Biology subjects

Tran, D. T.

Publications and source records attributed to Tran, D. T..

9 recordsLinked to original sources

bioRxiv2026

Sex-dependent control of renal tubular homeostasis and stress tolerance by KDM6A

Biological sex is an important determinant of kidney disease susceptibility and outcomes. The epigenetic modifier KDM6A is an X chromosome-expressed lysine demethylase and molecular scaffold that escapes X chromosome inactivation. Here, we compared the effects of deletion of KDM6A from kidney tubule epithelial cells in female and male mice (KDM6ATubKO). Knockout of KDM6A from tubule cells aggravated kidney fibrosis caused by unilateral ureteral obstruction (UUO) in female mice, whereas male mice were unaffected by KDM6A absence. Unexpectedly, female (but not male) KDM6ATubKO mice developed spontaneous glucosuria that, when stressed by ligation of one ureter, presented as polyuria and a Fanconi renotubular syndrome-like picture affecting the unobstructed kidney. Absence of KDM6A from tubule epithelial cells of female mice caused mitochondrial circularization, tubule cell vacuolization with focal atrophy and lymphoid infiltration, and diminished sodium/glucose cotransporter 2 (SGLT2). Spatial transcriptomics and untargeted metabolomics revealed that knockout of KDM6A in female mice caused a shift in gene programs and metabolic pathways indicative of tubule cell metabolic dysfunction. In male mice, transcripts of the Y chromosome-expressed gametolog of Kdm6a, Uty were present in tubule epithelial cells at levels comparable to Kdm6a and they were upregulated with UUO. In summary, KDM6A is essential for normal tubule epithelial cell homeostasis in females but not in males. KDM6A and UTY are a dynamically regulated X-Y gene pair with at least partial compensatory overlap in function necessary for the preservation of kidney health and stress tolerance. Graphical abstract. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/740137v1_ufig1.gif" ALT="Figure 1000"> View larger version (29K): org.highwire.dtl.DTLVardef@9186b8org.highwire.dtl.DTLVardef@23d4cborg.highwire.dtl.DTLVardef@67741eorg.highwire.dtl.DTLVardef@1f85dc7_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2026

Cell autonomous inflammation in VEXAS is mediated by cGAS-STING

VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is a severe adult-onset inflammatory disease caused by somatic mutations that reduce cytoplasmic activity of UBA1, the primary initiating enzyme for ubiquitylation. How this hypomorphic state drives cell-intrinsic immune activation in mature myeloid cells is unknown. Using unbiased multi-omic, biochemical, and cell biological analyses of model systems and patient-derived cells, we show that loss of cytoplasmic UBA1 activity convergently disrupts endoplasmic reticulum- associated degradation (ERAD) and mitochondrial homeostasis. ERAD failure arises from preferential under-charging of ERAD E2 enzymes, explaining hallmark VEXAS features, including ER-derived vacuoles and unfolded protein response activation, and promotes accumulation of the ERAD substrate STING. Simultaneously, mitochondrial dysfunction drives cytosolic leakage of mitochondrial DNA, inducing cGAS-dependent STING signaling and inflammatory cytokine production. STING inhibition or reversal of mitochondrial DNA leakage resolves multi-cytokine inflammation in VEXAS models and patient myeloid cells, establishing the cGAS-STING pathway as a therapeutically actionable vulnerability.

genetics↗

bioRxiv2025

A single catalytic domain residue regulates the substrate specificity of a mucin-type O-glycosyltransferase in salivary gland function

Human GalNAc-T1 is a ubiquitously expressed mucin-type O-glycosyltransferase that modulates various biological pathways, including immunity, extracellular matrix formation, and salivary gland development and function. However, substrates of GalNAc-T1 are mostly unknown and the mechanistic details of regulation are not well characterized. Here, we investigate the role of the Drosophila melanogaster GalNAc-T1 ortholog PGANT5 in salivary glands and provide structural and biochemical details into its mechanism of O-glycosylation. We find that loss of pgant5 causes irregular secretory granule morphology, altered mucin packaging, and disruption of secretion. Alternative splicing of pgant5 yields two isoforms, pgant5A and pgant5B, with higher expression of pgant5A in salivary glands. Rescue with pgant5A, but not pgant5B, partially restores secretory granule morphology and salivary gland function. A single residue difference within the substrate binding pockets of PGANT5A and PGANT5B increases the in vitro activity and specificity of PGANT5A towards salivary gland mucins relative to PGANT5B, corroborating the in vivo expression and role of pgant5A in salivary glands. Our data additionally provide new insights into a catalytic domain motif that regulates GalNAc-T activity. Overall, our studies illustrate how alternative splicing of an O-glycosyltransferase that results in modest amino acid changes can influence substrate specificity to regulate tissue-specific biological functions.

