Concurrent Delivery of Soluble and Immobilized Proteins to

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Concurrent Delivery of Soluble and Immobilized Proteins to Recruit and Differentiate Neural Stem Cells Trevor R. Ham,† Dakotah G. Cox,‡ and Nic D. Leipzig*,†,‡ †

Department of Biomedical Engineering, Auburn Science and Engineering Center 275, West Tower, The University of Akron, Akron, Ohio 44325, United States ‡ Department of Chemical and Biomolecular Engineering, Whitby 211, The University of Akron, Akron, Ohio 44325, United States

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ABSTRACT: Insufficient endogenous neural stem cell (NSC) migration to injury sites and incomplete replenishment of neurons complicates recovery following central nervous system (CNS) injury. Such insufficient migration can be addressed by delivering soluble chemotactic factors, such as stromal cell-derived factor 1-α (SDF-1α), to sites of injury. However, simply enhancing NSC migration is likely to result in insufficient regeneration, as the cells need to be given additional signals. Immobilized proteins, such as interferon-γ (IFN-γ) can encourage neurogenic differentiation of NSCs. Here, we combined both protein delivery paradigms: soluble SDF1α delivery to enhance NSC migration alongside covalently tethered IFN-γ to differentiate the recruited NSCs into neurons. To slow the release of soluble SDF-1α, we copolymerized methacrylated heparin with methacrylamide chitosan (MAC), to which we tethered IFN-γ. We found that this hydrogel system could result in soft hydrogels with a ratio of up to 70:30 MAC/heparin by mass, which enabled the continuous release of SDF-1α over a period of 2 weeks. The hydrogels recruited NSCs in vitro over 2 weeks, proportional to their release rate: the 70:30 heparin gels recruited a consistent number of NSCs at each time point, while the formulations with less heparin recruited NSCs at only early time points. After remaining in contact with the hydrogels for 8 days, NSCs successfully differentiated into neurons. CNS regeneration is a complex challenge, and this system provides a foundation to address multiple aspects of that challenge.

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INTRODUCTION Soluble chemokines,1 along with matrix-bound cues,2 allow the central nervous system (CNS) to maintain normal tissue function and structure. After a mild injury, the CNS has the ability to replenish cells by driving the migration of neural stem cells (NSCs) along gradients of soluble chemokines, such as stromal cell-derived factor 1α (SDF-1α).3 However, after a major pathological insult, the CNS is not equipped to regenerate:4 a chaotic cellular response wherein no new neurons are generated,5 among other challenges,6 results in a permanent loss of function. Protein delivery can be used to enhance regeneration from host and exogenous cells as part of biomaterial-based strategies for CNS repair and regeneration. An important element of such strategies is to both promote and guide growth through material properties or chemical cues, such as growth factors or guidance proteins. Soluble growth factors can be delivered from a biomaterial scaffold and enhance recovery following CNS injury.7,8 However, it remains important to provide regenerating cells additional instructions (e.g., lineage specification for differentiating cells or neurite guidance) in a specific and controlled manner. This can be accomplished through the use of immobilized proteins.2,9,10 Here, we sought to combine both approaches and slowly deliver a soluble cell recruitment protein over time from a hydrogel carrier also containing an © XXXX American Chemical Society

immobilized signaling protein to drive lineage commitment, allowing us to harness the advantages of both types of protein administration. To accomplish this, we started with methacrylamide chitosan (MAC), to which we can covalently tether recombinant proteins9 to guide NSC differentiation. We chose MAC because we can tune its elastic modulus by changing cross-linking to encourage neuronal differentiation,11 it closely mimics hyaluronan (a component of the native CNS extracellular matrix),9 and we have extensive experience modifying it to guide lineage specification.12 We copolymerized MAC with another naturally derived photo-cross-linkable polysaccharide, methacrylated heparin.13 Heparin, which normally sequesters signaling proteins in vivo via specific and nonspecific interactions,14 has been used in many applications to slow the release of soluble proteins.15−17 By adding heparin to our hydrogel system, we sought to change the release of soluble proteins from the quick release of pure MAC to a longer release time frame. We used this system to deliver soluble SDF-1α, which has been shown to promote improved function following injury via the recruitment of tissue-specific, reparative cells in mostly Received: May 22, 2019 Revised: August 16, 2019

