Morphology, Migration, and Transcriptome Analysis of Schwann Cell

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Morphology, Migration and Transcriptome Analysis of Schwann Cell Culture on Butterfly Wings with Different Surface Architectures Jianghong He, Cheng Sun, Zhongze Gu, Yumin Yang, Miao Gu, Chengbin Xue, Zhuoying Xie, Hechun Ren, Yongjun Wang, Yan Liu, Mei Liu, Fei Ding, Kam W. Leong, and Xiaosong Gu ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.8b00552 • Publication Date (Web): 20 Aug 2018 Downloaded from http://pubs.acs.org on August 21, 2018

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Morphology, Migration and Transcriptome Analysis of Schwann Cell Culture on Butterfly Wings with Different Surface Architectures

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Jianghong He , Cheng Sun , Zhongze Gu , Yumin Yang , Miao Gu ,Chengbin Xue , 2

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1

1

1

4,

Zhuoying Xie , Hechun Ren , Yongjun Wang , Yan Liu , Mei Liu , Fei Ding , Kam W. Leong *, 1,

Xiaosong Gu *

1

Key Laboratory for Neuroregeneration of Jiangsu Province and Ministry of Education,

Co-innovation Center of Neuroregeneration, Nantong University, Nantong, 226001, China 2

State Key Laboratory of Bioelectronics, Southeast University, Nanjing, 210096, China

3

Chengde Medical College, Chengde, 067000, China

4

Department of Biomedical Engineering, Columbia University, New York, New York10027, United

States

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These authors contribute equally to this work.

*Corresponding authors: [email protected] (K.W. Leong); [email protected] (X. Gu)

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ABSTRACT It has been shown that material surface topography greatly affects cell attachment, growth, proliferation and differentiation. However, the underlying molecular mechanisms for cell-material interactions are still not understood well. Here, two kinds of butterfly wings with different surface architectures were employed for addressing such an issue. Papilio ulysses telegonus (P.u.t.) butterfly wing surface is composed of micro/nano-concaves, while Morpho Menelaus (M.m.) butterfly wings are decorated with grooves. RSC96 cells grown on M.m. wings showed a regular sorting pattern along with the grooves. On the contrary, the cells seeded on P.u.t. wings exhibited random arrangement. Transcriptome sequencing and bioinformatics analysis revealed that huntingtin (Htt)-regulated lysosome activity is a potential key factor for determining cell growth behavior on M.m. butterfly wings. Gene silence further confirmed this notion. In vivo experiments showed that the silicone tubes fabricated with M.m. wings markedly facilitate rat sciatic nerve regeneration after injury. Lysosome activity and Htt expression were greatly increased in the M.m. wing fabricated grafts bridged nerves. Collectively, our data provides a theoretical basis for employing butterfly wings to construct biomimetic nerve grafts and establishes Htt-lysosome as a crucial regulator for cell-material interactions.

KEYWORDS: cell-material interaction, butterfly wings, surface architecture, Schwann cells, lysosome, huntingtin


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In vivo, most mammalian cells are adherent and must attach to and spread on a surface in order to survive, proliferate and function. Therefore, surface properties including chemical and physical characteristics play an essential role for cell adhesion, growth and differentiation.

1, 2

Recently,

numerous studies revealed that topographical cues have direct effects on cell behavior such as 3, 4

adhesion, migration, cytoskeletal arrangements and differentiation.

It has been shown that

biophysical cues, in the form of parallel microgrooves on the surface of cell-adhesive substrates, can replace the effects of small-molecule epigenetic modifiers and significantly improve 5

reprogramming efficiency of induced pluripotent stem cells. The optimized materials with specific micro/nano-structures significantly improve cell attachment and proliferation. Schwann cells (SCs) are specialized glial cells in the peripheral nervous system, playing important roles in maintaining neuronal structure and function and repairing damaged nerves.

6

7

Artificial nerve graft bridging is a commonly used strategy for treating peripheral nerve defects.

Microenvironments constructed by nerve grafts play a pivotal role for facilitating SC growth and 7

proliferation. Surface structures of grafts were considered as a key element of microenvironments. The topography of biomaterials, including surface roughness, pores and orientation, is an 8, 9

important factor for constructing the niche for tissue regeneration.

