2 and 1.4 ± 0.9 pmol/cm2 respectively) concentration of GRGDS. For gene analysis, we seeded the same number of samples for high concentration GRGES and high concentration GRGDS, however, samples had to be combined to get sufficient RNA. At day 3, Gfap expression was similar between low concentrations of RGE and RGD. While 2 combined samples were measured for xviii Gfap expression on aligned high concentration RGE fibers, only 1 sample had Ct < 30. Overall, these control samples highlight challenges in using null peptide (RGE) for cellular controls in synthetic systems. In addition, the lack of differences between the low RGE concentration and low RGD concentration demonstrate that the concentrations of both fiber configurations (<2.0 pmol/cm2) were insufficient to investigate the activity of RGD in the mESC differentiation process...... 159

7.18. Summary of gene expression of neural differentiated mouse embryonic stem cells over 14 days of differentiation on fibronectin-coated surfaces, RGD functionalized aligned and random nanofibers. (A) Pou5f1 is downregulated (<0) beginning at day 1 for all samples, and was not found within 30 cycles in fibronectin at days 3, 7, or 14 or random at days 7 or 14. (B) Nes, a neural precursor cell marker, was not found on fibronectin samples, and upregulated beginning at day 1 for both aligned and random fiber samples; no statistical differences were found between samples. (C) Gap43 expression, indicative of neuron development, remained similar to its pluripotent state for all fiber samples, and was upregulated by day 14 on fibronectin samples. * represents statistical significance between groups, with p<0.05 considered significant...... 160

7.19. Protein expression of pluripotent (SSEA1, POU5F1), neural precursor (NES, SOX1), glial (GFAP, OLIG1), and neuronal (TUBB3, MAP2, and GAP43) markers. The days lacking images were not examined (see Methods for further information). Images shown are modified according to the controls to highlight cells expressing positive markers. Scale bar of 20 µm...... 161

7.20. Summary of pluripotent (A, B), neural precursor (C, D), and neuronal (E) protein expression of neural differentiated mouse embryonic stem cells over 14 days of differentiation on RGD functionalized aligned and random nanofibers. Images were thresholded according to the brightness and contrast settings of control images, which were samples with secondary antibodies and nuclei label. Protein positive cells were normalized to the total number of cells expressing at least one protein label and expressed as a percentage. Data is represented as average of single and double labeled protein ± std dev of total labeled proteins. For A and B, double labeling was SSEA1+/POU5F1+. (C) Double labeling was NES+/POU5F1+/SSEA1-, NES+/POU5F1-/SSEA1+, and NES+/POU5F1+/SSEA1+. (D) Double labeling was SOX1+/GFAP+. (E) Double labeling was MAP2+/GAP43+/GFAP-. * represents statistical difference between respective topography timepoints and groups, with a p<0.05 considered significant...... 162

7.21. Double labeling of proteins on nanofiber substrates. Cells expressing GFAP+ and SOX1+ highlight an additional role of GFAP as a neural precursor marker (A). Additionally, for later time points, clusters of cells were found expressing both mature neuronal markers (B), and glial markers (C). However, these cells were distinctly different in their morphology and were singly labeled with either a neuronal or a glial marker. Scale bar of 20 µm...... 163

xix 7.22. Summary of correlation plots. At day 7, a strong correlation between TUBB3+ expression and GFAP+ expression (-0.826), and cluster area (0.595) was found (A and B respectively). Additionally, at day 14, a strong correlation between TUBB3+ and GFAP+ (-0.628), and GFAP+ and OLIG1+ expression (-0.570) were found (C and D respectively). At day 7 and 14 of neural differentiation, a strong correlation of TUBB3+ and GFAP+ (-0.785) cells was found (E)...... 164

1 7.23. H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after 1 polymerization. H NMR (500 MHz, CDCl3, 303 K): δ = 7.51 – 7.45 (m, aromatic), 3 3 5.56 (dd, JH-H = 3.2, 2.5 CHOH), 4.15 – 3.98 (m, CH2CH2OCH2), 3.10 (dd, JH-H = 3 15.2, 2.1 Hz, CH(H)CH), 2.93 (dd, JH-H = 15.1, 3.9 Hz, CH(H)CH), 2.38 – 2.22 (m, (C=O)CH2CH2), 1.72 – 1.54 (m, (C=O)CH2CH2CH2CH2CH2), 1.45 – 1.28 (m, (C=O)(CH2)2CH2((CH2)2) ppm...... 165

7.24. (A) DMF size exclusion chromatogram confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 50.8 kDa, Mw = 68.6 kDa, ĐM = 1.35). (B) UV-visible spectrometry was used to measure concentration of GRGDS peptide by comparison of absorbance at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO...... 165

7.25. 1H NMR spectrum of poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) (500 MHz, CDCl3, 303 K): δ = 5.83 – 5.62 (m, CH-CH=CH2), 5.13 – 4.98 (m, CH-CH=CH2), 4.18-3.92 (m, CH2CH(CH-CH=CH2)CO), 4.15–3.98 (m, CH2CH2OCH2), 2.43 – 2.16 (m, C=O)CH2CH2), 1.77 – 1.46 (m, (C=O)CH2CH2CH2CH2CH2), 1.49 – 1.20 (m, (C=O)(CH2)2CH2((CH2)2)) ppm. NMR spectrum confirms successful synthesis of polymer and incorporation of allyl functionality in the polymer chains...... 166

7.26. (A) Analysis by THF size exclusion chromatography confirms successful synthesis of high molecular mass poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) (Mn = 89,600 Da, Mw = 138,300 Da, ĐM = 1.54). Molecular mass was determined against polystyrene standards...... 166

7.27. Analysis of (A) SEM images was performed to estimate topography of nanoﬁbers. NIH ImageJ was used to estimate ﬁber diameter (ᴓ = 401 ± 162 nm) and (B) alignment (DirectionalityTM plugin, average angle = 0 ± 3°). Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1...... 167

7.28. DOSY NMR spectra of poly(ԑ-caprolactone-co-6-allyl-ԑ-caprolactone) (500 MHz, CDCl3, 303K) showed the presence of only one polymer species, attributed to the formation of only copolymer species and not two species of homopolymers. The polymerization was designed for targeted DP = 100 and 50:50 monomer ratio at monomer concentrations = 4 M...... 168

7.29. (A) Plot of monomer conversion versus time for the copolymerization of allyl-ε-Cl and ε-Cl using Mg(BHT)2(THF)2 as a catalyst at 80 °C in toluene, total monomer concentration = 4 M. (B) Kinetic plot for the same reaction. The liner fit for allyl-ε- xx Cl: y = 0.1056x - 0.0144, R2 = 0.9647, with slope = 0.1056; for ε-Cl slope y = 0.0404x + 2.6748, R2 = 0.8451, with slope = 0.0404. Calculated from conversions based on NMR...... 169

xxi

LIST OF SCHEMES

Scheme Page Number

3.1. DIBO-end-functionalized poly(ε-caprolactone) was synthesized via ring-opening polymerization of ε-caprolactone using DIBO as an initiator and was modiﬁed post- electrospinning with peptides via strain-promoted azide-alkyne cycloaddition...... 27

4.1. DIBO-end-functionalized poly(ε-caprolactone) was synthesized via ring-opening polymerization of ε-caprolactone using DIBO as an initiator and Mg(BHT)2(THF)2 as a catalyst. Surface of DIBO-PCL was modiﬁed post-electrospinning with GRGDS or GRGES peptides via strain-promoted azide-alkyne cycloaddition...... 57

6.1. (A) Poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) was synthesized via ring-opening polymerization of ԑ-caprolactone and 6-allyl ԑ-caprolactone using Mg(BHT)2(THF)2 as catalyst and (B) was used to produce aligned fibers using touch-spinning. (C) Gradient of FITC-PEG-SH dye was created via thiol-ene reaction by shining the UV- light (365 nm) through the photomask. (D) Image of aligned fibers (aligned vertically) touch-spun on the metal frame...... 106

xxii

CHAPTER I

INTRODUCTION

1.1. Peripheral nerve injury and its treatment

Since nerve tissue has a limited capacity to regenerate, PNI is a significant clinical challenge. But the best combination of material properties for successful replacement of damaged neural cells has yet to be realized. More than one million people suffer from

PNI annually in the world and it results in loss of motor, sensory and autonomic functions,1 which reduces the quality of life for these patients. Natural regeneration can occur only in short nerve gaps, and microsurgery is usually used to treat PNI in patients.

Autograft is the current gold standard clinical solution for the patients precluded from direct nerve repair.4 In the autograft surgery, the nerve graft is taken from the same patient and is placed in the damaged site. But it has some significant limitations including requirements of the second surgery, morbidity of the donor site, mismatch in size and nerve environment and poor recovery.5

The other approach for nerve grafts includes placement of nerve guidance conduits (NGC). Today, the use of hollow NGCs is clinically approved as an alternative to autograft. However, the use of hollow NGCs is currently limited to a critical nerve gap of approximately 4 cm and show poor functional recovery.1, 6 Poor regeneration could be related to the lack of fibrin cable bridges formation that leads to the limited SC migration and consequently lack of glial bands of Bungner formation that serve as topographical and trophic cues for regenerating axons.4, 7 Thus, in order to replace or support native fibrin

1 cables, studies were focused on incorporation of additional topographical guidance cues into NGC to enhance nerve regeneration. Strategies for improving existing hollow nerve guidance conduits are shown in Figure 1.1.1

The incorporation of intraluminal fillers showed the improved regeneration in comparison to hollow NGCs.8 It was demonstrated that further introduction of proteins and growth factors in addition to topographical cues enhanced nerve regeneration. For example, collagen fibers coated with whole protein laminin or its short peptide mimic

YIGSR increased axonal density in comparison to uncoated fibers. 9-10 In some studies the functional recovery was not significantly different than that of autograft and the critical gap was bridged.11

Figure 1.1. Strategies for improving existing hollow nerve guidance conduits. Adapted with permission from ref.1 Copyright Journal of the Royal Society Interface 2012.

The introduction of nanofibers with their advantages of high surface area-to- volume ratio and aligned topography as a guidance structures was shown to increase functional outcomes. For example, yarns made of aligned PLGA electrospun nanofibers

(200 - 600 nm in diameter) in combination with biomolecules like laminin and growth factors, bridged a nerve gap of 15 mm after 12 weeks in rats.12

Surface modification techniques including full protein coatings, chemical and physical treatments, or the addition of protein mimetics onto the surface of the material have been employed to increase functional outcomes. ECM molecules like laminin,13-15 collagen16 and fibronectin16 increased SC adhesion, proliferation, and enhanced neurite outgrowth. Since ECM molecules have large molecular weight and are hard to synthesize, short peptide mimics could be used instead to promote specific cell functions. It was reported that addition of various peptide sequences increased nerve regeneration in comparison to uncoated scaffolds.17-18

Other efforts to optimize NGCs design considers more closely mimic of the native micro-architecture of the peripheral nerve environment.19 For example, vascularization is taking into account for successful application of larger constructs in vivo. Zhao and colleagues demonstrated that modification of fibrous PCL scaffolds with vascular endothelial growth factor (VEGF) and hydrophobin HGFI protein layer, improved human umbilical vein endothelial cells (HUVECs) adhesion, migration, and proliferation in vitro, as well as enhanced cellularization and vascularization in vivo.20 Although many types of constructs have been examined for NGCs, the combination of factors that influence nerve regeneration remains largely unexplored.

Other strategies for nerve regeneration include cellular and molecular based therapies like Schwann cell therapy, stem cell therapy and genetically modified cells.1

1.2. Stem cell differentiation for nerve injury treatment

Differentiation of stem cells in vitro is one of the most potential approaches to the nerve regeneration, especially in terms of gap sizes. Stem cells are attractive for different applications because they can be differentiated into various kinds of cell lineages. The most promising sources of stem cells for nerve regeneration are bone marrow stromal cells (BMSCs) and adipose-derived stem cells (ASCs). These cells are easily extracted, easy to culture, have a relatively low cost, raise no ethical issues and have the ability to differentiate in neural cell lineages.1, 21-22

Stem cell differentiation towards a specific lineage is controlled by its microenvironment. However, control of stem cell differentiation into translationally relevant, high ordered tissues is still challenging.23

Additionally, in order to advance stem cell replacement therapy into clinical practice, there is a great need to overcome limitations such as 1) lack of a well-defined, xeno-free culture system for differentiation of stem cells; 2) lack of control over culture conditions that regulate stem cell behavior (no control over spatial presentation and concentration); 3) inability to produce neurons from stem cells on large scale; 4) expense of culture environments to direct the differentiation of stem cells into neural lineage. 24

1.3. Electrospun scaffolds for cell culture in nerve regeneration

In the electrospinning process, a polymer solution is placed in a syringe with needle or in a pipette and is subjected to an electric field, which induces charge on the surface of a solution. With increasing of the electric field, the surface of the solution at the tip form a conical shape (known as the Taylor cone) due to charge repulsion. At the critical

4 value of the electric field the repulsive electric force overcomes the surface tension force, and a charged jet of the solution is ejected from the tip of the Taylor cone. As the jet travels in air, the solvent evaporates, resulting in a polymer fiber mat that can be collected on a conductive substrate like aluminum foil or metal plate.25 The diameter of the electrospun fibers can reach down to a few nanometers and can be controlled by such parameters as voltage, tip-to-collector distance, solvent, diameter of the tube or needle.

The topography of the fibers can be also controlled by the choice of the collector and can be adjusted for various applications. For example, aligned fiber could be fabricated by modification of collector. 26-30 Recently the number of publications about electrospinning has been increasing exponentially, with huge amount in the biomedical field including tissue engineering, wound dressing, drug release, sensors, nanofiber reinforced composites due to ability of electrospun fibers to mimic ECM topography.31 High porosity and spatial interconnectivity of electrospun mats is well‐suited for cell attachment, migration, nutrient and waste transport and cell communication.32 Electrospun fibrous scaffolds have been shown to influence biological processes relevant to nervous tissue regeneration, including stem cell neural differentiation, guidance of neurite outgrowth and peripheral nerve injury treatments.33-34

Topography of electrospun nanofiber substrates can enhance the differentiation of mouse ES cells into neural lineages and provide contact guidance to the neurite outgrowth.23, 35 Ramakrishna et al. demonstrated that aligned PLLA nanofibers facilitated higher rate of neural differentiation of nerve stem cells and promote cell orientation with respect to the fiber diameters in vitro in comparison to random microfibers.36

It has been reported that immobilization of biomolecules such as gelatin37-38, growth factors39-40 and bioactive peptides27, 41-42 could enable further control of the fate of

5 stem cells34, 43. Neurite outgrowth can be also enhanced by functionalization of nanofibers scaffolds with bioactive molecules such as laminin,44 fibronectin, collagen,45 neuroactive peptides or growth factors (e.g., basic fibroblast growth factor, bFGF,44 and nerve growth factor, NGF).34 Introduction of bioactive molecules like collagen enhance Schwann cell migration as well.46 While aligned nanofibers increased peripheral nerve regeneration in a rat model, the addition of growth factor (glial cell‐derived neurotrophic factor, GDNF) facilitated a more significant recovery.7 Large surface area of nanofiber scaffold allows high loading of bioactive molecules to facilitate efficient and selective cellular responses.32

Further enhancement of the neural cell response can be achieved by other factors, for example electrical stimulation.47-48

1.4. Touch-spinning

Recently Minko et al. reported that aligned nanofibers can be produced by touch‐ and brush‐spinning.49 These methods in comparison to electrospinning do not require high voltage. In touch-spinning, a rotating rod contact a polymer solution flowing from the syringe with needle. As the rod rotates, polymer droplet is stretched in a liquid bridge and the solvent evaporates allowing to make fibers down to nano-scale. This simple method allows to create nanofibrous constructs of different dimensions, shapes and topography and have a potential to be used in nerve regeneration. 49

1.5. Strain-Promoted Azide-Alkyne Cycloaddition (SPAAC)

Due to the unique properties of the Cu(I) catalysis, the CuAAC reaction is one of the most frequently used biorthogonal reactions in polymer chemistry.50 It was shown to be highly relevant for biological applications since alkyne and azide functionality is

6 completely absent in biological systems. In addition, it can be performed under body temperatures and in water solutions.51 However, the introduction of copper to biological systems is limited in some cases due to potential toxicity to living organisms and induction of viruses strands degradation.51-52 Therefore, there was a great need for development of metal-free [3 + 2] cycloadditions, with overcoming the toxicity of Cu-catalyzed reaction.

As an alternative to copper catalyst, Wittig and Krebs demonstrated that ring strain of cycloalkyne can activate its reaction with azide without using of any catalyst.53 Bertozzi et al. developed strain-promoted [3 + 2] cycloaddition for cell surface labeling and showed that it is orthogonal to the biological systems.54

In order to increase the reaction rate, the electron-withdrawing fluorine substituents were added to the cyclooctyne. The resulted Cu-free “click” reaction proceeds within minutes on live cells with no apparent toxicity. 55 However, the synthesis of the molecules was difficult. Boons et al. synthesized 4-dibenzocyclooctynol (DIBO). 56 In this molecule, the ring strain and thus the rate of the [3 + 2] cycloaddition was increased by incorporation of aromatic rings, while the addition of the hydroxy group provided opportunity for further reactions. DIBO was prepared in four steps, and the rate of the reaction with azide was much higher than of just cyclooctyne.56

The primary application of cyclooctyne derivatives was studied on live cells and organisms. However, recently due to the simple reaction conditions SPAAC has brought attention for the other applications like fiber surface modification,2, 27, 42, 57-58 gel synthesis,59 dendrons and dendrimers modification60.

Recently, the Becker Lab investigated strain-promoted azide-alkyne cycloaddition

(SPAAC),61-64 for the post-electrospinning attachment of bioactive species to degradable polyesters.2-3, 58, 65-66 The DIBO was used as initiator of the ring-opening polymerization of

ε-caprolactone or L-lactide. This approach afforded facile, quantitative modification of

DIBO-functionalized PCL with azide-derivatized compounds with no catalyst or chemical activation. Post-electrospinning surface modification method is one of the most efficient ways to attach bioactive species to nanofibers. It affords control of concentration and spatial presentation in contrast to physically adsorbed bioactive species. Unlike conjugation methods that occur prior to electrospinning, where a significant fraction of bioactive species is hidden within the fiber and is not available for interacting with target cells, post-electrospinning surface modification results in the bioavailability of the tethered groups.3

CHAPTER II

MATERIALS AND INSTRUMENTATION

2.1. Materials

All reagents were used as received without additional purification unless specified otherwise. Silica gel (porosity 60 Å, particle size 200 x 400 mesh, surface area 450-550 m2/g, bulk density 0.5 g/mL, and pH 6.0-7.0) or and Silica XG TLC Plates (w/UV254, aluminum backed, 200 um) were purchased from Sorbent Technologies Inc). All Wang resins and fluorenylmethyloxycarbonyl (Fmoc)-protected amino acids for peptide synthesis were purchased from EMD Millipore (Billerica, MA) or Aapptec (Louisville, KY).

All organic solvents were purchased from Sigma Aldrich as ACS Grade and used as received without additional purification unless otherwise stated. Anhydrous dichloromethane (DCM), chloroform (CHCl3) and tetrahydrofuran (anhydrous, 99.9%, inhibitor-free), were purchased from Sigma-Aldrich and used as received. Hexanes, ethyl acetate and methylene chloride were purchased from Fisher Scientific (Houston, TX). Dry toluene (HPLC Grade, 99.7%, Alfa Aesar) for polymerizations was purified and dried on an Inert Pure Solv system (MD Solvent Purification system, model PS-MD-3) and degassed using three cycles of the freeze-vacuum-thaw.

ε-Caprolactone (ε -CL): ACROS OrganicsTM, 99%, was dried over calcium hydride

under nitrogen overnight and distilled under reduced pressure.

Phenylacetaldehyde: Fisher Scientific, 98%.

Lithium diisopropylamide mono(tetrahydrofuran) (1.5 M solution in cyclohexane,

AcroSealTM): Fisher Scientific.

Iodotrimethylsilane: Fisher Scientific, 95–97%.

N-butyllithium (2.5 M solution in hexanes, AcroSealTM): Fisher Scientific.

Calcium hydride: Sigma-Aldrich, 95%

Sodium thiosulfate pentahydrate: Amresco, LLC, 99%.

1,1,1,3,3,3-hexafluoro-2-propanol (HFIP): Oakwood Products, Inc, 99.5%.

Sodium sulfate anhydrous (ACS grade): VWR International.

Hydrochloric acid (ACS Grade): VWR International, 36.5–38%.

Hydroxybenzotriazole (HOBt): Fisher Scientific, ≥98%

Triisopropylsilyl (TIPS): Sigma Aldrich, ≥99%.

Trifluoroacetic acid (TFA): Sigma Aldrich, 99%.

3-chloroperoxybenzoic acid: Sigma Aldrich, ≤77%.

Sodium bicarbonate (ACS reagent): Sigma Aldrich, ≥99.7%.

Allylcyclohexanone (TCI America): VWR International, ≥97.0%.

2.2. Instrumentation

1H-NMR spectra were obtained using a 300 MHz or 500 MHz Varian NMR spectrophotometer. The relaxation time was 2 s with 64 transients for polymers and 2 s and 16 transients for small-molecule chemicals. Chemical shifts are reported in ppm (δ)

1 and referenced to the chemical shifts of the solvent ( H NMR, CDCl3, δ = 7.26 ppm). Data analysis was conducted on MestReNova processing software. Multiplicities were explained using the following abbreviations: s = singlet, d = doublet, t = triplet and m = multiplet.

Thin-Layered Chromatographic Analysis (TLC) for specific organic compounds was conducted by spotting and developing samples on flexible silica gel plates (Sorbent

Technologies, Norcross, GA) using customized solvents as eluents.

Size Exclusion Chromatography (SEC) analysis was used to determine the number average molecular mass (Mn), weight average molecular mass (Mw), and molecular mass distribution (Đm) using a calibration curve determined from linear polystyrene standards (PStQuick MP-M standards, Tosoh Bioscience, LLC).

Chromatograms were collected on a Tosoh EcoSEC HLC-8320GPC. The 2 columns were calibrated using narrow molecular mass polystyrene standards (20 standards from 0.5 kDa to 5,480 kDa). Sample solutions were prepared at 7 mg/mL in THF or in 0.1 M LiBr solution in DMF as the eluent. The specified flow rate was 0.5 mL/min with an RI detector at 40 - 50 °C, with a polystyrene standard curve. Analysis was performed on EcoSec processing software.

Synthesized peptides were analyzed using mass spectrometry. The spectra were recorded using a Bruker HCT ultra II quadrupole ion trap mass spectrometer (Bruker

Daltonics, Billerica, MA) by direct infusion with a syringe pump at a flow rate of 250 μL/h.

The temperature and flow rate of the drying gas (N2) were 300 °C and 8 L/min, respectively; the pressure of the nebulizing gas (N2) was set at 10 psi. Stock solutions of the peptides were prepared in H2O at 10 mg/mL. The sprayed samples were prepared by adding 1 μL of the peptide solution to 500 μL H2O and 500 μL of MeOH to obtain a final peptide concentration of 0.01 mg/mL in 1:1 (v/v) H2O:MeOH. ESI mass spectrometry was performed by Sahar Sallam in the Wesdimiotis group (Department of Polymer Science, the University of Akron).

UV-Visible spectroscopy (UV-Vis): UV-Vis analyses were performed on a

SynergyTM MX spectrophotometer (Biotek Inc.) using quartz 96-well plate, 0.3 mL solution was tested for each sample. Spectral resolution was 1 nm. Reader control was via

BioTeck’s Gen5TM Data Analysis Software.

High voltage power supply (ES30P-5W, Gamma High Voltage, Ormond Beach,

FL) was used for electrospinning. The solution of polymer was placed in a 2 mL glass syringe with a 22 gauge needle for aligned and 23 gauge needle for random fibers (JG22-

0.5X or JG23-0.5X, Jensen Global Dispensing Solutions). A voltage of 15 kV was applied to the solution, and the tip-to-collector distance was set to 10 cm. Aluminum foil was used as the grounded collector for random fibers and metal plate with gaps (24 x 110 mm) for aligned fibers. Random nanofibers were collected on glass cover slides placed on aluminum foil. Aligned nanofibers were collected by placing cover glasses in between the gaps of the collector.

