Biology subjects

Faucher, C.

Publications and source records attributed to Faucher, C..

3 recordsLinked to original sources

bioRxiv2025

QSProteome: A Community-Driven Interactive Platform for Large-Scale Exploration and Evaluation of Predicted Protein Complex Structures.

QSProteome (https://QSProteome.org) is a community-scale platform for modeling, evaluating, and refining quaternary protein structure. The resource hosts 35,528 unique modeled assemblies spanning over 42,000 genes, covering nearly all curated complexes in BioCyc and ComplexPortal databases. Each model is displayed on an interactive page with 3D visualization, chain-level confidence metrics, structural alignments, functional annotations, and automated stoichiometry checks against database expectations. A cloud-based server supports continuous user uploads and automated processing pipelines--enabling submission and validation of >54,000 models within 14 weeks. To promote iterative refinement, QSProteome includes a gamified re-curation workflow that transitions users from training modules into live curation, enabling the community-led assessment of 1,547 ABC transporter complexes. Together, these components form a dynamic, scalable infrastructure for proteome-scale structural biology. By unifying modeling, validation, and annotation in a reusable, searchable, and community-extensible framework, QSProteome enables proteome-scale structure accessibility and reuse--powering discovery, annotation, and collaborative refinement across the structural biology community.

bioinformatics↗

bioRxiv2021

A within-host infection model to explore tolerance andresistance

How are some individuals surviving infections while others die? The answer lies in how infected individuals invest into controlling pathogen proliferation and mitigating damage, two strategies respectively called resistance and disease tolerance. Pathogen within-host dynamics (WHD), influenced by resistance, and its connection to host survival, determined by tolerance, decide the infection outcome. To grasp these intricate effects of resistance and tolerance, we used a deterministic theoretical model where pathogens interact with the immune system of a host. The model describes the positive and negative regulation of the immune response, consider the way damage accumulate during the infection and predicts WHD. When chronic, infections stabilize at a Set-Point Pathogen Load (SPPL). Our model predicts that this situation can be transient, the SPPL being then a predictor of life span which depends on initial condition (e.g. inoculum). When stable, the SPPL is rather diagnostic of non lethal chronic infections. In lethal infections, hosts die at a Pathogen Load Upon Death (PLUD) which is almost independent from the initial conditions. As the SPPL, the PLUD is affected by both resistance and tolerance but we demonstrate that it can be used in conjunction with mortality measurement to distinguish the effect of disease tolerance from that of resistance. We validate empirically this new approach, using Drosophila melanogaster and the pathogen Providencia rettgeri. We found that, as predicted by the model, hosts that were wounded or deficient of key antimicrobial peptides had a higher PLUD, while Catalase mutant hosts, likely to have a default in disease tolerance, had a lower PLUD.

evolutionary biology↗

bioRxiv2020

Step-specific adaptation and trade-off over the course of an infection by GASP-mutation small colony variants

During an infection, parasites face a succession of challenges, each decisive for disease outcome. The diversity of challenges requires a series of parasite adaptations to successfully multiply and transmit from host to host. Thus, the pathogen genotypes which succeed during one step might be counter-selected in later stages of the infection. Using the bacteria Xenorhabdus nematophila and adult Drosophila melanogaster as hosts, we showed that such step-specific adaptations, here linked to GASP mutations in the X. nematophila master gene regulator lrp, exist and can trade-off with each other. We found that nonsense lrp mutations had lowered ability to resist the host immune response, while all classes of mutations in lrp were associated with a decrease in the ability to proliferate during early infection. We demonstrate that reduced proliferation of X. nematophila best explains diminished virulence in this infection model. Finally, decreased proliferation during the first step of infection is accompanied with improved proliferation during late infection, suggesting a trade-off between the adaptations to each step. Step-specific adaptations could play a crucial role in the chronic phase of infections in any diseases that show similar small colony variants (also known as SCV) to X. nematophila. ImportanceWithin-host evolution has been described in many bacterial diseases, and the genetic basis behind the adaptations stimulated a lot of interest. Yet, the studied adaptations are generally focused on antibiotic resistance, rarely on the adaptation to the environment given by the host, and the potential trade-off hindering adaptations to each step of the infection are rarely considered. Those trade-offs are key to understand intra-host evolution, and thus the dynamics of the infection. However, the understanding of these trade-offs supposes a detailed study of host-pathogen interactions at each step of the infection process, with for each step an adapted methodology. Using Drosophila melanogaster as host and the bacteria Xenorhabdus nematophila, we investigated the bacterial adaptations resulting from GASP mutations known to induce small colony variant (SCV) phenotype positively selected within-the-host over the course of an infection, and the trade-off between step-specific adaptations.

evolutionary biology↗