神经细胞能再生的技术，神经干细胞“再生”不是梦

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• 内容导航：
• 1、神经细胞能再生的技术：神经干细胞“再生”不是梦
• 2、神经细胞能再生的技术，神经再生研究新突破

1、神经细胞能再生的技术：神经干细胞“再生”不是梦

神经干细胞的神奇作用

中枢神经系统是由大脑和脊髓组成，是人体神经系统的最主体部分。多年来，人们一直认为成年人大脑里的中枢神经系统缺少再生能力，即神经系统损伤后不能通过神经细胞增殖来替代丢失、缺损的神经元。

但最近科学家研究发现，哺乳动物无论在胚胎发育期还是成年，中枢神经系统都存在可以分化为其他细胞的神经干细胞。科学家相继从哺乳动物及人的中枢神经系统中分离出神经干细胞，并培养成功，然后把神经干细胞移植到病损或者受伤的脑组织中，结果发现可以产生新的神经细胞，并能够分化出神经元、髓鞘细胞等多种类型神经细胞的特殊细胞。

大脑中神经干细胞的发现为神经系统的发育研究和中枢神经系统疾病的治疗提供了新的线索。2011年，美国哈佛大学干细胞研究所科学团队的一项新研究表明，神经细胞移植能够修复受损的大脑回路。

实验中，这些科学家从健康的老鼠胚胎中取出神经元，并将其移植到成年肥胖老鼠体内。最终研究发现，这些神经元在成年老鼠体内存活，并且融入它的大脑回路，存活后又分化成4种神经元，与老鼠体内已有的神经元相整合。上述情况表明，植入的神经元已经修复了成年老鼠的大脑回路。

这项研究成果表明，神经元不仅能够发展成相应的细胞，还能发出和接收受体大脑的信号，这一发现推动了自闭症和帕金森综合征等脑部受损疾病的治疗方案研究。

神经干细胞的来源

成体神经干细胞可以来源于患者本人，提取后经过体外扩增再移植到患者脑组织。但由于从成人神经系统中，活体提取成体神经干细胞非常困难，且手术风险高，目前成体神经干细胞的动物试验和临床应用均在利用流产胎儿的胎脑提取成体神经干细胞。在胎脑的发育过程中，越早期胎脑的成体神经干细胞比率越高。因此，直接分离自然流产的胎儿新鲜脑组织，可更容易地培养出细胞在体外增殖形成的神经球。

另外，科学家发现大脑中的海马区是分离并培养神经干细胞最有效的区域。海马区是大脑边缘系统与人体的学习、记忆、情绪、行为、内脏机能活动等方面均有密切联系的组成部分，从胎儿的海马区分离培养的神经干细胞，在神经系统受到各种伤害时，这种细胞能被诱导分化为某种新的神经元来替代损伤的神经细胞。比如，这类神经干细胞可分化为多巴胺神经元，改善帕金森综合征病人的临床症状。

细胞移植技术的发展

同时，科学家在分离培养神经干细胞的基础上又引入了基因转染技术。基因转染技术是指将特定的遗传信息传递到神经干细胞中，也就是说，利用基因告诉神经干细胞应该分化成什么样的神经元细胞，目的是使神经干细胞在体内能有更好的存活、迁移和分化。

美国加州大学洛杉矶分校的研究人员也同样做了一个实验，他们利用基因工程技术，给帕金森综合征大鼠模型脑内植入并增加了一个酪氨酸羟化酶基因的神经细胞（这种神经细胞是由酪氨酸羟化酶基因构成的，也就是说神经干细胞是由此种基因转染成的）。酪氨酸羟化酶基因是多巴胺合成所必需的酶，由于增加了这种激活的基因，神经干细胞内产生的多巴胺明显增多。试验证明，接受这些基因增强细胞的大鼠的神经系统受损症状改善了70%。