Nanofiber dimensions and alignment were imaged by scanning electron microscopy (SEM) with an applied voltage of 5 kV (JSM-7401F, JEOL, Peabody, MA).

Samples were sputter coated for 30 s with silver under nitrogen atmosphere prior to imaging.

CHAPTER III

ACCELERATED NEURAL DIFFERENTIATION OF MOUSE EMBRYONIC STEM

CELLS ON ALIGNED GYIGSR-FUNCTIONALIZED NANOFIBERS

In part this work has been reprinted with permission from Silantyeva, E.A.; Nasir,

W.; Carpenter, J.; Manahan, O.; Becker, M.L.; Willits, R.K. Accelerated neural

differentiation of mouse embryonic stem cells on aligned GYIGSR-functionalized

3.1. Abstract

Substrates for embryonic stem cell culture are typified by poorly defined

xenogenic, whole proteins or cellular components that are difficult and expensive to

generate, characterize, and recapitulate. Herein, the generation of well-defined scaffolds

of Gly-Tyr-Ile-Gly-Ser-Arg (GYIGSR) peptide-functionalized poly(ԑ-caprolactone) (PCL)

aligned nanofibers are used to accelerate the neural lineage commitment and

differentiation of D3 mouse embryonic stem cells (mESCs). Gene expression trends and

immunocytochemistry analysis were similar to laminin-coated glass, and indicated an

earlier differentiation progression than D3 mESCs on laminin. Further, GYIGSR-

functionalized nanofiber substrates yielded an increased gene expression of Sox1, a

neural progenitor cell marker, and Tubb3, Cdh2, Syp, neuronal cell markers, at early time

points. In addition, guidance of neurites was found to parallel the fiber direction. Herein,

we demonstrate the fabrication of a well-defined, xeno-free functional nanofiber scaffold

13 and demonstrates its use as a surrogate for xenogenic and complex matrixes currently used for the neural differentiation of stem cells ex vivo.

3.2. Introduction

The differentiation of stem cells in vitro yields novel sources of cells for neural tissue replacement or repair. Complex protein solutions, such as Matrigel®, have been utilized extensively as substrates for differentiation.67 However, Matrigel® is xeno- produced, differs from batch to batch, and contains a mixture of extracellular matrix (ECM) proteins, including laminin, collagen IV, entactin, heparin sulfate proteoglycans, and a multitude of growth factors.68 While xenogenic factors and additives have proven useful in vitro for mechanistic evaluation and development, the translation potential of this approach into clinical environments is limited, as xeno-derived components can initiate potent immune responses.69-70 In addition, several regulatory challenges exist to using these factors clinically. In order to push the translation of stem cells to clinical practice, synthetic xeno-free culture systems with defined concentration and spatial presentation of bioactive species for directed differentiation of stem cells and maintenance of cell maturity are required.24

In response to these challenges, polymeric substrates mimicking ECM elasticity, stiffness,71-72 geometrical architecture,73-74 chemical cues73, 75-76 and a combination of these factors77-79 have been explored to push stem cell differentiation into neural lineages with some success. However, the relative contributions of each these microenvironment parameters and how their combinations control cell behavior is still not completely understood. For neural tissue engineering, aligned fibers are of particular interest due to a highly polarized pattern of nerve cells. Aligned substrates have been shown to improve

14 neural cell alignment and migration, guide neural progenitor differentiation, and direct neurite extension during development and regeneration.23, 35, 73, 80-84

Electrospinning affords the fabrication of polymeric fiber meshes with nano- to micrometer topologies that mimic the architecture of native ECM.31, 85-87 Electrospun fibers influence stem cell behavior by mimicking ECM properties including fiber diameter and alignment (via modification of voltage, tip-to-collector distance, solvent composition and solution concentration34, 66, 88-90) and controlling the concentration and spatial placement of bioactive species. Electrospinning of ECM adhesive proteins including collagen,91 gelatin38, 92 or laminin93 has been used widely to produce cellular substrates, but most of the bioactive molecules are hidden in the bulk and unavailable for cell-substrate interactions, and are expensive to manufacture. Furthermore, ECM proteins often lose their structural functionality during electrospinning due to the stretching of molecules and denaturation.94-95 In contrast, most synthetic substrates lack biological signaling found in the natural ECM,96-97 but can be modified with bioactive species including peptides, growth factors and carbohydrates to yield simple, scalable and cost-effective substrates with improved cell-matrix interactions.20

Laminin is the most abundant glycoprotein present in basement membranes, appears at the very early stage during embryogenesis,98-99 and is a major component of

Matrigel®.67 It has various structural and biological activities including promotion of cell adhesion, migration, growth and differentiation.99-100 Substituting short synthetic peptides corresponding to binding domains of long protein chains101 for full proteins enables scalable, cost-effective substrate fabrication. For example, the six amino acid GYIGSR sequence, found in the B1 laminin chain, has been shown to exhibit cell adhesion, attachment, migration and binding to the 67 kDa laminin receptor.102-104

Recently, we investigated strain-promoted azide-alkyne cycloaddition (SPAAC),61-

64 for the post-electrospinning attachment of bioactive species to degradable polyesters.2-

3, 58, 65-66 This approach affords facile, quantitative modification of 4-dibenzocyclooctynol

(DIBO)-functionalized PCL with azide-derivatized compounds with no catalyst or chemical activation. Post-electrospinning surface modification method is the most efficient way to attach bioactive species to nanofibers. It affords control of concentration and spatial presentation in contrast to adsorbed bioactive species. Unlike conjugation methods that occur prior to electrospinning, where a significant fraction of bioactive species is hidden within the fiber and not available for interacting with target cells, post-electrospinning surface modification results in the bioavailability of the tethered groups.3

PLLA nanofiber scaffolds with tethered GYIGSR have previously been shown to enhance mESCs commitment to neural lineage within 3 days.66 However, further characterization regarding the commitment and maturation of the mESC over longer times were not reported. Therefore, this study investigated mESC commitment, differentiation, and maturation on aligned PCL nanofiber substrates functionalized with GYIGSR peptide for up to 14 days. By changing the degradable polyester to PCL, this work will enable the introduction of multiple functionalities in the polymer chain for post-electrospinning modification with biomolecules in a controlled manner.3, 58

3.3. Experimental

3.3.1. Materials

All materials were used as received unless otherwise stated. Tetrahydrofuran

(anhydrous, ≥99.9%, inhibitor-free), chloroform (anhydrous, contains amylenes as stabilizer, ≥99%), and calcium hydride (reagent grade, 95%) were purchased from Sigma-

Aldrich (St. Louis, MO). Phenylacetaldehyde (98%, stabilized), lithium diisopropylamide 16 mono(tetrahydrofuran) (1.5 M solution in cyclohexane, AcroSeal™), iodotrimethylsilane

(95-97%), n-butyllithium (2.5 M solution in hexanes, AcroSeal™), hexanes and methylene chloride were purchased from Fisher Scientific (Houston, TX). Sodium thiosulfate pentahydrate (Proteomics grade, 99%) was purchased from Amresco, LLC (Solon, OH).

1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) was purchased from Oakwood Products, Inc.

(Estill, SC). Sodium sulfate anhydrous (ACS grade) and methanol (ACS grade), hydrochloric acid (36.5-38%, ACS Grade) were purchased from VWR International

(Radnor, PA). Dry toluene (HPLC Grade, 99.7%, Alfa Aesar) for polymerization was purified and dried on an Inert Pure Solv system (MD Solvent Purification system, model

PS-MD-3) and degassed using three cycles of the freeze-vacuum-thaw. ε-Caprolactone

(ε-CL, 99%, ACROS Organics™) was dried over calcium hydride under nitrogen overnight and distilled under reduced pressure. Magnesium 2,6-di-tert-butyl-4-methylphenoxide

105-106 catalyst [Mg(BHT)2(THF)2] was synthesized using methods described previously. 4- dibenzocyclooctynol (DIBO) initiator was synthesized using methods described previously.2, 57, 62, 64, 107 Resins for peptide synthesis (Novabiochem®) were purchased from EMD Millipore (Billerica, MA). Fmoc-amino acids were purchased from Aapptec

(Louisville, KY). Flash chromatography was performed on silica gel (Sorbent

Technologies Inc., 70-230 mesh).

Square (22 x 22 mm) and round (8 mm) Fisherbrand™ borosilicate cover glasses

(#1.5) were washed with methanol/toluene/methanol, dried with nitrogen and cleaned with

UV light (355 nm) for 3 min prior to use. After nanofibers were collected on the glass coverslips, the nanofiber mats were glued to the edges of a glass slide by a silicone sealant and dried under vacuum overnight.

3.3.2. Experimental methods

Proton 1H nuclear magnetic resonance (NMR) (300 MHz and 500 MHz) spectra were recorded on Varian Mercury 300 and 500 spectrometers. The polymers were dissolved in CDCl3 solvent at 15 mg/mL, the relaxation time was 2 sec with 64 transients.

Size exclusion chromatography (SEC) was used to determine molecular mass and molecular mass distributions (ĐM). Eluograms were collected on a Tosoh EcoSEC HLC-

8320GPC using N,N-dimethylformamide (DMF) containing 0.1 M lithium bromide as the eluent. The 2 columns were calibrated using narrow molecular mass polystyrene standards (20 standards from 0.5 kDa to 5,480 kDa).

Nanofiber scaffolds were sterilized by ethylene oxide using an Anprolene benchtop sterilizer (Anderson Products, Inc., Haw River, NC) according to the manufacturer’s protocol for 12 h at room temperature and 35% humidity (concentration of ethylene oxide is about 0.5 g/L), purged for at least 48 h and stored in vacuum desiccator until cell study.

3.3.3. Materials for cell study

Synthesis Mouse embryonic stem cells (D3) were obtained from ATCC and cultured without a cell feeder support layer. ES-fetal bovine serum (ES-FBS, ES009B),

0.1% gelatin (ES006b), β-mercaptoethanol (100X, ES007E), sodium bicarbonate (S6014), sodium pyruvate (S8636), retinoic acid (R2625), insulin (I1882), apo-transferrin (T1147), progesterone (P8783), putrescine (P5780), sodium selenite (S5261), trypsin-EDTA

(T4174), and bisbenzimide H 33342 fluorochrome, trihydrochloride (H33342, 382065) were obtained from MilliporeSigma (St. Louis, MO). Dulbecco’s Modification of Eagle’s

Medium (90-013-PB), DMEM/F-12 (MT 15090CM) was obtained from Corning (Corning,

NY). L-glutamine (100X, 25030149), neurobasal medium (12349-015), paraformaldehyde

(04042-500), bovine serum albumin (BP9706-100), donkey anti-rabbit IgG Alexa Fluor 647

(A10040), goat anti-mouse IgM Alexa Fluor 546 (A-21045), donkey anti-mouse Alexa

Fluor 546 (A-10036), RNase-free glycogen (R0551), Trizol® (15596026), and molecular biology grade isopropanol (BP2618-500) were purchased from ThermoFisher Scientific

(Waltham, MA). mESC-qualified recombinant human recombinant leukemia inhibitory factor (LIF) (GSR-7001) and PluriQ serum replacement (GSM-6102) were purchased from

ThermoFisher Scientific. ES-qualified HEPES buffer (SH30851.01) was purchased from

GE Healthcare (Chicago, IL). Triton X-100 (8698.5-16) was purchased from RICCA

Chemical Company (Arlington, TX). Sodium borohydride (02102894) was purchased from

MP Biomedicals (Santa Ana, CA). Perfecta SYBR Green SuperMix, Low ROX (95056-

050) was obtained from Quanta Biosciences (Beverly, MA). The following antibodies were purchased from Abcam: anti-beta III tubulin (TUBB3, ab107216), goat anti-chicken IgY

Alexa Fluor 488 (ab150169), anti-SOX1 (ab22572), anti-nestin (NES, ab134017), anti-

OCT-4 (ab19857), anti-MAP2 (ab11267), anti-oligodendrocyte specific protein (ab53041), anti-CNPase (ab6319), anti-GAP43 (ab16053). The following antibodies were purchased from Biolegend: PE anti-mouse/human CD15 (SSEA-1) antibody (125606) and PE mouse

IgM isotype control (401611).

3.3.4. Synthesis of DIBO-end functionalized poly(ԑ-caprolactone)

The synthesis of DIBO-end functionalized poly(ԑ-caprolactone) and post electrospinning modification of the nanofibers with peptides via strain-promoted azide- alkyne cycloaddition is shown in Scheme 3.1. Using standard drying techniques, a glass ampoule was filled with ԑ-caprolactone (22.16 mL, 0.200 mol), toluene (76.83 mL, 0.723 mol) DIBO (0.0678 g, 0.308 mmol) and Mg(BHT)2(THF)2 (0.0941 g, 0.155 mmol). The ampoule was sealed and heated at 30 °C for 13 min. The polymerization was quenched with the addition of acidified (5 % v/v HCl) methanol, dissolved into chloroform and

19 precipitated into cold methanol. The crude polymer was re-dissolved in methylene chloride, precipitated into cold methanol and dried under high vacuum. The purified polymer was then stored in a desiccator. The monomer conversion (90%) and product

(yield 65%) were determined by 1H NMR spectroscopy (Figure 7.2, Appendix A), UV- visible spectrophotometry (306 nm, Figure 7.3B) and SEC (Figure 7.3A, Appendix A Mn =

1 60,600 Da, Mw = 83,700 Da, ĐM = 1.38). H NMR (500 MHz, CDCl3, 303 K): δ = 7.51 –

3 7.45 (m, aromatic), 5.56 (dd, JH-H = 3.2, 2.5 CHOH), 4.15 – 3.98 (m, CH2CH2OCH2), 3.10

3 3 (dd, JH-H = 15.2, 2.1 Hz, CH(H)CH), 2.93 (dd, JH-H = 15.1, 3.9 Hz, CH(H)CH), 2.38 – 2.22

(m, (C=O)CH2CH2), 1.72 – 1.54 (m, (C=O)CH2CH2CH2CH2CH2), 1.45 – 1.28 (m,

(C=O)(CH2)2CH2((CH2)2) ppm.

3.3.5. Electrospinning conditions and nanofiber collection

The electrospinning setup for aligned nanofiber scaffolds is shown in Figure 3.1A.

For aligned fiber scaffolds, the DIBO-terminated PCL was dissolved in HFIP (17% (w/v)) to yield a clear, slightly viscous solution. The solution was placed in a 2 mL glass syringe with a 22 gauge needle (JG22-0.5X, Jensen Global Dispensing Solutions). A voltage of

15 kV was applied to the solution, and the tip-to-collector distance was set to 10 cm. The gap size for the metal collector plate was 24 x 110 mm. Aligned nanofibers were collected by placing cover glasses in between the gaps of the collector. The collected nanofiber mats were glued to the edges of a glass slide by a silicone sealant and dried under vacuum overnight.

3.3.6. Characterization of diameter and orientation

Nanofiber Nanofiber dimensions and alignment were imaged by scanning electron microscope (SEM) with an applied voltage of 5 kV (JSM-7401F, JEOL, Peabody, MA).

Samples were sputter coated for 30 seconds with silver under nitrogen atmosphere prior

20 to imaging. A UVO Cleaner, Model #42A UV light unit was used to clean the glass coverslips for nanofiber collection. High voltage power supply (ES30P-5W, Gamma High

Voltage, Ormond Beach, FL) was used for electrospinning. The variation in nanofiber diameters was measured on at least 3 independent samples (5 images of each sample with >150 fibers per sample) using NIH ImageJ108 and reported as an average ± standard deviation. Distributions of fiber diameters are shown in Figure 7.4A, Appendix A. The

DirectionalityTM plugin of ImageJ109 was used to quantify the relative degree of alignment of the scaffolds by analyzing the angle distribution of fibers (Figure 7.4B, Appendix A).

The value is reported as an average ± standard deviation. Fityk 0.9.8 was used to fit a

Gaussian function (red curve), and calculate average angle as the peak of the fit distribution.110 Angles were normalized to 0. The highest peak was normalized to 1. Angle distribution of diameter directions was calculated using Gaussian fitting parameters. The quality (goodness) of fit to the Gaussian distribution curve calculated by DirectionalityTM plugin was reported as average ± standard deviation.

3.3.7. Solid phase peptide synthesis

N3-GYIGSR peptide was synthesized using standard FMOC conditions on a CEM

Discovery microwave peptide synthesizer. The N-terminus was derivatized with 6- azidohexanoic acid.111 The desired peptide product was conﬁrmed by electrospray

+ ionization mass spectrometry for N3-GYIGSR [M + Na] = 813.4 Da, yield = 71% (Figure

7.5, Appendix A).

3.3.8. Electrospray ionization (ESI) mass spectrometry experiments

Synthesized peptide was analyzed using mass spectrometry. The spectra were recorded using a Bruker HCT ultra II quadrupole ion trap mass spectrometer (Bruker

Daltonics, Billerica, MA) by direct infusion with a syringe pump at a flow rate of 250 μL/h.

3.3.9. Nanofiber functionalization

Nanofiber covered glass slides were dipped into a solution of the respective azide- functionalized peptide (1.587 µmol/mL) in 1:2 water/methanol (v/v) solution for 5 min. The cover slips with functionalized nanofibers were rinsed with 1:2 water/methanol (v/v) solution, blown with nitrogen and dried overnight in a desiccator. Scaffolds were sterilized using an ethylene oxide exposure cycle for 12 h, degassed for 2 days and stored in a vacuum desiccator until the cell studies.

The extent of functionalization with each peptide (reported as an average ± standard deviation) was conﬁrmed using UV−visible spectrophotometry using chloroform as a solvent. The peak intensity at 306 nm (which corresponds to π-π* transition in alkyne bond in DIBO-functionalized polymer) decreases after reaction with azide-functionalized peptide in comparison with fibers before functionalization. The concentration of GYIGSR peptide was measured using UV-visible spectrophotometry (SynergyTM MX plate reader from BioTek, with spectral resolution 1 nm).

3.3.10. D3 mouse embryonic stem cell culture and seeding

D3 mESC were maintained feeder-free using 0.1% gelatin coated flasks in pluripotent media (DMEM with high glucose, 10% FBS, 0.1mM 2-mercaptoethanol, 4 mM

L-glutamine, 4.7 mM HEPES, and 1000 U/mL LIF). Pluripotent cells were passaged every other day. All experiments utilized cells with less than 15 passages. The expression of

SSEA-1 was utilized to confirm pluripotency at the time of seeding by flow cytometry. Cells were seeded onto scaffolds at 125,000 cells/cm2 in neural differentiation media (80% 1:1

DMEM:F-12, 20% neurobasal-A medium, 1X N2 (50 µg/mL insulin, 1 mg/mL apo- transferrin, 60 ng/mL progesterone, 160 µg/mL putrescine, 0.3 µM sodium selenite, 0.5 mg/mL BSA, 6 mg/mL D-Glucose, 5mM HEPES, diluted in DMEM/F12), 1X PluriQ, 1mM sodium pyruvate, 2 mM L-glutamine, and 2 µM retinoic acid). Differentiation status was determined at day 1, 3, 7, and 14 using both gene and protein expression.

3.3.11. Quantitative polymerase chain reaction (qPCR)

RNA isolation was performed using Trizol® according to the manufacturer’s protocol. Two samples were combined prior to RNA isolation for scaffolds, while one sample was utilized for RNA isolation from cells on laminin substrates. UV-visible spectrophotometry was utilized to quantify RNA and gel electrophoresis was performed on every RNA sample to confirm quality using 2% agarose gel with ethidium bromide.

Quanta qScript DNase kit was used following the manufacturer’s protocol to digest any genomic DNA. Quanta qScript reverse transcriptase (RT) kit was used following manufacturer’s protocol to synthesize cDNA. The synthesized cDNA was stored at 4 °C until qPCR was performed. Real time PCR was performed using primers (Integrated DNA

Technologies, Coralville, IA) in Table 1. No-template controls and no RT controls were tested on each sample at the same primer concentration for housekeeping genes.

Reactions were prepared using Perfecta SYBR Green SuperMix, Low ROX and Applied

Biosystems 7500 real time PCR system was used at a standard run.

Table 3.1. Primers used for real time qPCR with accession numbers, forward and reverse sequences.

Primer Accession Gene Number Forward Sequence Reverse Sequence Gapdh NM_008084.3 AAT GGT GAA GGT CGG TGT GTG GAG TCA TAC TGG AAC G ATG TAG Actb (β-actin) NM_007393.5 GCT GTA TTC CCC TCC ATC CAC GGT TGG CCT TAG GGT GTG TCA G Pou5f1 (Oct- NM_013633.3 GGC ACT TCA GAA ACA TGG GAA GCC GAC AAC AAT GAG 4) TCT AAC Sox1 NM_009233 GGC AGT CAT ACA AAA GTT GTA CAG TAT TTA TCG TCC GGC GCA GA Pax6 NM_00131014 AAG GGC GGT GAG CAG ATG CAT GCT GGA GCT GGT TGG 4.1 T Nes NM_016701.3 CAC CTC AAG ATG TCC CTT GGA AAG CCA AGA GAA GCC AGT C T Tubb3 NM_023279.2 CCT CCG TAT AGT GCC CTT GTG GAC TTG GAA CCT GGA TG AC Map2 NM_00103993 CCA CTA ATG CCA GTT TCT GAC CCA GAG TGT GTG AGT 4.1 CTC T TTA T Gfap NM_010277.3 CCA CCA GTA ACA TGC AAG GCG ATA GTC GTT AGC TTC AGA GTG Th NM_009377.1 CCC TAC CAA GAT CAA ACC CTG GAT ACG AGA GGC ATA TAC C GTT C Foxo4 NM_018789.2 GCTCTTGGTGGATGCTGAAC AACTGCTTCGTGGACGGAAA

Cdh2 (n- NM_007664 GCCCGCTATTTGTTACCAGC CACAGACGCCTGAAGCAAGG cadherin) Gap43 NM_008083.2 AGG AGG AGA AAG ACG CTG TCA GGC ATG TTC TTG GTC TA AG Syp NM_009305.2 TTT GGA GGG TGA GCG AAA AGA GAA AGG GTG GAG AAG TG GTA G Olig1 NM_016968 TCC AGA CTT CTC TCC CAG AGC AAC TAC ATC GCT CCT AC TG

3.3.12. Immunocytochemistry

Protein expression was evaluated using immunocytochemistry (ICC). Cells were fixed at the appropriate timepoint with freshly prepared 4% paraformaldehyde in 1X PBS for 10 minutes at ambient temperature. Cells were permeated with 0.5% Triton X-100 for

10 minutes, quenched with 1 mg/mL sodium borohydride for 8 minutes, and blocked with

2 mg/mL BSA for 40 minutes. Cells were incubated with primary antibodies at 4 °C for 10 24 hours, washed 3 times, and incubated with secondary antibodies for ~8 hours at 4 °C. All cells were labeled with H33342. Day 1 samples were labeled with the pluripotency markers POU5F1 and SSEA-1, early neural markers NES and SOX1, and the neural marker TUBB3. Day 3 samples were labeled with the pluripotency marker POU5F1, early neural markers NES and SOX1, neuronal marker TUBB3, and glial marker GFAP. Day 7 and day 14 samples were labeled with the neuronal markers TUBB3, MAP2 and GAP43, and the glial markers OLIG1, GFAP and CNPase.

Images were taken on Zeiss AxioObserver Z1 microscope (Zeiss, Thornwood, NY) or Olympus FV1000 (Tokyo, Japan) at exposures relative to controls with only secondary antibodies. Up to five images were taken per substrate. To provide semi-quantitative information from the images, we utilized several techniques within ImageJ including pixel quantification, percent labeled cells, and neurite alignment.

Pixel Quantification: The control images, taken on substrates processed with no primary antibodies, were thresholded to less than 0.1% area fraction of fluorescence, and the thresholded values were used on the sample images. The area fraction of fluorescent pixels after thresholding was recorded for each fluorophore and image and normalized to area and the number of cells in the ROI. This pixel quantification was performed for images taken on the same microscope at the same magnification.