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DOI: 10.1021/acs.biomac.9b00719 Biomacromolecules XXXX, XXX, XXX−XXX

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Figure 1. Schematic of MAC/heparin hydrogel synthesis. We blended MAC and methacrylated heparin in varying ratios and formed photo-crosslinkable hydrogels with up to 30% heparin.

mesenchymal tissues (e.g., for cardiac repair),18,19 in addition to recruiting NSCs to sites of injury.3 Our goal was to create gradients of SDF-1α, which would last up to 2 weeks, as this has been shown to be the most critical time for CNS repair in vivo.20,21 In order to further promote repair and address a major challenge following moderate to severe CNS injury (insufficient and unguided endogenous cell response), we tested the delivery of SDF-1α alongside immobilized interferon-γ (IFN-γ, which differentiates NSCs into neurons9,22). We hypothesized that this system could increase NSC recruitment via gradients of released SDF-1α to a hydrogel and differentiate them into neurons via signaling from immobilized IFN-γ. We started by characterizing the effect of increasing heparin concentration within MAC/heparin hydrogels on rheological properties and a SDF-1α release rate over 2 wks in vitro. We also measured the ability of MAC/heparin hydrogels to recruit NSCs at various time points (0, 3, 7, and 14 days) and differentiate them into neurons via immobilized IFN-γ. The extensive in vitro testing described in this work lays the foundation for a system that can address multiple challenges facing CNS regeneration at once, strengthening endogenous NSC recruitment to overcome a weak innate response and encouraging recruited NSCs to differentiate and replenish damaged neurons, which are not naturally replaced following injury.

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conducted all experiments using passage 3−6 NSCs (dissociated from neurospheres via pipetting) in basal media (growth media without EGF or bFGF23), which we have found to retain native nestin expression, indicating that they have not begun to spontaneously differentiate. Synthesis of Azide-Tagged Interferon-γ. We synthesized azide-tagged IFN-γ (azIFN-γ), as previously reported,9 with no deviations. Briefly, azIFN-γ was inserted into a pET28a vector (GenScript), while N-myristoyltransferase was inserted into a pET11c vector (generously provided by Dr. Edward Tate, Imperial College London24). We coexpressed both proteins in BL21 (DE3) E. coli, using 12-azidododecanoic acid (synthesized as in ref 9) as the azide tag, isolated the protein under denaturing conditions via nickelnitrilotriacetic acid (Thermo Scientific), refolded it, and performed the final purification using fast protein liquid chromatography (FPLC, GE AKTApurifier 10 with Frac-950 collector; buffers in ref 9 and procedure in ref 25). We determined concentration for all experiments using the bicinchoninic acid (Micro BCA, Thermo Scientific) assay. Synthesis and Functionalization of Methacrylamide Chitosan. We synthesized, purified, and characterized methacrylamide chitosan as we have described previously,9,11 using Protosan UP B 80/ 20 chitosan (NovaMatrix) and methacrylic anhydride (SigmaAldrich). We functionalized MAC with dibenzocyclooctyne (MACDIBO) as in ref 9 using dibenzocyclooctyne-N-hydroxysuccinimide ester (Click Chemistry Tools). Synthesis of Methacrylated Heparin. We synthesized methacrylated heparin based on previous work.13 We reacted 2% (w/v) heparin (Sigma-Aldrich) in DI H2O with a 5 molar excess of methacrylic anhydride (Sigma-Aldrich) for 24 h. For the first 3 h, we adjusted the pH to 8.5 using 1 N NaOH every 15 m. We then transferred the reaction mixture to a 1k MW cutoff dialysis tube (Spectrum Laboratories) and dialyzed it against DI H2O for 48 h, with 8 buffer changes. We lyophilized (Labconco FreeZone 4.5) the remaining heparin for 3 days to remove all remaining water. We used 1H NMR (Varian 400 MHz NMR spectrometer) to determine the methacrylation percentage of heparin. We dissolved methacrylated heparin in D2O (0.5%, w/v) and recorded the 1H NMR spectrum. We then analyzed the methacrylate vinyl protons (δ 6.1−6.4 and δ 5.6−5.9) and the disaccharide repeat unit protons (δ 3.0−4.6). We calculated the percent methacrylation from the following formula:26