Due to the delicate

micro/nano surface structures, butterfly wings were received much more interest for the research and development of biomimetic biomaterials.

10, 11

RESULTS AND DISCUSSION Two species of butterflies, Morpho Menelaus (M.m.) and Papilio ulysses telegonus (P.u.t.) are chosen due to their significant differences in surface micro/nanostructures of wings. To increase hydrophilic property, butterfly wings were treated with acid and base solutions.

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After treatments,

butterfly wings lost their original shiny blue color (Figure 1A-a, A-b; Figure 1B-e, B-f). M.m. wing surface is decorated with parallel ridges, which are spaced approximately 2 µm apart (Figure 1A-c, A-d). For P.u.t. wings, SEM images revealed that their surface contain concave forms arrange periodically along the ridges (Figure 1B-g, B-h). Hydrophilic properties of butterfly wings were


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enhanced by the acidic/basic treatment as evidenced by the increases in contact angles (Figure 1A-i, A-j; Figure 1B-k, B-l). To investigate whether these two kinds of butterfly wings have similar chemical constituents, we performed a series of experiments including FTIR, solid state NMR

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C

and X-ray Photoelectron Spectroscopy (XPS). The FTIR spectra of M.m. and P.u.t. wings showed typical characteristics of chitin.

13

The similar spectra between M.m. and P.u.t wings indicate that

they have similar chemical bonds and functional groups (Supplementary S1). The NMR

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C

spectra in Supplementary S2, correspond to the structure of chitin and have defined peaks, C1 (δ104.5), C2 (δ55.6), C3 (δ73.8), C4 (δ83.5), C5 (δ76.1), C6 (δ61.4), C7 (δ23.2) and C=O 14

(δ173.8).

The spectra of M.m. wings were similar to that of P.u.t. wings with or without the

treatment. Furthermore, XPS was also employed for analyzing the surface elements of butterfly wings. As shown in Supplementary S3, similar to P.u.t. wings, M.m. wing surface was mainly composed of C, N and O. The above results showed that except big difference in the surface architectures, M.m. and P.u.t. butterfly wings have similar surface chemical composition. Next we examined growth behavior of cells grown on butterfly wings. As shown in Figure 2A, the primary SCs on M.m. wings exhibited regular radial sorting pattern. The cells on P.u.t. wings grew randomly. The SEM images further confirmed these phenomena (Figure 2B). Additionally, we also measured deviation angles of the individual SC from the ridge of butterfly wing scales, with 0° (90°) denoting a cell parallel (perpendicular) to the ridge direction. On M.m. wings, the deviation angles for the most SCs are below 15° (Figure 2C, D). On P.u.t. wings, the deviation angles for SC extensions are ranged from 0° to 90°. Furthermore, we also observed cell growth behavior using live cell image system. The representative snapped images for SCs grown on different substrates were shown in Figure 2E. Similarly, most of the cells grown on M.m. wings showed a regular radial sorting trend, while the major cells on P.u.t. wings exhibited random pattern (Figure 2E, F). Surface topography of materials is a key factor for cell adhesion, growth, proliferation and differentiation.

15, 16

For example, titanium implants having a rough surface perform much better

than those having a smooth surface for osteoblast attachment, host-implant integration, and the overall success of the implant.

17

Naturally derived materials with hierarchical organization provide


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great hints for generating high-performance and functional bionanomaterials. In the present study, the groove-shaped surfaces of M.m. wings are likely an ideal substrate for SCs adhesion and growth. In accordance with our findings, recent studies have shown that surfaces with nano- and micrometer topographical cues have positive influences on cell behavior such as enhancing 18

osteoblast maturation, muscle,

23

stimulating stem cell differentiation,

and regulating macrophage activity.