胎儿神经细胞的未来应用

鉴于这次试验的成功，科学家们对胎儿神经细胞未来的应用信心满满，他们认为神经干细胞作为基因治疗的载体细胞具有特殊的优点：它们可以在体外大量培养，可以与受体的脑组织形成结构和功能的整合；它们存活时间长，易于进行转基因操作；如取材于自体，还具有免疫耐受性及安全性等优点。

可以确定的是，胎儿神经细胞移植正逐步成为帕金森综合征的主要治疗方法，也能够为其它人类中枢神经系统疾病的基因治疗提供有力的武器。比如阿尔茨海默氏症、亨廷顿氏病、进行性核上麻痹，以及肌萎缩侧索硬化症，这些顽固的神经系统疾病都有可能通过帕金森综合征的治疗经验得到启发，发现传统治疗方法的突破点。

因此，科学界和医学界认为神经干细胞移植具有很大的潜能，它可以为神经外科医师提供全新的治疗模式。然而，如何获取大量可以用于移植的神经干细胞，如何保障神经干细胞移植后的安全性，如何解决异体移植免疫排斥反应，如何解决使用神经干细胞的伦理和法律等问题，都需要神经生物学家和神经外科医师的多方协作。

希望在不久以后的将来，细胞移植治疗能够成为一种安全有效的方式，引入到临床治疗方案中造福人类。

2、神经细胞能再生的技术，神经再生研究新突破

来自北京航空航天大学、首都师范大学、上海交通大学等机构的研究人员展开合作，在脊髓损伤再生研究中取得突破性的成果。两任职于北京航空航天大学及首都师范大学的李晓光（Xiaoguang Li）研究员，同济大学医学院和加州大学洛杉矶分校的孙毅（Yi E. Sun）教授，以及李晓光课题组的杨朝阳（Zhaoyang Yang）博士是这篇论文的共同通讯作者。

Transcriptome analyses reveal molecular mechanisms underlying functional recovery after spinal cord injury.October 12, 2015, doi: 10.1073/pnas.1510176112 PNAS October 12, 2015

由于恶劣的中枢神经系统(CNS)损伤环境以及CNS神经元较弱的内在再生能力， CNS中的轴突再生极具挑战性，因此脊髓损伤(SCI)被认为无法治愈。

在这篇文章中研究人员发现，载有神经营养因子-3(NT3)的壳聚糖可 提供良好的环境，促进大鼠神经生长、新神经发生及完全切断的脊髓恢复功能。为了了解其分子机制，研究人员在脊髓损伤后90天时间内对损伤位点的脊髓段，以 及损伤吻侧和尾侧区域进行了一系列全面的转录组分析。利用加权基因共表达网络分析(Weighted gene co-expression network analysis, WGCNA)，他们确立了在脊髓损伤后不同时间响应各种病理事件的基因模块/程序。客观测量基因模块表达还揭示出新神经发生和血管发生增加，炎症反应减少 是NT3-chitosan影响再生的关键。

NT3-chitosan elicits robust endogenous neurogenesis to enable functional recovery after spinal cord injury.October 12, 2015, doi: 10.1073/pnas.1510194112 PNAS October 12, 2015

成年哺乳动物中枢神经系统中的神经干细胞(NSCs)通过适当激活、分化和成熟，建立起新神经网络，整合到受损神经回路中修复功能，是神经再生的关键。然而，中枢神经系统损伤微环境往往是抑制及炎症性的，限制了活化的神经干细胞分化为神经元，形成新神经回路的能力。

在这篇文章中，研究人员报告称当将偶联NT3的壳聚糖材料插入到完全切断和切除的大鼠胸部脊髓5-mm缺口中时，可引起受损脊髓中內源NSCs有力 地活化。通过缓慢释放NT3，这一生物材料吸引NSCs迁移到了损伤区域，分化为神经元，形成了功能性神经网络，其与切断的上行和下行轴突相互连接，导致 了感觉与运动行为恢复。

这项研究提出了，促进内源性神经发生是脊髓损伤一种新治疗策略。

Proc Natl Acad Sci U S A. 2015 Oct 27; 112(43): 13360–13365.Published alt="神经细胞能再生的技术，神经干细胞“再生”不是梦" src="http://p3.toutiaoimg.com/large/7fa00096599b75fb8b4" />

Fig. S1.NT3-chitosan promotes nerve regeneration and motor functional recovery after complete SCI in rats. (A) Anatomic images (dorsal view) of regenerating nerve tissue (black arrows) in NT3-chitosan tube (NT3) or scar tissue (black arrows) in LC samples at ...