biochemistry↗

bioRxiv2024

Kinetic modeling of ethylene biosynthesis and signaling pathways in ripening tomato fruit

O_LIEthylene biosynthesis and signaling are pivotal pathways in various plant aging processes, including fruit ripening. Kinetic models can be used to better understand metabolic pathways, but modeling of the ethylene-related pathways is limited and the link between these pathways remains unsolved. C_LIO_LIA transcriptomics-based kinetic model was developed, consisting of ordinary differential equations describing ethylene biosynthesis and signaling pathways in tomato during fruit development, ripening and post-harvest storage. C_LIO_LIThis model was calibrated against a large volume of transcriptomic, proteomic and metabolic data during on-vine ripening of tomato fruit grown in winter and summer. The model was validated using data on off-vine postharvest ripening. The ethylene biosynthesis pathway under different conditions appeared to be largely driven by gene expression levels. C_LIO_LIThe ethylene-regulation of fruit ripening of a heat tolerant tomato grown in different seasons is identical but with quantitative differences at the targeted omics levels. This is reflected by some of the same parameters with distinct values for summer and winter fruit. The current model is the first attempt to model the ethylene signaling pathway starting from gene expression, the various protein - protein interactions, including the link with ethylene production, internal ethylene levels and its receptors. C_LI

plant biology↗

bioRxiv2023

Towards a Foundation Model of the Mouse Visual Cortex

The complexity of neural circuits makes it challenging to decipher the brains algorithms of intelligence. Recent break-throughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brains computational objectives and neural coding. However, these models struggle to generalize beyond their training distribution, limiting their utility. The emergence of foundation models, trained on vast datasets, has introduced a new AI paradigm with remarkable generalization capabilities. We collected large amounts of neural activity from visual cortices of multiple mice and trained a foundation model to accurately predict neuronal responses to arbitrary natural videos. This model generalized to new mice with minimal training and successfully predicted responses across various new stimulus domains, such as coherent motion and noise patterns. It could also be adapted to new tasks beyond neural prediction, accurately predicting anatomical cell types, dendritic features, and neuronal connectivity within the MICrONS functional connectomics dataset. Our work is a crucial step toward building foundation brain models. As neuroscience accumulates larger, multi-modal datasets, foundation models will uncover statistical regularities, enabling rapid adaptation to new tasks and accelerating research.

neuroscience↗

bioRxiv2023

Bipartite invariance in mouse primary visual cortex

A primary goal of sensory systems is to extract robust and meaningful features that are invariant to variations in the sensory input. Characterizing these invariances at the neuronal level is crucial for understanding how the visual system supports generalization, but the high-dimensional nature of ecological stimuli poses major challenges. Consequently, our understanding of how the brain represents invariances has historically depended on a few examples, such as phase invariance to grating stimuli in V1 complex cells. Here, we leverage the inception loop paradigm --iterating between large-scale recordings, deep learning neuronal predictive models, and in silico experiments with in vivo verification--to characterize neuronal invariances in mouse V1. Using a neuronal predictive model, we synthesized Diverse Exciting Inputs (DEIs) that strongly drive target neurons while differing substantially in image space. These DEIs revealed a novel bipartite invariance: one portion of the receptive field encodes shift-invariant, high-frequency textures, while the other encodes a fixed, low-frequency spatial pattern. This subfield division aligned with object boundaries defined by spatial frequency differences in highly activating stimuli, suggesting bi-partite invariance contributes to segmentation. Our analysis of computational models and anatomical data from the MICrONS dataset revealed a hierarchical organization of excitatory neurons in mouse V1 Layers 2/3: We found that postsynaptic neurons exhibited greater invariance than their presynaptic inputs, while neurons with lower invariance formed more connections. These findings suggest a synaptic-level hierarchy that progressively increases neural invariance within the primary visual cortex. Intriguingly, similar high-low frequency bipartite patterns strongly activate certain units in artificial neural networks, suggesting that universal visual representations govern both biological and artificial systems, potentially aiding in the extraction of visual features from complex backgrounds.