EXPERIMENTAL SECTION

Isolation and Culture of Neural Stem Cells. All procedures involving animals were approved by the University of Akron Institutional Animal Care and Use Committee. We isolated NSCs from the subventricular zone of adult female Fisher 344 rats (Harlan) via dissection and papain dissociation as per manufacturer’s instructions (Worthingon Biochemical Corporation) and cultured them as previously described.9,12,23 We expanded them in suspension culture using growth medium: neurobasal medium, 2 mM Lglutamine, 100 μg/mL penicillin−streptomycin, B27 supplement (all Thermo Fisher Scientific), 20 ng/mL epidermal growth factor (EGF, Sigma-Aldrich), 20 ng/mL basic fibroblast growth factor (bFGF, Peprotech), and 2 μg/mL heparin (Sigma-Aldrich). We B

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Biomacromolecules % methacrylation =

1/2(I1 + I2) × 100 1/9(I )

pH = 7.4). We placed the gels in an incubator set to 37 °C. At specified time points (1.5, 3, 6, 12, and 24 h, then daily for 2 weeks), we removed the entire volume of PBS and replaced it with fresh PBS.27 We stored the collected release samples at −80 °C for the duration of the study. To determine the amount of released SDF-1α at each time point, we performed an enzyme-linked immunosorbent assay (ELISA, Peprotech) according to the manufacturer’s instructions. We calculated the cumulative amount of SDF-1α released at each time point and propagated the error through each successive calculation. Verification of SDF-1α Bioactivity. To verify that our NSC population was responsive to SDF-1α in a typical manner, we conducted a Boyden chamber assay.28−30 Prior to beginning experiments, we coated the transwell inserts (8 μm pores, Corning) with poly-D-lysine (50 μg/mL, Sigma-Aldrich) and laminin (5 μg/mL, Thermo Scientific) to ensure the attachment of NSCs. We then seeded 100 μL of an NSC suspension (5 × 105 cells/mL in basal media) on top of each membrane and added basal media to the bottom of the well (until it just contacted the bottom of the membrane, approximately 500 μL), containing SDF-1α in the following concentrations: 0, 30, 50, 75, 100, or 200 ng/mL. We then incubated the plates (37 °C, 5% CO2) for 24 h. Next, we removed the inset from each well, gently swabbed the top of the membrane to remove excess media and nonmigrated cells, and placed them in a solution of 3.7% paraformaldehyde in PBS (Sigma-Aldrich) for 30m at RT. We then stained the membranes for nuclei (Hoechst 33342, Thermo Scientific), removed the membrane from the inset using a #11 scalpel blade (Integra), and mounted each membrane on a slide with ProLong Gold (Thermo Scientific). To determine the number of cells that migrated to the bottom of the membrane, we imaged each membrane on an Olympus IX81 fluorescent microscope (20×) and counted the nuclei in each field of view (six images per membrane in random locations). All results are presented as normalized to the 0 ng/mL control (control = 1). We also fixed and stained the number of cells on the bottom of each well to see if there was a different trend than on the bottom of the membrane; there was not. Analysis of NSC Recruitment from Released SDF-1α. To determine the ability of the released SDF-1α to recruit NSCs over time, we conducted a modified Boyden chamber assay as described above, with the following modifications: in the bottom of the 24-well plates, we formed 250 μL gels (n = 4 per ratio, including a no gel control) as described above, with SDF-1α (all sterile). We then added NSC basal media to each well (1.25 mL) and allowed the gels to equilibrate for 0, 3, 7, or 14 days. Next, we removed the media, added the coated transwell inserts, seeded NSCs on top of the membrane, and carefully added approximately 250 μL basal media to the bottom of the well (on top of each gel) until it just contacted the bottom of the membrane. We then incubated the plates (37 °C, 5% CO2) for 24 h. After incubation, we measured the number of migrated NSCs as described above and normalized each group to the no SDF-1α control (control = 1). We measured the concentration of SDF-1α in each well during migration via ELISA (Peprotech). Analysis of Recruited NSC Differentiation. To see whether the recruited NSCs could be differentiated following exposure to immobilized IFN-γ, we again formed MAC/heparin hydrogels, as described above, with two major changes: first, we used MAC-DIBO instead of MAC; second, prior to mixing the two solutions of polysaccharide, we reacted MAC-DIBO with azIFN-γ at a final concentration of 300 ng/mL for 1 h at 4 °C.9 Additionally, prior to cross-linking, we added 50 μg of photoreactive laminin (prepared as in ref 12) per gram of polysaccharide solution. We conducted a similar experiment to that described above: we formed gels containing immobilized IFN-γ and soluble SDF-1α (or no SDF-1α for controls) on methacrylated coverslips (prepared as described in ref 9, n = 4) and placed them into the bottom of each well. We then added transwell inserts, seeded NSCs on top of each membrane, and carefully added basal media to the bottom of each well. After allowing the NSCs to migrate for 24 h, we removed the insets. We then allowed the NSCs that had migrated onto each gel to remain on the

