Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.06.19.733425

Female-specific m6A remodeling in the liver correlates with post-transcriptional metabolic adaptation to high fat diet

Abstract

Sex differences strongly influence susceptibility to metabolic dysfunction-associated steatotic liver disease (MASLD), yet the regulatory mechanisms underlying these differences remain incompletely understood. To examine sex-specific hepatic adaptation to a high-fat (HF) diet mouse model of MASLD, we integrated proteomics, transcriptomics, and Oxford Nanopore direct RNA sequencing for transcriptome-wide m6A profiling in male and female mouse livers. Female mice were relatively protected from HF diet-induced hepatic steatosis and exhibited distinct proteome remodeling enriched for peroxisomal pathways. In contrast, transcriptomic responses in females were dominated by inflammatory signatures and did not recapitulate the metabolic adaptations observed at the protein level, revealing extensive RNA-protein discordance and post-transcriptional remodeling. Integrated RNA-protein analyses identified female-specific amplification of peroxisomal proteins despite modest transcript-level changes. HF diet also induced sex-specific remodeling of m6A RNA methylation and altered regulation of the m6A methylation system. Notably, reduced 3' UTR m6A methylation of peroxisomal transcripts inversely correlated with increased protein abundance relative to RNA expression in female mice. Together, these findings implicate m6A-associated post-transcriptional regulation in sex-specific hepatic adaptation to HF diet exposure and the basis for discordance between many of the mRNAs and proteins in the liver.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Krylova, S. V., Horton, M., Bucciarelli, G., Liu, L., Berrigan, J., Cutler, R., Chandran, K., Snyder, N. W., Tebaldi, T., Sidoli, S., Singh, K., Pessin, J. E.. 2026-06-22. Female-specific m6A remodeling in the liver correlates with post-transcriptional metabolic adaptation to high fat diet. https://doi.org/10.64898/2026.06.19.733425

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Limit-pushing overexpression reveals constraints on protein abundance

Proteins are often classified as toxic or non-toxic without measuring the abundance reached, leaving constraints on tolerable protein abundance unresolved. We established a limit-pushing approach in Saccharomyces cerevisiae combining strong inducible expression with gTOW-mediated high-copy selection to counteract copy-number compensation while measuring protein abundance and growth. Nearly all of approximately 80 chromosome I proteins severely inhibited growth or reduced viability at sufficiently high abundance. We established IE50, the expression level associated with a 50% reduction in growth rate, to quantify their widely varying overexpression tolerance. IE50 was positively associated with predicted structural order and cytoplasmic localization propensity and negatively associated with sulphur content. Single-cell imaging linked higher tolerance to proteins remaining cytoplasmic without becoming aggregation-positive and revealed abundance-dependent changes in localization and organelle morphology. At extreme abundance, Fun12, Nup60, and Pex22 generated distinct large-scale intracellular states through specific sequence regions. These findings establish overexpression toxicity as a quantitative property linked to protein characteristics and reveal both constraints on tolerable abundance and sequence-dependent capacities for intracellular organization.

systems biology↗

Accessing Enzyme Kinetic Data and Prediction Methods at Scale

Enzyme kinetic parameters inform metabolic models, yet experimental measurements are sparse. A growing body of work predicts them from protein and substrate features, but software fragmentation hinders adoption, so downstream tools lock into the most accessible method. We present OpenKinetics Predictor (at predictor.openkinetics.org), an open-source platform integrating thirteen methods in isolated environments behind one interface. The platform optionally reports similarity between query proteins and each method's training data to contextualise reliability. A common featurisation-prediction abstraction keeps it extensible, and independent parties, including original authors, contributed many methods. We pair it with a data portal (at data.openkinetics.org) that exposes CatLog, a curated kinetic dataset, with precomputed embeddings, predicted binding sites, and standardised splits. Both offer a web interface and an API, and the GECKO modelling toolbox already calls the predictor API. As a case study, we predict across an E. coli model and find inter-predictor agreement varies with metabolic context and data availability.

systems biology↗

A thermoregulatory design principle for transitions into hypometabolism

Mammals entering torpor or hibernation undergo an abrupt transition from normothermia to hypothermia, yet how thermoregulation enables this switch remains poorly understood. Here, we identify dynamical signatures that precede these transitions and a mathematical principle that can generate them. In fasting-induced torpor in mice, body-temperature fluctuations increased before torpor onset, providing an early-warning signal that tracked proximity to the transition better than temperature decline alone. A heat-balance model showed that reducing how strongly the effective heat-loss coefficient depends on body temperature reorganizes thermoregulatory stability, allowing a low-temperature equilibrium to emerge while the normothermic state remains stable. This organization is consistent with a symmetry-broken pitchfork involving a saddle-node. Similar increases in temperature fluctuations preceded hibernation onset in hamsters. These findings link pre-transition temperature dynamics to changes in the underlying thermoregulatory landscape and provide a framework for detecting and understanding transitions from normothermia to hypothermia.

systems biology↗