Project description:Pancreatic beta-cells are essential for survival, being the only cell type capable of insulin secretion. While they are believed to be vulnerable to damage by inflammatory cytokines such as interleukin-1 beta (IL-1beta) and IFN-gamma, we have recently identified physiological roles for cytokine signaling in rodent beta-cells that include that stimulation of antiviral and antimicrobial gene expression and the inhibition of viral replication. In this study, we examine cytokine-stimulated changes in gene expression in human islets using single-cell RNA sequencing. Surprisingly, the global responses of human islets to cytokine exposure were remarkably blunted compared to our previous observations in the mouse. The small population of human islet cells that were cytokine responsive exhibited increased expression of IL-1beta-stimulated antiviral guanylate binding proteins, just like in the mouse. Most human islet cells were not responsive to cytokines, and this lack of responsiveness was associated with high expression of genes encoding ribosomal proteins. We further correlated the expression levels of RPL5 with stress response genes, and when expressed at high levels, RPL5 is predictive of failure to respond to cytokines in all endocrine cells. Further, we postulate that donor cause of death and isolation methodologies may contribute to stress of the islet preparation. Our findings indicate that induction of stress responses in human islets (associated with isolation and/or cause of death) limit cytokine stimulated gene expression, and we urge caution in the evaluation of studies that have examined cytokine-stimulated gene expression in human islets without evaluation of stress-related gene expression.
Project description:Toolsets available for in-depth analysis of scRNAseq datasets by biologists with little informatics experience is limited. Here we describe an informatics tool (PyMINEr) that fully automates cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine/paracrine signaling networks in silico. We applied PyMINEr to interrogate human pancreatic islet scRNAseq datasets and discovered several features of co-expression graphs including: concordance of scRNAseq-graph structure with both protein-protein interactions and 3D-genomic architecture; association of high connectivity and low expression genes with cell type-enrichment; and potential for graph-structure to clarify potential etiologies of enigmatic disease-associated variants. We further created a consensus co-expression network and autocrine/paracrine signaling networks within and across islet cell types from 7-datasets. PyMINEr correctly identified changes in BMP/WNT signaling associated with cystic fibrosis pancreatic acinar-cell loss. This proof-of-principle study demonstrates that the PyMINEr framework will be a valuable resource for scRNAseq analyses.
Project description:Biomarkers capable of monitoring β cell stress during the evolution of type 1 diabetes (T1D) are currently lacking. MicroRNAs (miRNAs) are a class of small non-coding RNAs ~22 nucleotides in length that modulate gene expression by binding to the 3’untranslated region of target mRNAs. Given their stability in biological fluids and enrichment in cell-derived EVs, we hypothesized that miRNAs from human islet and islet-derived EVs could identify β-cell stress/death and be leveraged in T1D biomarker strategies. To test this, human islets were obtained from 10 cadaveric donors (5 male/5 female) and treated with or without cytokines (IL-1β and IFN-γ) for 24 hrs, as an ex vivo model of T1D. Small RNA sequencing was performed and identified 1110 and 890 miRNAs in total and 20 and 14 differentially expressed (DE) miRNAs (fold change≥1.5 and p<0.05) from islets and EVs, respectively. These findings were validated in an independent set of cytokine-treated islets and islet-derived EVs (7M and 5F donors). Interestingly, miRNA expression pattern was strikingly different between male and female donors at baseline and under cytokine stress with < 10% overlap among the DE miRNAs. miR-155-5p and miR-146a-5p were the only two miRNAs that were upregulated in cytokine-treated islets and EVs in both the sexes. Functional enrichment analysis of DE miRNAs identified pathways such as insulin signaling, ER stress and apoptosis. Taken together, these data suggest that miRNA expression patterns change dynamically in both human islets and islet-derived EVs in response to pro-inflammatory cytokine stress. EV miRNAs were largely distinct from those in the islet fraction, suggesting that miRNAs are selectively packaged into EVs in response to extrinsic cues. Finally, these data highlight the importance of considering sex as a biological variable when defining T1D biomarkers.
Project description:Inhibition of polyamine biosynthesis using α-difluoromethylornithine (DFMO), an inhibitor of ornithine decarboxylase (ODC), reduces β-cell stress and type 1 diabetes (T1D) incidence in preclinical models. However, underlying cellular and molecular mechanisms and the tolerability and effectiveness of polyamine depletion by DFMO in humans with T1D remain unknown. Transcriptomics and proteomics of cytokine-stressed human islets treated with DFMO reveal alterations in mRNA translation, nascent protein transport, and secretion. Collectively, our data suggest that inhibition of polyamine biosynthesis may preserve β-cell function in T1D via islet cell-autonomous responses to stress.