Animals were euthanized at 1, 3, 10, 20, 30, 60, and 90 d postsurgery, and 5-mm segments of the spinal cord at the lesion site, as well as immediately caudal or rostral to the lesion segment, were collected and labeled with “R” for rostral, “C” for caudal, and “M” for lesion site (Fig. 1A). Spinal cord segments from four animals together were needed to provide sufficient RNA for microarray analyses as a single sample; thus, a total of 12 animals were euthanized to provide three samples at each time point. Quality mRNA was extracted, reverse-transcribed, and subjected to Affymetrix GeneChip (Rat Genome 230) 2.0 array analysis. Three uninjured spinal cord control samples corresponding to the lesion segment (5 mm) at T7-8 from 12 animals were included. Five reference RNA samples included in the microarray kit were used to control for a potential microarray batch effect.

Fig. 1.Sample clustering revealed temporal and spatial changes following SCI with or without NT3-chitosan treatment. (A) A schema describing anatomic positions of spinal cord segments for the LC and NT3 samples used for transcriptome analyses. Empty chitosan ...

Region-Specific Changes Following SCI Revealed by Sample Clustering.

Unbiased hierarchical clustering of the complete dataset (167 samples from 668 animals) based alt="神经细胞能再生的技术，神经干细胞“再生”不是梦" src="http://p3.toutiaoimg.com/large/7fc0009693c30dd1e4e" />

Fig. 2.WGCNA of LC samples in R and C regions identified gene modules underlying pathological events at different time points post-SCI. (A) Hierarchical cluster dendrogram of LC samples in R and C regions showing coexpression modules identified using WGCNA alt="神经细胞能再生的技术，神经干细胞“再生”不是梦" src="http://p3.toutiaoimg.com/large/7fc00096950a450a34b" />

Fig. 3.WGCNA of uninjured and all M region injury samples uncovered molecular mechanisms underlying the proregeneration function of NT3-chitosan. (A) Hierarchical cluster dendrogram using WGCNA analyzing uninjured samples (N) and samples in the M regions. A ...

GO and hub gene network analyses, shown in Fig. S2 and Dataset S2, indicated that Cm1 and Cm2 were related to neurogenesis; Cm4 was related to muscle contraction; Cm3 was related to pain and temperature sensory processing; Cm5 was related to angiogenesis, response to oxygen levels, and nervous system development; Cm6 was related to immune response; and Cm7 was related to response to wounding, stress, and inflammation. The averaged gene expression of each module further indicated that NT3-chitosan enhanced vascularization (blood supply), which was required for proper tissue repair. NT3-chitosan also clearly suppressed inflammatory responses (Cm6 and Cm7), which were classically considered key to attenuating secondary lesions after SCI. Therefore, the antiinflammatory effect elicited by NT3-chitosan also could contribute to the better regeneration outcome.

Fig. S2.Hub gene networks of seven modules significantly influenced by NT3-chitosan in M region injury samples.

