Background & Aims
While the initiation and maintenance of neuropathic pain have been extensively studied, the process of active pain resolution has barely been investigated so far. Identifying potential mechanisms that actively trigger the resolution of chronic neuropathic pain can shape a basis for treating patients with non-resolved pain. The rat model for neuropathic pain using chronic constriction injury (CCI) of the sciatic nerve causes pronounced thermal and mechanical hypersensitivity after 1 week, which gradually improves after 3-6 weeks – the phase of natural pain resolution. In this study, we aimed to identify genes that can trigger the resolution of pain after nerve injury employing Spatial Transcriptomics (ST) – an RNA-seq based technique that allows the spatiotemporal analysis of the nerve injury-induced pain resolution transcriptome.
Methods
Eight male Wistar rats received CCI surgery. Longitudinal 10 µm-thick sections of fresh-frozen nerves (after 1 and 4.5 wks) were placed on capture areas of slides for ST analysis (Visum 10x Genomics platform). Immunofluorescence staining and imaging were performed to differentiate between endo- and epineurium later-on. cDNA synthesis and library construction were carried out according to the manufacturer’s instructions. The resulting Illumina dual indexed sequencing data was subsequently preprocessed by the 10x SpaceRanger pipeline, employing the aligned images/barcodes, the rat genome mRatBN7.2 [1], and the EnsEMBL 109 transcriptome annotation as references. All 11 ST experiments from the different time points and rat pools were processed separately, before normalizing and aggregating them into one spatiotemporal dataset which was analyzed using Loupe Browser 7. The DAVID tool was used for the functional annotation of genes by the gene ontology (GO) classification [2, 3].
Results
Our experiment yielded 25,852 tissue-covered spots from the 11 areas (naive nerve, distal and proximal from injury) which were clustered by gene expression similarities into 20 groups. We were able to assign clusters to endo-, peri-, and epineurial tissue based on GO-terms and verified these with the corresponding images. Clusters that matched in their spatiotemporal identity were merged, resulting in 9 tissue- and time-specific clusters. A pairwise comparison of distal endoneurial clusters after 1 vs. 4.5 wks revealed 197 significantly up- and 68 downregulated genes (p < 0.001), including some long non-coding RNAs, which were unchanged (p > 0.05) at 1 wk compared to the naive nerve. These genes could be subsumed by the GO-terms ‘myelination’, ‘axon’, or ‘innate immunity’. Regulated genes in the epineurial clusters were classified by more general GO-terms such as ‘transmembrane’ or ‘cell cycle’ for 54 up- and ‘neutrophil chemotaxis’ or ‘extracellular space’ for 140 downregulated genes.
Conclusions
Our study aims for investigating the gene expression profiles of spatially segregated cells in injured sciatic nerves during pain resolution. Our first results demonstrate ST as a versatile and convenient tool for the unbiased analysis of nerve tissue, allowing the identification of different cell populations based on clustering common transcriptome patterns and examining visually fluorescent markers in the tissue section. Although the spatial resolution of ST spots per design did not isolate ‘pure’ macrophage or endoneurial capillary spots, a substantial number of protein-coding and long non-coding RNAs were detected to be upregulated specifically during the phase of natural pain resolution. To decipher, which of those genes might actually drive pain resolution, an in-depth analysis is required, taking into account complementary processes, such as axonal regrowth and remyelination.
References
1.de Jong, T.V., et al., mRatBN7.2: familiar and unfamiliar features of a new rat genome reference assembly. Physiol Genomics, 2022. 54(7): p. 251-260.
2.Huang da, W., B.T. Sherman, and R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009. 4(1): p. 44-57.
3.Sherman, B.T., et al., DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res, 2022. 50(W1): p. W216-w221.