Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.06.15.659758

Fetal sex is associated with the maternal gut microbiota composition and its metabolic function

Williams, B. M.·Liu, J.·Bernabe, B. P.
View original source ↗Export metadata ↓

Abstract

BackgroundPregnancy affects almost every organ and system, including the microorganisms that resides in the gastrointestinal track, the gut microbiota. Pregnancy hormones, such as progesterone and estradiol, alter the composition of the maternal gut microbiota, directly and indirectly, and in turn, the gastrointestinal microorganism can modify the activity of reproductive hormones. While the levels of pregnancy hormones depend on the fetal sex, the role of fetal sex in the maternal gut microbiota composition and function has not been explored yet. MethodsUsing publicly available microbial sequencing data from a cohort of 485 pregnant women in Guangzhou, China, we identified taxonomical and predicted metabolic signatures associated with fetal sex and gestational age using zero-inflated Gaussian models and linear models, respectively, correcting for pre-pregnancy BMI, maternal age, parity, and residency status. Further, we determined sex-specific co-abundance microbial networks using SPIEC-EASI. ResultsWe observed higher diversity levels in male than in female pregnancies and identified multiple microbial species and predicted microbial enzymes that were differentially abundant between the fetal sex groups, such as increased levels of Tyzerrella and {beta}-glucuronidase in female pregnancies, respectively. {beta}-glucuronidase deconjugates glucuronide-bound estrogens into free estrogens and glucuronic acid. Further, the microbial co-abundance networks between the male and female pregnancies were distinct, with efficient information transfer being representative of the female network while the male network was characterized by a larger number of competitive or exclusion interactions between microbial species. While the two networks had similar core communities, there were distinct connections between hormone metabolizing microbes, with {beta}-glucuronidase expressing microbes being more highly connected in the female network. ConclusionsOur study suggests that differences in the maternal-fetal interactions, such as fetus/placenta-produced hormone levels, may affect and be affected by the composition of the gut microbiota of pregnant individuals in a sex-specific manner. A better understanding of the relationship between fetal sex and the maternal gut microbiota may improve maternal health and fetal outcomes. Plain English SummaryThe adequate functioning of the microbial communities that reside in the maternal gastrointestinal tract is essential for normal fetal development and their abnormal behavior has been associated with multiple conditions such as preterm birth, gestational diabetes, or depression. Yet, male and female fetuses interact differently with the maternal systems, in part due to the differences in fetal/placental-produced sex hormones. As studies outside pregnancy have shown that estrogen and progesterone metabolites can affect and be affected by the gut microbiota, fetal sex may have direct and indirect effects on maternal outcomes. Understanding these differences could enable better tailoring of prenatal care. HighlightsO_LIFetal/placental-produced sex hormones may affect and be affected by the maternal gut microbiota composition and its metabolic functions. C_LIO_LIGut microbiota diversity and composition during pregnancy is linked to the fetal sex. C_LIO_LIBacterially produced beta-glucuronidase (GUS), an enzyme that can deconjugate glucuronide-bound estrogens into free glucuronic acid and free estrogen, is increased in pregnancies with female fetuses, plausibly due higher levels of glucuronide-bound estrogens in female pregnancies that benefit GUS-expressing bacterial species that consume glucuronic acid C_LIO_LIThe maternal co-abundance gut microbial communities (networks) are distinct in pregnancies with female versus male fetuses specially among taxa that could produce GUS. C_LI

Explore related subjects

bioinformaticsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Williams, B. M., Liu, J., Bernabe, B. P.. 2025-06-15. Fetal sex is associated with the maternal gut microbiota composition and its metabolic function. https://doi.org/10.1101/2025.06.15.659758

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

KEEP EXPLORING

Related preprints

bioRxiv2026

Targeted finetuning enables co-folding models to learn ligand-induced protein conformational states

Advances in protein structure prediction have enabled all-atom protein-ligand co-folding models that predict bound conformations directly from sequence and small-molecule structure. However, these models often fail to generalize to novel binding sites or alternative protein conformational states, limiting their utility for chemical biology and drug discovery. Here we show this limitation reflects training data bias rather than architectural constraints and can be overcome through targeted finetuning. Using ten previously unseen X-ray structures of Werner (WRN) helicase from a drug discovery program, we finetune Boltz-1 to learn both an allosteric binding site and a large conformational change locking the enzyme in an inactive state, while preserving accuracy on the ATP-bound state. The finetuned model generalizes to different chemical series and transfers the conformational logic across RecQ-family helicases in a binding-site sequence-dependent manner. This approach provides a blueprint for adapting foundation models as new structural and mechanistic data emerge, enabling co-folding networks to capture ligand-induced conformational switches and binding poses absent from their training data but central to biological regulation and therapeutic intervention.

bioinformatics↗
bioRxiv2026

Benchmarking single-cell foundation models for aging biology

Single cell foundation models (scFMs) provide representations of cellular states, but their utility across biological questions in aging research remains unclear. We established a benchmark of cellular representations for aging research, evaluating ten general-purpose scFMs, three aging-specific models and conventional methods across five biological questions using more than 2.5 million single cell transcriptomes. Using frozen pretrained representations, Geneformer performed best among scFMs for chronological age prediction and age pseudotime concordance, although 2,000 highly variable genes achieved higher mean performance. Several scFMs captured positive molecular age shifts across three disease contexts, consistent with reported aging-associated changes. SCimilarity performed well for rare cellular state identification across out-of-distribution datasets, exceeding aging specific models and conventional baselines. At the gene level, scGPT showed the highest recovery of reference TF target interactions, including aging-related regulatory hubs. Overall, scFMs supported diverse aging analyses, but performance depended on the biological question, highlighting their utility for rare cellular state identification and regulatory analysis.

bioinformatics↗
bioRxiv2026

CryoMV: Structure-Prior-Guided Modeling and Real-Particle Validation of Continuous Conformational Transitions in Cryo-EM

Continuous protein conformations are essential for understanding fundamental biological processes and supporting drug discovery. Although cryo-EM can resolve individual states at high resolution, recovering continuous heterogeneity from 2D particle images remains challenging. High noise, motion blur, and limited structural priors make it difficult to accurately generate and validate high-resolution continuous conformations using raw particle data. Here, we introduce cryoMV, a framework that integrates structure-prior-guided modeling with real-particle validation for continuous conformational transitions. CryoMV uses reference density maps to establish structural anchors and motion priors, models candidate transition paths between selected conformations, and transfers the learned representation to raw 2D cryo-EM particle images. Each candidate conformation is subsequently evaluated using the estimated particle poses and contrast transfer functions. Supported conformations are reconstructed through raw particle back-projection and assessed using canonical half-maps and Fourier shell correlation. On EMPIAR-10516 and EMPIAR-10345, cryoMV achieves excellent performance in terms of robustness, verifiability, and reconstruction resolution. By incorporating structure-prior modeling and evidence from the raw particles, cryoMV offers an explicit mechanism for assessing whether generated conformations are supported by experimental data and provides a practical approach to reducing model-induced artifacts in continuous cryo-EM heterogeneity analysis.

bioinformatics↗