(1)

where I is the area of the disaccharide unit peak and I1 and I2 are the areas of the two methacrylate vinyl proton peaks. Rheological Analysis of MAC/Heparin Gels. To prepare MAC/heparin hydrogels for rheological characterization, we separately dissolved lyophilized MAC and lyophilized methacrylated heparin in DI H2O at 2% (w/v). We then mixed these solutions together in the following ratios: 100:0, 90:10, 80:20, and 70:30, expressed as %MAC/%heparin. For example, to form 1 mL of an 80:20 hydrogel, we would mix 800 μL of 2% MAC and 200 μL 2% methacrylated heparin to form a hydrogel that is 2 wt % total polysaccharide in solution. We then prepared a 300 mg/mL solution of Irgacure 184 in 1-vinyl-2-pyrrolidinone (both Sigma-Aldrich). To each of the solutions of blended polysaccharide, we added 6 μL of photoinitiator per gram of total solution. Next, we mixed the solutions at 3000 rpm for 3 min in a dual asymmetric centrifugal mixer (SpeedMixer DAC 150 FVZ, Hauschild Engineering) prior to crosslinking via exposure to 365 nm UV light for 3 min (see Figure 1). Following cross-linking, we washed the gels in PBS overnight and performed a rheological characterization on an Ares RFS-III rheometer (Rheometric Scientific) with 8 mm parallel plate geometry. We conducted a dynamic frequency sweep (strain controlled, 1% strain) from 1 to 100 rad/s. We measured the elastic modulus (G′), the viscous modulus (G″), the dissipation factor (tan δ), and calculated the complex modulus (G*), which is reported here.9,23 The data presented in Figure 2 were averaged from frequencies between 1 and 20 rad/s, as frequencies more than 20 rad/s were too noisy to use.

Figure 2. Methacrylated heparin can be incorporated into MAC hydrogels via photo-cross-linking. All formulations with up to 30% heparin were able to form gels, and all had complex moduli (G*) within the range where neuronal differentiation is favored (100−1000 Pa). While there are differences between groups (p < 0.001, one-way ANOVA), the trend is not linearly proportional to increasing heparin content over the range studied (p = 0.246, regression analysis). Mean ± SD, n = 4. Letters indicate the significance determined by Tukey’s posthoc test. Release of Soluble SDF-1α from MAC/Heparin Gels. To determine the effect of increasing heparin content on the release of soluble SDF-1α from our hydrogels, we first formed gels as described above (same four ratios), with the following addition: prior to crosslinking, we added 75 μL of a 2000 ng/mL solution of SDF-1α (Peprotech) in ultrapure (Type 1) water per gram of polysaccharide solution. Additionally, we sterile-filtered (0.22 μm, Pall Corporation) the heparin, SDF-1α, and photoinitiator solutions and autoclaved the MAC solution prior to cross-linking. We carried out the entire release study under sterile conditions. We prepared 100 μL of hydrogels for each condition (n = 4) and placed them in 1.5 mL centrifuge tubes (sterilized by autoclave). To each tube, we added 500 μL of sterile phosphate buffered saline (PBS, C