One exciting finding was the enhanced expression of modules Cm1 and Cm2 (related to neurogenesis and neurotransmission) in response to NT3-chitosan. Moreover, Cm3 and Cm5 also contained many neurogenesis genes, including Dlx5, Isl2, Trpv1, Chrna3, Ntrk1, Ngfr, Agrn, GDNF receptors, Nrep, Smo, and Gata2. Although NT3-chitosan enhanced gene expression in Cm1 and Cm 2 and in Cm3 and Cm5, these four modules behaved differently. Cm1/2 represented genes related to neuronal differentiation, which were expressed at high levels in uninjured/normal spinal cord, whereas Cm3/5 represented neuronal differentiation genes, which were not highly expressed in normal adult spinal cord but were elicited de novo by NT3-chitosan. Interestingly, a muscle contraction module (Cm4) also was heavily induced by NT3-chitosan in the M region. This finding was unexpected and merited further investigation to determine the contribution of this module to better functional recovery after SCI. Expression levels of candidate genes from Cm1 (Dcx and Snap25), Cm2 (Ntrk3), and Cm5 (Dlx5) across all samples (all regions and all times) demonstrated robust regulation of these genes by NT3-chitosan in the M region compared with R and C regions (Fig. 3D). Expression plots for additional genes involved in NSC differentiation are shown in Fig. S3.

Fig. S3.Averaged expression of some representative genes related to neuronal and oligodendroglial differentiation across all samples. Note that NT3-chitosan promoted not alt="神经细胞能再生的技术，神经干细胞“再生”不是梦" src="http://p3.toutiaoimg.com/large/7fb00096af8b815cd26" />

Fig. 4.NT3 chitosan creates a reduced inflammatory environment, which is beneficial for functional recovery post-SCI. (A and B) CD45 staining to label inflammatory leukocytes in injured rat spinal cord sections for both NT3 and LC groups and quantitative analyses ...

Moreover, we found that when RAW cells were cocultured with rat spinal cord slices, the aforementioned inflammatory cytokine secretion was increased as well, which could be suppressed by NT3-chisosan, and that NT3 antibody could block the effect of NT3-chitosan. Of note, we observed the same phenomenon when measuring mouse-specific cytokines (generated from RAW cells) or rat-specific cytokines (generated from rat spinal cord slices) (Fig. 4 C and D and Fig. S4).

Fig. S4.(A and B) ELISA demonstrating that NT3-chitosan suppressed the generation and/or release of mouse inflammatory cytokine from mouse RAW264.7 cells cocultured with or without rat spinal cord slices (A) and rat inflammatory cytokine from spinal cord slices ...

To obtain evidence to support the notion that antiinflammation was beneficial for functional recovery following SCI, we compared functional recovery using the Basso Mouse Scale (BMS) scoring system in a double-blinded manner on spinal cord crush-injured wild type and immunocompromised SCID mice. The SCID mice clearly demonstrated better functional recovery post-SCI (Fig. 4E). Finally, staining of injured spinal cords at the lesion site in the LC and NT3-chitosan groups revealed robust neural filament (NF) staining only in the NT3-chitosan–treated samples. Numerous NF cells were present in the NT3-chitosan tube, suggesting the addition of new neuronal components in the biomaterial, consistent with the transcriptome analyses. More detailed analyses were described in same issue (15), addressing the role of NT3-chitosan in the promotion of new neurogenesis, formation of a nascent local neural network, and subsequent connection to ascending and descending nerve fibers, leading to functional recovery.

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DISCUSSION

In this study, we used unbiased objective analyses of the transcriptomes of injured spinal cord segments to reveal important underlying molecular programs that were altered in a temporally and spatially specific manner after complete SCI. This analysis identified quantifiable changes in various gene programs representing distinct biological/pathological processes postinjury, which could be regulated individually or in combination by various interventions. Specifically, we revealed that NT3-chitosan enhanced vascularization and suppressed inflammatory immune responses, providing an optimal environment for endogenous NSCs (likely including CD133 ependymal cells and their downstream lineage cells) to generate newly born neurons, forming a nascent neural synaptic network, which served as an information relay station to reconnect ascending and descending sensory and motor information, achieving functional recovery (16).