19-22

engineering intestinal smooth

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The different growth behavior of SCs on the wings of M.m. and P.u.t. prompt us to uncover the underlying mechanisms. To address this issue, we carried out transcriptome-based network analysis and tried to find the key differentially expressed genes. We first applied weighted gene co-expression network analysis (WGCNA) and identified 14 co-expression modules in M.m. wings (Figure 3A). Module preservation analysis showed that these modules are highly preserved (Zsummary > 10), indicating a strongly similar transcriptional architecture of biological process in these two groups (Figure 3A). Next we investigated each module’s biological trajectory by calculating the module eigengene (ME, the first principal component of the module) and assessed shared function among genes within the module by enrichment for Gene Ontology (GO) annotation terms. Representative examples for up- and down-regulated modules are shown in Figure 3B. MEs for M3, M5, and M7 increased during the early stage (0-12 h) and are enriched for the GO terms lysosome, cell migration and cell cytoskeleton (Figure 3B). Notably, M3 associated with lysosome, nucleotide binding and transport increased at the earliest stage (0-1 h), followed by M5 representing cell migration and ion binding (Figure 3B). It should be mentioned that, M3 and M5 modules in M.m. wings exhibited high levels of preservation with P.u.t. group (Figure 3A); however, they are different in expression trajectory based on ME values (Supplementary S4). Moreover, we also examined the main biological events happened after cell seeding on M.m. wings. To track down the biological processes along with the time, we separated the whole time series into 3 stages, stage 1 (0.5 h-3 h), stage 2 (6 h-12 h) and stage 3 (24 h-72 h). As shown in Figure 3C, lysosome, protein synthesis, cell migration, morphogenesis, cell cycle and lipid metabolism were sequentially activated. Collectively, our systems analysis revealed that M3 module correlated with lysosome activity may account for the different cell growth behavior on


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M.m. and P.u.t. butterfly wings. By applying WGCNA to the P.u.t. group, 16 co-expression modules were identified. Module-stage analysis showing a different trend for each module in the P.u.t group with comparison of the M.m. group (Supplementary S5). For example, genes in M3 involved in lysosome and axon guidance overexpressed at the late stage (24 h-72 h) in the P.u.t. group. Thus far the analyses focused on system-level transcriptional change, then we go further to individual gene-transcript changes responsible for the different module expression pattern between two groups. To this aim, the differential expressed genes (DEGs) were identified. A total of 3319 DEGs were obtained, including 1294 up-regulated genes and 2025 down-regulated genes. The significant DEGs at each stage were presented as heatmap plot (Figure 4A; Supplementary S6). We found that, at stage 1 (0.5 h-3 h), genes up-regulated in M.m. group are those involve in endosome, cell adhesion, cell motility, signal transduction and integral component of membrane (Figure 4A). In agreement with the observed cell growth behavior (Figure 2), these biological events are closely related with cell adhesion, movement and growth. Together with the module analysis showing the activated endosome related events such as lysosome activity at the earliest stage after cell seeding, hence, we predicted that the lysosome related activities including compound transport and/or signaling transduction in cells may determine SC growth pattern on M.m. butterfly wings. Furthermore, based upon gene set enrichment analysis (GSEA), the DEGs related with cell adhesion and lysosome activity were subjected to protein-protein interaction (PPI) network construction (Figure 4B). In the PPI network for up-regulated DEGs at stage 1, 10 nodes with the high connectivity with regulation of actin cytoskeleton and lysosome were observed (left panel, labeled in pink and red color; Figure 4B). However, in P.u.t group, a few nodes connected with the pathways we interested in were found in the PPI networks (right panel; Figure 4B). To define the observed DEGs were regulated by which transcriptional factors (TFs), we performed the regulatory network inference assay. The results showed that several TFs including Rela, Ccnd1, Hmga1, Htt and Crebbp were designated as potential regulators (Figure 5A). Among these predicted key genes, Htt caught our attention since it has been shown that Htt plays 25, 26

an important role in microtubule-mediated transport and vesicle function.