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Biomacromolecules gel surface (with immobilized IFN-γ) for 8 d. After this differentiation period, we fixed the cells (3.7% PFA in PBS, RT for 30m) and stained for βIII-tubulin12,31 (BioLegend, 1:300 dilution, with goat antimouse Alexa Fluor 546 secondary, 1:400, Thermo Scientific) and nuclei (Hoechst 33342). For each group, the total number of recruited cells was normalized to its respective no SDF-1α control, and neuronal differentiation was analyzed by determining the percentage of βIIItubulin+ cells. Statistical Analysis. For all hypothesis tests, we considered a pvalue < 0.05 to be significant. When groups were measured across time, we performed a repeated measures ANOVA, with time as the within-subjects variable. For other experiments, we performed either a one-way ANOVA or a regression analysis. Where posthoc tests were performed, we used Tukey’s. We used Minitab 18 or SAS 9.4 for statistical software.

(Figure S4). We did not observe obvious differences in trends (G′ vs G″) between the formulations. Blending Heparin with MAC Slows the Release of Soluble SDF-1α. After demonstrating that we could incorporate MAC and heparin together into hydrogels, we wanted to see if this would affect the release rate of soluble SDF-1α, with the goal of maintaining a gradient of SDF-1α from the hydrogel over an extended period of time (weeks). The long-term goal of such a system is to enhance the endogenous recruitment of NSCs to an injury site in vivo soon after injury, strengthening and localizing the endogenous cell response to injury. After loading SDF-1α into gels of varying heparin content (0 to 30%), we analyzed the cumulative release profiles of SDF-1α over a period of 2 weeks via ELISA (Figure 3). Our hypothesis was that adding heparin would

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RESULTS AND DISCUSSION Heparin Can Be Incorporated into Soft MAC Hydrogels. In order to develop a system for delivering both soluble and immobilized proteins, we sought to augment MAC hydrogels with heparin, as heparin has been shown to slow the release of a wide variety of proteins.17 To do this, we added a methacrylate group to heparin so that it could be photocross-linked together with MAC,13 creating a hydrogel of the two materials blended together. After verifying that we had successfully methacrylated heparin (33% methacrylation, Figure S1) via 1 H NMR, we blended MAC (23% methacrylation32) and heparin together in varying ratios, increasing the amount of heparin in increments of 10%. We found that heparin amounts above 30% resulted in the immediate precipitation of polysaccharide from solution. This is due to electrostatic complexing between MAC (positively charged amines) and heparin (negatively charged hydroxyls and sulfated side chains), as has been exploited by others for the purpose of forming nanoparticles.33 Thus, we pursued gels in the following ratios (%MAC/%heparin): 100:0, 90:10, 80:20, and 70:30. We did observe some minor electrostatic complexation from the 80:20 and 70:30 groups, but were able to still form gels. The lack of precipitation from those groups when compared to ref 33 is likely due to the neutralization of primary amines on pure chitosan and hydroxyls on heparin caused by methacrylation (all mixing was carried out in pH 7.4 PBS). We then experimented with a variety of gelation conditions (varying the amount of photo-cross-linker and UV exposure time) until we found one set of conditions that resulted in gels in our target stiffness range for each condition (G* = 100− 1000 Pa, as we have shown that this encourages neuronal lineage commitment from NSCs,11 Figure 2). We found that the groups were different from each other (one-way ANOVA, p < 0.001), but this difference was not linearly dependent on increasing amounts of heparin (regression analysis, p = 0.246). It is possible that the differing stiffness can be explained by a charge-based phenomenon. Others have observed that hydrogel rheological properties are dependent on heparin concentration,34 supporting the notion that a charge-based phenomenon is responsible. However, we observed absolute differences smaller than previously reported,34 and importantly, all of the groups resided comfortably in the range of stiffnesses that favors neuronal over oligodendrocytic or astrocytic differentiation.11 We also investigated a frequency sweep G′ and G″ and found that all of the heparin-containing formulations were able to form gels with primarily covalent cross-links, as indicated by the lack of frequency dependence

