Candida albicans is responsible for the majority of life-threatening fungal infections occurring in hospitalized patients and is also the most frequently isolated fungal commensal of humans. The C. albicans population includes at least 18 phylogenetic groups (or clades). Specific phenotypes can distinguish isolates within a given clade from those in other clades and yet, the relationships between C. albicans natural genetic and phenotypic diversities have not been explored in depth. We have sequenced the diploid genomes of >150 C. albicans isolates selected from a collection of commensal/clinical isolates previously used to characterize the population structure and belonging to the 12 major C. albicans clades. The aim of this project is to develop the tools necessary for an in depth analysis of these genome sequences in order to allow us ask questions about the extent of C. albicans genetic diversity, the contribution of loss-of-heterozygosity to this diversity, and the history of C. albicans population.

Candida albicans is responsible for the majority of life-threatening fungal infections occurring in hospitalized patients and is also the most frequently isolated fungal commensal of humans. Microevolution of C. albicans isolates has been observed in a number of instances, being in particular characterized by loss-of-heterozygosity events. Yet, most studies that have investigated such microevolutions have not used whole-genome sequencing. In this project, we aim to characterize C. albicans microevolution at the genome-wide level. To this aim, we will take advantage of multiple isolates collected at the same time in healthy individuals and that share the same molecular type, thus providing information on the extent of genetic diversity of commensal isolates. We will also take advantage of series of isolates collected in patients with different forms of candidiasis and/or that have received antifungal therapy, thus providing information of the impact of pathogenic interaction and antifungal treatment on genome dynamics.

The gastrointestinal tract of humans is colonized by hundreds of microbial species, - bacteria, archaebacterial, fungi, protozoa and viruses -, collectively named the gut microbiome. The intestinal commensal bacteria have an important role in metabolic processes and contribute to colonization resistance against intestinal pathogens. Fungi are usually considered to be a minor component of the global microbiome. However, the mycobiome (fungal component of the entire microbiome) has been in fact little studied particularly with regards to its relationships with the other components of the microbiome. It seems however that fungi can be important players of the microbiome because some fungal species are able to proliferate in response to diet or during dysbiosis due to antibiotic treatment or gut inflammation. Consensus approaches to explore mycobiome together with other components of the mycobiome are still lacking. In this context the primary goal of our project will be to determine the best means to analyze bacterial and fungal microbiome concomitantly, using an identical technical procedure. We will evaluate the effectiveness of different methods for: 1) sample conservation; 2) DNA extraction; 3) mapping fungal and bacterial databases. The best procedure then will be used on samples from different studies to analyze interactions and respective dynamics of fungal and bacterial microbiome in different clinical settings.

Invasion of epithelial cells by the obligate intracellular bacterium Chlamydia trachomatis results in its enclosure inside a membrane-bound compartment termed an inclusion. The bacterium quickly begins manipulating interactions between host intracellular trafficking and the inclusion interface, diverging from the endocytic pathway and escaping lysosomal fusion. We have isolated a mutant strain that shows several developmental defects. The C3BI will contribute to the statistical analysis of the data.

Ce projet, discuté avec le groupe « Statistiques », a pour but de proposer une analyse statistique des données quantitatives de phénotypage à haut débit générées au laboratoire. Le groupe Statistiques se propose de former et d’accompagner C. Maufrais à ce type d’analyse. Notre jeu de données de phénotypage consiste en des données multivariées (mesure de 16 variables sur 42 souches cultivées dans 100 conditions de croissance, avec réplicats biologiques et techniques).