Biology subjects

Pothier, J.

Publications and source records attributed to Pothier, J..

4 recordsLinked to original sources

bioRxiv2025

Nucleolar Targeting and ROS-dependent inhibition of rRNA synthesis by Epstein-Barr Virus Nuclear Antigen 1

Epstein-Barr virus nuclear antigen 1 (EBNA-1) is essential for viral episome maintenance and is consistently expressed in all forms of EBV latency. In a previous study, we observed EBNA-1 localizing in the nucleolus, as well as its interaction with the nucleolar protein EBP2 in both the nucleoplasm and nucleoli. Nucleoli are dynamic nuclear domains that coordinate ribosome assembly with the regulation of cell cycle progression and stress responses. Here, we studied the mechanism by which EBNA-1 achieves nucleolar localization and functional consequences for host cell physiology. We observed that EBNA-1 nucleolar accumulation occurs specifically during late G1 and S phase and depends on a bipartite nucleolar localization signal (NoLS) composed of two cooperative Weber motifs separated by 24 amino acids. Mutations disrupting NoLS abolish interaction with the nucleolar protein EBP2, whose depletion similarly prevents EBNA-1 nucleolar import. Once in the nucleolus, EBNA1 triggers a 50 % reduction in the synthesis of ribosomal RNA (rRNA) which leads to a global reduction in cellular protein production. In addition, EBNA1 nucleolar targeting induces reactive oxygen species (ROS) production and antioxidant treatment restores both rRNA transcription and protein synthesis. These findings identify EBP2 as a viral nucleolar docking partner and establish nucleolar targeting of EBNA1 as a regulated, cell cycle-dependent process that links oxidative stress to the perturbation of ribosome biogenesis. This mechanism may contribute to EBNA1s ability to promote cell survival and transformation. IMPORTANCEEBNA1 is the only Epstein-Barr virus protein that is consistently expressed in all forms of latency and in every EBV-associated tumor. Although it localizes to the nucleolus and interacts with three nucleolar proteins, its influence on nucleolar functions had never been investigated. Here, we demonstrate that EBNA1s nucleolar targeting is a strictly cell-cycle-regulated process that depends on a previously unrecognized bipartite nucleolar localization signal as well as its interaction with the nucleolar protein EBP2. Once inside the nucleolus, EBNA1 induces a ROS-dependent suppression of rRNA synthesis, resulting in a global decrease in cellular protein production. In addition, these findings uncover a new function of EBNA1: the ability to induce nucleolar stress without activating canonical apoptotic pathways, thereby promoting host-cell survival and potentially contributing to EBV-driven oncogenesis

microbiology↗

bioRxiv2020

A minimal yet flexible likelihood framework to assess correlated evolution

An evolutionary process is reflected in the sequence of changes of any trait (e.g. morphological, molecular) through time. Yet, a better understanding of evolution would be procured by characterizing correlated evolution, or when two or more evolutionary processes interact. Many previously developed parametric methods often require significant computing time as they rely on the estimation of many parameters. Here we propose a minimal likelihood framework modelling the joint evolution of two traits on a known phylogenetic tree. The type and strength of correlated evolution is characterized by few parameters tuning mutation rates of each trait and interdependencies between these rates. The framework can be applied to study any discrete trait or character ranging from nucleotide substitution to gain or loss of a biological function. More specifically, it can be used to 1) test for independence between two evolutionary processes, 2) identify the type of interaction between them and 3) estimate parameter values of the most likely model of interaction. In its current implementation, the method takes as input a phylogenetic tree together with mapped discrete evolutionary events on it and then maximizes the likelihood for one or several chosen scenarios. The strengths and limits of the method, as well as its relative power when compared to a few other methods, are assessed using both simulations and data from 16S rRNA sequences in a sample of 54 {gamma}-enterobacteria. We show that even with datasets of fewer than 100 species, the method performs well in parameter estimation and in the selection of evolutionary scenario.

evolutionary biology↗

bioRxiv2020

Gene transmission and antibiotic usage are the key factors responsible for the positive correlation between antibiotic resistance gene diversity and virulence gene diversity in human metagenomes

1.This study aims to understand the cause of the recent observation that humans with a higher diversity of virulence genes in their metagenomes tend to be precisely those with higher diversity of antibiotic-resistance genes. We simulated the transferring of virulence and antibiotic-resistance genes in a community of interacting people where some take antibiotics. The diversities of the two genes types became positively correlated whenever the contagion probability between two people was higher than the probability of losing resistant genes. However, no such positive correlations arise if no one takes antibiotics. This finding holds even under changes of several simulations parameters, such as the relative or total diversity of virulence and resistance genes, the contagion probability between individuals, the loss rate of resistance genes, or the social network type. Because the loss rate of resistance genes may be shallow, we conclude that the contagion between people and antibiotic usage is the leading cause of establishing the positive correlation mentioned above. Therefore, antibiotic use and something as prosaic as the contagion between people may facilitate the emergence of virulent and multi-resistant bacteria in peoples metagenomes with a high diversity of both gene types. These superbugs may then circulate in the community.

microbiology↗

bioRxiv2018

Correlation among antibiotic resistance and virulence traits in human gut microbiomes

Human beings have used large amounts of antibiotics, not only in medical contexts but also, for example, as growth factors in agriculture and livestock, resulting in the contamination of the environment. Even when pathogenic bacteria are the targets of antibiotics, hundreds of non-pathogenic bacterial species are affected as well. Therefore, both pathogenic and non-pathogenic bacteria have gradually become resistant to antibiotics. We tested whether there is still co-occurrence of resistance and virulence determinants. We performed a comparative study of environmental and human gut metagenomes issuing from different individuals and from distinct human populations across the world. We found a great diversity of antibiotic resistance determinants (ARd) and virulence factors (VFd) in metagenomes. Importantly there is a correlation between ARd and VFd, even after correcting for protein family richness. In the human gut there are less ARd and VFd than in more diversified environments, and yet correlations between the ARd and VFd are stronger. They can vary from very high in Malawi, where antibiotic consumption is unattended, to non-existent in the uncontacted Amerindians. We conclude that there is co-occurrence of resistance and virulence determinants, suggesting a possible co-selective mechanism. For example, by selecting for resistant bacteria, we may be selecting for more virulent strains as a side effect of antimicrobial therapy.

genomics↗