Figure 3. Adding heparin to MAC hydrogels affects the release of soluble SDF-1α. An investigation of SDF-1α release over 2 weeks shows that gels containing 30% heparin (70:30) released in a more linear manner, while the other groups showed release over 5−6 days, followed by a plateau. Interestingly, the 90:10 group released SDF-1α differently than the 100:0 group, possibly due to the stability of the gel itself. Heparin content (p = 0.0001), time (p < 0.0001), and heparin × time (p < 0.0001) were all significant factors (repeated measures ANOVA). Mean ± cumulative SEM, n = 4.

result in a slower release rate. We confirmed our hypothesis by a repeated measures ANOVA, which indicated that heparin content (p = 0.0001), time (p < 0.0001), and heparin × time (p < 0.0001) were all significant factors. The 100:0 and 90:10 formulations showed an initial release and then slowed down, plateauing after approximately 1 week. Neither the 80:20 nor the 70:30 formulations experienced rapid initial release. Both showed a steady rate of release for the first week, with 80:20 then reaching a plateau. The 70:30 formulation continued to release over the entire 2 weeks. The large differences in total protein released (48.6 ± 4.08%, 60.7 ± 4.97%, 28.6 ± 4.23%, and 52.7 ± 8.34% for 100:0, 90:10, 80:20, and 70:30, respectively, mean ± SEM) are somewhat surprising. This may be due to differences in erosion/degradation rates of the two polysaccharides. A frequency sweep of G′ and G″ shows that all of the heparincontaining groups formed stable, covalently cross-linked gels,35 indicating that differences in cross-linking were not responsible for differences in total protein released or the different trends between formulations (Figure S4). This warrants investigation in future studies: perhaps the relative degradation rate of each polysaccharide could be correlated to protein release. Overall, the rate and total protein released compare well with D

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membrane and allowed them to migrate for 24 h. Our hypothesis was that the early (0, 3 days) time points would show increased migration from 100:0, 90:10, and 80:20 formulations, while later time points would show increased migration from the 70:30 formulation, as the former gels would not be able to release new SDF-1α beyond 3 days. Put another way, we hypothesized that the migration of NSCs would be proportional to the slope of each release curve at the specified time point. A statistical analysis of the data supports our hypothesis (Figure 4B). Both time (p < 0.0001) and formulation (p = 0.0107) were significant factors in our repeated measures ANOVA, as was time × formulation (p < 0.0001). Additionally, at day 0, when 100:0 and 90:10 experienced rapid release, they also both recruited significantly more cells versus 80:20 and 70:30, which did not show a large initial release. At day 3, when all formulations had roughly the same rate of change, they all recruited the same number of cells. After day 3, only the 70:30 formulation was able to recruit cells, reflecting the release curves plateauing for all but that group. The 70:30 group recruited generally the same number of cells at all time points, reflecting the more linear nature of that release profile. These findings agree with the measured concentration of SDF-1α in the Boyden chambers during each recruitment window (Figure S3). Concurrent Delivery of Soluble SDF-1α and Immobilized IFN-γ Differentiates Recruited NSCs into Neurons. Other groups have investigated delivering SDF-1α with a variety of different methods, including (but not limited to) SDF-1α-secreting MSCs38 and polymeric nanoparticles39 to heal a wide variety of tissues. Typically, this is accomplished by increased vascularization or stem cell recruitment. While functional regeneration has been observed when delivering soluble SDF-1α to mesenchymal tissues,18 the same does not necessarily hold true for the CNS. SDF-1α delivery within the CNS has not been extensively investigated,40 but preliminary studies within the spinal cord39 have indicated a lack of therapeutic benefit. In the brain, where increased angiogenesis may have functional benefits,41 SDF-1α delivery improves the migration of grafted NSCs,42 but its effects on functional recovery remain largely unstudied. While encouraging more NSCs to survive and migrate may indirectly support recovery, it is important for their behavior to be modulated (e.g., lineage specification) to improve integration with the host tissue. Thus, we were motivated to include another factor in our approach: immobilized IFN-γ, which we have shown drives robust neurogenesis (a key treatment target) from NSCs under a variety of conditions.9,12,22,31,43 To demonstrate the feasibility of this approach to first recruit NSCs via a gradient of soluble SDF-1α and then differentiate them into neurons via immobilized IFN-γ, we formed MAC/heparin gels containing both factors in the bottom of well plates and seeded cells onto transwell membranes. After allowing the NSCs to migrate, we removed the insets and allowed the migrated NSCs to remain on top of the gels for 8 days (Figure 5A). Following this, we stained for βIII-tubulin to assess neuronal differentiation (Figure 5B). We found, expectedly, that the migrated cells differentiated into neurons (Figure 5B,D). There were also interesting qualitative differences between the groups (Figure 5B). The 100:0 gels showed cells with morphologies typically seen when differentiating NSCs into neurons: elongated cell bodies with axonal projections. However, the gels containing heparin (90:10, 80:20, and 70:30) showed cell morphologies that were

