A post-translational cysteine-to-serine conversion in human and mouse insulin generates a diabetogenic neoepitope.

Type 1 diabetes (T1D) affects a genetically susceptible population that develops autoreactive T cells attacking insulin-producing pancreatic β cells. Increasingly, neoantigens are recognized as critical drivers of this autoimmune response. Here, we report a novel insulin neoepitope generated via post-translational cysteine-to-serine conversion (C>S) in human patients, which is also seen in the autoimmune-prone non-obese diabetic (NOD) mice.

Lipid droplet protein Perilipin 2 is critical for the regulation of insulin secretion through beta cell lipophagy and glucagon expression in pancreatic islets.

Knockdown (KD) of lipid droplet (LD) protein perilipin 2 (PLIN2) in beta cells impairs glucose-stimulated insulin secretion (GSIS) and mitochondrial function. Here, we addressed a pathway responsible for compromised mitochondrial integrity in PLIN2 KD beta cells. In PLIN2 KD human islets, mitochondria were fragmented in beta cells but not in alpha cells.

Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics.

RNA isoform diversity, produced via alternative splicing, and alternative usage of transcription start and poly(A) sites, results in varied transcripts being derived from the same gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing-and later, spatial approaches-which are now widely used for the identification of differentially expressed genes, rely on short reads and offer the ability to transcriptomically compare different cell types but are limited in their ability to measure differential isoform expression.

Sliding Window INteraction Grammar (SWING): a generalized interaction language model for peptide and protein interactions.

The explosion of sequence data has allowed the rapid growth of protein language models (pLMs). pLMs have now been employed in many frameworks including variant-effect and peptide-specificity prediction. Traditionally, for protein-protein or peptide-protein interactions (PPIs), corresponding sequences are either co-embedded followed by post-hoc integration or the sequences are concatenated prior to embedding.