Moreover, Htt was

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significantly up-regulated on M.m. wings both in the DEG analysis and PPI networks at stage 1 (Figure 4A, B). For these reasons, Htt was chosen as a potential regulator of lysosome activity. To address this prediction, we transfected RSC96 cells with siRNAs against Htt. Htt siRNA-2 exhibits the best knockdown efficiency based upon qRT-PCR and Western blot assays (Figure 5B). As expected, the cells transfected with the control siRNA exhibit a regular sorting growth pattern on M.m. wings. However, Htt knockdown impairs this pattern and the cells were randomly spread (Figure 5C). Furthermore, lysosome activity was greatly down-regulated by Htt knockdown (Figure 5D). These results clearly indicate that Htt is a key regulator for lysosome activity, which was responsible for cell-material interaction. 6

Due to the pivotal roles of SCs for peripheral nerve regeneration, we speculate that nerve grafts fabricated with butterfly wings of M.m. may play beneficial effects for nerve repair after injury. To test this hypothesis, we transected rat sciatic nerves and bridged the resulting nerve gaps with silicone tubes, into which the butterfly wings were inserted (Figure 6A). The sciatic nerves were collected at different time points and tissue regeneration was evaluated. The results showed that Htt expression in the sciatic nerves bridged by M.m. wings fabricated grafts was markedly increased. Similar to Htt expression, SC proliferation was greatly stimulated (Figure 6B). It is worthy to note that the growth tracks of SCs were in a radial sorting pattern along with the parallel grooves of M.m. wings. These data indicate that the nerve grafts fabricated with M.m. wings improves nerve regeneration, suggesting the biomimetic replicates of M.m. butterfly wings might be employed for clinical implementation.

CONCLUSIONS Taken together, in the present study, we found that the butterfly wings of M.m. with natural elegant micro/nano grooved surface structures are suitable for SC growth. In vivo experiments indicated that the nerve grafts fabricated with the butterfly wings of M.m. improves sciatic nerve regeneration after injury. The Htt-associated lysosome activity may account for the observed cell growth behavior on wings of M.m. Our data revealed a molecular mechanism for cell-biomaterial


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interactions and provided a direction for constructing biomimetic nerve grafts to facilitate nerve regeneration.

METHODS Fabrication of butterfly wing scaffolds: Butterfly wings were sequentially treated with 1 M HCl for 2 h and 2 M NaOH solution at 60°C for 6 h. The wings were rinsed with double distilled water to remove the remaining NaOH. For sterilization, the butterfly wings were soaked in 70% ethanol overnight and subjected to ultraviolet irradiation for 30 min. The resulting butterfly wings were incubated in DMEM for 3 h prior to cell seeding. Physical and chemical characteristics of butterfly wings: The water contact angles of butterfly wings were measured with a horizontal microscope equipped with the JC2000C1 contact Angle Goniometer. A water droplet (10 µL) was dispensed with a micrometric syringe (Gilmont Instrument) onto the surface. The slope of the tangent to the drop at the liquid-solid-vapor interface line was measured repeatedly for at least five instances, and the mean value was calculated as a measure of the static contact angle. For field emission scanning electron microscopy (FESEM) observation, the samples of butterfly wings were coated with platinum after critical point drying, followed by observation under a SEM (Hitachi, S-3400N, Japan). Cell culture：：RSC96 cells were obtained from American Type Culture Collection (ATCC) and were maintained in Dulbecco’s modified Eagle’s medium (DMEM) (Gibco, Grand Island, NY, USA) supplemented with 5% newborn calf serum (NCS, Gibco), streptomycin (100 U/mL), and penicillin (100 U/mL) and grown at 37°C in a humidified atmosphere of 5% CO2. The primary SCs were harvested from postnatal 1-2 d Sprague-Dawley rats as described previously.

