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<p>Background. Spinal cord injury (SCI) is a debilitating neurological disorder characterized by complex pathological processes involving dynamic responses of multiple cell types and intricate regulatory networks. Although single-cell RNA sequencing (scRNA-seq) has been employed to dissect cellular heterogeneity in SCI, the activity and regulatory functions of microRNAs (miRNAs) at single-cell resolution remain largely unexplored. Methods. This study utilized the GSE189070 dataset, integrating single-cell transcriptomic data from mouse spinal cord tissues at eight time points: uninjured control and 0.5, 1, 3, 7, 14, 60, and 90 days post-injury. Following quality control, batch correction, and cell-type annotation, miRNA activities across 12 major cell types were computationally inferred using a motif enrichment-based approach. Temporal clustering of miRNA activity was performed with Mfuzz, and subsequent analyses included target gene prediction, functional enrichment, and network construction. Inferred miRNA activity patterns were validated using an independent bulk miRNA sequencing dataset (GSE90452). Key findings were experimentally verified in BV-2 microglial cells and C8-D1A astrocytes using miRNA inhibitors and mimics. Results. We successfully constructed a single-cell transcriptomic atlas and a dynamic computationally inferred miRNA activity landscape during SCI progression. Independent dataset validation confirmed that inferred miRNA activity changes (e.g., mmu-miR-488-3p, mmu-miR-132-3p) were consistent with actual miRNA expression alterations. Our analysis revealed that microglia and macrophages exhibited dynamic miRNA activity patterns closely associated with inflammatory pathways, including TNFA_SIGNALING_VIA_NFKB and TOLL-LIKE RECEPTOR signaling. Cross-cell-type comparison identified 38 common differentially active miRNAs shared between microglia and macrophages, with network analysis revealing coordinated regulation of key inflammatory genes (e.g., Lif, Csf1, Il18rap). In astrocytes, specific miRNAs (e.g., miR-7a-5p, miR-124-3p) were found to regulate apoptotic pathways by targeting Casp3 and Bcl2 family genes. Experimental validation confirmed that miR-130a-3p promotes microglial inflammation, while miR-7a-5p inhibits astrocyte apoptosis under oxidative stress. Conclusion. This study presents a computationally inferred, experimentally validated single-cell-resolution map of miRNA activity dynamics during SCI, revealing potential regulatory networks in key cell types. The concordance between computational inference and independent experimental data supports the biological plausibility of our findings and provides a foundation for further therapeutic exploration.</p>

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Construction of a Computationally Inferred Single-Cell miRNA Activity Atlas and Analysis of Regulatory Networks in Spinal Cord Injury

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月25日

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  • Changli Xu,
  • Bingxuan Wang,
  • Zhengqiang Li,
  • Suchi Qiao,
  • Jianli Bu

摘要

Background. Spinal cord injury (SCI) is a debilitating neurological disorder characterized by complex pathological processes involving dynamic responses of multiple cell types and intricate regulatory networks. Although single-cell RNA sequencing (scRNA-seq) has been employed to dissect cellular heterogeneity in SCI, the activity and regulatory functions of microRNAs (miRNAs) at single-cell resolution remain largely unexplored. Methods. This study utilized the GSE189070 dataset, integrating single-cell transcriptomic data from mouse spinal cord tissues at eight time points: uninjured control and 0.5, 1, 3, 7, 14, 60, and 90 days post-injury. Following quality control, batch correction, and cell-type annotation, miRNA activities across 12 major cell types were computationally inferred using a motif enrichment-based approach. Temporal clustering of miRNA activity was performed with Mfuzz, and subsequent analyses included target gene prediction, functional enrichment, and network construction. Inferred miRNA activity patterns were validated using an independent bulk miRNA sequencing dataset (GSE90452). Key findings were experimentally verified in BV-2 microglial cells and C8-D1A astrocytes using miRNA inhibitors and mimics. Results. We successfully constructed a single-cell transcriptomic atlas and a dynamic computationally inferred miRNA activity landscape during SCI progression. Independent dataset validation confirmed that inferred miRNA activity changes (e.g., mmu-miR-488-3p, mmu-miR-132-3p) were consistent with actual miRNA expression alterations. Our analysis revealed that microglia and macrophages exhibited dynamic miRNA activity patterns closely associated with inflammatory pathways, including TNFA_SIGNALING_VIA_NFKB and TOLL-LIKE RECEPTOR signaling. Cross-cell-type comparison identified 38 common differentially active miRNAs shared between microglia and macrophages, with network analysis revealing coordinated regulation of key inflammatory genes (e.g., Lif, Csf1, Il18rap). In astrocytes, specific miRNAs (e.g., miR-7a-5p, miR-124-3p) were found to regulate apoptotic pathways by targeting Casp3 and Bcl2 family genes. Experimental validation confirmed that miR-130a-3p promotes microglial inflammation, while miR-7a-5p inhibits astrocyte apoptosis under oxidative stress. Conclusion. This study presents a computationally inferred, experimentally validated single-cell-resolution map of miRNA activity dynamics during SCI, revealing potential regulatory networks in key cell types. The concordance between computational inference and independent experimental data supports the biological plausibility of our findings and provides a foundation for further therapeutic exploration.