运动神经元和感觉神经元对周围神经损伤反应的转录重编程的趋同性和差异性。

Jian Yang, Shuqiang Zhang, Xiaodi Li, Zhifeng Chen, Jie Xu, Jing Chen, Ya Tan, Guicai Li, Bin Yu, Xiaosong Gu, Lian Xu
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引用次数: 0

摘要

引言运动神经元在起源和周围环境等方面与感觉神经元不同。了解感觉神经元和运动神经元对周围神经损伤(PNI)和再生的分子反应的异同对于开发中枢神经系统再生的有效药物靶点至关重要。然而,对外周神经损伤后感觉神经元和运动神经元分子变化的全基因组比较仍然有限:本研究旨在调查感觉神经元和运动神经元损伤反应的全基因组趋同性和差异性,以确定神经修复的新型药物靶点:我们分析了原位捕获的感觉神经元(SN)和运动神经元(MN)在PNI、视网膜神经节细胞和脊髓中枢神经系统损伤时的两个大规模RNA-seq数据集。此外,我们还将这些数据与其他相关的单细胞水平数据集进行了整合。我们使用 Bootstrap DESeq2 和 WGCNA 来检测和探索差异表达基因(DEGs)的共表达模块:结果:我们发现SN和MN表现出相似的损伤状态,但MN的反应延迟。我们发现了一个包含 274 个共有 DEGs 的保守再生相关模块(cRAM)。其中,47%的 DEGs 可在单细胞分辨率数据集的支持下在损伤神经元中发生变化。我们还在cRAM中发现了一些研究较少的候选基因,包括与转录、泛素化(Rnf122)和神经元-免疫细胞交叉对话相关的基因。进一步的体外实验证实了 Rnf122 在轴突生长中的新作用。对分歧较大的前10% DEGs的分析表明,外在因素(如免疫微环境)和内在因素(如发育)都是导致损伤后SN和MN表达分歧的原因:这项综合分析揭示了SNs和MNs中趋同和分歧的损伤反应基因,为感觉和运动神经元对轴突损伤和随后的再生做出反应的转录重编程提供了新的见解。它还发现了一些新的再生相关候选基因,这些基因可能有助于轴突再生策略的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convergent and divergent transcriptional reprogramming of motor and sensory neurons underlying response to peripheral nerve injury.

Introduction: Motor neurons differ from sensory neurons in aspects including origins and surrounding environment. Understanding the similarities and differences in molecular response to peripheral nerve injury (PNI) and regeneration between sensory and motor neurons is crucial for developing effective drug targets for CNS regeneration. However, genome-wide comparisons of molecular changes between sensory and motor neurons following PNI remains limited.

Objectives: This study aims to investigate genome-wide convergence and divergence of injury response between sensory and motor neurons to identify novel drug targets for neural repair.

Methods: We analyzed two large-scale RNA-seq datasets of in situ captured sensory neurons (SNs) and motoneurons (MNs) upon PNI, retinal ganglion cells and spinal cord upon CNS injury. Additionally, we integrated these with other related single-cell level datasets. Bootstrap DESeq2 and WGCNA were used to detect and explore co-expression modules of differentially expressed genes (DEGs).

Results: We found that SNs and MNs exhibited similar injury states, but with a delayed response in MNs. We identified a conserved regeneration-associated module (cRAM) with 274 shared DEGs. Of which, 47% of DEGs could be changed in injured neurons supported by single-cell resolution datasets. We also identified some less-studied candidates in cRAM, including genes associated with transcription, ubiquitination (Rnf122), and neuron-immune cells cross-talk. Further in vitro experiments confirmed a novel role of Rnf122 in axon growth. Analysis of the top 10% of DEGs with a large divergence suggested that both extrinsic (e.g., immune microenvironment) and intrinsic factors (e.g., development) contributed to expression divergence between SNs and MNs following injury.

Conclusions: This comprehensive analysis revealed convergent and divergent injury response genes in SNs and MNs, providing new insights into transcriptional reprogramming of sensory and motor neurons responding to axonal injury and subsequent regeneration. It also identified some novel regeneration-associated candidates that may facilitate the development of strategies for axon regeneration.

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