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Scanning electron microscopy：：The alignment of SCs on the butterfly wings were studied using a scanning electron microscope (SEM). After 1d incubation, the samples were washed with PBS and fixed in 4% glutaraldehyde solution. The samples were then post fixed with 1% OsO4, dehydrated in graded acetone and dried at critical point drier (Hitachi, Tokyo, Japan). After this, the


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samples were coated with gold in a JFC-1100 unit (Jeol Inc., Japan) and observed under a SEM (Hitachi, S-3400N, Japan). Gene expression profiling and bioinformatics analysis: Total RNA was extracted using TRIZOL Reagent and checked for a RIN number to inspect RNA integrity by an Agilent Bioanalyzer 2100. Qualified total RNA was further purified by RNeasy micro kit and RNase-Free DNase Set. Total RNA was amplified and labeled by Low Input Quick Amp Labeling Kit, One-Color (Cat.# 5190-2305), and then hybridized to Agilent Whole Rat Genome Microarray 4 × 44 K and scanned by Agilent Microarray Scanner. Raw data were normalized by Quantile algorithm, Gene Spring Software 11.0 (Agilent technologies, Santa Clara, CA, US). For all analyses, background signals were calculated resulting in 27716 probes to be present at least one time point. Weighted gene co-expression network analysis (WGCNA): The R package WGCNA was 27

used to find sets of co-regulated genes, defined as module.

Gene modules were labeled in

different colors. Unassigned genes were assigned to the grey module. The module eigengene (ME) corresponding to the first principal component was calculated for each module and a ME-to-condition correlation visualized as a heatmap chart. Functional annotation for each module was performed by David online tool (http://david.abcc.ncifcrf.gov/). Gene ontology terms shown in this study summarized all similar sub-terms into an overarching term. Module preservation statistics: In order to assess whether the density and connectivity patterns of individual modules are preserved between datasets, Z-summary static which summarizes the evidence that a module is preserved and indicative of module robustness and reproducibility is calculated by R function ‘module Preservation’ to evaluate the preservation.

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In

general, modules with Z-summary scores > 10 are interpreted as strong preservation. Differential expression gene analysis: The R package limma was employed to find genes which are differentially expressed between the two datasets. Genes with cutoff adj. pval < 0.05 and fold change > = 2 were considered as differentially expressed. PCA analysis were performed by R package ‘FactoMineR’. Genes with high correlation with PC1 and PC2 were selected as significant

differential

expression.

correlation coefficients with PC1.

GO

For

GSEA

gene

sets

analysis, were


DEGs were downloaded

ranked from

by

its

GO2MSIG

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(http://www.go2msig.org/cgi-bin/prebuilt.cgi?taxid=10116) and pathway gene sets were obtained from KEGG database (http://www.kegg.jp/). Gene interaction network analysis: Gene interaction relationship was from two sources. (1) 29

STRING database which defined protein-protein interaction (PPI);

(2) KEGG database defined.

Networks were constructed by Cerebral software. Up-stream network inference: The regulator-target associations were from the TF enrichment module of the IPA software (http://www.ingenuity.com/). The putative targets are those differentially expressed genes belonging to each WGCNA module. Each edge in the regulatory network was assigned a time stamp based on the expression profiles of its respective regulator and target nodes. For the target node, the time points at which a gene was significantly induced in M.m. were considered. A regulator node was defined as ‘present’ at a given time point if: (1) it was up-regulated in M.m. relative to P.u.t. (fold change >=1.3); and (2) the expression is high (minimal log2 transferred expression value of 6). If an edge was assigned with several time points, then only keep the first time points. In vivo experiments: The treated butterfly wings were cut into a suitable size and the trimmed wings were inserted into silicone tubes (1.5 mm/6.0 mm, i.d./length). Adult male SD rats were anaesthetized before the sciatic nerve was exposed through an incision on the left hind limb and transected to create a gap. The decorated silicone tubes were implanted to bridge the gap with the proximal nerve stump anastomosed to the tube at the junction. At 6 h, 12 h, 18 h after surgery, rats were sacrificed and the silicone tubes, together with regenerated nerves, were harvested for cutting into sections, which were subjected to immunohistochemistry using anti-S100β and anti-Htt antibodies.

ACKNOWLEDGEMENTS This work was supported by the National Key Research and Development Program of China (Grant Nos. 2017YFA0104703, 2017YFA0701304 and 2016YFC1101603), and the Ministry of Science and Technology of China Grants (973 Program, 2014CB542202), the National Natural Science Foundation of China (Grant Nos. 31730031 and 81671823).