Percent labeled cells: To determine percentages of labeled cells, the number of cells expressing various markers on day 1 and day 3 were manually counted and expressed as % cells ± standard error of the mean.

Neurite alignment: Finally, to quantify the alignment of the neurites, all TUBB3 labeled neurites in images were traced using NeuronJ plugin of ImageJ. The fiber orientation was measured in the phase channel, and all tracings were oriented to the fibers

25 at 0º. The tracings were then processed through DirectionalityTM plugin of ImageJ.

Goodness of fit to a Gaussian curve was used to measure alignment of the neurites and reported as average angle ± standard deviation and by the width of the Gaussian peak at half its maximum intensity. This process also provided a measure of total neurite length per area, but as starting and ending positions of neurites could not be identified in each case, only the total neurite length was reported.

3.3.13. Statistics

All experiments were conducted at least 3 times (n ≥ 3). Cellular experiments have a minimum of 3 biological replicates. PCR data are presented as the average ± standard deviation and image analysis is expressed as average ± standard error of the mean. Two- way ANOVA with Bonferroni’s post hoc analysis was used to express statistical differences with 95% confidence interval and a significance value of p>0.05. Two-sample t-test was performed to show statistical difference between neurite alignment cultured on different substrates with 95% confidence interval and a significance value of p>0.05.

3.4. Results

3.4.1. PCL nanofibers functionalized with GYIGSR

DIBO-end functionalized poly(ԑ-caprolactone) was synthesized by ring-opening polymerization of ԑ-caprolactone using Mg(BHT)2(THF)2 as a catalyst using standard techniques. This method yielded high molecular mass PCL with high end group fidelity.

High (90%) monomer conversion was obtained within 13 min at 30 °C and yielded polymer with high molecular mass and narrow molecular mass distribution (Mn = 60,600 Da, Mw =

83,700 Da, ĐM = 1.38). This polymer was used to fabricate highly aligned nanofiber scaffolds with a narrow angular distribution of fibers (0 ± 6°, average ± standard deviation).

The average diameter of fibers was ᴓ = 212 ± 63 nm. Aligned nanofibers were modified post-electrospinning with GYIGSR peptide via strain-promoted azide-alkyne cycloaddition and the surface concentration of GYIGSR peptide was determined to be 17.3 ± 6.6 pmol/cm2.

Scheme 3.1. DIBO-end-functionalized poly(ε-caprolactone) was synthesized via ring- opening polymerization of ε-caprolactone using DIBO as an initiator and was modiﬁed post-electrospinning with peptides via strain-promoted azide-alkyne cycloaddition.

Figure 3.1. Nanofibers were fabricated by electrospinning from a solution of DIBO- terminated poly(ε-caprolactone) in HFIP (17% w/v) and a voltage of 15 kV. (A) Highly aligned nanofibers were collected on cover glasses in the gaps of metal collector plate. (B) Analysis of SEM images was performed to estimate topography of nanofibers. NIH ImageJ was used to estimate fiber diameter (ᴓ = 212 ± 63 nm) and alignment (DirectionalityTM plugin, average angle = 0 ± 6°). (C) Post-electrospinning modification with GYIGSR peptide via strain-promoted azide-alkyne cycloaddition. The concentration of peptide (17.3 ± 6.6 pmol/cm2) was measured using (D) UV–visible spectrophotometry by comparison of absorbance at 306 nm (peak corresponding to DIBO groups) before (red curve) and after (black curve) post-electrospinning modification based on calibration curve of DIBO in chloroform. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.4.2. mESC response

To investigate whether PCL nanofiber substrates with a tethered synthetic laminin mimic (GYIGSR peptide) supported neural differentiation of mESC, pluripotent D3 mESC

(>95% SSEA-1 positive via flow cytometry) were seeded on the YIGSR nanofiber substrates and laminin-coated cover slips as a positive control. Cells were then cultured

28 for 14 days in presence of neural differentiation medium. The progress of neural differentiation was assessed using gene expression by qPCR and protein expression by

ICC at day 1, day 3, day 7 and day 14. Cultured cells formed aggregates on both GYIGSR- functionalized PCL nanofibers and laminin-coated glass (Figure 7.9, Appendix A).

Initially, the adhesion was investigated to assure sufficient cell interactions with the scaffold. The number of cells at day 1 was determined by counting the nuclei on each substrate sample. Of the seeded cells, 1.1 ± 0.2% adhered to the YIGSR-aligned scaffolds and 53.6 ± 7.0% of the cells adhered to laminin-coated glass. In a preliminary study on aligned nanofibers made from the same material but without any peptide or non-bioactive peptide RGES, only a few cells adhered to the surface (≤0.2% after 24 h, with fewer cells at day 3, data not shown), which was an insufficient amount to perform qPCR or ICC.

3.4.3. Gene Expression

To characterize neural differentiation by gene expression, stage specific pluripotency markers, neural progenitors, early and late neural markers, and glial markers were analyzed by qPCR. Figure 3.2 and Figure 7.6 (Appendix A) show fold change

(normalized to average of two housekeeping genes – Gapdh and Actb and day 0) over time on YIGSR aligned fibers and laminin-coated glasses.

Figure 3.2. Comparison of gene expression of D3 mESCs cultured on GYIGSR- functionalized aligned nanofibers and laminin-coated glass at day 1, 3,7 and 14. Expression of neural progenitor (Nes, Sox1, Pax6) and neuronal (Tubb3, Map2, Cdh2, Th, Gap43, Syp) as well as glial (Foxo4, Olig1, Gfap) gene markers demonstrated that aligned GYIGSR-functionalized nanofiber scaffolds have similar neuronal differentiation into neural lineage compared to laminin-coated glass. No significant differences were found between fibers and laminin glasses in most of the gene expression, with similar differentiation states at day 7 and day 14. Two exceptions of higher expression of neuronal genes on aligned GYIGSR fiber scaffolds at earlier time points were Sox1 at day 1 and Cdh2 at day 3 and day 7. ● indicates statistically significant difference (p < 0.05) in comparison to the previous time point for the same substrate, * indicates that gene expression on fibers is statistically significantly different (p < 0.05) than on laminin for the same time point.

The pluripotent marker (Pou5f1) was downregulated in both groups (Figure 7.6,

Appendix A) implying that cells were undergoing differentiation, with downregulation at day 14. Higher levels of Pou5f1 gene expression were found from cells on fibers compared to cells on laminin on day 1 and day 3, but the result was not significantly different on day 7 and 14.

Neural commitment was confirmed by expression of neural progenitor genes

(Sox1, Pax6, Nes). Expression of these neural progenitor markers was upregulated at day 1 and day 3 and then down-regulated by day 14. Expression of Sox1 was significantly 30 higher for cells on fibers than cells on laminin at day 1, but no significant differences were found between samples at each later time point (day 3, 7 and 14). Expression of Pax6 was not significantly different between samples for day 1, 3 and 7, but had a significantly lower level from cells on fibers than cells on laminin at day 14. No significant difference was noticed on Nes expression trends and on either substrate.

Cdh2, responsible for neural cell to cell interaction, had the same expression for both samples at day 1, but a significantly higher level of expression from cells on fibers at days 3 and 7. At day 14, the difference between the two samples was not significant.

After neural commitment, cells start to express neuronal markers (Tubb3, Map2,

Gap43, Syp, Th), which indicated differentiation into neural lineage. Both Tubb3 and

Map2 were up-regulated on day 7 in comparison to day 3. Expression of Tubb3 at day 7 and 14 by cells on laminin and cells on fibers had no significant differences from each other. Similarly, no differences were found at days 7 and 14 for Map2. However, early stage neuronal marker Tubb3 was expressed earlier by cells on fibers, with significant differences compared to cells on laminin at day 3. Gap43 was expressed at a higher level on fibers than on laminin at day 3. Late stage neuronal marker Syp, a protein that plays a role in synaptic plasticity112, was upregulated during the differentiation, with the highest expression on day 14. The expression of Syp was increased for cells on laminin over cells on fiber substrates for day 3 and 14. Expression of tyrosine hydroxylase (Th), associated with dopaminergic neurons, demonstrated statistical increases at day 3 compared to day

1 on fibers (at day 3), but not until day 7 on laminin.

Glial cell markers expressed similarly on both substrates at similar time points, except Foxo4 at day 14 and Olig1 at day 1, where the gene expression was lower for cells

31 on fibers. Gfap had significant increases (511-fold increase on fibers and 565-fold increase on laminin) by cells on both substrates by day 14.

3.4.4. Protein Expression

The expression of proteins typical for pluripotent state (SSEA-1, POU5F1), neural progenitors (NES, SOX1), neural (TUBB3 for early neuronal, MAP2 and GAP43 for late neuronal stage), and glial cells (GFAP for astrocytes, OLIG1 and CNPase for oligodendrocytes) was visualized and quantified. Third quartile images, based on pixel quantification, are shown in Figure 3.3.

Figure 3.3. Protein expression during differentiation on YIGSR-aligned fibers and laminin over 14 days. Displayed images are from the 3rd quartile of fluorescent intensity for each protein. Expression is noted as typical for pluripotent state (SSEA-1, POU5F1), neural progenitors (NES, SOX1) neural (TUBB3, MAP2, GAP43) and glial cells (GFAP, OLIG1, CNPase), scale bars = 100 mm. Images indicate similar neural differentiation on (A) aligned GYIGSR-functionalized nanofiber scaffolds and (B) laminin glasses but with faster

32 rates on ﬁbers (earlier expression of NES, TUBB3, MAP2 and GAP43 on aligned ﬁbers). ICC images were enhanced (+40% brightness, +20% contrast).

The pluripotent marker SSEA-1 was present on cells after day 1 of neural differentiation on both fiber and laminin substrates. While quantification showed a statistically increased number of cells expressing SSEA-1 on fibers (73 ± 4.7%) over laminin (38 ± 3.1%), the number of cells expressing pluripotent marker POU5F1 was not statistically different between fibers and laminin, 11 ± 4% and 0.59 ± 4%, respectively.

Neural progenitor markers, such as NES, should be up- and then down-regulated during neural commitment. On fibers, NES appeared on day 1 (71 ± 6.6% of cells) and was minimally detectable by day 3 (0.8 ± 0.3%). On laminin, only 0.01% ± 0.01% of cells were expressing NES at day 1; this result was statistically lower than the expression on fibers.

The percent of cells expressing NES on laminin statistically increased on day 3 to 5.6 ±

1.8%. A low number of cells expressed SOX1, resulting in no statistical differences between laminin and fibers at day 1.

TUBB3 appeared on day 1 on cells seeded on fiber substrates in comparison to cells cultured on laminin-substrates, where TUBB3 began to appear by day 3. On day 1,

29 ± 8.3% of cells expressed TUBB3 on fibers, which was statistically higher than 0.03 ±

5.3% of cells expressing TUBB3 on laminin. Compared to day 3, TUBB3 expression statistically increased by day 7 on laminin and fibers with more visible expression by cells on fibers than cells on laminin, although little visual differences were seen on day 14. For fiber scaffolds, the neurites primarily followed the path of the fibers, while neurites extended in all directions on laminin-coated substrates (Figure 3.4).

Figure 3.4. (A) ICC of neural marker TUBB3 at day 14 showed the primary effect of the fibers to guide spreading of neurites along the fiber direction, while (B)neurites on laminin- coated glass spread in all directions. Scale bars = 50 mm. (C) Orientation distribution of neurites on aligned fibers and on (D) laminin coated glass with Gaussian fitting. Average angle of neurite orientation on fibers relative to the fiber direction was found to be -2.8 ± 21.5° and 21.5 ± 43.5° and on laminin glass. The goodness of fit (r2) to the Gaussian curve (0.82 ± 0.14) was statistically increased on aligned fibers in comparison to laminin glass (0.48 ± 0.21). The width of the Gaussian peak at half its maximum intensity was more narrow for neurites on fibers (50.6°) than on laminin glass (102.5°), also demonstrating the alignment.

The alignment relative to the fibers was demonstrated by the orientation angle of the neurites (-2.8 ± 21.5° on fibers in comparison to 21.5 ± 43.5° on laminin glass) and the goodness of the fit, which was statistically improved on fibers, 0.82 ± 0.14, compared to laminin 0.48 ± 0.21. The width of the Gaussian peak at half its maximum intensity was more narrow for neurites on fibers (50.6°) than on laminin glass (102.5°). By 7 and 14

34 days of differentiation, the neurites were extensively networked on glass substrates and elongated on fibers. Average neurite length and number of neurites could not be measured directly due to the inability to determine starting and ending positions of the actual neurites. In addition, many of the individual neurites could not be distinguished as they intertwined, particularly on fibers, making a measurement of total neurite length inaccurate. Total neurite length was statistically higher on fibers (55.4 ± 30.2 mm per 1 mm2) than on laminin glass (31.5 ± 21.6 mm per 1 mm2), with p = 0.016. Mature neuronal markers GAP43 and MAP2 were expressed earlier by cells on fibers than by cells on laminin, where day 7 protein expression is noticeably increased by cells on fibers in contrast to cells on laminin. Pixel quantification of MAP2 expression of the images at day

7 showed no statistical differences between laminin and fibers (p=0.11), although 2 of 5 images of cells on laminin had no fluorescence.

GFAP was present on cells on both fiber and laminin substrates by day 3. While

GFAP was present on cells on fiber substrates, the expression of GFAP by cells on laminin-coated surfaces showed more distinct glial morphology at day 14 (Figure 3.4).

Pixel quantification for GFAP at day 7 was statistically higher on laminin substrates than

YIGSR-aligned fibers. The expression of oligodendrocyte marker OLIG1 was slight for cells on laminin at day 7, and more prominent at day 14, but was not visibly expressed on cells on fibers (Figure 3.3). Another oligodendrocyte marker CNPase was also slightly expressed by day 7 on laminin, but was not noticeably expressed on cells on fibers until day 14. Pixel quantification of CNPase was not statistically different (p=0.07), with 12/12 images for cells on fibers had no labeling and 2/5 images for cells on laminin had no labeling.

3.5. Discussion

To translate the use of stem cells to clinical practice, xenogenic components of differentiation media need to be substituted by recombinant proteins or synthetic mimics.5

One method to reduce these components is to develop material-based systems that recapitulate the culture microenvironment currently utilized for stem cells. Cells produced via substrate-directed differentiation may improve access to neural cells for cell-based therapies by reducing exposure to potential immunogens. To address this concern, we designed a synthetic nanofibrous substrate with surface-tethered GYIGSR that increased the rate of mESC differentiation compared to laminin-coated surfaces, demonstrating an improved xeno-free substrate for neural differentiation of mESC. While current papers investigated neurite length and cell number as criteria for improved differentiation, in this work we provided a variety of gene and protein expression profiles in order to demonstrate a broader picture of differentiation capability of substrates and to have an insight in the mechanism of neural differentiation. To the best of our knowledge, no reports exist in literature that provide such a comprehensive comparison of cell differentiation on peptide- functionalized substrates to its whole protein as presented here.

To first characterize the D3 mESC neural differentiation culture, we seeded dissociated cells, directly from pluripotent culture, onto laminin-coated substrates to investigate the commitment and differentiation. Protein-coated substrates are commonplace in stem cell culture, particularly when investigating neural differentiation. In the literature, a variety of protein substrates have been studied as a means of simplifying culture away from embryoid body formation or use of feeder cells to induce differentiation, including laminin,113 Matrigel®, heparan sulfate,114 gelatin115 and sulfated chitosan.116 The

36 time course of this differentiation protocol is demonstrated through down regulation of both gene expression (Figure 3.2, Figure 7.6, Appendix A) and protein expression (Figure 3.3).

By culturing the mESCs out to 14 days, transient gene expression for early and late markers was noted. For example, by 3 days post-seeding, the gene expression of the pluripotent marker Pou5f1, was downregulated, while Nes, Sox1 and Pax6, neural progenitor markers, were increased. Confirming neural differentiation, neuronal and glial gene and protein makers were upregulated over the 14 day time course. While it is challenging to directly compare timepoints between mESC lines, differentiation techniques, and media types, N-cadherin bound surfaces demonstrated neurites within 10 days of differentiation of mESC ST1 line and Nanog-GFP expressing miPS cell line, yet had low expression of TUBB3 at day 4, indicating a similar progression to our study.117

Overall, the laminin-substrate, along with the differentiation medium, encouraged both the commitment and differentiation toward neurons and glia over 14 days.

We next investigated the effect of fibers on the same process. Electrospun nanofibers have been shown to enhance differentiation of embryonic stem cells into various types of cell lineages compared to flat surfaces,118 including osteogenic differentiation,119 cardiomyocytes,120 adipocytes,121 and neurons.23, 122 Ultimately, interactions between nanofibers and neural stem cells, mesenchymal stem cells, or other cells have been broadly studied, yet little has been done to investigate the direct interactions between nanofibers and pluripotent stem cells for neural differentiation.123 As each cell type offers unique challenges, much of our focus of comparison from the literature is to mESCs and nanofibers, and the induction, commitment, and differentiation to neural cells. Synthetic nanofibers offer many advantages in processing and manufacture, yet, in general, synthetic electrospun fibers do not offer bioactive sites for

37 mESCs with which to interact, which is a significant drawback. The need to have bioactive components adsorbed or bound to the fiber surface to exert its influence has limited studies seeking to avoid costly protein or xenogenic components. While some studies have not utilized an adsorbed protein, these protocols employed embryoid body to induce differentiation prior to cell seeding on the fibers. For example, mESC neural differentiation was examined on uncoated PLLA microfibers after induction by embryoid body formation.84 By post-electrospinning placement of bioactive components, our fibers offered an advantage over others by preventing peptides from possible degradation during electrospinning and focusing them on the surfaces that could be in contact with cells. Our simple method of nanofiber post-electrospinning modification with peptide involving strain- promoted azide-alkyne cycloaddition provided easier characterization of the surface peptide concentration. Our previous work on YIGSR-functionalized PLLA fibers demonstrated early commitment of mESCs on aligned over random nanofibers without embryoid body formation,66 however, did not compare results for time points after 3 days or to whole protein. To fully investigate the effects of the topography or the peptide, a more stringent comparison over longer times to the whole protein is necessary.

The topography of the substrate is defined by both the fiber diameter and alignment. While fiber diameter has been found to play a role in neural differentiation, the results are mixed. For example, fiber diameter played a role in rat neural stem cell differentiation on laminin-adsorbed polyethersulfone fibers in comparison to laminin- adsorbed tissue culture polystyrene, where at 5 days of culture, cells had higher TUBB3 protein expression on 749 nm fibers compared to gelatin-coated plastic and 283 nm nanofibers. In contrast, oligodendrocytes were found in higher numbers on 283 nm fibers over larger fibers and gelatin-coated plastic.35 In this study, we found few

38 oligodendrocytes on 212 nm fibers, and high expression of β-III tubulin both in protein and gene expression, high Nes in gene expression, and little detectable GFAP by both gene and protein expression by day 7. These results were more similar to previous work on

PLLA fibers with tethered GYIGSR66 and neat PLLA fibers, where the rate of neural stem cell differentiation was higher on nanofibers (250-300 nm) than on microfibers (1.25-

1.5µm).81 The differences noted between each study can be due to surface/protein/peptide functionality, fiber density,124 or potential topography influences.

While we did not study fiber diameter as a variable, this variable could be studied in the future to potentially drive one cell population over another.

As noted above, the alignment of the fibers has played a role in the resulting differentiation, with aligned topographies demonstrating increased neuronal differentiation. After 10 days on PLGA fibers, mESCs (mESC1 and mESC5) on aligned scaffolds had statistically higher Nes gene expression than gelatin-coated substrates or random fibers, but not Tubb3 or Pax6.84 In addition, PLLA fibers (350 nm) with bound

YIGSR had increased neural differentiation after 3 days over similar fibers that were randomly oriented, or aligned or random unfunctionalized fibers.66 This trend is similar with adult neural stem cells.125 Therefore, we selected to only study aligned fibers, and compare those results to laminin-coated substrates, which are a typical platform for neural differentiation. In this comparison at early time points, YIGSR-aligned fibers had higher expression of neural progenitor and neuronal genes Sox1, Tubb3, Cdh2, Gap43, Syp, and earlier NES, TUBB3, GAP43 and MAP2 protein expression on synthetic nanofiber substrates. Thus, YIGSR-aligned fibers were a suitable substrate for neural differentiation, producing an increased rate of differentiation compared to whole-protein coated glass substrates. After 14 days, any differences were gone, implying a more

39 mature population on both substrates. Future work, over longer time frames, can continue to determine if further differences exist after differentiation on a peptide-modified scaffold with different topographies.

GYIGSR-tethered substrates were shown to promote neural differentiation previously for neural stem cells on membranes,126 embryonic hippocampal neurons on

YIGSR-modified substrates,41 and human mesenchymal stem cells on silk fibroin films104 compared to laminin-coated surfaces. The role of GYIGSR in cell adhesion has been well established,126 and we demonstrated that surface-tethered GYIGSR peptide increased mESC adhesion over non-functionalized fibers. However, the numbers of cells adhering to the functionalized nanofibers was far less than those adhering to the flat laminin-coated substrate. As activity of the substrate has been found to be dependent upon the surface concentration of peptide, we calculated that the GYIGSR peptide on laminin-coated surfaces would be approximately 1.2 pmol/cm2.79 Since laminin has other bioactive sites, a higher surface concentration of GYIGSR peptide on synthetic substrates was used (17.3

± 6.6 pmol/cm2) than on laminin-coated glass, but this concentration was still lower than previous studies on PLLA fibers (57.3 pmol/cm2).66 While the concentration of GYIGSR was theoretically lower on the laminin-coated substrates, adhesion of the cells to a surface can rely on multiple cell-substrate binding sites, which is demonstrated here by the increased adhesion to whole protein over peptide-functionalized fibers. Interestingly, the reduction in cell number would typically be thought of as a negative influence on differentiation, yet, we saw increased rates of differentiation on the fiber substrates compared to the laminin substrates. This result provides even further evidence of the potential power in using topography and peptides in the differentiation process.

The authors could not find another single-peptide system that increased the rate of mESC commitment and differentiation over protein-coated substrates. Our nanofiber scaffolds, which combine topographical properties with bioactive binding sites, represent a versatile biomaterial platform that can be used for differentiation of other cell lines for neural lineages. Similar to our study, neural progenitor cells had a higher rate of differentiation on peptide (IKVAV)-functionalized peptide nanofibers than on laminin- coated substrates, where a higher percentage of cells expressed TUBB3 and fewer cells expressed GFAP on fibers than on laminin.79 However, the concentration of peptide on the nanofiber surface was higher by a factor of 103 than on laminin, where our concentration was only 10-fold higher. As our previous study was 50-fold higher GYIGSR concentration and a slightly higher fiber diameter (~338 nm), yet demonstrated similar results, we hypothesize that the faster differentiation is related to both the peptide specificity and alignment of the fibers, compared to protein-coated glass substrates. But by day 7 and day 14, cells on both substrates are at the same differentiation stage, suggesting that GYIGSR sequence plays a more important role at the early stages of neural commitment and differentiation than at the late stages. However, at later stages, the fiber topography played a more significant role in directing the neurite extensions.23, 81,

125, 127-130 Our work demonstrated that aligned GYIGSR-functionalized scaffolds provided this contact guidance for the extension of neurites along the fiber direction and showed increased total neurite length. Previous results using bioactive species demonstrated improved neurite extensions on bioactive fibers compared to neat fibers.127 This directional guidance could be useful in the end applications, but the exact role of fiber alignment in the neural induction or differentiation process is still unclear and would require further study.