previously published studies combining heparin with other materials,15 approximately 50−60% release over 2 weeks, with relatively linear release followed by a plateau. NSC Recruitment is Proportional to a SDF-1α Release Rate. The ability of SDF-1α to induce the migration of NSCs both in vitro28,36 and in vivo3 is known. As populations of NSCs can be heterogeneous and behave differently, we wanted to confirm that the migration in our NSC population due to SDF-1α was consistent with previous reports. We conducted a standard Boyden chamber assay and found that increasing SDF-1α resulted in greater NSC chemotaxis, up to 100 ng/mL (Figure S2). Concentrations of SDF-1α above 100 ng/mL resulted in decreased chemotaxis in vitro due to the formation of repellant dimers.37 This agrees well with results published by other groups,28 demonstrating that our population of NSCs responds appropriately to SDF-1α. After establishing that heparin can affect the release of soluble SDF-1α when mixed and copolymerized with MAC, we wanted to investigate the ability of this system to promote chemotaxis in vitro. We formed SDF-1α-loaded hydrogels in the bottom of well plates (Figure 4A) and allowed the gels to

Figure 4. MAC/heparin hydrogels with SDF-1α recruit NSCs proportional to their release rate over 2 weeks. (A) Schematic showing experimental setup. (B) At early time points (0 and 3 days), all formulations increased the recruitment of NSCs compared to a baseline control. However, at 7 and 14 days, only the 70:30 formulation resulted in increased recruitment. The initial release of the 100:0 and 90:10 formulations is evident at the 0 d time point. The actual concentration of SDF-1α in the wells at each time point can be seen in Figure S3. A repeated measures ANOVA indicated that both time (p < 0.0001) and formulation (p = 0.0107), as well as time × formulation (p < 0.0001) were significant factors. Mean ± SD, n = 4. Groups sharing a letter (A, B) are not significantly different at each time point.

release SDF-1α into NSC basal media for various durations based on the observed release profiles: 0, 3, 7, or 14 days. At each time point, we replaced the media with fresh basal media, requiring the concentration gradient to reform in a manner proportional to the slope of the release profile at each time point. We then seeded NSCs on top of the transwell E