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ASSOCIATED CONTENT Supporting Information Available: The methods for butterfly wing surface chemical composition analysis, the FTIR spectra, the solid state NMR

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analysis, the expression trajectory of specific modules, the network analysis of cell growth on P.u.t. butterfly wings, and the differential expressed gene analysis of stage 2 and stage 3. These materials are available free of charge via the Internet at http://pubs.acs.org. Financial interest statements The authors declare no competing financial interests.

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20. Long, J.; Kim, H.; Kim, D.; Lee, J. B.; Kim, D. H. A Biomaterial Approach to Cell Reprogramming and Differentiation. J. Mater. Chem. B 2017, 5, 2375-2379. 21. Chen, W.; Shao, Y.; Li, X.; Zhao, G.; Fu, J. Nanotopographical Surfaces for Stem Cell Fate Control: Engineering Mechanobiology from the Bottom. Nano today 2014, 9, 759-784. 22. Kulangara, K.; Adler, A. F.; Wang, H.; Chellappan, M.; Hammett, E.; Yasuda, R.; Leong, K. W. The Effect of Substrate Topography on Direct Reprogramming of Fibroblasts to Induced Neurons. Biomaterials 2014, 35, 5327-5336. 23. Kobayashi, M.; Lei, N. Y.; Wang, Q.; Wu, B. M.; Dunn, J. C. Orthogonally Oriented Scaffolds with Aligned Fibers for Engineering Intestinal Smooth Muscle. Biomaterials 2015, 61, 75-84. 24. Luu, T. U.; Gott, S. C.; Woo, B. W.; Rao, M. P.; Liu, W. F. Micro- and Nanopatterned Topographical Cues for Regulating Macrophage Cell Shape and Phenotype. ACS Appl. Mater. Interfaces 2015, 7, 28665-28672. 25. Elias, S.; McGuire, J. R.; Yu, H.; Humbert, S. Huntingtin Is Required for Epithelial Polarity through RAB11A-Mediated Apical Trafficking of PAR3-aPKC. PLoS Biol. 2015, 13, e1002142. 26. Yano, H.; Baranov, S. V.; Baranova, O. V.; Kim, J.; Pan, Y.; Yablonska, S.; Carlisle, D. L.; Ferrante, R. J.; Kim, A. H.; Friedlander, R. M. Inhibition of Mitochondrial Protein Import by Mutant Huntingtin. Nat. Neurosci. 2014, 17, 822-831. 27. Langfelder, P.; Horvath, S. WGCNA: an R Package for Weighted Correlation Network Analysis. BMC Bioinf. 2008, 9, 559. 28. Langfelder, P.; Luo, R.; Oldham, M. C.; Horvath, S. Is My Network Module Preserved and Reproducible? PLoS Comput. Biol. 2011, 7, e1001057. 29. Franceschini, A.; Szklarczyk, D.; Frankild, S.; Kuhn, M.; Simonovic, M.; Roth, A.; Lin, J.; Minguez, P.; Bork, P.; von Mering, C.; Jensen, L.J. STRING v9.1: Protein-protein Interaction Networks, with Increased Coverage and Integration. Nucleic Acids Res. 2013, 41, D808-815.


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Figures’ Captions Figure 1. Optical and scanning electron microscope (SEM) images of Morpho Menelaus (M.m.) and Papilio ulysses telegonus (P.u.t.) butterfly wings. (A) Digital image of M.m. intact butterfly. (a, b) Optical image of the blue region of M.m. before (a) and after (b) acidic and basic treatment. Scale bar = 50 µm. (c, d) SEM images of the blue region showing surface nanostructures before (c) and after (d) acidic and basic treatment. Scale bar = 2 µm. (B) Digital image of P.u.t intact butterfly. (e, f) Optical image of the blue region of M.m. before (e) and after (f) acidic and basic treatment. Scale bar = 50 µm. (g, h) SEM images of the blue region showing surface nanostructures before (g) and after (h) acidic and basic treatment. Scale bar = 2 µm. Hydrophilic evaluation of the butterfly wings. A drop of pure water (10 µl) is used to measure contact angles. (i, j) Contact angles on the untreated (i) and treated butterfly wings (j) of M.m. (k, l) Contact angles on the untreated (k) and treated butterfly wings(l) of P.u.t. Data are shown as mean ± standard deviation of 10 independent experiments.