Even though most of our results indicate faster differentiation on YISGR-modified fibers than on laminin, better cell performance on laminin substrates was also noted, including higher adhesion, higher expression of the Syp by day 14, and earlier and more mature glial and oligodendrocyte markers. These results, in particular the high level of initial cell adhesion, are likely related to multiple bioactive sites working synergistically as a consequence of laminin having a native ECM.3 Therefore, in order to fully mimic the cell-laminin interaction it would be interesting to investigate nanofiber substrates with multiple functionalized bioactive cues, with ability to balance each of their concentrations to promote target cell behavior. This functionality could be easily achieved by introducing functional monomers into the PCL chain with the possibility for easy post-electrospinning modification with multiple factors.58 These results, and the possibility of future modifications, demonstrate the versatility of our substrates, which could be used for culturing or differentiation of other cell lines by tethering other bioactive factors.

3.6. Conclusions

The present study describes fabrication of a versatile nanofiber platform, combining topographical features and surface-tethered bioactive species, and its application as a substrate for mESC neural differentiation. Detailed analysis of gene and protein expression results reveals that even with fewer adherent cells, GYIGSR- functionalized fibers promoted similar neural differentiation of D3 mESCs when compared to laminin-coated glass, and induced faster differentiation times on functional nanofibers

(higher expression of neural progenitor and neuronal genes Sox1, Tubb3, Cdh2, Gap43,

Syp at early time points, and earlier NES, TUBB3, GAP43 and MAP2 protein expression on synthetic nanofiber substrates). These results indicated that functional nanofiber

42 substrates could promote even faster differentiation than laminin. The aligned nanofibers can also be used as substrates to guide neurite extension. Aligned nanofibers and post- electrospinning surface modification with bioactive species can be combined to produce translationally relevant xeno-free substrates for stem cell therapy. Future development efforts are focused on additional bioactive species that are able to function as surrogates for other xenogenic factors found in differentiation media.

3.7. Acknowledgement

This work is funded by the National Institutes of Health (R15-GM113155) and

National Science Foundation (CBET BME 1603832). RKW acknowledges support from the Margaret F. Donovan Endowed Chair for Women in Engineering and MLB acknowledges support from the W. Gerald Austen Endowed Chair in Polymer Science and Polymer Engineering via the John S. and James L. Knight Foundation. OM would like to thank the National Science Foundation REU Program in Polymer Science and

Engineering at the University of Akron (DMR# 1359321).

CHAPTER IV

RGD-FUNCTIONALIZED NANOFIBERS INCREASE EARLY GFAP EXPRESSION

DURING NEURAL DIFFERENTIATION OF MOUSE EMBRYONIC STEM CELLS

In part this work has been accepted to Biomacromolecules as Philip, D.L.†;

Silantyeva, E.A.†; Becker, M.L.; Willits, R.K. RGD-functionalized nanofibers increase early GFAP expression during neural differentiation of mouse embryonic stem cells.

4.1. Abstract

Stem cell differentiation towards a specific lineage is controlled by its microenvironment. Polymer scaffolds have long been investigated to provide microenvironment cues; however synthetic polymers lack the specific signaling motifs necessary to direct cellular responses on their own. In this study, we fabricated random and aligned poly(ɛ-caprolactone) nanofiber substrates, surface-functionalized with RGD via strain-promoted azide-alkyne cycloaddition, that were used to investigate the role of a covalently tethered bioactive peptide (RGD) and nanofiber orientation on neural differentiation of mouse embryonic stem cells. Gene and protein expression showed neural differentiation progression over 14 days, with similar expression on RGD random and aligned nanofibers for neurons and glia over time. The high levels of glial fibrillary acidic protein expression at early time points were indicative of neural progenitors, and

44 occurred earlier than on controls or in previous reports. These results highlight the influence of RGD binding versus topography in differentiation.

4.2. Introduction

Embryonic stem cells (ESCs) have unique properties of self-renewal and differentiation, making them suitable choices for in vitro models to study various pathologies. With the potential to differentiate into a wide variety of lineages, ESCs can be used for tissue culture models of diseases or for therapeutic approaches for neurodegenerative diseases131-132. Soluble bioactive agents combined with a compatible protein-coated surface are the typical strategy to support and direct differentiation. While use of adsorbed protein is convenient, this method suffers from batch-to-batch variation and the presentation of bioactive protein motifs is uncontrolled and highly variable.

However, using rationally designed synthetic or biomimetic materials133, the topographical73, 134-137 and bioactive cues66, 73, 125, 137-141 can be controlled tightly to regulate the differentiation of these ESC cultures. These physical and biochemical cues, inspired by the native extracellular matrix (ECM), can be used to study the differentiation process and design therapeutic devices which take advantage of the specific features.

As the ECM plays a crucial role in regulating cell behavior, synthetic polymer scaffolds have been fabricated to mimic ECM topography using nanofibers125, 142.

Topographical factors, such as nanofiber orientation, have influenced proliferation143-144 and cell function for various tissues, e.g., nerve66, 134 and smooth muscle136. Random fiber orientations mimic the ECM structure more closely134, while an aligned fiber topography facilitates contact guidance139, cellular alignment, and directional migration, which are desirable responses for neuronal regeneration and neurite outgrowth139. Electrospinning of various synthetic polymers, including poly(ɛ-caprolactone) (PCL)138-139, 145-146, poly(L-

45 lactic acid)66, 146, poly(glycolic acid)146 and poly(DL-lactic-co-glycolic acid)146 has been used to develop nanofiber substrates for bone147, vascular tissue136, 148, and nerve tissue engineering. However, the aforementioned synthetic polymer substrates are hydrophobic and lack bioactive cell-recognition sites, resulting in low cell adhesion and proliferation.

Generally, bioactivity is added via addition of whole proteins during138, 145, 148,149-151 or after152-153 electrospinning. Although whole proteins are useful, as they add multiple binding sites for cells, electrospinning or adsorbing whole proteins eliminates control over the presentation of the bioactive sites, increasing the batch-to-batch variation in the preformed substrates. By functionalizing synthetic nanofibers after electrospinning with a tethered synthetic peptide, the bioactivity and concentration of the peptide can be maintained2, 58, 66.

Covalently tethering bioactive peptides to the surface of the nanofiber is an attractive alternative to adsorbed proteins. Strain-promoted azide-alkyne cycloaddition

(SPAAC) reactions has been used widely to functionalize the surfaces of nanofibers due to the high eﬃciency, mild reaction conditions and orthogonality of the reactants58, 66, 154.

This rapid and convenient method of bioconjugation is scalable and highly reproducible in comparison to other surface-tethering techniques such as plasma treatment, wet chemical methods, surface graft polymerization154-155. The SPAAC method of surface modification of the nanofibers post electrospinning affords precise control over the amount of functionality available on the surface58. The use of 4-dibenzocyclooctynol (DIBO) as an initiator of the ε-caprolactone polymerization results in end-functionalized PCL, where the reactive handle survives the electrospinning process2. Strained cyclooctynes, such as

DIBO, react quickly with azides due to ring strain,62 allowing fast surface functionalization

46 in metal-free conditions. In addition, the aromatic rings afford characterization of the peptide surface concentration by UV-visible spectroscopy2.

We have shown previously139 that aligned nanofibers functionalized with tethered GYIGSR peptide mimicked adsorbed laminin during mESC neural differentiation. Therefore, we were interested in investigating how other bioactive laminin peptides influenced the neural differentiation process. RGD is an ubiquitous peptide that has been previously shown to mimic fibronectin156, but is also found on the α chain of laminin157. The RGD peptide has been used in studies of mESC pluripotency151 and neural stem cell differentiation158 and has clear integrin interaction sites with cells159. Here, we investigated RGD-tethered nanofibers to compare random and aligned nanofiber orientations on mESC neural differentiation.

4.3. Experimental

4.3.1. Materials

4.3.1.1. Nanofibers

All materials were used as received unless otherwise stated. Tetrahydrofuran

(anhydrous, ≥99.9%, inhibitor-free), chloroform (anhydrous, contains amylenes as stabilizer, ≥99%), and calcium hydride (reagent grade, 95%) were purchased from Sigma-

Aldrich (St. Louis, MO). Phenylacetaldehyde (98%, stabilized), lithium di-isopropylamide mono(tetrahydrofuran) (1.5 M solution in cyclohexane, AcroSeal™), iodotrimethylsilane

1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) was purchased from Oakwood Products, Inc.

(Estill, SC). Sodium sulfate anhydrous (ACS grade) and methanol (ACS grade), hydrochloric acid (36.5-38%, ACS Grade) were purchased from VWR International

(Radnor, PA).

Dry toluene (HPLC Grade, 99.7%, Alfa Aesar) for polymerization was purified and dried on an Inert Pure Solv system (MD Solvent Purification system, model PS-MD-3) and degassed using three cycles of the freeze-vacuum-thaw. ε-Caprolactone (ε-CL, 99%,

ACROS Organics™) was dried over calcium hydride under nitrogen overnight and distilled under reduced pressure. Magnesium 2,6-di-tert-butyl-4-methylphenoxide catalyst

106 2 [Mg(BHT)2(THF)2] , 4-dibenzocyclooctynol (DIBO) initiator and DIBO-end functionalized poly(ԑ-caprolactone) were synthesized using methods described previously139. Resins for peptide synthesis (Novabiochem®) were purchased from EMD

Millipore (Billerica, MA). Fmoc-amino acids were purchased from Aapptec (Louisville, KY).

Square (22 x 22 mm) and round (8 mm) Fisherbrand™ borosilicate cover glasses

(#1.5) were washed with methanol / toluene / methanol, dried with nitrogen, and cleaned with UV light (355 nm) for 3 min prior to use. A UVO Cleaner, Model #42A UV light unit was used to clean the glass coverslips for nanofiber collection. After nanofibers were collected on the glass coverslips, the nanofiber mats were glued to the edges of a glass slide by a silicone sealant and dried under vacuum overnight.

4.3.1.2. Cell study

Materials used during this study included the following: D3 mESCs (ATCC); ES-qualified

0.1% gelatin (Embryomax, Millipore); D3 growth medium consisted of Dulbecco’s

Modification of Eagle’s Medium (DMEM) (Corning) prepared with sodium bicarbonate

(Sigma), supplemented with 10% ES-qualified fetal bovine serum (Millipore), 10-4 M β- mercaptoethanol (Millipore Embryomax), 4 mM L-glutamine (Life Technologies), 4.7 mM

4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (Hyclone GE Healthcare), and 1000 units/mL human recombinant leukemia inducing factor (GlobalStem); trypsin-EDTA

(Sigma Aldrich); flow cytometry antibodies: anti-SSEA1 (BioLegend 125606) and isotype control (BioLegend 401611). Neural differentiation medium consisted of 70% DMEM/F-

12 (Corning), 20% neurobasal medium (Life Technologies), 1X N2 supplement, 20%

PluriQ serum replacement (GlobalStem), 10-3 M sodium pyruvate (Sigma), 2 mM L- glutamine (Life Technologies), and 2 μM retinoic acid (Sigma). TRIzol reagent (Life

Technologies); cDNA Synthesis Kit (Quantabio), SYBR Green (Quantabio).

Paraformaldehyde (Fisher Scientific); Triton-X (Sigma); sodium borohydride (MP

Biomedicals). Primary antibodies: NES (Abcam 134017; 1:10,000), SSEA1 (DSHB

MC480; 1:8), POU5F1 (Abcam 198857; 1:1000), SOX1 (Cell Signaling Tech 4194; 1:200),

GFAP (BioLegend 82401; 1:1000), and TUBB3 (Abcam 78078; 1:500) for early time points

(days 1 and 3); GFAP, TUBB3, MAP2 (Abcam 11267; 1:500), GAP43 (Abcam 16053;

1:500), and OLIG1 (Abcam 53041; 1:500). Nuclei stain: H33342 (Life Technologies

H1399). Secondary antibodies were diluted at 1:400; goat anti-mouse IgM AF546 (Life

Technologies A21045), donkey anti-rabbit IgG AF647 (Life Technologies A31573), goat anti-chicken IgY AF488 (Life Technologies A11039), goat anti-mouse IgG2a AF546 (Life

Technologies A21133), and goat anti-mouse IgG1 AF546 (Life Technologies A21123).

4.3.2. Experimental methods

4.3.2.1. Fabrication of Synthetic Nanofibers

Size exclusion chromatography (SEC) was used to determine molecular mass and molecular mass distributions (Đm). Chromatograms were collected on a Tosoh EcoSEC

HLC-8320GPC using refractive index detector and N,N-dimethylformamide (DMF) containing 0.1 M lithium bromide as the eluent at a flow rate of 0.3 mL/min and 40 °C. The

2 columns were calibrated using narrow molecular mass poly(styrene) standards (20 standards from 0.5 kDa to 5,480 kDa). Nanofiber scaffolds were sterilized by ethylene oxide using an Anprolene benchtop sterilizer (Anderson Products, Inc., Haw River, NC) according to the manufacturer’s protocol for 12 h at room temperature and 35% humidity

(concentration of ethylene oxide is about 0.5 g/L), purged for at least 48 h and stored in a vacuum desiccator until further use.

4.3.2.2. Electrospinning conditions and nanofiber collection

The electrospinning setup for aligned nanofiber scaffolds is shown in Figure 4.1

(B, D). For aligned fiber scaffolds, the DIBO-terminated PCL was dissolved in HFIP (17%

(w/v)) to yield a clear, slightly viscous solution. The solution was placed in a 2 mL glass syringe with a 22 gauge needle for aligned and 23 gauge needle for random fibers (JG22-

0.5X or GJ23-0.5X, Jensen Global Dispensing Solutions). A voltage of 15 kV was applied to the solution, and the tip-to-collector distance was set to 10 cm. Aluminum foil was used as the grounded collector for random fibers and metal plate with gaps (24 x 110 mm) for aligned fibers. Random nanofibers were collected on glass cover slides placed on

50 aluminum foil. Aligned nanofibers were collected by placing cover glasses in between the gaps of the collector. The collected nanofiber mats were glued to the edges of a glass slide with a silicone sealant and dried under vacuum overnight.

4.3.2.3. Characterization of diameter and orientation

Nanofiber dimensions and alignment were imaged by scanning electron microscope (SEM) with an applied voltage of 5 kV (JSM-7401F, JEOL, Peabody, MA).

Samples were sputter coated for 30 seconds with silver under nitrogen atmosphere prior to imaging. High voltage power supply (ES30P-5W, Gamma High Voltage, Ormond

Beach, FL) was used for electrospinning. The variation in nanofiber diameters was measured on at least 3 independent samples (5 images of each sample with >150 fibers per sample) using ImageJ and reported as an average ± standard deviation. The

DirectionalityTM plugin of ImageJ was used to quantify the relative degree of alignment of the scaffolds by analyzing the angle distribution of fibers. The values are reported as an average ± standard deviation. Fityk 0.9.8 was used to fit a Gaussian function (red curve) and calculate average angle as the peak of the distribution fit. Angles for aligned fibers were normalized to 0. The highest peak was normalized to 1.

4.3.2.4. Solid phase peptide synthesis

N3-GRGDS and N3-GRGES peptides were synthesized using standard FMOC conditions on a CEM Discovery microwave peptide synthesizer. The N-terminus was derivatized with 6-azidohexanoic acid139, 160. The peptides were purified by precipitation from trifluoroacetic acid into cold diethyl ether and wash 3 times into cold diethyl ether, followed by dialysis against water for 3 days and lyophilization. The desired peptide product was conﬁrmed by electrospray ionization mass spectrometry.

4.3.2.5. Nanofiber functionalization

Nanofiber covered glass slides were dipped into a solution of the respective azide- functionalized peptide (1.59 µmol/mL) in 1:2 water/methanol (v/v) solution for 5 min. The cover slips with functionalized nanofibers were rinsed with 1:2 water/methanol (v/v) solution, blown with nitrogen and dried overnight in a desiccator. Scaffolds were sterilized using an ethylene oxide exposure cycle for 12 h, degassed for 2 days and stored in a vacuum desiccator until further use.

The extent of functionalization with each peptide (reported as an average ± standard deviation) was conﬁrmed using UV−visible spectroscopy (SynergyTM MX plate reader from BioTek, with spectral resolution 1 nm), using chloroform as a solvent. The peak intensity at 306 nm (which corresponds to π-π* transition in alkyne bond in the DIBO- functionalized polymer) decreases after reaction with azide-functionalized peptide in comparison with fibers before functionalization. The surface concentrations of the

GRGDS or GRGES peptide were calculated by dividing number of moles of reacted alkyne groups by surface area of the fibers. The surface area of the fibers was calculated by finding the volume of the fibers from measured mass of the fiber mats and measured by

SEM fiber diameter. Density of the DIBO-PCL was assumed to be the same as of PCL

(1.145 g/cm3).

4.3.2.6. mESCs culture

D3 mESCs were maintained pluripotent on feeder-free gelatin coated culture flasks in an incubator at 37 ºC and 5% CO2. Growth medium for maintaining pluripotent mESCs was changed daily. The cells were passaged once they reached 75-85% confluency; they were washed with 1x PBS and incubated in 1x trypsin EDTA for 2 min at 37 ºC. The detached cells were neutralized with growth medium and centrifuged (160 g for 5 min at

4 ºC) to collect in a pellet. Cells were seeded at 20,000 cells/cm2 for further culture; pluripotency was determined using flow cytometry by staining against SSEA1. Anti-

SSEA1 was incubated with 250,000 cells for 1 hour at 4 °C and then analyzed using flow cytometry against an isotype control. Cells which expressed an average of 98.8% SSEA1+ were used for neural differentiation of mESCs.

4.3.2.7. Neural differentiation

Pluripotent mESCs were seeded in neural differentiation medium at a seeding density of 125,000 cells/cm2 on the substrates, and neural differentiation was induced using retinoic acid. The neural differentiation profile was analyzed at days 1, 3, 7, and 14 after seeding; pluripotent, neural progenitor, neuronal, and glial markers were analyzed using gene and protein expression.

4.3.2.8. Gene expression

RNA isolation was performed using TRIzol Reagent and reverse transcribed using a cDNA synthesis kit, according to the manufacturer’s protocols. Quantitative PCR was performed using SYBR Green on pluripotent, neural progenitor, neuronal, and glial genes

(Applied Biosciences 7500 qPCR system) using MIQE guidelines. Data analysis of ΔCt was calculated by subtracting the Ct of the gene of interest from housekeeping genes (β- actin and Gapdh) at the time point (days 1, 3, 7, or 14 of differentiation); ΔΔCt was calculated as the difference between the ΔCt(timepoint) - ΔCt(pluripotent). Data is represented as log2(fold change). Primer sequences can be found in Table 1. Note that we use standard gene and protein symbols, with italicized symbols indicating genes while proteins are not italicized. Pou5f1 is seen in many reports as Oct4.

Table 4.1. Summary of genes and their sequence utilized for gene analysis Gene Sequence (Reverse) Sequence (Forward) GGC ACT TCA GAA ACA TGG Pluripotent Pou5f1 GAA GCC GAC AAC AAT GAG AAC TCT CAC CTC AAG ATG TCC CTT Nes GGA AAG CCA AGA GAA GCC T Neural AGT C Progenitor GTA CAG TAT TTA TCG TCC GCA GGC AGT CAT ACA AAA GTT Sox1 GA GGC Pax6 AAG GGC GGT GAG CAG ATG T CAT GCT GGA GCT GGT TGG Tubb3 GTG GAC TTG GAA CCT GGA AC CCT CCG TAT AGT GCC CTT TG GAC CCA GAG TGT GTG AGT TTA CCA CTA ATG CCA GTT TCT Neuronal Map2 T CTC T AGG AGG AGA AAG ACG CTG Gap43 TCA GGC ATG TTC TTG GTC AG TA CCA CCA GTA ACA TGC AAG Gfap GCG ATA GTC GTT AGC TTC GTG Glial AGA Olig1 AGC AAC TAC ATC GCT CCT TG TCC AGA CTT CTC TCC CAG AC CAC GGT TGG CCT TAG GGT TCA GCT GTA TTC CCC TCC ATC β-actin G GTG Housekeeping GTG GAG TCA TAC TGG AAC ATG Gapdh AAT GGT GAA GGT CGG TGT G TAG

4.3.2.9. Protein expression

At the appropriate timepoint, samples were fixed with freshly prepared 4% buffered paraformaldehyde, washed, and stored in PBS at 4 °C. Cells were permeabilized in 0.5% and 0.1% Triton-X for 10 and 5 min respectively, and permeabilized with 1mg/mL of sodium borohydride twice for 4 min. Blocking was performed with BSA and 0.1% Triton-

X for 1 hour. The cells were then stained with primary antibodies overnight at 4 °C, followed by staining with the appropriate secondary antibody overnight at 4 °C. Proteins of interest were NES, SSEA1, POU5F1, SOX1, GFAP, and TUBB3 for early time points

(days 1 and 3) and GFAP, TUBB3, MAP2, GAP43, and OLIG1 for later time points (days

7 and 14).

4.3.2.10. Analysis of images

Images were captured on an inverted fluorescent microscope at exposure times set by controls that had only secondary antibodies and nuclei stain. At least five images were obtained from each sample. Image analysis was done on ImageJ (National Institutes of Health, v1.5h)161.

4.3.2.10.1. Cell aggregate size

Using ImageJ, the sizes All images were captured at the same exposure as the respective control. A threshold for captured control images (no primary antibody) was set at <0.1% pixel intensity for each channel. The acquired brightness and contrast setting from the control was applied to the appropriate fluorescent channel on an image, so as to express only protein-positive cells. If necessary, the images were further adjusted until a distinct protein morphology was observed, and cells were then manually counted as protein positive. These positive cells were then normalized to the total number of cells labeled with any protein, to obtain a percent positive number. Results are expressed as

+ or – of the protein; for example, if a sample was labeled with SOX1, GFAP, and TUBB3 and showed only GFAP labeling, the result would be expressed as GFAP+ (SOX1- /

TUBB3-).

4.3.2.10.2. Percent positive cells

All images were captured at the same exposure as the respective control. A threshold for captured control images (no primary antibody) was set at <0.1% pixel intensity for each channel. The acquired brightness and contrast setting from the control was applied to the appropriate fluorescent channel on an image, so as to express only protein-positive cells.

If necessary, the images were further adjusted until a distinct protein morphology was observed, and cells were then manually counted as protein positive. These positive cells

55 were then normalized to the total number of cells labeled with any protein, to obtain a percent positive number. Results are expressed as + or – of the protein; for example, if a sample was labeled with SOX1, GFAP, and TUBB3 and showed only GFAP labeling, the result would be expressed as GFAP+ (SOX1- / TUBB3-).

4.3.2.10.3. Neurite extension

Neurite extension was quantified by tracing TUBB3+ neurites on aligned and random substrates. Using the NeuronJ plugin in ImageJ, these tracings were quantified and reported as total neurite length per mm2. In addition, the direction of neurite outgrowth was measured utilizing the Directionality™ plugin in ImageJ, similar to the nanofiber orientation analysis above. The direction of the aligned fibers was determined from the phase contrast image and set to 0°.

4.3.2.11. Statistical analysis

Each experimental group consisted of at least three biological replicates, and quantitative data was represented as average ± standard deviation. Two-sample t-test with 95% confidence interval and a significance value of p > 0.05 was performed to prove that there was no statistical difference between diameters of random and aligned fibers as well as to show statistical difference between neurite alignment cultured on different substrates. Two-way ANOVA with Bonferroni post-hoc test was utilized to determine significance between gene expression using ΔΔCt, with p<0.05 considered significant.

Kruskal-Wallis test with Bonferroni correction was utilized to determine significance in protein expression and neurite extension, with p<0.05 considered significant. Pearson’s correlation was performed to investigate correlations between protein expression (GFAP,

TUBB3, and OLIG1), and number and size of aggregates.

4.4. Results

4.4.1. RGD and RGE functionalized synthetic scaffolds

4.4.1.1. Synthesis of functionalized polymer

DIBO-end functionalized poly(ԑ-caprolactone) was synthesized by the ring- opening polymerization of ԑ-caprolactone using standard Schlenk techniques as shown in

Scheme 1. DIBO was used as initiator to introduce functionality at the polymer chain end to facilitate efficient metal-free surface modification with peptides post-polymerization and post-electrospinning. The purity of the polymer and successful incorporation of DIBO into the polymer chain was shown by the 1H NMR spectra (the peaks at δ = 5.56, 3.10 and

2.93 ppm corresponding to protons from DIBO (Figure 7.11, Appendix A) and UV-visible spectroscopy (λmax = 306 nm corresponds to π-π* transition of the strained alkyne in DIBO,

Figure 7.12, Appendix A). The use of Mg(BHT)2(THF)2 as a catalyst yielded a controlled polymerization with high (>90%) monomer conversion within short period of time (13 min) at 30 °C. The use of these catalytic conditions affords high molecular mass and narrow molecular mass distribution polymer (Mn = 60,600 Da, Mw = 83,700 Da, ĐM = 1.38) as shown in Figure 4.1.