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Figure 5. Delivering soluble SDF-1α alongside immobilized IFN-γ differentiates recruited NSCs into neurons. After recruiting NSCs via soluble SDF-1α gradients, they were exposed to immobilized IFN-γ, which induced neuronal differentiation. (A) Schematic of experimental approach. (B) IHC images showing mostly βIII-tubulin+ (a neuronal marker) cells on all four formulations. Scale bars = 100 μm. (C) The gels recruited similar numbers of NSCs as the previous 0 d time point (Figure 4), indicating that immobilized IFN-γ does not appear to affect NSC recruitment. Mean ± SD, n = 4. Groups not sharing a letter are significantly different (p < 0.0001) as determined by one-way ANOVA with Tukey’s posthoc. (D) Similar lineage specification was observed on all formulations, indicating that heparin does not affect the ability of immobilized IFN-γ to differentiate NSCs into neurons. Mean ± SD, n = 4. No significance (p = 0.0574) was determined by one-way ANOVA with Tukey’s posthoc.

investigation in future work. Accordingly, it is possible that the combination of SDF-1α and IFN-γ will fail to show benefits in an injury model. Due to the wide variety of soluble proteins for which heparin-containing biomaterials can increase release latency and our experience immobilizing many different recombinant signaling proteins, the system is applicable to combinations beyond the one tested here. For example, we could release a neurotrophic factor instead (e.g., BDNF45) and immobilize neurite guidance cues.46

more compact, with less axonal projections. A dependence of morphology on differences between similar polysaccharides (MAC/heparin vs MAC) is consistent with previous work,9 where we found that methacrylated hyaluronan and MAC with identical immobilized proteins resulted in subtle differences in gene and protein expression from NSCs. Quantitatively, we observed a similar number of recruited cells (total nuclei, Figure 5C), as in Figure 4. Neuronal differentiation (% βIIItubulin+ cells) was consistent across all formulations (Figure 5D), suggesting that immobilized IFN-γ functions independently of the released SDF-1α to differentiate NSCs into neurons. All of the gels containing immobilized IFN-γ differentiated NSCs into neurons at a rate higher than that for pure MAC,9 and the consistent neuronal differentiation between the formulations studied here suggests that the presence of heparin does not affect neuronal differentiation. Future work will investigate the applicability of this system to in vivo models of CNS injury. Neuronal loss is one of the primary drivers of functional deficits following CNS trauma such as spinal cord or traumatic brain injury.44 Increasing the migration of endogenous NSCs to an injury site, and then differentiating them into neurons, which this system is uniquely capable of, represents a new avenue of investigation. It is likely that the number of NSCs available to migrate in vivo will be substantially different than the number of cells that we studied here, and exogenous cell sources may be needed to supplement the response. This will be an important area of

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CONCLUSIONS We have developed a polysaccharide-based system for slowing the release of soluble SDF-1α alongside delivery of immobilized IFN-γ. This was accomplished via a hydrogel consisting of methacrylated heparin copolymerized with MAC into hydrogels. We showed that this system can be used to recruit NSCs and differentiate them into neurons in vitro. Adding heparin to MAC slowed the release of SDF-1α over 2 weeks. The 100:0, 90:10, and 80:20 formulations increased recruitment of NSCs at early time points (0 and 3 days), while 70:30 gels increased migration more evenly. All of the hydrogel formulations were able to differentiate the recruited cells into βIII-tubulin+ neurons via immobilized IFN-γ with similar efficiencies. Given that insufficient number and improper phenotype are common issues regarding the endogenous response of NSCs following CNS injury, this work provides a F

DOI: 10.1021/acs.biomac.9b00719 Biomacromolecules XXXX, XXX, XXX−XXX

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Biomacromolecules

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foundation for future development and testing as a potential treatment.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.biomac.9b00719. 1 H NMR of methacrylated heparin, soluble SDF-1α bioactivity, SDF-1α concentration during NSC recruitment experiment, and frequency sweep of G′ and G″ for the heparin-containing gels (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Nic D. Leipzig: 0000-0002-6356-7691 Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was partially supported by the National Institute of Neurological Disorders and Stroke (R21NS096571-01). Additionally, we thank Dr. Rebecca Willits (UA) for the use of her rheometer.

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REFERENCES

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DOI: 10.1021/acs.biomac.9b00719 Biomacromolecules XXXX, XXX, XXX−XXX

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DOI: 10.1021/acs.biomac.9b00719 Biomacromolecules XXXX, XXX, XXX−XXX