Biology subjects

Webb-Robertson, B.-J. M.

Publications and source records attributed to Webb-Robertson, B.-J. M..

6 recordsLinked to original sources

bioRxiv2025

Islet-intrinsic sex differences in inflammatory signaling contribute to autoimmune diabetes susceptibility

Whereas most autoimmune diseases exhibit female predominance, type 1 diabetes (T1D) occurs more frequently in males after puberty, suggesting a role for sex hormones in disease modification. Because islet {beta} cells actively shape local immune responses, we hypothesized that sex-specific islet responses to inflammation contribute to this disparity. Using transcriptomic and proteomic analyses of human islets from male and female donors, we found that male islets exhibit a more aggressive response to proinflammatory cytokines, characterized by greater induction of interferon signaling and suppression of developmental signaling compared to female islets. Treatment of human islets and mouse {beta} cells with the sex hormone 17{beta}-estradiol (E2) suppressed inflammatory signaling and markers of {beta}-cell maturity while enhancing developmental gene programs. Complementary studies in non-obese diabetic (NOD) mice showed that E2 treatment reduces diabetes incidence and limits progression to severe insulitis. Islet single-cell RNA sequencing revealed that E2 treatment of NOD mice suppresses interferon signaling, chemokine production, and antigen presentation in {beta} cells, while reducing activation and cytotoxicity pathways in immune cells. In co-culture studies in vitro, E2 pretreatment of mouse islets reduces subsequent activation of T cells, and in an aggressive adoptive transfer model in vivo, E2 pretreatment of the recipient mice was found to attenuate hyperglycemia. These findings support a model in which E2-mediated {beta}-cell reprogramming reduces {beta}-cell immunogenicity and promotes local immune tolerance, offering mechanistic insight into sex-biased T1D susceptibility.

cell biology↗

bioRxiv2024

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort

BackgroundBiomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk MethodsTwelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA ResultsAll 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated ConclusionsResults further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.

biochemistry↗

bioRxiv2023

Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images

Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Machine learning methods promise the possibility of automating this process. This study seeks to advance the performance of prior models through optimizing transfer learning. We fine-tuned the existing TrailMap model using expert-labeled data from noradrenergic axonal structures in the mouse brain. By fine-tuning the final two layers of the neural network at a lower learning rate of the TrailMap model, we demonstrate an improved recall and an occasionally improved adjusted F1- score within our test dataset over using the originally trained TrailMap model. Availability and implementation: The software and data are freely available at https://github.com/pnnl/brain_ohsu and https://data.pnl.gov/group/204/nodes/dataset/35673, respectively.

neuroscience↗

bioRxiv2023

Suppression of the Integrated Stress Response in Islet β Cells Decreases Risk of Autoimmune Diabetes

Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress-responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eIF2. In T1D, maladaptive unfolded protein response (UPR) in insulin-producing {beta} cells renders these cells susceptible to autoimmunity. We show that inhibition of the eIF2 kinase PERK, a common component of the UPR and ISR, reverses the mRNA translation block in stressed human islets and delays the onset of diabetes, reduces islet inflammation, and preserves {beta} cell mass in T1D-susceptible mice. Single-cell RNA sequencing of islets from PERK-inhibited mice shows reductions in the UPR and PERK signaling pathways and alterations in antigen processing and presentation pathways in {beta} cells. Spatial proteomics of islets from these mice shows an increase in the immune checkpoint protein PD-L1 in {beta} cells. Golgi membrane protein 1, whose levels increase following PERK inhibition in human islets and EndoC-{beta}H1 human {beta} cells, interacts with and stabilizes PD-L1. Collectively, our studies show that PERK activity enhances {beta} cell immunogenicity, and inhibition of PERK may offer a strategy to prevent or delay the development of T1D.

cell biology↗

bioRxiv2020

From plants to ants: Fungal modification of leaf lipids for nutrition and communication in the leaf-cutter ant fungal garden ecosystem