Scheme 4.1. DIBO-end-functionalized poly(ε-caprolactone) was synthesized via ring- opening polymerization of ε-caprolactone using DIBO as an initiator and Mg(BHT)2(THF)2 as a catalyst. Surface of DIBO-PCL was modiﬁed post-electrospinning with GRGDS or GRGES peptides via strain-promoted azide-alkyne cycloaddition.

B C D E

A F

Figure 4.1. (A) Analysis by DMF size exclusion chromatography confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 60,600 Da, Mw = 83,700 Da, ĐM = 1.38). Molecular mass was determined against polystyrene standards. (B, D) Nanofibers were fabricated by electrospinning from a solution of DIBO- terminated poly(ε-caprolactone) in HFIP (17% w/v) and a voltage of 15 kV. Cover glasses were placed on aluminum foil or in the gaps of metal collector plate for collecting of random or highly aligned nanofibers. (C, E) Analysis of SEM images was performed to estimate topography of nanofibers. NIH ImageJ was used to estimate fiber diameter (ᴓ = 212 ± 63 nm for aligned and 219 ± 36 nm for random fibers) and alignment (DirectionalityTM plugin, average angle = 0 ± 6° for aligned and -2 ± 111° random nanofiber scaffolds). (F) Post- electrospinning modification with GRGDS or GRGES peptides via strain-promoted azide- alkyne cycloaddition. The concentration of GRGDS or GRGES peptides was measured using UV–visible spectroscopy by comparison of absorbance at 306 nm (peak corresponding to DIBO groups) before (black curve) and after (green curve) post- electrospinning modification. 4.4.1.2. Characterization of diameter and orientation of nanofibers DIBO-functionalized poly(ԑ-caprolactone) was used to fabricate highly aligned

(with a narrow angular distribution 0 ± 6°, average ± standard deviation) and random (-2

± 111°) nanofiber scaffolds (Figure 7.13, Appendix A) by using different electrospinning setups (Figure 4.1 B, D). Using aluminum foil as a collector yielded random nanofibers.

Use of a conductive metal frame with gaps afforded fabrication of aligned nanofibers. The 58 quality of the Gaussian fit calculated by the DirectionalityTM plugin was high for aligned fibers (0.91 ± 0.06) and low for random fibers 0.41 ± 0.2, average ± standard deviation).

Diameters of aligned and random fibers were not statistically different (ᴓ = 212 ± 63 nm and 219 ± 36 nm accordingly, p = 0.127). The distributions of nanofiber diameters are shown in Figure 7.14, Appendix A.

4.4.1.3. Solid phase peptide synthesis End-functionalization of the respective peptides with 6-azidohexanoic acid serves as a spacer for the peptides to react with DIBO groups on the surface of the nanofibers.

+ ESI mass spectrometry confirmed the mass and purity of each peptide; [M] of N3-GRGDS

+ = 630.01 Da, yield = 84% and [M] of N3-GRGES = 644.27 Da (Figures 7.15 and 7.16 respectively, Appendix A).

4.4.1.4. Post-electrospinning surface modification and quantification Post-electrospinning modification of nanofibers with either GRGDS or GRGES peptide via strain-promoted azide-alkyne cycloaddition was carried out by dipping nanofiber scaffolds in the water-methanol solution of azide-functionalized peptides at ambient temperature. The peak intensity at 306 nm (which corresponds to π-π* transition of DIBO) decreased after reaction with azide-functionalized peptide in comparison with fibers prior to functionalization (Figure 4.1F). Quantitative assessment of the amount of the peptides attached to the surface of nanofibers with different orientation gave comparable values. The surface concentration of GRGDS peptide was determined to be

10.8 ± 5.8 pmol/cm2 for random and 19.8 ± 2.1 pmol/cm2 for aligned nanofibers; and of

GRGES peptide was measured to be 24.7 ± 8.4 pmol/cm2 for random and 8.4 ± 3.8 pmol/cm2 for aligned nanofibers. The degree of functionalization with peptides was calculated as the ratio of reacted DIBO groups to the total amount of polymer chains (0.10

± 0.06 for random and 0.20 ± 0.02 for aligned nanofibers with GRGDS; and 0.24 ± 0.08 for random and 0.08 ± 0.04 for aligned nanofibers with GRGES).

4.4.2. mESC response

Control nanofibers with RGE (null peptide), or too little RGD (1.4 ± 0.9 pmol/cm2 and 1.9 ± 1.5 pmol/cm2 on random and aligned nanofibers respectively), had insufficient cell adhesion for a complete analysis of gene expression or any protein expression analysis. An example of the gene expression for the controls at day 3 for Gfap is in Figure

7.17, Appendix A.

4.4.2.1. Gene expression

To investigate the neural differentiation of mESCs on the RGD nanofibers, we calculated fold change to describe the up or down regulation of genes via ΔΔCt using 2 housekeeping genes within each sample and pluripotent mESCs as the comparator. A log2(fold change) of 0 shows no difference between expression of pluripotent mESCs.

First, as expected during the differentiation process, the pluripotent gene, Pou5f1 expression (Figure 7.18A, Appendix A), decreased in all groups over time. By day 7, the gene was not expressed in random nanofibers in quantities that could be detected within

35 cycles.

Next, we investigated Sox1 expression (Figure 4.2A) to demonstrate differentiation toward neural progenitors. Sox1 is upregulated in all samples at days 1 and 3. At day 7, a statistical increase in Sox1 upregulation occurred in random nanofibers compared to days 1 and 3 that was sustained at day 14, while the upregulation at day 7 remained similar to days 1 and 3 in both aligned nanofibers and fibronectin-coated surfaces. For days 7 and 14, a fold change of 250 ± 180 and 31 ± 14 was found on random nanofibers, compared to fold change of 1 ± 0 and 2 ± 4 on aligned nanofibers, and 3 ± 10 and 9 ± 4

60 fibronectin-coated substrates. Nes, another neural precursor cell marker, was not found on fibronectin samples, and upregulated beginning at day 1 for both aligned and random fiber samples; no statistical differences were found between samples (Figure 7.18B,

Appendix A).

Further differentiation of neural precursors cells results in either glial or neuronal lineages. Gfap expression, indicates glial expression, (Figure 4.2B) was upregulated on both nanofiber topographies beginning at day 1. The upregulation was noted for days 1,

3, and 7 on both random and aligned nanofibers. A fold change of 102 ± 43 and 47 ± 33 was observed on random nanofibers at days 1 and 3 respectively, compared to 53 ± 21 and 38 ± 4 on aligned nanofibers. In contrast, Gfap on fibronectin-coated surfaces was downregulated until day 7. However, by day 14, cells on fibronectin-coated surfaces showed upregulated Gfap, which increased to the same level as the upregulation of cells on the nanofibers. At day 14, a fold change of 67 ± 52 was found on fibronectin-coated surfaces, compared to 30 ± 25 on aligned and 106 ± 112 on random nanofibers.

Figure 4.2. Summary of neural precursor (A), glial (B, C), and neuronal (D-F) gene expression over 14 days of neural differentiation of mouse embryonic stem cells, on fibronectin coated surfaces and RGD functionalized aligned and random nanofibers. Gene expression is represented as log2 (fold change). Statistical differences are highlighted between groups with p<0.05 considered significant. As Gfap was upregulated early, we were interested in the potential to derive oligodendrocytes. Oligodendrocyte expression was determined by Olig1 expression

(Figure 4.2C); at days 3, 7, and 14, higher expression was found on both nanofiber topographies than fibronectin-coated surfaces. On fibronectin-coated substrates, cells had upregulated Olig1 by day 14, which was statistically higher than on fibronectin at days

3 and 7. Cells on aligned substrates had a similar response, with upregulation of Olig1 at day 14 that was statistically increased over day 3. However, the upregulation of Olig1 on random substrates was statistically increased earlier and sustained these levels through day 14. For days 7 and 14, a fold change of 905 ± 222 and 284 ± 177 was found on

62 random nanofibers, compared to a fold change of 1 ± 2 and 18 ± 20 on aligned nanofibers, and a fold change of -9 ± 5, and 5 ± 2 on fibronectin-coated substrates.

Expression of neuronal genes should advance from Pax6 to Tubb3 to Map2 and

Gap43. Pax6 expression exists in early tissue development from the embryo. The progression toward neurogenesis is indicated by Tubb3 expression, and finally towards axonal growth, indicated by Gap43 and Map2 expression. Compared to mESCs, Pax6 was upregulated beginning at day 1 in all samples. Pax6 upregulation was consistently and statistically increased for both random and aligned nanofibers over fibronectin-coated substrates. Tubb3, however, was downregulated on days 1 and 3 on fibronectin-coated substrates. In contrast, cells on both aligned and random nanofibers samples showed statistical upregulation of Tubb3 beginning at day 1 (Figure 4.2E). At days 7 and 14, Tubb3 was slightly upregulated in cells on fibronectin-coated substrates but was statistically higher on both aligned and random nanofibers for those time points. A fold change of

1226 ± 668 and 249 ± 147 was found on random nanofibers at days 7 and 14 respectively, compared to a fold change of 156 ± 75 and 24 ± 12 on aligned nanofibers, and -1 ± 2 and

0 ± 3 on fibronectin-coated substrates. For Map2, cells on all substrates had downregulated expression on days 1 and 3, and by day 7, the expression was upregulated

(Figure 4.2F). The upregulation was higher on fibronectin-coated substrates and random nanofibers than on aligned nanofibers. A fold change of 29 ± 9 was found on fibronectin- coated substrate, compared to 105 ± 78 on random nanofibers, and 4 ± 1 on aligned nanofibers for day 7 of neural differentiation. Gap43 expression remained similar to its pluripotent state for all fiber samples and was upregulated by day 14 on fibronectin sample

(Figure 7.18C, Appendix A).

4.4.2.2. Protein expression

The profile of protein expression was tracked over 14 days using pluripotent, early and late neural markers (Figure 7.19, Appendix A). We saw a significant decrease of pluripotent markers (SSEA1 and POU5F1) by day 3 of neural differentiation on both random and aligned nanofibers (Figures 7.20A and 7.20B respectively, Appendix A). By day 3, POU5F1 was expressed on 60 ± 20% of the cells on aligned nanofibers, compared to 22 ± 16% of the cells on random nanofibers. In addition, a decrease in dual labeling of

SSEA1+ / POU5F1+ / NES- labeling was also observed by day 3 for random and aligned nanofibers. As pluripotent marker expression decreased, neural precursor marker expression increased. An increase in NES+ expression was found from day 1 to day 3, although not statistically significant (Figure 7.20C, Appendix A). NES expression increased from 0 ± 1% to 16 ± 27% of the cells on aligned nanofibers, compared to 9 ±

8% to 11 ± 16% of the cells on random nanofibers. Compared to day 1, a decrease in

SOX1 was observed by day 3 on random nanofibers, while SOX1 expression remained similar on aligned nanofibers (Figure 7.20D, Appendix A); SOX1 expression decreased from 30 ± 22% to 7 ± 15% of the cells on random nanofibers at days 1 and 3 respectively, compared to 20 ± 15% and 31 ± 5% for aligned nanofibers.

Similar to the gene expression data, we found that 81 ± 15% and 79 ± 15% of the cells were GFAP labelled on random and aligned nanofibers, respectively, at day 1 of neural differentiation (Figure 4.3A). Co-labeling with SOX1 was also evident at day 1

(Figure 7.21A, Appendix A). In addition, GFAP labeling was consistently high over the course of 14 days, with only a decrease in GFAP+ (TUBB3- / OLIG1-) expression on random fibers at day 7 compared to day 3. GFAP expression decreased from 84 ± 20% to 35 ± 18% of the cells on random nanofibers at day 3 and 7, respectively, while

64 expression increased slightly from 53 ± 36% to 70 ± 28% of the cells on aligned nanofibers.

Total OLIG1+ expression of 14 ± 19% to 19 ± 22% of the cells on random nanofibers at day 7 and 14 respectively, compared to 6 ± 10% to 15 ± 20% of the cells on aligned nanofibers (Figure 4.3C).

Next, we compared neuronal protein expression between nanofiber topographies.

We found significantly higher TUBB3+ (SOX1- / GFAP- and GFAP- / OLIG1-) expression at day 7 (Figure 4.3B) compared to days 1, 3, and 14 on random nanofibers. TUBB3+ expression increased from 6 ± 7% to 49 ± 21% on random nanofibers, compared to 13 ±

6% to 32 ± 36% on aligned nanofibers from days 3 to 7 of neural differentiation. We also investigated the expression of mature neuronal markers MAP2+ (Figure 4.3D) and

GAP43+ (Figure 7.20E, Appendix A) at days 7 and 14. We observed similar MAP2+

(GFAP- / GAP43-) expression on both aligned and random nanofibers. Cells were also double labeled (GFAP- / MAP2+ / GAP43+), on both nanofiber topographies (Figure 4.3D and Figure 7.21B, Appendix A), with similar total labeling on 48 ± 12% and 29 ± 9% on aligned nanofibers, and 35 ± 15% and 37 ± 29% on random nanofibers, at days 7 and 14 respectively. In addition, cells were distinctly different in their glial and neuronal morphologies (Figure 7.21C, Appendix A) and very few cells were multi-labeled with both glial and neuronal proteins (e.g., GFAP+ / MAP2+ / GAP43- or GFAP+ / MAP2- / GAP43+ or GFAP+ / MAP2+ / GAP43+).

Figure 4.3. Protein quantification of glial (A, C) and neuronal (B, D) proteins. Cells were considered positive for the respective protein if they possessed the appropriate protein morphology. Prior to morphology assessment, the images were thresholded according to the brightness and contrast settings of control images, which were samples stained with secondary antibodies and nuclei stain only. Protein positive cells were normalized to the total number of cells expressing at least one protein label, and expressed as a percentage. Data is represented as average of single and double labeled protein ± standard deviation of total labeled proteins. Double labeling of GFAP is noted with SOX1 (days 1 and 3) and OLIG1 (days 7 and 14); TUBB3 with SOX1; OLIG1 with GFAP; and MAP2 with GAP43. * represents statistical difference between respective topography timepoints and groups, with a p<0.05 considered significant.

4.4.3. Cell morphology, neurite extension and alignment

Both glia and neurons have distinct morphology that developed with time during culture. Neurite morphology showed by day 3 and glial morphology by day 14 (Figure

4.4). We compared neurite extension length by quantifying total neurite length per mm2 of traced TUBB3+ neurites on random and aligned topographies of RGD functionalized nanofibers. At day 7 of neural differentiation, total neurite length of 185.99 ± 213.35 mm per mm2 was found on aligned nanofibers, compared to 672.33 ± 497.38 mm per mm2 on random nanofibers (Figure 4.5). However, these differences were not significant.

Neurites followed the nanofiber direction on aligned fibers, but extended in all directions on random topography (average orientation angle was 2.1 ± 16.4° and -11.9 ± 78.1° accordingly, Figure 4.5). The full width of the Gaussian peak at the half of its maximum was much narrower on aligned (30.4°) than on random fibers (115.8°). The small peaks around 45° on both topographies correspond to the square or rectangular shape of analyzing images and are in accordance with previous analysis139.

Figure 4.4. Glial (A) and neuronal (B) protein expression of mESCs for 14 days of neural differentiation. Images have been adjusted to control thresholds to highlight cells expressing positive markers and have been enhanced for display. At early time points, cells expressed GFAP, however more distinct glial morphology was seen at later time points. Similarly, neuronal expression was also found at early time points, however more distinct neurites were found at later time points of neural differentiation. Scale bar of 20 µm.

Figure 4.5. Neurite extension tracings. TUBB3 from day 7 on (A) aligned and (B) random nanofibers were used for (B, E) neurite tracings and (C, F) directionality measurements. (B) The aligned traces were rotated to orient the aligned fibers (from phase image) at 0°, and directionality of these neurite traces was measured. Gaussian fit (the red curve) was applied to measure neurite orientation. Scale bar of 50 µm.

4.4.4. Correlations

Water As we observed many cells growing in aggregates, and a high deviation in mature glial (GFAP+ and OLIG+) and neuronal (TUBB3+) protein expression, we investigated if there was any correlation between protein expression, aggregate size, and number of aggregates found on the substrates. At days 7 and 14 of neural differentiation, we found a significantly high inverse correlation between GFAP+ and TUBB3+ expression

(-0.826 and -0.628, respectively) (Figures 7.22A and 7.22C respectively, Appendix A).

Strong positive correlations were found between TUBB3+ expression and aggregate area

(0.595) at day 7 and TUBB3+ expression and number of aggregates (0.682) at day 14.

Furthermore, at day 14 of neural differentiation, we also found a strong correlation between GFAP+ and OLIG1+ (0.570) expression (Figure 7.22D, Appendix A).

4.5. Discussion

Control of stem cell differentiation into a specific neural lineage is important to push stem cell therapy to clinical practice in treatment neurological diseases, however it has been a great challenge. There are some reports investigating various factors that can influence stem cells neural differentiation. For example, nanofiber topography has been demonstrated to play an important role in ESC neural differentiation135. In particular, neural stem cell differentiation was faster on nanofibers than on microfibers36. The rate of neural differentiation on aligned fibers was increased in some reports66, 135, and was similar to random fibers in other reports36. It was also demonstrated that aligned orientation of fibers could guide the neurite outgrowth36, 135, 139, and have the potential to restore cellular architecture that is lost after nerve injury135. To investigate the effect of nanofiber orientation on neural differentiation of mESC, we fabricated random and aligned nanofibers. By using different electrospinning setups (Figure 4.1), we were able to fabricate nanofibers different in orientation, but similar in diameters.

While unfunctionalized PCL fibers have been found to support limited differentiation,36, 135 coating of fibers with whole ECM proteins enhanced the response80,

137-138. However, the use of animal- or human-derived proteins limits their clinical application due to potential immune response. Short peptides can be used as a mimic of whole proteins in order to advance application of stem cell therapy to clinical practice.

Chemical tethering of bioactive molecules is preferred over physical adsorption since it

70 can prevent their loss over time, but typically requires multi-step processing and harsh conditions2. Reaction conditions including solvent system is important when choosing method of surface functionalization so nanoﬁber topography could be preserved. SPAAC used for surface modification of nanofibers, allowed scalable and efficient method that can be performed under simple metal-free conditions: ambient temperature, short times, and water/methanol-based solvent system2. This surface modification was achieved by reaction of DIBO incorporated into the polymer chain and azide-functionalized peptide, involving synthetic molecules without any animal or human components. Introducing azide functionality to the peptide could be easily performed by using azide-containing acid and allows to attach different amino acid sequences to the nanofiber surface in a controlled manner, allowing to induce different cellular responses and making the method versatile.

Another regulatory limitation is the lack of direct methods for surface-bonded peptide quantification. Using DIBO as a functional group incorporated in the polymer allows easy quantitative assessment of the amount of peptide that attached to the surface via SPAAC by UV-visible spectroscopy58, 66. Thus, to have an insight into which factors can help to control ESC differentiation to a specific neural lineage, we investigated the influence of topography (aligned or random orientation) and tethered peptide (RGD) on ESCs neural differentiation. This result was achieved through material design using SPAAC and different electrospinning setups that allow to fabricate nanofibers with similar diameters and amount of tethered peptide, but different orientation. While other groups attempted to control differentiation to specific lineage by topography or bioactive species, there are only few reports investigating influence of their combination and achieved control of both chemically tethered peptide and topography.

RGD was selected as the binding peptide for this study to further characterize potential binding sites on laminin to control neural differentiation. However, it is clear that laminin is not the only protein of interest when studying RGD, as fibronectin is generally the target protein when studying RGD156 and RGD peptide was found to be a primary interaction site for mESCs on collagen scaffolds151. Here, we found that RGD at low concentrations, 1.4 ± 0.9 pmol/cm2 and 1.9 ± 1.5 pmol/cm2 on random and aligned nanofibers respectively, did not support cellular attachment or proliferation. This result matched our controls with RGE peptide, where too few cells were found for analysis.

While these results are in contrast to a previous report135 using unfunctionalized fibers, the previous group did not change the media during differentiation, and therefore, did not lose cells if they were loosely adherent. With regular media changes, the lack of specific binding sites (RGE) or low concentrations of binding sites (RGD) on the fibers reduced cell numbers over time, limiting our ability to characterize differentiation. In addition, neural stem cells (NSCs) have been found to require between 5-11 pmol/cm2 of RGD to be comparable to laminin-coated substrates162. Our RGD concentration of at least 10.8 pmol/cm2 is similar to this previous result for NSCs, and we were able to characterize 14 days of the neural differentiation progress of mESCs on the substrates with sufficient

RGD.

In neural differentiation, mESCs begin to express neural lineage markers and lose their pluripotency markers by both gene and protein expression. Our findings suggest that mESCs begin to differentiate within 1 day of exposure to retinoic acid, as pluripotency genes were downregulated and neural precursor genes were upregulated on all substrates. Downregulation of Pou5f1 and upregulation of Sox1 and Pax6 was observed on day 1 for all substrates, which is similar to previous work139 with D3 mESCs. The

72 progression continued and many of the markers investigated followed with both gene and protein expression, along with the typical morphology for glia and neurons, suggesting both the differentiation and maturation of the cells over 14 days, similar to other in vitro assessments of neural differentiation of mESCs134, 163. The correlations between TUBB3+ and GFAP+ cells were appropriate within the neural differentiation process, and moderate positive correlations between TUBB3+ cells and aggregate size agreed with other culture systems164 demonstrating mESCs neuronal differentiation was altered with cell contacts.

Overall, the cells progressed through neuronal differentiation as would be expected.

In contrast to neuronal differentiation, we found significant upregulation of the glial marker, Gfap, on both orientations of RGD-functionalized nanofibers by day 1, without concomitant upregulation on fibronectin-coated glass substrates. On both nanofiber substrates, GFAP expression was evident early and consistently throughout the 14 days of neural differentiation. These results potentially indicated that peptide-tethered nanofibers, regardless of alignment, enhanced GFAP expression. However, our previous study139 on GYIGSR-tethered nanofibers had similar gene expression at day 1 to protein- coated substrates, with Gfap expression initially downregulated. Although gene expression is not always indicative of protein expression, we found similarly high GFAP protein expression at early timepoints on both nanofiber topographies for RGD-tethered scaffolds. This result, too, was in contrast to GYIGSR nanofibers139, indicating that nanofiber topographies alone are not responsible for GFAP upregulation. So, rather than the topography being the influencer, we looked to the influence of RGD peptide. While a previous study of neural stem cell differentiation on RGD lipid-bilayer substrates showed similar levels of GFAP and TUBB3 as adsorbed laminin after a 5 day differentiation165,

RGD has been found to be a mechanosensitive interaction for a variety of stem cells and

73 differentiation166, and topography, such as nanofibers, can further induce mechanotransduction159. For example, using RGD as an interaction point, neural stem cells have been shown to preferentially differentiate to glia at increased mechanical stiffnesses158, 167. In addition, the downregulation of β1 integrin, one binding site for RGD, has been previously shown to increase gliogenesis168 and retinoic acid exposure has been found to reduce β1 expression in some cells169. Taken together, these results indicated that the combination of retinoic acid with the specificity of the RGD-tethered nanofibers, regardless of alignment, are likely responsible for the upregulation of GFAP. Further work would be necessary to demonstrate if this early upregulation of GFAP is due to interactions between the integrins on mESCs and RGD or soluble factors in differentiation.