neuroscience↗

bioRxiv2023

Pattern completion and disruption characterize contextual modulation in mouse visual cortex

Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli--where the center and surround share the same orientation--are more inhibitory than when orientations are orthogonal, potentially serving redundancy reduction and predictive coding. Understanding these center-surround interactions in relation to natural image statistics is challenging due to the high dimensionality of the stimulus space, yet crucial for deciphering the neuronal code of real-world sensory processing. Utilizing large-scale recordings from mouse V1, we trained convolutional neural networks (CNNs) to predict and synthesize surround patterns that either optimally suppressed or enhanced responses to center stimuli, confirmed by in v ivo experiments. Contrary to the notion that congruent stimuli are suppressive, we found that surrounds that completed patterns based on natural image statistics were facilitatory, while disruptive surrounds were suppressive. Applying our CNN image synthesis method in macaque V1, we discovered that pattern completion within the near surround occurred more frequently with excitatory than with inhibitory surrounds, suggesting that our results in mice are conserved in macaques. Further, experiments and model analyses confirmed previous studies reporting the opposite effect with grating stimuli in both species. Using the MICrONS functional connectomics dataset, we observed that neurons with similar feature selectivity formed excitatory connections regardless of their receptive field overlap, aligning with the pattern completion phenomenon observed for excitatory surrounds. Finally, our empirical results emerged in a normative model of perception implementing Bayesian inference, where neuronal responses are modulated by prior knowledge of natural scene statistics. In summary, our findings identify a novel relationship between contextual information and natural scene statistics and provide evidence for a role of contextual modulation in hierarchical inference.

neuroscience↗

bioRxiv2021

Orchestrated Restructuring Events During Secretory Granule Maturation Mediate Intragranular Cargo Segregation

Regulated secretion is an essential process where proteins are packaged into membranous secretory vesicles. However, the details of cargo packaging and secretory granule maturation are largely unknown. Here, we demonstrate that multiple distinct proteins undergo intragranular restructuring during secretory granule maturation in vivo, resulting in spatial segregation of distinct protein components within the same granule. Furthermore, through a combination of genetics and multimodality imaging, we demonstrate the molecular identity of each distinct intragranular structure. We further identify temporally-regulated genes that are essential for the restructuring events, including those controlling pH (Vha16-1), Cl- ions (Clic and ClC-c) and Ca2+ ions (fwe). Finally, we show that altered cargo glycosylation influences dimensions of these structures, thereby affecting secretory granule morphology. This study elucidates key steps and factors involved in intragranular, rather than intergranular segregation of cargo through regulated restructuring events during secretory granule maturation. Understanding how multiple distinct proteins are efficiently packaged into and secreted from the same secretory granule may provide insight into diseases resulting from defects in secretion.

cell biology↗

bioRxiv2019

A reference map of the human proinsulin biosynthetic interaction network

The beta-cell protein synthetic machinery is dedicated to the production of insulin, which plays a critical role in organismal homeostasis. Insulin synthesis requires the proper folding and trafficking of its precursor, proinsulin, yet the precise network of proinsulin protein interactions in the secretory pathway remains poorly defined. In the present study we conducted unbiased profiling of the proinsulin interactome in human islets, utilizing a human proinsulin-specific monoclonal antibody for affinity purification and mass spectrometry. Stringent analysis identified a central node of interactions between human proinsulin and sequential secretory pathway proteins that is remarkably conserved across 3 ethnicities and both genders. Among the most prominent proinsulin interactions was with ER-localized peroxiredoxin-4 (PRDX4). A functional role for PRDX4 in beta-cells was demonstrated by gene silencing that rendered proinsulin susceptible to misfolding, particularly in response to oxidative stress. Conversely, exogenous PRDX4 improved proinsulin folding. Notably, oxidative stress and even high glucose treatment alone induced proinsulin misfolding in human islets and MIN6 cells, and this was accompanied by sulfonylation of PRDX4, a modification known to inactivate peroxiredoxins. This finding prompted PRDX4 analysis in a panel of human islet samples that revealed significantly higher levels of sulfonylated (inactive) PRDX4 in islets from patients with T2D compared to that of healthy individuals. Taken together, these data highlight the importance of elucidating the complete proinsulin interactome in human islets in order to understand critical steps controlling insulin biosynthesis, beta cell function, and T2D.

biochemistry↗