Mehdi, A. | bioRxiv Science

bioRxiv2025

Glucose and Oxygen Metabolism Coordinate Human Cortical Developmental Decisions

Defining metabolic regulation of neurodevelopmental programs is essential to approach developmental disorders and injuries driven by alterations in metabolism. In vitro cultures are the only available method to temporally perturb and study living human brain cells throughout neurogenesis, however most culture systems use supraphysiologic conditions of essential nutrients, glucose and oxygen. We probed how environmental exposure to endogenous-like concentrations impact metabolic state and developmental progression of cortical cell types using organoids. Nutrient accessibility globally impacted metabolic state, yet developmental responses to metabolic changes were cell type-specific. Metabolomic and transcriptomic datasets reveal increased TCA metabolites and amino acids and oxidative phosphorylation (OXPHOS) genes, under physiologic glucose conditions. Oxygen level had a modest, yet specific, molecular impact on deep layer excitatory neurons. We assessed consequences of metabolic changes on fate and observed that physiologic glucose expanded the human-enriched population of cortical stem cells, outer radial glia, and their progeny, upper layer excitatory neurons. Alterations in oxygen, instead, affected production of neurogenic progenitors and neuronal differentiation, with higher oxygen availability supporting shifts toward mitochondrial metabolism necessary for maturing cell types. We functionally tested this transition by inhibiting glycolysis; total inhibition promoted neuronal differentiation, whereas inhibition of anaerobic glycolysis/lactate production led to oRG expansion. Lactate signaling was sufficient to suppress oRG development and promote self-renewal of neurogenic progenitors. These data suggest that refined metabolic switches and decreased reliance on glucose are required for transition from stem cell self-renewal to more mature, diversified progenitor subtypes, where switch from anaerobic to aerobic metabolism discretely impacts progenitor diversification.

neuroscience↗

bioRxiv2022

Deficiencies of Runx3 and tissue-resident CD4+ intestinal epithelial lymphocytes link intestinal dysbiosis and inflammation in mouse and human spondyloarthropathy

ObjectiveDisturbances in immune regulation, intestinal microbial dysbiosis and intestinal inflammation characterize ankylosing spondylitis (AS), which is associated with RUNX3 loss-of-function variants. ZAP70W163C mutant (SKG) mice have reduced ZAP70 signaling, spondyloarthritis and ileitis. At intestinal epithelial interfaces, lamina propria Foxp3+ regulatory T cells (Treg) and intraepithelial CD4+CD8+TCR{beta}+ lymphocytes (CD4-IEL) control inflammation. TGF-{beta} and retinoic acid (RA)-producing dendritic cells are required for induction of Treg and for CD4-IEL differentiation from CD4+ conventional or Treg precursors, with upregulation of Runx3 and suppression of ThPOK. We investigated Treg, CD4-IEL, ZAP70 and Runx3 in SKG mice and AS patients. MethodsWe compared ileal Treg and CD4-IEL numbers and differentiation in BALB/c and SKG mice, and with ZAP70 inhibition, and related differentially-expressed genes in terminal ileum to ChIP-seq-identified Runx3-regulated genes. We compared proportions of CD4-IEL in ileum and CD4+8+ T cells in blood of AS patients and healthy controls. ResultsZAP70W163C or ZAP70 inhibition prevented intestinal CD4-IEL but not Foxp3+ Treg differentiation in context of TGF-{beta} and RA in vitro and in vivo, resulting in Runx3 and ThPOK dysregulation. CD4-IEL frequency and expression of tissue resident memory T-cell and Runx3-regulated genes was reduced in SKG intestine. Multiple under-expressed genes were shared with risk SNPs identified in human spondyloarthropathies. CD4-IEL were decreased in AS intestine. Double-positive T cells were reduced and Treg increased in AS peripheral blood. ConclusionHigh-affinity TCR-ZAP70 signalling is required for Runx3-mediated intestinal CD4-IEL differentiation from Treg. Genetically-encoded relative immunodeficiency of T cells underpins poor intestinal barrier control in mouse and human spondyloarthropathy. What is already known about this subject?Ankylosing spondylitis (AS) is associated with RUNX3 loss-of-function variants. Capacity of the AS T cell receptor repertoire to expand in response to infectious antigens is reduced. Foxp3+ regulatory T cells (Treg) are increased in AS intestine. ZAP70W163C mutant (SKG) mice have reduced ZAP70 signaling, spondyloarthritis (SpA) and ileitis. Intestinal epithelial Foxp3+ Treg and CD4+CD8+ cytotoxic lymphocytes (CD4-IEL) control local inflammation. CD4-IEL differentiate from Treg, with upregulation of Runx3 and suppression of ThPOK transcription factors. What does this study add?High-affinity TCR-ZAP70 signalling is required for Runx3-mediated intestinal CD4-IEL differentiation from Treg Intestinal CD4-IEL and circulating CD4+CD8+ T cells are reduced in AS while circulating Treg are increased. Impaired CD8 expression may be correctible by TNF inhibition in AS CD4+ T cells. Deficiencies of Runx3 and tissue-resident CD4-IEL link intestinal dysbiosis and inflammation in mouse and human SpA. How might this influence clinical practice or future developments?Genetically-encoded relative T immunodeficiency underpins poor intestinal barrier control in SpA

immunology↗

bioRxiv2022

Pytri: A multi-weight detection system for biological entities

The enumeration of biological entities is a critical part of experimental assays and usually requires large lengths of time. The standard method is to count the entities by hand or with OpenCV-based software, which can lead to inaccurate results. Here, we propose an online platform for biologists consisting of a system with multiple trained machine learning weights to detect various biological entities such as yeast colonies, bacterial colonies, and melanoma clusters. The Pytri model achieved a median relative error rate of 7.56% for bacterial and yeast colonies on Petri dishes, 6.58% for colonies on 96-well plates and 10.28% for melanoma cluster microscopy images. We showcase the application of state-of-the-art deep learning tools in bacterial entity detection, achieving significantly higher accuracy than traditional methods when compared to our base standard manual count.

bioinformatics↗