This mechanistic insight was further substantiated by the observation that NT3-chitosan elicited strong antiinflammatory effects in vitro and in vivo using classical biochemical measures and immunohistochemistry analyses. Moreover, these analyses revealed that a failure in generating new neurons from endogenous NSCs, due to the harsh inflammatory environment, could be a major obstacle to proper regeneration and functional recovery after SCI (15). One underlying premise for WGCNA is that genes functioning together are regulated together. This premise likely explains why WGCNA is a very powerful analysis for revealing molecular gene networks underlying biological functions (12–14). In addition to gene modules, the hub gene network analyses also revealed potential key regulatory factors (hub genes, with the greatest module membership and connectivity), which potentially could serve as therapeutic targets to alter specific gene programs following SCI. Once expression of gene modules can be used to quantitatively represent the various pathological events, these sets of new criteria can be used in outcome measurement of various potential therapeutic interventions. In addition, these potential biomarkers can be used to evaluate the severity of SCI. With such useful tools, rational designs of combinatorial therapies, for example, those that aimed at promoting neurogenesis and those aimed at suppressing inflammatory immune responses, could be applied and evaluated. In addition, if correlations can be established between the transcriptome of the injured spinal cord and that of the peripheral blood, new sets of biomarkers for molecular diagnostics, as well as outcome measurements of SCI and potential treatment, can be established, which will greatly benefit future SCI research and therapeutic development.

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MATERIALS AND METHODS

Animal Surgery.

All animal procedures were carried out in accordance with the guidelines from the Capital Medical University Institutional Animal Care and Use Committee. Wistar rats weighing 200–220 g were used for the rat complete transection SCI study. In addition, 6- to 8-wk-old C57 and SCID male mice were subjected to spinal cord crush injury. Details are provided in SI Materials and Methods.

Behavioral Analyses.

Before the operation and at 1 d postsurgery and each week thereafter, observers who were blinded to the treatment methods and groups applied Basso–Beattie–Bresnahan (BBB) scoring in an open field to evaluate hindlimb locomotor function (10, 17). BMS was used for mouse analyses.

Microarray Analyses.

These analyses are described in detail in SI Materials and Methods.

WGCNA.

Both MN datasets (42 samples, including M region injury data and normal/uninjured controls) and RCN-LC datasets (45 samples, including R and C region lesion control/LC samples together with normal/uninjured controls) were independently constructed for WGCNA (18, 19). Details are provided in SI Materials and Methods.

Quantitative PCR and ELISA Analyses.

These analyses are described in SI Materials and Methods.

RAW Cell Culture and Coculture with Rat Spinal Cord Slices.

Mouse microphage RAW264.7 cells were used to evaluate the antiinflammatory effects of NT3-chitosan. Details are provided in SI Materials and Methods.

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SI MATERIALS AND METHODS

Animal Surgery.

Wistar rats weighing 200–220 g were anesthetized by i.p. injections of 6% chloral hydrate (0.6 mL/kg body weight). To prepare the rat model of thoracic spinal cord transection, laminectomy was done at T7-8 under an operating microscope, followed by transection to remove a 5-mm-long spinal cord segment. The blade was repeatedly scraped along the ventral surface of the spinal canal, and any residual fibers at the lesion site were removed by aspiration. The rats were divided into four groups: uninjured, LC, ET, and NT3-chitosan. The groups and time points for sample collection are described in Results.

For the mouse spinal cord crush injury, 6- to 8-wk-old C57 black 6 and SCID male mice were anesthetized by i.p. injections of sodium pentobarbital (10 mg/mL; 70 mg/kg). The skin and muscle were opened, and the T9 segment vertebral plate was removed. A retrofit artery clamp with a constant front-end pressure of 60 g was used to crush the T9 segment persistently for 3 s. In the control group, only the T9 segment vertebral plate was removed, with no crush injury performed.

Behavioral Analyses.

Before the operation, and at 1 d and each week after the operation, observers who were blind to the treatment methods and groupings performed BBB scoring in an open field to evaluate hindlimb locomotor function restoration after SCI (10, 17). Eight animals per group were used. At 52 wk after the operation, four of these eight rats were selected at random from each group for re-resection at the original lesion site. BBB scoring was performed during the subsequent 5 wk. Repeated-measures ANOVA and Bonferroni post hoc analysis were used to identify statistically significant differences among the groups (10). For SCID mice, SCI experimental crush models were used, and BMS was scored in a double-blinded manner.