As GFAP expression was seen at day 1, we also wondered if this early expression was indicative of neural progenitor cells rather than glial differentiation. Previous studies have found early GFAP expression on both neuronal and glial cell lineages, demonstrating that GFAP can act as a neural precursor marker170-172. Here, at day 3, up to 14% of the cells on random and aligned nanofibers were dual labeled with SOX1 and GFAP (Figure

4.3A). Therefore, the protein expression evaluation indicated that GFAP at early stages was labeling neural progenitor cells. Previous studies showed GFAP labeling by day 3 on laminin-coated substrates and aligned YIGSR-nanofibers139, but did not show distinct glial morphology until day 14, and then only on laminin-coated substrates. At later time points during differentiation, GFAP is considered mature astrocyte marker170-172, and can be matched via morphology, as we saw in Figure 4.4A.

In addition to observed astrocyte morphology at later stages of differentiation, we observed oligodendrocyte expression on both fiber orientations via gene and protein expression at days 7 and 14. This OLIG1 expression was earlier than in previous

74 studies173, including on YIGSR nanofibers, where we did not observe OLIG1 on aligned nanofibers at day 14139. An increased expression of oligodendrocytes may be related to fiber diameter, as NSCs on 283 nm fibers had increased oligodendrocytes after 5 days compared to tissue culture plastic or 749 nm fibers35, although our previously aligned

YIGSR fibers were also in this smaller size range139. Additionally, fiber alignment was found to influence oligodendrocyte survival, with improved survival on random nanofibers over aligned nanofibers125, which agreed with our gene expression results (Figure 4.2C).

In contrast, we found oligodendrocytes via protein expression largely within aggregates as has been previously reported134-135, where the percentage of oligodendrocytes was similar on random and aligned substrates. The RGD-tethered nanofibers supported oligodendrocytes regardless of fiber orientation, but more work is needed to determine how influential the RGD peptide and integrin binding or nanofiber orientation is in the process.

The influence of the nanofiber topography was not obvious in neurogenesis or gliogenesis. By day 14, approximately 60% of the cells expressed GFAP+ while 40% expressed MAP2+ on random nanofibers, and 70% and 25% of the cells expressed GFAP+ and MAP2+, respectively, on aligned nanofibers. The progression of the differentiation over time was similar, and agreed with previous studies that compared neural differentiation process between random and aligned PCL135 and PLGA134 nanofibers. Both investigations on nanofibers found no significant differences between nanofiber orientations for pluripotent (POU5F1), neural precursor (NES), neuronal (TUBB3), and glial (GFAP) markers. Consistently, differences noted in the literature between nanofiber orientation are with respect to contact guidance of neurite extension, where aligned nanofiber substrates have produced aligned neurites66, 134-135, 138. Total neurite extension,

75 which was similar on both aligned and random fiber orientations, was comparable to the literature36, 135, 139. Ultimately, nanofibers may limit the total extension due to contact guidance limitations, however, topography can also act as a stimulus to direct and orient neurites as needed. Guidance of extending neurites or directing cell migration have been primary reasons to use aligned nanofibers, and our results further support this potential outcome.

4.6. Conclusion

In this study, we synthesized and characterized random and aligned PCL nanofibers with covalently attached RGD. Using DIBO as an initiator of ring-opening polymerization yielded an end-functionalized PCL that could be modified with RGD peptide post-electrospinning surface via strain-promoted azide-alkyne cycloaddition. This method of surface modification in combination with electrospinning resulted in fabrication of nanofibers with same diameter and amount of RGD functionalization, but with different orientation – random and aligned. Nanofibers with covalently tethered RGD increased

GFAP expression at both gene and protein levels, likely due to a combination of the effect of retinoic acid and RGD peptide. At early time points, GFAP expression on RGD nanofibers likely serves as a neural progenitor marker rather than as a mature astrocyte marker. Oligodendrocytes were also formed by day 7 on RGD nanofibers, which is earlier than in previous reports. Neurite length on both fiber substrates was similar, but alignment of the neurites was significantly higher on aligned fibers due to contact guidance. The resulting differentiation of neurons progressed through mature neuronal markers, and was not influenced by the orientation of the nanofibers. Overall, the results indicated that the

76 peptide-tethered nanofibers and soluble factors play an integrated role in the neural differentiation process, and that topography was less important in the outcomes.

4.7. Acknowledgement

This work is funded by the National Institutes of Health (R15-GM113155) and the

National Science Foundation (CBET BME 1603832). R.K.W. acknowledges the generous support of the Margaret F. Donovan Endowed Chair for Women in Engineering. M.L.B is grateful for support from the W. Gerald Austen Endowed Chair in Polymer Science and

Polymer Engineering from the John S. and James L. Knight Foundation. We thank

Jacqueline Carpenter for collection of the low concentration RGE and RGD data presented, and Wafaa Nasir for collection of the fibronectin gene expression data.

CHAPTER V

RGD-MODIFIED NANOFIBERS ENHANCE FUNCTIONAL OUTCOMES IN RATS

AFTER SCIATIC NERVE INJURY

In part, this work was submitted to the Journal of Functional Biomaterials as

Cavanaugh, M.; Silantyeva, E.A.; Pylypiv Koh, G.; Malekzadeh, E.; Lanzinger, W.D.;

Rebecca K. Willits and Matthew L. Becker, RGD-modified nanofibers enhance functional outcomes in rats after sciatic nerve injury. Journal of Functional Biomaterials 2019,

Submitted.

1.1. Abstract

Nerve injury requiring surgery is a significant problem without good clinical solutions to the autograft, which are considered the gold standard solution. Tissue engineering strategies are critically needed to provide an alternative. In this study, we utilized aligned nanofibers that were click-modified with the bioactive peptide RGD for rat sciatic nerve repair. Empty conduits or conduits filled with either non-functionalized aligned nanofibers or RGD-functionalized aligned nanofibers were used to repair a 13 mm gap in the rat sciatic nerve and animals for 6 weeks. The aligned nanofibers encouraged cell infiltration and nerve repair via histology. However, RGD functionalization nanofibers reduced muscle atrophy. During the 6 weeks of recovery, animals were subjected to motor and sensory tests. Motor assessment demonstrated improved extensor postural thrust in animals with RGD functionalized nanofibers at week 4. Thus, the use of functionalized

78 nanofibers provides cues that aid in in vivo nerve repair and should be considered as a future repair strategy.

1.2. Introduction

Peripheral nerve defects are serious and challenging health issues for surgical procedures in the fields of neurosurgery, plastic, and orthopedic surgery174, with an approximate incidence rate of 13 to 23 cases per 100,000 persons175-176 primarily as traumatic injury. Clinically, tension-free repair is paramount, and when anastomosis is not possible, nerve grafts or conduits must be utilized. In spite of being considered the gold standard of repair, autografts are often accompanied by shortcomings, such as sensory loss, scarring, denervation distal to the donor site, necessity for additional surgical procedures and formation of neuroma177. Hollow nerve guidance conduits (NGCs) are a clinically approved alternative to autograft repair, but application is limited to a critical nerve gap of approximately 5 cm1, 177. Cellular tissue engineered alternatives have shown promise178; however, translational limitations for pathways with cells are long and complex.

Acellular nerve grafts provide alternatives to nerve gap repair that involve extracellular matrix-like structures to encourage cell infiltration, however, our knowledge is still limited in the design of these intraluminal fillers to optimize neuroregeneration.

Cells play a critical role in the neuroregeneration process. For example, Schwann cells (SC) have been shown to be critical to guide a growing axon, providing the appropriate growth factor signals for regeneration179 and macrophages and endothelial cells have been found to be critical to the endogenous repair process, helping increase

SC infiltration180. Therefore, supporting SC migration into an acellular graft is an important step to consider in the development of intraluminal scaffolds179, 181-182. A variety of cues have been used to enhance the regenerative response, including electrical stimulation183,

79 mechanical stimulation184, and topographical cues. The incorporation of intraluminal guidance structures in NGCs is one of the most promising tools to improve nerve regeneration since it can serve as replacement for fibrin cables, improve SC migration and nerve regeneration and axon outgrowth through providing of additional topographical cues.1 In addition, nano-scale fibers were found to support SC adhesion and proliferation in vitro58 and SC migration in vivo185. Aligning nanofibers were shown to improve regeneration over random nanofibers186 in rat nerve defects, and the inclusion of laminin protein within the polymeric blends further enhanced functional recovery.

Along with topography-based cues, bioactive proteins or peptides can further improve nerve regeneration for bridging peripheral nerve gaps187-188. Laminin and its peptides, such as YIGSR and IKVAV, have been used as supportive extracellular matrix

(ECM) additives to synthetic scaffolds for nerve regeneration186, 188-190. Incorporation of these bioactive cues as a chemical tethering allows control of concentration and spatial presentation in comparison to physically adsorbed proteins. One of the most efficient tools of fibers surface modification with peptides is strain-promoted azide-alkyne cycloaddition

(SPAAC), a facile and quantitative post-fabrication modification chemistry requiring no catalyst or chemical activation. SPAAC has been used to fabricate peptide-functionalized nanofiber substrates for neural differentiation in vitro, including YIGSR 42, 191 and RGD192.

These peptides have been previously studied for peripheral nerve regeneration, and depending upon how the peptide is integrated, they alter the response for peripheral nerve regeneration193-194.

In the current study we sought to combine the use of bioactive RGD along with the topographical cue of nanofibers to determine their influence as intra-luminal fillers in vivo for sciatic nerve defects. Over a 6-week period, the motor and sensory ability of the 80 experimental subjects was observed. Histological analysis was performed to observe muscle atrophy and infiltration of SC, endothelial cells and other tissue regeneration.

1.3. Experimental

1.3.1. Materials

All materials were used as received unless otherwise stated. Chloroform

(anhydrous, contains amylenes as stabilizer, ≥99%) and calcium hydride (reagent grade,

95%) were purchased from Sigma-Aldrich (St. Louis, MO). Methylene chloride was purchased from Fisher Scientific (Houston, TX). 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) was purchased from Oakwood Products, Inc. (Estill, SC). Methanol (ACS grade), hydrochloric acid (36.5-38%, ACS Grade) were purchased from VWR International

(Radnor, PA). Dry toluene (HPLC Grade, 99.7%, Alfa Aesar) for polymerization was purified and dried on an Inert Pure Solv system (MD Solvent Purification system, model

PS-MD-3, Amesbury, MA) and degassed using three cycles of the freeze-vacuum-thaw.

ε-Caprolactone (ε-CL, 99%, ACROS Organics™) was dried over calcium hydride under nitrogen overnight and distilled under reduced pressure. Magnesium and 4- dibenzocyclooctynol (DIBO) initiator 2,6-di-tert-butyl-4-methylphenoxide catalyst

105, 195-197 [Mg(BHT)2(THF)2] were synthesized using methods described previously . N3-

GRGDS peptide was purchased from AnaSpec Inc, Fremont, CA. Hollow silicone tubing

(inner diameter = 1.7 mm, outer diameter = 2.0 mm) was purchased from Specialty

Manufacturing, Inc, Saginaw, MI.

1.3.2. Nerve guidance conduits fabrication methods

Proton 1H NMR (300 MHz and 500 MHz) spectra were recorded on Varian Mercury

300 and 500 spectrometers. The polymer was dissolved in CDCl3 solvent at 15 mg/mL, the relaxation time was 2 sec with 64 transients.

Size exclusion chromatography (SEC) was used to determine molecular mass and molecular mass distributions (ĐM). Chromatograms were collected on a Tosoh EcoSEC

HLC-8320GPC using N,N-dimethylformamide (DMF) containing 0.1 M lithium bromide as the eluent. The 2 columns were calibrated using narrow molecular mass polystyrene standards (20 standards from 0.5 Da to 5480 kDa).

High voltage power supply (ES30P-5W, Gamma High Voltage, Ormond Beach,

FL) was used for electrospinning. The nanofiber scaffolds were characterized using scanning electron microscope (SEM) with an applied voltage of 5 kV (JSM-7401F, JEOL,

Peabody, MA).

DIBO-end functionalized poly(ԑ-caprolactone) was synthesized, electrospun and modified with GRGDS peptide using methods described previously 42. Briefly, using standard drying techniques, an ampoule was filled with ԑ-CL (0.3340 mol, 37.01 mL),

DIBO (0.5148 mmol, 113.25 mg), toluene (120.93 mL) and Mg(BHT)2(THF)2 (0.285 mmol,

173.00 mg). The ampoule was sealed and heated at 30 °C for 20 min. The polymerization was quenched with the addition of acidified (5 % v/v HCl) methanol, dissolved into chloroform and precipitated into cold methanol. The crude polymer was re-dissolved in methylene chloride and dried under high vacuum. The purified polymer was then stored in a desiccator. The monomer conversion (~100%) the purity of the product (yield 77%) was confirmed by 1H NMR spectroscopy (Figure 7.23, Appendix A), UV-visible spectroscopy and SEC (Figure 7.24, Appendix A, Mn = 50,800 Da, Mw = 68,600 Da, ĐM =

1.35).

Aligned nanofibers were fabricated via electrospinning of the DIBO-terminated

PCL solution in HFIP (17% (w/v)). The solution was placed in a 2 mL glass syringe with

22 gauge needle (Jensen Global Dispensing Solutions, Santa Barbara, CA), and a voltage

82 of 15 kV was applied. Aligned nanofibers were collected in the gaps of collector, placed at 10 cm from the tip, by tweezers to form yarns (Figure 5.1C). Yarns were modified with

GRGDS peptide via strain-promoted azide-alkyne cycloaddition by dipping into a solution of the N3-GRGDS peptide (1.587 µmol/mL) in 1:2 water/methanol (v/v) solution for 5 min, rinsed with 1:2 water/methanol (v/v) solution, blown with nitrogen and dried overnight in a desiccator. Yarns were cut into 13 mm stripes and placed inside 17 mm hollow silicone tube in a way that 2 mm space is left on each sides of the tube (Figure 5.1D). For control fiber group samples were placed in the tube without modification.

Figure 5.1. Electrospinning setup for aligned nanofibers: solution of DIBO-terminated poly(ԑ-caprolactone) in HFIP (17% w/v) was placed in syringe, and a voltage of 15 kV was applied to form aligned nanofibers in the gaps of metal collector. (b) Analysis of SEM images was performed to estimate topography of nanofibers. (c) Distribution of fiber diameters (average diameter ᴓ = 112 ± 35 nm) was calculated using NIH ImageJ198 (d) Aligned nanofibers were collected in the gaps of collector by tweezers to form yarns. (e) Yarns were functionalized with GRGDS peptide, cut into 13 mm stripes and placed inside 17 mm silicone tube in a way that 2 mm space is left on each sides of the tube. For the non-functionalized fiber group samples were placed in the tube without functionalization. (f) SEM of the cross-section of silicone tube with fiber yarns inside was cut at 45°.

Samples for SEM analysis were collected on glass slides, fixed with a double-side conductive tape to a metallic stud and sputter coated for 30 seconds with silver under 83 nitrogen atmosphere prior to imaging. The nanofiber diameters were measured on SEM images using NIH ImageJ199 and reported as an average ± standard deviation. The extent of functionalization with peptide was conﬁrmed using UV−visible spectroscopy (SynergyTM

MX plate reader from BioTek, with spectral resolution 1 nm) using chloroform as a solvent.

The peak intensity at 306 nm (which corresponds to π-π* transition in alkyne bond in

DIBO-functionalized polymer) was compared for fibers before and after reaction with azide-functionalized peptide.

Nerve guidance conduits were sterilized by ethylene oxide using an Anprolene benchtop sterilizer (Anderson Products, Inc., Haw River, NC) according to the manufacturer’s protocol for 12 h at room temperature and 35% humidity (concentration of ethylene oxide is about 0.5 g/L), purged for 48 h and stored in vacuum desiccator until surgeries.

1.3.3. Experimental design and animals

All procedures and experiments involving animals were reviewed and approved by the Institutional Animal Care and Use Committee at The University of Akron. A total of 36 male Lewis rats from Envigo weighing an average of 262  35.17 g each were utilized in the study. The rats were randomly divided into three experimental groups: empty conduit

(n = 12) as the negative control (empty silicone tube); PCL fibers (n = 12) as non- functionalized aligned nanofiber grafts; and RGD-PCL (n = 12) as RGD-functionalized aligned nanofiber grafts. Animals were housed in pairs in a cage with an ambient temperature of 69-79 °F, 30-70% air humidity, and a 12-hour day/night cycle. The rats had free access to standard rodent laboratory food (at least 5 g food per 100 g of animal’s body weight per day) and water. The animals were analyzed for functional recovery

84 metrics involving both sensory and motor tests every 2 weeks after surgery over the course of the 6-week study.

1.3.4. Surgical procedures

All animals underwent a surgical procedure to expose the sciatic nerves of both legs. A cutaneous incision was made directly below the acetabulofemoral joint and an intermuscular plane parallel to the femur was separated to expose the sciatic nerve. For each animal, a randomly chosen leg served as a sham, where the sciatic nerve was exposed but remained uninjured. In the contralateral leg, which served as the experimental leg, a 10 mm nerve segment was excised to create a 13 mm gap defect after retraction of the nerve ends. For entubulated groups, 2 mm of each nerve stump were positioned at the ends of a 17 mm silicone tube and sutured in place, creating a 13 mm end-to-end gap defect. For Group II, an isograft was used to bridge the 13 mm gap via epineurial suturing. The muscle layers separated during dissection were gently pulled back together and sterile Michel clips were used to close the skin. Recovery was carried out on a heated pad for observation of breathing and mobility until full consciousness and motion were restored, whereupon the animal was returned to its cage. The animals were inspected on a daily basis for mobility and evidence of pain or discomfort. Wound status was examined until Michel clips were removed.

1.3.5. Tissue analysis

Gastrocnemius muscles were harvested at 6 weeks and were utilized to assess muscle maturity over the time period of nerve recovery. Muscles were harvested from both legs, fixed in 4% paraformaldehyde for 48 hours at 4 C, and then stored in sterile

PBS with 1% penicillin streptomycin and 0.01% sodium azide at 4 C. Wet muscle weights

85 were recorded using an electronic balance and the relative gastrocnemius muscle weight was calculated as the ratio of the muscle weight on the experimental side to the sham side weight.

Sciatic nerve explants were utilized to evaluate histological differences. At 6 weeks, 6 random nerve samples from each group were processed for histological analysis. The samples were post-fixed in 2% buffered paraformaldehyde and 2% glutaraldehyde. After fixation, the samples were embedded in polybed epoxy, sectioned into 500 nm sections on an ultramicrotome and placed on superfrost charged slides. The samples with a conduit were cut at the estimated midline and at the nerve-scaffold junction of the distal end.

Multiple slides from each sample were prepared. Contrast staining was performed by applying toluidine blue stain to midline and distal sections. Whole sections were imaged at 20X using tile imaging light microscopy to observe overall structure of the samples at the midline and distal ends. Samples of midline sections (n = 3) were further imaged at 100X to observe structural details.

To prepare the slides for immunohistochemistry, sections were processed and rehydrated following a procedure adapted from literature200. The slides were soaked in sodium ethoxide for 15 min to remove the surrounding polybed solution from around the nerve tissue. Next, the samples were rehydrated by soaking in a series of ethanol dilutions with decreasing concentrations, including 100%, 95%, 70%, 50%, and 25%. Antigen retrieval was performed by boiling the slides in a 0.01M (pH = 6) citrate buffer for a total of 20 min in a 700 W microwave, in 5 min intervals200. After boiling, the slides were left to cool for 30 min, while submerged in the citrate buffer.

Immunohistochemistry was performed to identify expression of myelin basic protein (MBP), vimentin, and S-100. After antigen retrieval, samples were blocked with

7.5% bovine serum albumin for 30 min, rinsed with 1X PBS for 5 min, and primary antibodies were applied at 4 ºC overnight. Each experimental group had a minimum of 3 control sections, which were not exposed to primary antibodies. After primary antibodies, samples were washed with 1X PBS three times for 5 min each before applying secondary antibodies. The antibodies for S-100 intracellular protein, a common label for Schwann cells, were anti- S-100 rabbit polyclonal IgG primary antibody (MilliporeSigma, SC644, St.

Louis, MO) and donkey anti-rabbit IgG Alexa Fluor 647 secondary antibody preadsorbed for mouse (Abcam, ab150063, Cambridge, MA). The antibodies for myelin basic protein were mouse monoclonal IgG2b (Abcam, ab62631, Cambridge, MA) and goat anti-mouse

IgG2b Alexa Fluor 488 secondary antibody preadsorbed against mouse IgG1

(ThermoFisher, A-21141, Rockford, IL). The antibodies for vimentin were mouse monoclonal IgG1 primary antibody (Abcam, ab8978, Cambridge, MA) and goat anti- mouse IgG1 Alexa Fluor 546 secondary antibody preadsorbed against mouse IgG2b

(ThermoFisher, A-21123, Rockford, IL). Finally, the sections were washed 4 times with

1X PBS for 5 min per wash, rinsed with DI water, and dehydrated by applying a series of ethanol dilutions with increasing concentrations, including 25%, 50%, 70%, 90%, and

100%. The slides were dried fully using kimwipes through capillary action and evaporation of ethanol and mounted using fluoromount and coverslips. The mount set overnight and was sealed around the edges the next day to prepare for imaging. Each section had a control well which was treated with only secondary antibody and used during analysis to determine background florescence. Entire sections were imaged at 20X using fluorescent microscopy to observe protein expression. All images at same magnification were taken

87 at same exposure times and a control with only secondary antibody was utilized to set maximum exposure. The images were analyzed by randomly selecting three images per section removing the background fluorescence determined by the control well and then determining the average intensity per area section using ImageJ (n=3)201.

1.3.6. Functional assessment of re-innervation

Functional recovery results were collected every 2 weeks over 6 weeks after surgery.

1.3.6.1. Motor recovery

Motor recovery was assessed using two complementary methods, sciatic functional index (SFI) and extensor postural thrust (EPT). For SFI, foot prints were recorded. The following measurements were collected: print length (distance from the heel to the third toe; PL), toe spread (distance from the first to the fifth toe; TS) and, intermediate toe spread (distance from the second to the fourth toe; IT). These values were taken from both the non-operated foot (NPL, NTS and NIT) and the operated, experimental surgically injured foot (EPL, ETS and EIT). These measures were used to calculate SFI, based on the equation developed by De Medinaceli et al.202, and adapted by Bain et al.203

SFI= (−38.3×PLF)+(109.5×TSF)+(13.3×ITF) −8.8 Eq. (1) where PLF= (EPL−NPL)/NPL; TSF= (ETS− NTS)/NTS; and ITF= (EIT−NIT)/NIT

SFI score ranges from -8.8 to -100, with -8.8 indicating no differences between injured and non-injured paw and -100 indicating total impairment.

Motor performance was also examined using EPT. The entire body of the rat, excepting one hind-limb, was gently wrapped in a surgical towel with the hind-limbs extending out. The animal was placed over the platform of a digital balance. Once the

88 animal made a contact between the distal metatarsus and digits, the force in grams was recorded. The force generated by the animal was measured every 2 weeks following for up to 12 weeks. The normal (unaffected limb) EPT (NEPT) and experimental EPT (EEPT) measurements were inserted into Equation 2 to obtain the percentage of motor deficit

(MD%), as described by Koka and Hadlock.204

MD%= (NEPT-EEPT)/NEPT×100 Eq. (2)

1.3.6.2. Sensory recovery

The sensory test of the plantar surface of the paw were conducted with a device developed based on the Hargreaves method using unilateral hind paw withdrawal latency to radiant heat stimulation. As the animals were unrestrained, they were allowed to acclimate to the enclosure prior to testing. The rats were placed in clear plexiglass rectangular chambers (12 x 16 x 30 cm) on a glass shelf (2-mm thick) and a thermal lamp was held beneath the plantar surface of the paw to be tested until retraction of the paw or cutoff time, which was set at 20 seconds. An indicator light was used to locate the center of the rat's hind paw. A switch activated both the radiant heat sources and an electronic timer, which was used to determine the exposure time until the paw was retracted. For all animals, the time delay between heat exposure to the right and left paws were randomly selected to avoid errors caused by subject adaptation. The average baseline PWL was measured in triplicate for the all groups. Percent maximal possible effect (%MPE) was calculated according to the following formula205:

%MPE= (Experimental latency- Normal latency) / (Cutoff time Eq.3

(20s) - Normal latency) x 100

1.3.7. Statistical analysis

Experimental results were expressed as mean ± standard deviation and p<0.05 was considered significant. Differences between groups for each time point were evaluated using one-way ANOVA and multiple/post hoc group comparisons were performed by Bonferroni test. Additionally, recovery over time was assessed using a repeated measures ANOVA and Tuckey test was performed to determine comparison within groups. The relative gastrocnemius muscle weight measurements were evaluated using one-way ANOVA and multiple/post hoc group comparisons were performed by

Bonferroni test.

