Biology subjects

Tam, E.

Publications and source records attributed to Tam, E..

5 recordsLinked to original sources

bioRxiv2026

A Druggable G Protein Checkpoint in Cholesterol Efflux

Immunometabolic diseases such as obesity, fatty liver, and atherosclerosis arise when lipid-associated macrophages (LAMs) fail to resolve lipid overload via reverse cholesterol transport (RCT), the bodys sole pathway for lipid disposal. How RCT is restrained in disease remains unknown. Integrating systems modeling with human plaque transcriptomes, we identify LAM subpopulations associated with plaque progression and uncover CCDC88A (GIV) as a macrophage-intrinsic checkpoint on RCT. Myeloid-specific GIV deletion in mice reduces aortic plaque burden, mobilizes hepatic and adipose lipid stores and promotes fecal sterol disposal. Mechanistically, GIV sequesters the cholesterol transporter ABCA1 within endomembranes and activates Gi[bullet]{beta}{gamma} signaling to suppress cAMP/PKA-CREB-dependent efflux programs. Pharmacogenomic disruption of this checkpoint reactivates efflux programs. In human plaque-in-a-dish models targeting this pathway restored efflux where statins and {beta}-blockers failed, translating to an estimated [~]98% reduction in plaque-progression risk in outcome modeling. Thus, RCT-restoration represents a macrophage-intrinsic therapeutic paradigm for immunometabolic disease. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/705962v2_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@50dd10org.highwire.dtl.DTLVardef@e16d9borg.highwire.dtl.DTLVardef@1e2eaf3org.highwire.dtl.DTLVardef@af29b9_HPS_FORMAT_FIGEXP M_FIG C_FIG eTOC blurbLipid-associated macrophages drive immunometabolic disease. Katkar et al. show that disabling a GIV-dependent G-protein brake restores cholesterol efflux, reverses plaque lipid accumulation, and establishes reverse cholesterol transport as a druggable therapeutic axis. HighlightsO_LIStatins slow but rarely reverse plaque burden, leaving residual risk driven by LAM dysfunction C_LIO_LIGIV (CCDC88A) non-canonically modulates Gi to suppress macrophage cholesterol efflux C_LIO_LIGIV loss or inhibition restores ABCA1 activity via transcriptional and post-translational control C_LIO_LIBlocking GIV[bullet]Gi checkpoint defats LAMs, regresses plaques, and relieves systemic lipid overload C_LIO_LISIdentifies a druggable node that redefines RCT restoration as a therapeutic paradigm in immunometabolic disease C_LI

immunology↗

bioRxiv2025

SPARK: in silico simulations for benchmarking nascent RNA sequencing experiments

Nascent RNA sequencing offers profound insights into transcriptional dynamics, yet there are substantial challenges to analyzing these data. The development of proper computational tools necessitates realistic benchmarking datasets that reflect biological variability and technical biases. We present simulated pre-mRNA and RNA kinetics (SPARK), a versatile in silico framework for generating reads across nascent RNA sequencing approaches. SPARK simulates the process of transcription -- allowing for variable elongation rates and pausing events -- and key experimental features. SPARK provides a comprehensive platform for computational development and benchmarking in nascent RNA genomics.

genomics↗

bioRxiv2025

Endothelial cell-intrinsic NOD2 signaling regulates the intestinal immune response through the generation of effector and memory T cells.

Crohns disease (CD) is marked by vascular endothelial dysfunction and aberrant T cell immunity in the gastrointestinal tract. However, mechanistic understanding is lacking of how CD-associated gene variants, particularly those that compromise NOD2 function, impact the intestinal vascular endothelium and orchestration of T cell immunity. Here, we find that NOD2, when triggered by its ligand, muramyl dipeptide, is unique among pattern recognition receptors in its ability to induce endothelial cell expression of chemokines and immune adhesion molecules. Consequently, NOD2 signaling promoted T cell homing specifically to gut-associated lymphoid tissue during intestinal infection. Endothelial cell-specific deletion of Nod2 resulted in fewer effector and memory T cells in the small intestine, impacting the hosts ability to clear secondary infection. Together, our findings suggest that vascular endothelial cell expression of NOD2 coordinates intestinal immune responses, and that CD-associated loss of NOD2 function promotes aberrant inflammation due to alterations in the magnitude and specificity of host defense within the intestine.

immunology↗

bioRxiv2022

Sleep and circadian rhythm disruption alters the lung transcriptome to predispose to viral infection

Sleep and circadian rhythm disruption (SCRD), as encountered during shift work, increases the risk of respiratory viral infection including SARS-CoV-2. However, the mechanism(s) underpinning higher rates of respiratory viral infection following SCRD remain poorly characterised. To address this, we investigated the effects of acute sleep deprivation on the mouse lung transcriptome. Here we show that sleep deprivation profoundly alters the transcriptional landscape of the lung, causing the suppression of both innate and adaptive immune systems, disrupting the circadian clock, and activating genes implicated in SARS-CoV-2 replication, thereby generating a lung environment that promotes viral infection and associated disease pathogenesis. Our study provides a mechanistic explanation of how SCRD increases the risk of respiratory viral infections including SARS-CoV-2 and highlights therapeutic avenues for the prevention and treatment of COVID-19.

neuroscience↗

bioRxiv2020

Deep learning and automated Cell Painting reveal Parkinson's disease-specific signatures in primary patient fibroblasts

Drug discovery for diseases such as Parkinsons disease are impeded by the lack of screenable cellular phenotypes. We present an unbiased phenotypic profiling platform that combines automated cell culture, high-content imaging, Cell Painting, and deep learning. We applied this platform to primary fibroblasts from 91 Parkinsons disease patients and matched healthy controls, creating the largest publicly available Cell Painting image dataset to date at 48 terabytes. We use fixed weights from a convolutional deep neural network trained on ImageNet to generate deep embeddings from each image and train machine learning models to detect morphological disease phenotypes. Our platforms robustness and sensitivity allow the detection of individual-specific variation with high fidelity across batches and plate layouts. Lastly, our models confidently separate LRRK2 and sporadic Parkinsons disease lines from healthy controls (receiver operating characteristic area under curve 0.79 (0.08 standard deviation)), supporting the capacity of this platform for complex disease modeling and drug screening applications.

cell biology↗