The Development of Mechanical Allodynia in Diabetic Rats Revealed by Single-Cell RNA-Seq

Abstract

Mechanical allodynia (MA) is the main reason that patients with diabetic peripheral neuropathy (DPN) seek medical advice. It severely debilitates the quality of life. Investigating hyperglycemia-induced changes in neural transcription could provide fundamental insights into the complex pathogenesis of painful DPN (PDPN). Gene expression profiles of physiological dorsal root ganglia (DRG) have been studied. However, the transcriptomic changes in DRG neurons in PDPN remain largely unexplored. In this study, by single-cell RNA sequencing on dissociated rat DRG, we identified five physiological neuron types and a novel neuron type MAAC (Fxyd7 ⁺ /Atp1b1 ⁺) in PDPN. The novel neuron type originated from peptidergic neuron cluster and was characterized by highly expressing genes related to neurofilament and cytoskeleton. Based on the inferred gene regulatory networks, we found that activated transcription factors Hobx7 and Larp1 in MAAC could enhance Atp1b1 expression. Moreover, we constructed the cellular communication network of MAAC and revealed its receptor-ligand pairs for transmitting signals with other cells. Our molecular investigation at single-cell resolution advances the understanding of the dynamic peripheral neuron changes and underlying molecular mechanisms during the development of PDPN.

Keywords: mechanical allodynia; neuropathic pain; painful diabetic peripheral neuropathy; single-cell RNA sequencing; somatosensory neurons.

Figure 1

The heterogeneity of dorsal root ganglia (DRG) cells in the painful diabetic peripheral neuropathy (PDPN) model. (A) Workflow of the pain threshold evaluation, sample preparation, sequencing, and bioinformatic analysis. The red region in the center of the rats' paws was stimulated by von Frey filaments. Sensation in this area is within the innervation range of the tibial nerve, originating from L5 DRG in rat. (B) t-distributed scholastic neighbor embedding (t-SNE) plot of single cells profiled in the presenting work colored by cell types. Each colored dot represents a cell. (C) Feature heatmap shows the marker genes in each cell type. The color represents the gene expression level after batch effect correction and normalization. (D) t-SNE plot shows the unsupervised clustering DRG neurons. Dots, individual cells; colors, neuron clusters. (E) Dot plot shows the differentially expressed genes (DEGs) of each DRG neuron cluster. The size of the dot means the percentage of cells expressing the gene, and the color indicates the average expression level.

Figure 2

Novel neuron cluster mechanical allodynia-associated cluster (MAAC) appeared in the development of PDPN. (A) t-SNE plot shows somatosensory neuron clusters in control versus in diabetic rats without or with mechanical allodynia (MA). The dots in the control group are grayed out when they are compared with the dots in the other two groups. Dots, individual cells; colors, neuron clusters. (B) Summary of neuron type classification in this work and previous study. (C) Heatmap shows the DEGs of MAAC. The genes with the largest fold difference are marked. Color, expression level. (D) Bar plot shows gene ontology (GO) terms of biological processes [false discovery rate (FDR) <0.3] enriched for the DEGs of MAAC.

Figure 3

The origin and transition of MAAC. (A) Heatmap shows the Pearson correlation of each neuron cluster based on their genes expression files. (B) Pseudo-time trajectories show the fate of MAAC originated from peptidergic nociceptors (PEP). Dot, cells; colors, neuron clusters or pseudotime. (C) Heatmaps show the DEGs clustered based on their dynamic expression characteristic, which were shown in pseudo-time from PEP to MAAC.

Figure 4

Specifically expressed transcription factors and regulatory network of MAAC. (A) The binary heatmap shows the activity of inferred transcription factors in different neuron clusters. (B) t-SNE plots show the activities cells distribution of two specific expressed regulons of MAAC. Dots, individual cells; colors, activated cells. (C) Gene regulatory networks of Hobx7 and Larp1 inferred by single-cell regulatory network inference and clustering (SCENIC). Colors indicated the log2FC of DEGs of MAAC.

Figure 5

The intercellular communication of MAAC. (A) Intercellular communication network reflects the number of interactions between clusters. Nodes, neuronal clusters; node size, cell counts; edge width, number of interactions. (B) Intercellular communication network shows the number of interactions between MAAC and other neuron clusters. Nodes, neuronal clusters; node size, cell counts; edge width, number of interactions. (C) Dot plot shows the incoming and outgoing strength of each cell type. The outgoing /incoming interaction strength is defined by the comprehensive communication probability between the signal sending /target cells and all cell types. (D) Dot plot shows the communication probabilities of ligand-receptor pairs when MAAC are sender cells. Only the ligand-receptor pairs with significant changes (p <0.05) are shown in the picture. Commun. Prob, communication probability. The communication probability here equals to the interaction strength and is not exactly a probability. Dot color means communication probabilities and dot size represents computed p-values. (E) Dot plot shows the communication probabilities of ligand-receptor pairs when MAAC serves as target cells.