Chen Meng

The paper investigates how microbial communities adapt metabolically in different environments, showing changes in carbon usage, biosynthesis, and interactions across monocultures, in vitro communities, and the mouse gut.

This study shows that ATM-deficient pancreatic cancers reprogram the tumor microenvironment via TGF-β-driven myCAF enrichment, and targeting this stromal axis with chemotherapy improves therapeutic efficacy.

This study shows that high-fat diets promote GEAC by altering the microbiota-Bile Acid axis and inhibiting FXR, with FXR agonists like OCA slowing disease progression.

This study shows that butyrate is metabolized into the TCA cycle in fly heads and increases oxygen consumption without affecting proteome or acetylome.

This study investigates metabolic changes during skeletal muscle hypertrophy using metabolomics and finds rewiring of glycolytic intermediates into anabolic pathways, particularly the serine synthesis pathway.

This study shows that microbiota and metabolite rhythmicity develops early in life, influenced by diet and breastfeeding, with GOS-supplemented formula promoting bifidobacteria.

This study identifies HP1021 as a regulator of oxidative stress response and competence in H. pylori through multi-omics analysis.

This study shows that the intestinal clock influences microbiome oscillations and host metabolism, with dietary fiber playing a key role in linking circadian rhythms to metabolic health.

omicsViewer is a platform for visualizing and analyzing omics data, allowing interactive exploration and sharing of results with collaborators.

Adding tandem mass tag proteomics to genome and transcriptome data resolved 22% of 121 unsolved suspected mitochondrial disease cases and surfaced two new disease genes.

MOGSA integrates multiple omics data to improve gene set analysis by combining features across data types and reducing noise, revealing molecular subtypes in bladder cancer.

The paper creates a proteome and transcriptome atlas of 29 human tissues, revealing differences in mRNA-protein abundance and challenges in proteogenomics.