bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.03.02.708596

ER Stress-Induced beta-Cell Apoptosis is Linked to Novel Select Lipid Signaling at the Transcriptional Level: Implications in T1D Development

Lei, X.·Challa, A. K.·Nozell, S. E.·Ali, T.·Stephenson, D. J.·Nafzinger, A.·Hunter, C. S.·Wende, A. R.·Nakayasu, E. S.·Gai-Tusing, Y.·Chalfant, C. E.·Ramanadham, S.
View original source ↗Export metadata ↓

Abstract

Type 1 diabetes (T1D) is a consequence of {beta}-cell death. ER stress precedes T1D onset and prolonged ER stress in {beta}-cells can lead to {beta}-cell apoptosis. We reported that lipid signaling generated by the Ca2+-independent phospholipase A2{beta} (iPLA2{beta}), encoded by Pla2g6, participates in ER stress-mediated {beta}-cell apoptosis. {beta}-Cell membranes are enriched in arachidonic acid containing glycerophospholipids and the iPLA2{beta} catalyzes the hydrolysis of arachidonic acid in ER stressed {beta}-cells. Metabolism of arachidonic acid leads to the generation of various proinflammatory lipids, raising the possibility that they contribute to ER stress and {beta}-cell death leading to T1D. However, molecular mechanisms by which such {beta}-cell-iPLA2{beta}-derived lipid (iDL) signaling contributes to {beta}-cell apoptosis are not understood. It is well known that ER stress-mediated {beta}-cell apoptosis is associated with induction of transcription factors, NF{kappa}B and STAT1. We report here that both induce Pla2g6 and, unexpectedly, we find that iPLA2{beta}, which lacks DNA-binding motifs, associates with NFkB, Stat1, and Pla2g6 promoter regions. Consistently, p65-NF{kappa}B and pSTAT1 induction is reduced with select inhibition or knockdown of iPLA2{beta}. Surprisingly, iPLA2{beta} expression is also reduced by select inhibition of iPLA2{beta}, raising the possibility of feedback regulation by iDLs. In support, we find that select iDLs, recognized to be proinflammatory, enhance association of iPLA2{beta} with Pla2g6, Nfkb, and Stat1 promoter regions leading to induction of all three gene products and {beta}-cell apoptosis. Our findings reveal previously unrecognized transcriptional regulation by iDL signaling and, iPLA2{beta} itself, that leads to gene products that promote {beta}-cell apoptosis. Analogous findings in human islets validate this mechanism raising the possibility that targeting select lipid signaling can reduce ER stress in {beta}-cells and ameliorate T1D development.

Explore related subjects

cell biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lei, X., Challa, A. K., Nozell, S. E., Ali, T., Stephenson, D. J., Nafzinger, A., Hunter, C. S., Wende, A. R., Nakayasu, E. S., Gai-Tusing, Y., Chalfant, C. E., Ramanadham, S.. 2026-03-04. ER Stress-Induced beta-Cell Apoptosis is Linked to Novel Select Lipid Signaling at the Transcriptional Level: Implications in T1D Development. https://doi.org/10.64898/2026.03.02.708596

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Deep generative embeddings of gene expression and splicing reposition the interpretation of single-cell transcriptomic signatures

Single-cell transcriptomic analysis predominantly derives cell identity from gene expression analysis, while alternative splicing is processed separately despite its fundamental role for cell homeostasis. To overcome the limits of separate investigations, we developed a probabilistic deep learning framework, Crecerelle, enabling resolution of the contributions of gene expression and alternative splicing in each cell. Crecerelle learns cell embeddings from gene expressions and alternative splicing isoforms, to decipher their mutually dependent impact on the functional characterisation of cells in a data-driven manner, exemplified for the Tabula Muris dataset. This is enabled through a zero-and-N-inflated Dirichlet-Multinomial for a variational autoencoder that learns cell embeddings solely from splicing profiles, as well as a bi-modal variational autoencoder with a relevance-weighted mixture-of-experts variational posterior to consolidate the modality-specific contribution at single-cell level. Crecerelle reveals cell-type-specific isoform markers as well as subpopulations with unique isoforms and uncovers regulatory and disease-associated pathways not detected by gene expression analyses alone. This scalable and interpretable framework thus allows a more holistic study of transcriptomic regulation and will open a route to modality-relevance-weighted investigations across single-cell multiomics datasets and their influence on cellular homeostasis, tissue development and disease phenotypes.

cell biology↗
bioRxiv2026

MHC Molecules on B Cell Microvilli Are Spatially Associated with IL-15Rα

Interleukin-15 (IL-15) trans-presentation (TP) by B cells is an important mechanism of T-cell activation; however, the spatial organisation of interleukin-15 receptor (IL-15R) relative to major histocompatibility complex (MHC) molecules on B-cell microvilli remains poorly understood. As microvilli protrude from the B-cell surface and may serve as sites of initial B cell-T-cell contact, the distribution of IL-15R and MHC molecules within these structures may be important during the earliest stages of T-cell recognition and activation. Here, we investigated the spatial association and molecular proximity of IL-15R with MHC class I and class II molecules on B-cell microvilli before immunological synapse formation, using confocal microscopy, stimulated emission depletion (STED) microscopy, stochastic optical reconstruction microscopy (STORM), and fluorescence lifetime imaging microscopy-based Forster resonance energy transfer (FLIM-FRET). Both MHC class I and class II molecules showed significant spatial association with IL-15R; however, the extent of colocalisation decreased as spatial resolution increased. STED microscopy revealed significant colocalisation between IL-15R and MHC class I, whereas STORM did not detect this association. In contrast, IL-15R and MHC class II remained significantly colocalised at both resolutions. FLIM-FRET further demonstrated molecular proximity between IL-15R and both MHC class I and class II molecules, with higher FRET efficiency observed for MHC class II. Collectively, these findings indicate that IL-15R is spatially organised in proximity to both MHC class I and class II molecules on B-cell microvilli before immunological synapse formation. This arrangement at potential sites of initial B-cell-T-cell contact may facilitate the coordination of IL-15 trans-presentation and antigen presentation during the earliest stages of B-cell-T-cell interactions.

cell biology↗
bioRxiv2026

Pulsed-SILAC in single mouse embryos reveals early embryonic protein synthesis dynamics and phosphosite regulation

Early embryogenesis relies extensively on maternally deposited products until zygotic genome activation, yet the dynamics for the synthesis of new proteins in mammalian embryos remains poorly characterized. To address this, we applied pulsed stable isotope labelling by amino acids in cell culture (pSILAC) combined with narrow-window data-independent acquisition mass spectrometry to single mouse oocytes and embryos to resolve de novo protein synthesis during early embryogenesis. This revealed that the maternal proteome is not a static reservoir, with components of the subcortical maternal complex and amino acid transporters SLC7A1/2 being actively synthesized during the earliest developmental stages. Furthermore, phosphoproteomic analysis identified hundreds of previously unreported phosphosites and extensive regulation during the oocyte-to-embryo transition. Notably, phosphorylation of the PRC2-interacting KLP motif of EZHIP emerged as a potential regulatory mechanism, with modification of this region reducing EZHIP-PRC2 interaction and coinciding with H3K27me3 remodelling. Together, single embryo pSILAC revealed a maternal proteome that is continuously synthesized, recycled, and post-translationally regulated during early embryogenesis.

cell biology↗