Figure 2. Growth behavior and morphological characteristics of SCs on butterfly wings. (A) Immunostaining of SCs. SCs were seeded on the treated butterfly wings. After 12 h-culture, the cells were subjected for immnuofluoresence analysis. Scale bar = 50 µm. (B) SEM images of SCs showing different growth behavior. SCs were grown on the butterfly wings for 12 h and then the cell morphology was monitored by SEM. The boxed area was magnified and placed at the right panel. (C) Visual representation of SCs angle in respect to the pattern axis. Y-axis represents the axis parallel to the pattern, whereas x-axis represents perpendicular to the pattern of SCs alignment. (D) Quantification of SCs directionality.

45° represents completely random orientation.

(E) The live cell motion trajectories of GFP-labeled SCs. SCs were isolated from GFP-transgenic mice and these cells were cultured on the butterfly wings. The images were taken at 12 h after seeding.


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(F) Graphical representation of cell displacements. The graphs trace the displacements of two representative cells (shown in red and blue) from each group over 12 h. Each dot represents the position of a few select cell nuclei at 3-min intervals relative to their position at time 0. Scale bar = 50 µm.

Figure 3. Gene network analysis of cells grown on M.m. butterfly wings. (A) Gene dendrogram showing the co-expression modules defined by the WGCNA labeled by colors. Module band: Cluster dendrogram groups genes into distinct modules using all samples of M.m. The modules were designated numerically based on size, and the 13 largest modules are labeled adjacent to their respective color band. The grey band (M0) contains probes not assigned to any module. Pre (M.m. vs P.u.t) band: preservation of modules between M.m. and P.u.t. Red corresponds to significant preservation and white to no significant preservation. (B) Matrix with the Module-trait relationships association with time variables on the x-axis. The top number in each cell corresponds to correlation and the bottom number is the p-value. Red is a strong positive correlation, while blue is a strong negative correlation. Corresponding functional annotation is superimposed on the right frame. (C) Biological process diagram throughout cell growing time periods.

Figure 4. Differential expressed gene analysis. (A) Heatmap showing relative expression patterns of DEGs across stage 1 (0.5 h to 3 h), with selected enriched GO terms. (B) Protein-protein interaction (PPI) networks based upon the up-regulated and down-regulated genes enriched by GSEA.

Figure 5. Regulatory network inference for transcriptional factors. (A) The potential transcriptional factors (TFs) for the up-regulated DEGs on M.m. wings. TF in orange color means this TF appears more than one time. Heatmap showing the relative


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expression level of target gene with color band from blue (low expression) to red (high expression). (B) Htt knockdown. The RSC96 cells were transfected with siRNAs against Htt for 72 h. The mRNA and protein levels were assayed by qRT-PCR and Western blot, respectively. (C) Htt knockdown impairs cell radial sorting pattern on the butterfly wings of M.m. (D) Htt knockdown represses lysosome activity. The RSC96 cells were transfected with Htt siRNA-2 for 72 h, and then the cells were subjected for immunofluorescence analysis.

Figure 6. Nerve grafts fabricated with butterfly wings facilitates peripheral nerve regeneration. (A) The diagram for silicon tubes fabricated with butterfly wings. The square by dashed lines indicates the collected section for morphological analysis. (B) The morphological analysis for evaluating sciatic nerve regeneration bridged by silicon tubes fabricated with butterfly wings. Htt was labeled in green, SCs were designated in red using anti-S100 antibody. Scale bar = 25 µm.


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Figure 1 166x140mm (300 x 300 DPI)


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Figure 2 145x231mm (300 x 300 DPI)


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Figure 3 142x205mm (300 x 300 DPI)


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Figure 4 205x201mm (300 x 300 DPI)


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Figure 5 130x160mm (300 x 300 DPI)


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Figure 6 150x140mm (300 x 300 DPI)


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TOC graphic 82x44mm (300 x 300 DPI)


Morphology, Migration, and Transcriptome Analysis of Schwann Cell

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