1.4. Results

1.4.1. Nanofibrous nerve constructs

High molecular mass (Mn = 50.8 kDa, Mw = 68.6 kDa, ĐM = 1.35) DIBO-end functionalized poly(ԑ-caprolactone) was synthesized by ring-opening polymerization of ԑ- caprolactone (yield = 77%) and was used to fabricate aligned nanofibers. The average diameter of fibers was determined to be ᴓ = 112 ± 35 nm by SEM. Yarns of aligned nanofibers were modified post-electrospinning with GRGDS peptide via strain-promoted azide-alkyne cycloaddition, the surface concentration of the peptide was determined to be

~16.1 pmol/cm2 by UV-vis spectroscopy.

1.4.2. Tissue analysis

From a gross evaluation of the injury site, no signs of neuroma formation or inflammation were observed in the area surrounding the repaired nerves. From a gross evaluation of the scaffold explants, no signs of degradation of the silicone conduit, PCL nanofibers, or RGD-PCL nanofibers were detected at the time of sacrifice.

Toluidine blue contrast staining revealed structural differences between the nerve sections from different groups. The empty conduit group, which served as the negative control, had visible nerve growth in one of six analyzed samples at the midline. Overall, it was found that 3 out of the 12 empty conduit samples at the 6-week time point had some tissue growth through the conduit via gross evaluation. Sections from the midline and distal ends of both nanofiber groups were evaluated using 20X tile imaging on a light microscope. The midline segments indicated a regenerative response, with the ability of axons to grow within the nanofiber scaffolds (Figure 5.2 a and b). The midline sections of

RGD-PCL fibers and PCL control fibers both showed some level of tissue with visible axons. This tissue presence indicated that both of these groups had some proximal to distal connection at week 6. Midline sections were evaluated using 100X light microscopy to visualize structural detail and quantify the number of axons and axon density. In both the fiber groups, we saw evidence of red blood cells, indicating the presence of a blood supply at the midline (Figure 5.2 c and d). No differences were found in axon count or fiber density between either fiber group (Figure 5.3 a and b).

Figure 5.2. Toludine blue staining on midline sections of (a) PCL fibers and (b) RGD-PCL fibers imaged at 20X shows presence of regenerated nerve tissue. Toluedine blue staining on midline sections imaged at 100X on (c) PCL and (d) RGD-PCL samples at 100X (from boxed regions from A and B respectively), show myelinated axons (white arrow), fibers, and red blood cells (red arrows).

Figure 5.3. Average axon count per region of interest (ROI) (a). 3 ROIs (250x250pixel) were randomly chosen from 100X toludine blue images and counted (n = 3). PCL group had 27.9 ± 10.3 axons per ROI and RGD-PCL group had 29.0±11.7 axons per ROI, no 92 significant differences were found between groups. (b) Fiber density was calculated by diving average number of axons by ROI. PCL have 2999 ± 1103 (axons/ROI) and RGD had a density of 3118 ± 1259 (axons/ROI). No significant differences were found between groups.

Figure 5.4. Immunohistochemical staining shows myelin basic protein (MBP, green), vimentin (orange), and S-100 Schwann cell label (red) in midline sections from 6 weeks samples (a) RGD-PCL fibers and (b) PCL control fibers. Both fiber groups showed similar presence of MBP, vimentin, and S-100 at the midline. Scale bars = 20 µm.

Immunohistochemistry revealed no qualitative differences in cellular composition between the segments from each experimental group. Myelin basic protein, vimentin, and

S-100 were expressed in the RGD fiber samples (Figure 5.4a) and control fiber samples

(Figure 5.4b). Based on a visual evaluation, myelin basic protein had a similar expression between RGD and control fiber samples, where it was expressed throughout the nerve segment. Analysis of the flourescent images via ImageJ showed no significant differences between RGD-PCL and PCL fibers.

Muscle atrophy was determined by taking the relative difference of the experimental and sham then normalized to the sham gastrucnemious wet muscle. The muscle weight change was calculated (Figure 5.5) to evaluate muscle atrophy after the nerve injury. RGD-PCL fiber groups had less muscle loss at week 6 than control fibers or empty conduits (0.307 ± 0.0348; 0.262 ± 0.0135; and 0.264 ± 0.0296 respectively), with

93 statistical differences found between RGD-PCL and empty conduit (p = 0.002), and RGD-

PCL and PCL fibers (p = 0.001).

Figure 5.5. Muscle weight at week 6. RGD-PCL fibers were found to have significantly less atrophy compared to empty conduits and PCL fibers (p = 0.002 and p = 0.001). Significant differences were not found between the PCL fibers and the empty conduit. Outliers in the empty group (muscle weight ratio = 0.33) represent conduits with nerve cable formation. (* denotes p < 0.05 and ** denotes p < 0.001).

1.4.3. Functional assessment of re-innervation

The evaluation of sciatic function index (SFI) was performed every 2 weeks over

6 weeks post-surgery. At 2 weeks, RGD-PCL had significantly less motor impairment (-

87.0 ± 4.00) when compared to PCL control fibers (p < 0.001; -97.5 ± 3.78). At the same time point, PCL fibers had a more significant deficit than the empty conduit group (p =

0.003; -97.5 ± 3.78 and -89.5 ± 7.45). At weeks 4 and 6, SFI was not found to differ between any groups (Figure 5.6a), although at week 6, the empty group had n = 5 due to a video failure.

Figure 5.6. Motor and sensory functional data over the 6 weeks of the study. The SFI (a) and EPT (b) is presented for each group over time. As SFI improves, the values become less negative. After 2 weeks RGD-PCL was found to be significantly different from PCL fibers (p < 0.001) and PCL fibers were found to significantly different from empty conduit (p = 0.003). No significant differences were found at weeks 4 and 6. As EPT improves, the values increase. Significant differences were found between RGD-PCL fibers, empty conduits and PCL fibers groups at week 4 (p = 0.0023 and p = 0.001 respectively). Baseline latency (c) was not different between groups. Sensory improvement (d) was demonstrated by a decrease in latency (s). Data is represented as the difference in latency for each rat compared to the corresponding presurgery latency. At 2 weeks RGD- PCL fibers have significantly improved sensory function compared to empty fibers (p = 0.027). Significant differences were not found between fibers at week 4. Sensory improvement was seen in RGD-PCL and PCL fibers groups compared to empty conduits at week 6 (p = 0.002 and p = 0.001 respectively) (*denotes p < 0.05 and ** denotes p > 0.001).

Extensor postural thrust (EPT) provided another measure of motor performance after nerve injury that has lower standard deviation than SFI206. The force generated by the experimental limb and the sham limb was recorded and data is presented as the difference between the two legs normalized to the sham, or percent functional motor deﬁcit

MD%. No statistical difference was found between PCL (n = 8) and RGD-PCL (n = 12) at week 2. Data was not collected at week 2 for the empty conduit group. By week 4, RGD-

PCL (0.712 ± 0.0653, n = 12) fiber group had a significantly higher EPT compared to empty conduits (n = 8) and PCL fibers (n = 12) (p = 0.023 and p = 0.001; 0.610 ± 0.106 and 0.581 ± 0.0667 respectively), indicative of faster recovery for the RGD functionalized fibers at this timepoint. Statistical differences were not found between any of the groups by week 6 (Figure 5.6b).

Sensory function was evaluated using a modified Hargraeves test, where response to a thermal stimulus via latency of paw retraction was measured in bi-weekly intervals during the 6 weeks of recovery. The baseline was set to ~4 s, and the animals demonstrated no variations in latency at time 0 (Figure 5.6c). Sensory function was analyzed by taking the difference between the latency at each timepoint and the baseline latency time for each animal. After 2 weeks, animals with RGD-PCL nanofibers showed significantly more sensory improvement compared to empty conduits (p = 0.027; std dev

=  5.47). At week 4, statistical differences in sensory function were not found between the different groups. However, statistical differences were found between both fiber groups and the empty conduit at the 6-week timepoint, with latencies similar to the baseline value (p = 0.002 and p = 0.001; standard deviation =  1.62 and standard deviation =  1.28 respectively) (Figure 5.6d).

1.5. Discussion

Several studies have shown the effect of natural and synthetic polymeric single hollow nerve conduits in axonal guidance and nerve regeneration to treat small gaps (< 3 cm)182. The efficacy of these conduits decreased with the increase of nerve gap length207.

Luminal fillers, including electrospun nanofibers, have been introduced as solutions to replace fibrin cable – the aligned ECM bridge that serves as a topographical guidance for

SC migration and regenerating nerve 1, 208. To further mimic the structure of ECM that facilitates nerve regeneration, incorporation of bioactive molecules should be considered in the NGC design. The use of SPAAC resulted in efficient tethering of peptide to the surface of DIBO-PCL nanofibers. While nanofibers functionalized with peptides via

SPAAC were used for directing stem cells27, 42, 209 as well as Schwann cells3 in vitro, the current study is the first effort to evaluate those substrates in vivo on a peripheral nerve injury model. With the ability to tether peptides on PCL nanofibers 58, 192, 210, we hypothesized that a longitudinally aligned scaffold functionalized with bioactive molecules would enhance nerve regeneration211 through functional tests and histological evaluation.

As RGD had been previously shown to enhance SC adhesion and proliferation compared to other peptides212, and SC are critical to nerve regeneration179, we investigated if RGD functionalization would improve the neuroregenerative response compare to non- functionalized fibers.

A critical gap is a nerve defect that will not regenerate if unaided, estimated as ~10 mm in the rat sciatic nerve injury model in a silicone tube, due to the lack of the formation of a fibrin cable187, 213. For this study, 3 out of 12 empty conduit samples, evaluated at week 6 after a 13 mm gap defect, had visible tissue by gross analysis at the midline, indicating some regeneration through the empty conduit. To determine if the tissue

97 ingrowth was due to gap size surgical error, the distance between sutures was measured on each empty conduit explant. When our suture distance measurements were found to be appropriate for all explants, it was not found to be correlated to the generation of tissue

(data not shown). This small rate of regeneration in our empty conduit control group for our 13 mm gap injury was similar to previous work214-215 that demonstrated the potential variability of the rodent model. Overall, this control was utilized to characterize the baseline response for rat nerve regeneration in the sciatic nerve model.

Histology was used to determine how fibers supported a response at the tissue level. Toluidine blue stained cross-sections of the conduits revealed nerve tissue, with visible axons and vascularization at the midline. This tissue presence is indicative of nerve repair and blood supply by week 6, both pivotal parts of nerve regeneration and muscle reinnervation216. At the midline, quantitative evaluation of the histological sections showed that neither axon density nor number were different between fiber groups after 6 weeks. toluidine blue staining did not reveal cellular level differences, immunohistochemistry was used to evaluate SC infiltration into the scaffolds. Our results demonstrated that SC were present at the midline of both fiber scaffolds at 6 weeks. While others have demonstrated

SC infiltration into grafts of self-assembled RGD peptide adsorbed fibers after 12 weeks194, our results show evidence of infiltration after only 6 weeks (Figure 5.3). The difference might be related to the large fiber diameter (2 to 4.5 µm)194 , while our nanofibers with smaller diameters (~112 nm) were more close to the nanogrooves on aligned fibers with higher surface area,217 where S-100 labeling was present after only 6 weeks. Myelin basic protein was also found in both nanofiber groups, showing evidence of maturation of the

SC through the early stages of myelination218. In native repair, SC along with fibroblasts form the bands of Bünger, providing the framework for the repair process. Vimentin was

98 used as a label for fibroblasts219 and found in all sections (Figure 5.5). As vimentin is also expressed on a variety of cells, including SC220, it was difficult to fully evaluate the presence or quantity of fibroblasts221. The presence of these markers demonstrated that both groups of nanofibers were providing guidance and support for SC infiltration and regenerative development within the NGC. Others have found differences in tissue evaluation between RGD containing groups and controls after 12 weeks194 over the 6 weeks completed here. To better evaluate the differences between fiber groups, earlier time points may be necessary to provide a more thorough understanding of tissue development within the grafts and determine differences throughout the time of repair.

While we did not find significant differences in the nerve histology, after 6 weeks the muscle atrophy was found to be statistically lower in the RGD-PCL group than in the

PCL group or the empty conduit controls. This lower muscle atrophy in the RGD- functionalized group was supported by the functional assessments. As motor recovery has proven difficult to measure in the past in short duration studies, it was evaluated by two methods, SFI and EPT204, which were used in combination with tissue analysis and other testing to show nerve recovery over time204. Specifically, SFI calculations have been shown to be highly variable in early recovery time points222. While The SFI tests are could provide lower reliability at early time points 223, the SFI values found in the current study are consistent with those found in other nerve gap studies190, 193-194. However, PCL fibers have been previously found to support less motor recovery, measured via SFI, compared to bioactive peptide in conjugation with PCL 194. The EPT test, which correlates with SFI while having less variability, provided another measure of motor function204. With this test, we found faster motor recovery in the RGD-functionalized group, with significant improvement by week 4 over the other groups. In combination with the reduced muscle

99 atrophy, these results indicate that the functionalization of PCL fibers with RGD peptide has improved motor recovery in the early stages. In addition to the improved motor response, functional sensory response improved to pre-surgery levels by 4 weeks only in the RGD group. Therefore, the addition of bioactive groups to the fibers was found to speed sensory recovery, which agreed with previous literature where laminin was used in conjugation with aligned nanofibers showed best sensory function over 6 weeks in a rat tibial defect, although aligned nanofibers to show best sensory function over 6 weeks in a rat tibial defect, although aligned nanofibers alone also had significant improvements in sensory function186. Overall, nanofibers support functional recovery in both motor and sensory evaluations, but the addition of RGD seems to speed the response. Future work should focus on the identification of the specific axons regenerating to specifically match the functional response to the histological evaluation.

In summary, RGD-tethered nanofibers showed improved motor and sensory function after 4 weeks as well as reduced muscle atrophy. After 6 weeks, both fiber groups had SCs present at the midline as well as organized myelin basic protein in addition to vimentin labeling. Overall, these results indicated that the addition of RGD to the aligned

PCL nanofibers improved nerve regeneration both functionally and histologically by improving initial motor recovery, sensory recovery and decreasing muscle atrophy.

However, it is clear that the topography was important in the process, as both groups showed nerve regeneration and cell infiltration.

1.6. Acknowledgement

This development of the nanofibers was funded by the National Science

Foundation (CBET 1603832) and National Institutes of Health (R15-GM113155). R.K.W. and the project were partially funded by the Margaret F. Donovan Endowed Chair for

100

Women in Engineering. M.L.B. and the project were partially funded by the W. Gerald

Austen Endowed Chair in Polymer Science and Polymer Engineering from the John S. and James L. Knight Foundation. The authors would like to acknowledge the support of

Robert (Gunnar) Tysklind for assistance with surgical procedures; Dr. Denise Inman for consultation and histological support, and Nik Prasad for support during the animal studies.

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CHAPTER VI

GRADIENT-MODIFIED ALLYL-POLY(Ԑ-CAPROLACTONE) ALIGNED NANOFIBERS

AS A PLATFORM FOR CELL MIGRATION

In part, this work is in preparation for submission to the scientific journal.

6.1. Abstract

Substrates with combination of gradient of bioactive molecules and topographical cues are highly desired for cell migration applications. Herein, we demonstrated the synthesis of PCL with allyl pendant groups used for nanofiber fabrication by touch- spinning and post-fabrication gradient decoration with thiol-containing fluorescently labeled molecules (FITC-PEG-SH). Different amount of allyl functionalities was incorporated in poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone). Increasing surface concentration of FITC-PEG-SH in a gradient manner had the same trend as greyscale intensity of the photomask used for thiol-ene reaction. These functional nanofiber substrates can be potentially used for cell migration optimization.

6.2. Introduction

Despite advances in the biological understanding of nerve regeneration after peripheral nerve injuries, the recovery of damaged nerve is limited.1 It has been demonstrated that Schwann cell (SC) migration promotes nerve regeneration and play a supportive role to regenerating nerve,224 but the optimal combination of factors that influences that process is still unclear. Both topographical and bioactive cues play an essential role in SC guidance of nerve outgrowth.3 Introduction of aligned topography improved cell response, and addition of peptide-based motifs improved the SC response.3

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Gradient of bioactive molecules along with aligned topography can further improve cell guidance.225

The influence of the gradient pattern on cell migration was shown previously.226

Since gradient pattern of immobilized bioactive factor (EGF) was optimized for cell

(keratinocytes) migration experiments and the total average cumulative migration was higher on quadratic gradients than migration on all other gradient patterns,226 in this study we chose quadratic type of photomask pattern.

Pokorski et al. modified PCL ﬁbers with gradient of IKVAV through photochemistry and demonstrated that gradient on aligned fibers have potential to improve neural cell migration and differentiation. 227 Since bioactive factors work synergistically and in concentration-dependent manner to regulate cell response, there is a need for translationally relevant substrates with a multi-pronged approach using combination of topography and multiple bioactive species that will guide SC and nerve regeneration.

Commonly available nanofibers are incapable of being functionalized with multiple factors.

While a photochemical gradient modification of fibers has been previously demonstrated, it would be hard to introduce other functionalities in a controlled and translationally relevant manner.

The goal of this study is to develop method for fabrication of aligned nanofibers with the gradient of bioactive factors and with potential for functionalization with multiple biomolecules. For this purpose we chose copolymer of ε-caprolactone with allyl- functionalized ε-caprolactone. Bioactive molecules were placed on the surface of aligned fibers in a gradient manner through thiol-ene reaction by shining the UV light through the designed photomask. Other functional groups could be easily incorporated in the PCL copolymer through introduction of another comonomer or through end-functionalization.

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6.3. Materials and methods

6.3.1. Materials

All materials were used as received unless otherwise stated. Tetrahydrofuran

(anhydrous, ≥99.9%, inhibitor-free), chloroform (anhydrous, contains amylenes as stabilizer, ≥99%), calcium hydride (reagent grade, 95%), sodium bicarbonate (ACS reagent, ≥99.7%) and 3-chloroperoxybenzoic acid (≤77%) were purchased from Sigma-

Aldrich (St. Louis, MO). Phenylacetaldehyde (98%, stabilized), lithium diisopropylamide mono(tetrahydrofuran) (1.5 M solution in cyclohexane, AcroSeal™), iodotrimethylsilane

(95-97%), n-butyllithium (2.5 M solution in hexanes, AcroSeal™), hexanes, ethyl acetate and methylene chloride were purchased from Fisher Scientific (Houston, TX). Sodium thiosulfate pentahydrate (Proteomics grade, 99%) was purchased from Amresco, LLC

(Solon, OH). 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP) was purchased from Oakwood

Products, Inc. (Estill, SC). Sodium sulfate anhydrous (ACS grade) and methanol (ACS grade), hydrochloric acid (36.5-38%, ACS Grade) and 2-allylcyclohexanone (≥97.0%, TCI

America) were purchased from VWR International (Radnor, PA). Dry toluene (HPLC

Grade, 99.7%, Alfa Aesar) for polymerization was purified and dried on an Inert Pure Solv system (MD Solvent Purification system, model PS-MD-3) and degassed using three cycles of the freeze-vacuum-thaw. ε-Caprolactone (ε-CL, 99%, ACROS Organics™) was dried over calcium hydride under nitrogen overnight and distilled under reduced pressure.

6-Allyl-ε-caprolactone (7-allyl-1-oxacycloheptan-2-one) was synthesized using methods described previously.228 Magnesium 2,6-di-tert-butyl-4-methylphenoxide catalyst

105-106 [Mg(BHT)2(THF)2] was synthesized using methods described previously. Flash chromatography was performed on silica gel (Sorbent Technologies Inc., 70-230 mesh).

104

FITC-PEG-SH (molecular weight 1425 Da) was purchased from Nanocs Inc. (Boston,

MA). Lithium Phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) photoinitiator was synthesized according to previously published work.162

Square (22 x 22 mm) and round (8 mm) Fisherbrand™ borosilicate cover glasses

(#1.5) were washed with methanol/toluene/methanol, dried with nitrogen and cleaned with

UV light (355 nm) for 30 min prior to use.

6.3.2. Experimental Methods

Size exclusion chromatography (SEC) was used to determine molecular mass and molecular mass distributions (ĐM). Chromatorgams were collected on a Tosoh EcoSEC

HLC-8320GPC using THF as the eluent. The 2 columns were calibrated using narrow molecular mass polystyrene standards (20 standards from 0.5 kDa to 5,480 kDa).

A UVO Cleaner, Model #42A UV light unit was used to clean the glass coverslips for nanofiber collection. Fluorescent images were obtained using a Keyence BZ-X700 microscope at 20 × magnification.

6.3.2.1. Synthesis of allyl-functionalized poly(ԑ-caprolactone)

The synthesis of allyl-functionalized poly(ԑ-caprolactone) and post touch-spinning gradient modification of the nanofibers with fluorescently labeled FITC-PEG-SH via radical thiol-ene reaction is shown in Scheme 6.1. Ring-opening copolymerization of ԑ- caprolactone (26.16 mmol) and allyl-ԑ-caprolactone (6.54 mmol) in toluene (5.27 mL) was carried out under a dry nitrogen atmosphere in a dry box (H2O < 0.1 ppm, O2 < 0.1 ppm) using benzyl alcohol as initiator (0.05 mmol) and Mg(BHT)2(THF)2 (0.025 mmol) as

105 catalyst. The ampoule was sealed and heated at 80 °C for 20 min. The polymerization was quenched with the addition of acidified (5 % v/v HCl) methanol, dissolved into chloroform and precipitated into cold methanol. The crude polymer was re-dissolved in methylene chloride, precipitated into cold methanol 2 times and dried under high vacuum.

The purified polymer was then stored in a desiccator. The co-monomers conversions

(98% of ԑ-caprolactone and 84% of allyl-ԑ-caprolactone) were determined by 1H NMR spectroscopy. Product (yield 83%) was characterized by SEC (Figure 7.27, Appendix A,

1 Mn = 89,600 Da, Mw = 138,300 Da, ĐM = 1.54) and H NMR (500 MHz, CDCl3, 303 K): δ =

5.83 – 5.62 (m, CH-CH=CH2), 5.13 – 4.98 (m, CH-CH=CH2), 4.18-3.92 (m, CH2CH(CH-

CH=CH2)CO), 4.15–3.98 (m, CH2CH2OCH2), 2.43 – 2.16 (m, C=O)CH2CH2), 1.77 – 1.46

(m, (C=O)CH2CH2CH2CH2CH2), 1.49 – 1.20 (m, (C=O)(CH2)2CH2((CH2)2)) ppm. (Figure

6.1 and Figure 7.25, Appendix A). The amount of allyl groups incorporated into polymer chains (14%) was calculated by the ratio of peaks integration from 1H NMR (Figure 7.26,

Appendix A and Figure 6.1).

Scheme 6.1. (A) Poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) was synthesized via ring- opening polymerization of ԑ-caprolactone and 6-allyl ԑ-caprolactone using Mg(BHT)2(THF)2 as catalyst and (B) was used to produce aligned fibers using touch- spinning. (C) Gradient of FITC-PEG-SH dye was created via thiol-ene reaction by shining 106 the UV-light (365 nm) through the photomask. (D) Image of aligned fibers (aligned vertically) touch-spun on the metal frame.

Figure 6.1. Polymer 1H-NMR overlay of allyl-PCL with 5%, 14% and 23% of allyl functionality. Peaks at the characteristic ‘b’, ‘c’ and ‘d’ resonances confirmed successful incorporation of allyl functionality in polymer chains. The molar ratio of the incorporated allyl groups in the afforded polymers were calculated from the characteristic ‘d’ resonances in blue from allyl-ε-CL comonomer, and the ‘e’ resonances in grey from ε-CL comonomer.