Microarray Analyses.

Samples for microarray analysis were homogenized in 1 mL of TRIzol (Invitrogen), and RNA was extracted using RNeasy Miniprep columns (Qiagen) according to the manufacturer’s instructions. An average of 40–60 μg of RNA was obtained from 80–120 mg of tissue pooled from four animals for microarray analysis, which was performed using an Affymetrix GeneChip Rat Genome 230 2.0 array for each time point. All assays were performed in at least three biologically independent pooled samples. An aliquot of 1 μg of total RNA was used to synthesize double-stranded cDNA, and biotin-tagged cRNA was amplified using a MessageAmp II aRNA Amplification Kit (Ambion). Microarray analysis was performed on an Affymetrix Gene Chip platform by CapitalBio. The resulting biotagged cRNA was fragmented and hybridized to the Affymetrix GeneChip Rat Genome 230 2.0 array containing 30,000 rat transcripts. Hybridization was performed at 45 °C with rotation for 16 h in an Affymetrix GeneChip Hybridization Oven 640. The GeneChip arrays were washed and then stained (streptavidin-phycoerythrin) on an Affymetrix GeneChip Fluidics Station 450, followed by scanning on an Affymetrix GeneChip Scanner 3000. Data were extracted from scanned images using Affymetrix GeneChip Operating Software. The raw data were normalized using a multiarray method with Affymetrix Expression Console Software.

Because this assay was performed in different batches, to evaluate batch-to-batch variations, we purchased Universal Rat Reference RNA samples from Stratagene (Agilent; catalog no. 740200). In the chip assay for one batch, we used the reference RNA sample to make a chip in parallel, obtaining chip data for five reference RNA samples all together. The five chips were analyzed and found to have a signal correlation efficiency of 0.9936 ± 0.0043, indicating only slight batch-to-batch variations.

WGCNA.

Both MN datasets (42 samples, including M region injury data and normal/uninjured controls) and RCN-LC datasets (45 samples, including R and C region lesion control/LC samples together with normal/uninjured controls) were constructed independently using the following method. A signed weighted correlation network was constructed by first creating a matrix of pairwise correlations between all pairs of genes with annotation. The resulting Pearson correlation matrix was transformed into a matrix of connection strengths (e.g., an adjacency matrix) using a power of 12 (12). Then the topological overlap was calculated to measure network interconnectedness (18).

For each dataset, we used average linkage hierarchical clustering to group genes on the basis of the topological overlap dissimilarity measure (1-topological overlap) of their network connection strengths. Using a dynamic tree-cutting algorithm (13) and merging threshold function at 0.25, we identified 19 modules in the MN dataset and 10 modules in the RCN-LC dataset. The freely available statistical analysis software (WGCNA R package) and R tutorials for constructing a weighted gene coexpression network have been described previously (13). To better describe molecular events after SCI, for the RCN-LC dataset, instead of using all 18,000 annotated genes, we used Limma, a R/Bioconductor software package that applies linear models and empirical Bayes methods to assess differential expression, to identify the top 10,000 transcripts, 7,500 of which were annotated genes. The expression of these genes in LC samples changed most significantly with time in the R and C regions.

Identification and Visualization of Hub Genes.

We summarized the expression profile of each module by the corresponding module eigengene (i.e., the first principal component obtained by singular value decomposition). We then defined the module membership for each gene with respect to each module as the Pearson correlation between the expression level of the gene and the module eigengene, also known as module eigengene-based connectivity (kME). This measure was naturally scaled to lie in the interval [−1, 1]. Genes with the greatest module membership values are referred to as intramodular hub genes. We used Cytoscape 3.0.0 to visualize the top 250 gene connections (based on topological overlap). Intramodular hub genes (i.e., genes with the highest kME values) usually are centrally located inside the module (19).

GO Analysis.