Lipids are essential to all living organisms, as an energy source, as an important cellular structural component, and as a communication tool. In this study, we used global lipidomic methods to evaluate the lipids in leaf-cutter ant fungal gardens. Leaf-cutter ants and their coevolved fungal cultivar, Leucoagaricus gongylophorus, are a model mutualistic system. The fungus enzymatically digests fresh plant material that the ants cut and deliver, converting energy and nutrients from plants, and providing them to the ants through specialized hyphal swellings called gongylidia. Using combined liquid chromatography, ion mobility spectrometry, and tandem mass spectrometry we evaluated differences between the molecular speciation of lipids in the leaf-cutter ant fungal garden ecosystem. This lipidomic study characterized leaves that are fed to the gardens, gongylidia that are produced by the fungus to feed the ants, and spatially resolved regions of the fungal garden through stages of leaf degradation. Lipids containing alpha-linolenic acid (18:3) were enriched in leaves and the top of the gardens, but not dominant in the middle or bottom regions. Gongylidia were dominated by lipids containing linoleic acid (18:2). To evaluate the communicative potential of the lipids in fungal gardens we conducted a behavioral experiment that showed Atta leaf-cutter ants responded differently to 18:3 and 18:2 fatty acids, with aggression towards 18:3 and attraction for 18:2. This work demonstrates the role of lipids in both the transfer of energy and as an inter-kingdom communication tool in leaf-cutter ant fungal gardens. ImportanceIn this work we examined the role of lipids in the mutualism between leaf-cutter ants and fungus. These ants cut fresh leaf material, which they provide to their fungal cultivar, that converts energy and nutrients from the plants and provides it to the ants in specialized hyphal swellings called gongylidia. This work constitutes the first example of a global lipidomics study of a symbiotic system and provides insights as to how the fungus modifies plant lipids into a usable source for the ants. Through a behavioral experiment, this work also demonstrates how lipids can be used as an inter-kingdom communication tool, in this case an attractant, rather than as a repellant, which is more often seen.

systems biology↗

bioRxiv2018

Proximity-dependent proteomics of the Chlamydia trachomatis inclusion membrane reveals functional interactions with endoplasmic reticulum exit sites

Chlamydia trachomatis is the most common bacterial sexually transmitted infection, responsible for millions of infections each year. Despite this high prevalence, the elucidation of the molecular mechanisms of Chlamydia pathogenesis has been difficult due to limitations in genetic tools and its intracellular developmental cycle. Within a host epithelial cell, chlamydiae replicate within a vacuole called the inclusion. Many Chlamydia-host interactions are thought to be mediated by the Inc family of type III secreted proteins that are anchored in the inclusion membrane, but their array of host targets are largely unknown. To investigate how the inclusion membrane proteome changes over the course of an infected cell, we have adapted the APEX system of proximity-dependent biotinylation. APEX is capable of specifically labeling proteins within a 20 nm radius in living cells. We transformed C. trachomatis to express the enzyme APEX fused to known inclusion membrane proteins, allowing biotinylation and pull-down of inclusion-associated proteins. Using quantitative mass spectrometry against APEX labeled samples, we identified over 400 proteins associated with the inclusion membrane at early, middle, and late stages of epithelial cell infection. This system was sensitive enough to detect inclusion interacting proteins early in the developmental cycle, at 8 hours post infection, a previously intractable time point. Mass spectrometry analysis revealed a novel, early association between C. trachomatis inclusions and endoplasmic reticulum exit sites (ERES), functional regions of the ER where COPII-coated vesicles originate. Pharmacological and genetic disruption of ERES function severely restricted early chlamydial growth and the development of infectious progeny. APEX is therefore a powerful in situ approach for identifying critical protein interactions on the membranes of pathogen-containing vacuoles. Furthermore, the data derived from proteomic mapping of Chlamydia inclusions has illuminated an important functional role for ERES in promoting chlamydial developmental growth.

microbiology↗