Biology subjects

Santus, L.

Publications and source records attributed to Santus, L..

3 recordsLinked to original sources

bioRxiv2026

Multi-omic dissection of reversible and persistent molecular alterations in diet-induced obesity

Diet-induced obesity drives broad molecular remodeling across host and microbial systems, but why lifestyle intervention reverses some of these alterations while others persist remains unclear. To address this, we performed a multi-omic characterization of diet-induced obese mice after a combined nutritional and exercise intervention, integrating liver transcriptomics, epigenomics, metabolomics and metallomics with gut metagenomics and metallomics. Multi-omics factor analysis resolved two dominant axes of variation. The first captured a broadly reversible response (~72% of altered variables), restored by dietary restriction and exercise, involving coordinated remodeling of hepatic metal homeostasis, epigenetic regulation, and immune and cell-turnover pathways. The second comprised persistent alterations resistant to intervention and driven primarily by microbial functional profiles: notably, functional diversity remained reduced despite substantial taxonomic recovery. Using germ-free mice to define the microbiota-responsive hepatic space, we found that a significant fraction of the persistent liver features fell within it, enriched in lipid metabolism (PPAR signaling, steroid and cholesterol biosynthesis, peroxisomal activity) and retinol metabolism. Sequential correlation analysis traced these changes to the loss of specific low-abundance taxa and their biosynthetic capacities, particularly vitamin (folate, biotin, cobalamin, pantothenate, thiamine) and cofactor metabolism, implicating microbiota-derived vitamin metabolism in sustained hepatic dysfunction. Cobalt was the sole essential element that remained persistently dysregulated and tracked dietary cobalt content, suggesting a diet--microbiota route to the persistent phenotype. These findings establish a dual regulatory framework in which metabolic plasticity is governed by reversible host-intrinsic and persistent microbiota-dependent processes, providing a systems-level explanation for obesogenic memory.

systems biology↗

bioRxiv2025

An nf-core framework for the systematic comparison of alternative modeling tools: the multiple sequence alignment case study

The computational complexity of many key bioinformatics problems has resulted in numerous alternative heuristic solutions, where no single approach consistently outperforms all others. This creates difficulties for users trying to identify the most suitable tool for their dataset and for developers managing and evaluating alternative methods. As data volumes grow, deploying these methods becomes increasingly difficult, highlighting the need for standardized frameworks for seamless tool deployment and comparison in HPC environments. Multiple sequence aligners (MSAs) rank among the most commonly employed modeling techniques in bioinformatics, playing a crucial role in applications such as protein structure prediction, phylogenetic reconstruction, and variant effect prediction. The NP-hardness of MSAs makes them a major example of problems where heuristics stand central, as no optimal solution can be currently obtained, within the limits of operational computational requirements. Here, we present a pilot design of an nf-core framework for streamlined tool deployment and rigorous performance evaluation focusing on the MSAs software ecosystem. By integrating the most popular MSA tools and focusing on a modular, and extensible architecture, we aspire to provide a key platform supporting MSA deployment, evaluation, and algorithmics development to the MSA community, and a proof-of-principle to the wider bioinformatics community.

bioinformatics↗

bioRxiv2022

In vivo single-cell profiling of lncRNAs during Ebola virus infection

Long non-coding RNAs (lncRNAs) are pivotal mediators of systemic immune response to viral infection, yet most studies concerning their expression and functions upon immune stimulation are limited to in vitro bulk cell populations. This strongly constrains our understanding of how lncRNA expression varies at single-cell resolution, and how their cell-type specific immune regulatory roles may differ compared to protein-coding genes. Here, we perform the first in-depth characterization of lncRNA expression variation at single-cell resolution during Ebola virus (EBOV) infection in vivo. Using bulk RNA-sequencing from 119 samples and 12 tissue types, we significantly expand the current macaque lncRNA annotation. We then profile lncRNA expression variation in immune circulating single-cells during EBOV infection and find that lncRNAs expression in fewer cells is a major differentiating factor from their protein-coding gene counterparts. Upon EBOV infection, lncRNAs present dynamic and mostly cell-type specific changes in their expression profiles especially in monocytes, the main cell type targeted by EBOV. Such changes are associated with gene regulatory modules related to important innate immune responses such as interferon response and purine metabolism. Within infected cells, several lncRNAs have positively and negatively correlated expression with viral load, suggesting that expression of some of these lncRNAs might be directly hijacked by EBOV to attack host cells. This study provides novel insights into the roles that lncRNAs play in the host response to acute viral infection and paves the way for future lncRNA studies at single-cell resolution.

genomics↗