6.3.2.2. Touch-spinning conditions and nanofiber collection

The DIBO-terminated allyl-PCL was dissolved in chloroform (5 wt%) to yield a clear, slightly viscous solution. The solution was placed in a glass syringe with a 22-gauge needle (JG22-0.5X, Jensen Global Dispensing Solutions), connected to a pump with speed 5 µL/min. The rotation speed of the two metal rods of 2500 rpm was applied.

Aligned fibers were collected on the metal frame (Scheme 6.1D), functionalized and then placed on cover glasses in between the gap of the metal frame for analysis. 107

6.3.2.3. Characterization of diameter and orientation

Nanofiber dimensions and alignment were imaged by scanning electron microscope (SEM) with an applied voltage of 5 kV (JSM-7401F, JEOL, Peabody, MA).

Samples were sputter coated for 30 seconds with silver under nitrogen atmosphere prior to imaging. The variation in nanofiber diameters was measured on at least 3 independent samples using NIH ImageJ108 and reported as an average ± standard deviation The

DirectionalityTM plugin of ImageJ109 was used to quantify the relative degree of alignment of the scaffolds by analyzing the angle distribution of fibers (Figure 7.27B, Appendix A).

The value is reported as an average ± standard deviation. Angles were normalized to 0.

The highest peak was normalized to 1. Angle distribution of diameter directions was calculated using Gaussian fitting parameters. The quality (goodness) of fit to the Gaussian distribution curve calculated by DirectionalityTM plugin was reported as average ± standard deviation.

6.3.2.4. Photomask

Gradient images for the photomask were created in Adobe Illustrator 10 and were then used for patterning print of chromium on quartz plate since quartz is transparent to

UV contrary to the chromium (custom-purchased from Photo Sciences Inc. (Torrance,

CA). Pattern was designed for a 20 mm gradient, with a profile of transparent regions shown in Figure 6.2 and Figure 6.3. The greyscale intensity versus pixels of the photomask followed the equation y = 0.0004x4 + 0.0094x3 + 0.2424x2 + 0.3927x (R2 =

0.9996), with resolution ± 0.25 µm.

6.3.2.5. FITC-PEG-SH surface functionalization of nanofibers

Metal frames with nanofibers were placed in silicone isolators (Grace Bio-Labs,

Inc., Bend, OR) on polystyrene culture plate dish and 0.7 mM solution of FITC-PEG-SH

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(5.0 µmol) and LAP (2.5 µmol) in H2O/MeOH (4:5 v/v) was pipetted on top of fibers. The photomask was placed on top of the fibers with gradient along the fiber direction. The UV- light (λ = 365 nm, I = 1.2 mW/cm2) was applied for 15 min from the distance of 5 cm. Upon

UV exposure, the thiol group enables immobilization of FITC-PEG-SH to the fiber surface in a gradient manner. After treatment fibers were washed with water (3 ×), soaked in water for 15 min, soaked in methanol for 15 min and blown with nitrogen. After functionalization fibers were collected on glass slides by placing them in the gaps of metal frames. Fibers were imaged by fluorescent microscope in the center of each of 5 zones along the fiber direction. The fluorescence intensity along the fiber direction was measured using NIH

ImageJ software and plotted against gradient path length. For surface quantification, fibers were divided in 5 regions along the fiber direction, each region was weighted and dissolved in HFIP for fluorescence measurement. Fluorescence studies were carried out using a BioTek SynergyTM Mx Microplate Reader (BioTek, Vermont) with Gen 5TM reader control and data analysis software (λex = 451 nm, emission range 510-551 nm).

6.4. Results

6.4.1. Allyl-PCL synthesis

Poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) (Allyl-PCL) was synthesized by ring-opening copolymerization of ԑ-caprolactone using standard Schlenk techniques. This method yielded high molecular mass PCL with different extent of allyl functionalization.

Using of Mg(BHT)2(THF)2 as a catalyst allows high monomer conversion (98% of ԑ- caprolactone and 84% of allyl-ԑ-caprolactone) within 20 min at 80 °C and yielded polymer with high molecular mass and narrow molecular mass distribution (Mn = 89,600 Da, Mw =

138,300 Da, ĐM = 1.54, Figure 7.26, Appendix A). Kinetic plot shows rapid ԑ-caprolactone

109 consumption followed by incorporation of allyl ԑ-caprolactone (Figure 7.29, Appendix A).

DOSY NMR spectroscopy showed the presence of only one polymer species, attributed to the formation of only copolymer species and not two species of homopolymers (Figure

7.28, Appendix A).

6.4.2. Fabrication of aligned Allyl-PCL nanofibers and gradient modification

This polymer was used to fabricate highly aligned nanofiber scaffolds with a narrow angular distribution of fibers (0 ± 3°, average ± standard deviation). The average diameter of fibers was ᴓ = 401 ± 162 nm. Aligned nanofibers were modified post-touch- spinning with fluorescently labeled FITC-PEG-SH via thiol-ene reaction and the surface concentration of GYIGSR peptide was determined to be patterned along the fiber direction with concentrations ranging from 106.1 pmol/cm2 to 253.3 pmol/cm2. (Figure 6.2 and

Figure 6.3). Both fluorescent microscopy imaging and fluorescent measurements had the same trend as greyscale intensity of the photomask used for thiol-ene reaction.

110

Figure 6.2. Top: photomicrograph of aligned fibers with fluorescently labeled FITC-PEG- SH gradient along the fiber direction patterned via thiol-ene reaction using a quadratic gradient photomask. Images were taken with exposures 0.5 s and intensity was enhanced (+40% brightness). Scale bar is 100 µm. Bottom: corresponding graph of the increasing concentration gradient of immobilized FITC-PEG-SH (red circles). Graph of photomask pattern (black circles). The concentration of FITC-PEG-SH along the fiber direction had the same trend as greyscale intensity of the photomask used for thiol-ene reaction.

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Figure 6.3. Graph of the increasing concentration gradient of immobilized FITC-PEG-SH measured at 550 nm endpoint emission (red squares). Graph of photomask pattern (black squares). The concentration of FITC-PEG-SH along the fiber direction had the same trend as greyscale intensity of the photomask used for thiol-ene reaction.

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6.5. Summary

The present study demonstrates fabrication of a nanofiber platform for cell migration, combining gradient of surface-tethered thiol-functionalized species with topographical features of fibers. Poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) with different amount of allyl functionalities was synthesized via ring-opening polymerization of

ԑ-caprolactone and 6-allyl ԑ-caprolactone. This polymer was used for fiber manufacturing by touch-spinning and decorated with a gradient of thiol-functionalized fluorescently labeled poly(ethylene glycol) (FITC-PEG-SH). Analysis of surface concentration reveals that increasing gradient of FITC-PEG-SH had the same trend as greyscale intensity of the photomask used for thiol-ene reaction.

This simple method of nanofiber decoration with gradient is easy, require water- based solutions, short times and ambient conditions. It can be applied to any peptide sequence that can be easily synthesized and functionalized with thiol group by adding extra cysteine unit. These substrates could be used for producing scalable, xeno-free substrates for cell migration.

Since cells respond to the bioactive molecule gradient in a concentration- dependent manner, it is very important to have the opportunity to control the surface concentration of attached biomolecules without significant change of other polymer properties. While for end-functionalized polymers there is a need to decrease molecular weight of polymer chains in order to increase the surface concentration of tethered species, for copolymers with pendant functionality the extent of tethered biomolecules could be adjusted by changing concentration of functional groups without significant change in other polymer properties. We demonstrated that different amount of allyl functionality could be incorporated in polymer chain. Different applications required

113 different bioactive factors and different concentrations of them. If the concentration of biomolecules is too high or too low, gradient will not influence cell migration. Our substrates are versatile since they are easy to adapt for specific application by synthesizing different thiol-biomolecules and changing the gradient slope through photomask design and concentration range through amount of allyl group incorporation into the polymer.

Synthetic polymers with pendant functional groups are desired in biomedical applications since they provide opportunity for covalent immobilization of bioactive compounds. The opportunity to change concentration range by using different amount of incorporated allyl groups give the unlimited potential to explore these substrates for various biomedical applications. Future development efforts are focused on additional bioactive species that can enhance cell response.

6.6. Acknowledgements

This work is funded by the National Institutes of Health (R15-GM113155) and

National Science Foundation (CBET BME 1603832). MLB acknowledges support from the W. Gerald Austen Endowed Chair in Polymer Science and Polymer Engineering via the John S. and James L. Knight Foundation. The authors would like to thank Z. Zander for donation of LAP.

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CHAPTER VII

CONCLUSION

My dissertation describes fabrication of a versatile nanofiber platforms, combining topographical features with surface-tethered bioactive species, and their application as substrates for peripheral nerve regeneration.

The first two parts of this dissertation focused on fabrication of nanofiber substrates for stem cell differentiation and substitution of xenogenic factors from the differentiation process by synthetic polymer substrates. First, we demonstrated that aligned nanofibers and post-electrospinning surface modification with bioactive species can be combined to produce translationally relevant xeno-free substrates for stem cell therapy. Detailed analysis of gene and protein expression results reveals that GYIGSR-functionalized fibers promoted faster neural differentiation of D3 mESCs then laminin-coated glass. In addition, the aligned nanofibers can also be used as substrates to guide neurite extension. Next, we investigated the influence of topography and bioactive species of random and aligned

PCL nanofibers with covalently attached RGD. Nanofibers with covalently tethered RGD increased GFAP expression at both gene and protein levels. At early time points, GFAP expression on RGD nanofibers likely serves as a neural progenitor marker rather than as a mature astrocyte marker. The results indicated that the peptide-tethered nanofibers and soluble factors play an integrated role in the neural differentiation process, and that topography was less important in the outcomes.

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The next part focused on fabrication of nanofiber constructs functionalized with

RGD and their evaluation in vivo on rat sciatic nerve repair model. We demonstrated that the addition of bioactive molecules like RGD to the aligned fiber topography improved nerve regeneration in vivo both functionally and histologically.

Finally, for further improvement of nerve regeneration, we developed the nanofiber substrates with gradient surface modification via thiol-ene reaction. Analysis of surface concentration reveals that increasing gradient of fluorescently labeled molecules along the aligned fiber direction had the same trend as greyscale intensity of the photomask used for producing gradient. These substrates can be used as a platform for cell migration with possibility to optimize the gradient profile of thiol-functionalized biomolecules.

The mentioned substrates were prepared by ring-opening polymerization using

Mg(BHT)2(THF)2 catalyst allowing high molecular mass polymers with narrow molecular mass distributions. Surface functionalization was performed via either thiol-ene reaction or SPAAC - the easy and efficient method of copper-free nanofiber surface functionalization developed in the Becker Lab. These efficient methods of surface modification in combination with electrospinning or touch-spinning resulted in fabrication of xeno-free, scalable and translationally relevant substrates that have a great potential to be used clinically.

Future development efforts are focused on additional bioactive species that are able to substitute surrogates for other xenogenic factors found in differentiation media or can guide cell migration.

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APPENDICES

148

APPENDIX A-SUPPORTING FIGURES

1 Figure 7.1. H NMR of 4-dibenzocyclooctynol (DIBO) (300 MHz, CDCl3, 303 K): δ = 7.75 3 3 (d, JH-H = 7.8 Hz, 1H, aromatics), 7.54 – 7.28 (m, 7H, aromatics), 4.64 (dd, JH-H = 3.2, 3 3 2.5, 1H, CHOH), 3.11 (dd, JH-H = 14.7, 2.1 Hz, 1H, CH2), 2.94 (dd, JH-H = 14.7, 3.6 Hz, 1H, CH2), 2.14 (s, 1H, OH) ppm. DIBO was synthesized in accordance with the literature and was used as an initiator for ring-opening polymerization of ε-caprolactone.

149

Figure 7.2. 1H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after polymerization (peaks a, c and d at δ = 5.56, 3.10 and 2.93 ppm correspond to protons from DIBO).

Figure 7.3. (A) Analysis by DMF size exclusion chromatography confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 60,600 Da, Mw = 83,700 Da, ĐM = 1.38). Molecular mass was determined against PS standards. (B) UV-visible spectra of DIBO-terminated poly(ԑ-caprolactone) in chloroform confirms survival of DIBO group after polymerization: absorbance peak at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO.

150 . Figure 7.4. (A) Distribution of fiber diameters (average diameter ᴓ = 219 ± 36) was calculated using NIH ImageJ.108 (B) DirectionalityTM plugin109 was used to estimate alignment of the scaffolds and Fityk 0.9.8 was used to fit Gaussian function (red curve) and calculate average angle as peak of fitting.110 Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1. Average angle was calculated to be 0 ± 6°, and goodness of fitting of Gaussian curve calculated by DirectionalityTM plugin was high (0.91 ± 0.06, average ± standard deviation).

Figure 7.5. ESI spectra and structure of N3-GYIGSR peptide confirms successful + synthesis of N3-GYIGSR peptide, m/z for [M + Na] = 813.4 Da. 151 Figure 7.6. Gene expression of pluripotency marker Pou5f1 on GYIGSR-functionalized aligned nanofibers and laminin-coated glasses shows that cells were pushed to differentiation.

Figure 7.7. Representative images of flow cytometry indicating the purity of pluripotent D3 mouse embryonic stem cell population before seeding.

152

Figure 7.8. SEM images of fibers A) before and B) after modification with peptide did not show differences in the fiber structure.

Figure 7.9. Phase images of mESCs cultured on fibers and laminin coated glass.

153

1 111 Figure 7.10. H NMR spectra of 6-azidohexanoic acid (300 MHz, CDCl3): δ = 3.28 (t, 3 3 JH-H = 6.8 Hz, 2 H), 2.38 (t, JH-H = 7.3 Hz, 2 H), 1.74 – 1.52 (m, 4 H), 1.50 – 1.36 (m, 2 H) ppm. 6-azidohexanoic acid was synthesized according to literature111. Sodium azide (3.0 g, 15.4 mmol) was added to solution of 6-bromohexanoic acid (4.5 g, 7.7 mmol) in N,N-dimethylformamide (15 mL) and the mixture was heated at 85 °C for 3 h. The crude reaction mixture was diluted in methylene chloride, and this solution washed with 0.1 N aq. HCl. The organic layer was dried over anhydrous Na2SO4, filtered, and concentrated under reduced pressure to give 6-azidohexanoic acid (2.7 g, 74%) as an oil.

154

Figure 7.11. 1H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after polymerization (peaks a, c and d at δ = 5.56, 3.10 and 2.93 ppm correspond to protons from DIBO).

Figure 7.12. UV-visible spectra of DIBO-terminated poly(ԑ-caprolactone) in chloroform confirms survival of DIBO group after polymerization: absorbance peak at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO.

155

Figure 7.13. DirectionalityTM plugin109 was used to estimate alignment of the (A) aligned and (B) random fiber scaffolds. Fityk 0.9.8 was used to fit Gaussian function (red curve) and calculate average angle as peak of fitting110. Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1. Average angle was calculated to be 0 ± 6° for aligned and -2 ± 111° for random fibers. Goodness of fitting of Gaussian curve calculated by DirectionalityTM plugin was high for aligned fibers (0.91 ± 0.06) and low for random fibers 0.41 ± 0.2, average ± standard deviation).

Figure 7.14. Distribution of fiber diameters for (A) aligned and (B) random nanofibers was calculated using NIH ImageJ.108 (average diameter ᴓ = 212 ± 63 nm and 219 ± 36 nm accordingly).

156

Figure 7.15. ESI spectra and structure of N3-GRGDS peptide confirms successful synthesis of peptide, m/z for [M]+ = 630.01 Da

157

Figure 7.16. ESI spectra and structure of N3-GRGES peptide confirms successful synthesis of peptide, m/z for [M]+ = 644.27 Da.

158 Figure 7.17. For gene expression, the cell number was insufficient to fully evaluate. The example here is for Gfap on aligned and random nanofibers functionalized with high (8.4 ± 3.8 pmol/cm2 and 24.7 ± 8.4 pmol/cm2 respectively) and low (1.5 ± 0.2 pmol/cm2 and 2.5 ± 1.4 pmol/cm2 respectively) concentrations of GRGES, and low (1.9 ± 1.5 pmol/cm2 and 1.4 ± 0.9 pmol/cm2 respectively) concentration of GRGDS. For gene analysis, we seeded the same number of samples for high concentration GRGES and high concentration GRGDS, however, samples had to be combined to get sufficient RNA. At day 3, Gfap expression was similar between low concentrations of RGE and RGD. While 2 combined samples were measured for Gfap expression on aligned high concentration RGE fibers, only 1 sample had Ct < 30. Overall, these control samples highlight challenges in using null peptide (RGE) for cellular controls in synthetic systems. In addition, the lack of differences between the low RGE concentration and low RGD concentration demonstrate that the concentrations of both fiber configurations (<2.0 pmol/cm2) were insufficient to investigate the activity of RGD in the mESC differentiation process.

159 Figure 7.18. Summary of gene expression of neural differentiated mouse embryonic stem cells over 14 days of differentiation on fibronectin-coated surfaces, RGD functionalized aligned and random nanofibers. (A) Pou5f1 is downregulated (<0) beginning at day 1 for all samples, and was not found within 30 cycles in fibronectin at days 3, 7, or 14 or random at days 7 or 14. (B) Nes, a neural precursor cell marker, was not found on fibronectin samples, and upregulated beginning at day 1 for both aligned and random fiber samples; no statistical differences were found between samples. (C) Gap43 expression, indicative of neuron development, remained similar to its pluripotent state for all fiber samples, and was upregulated by day 14 on fibronectin samples. * represents statistical significance between groups, with p<0.05 considered significant.

160 Figure 7.19. Protein expression of pluripotent (SSEA1, POU5F1), neural precursor (NES, SOX1), glial (GFAP, OLIG1), and neuronal (TUBB3, MAP2, and GAP43) markers. The days lacking images were not examined (see Methods for further information). Images shown are modified according to the controls to highlight cells expressing positive markers. Scale bar of 20 µm.

161 Figure 7.20. Summary of pluripotent (A, B), neural precursor (C, D), and neuronal (E) protein expression of neural differentiated mouse embryonic stem cells over 14 days of differentiation on RGD functionalized aligned and random nanofibers. Images were thresholded according to the brightness and contrast settings of control images, which were samples with secondary antibodies and nuclei label. Protein positive cells were normalized to the total number of cells expressing at least one protein label and expressed as a percentage. Data is represented as average of single and double labeled protein ± std dev of total labeled proteins. For A and B, double labeling was SSEA1+/POU5F1+. (C) Double labeling was NES+/POU5F1+/SSEA1-, NES+/POU5F1-/SSEA1+, and NES+/POU5F1+/SSEA1+. (D) Double labeling was SOX1+/GFAP+. (E) Double labeling was MAP2+/GAP43+/GFAP-. * represents statistical difference between respective topography timepoints and groups, with a p<0.05 considered significant.

162 Figure 7.21. Double labeling of proteins on nanofiber substrates. Cells expressing GFAP+ and SOX1+ highlight an additional role of GFAP as a neural precursor marker (A). Additionally, for later time points, clusters of cells were found expressing both mature neuronal markers (B), and glial markers (C). However, these cells were distinctly different in their morphology and were singly labeled with either a neuronal or a glial marker. Scale bar of 20 µm.

163 Figure 7.22. Summary of correlation plots. At day 7, a strong correlation between TUBB3+ expression and GFAP+ expression (-0.826), and cluster area (0.595) was found (A and B respectively). Additionally, at day 14, a strong correlation between TUBB3+ and GFAP+ (-0.628), and GFAP+ and OLIG1+ expression (-0.570) were found (C and D respectively). At day 7 and 14 of neural differentiation, a strong correlation of TUBB3+ and GFAP+ (- 0.785) cells was found (E).

164 Figure 7.23. 1H NMR spectrum of DIBO-terminated poly(ԑ-caprolactone) (500 MHz, CDCl3, 303 K) confirms successful synthesis of polymer and survival of DIBO groups after 1 polymerization. H NMR (500 MHz, CDCl3, 303 K): δ = 7.51 – 7.45 (m, aromatic), 5.56 3 3 (dd, JH-H = 3.2, 2.5 CHOH), 4.15 – 3.98 (m, CH2CH2OCH2), 3.10 (dd, JH-H = 15.2, 2.1 Hz, 3 CH(H)CH), 2.93 (dd, JH-H = 15.1, 3.9 Hz, CH(H)CH), 2.38 – 2.22 (m, (C=O)CH2CH2), 1.72 – 1.54 (m, (C=O)CH2CH2CH2CH2CH2), 1.45 – 1.28 (m, (C=O)(CH2)2CH2((CH2)2) ppm.

Figure 7.24. (A) DMF size exclusion chromatogram confirms successful synthesis of high molecular mass DIBO-terminated poly(ԑ-caprolactone) (Mn = 50.8 kDa, Mw = 68.6 kDa, ĐM = 1.35). (B) UV-visible spectrometry was used to measure concentration of GRGDS peptide by comparison of absorbance at 306 nm corresponds to π-π* transition of the strained alkyne in DIBO.

165 Figure 7.25. 1H NMR spectrum of poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) (500 MHz, CDCl3, 303 K): δ = 5.83 – 5.62 (m, CH-CH=CH2), 5.13 – 4.98 (m, CH-CH=CH2), 4.18-3.92 (m, CH2CH(CH-CH=CH2)CO), 4.15–3.98 (m, CH2CH2OCH2), 2.43 – 2.16 (m, C=O)CH2CH2), 1.77 – 1.46 (m, (C=O)CH2CH2CH2CH2CH2), 1.49 – 1.20 (m, (C=O)(CH2)2CH2((CH2)2)) ppm. NMR spectrum confirms successful synthesis of polymer and incorporation of allyl functionality in the polymer chains.

Figure 7.26. (A) Analysis by THF size exclusion chromatography confirms successful synthesis of high molecular mass poly(ԑ-caprolactone-co-6-allyl ԑ-caprolactone) (Mn = 89,600 Da, Mw = 138,300 Da, ĐM = 1.54). Molecular mass was determined against polystyrene standards.

166 Figure 7.27. Analysis of (A) SEM images was performed to estimate topography of nanoﬁbers. NIH ImageJ was used to estimate ﬁber diameter (ᴓ = 401 ± 162 nm) and (B) alignment (DirectionalityTM plugin, average angle = 0 ± 3°). Angles were normalized to 0° for aligned fibers. The highest peak was normalized to 1.

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Figure 7.28. DOSY NMR spectra of poly(ԑ-caprolactone-co-6-allyl-ԑ-caprolactone) (500 MHz, CDCl3, 303K) showed the presence of only one polymer species, attributed to the formation of only copolymer species and not two species of homopolymers. The polymerization was designed for targeted DP = 100 and 50:50 monomer ratio at monomer concentrations = 4 M.

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Figure 7.29. (A) Plot of monomer conversion versus time for the copolymerization of allyl- ε-Cl and ε-Cl using Mg(BHT)2(THF)2 as a catalyst at 80 °C in toluene, total monomer concentration = 4 M. (B) Kinetic plot for the same reaction. The liner fit for allyl-ε-Cl: y = 0.1056x - 0.0144, R2 = 0.9647, with slope = 0.1056; for ε-Cl slope y = 0.0404x + 2.6748, R2 = 0.8451, with slope = 0.0404. Calculated from conversions based on NMR.

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APPENDIX B-SUPPORTING SCHEMES AND TABLES

Table 8.1. Optimal concentrations and efficiencies of primers used for real time qPCR.

Gene Optimal Concentration (nM) Efficiency (%)

Gapdh 200 103.4

Actb 200 96.8

Pou5f1 100 97.1

Sox1 200 103.1

Pax6 200 100.9

Nes 100 98.4

Tubb3 200 104.9

Map2 300 98.4

Gfap 300 102.8

Th 300 96.9

Foxo4 300 92.1

Cdh2 100 100.8

Gap43 300 96.8

Syp 100 101.3

Olig1 300 100.8

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