Functional annotation was performed with the Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resource (20). Genes with kME >0.65 within each module were subjected to this analysis. GO terms with a false discovery rate <0.0001 are shown in Datasets S1 and S2.

Immunohistochemistry.

Mouse monoclonal anti-mouse NF (diluted 1:50; Zymed), labeling neurons, polyclonal rabbit anti-GFAP (diluted 1:300; Zymed), labeling astrocytes, and rabbit anti-CD45 (diluted 1:200; Chemicon), labeling leukocytes, were used in this study. At each time point after the operation, four to five rats were selected at random from each group and euthanized by an overdose of anesthesia. After transcardial perfusion with 44% (wt/vol) paraformaldehyde with 0.1 M phosphate buffer used as the solvent, spinal cords were excised using a dissecting microscope and then fixed at 4 °C in fixing solution for 6–8 h. The spinal cord tissue including the lesion area was embedded in OCT compound embedding medium for frozen tissue specimens (Sakura Finetechnical) to ensure an optimal cutting temperature and then sliced longitudinally or transversely with a cryostat microtome to produce 8-μm sections. All sections were subjected to immunohistochemical staining.

qPCR and ELISA Analyses.

Total RNA from RAW264.7 cells and spinal cord slices cultured for 1 d and 3 d were isolated using the Qiagen RNeasy Mini Kit. Single-stranded cDNA was prepared from total RNA using random primers under standard conditions with MultiScribe Reverse Transcriptase (Applied Biosystems). The cDNA from each sample was diluted and used for qPCR analysis based on Taqman assays (Invitrogen), quantifying IL-1α, IL-1β, NF- kB, IL-6, and TGF-β. Beta-actin served as an internal positive control. qPCR amplifications were performed in duplicate using the Chromo4 Real-Time PCR Detection System (Bio-Rad) at 94 °C for 30 s, followed by 35 cycles of 94 °C for 5 s and 57 °C for 30 s. All experiments included negative controls of no cDNA in the reaction mixture. Corresponding ELISA analyses (Fig. S4) were performed using kits from Dingguo Biotech (catalog no. CSB-E04622r).

RAW Cell Culture and Coculture with Rat Hippocampal Slices.

Mouse microphage RAW264.7 cells were used to evaluate the antiinflammatory effect of NT3-chitosan. Chitosan particles loaded with NT3 were applied to RAW cell cultures as described previously (21). Cytokine production was measured by either qPCR or ELISA. For RAW cell and rat hippocampal slice cocultures, four to five 350-μm-thick slices (transverse sections) from adult rat spinal cord were cocultured with RAW cells in a 35-mm dish for cytokine measurement in either RAW cells or spinal cord slices.

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SUPPLEMENTARY MATERIAL

Supplementary File

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Supplementary File

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ACKNOWLEDGMENTS

This work was supported by the State Key Program of the National Natural Science Foundation of China (Grants 31130022, 31271037, 31320103903, 81330030, 9139309, 31271371, and 81350110525), the National Science and Technology Pillar Program of China (Grant 2012BAI17B04), the International Cooperation in Science and Technology Project of the Ministry of Science and Technology of China (Grants 2014DFA30640 and 2011CB965100), the National 863 Project (Grant 2012AA020506), the National Ministry of Education Special Fund for Excellent Doctoral Dissertation (Grant 201356), the Special Fund for Excellent Doctoral Dissertation of Beijing (Grant 20111000601), the Key Project of the Department of Science and Technology of Beijing (Grant D090800046609004), and a YunNan Innovation Talents of Science and Technology Grant 2012HA013 (to Y.E.S.), as well as grants from the National Institutes of Health (P01 GM081621-01A1) and the Transcriptome and Epigenetics Core of Center for Study of Opioid Receptors and Drugs of Abuse (NIH-P50DA005010) and the Intellectual and Developmental Disabilities Research Center (NIH-P30HD004612) at University of California Los Angeles.

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FOOTNOTES

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: The data reported in this paper have been deposited in the Gene Expression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE69334).

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1510176112/-/DCSupplemental.

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REFERENCES

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