Biology subjects

Tsai, T.-H.

Publications and source records attributed to Tsai, T.-H..

4 recordsLinked to original sources

bioRxiv2026

In Vivo Quantification of Histone Acetylation Turnover and Acetyl-CoA Sources Using 2H2O Metabolic Labeling and High-Resolution Mass Spectrometry.

Dysregulated histone acetylation links cellular metabolism to gene expression, but measuring its in vivo turnover remains technically challenging. Here, we introduce a 2H2O-based metabolic labeling method coupled with high-resolution Orbitrap mass spectrometry to quantify in vivo histone acetylation dynamics. The approach leverages differing deuterium incorporation rates between fast-labeling acetyl groups and slow-labeling peptide backbones. A two-tier analytical workflow uses full-scan mass spectrometry for mono-acetylated peptides, combined with parallel reaction monitoring (PRM) to resolve site-specific turnover and stoichiometry. Furthermore, monitoring acetyl-group plateau 2H enrichment enables the evaluation of specific substrate contributions to the acetyl-CoA pool supporting histone acetylation. To demonstrate biological utility, we applied this approach to mice maintained on a high-carbohydrate diet or subjected to 48-h fasting to assess nutrient-dependent histone acetylation dynamics. Acetyl-group labeling reflected the metabolic origin of acetyl-CoA, showing greater 2H enrichment in the fed state and reduced enrichment during fasting due to increased utilization of unlabeled fatty acid-derived acetyl-CoA. Fasting accelerated acetylation turnover across multiple histone sites and reduced overall acetylation stoichiometry. Quantitative tracing revealed that fatty acid oxidation becomes an important contributor to histone acetylation during fasting, whereas glucose remains the predominant source of nucleo-cytosolic acetyl-CoA (supplying > 60% of acetylation used carbon). This approach enables simultaneous in vivo assessment of histone acetylation turnover, site occupancy, and acetyl-CoA substrate utilization, offering a robust platform to investigate metabolic-epigenetic crosstalk in health and disease.

biochemistry↗

bioRxiv2026

Integrated multi-omics reveals adaptive anti-oxidant remodeling in early alcohol-associated liver disease

Alcohol-associated liver disease (ALD) is a leading cause of liver-related morbidity and mortality. Although various omics approaches have revealed early metabolic alterations, individual datasets provide limited mechanistic insight. Here, we integrated RNA sequencing with mass spectrometry-based analyses to quantify gene expression, protein abundance, proteome and acetylome dynamics, and metabolic fluxes in livers of alcohol-fed mice. This multi-layered approach revealed extensive metabolic rewiring characterized by suppressed mitochondrial energy metabolism and compensatory upregulation of glutathione (GSH) production, utilization, and recycling, establishing a high-flux antioxidant network. These changes were coupled to epigenetic histone H3 remodeling, marked by increased permissive acetylation and decreased suppressive methylation, linking alcohol-induced metabolic and redox alterations to chromatin reprogramming. ChEA-based in silico upstream transcription factor analysis, identified hepatocyte nuclear factor 4 (HNF4) and nuclear factor erythroid 2-related factor 2 (NRF2) as key regulatory nodes. Alcohol exposure was associated with a modest HNF4 suppression alongside increased expression of NRF2, indicating a shift from HNF4-driven metabolic programs toward NRF2-mediated antioxidant responses. Despite acetylation-associated impairment of mitochondrial proteins, GSH-related enzymes were preserved, supporting a protective, high-turnover antioxidant response that limits early oxidative stress and defines an adaptive state maintaining redox homeostasis while potentially predisposing to ALD progression.

biochemistry↗

bioRxiv2022

MSstatsPTM: Statistical relative quantification of post-translational modifications in bottom-up mass spectrometry-based proteomics

Liquid chromatography coupled with bottom up mass spectrometry (LC-MS/MS)-based proteomics is increasingly used to detect changes in post-translational modifications (PTMs) in samples from different conditions. Analysis of data from such experiments faces numerous statistical challenges. These include the low abundance of modified proteoforms, the small number of observed peptides that span modification sites, and confounding between changes in the abundance of PTM and the overall changes in the protein abundance. Therefore, statistical approaches for detecting differential PTM abundance must integrate all the available information pertaining to a PTM site, and consider all the relevant sources of confounding and variation. In this manuscript we propose such a statistical framework, which is versatile, accurate, and leads to reproducible results. The framework requires an experimental design, which quantifies, for each sample, both peptides with post-translational modifications and peptides from the same proteins with no modification sites. The proposed framework supports both label-free and tandem mass tag (TMT)-based LC-MS/MS acquisitions. The statistical methodology separately summarizes the abundances of peptides with and without the modification sites, by fitting separate linear mixed effects models appropriate for the experimental design. Next, model-based inferences regarding the PTM and the protein-level abundances are combined to account for the confounding between these two sources. Evaluations on computer simulations, a spike-in experiment with known ground truth, and three biological experiments with different organisms, modification types and data acquisition types demonstrate the improved fold change estimation and detection of differential PTM abundance, as compared to currently used approaches. The proposed framework is implemented in the free and open-source R/Bioconductor package MSstatsPTM.

bioinformatics↗

bioRxiv2020

Proteomics of autophagy deficient macrophages reveals enhanced antimicrobial immunity via the oxidative stress response

Defective autophagy is associated with chronic inflammation. Loss-of-function of the core autophagy gene Atg16l1 increases risk for Crohns disease by enhancing innate immunity in macrophages. However, autophagy also mediates clearance of intracellular pathogens. These divergent observations prompted a re-evaluation of ATG16L1 in antimicrobial immunity. In this study, we found that loss of Atg16l1 in macrophages enhanced the killing of virulent Shigella flexneri (S.flexneri), an enteric bacterium that resides within the cytosol by escaping all membrane-bound compartments. Quantitative multiplexed proteomics revealed that ATG16L1 deficiency significantly upregulated proteins involved in the glutathione-mediated antioxidant response to compensate for elevated oxidative stress, which also promoted S.flexneri killing. Consistently, myeloid cell-specific deletion of Atg16l1 accelerated bacterial clearance in vivo. Finally, pharmacological modulation of oxidative stress by suppression of cysteine import conferred enhanced microbicidal properties to wild type macrophages. These findings demonstrate that control of oxidative stress by ATG16L1 regulates antimicrobial immunity against intracellular pathogens. Impact statementMaculins et al utilize multiplexed mass spectrometry to show that loss of the autophagy gene Atg16l1 in macrophages enhances antimicrobial immunity against intracellular pathogens via the oxidative stress response.

cell biology↗