Thèse Décrypter le Métabolisme Microbien Inexploré au Sein du Périphyton d'Eau Douce H/F - Doctorat.Gouv.Fr

Établissement : Université de Toulouse École doctorale : SEVAB - Sciences Ecologiques, Vétérinaires, Agronomiques et Bioingenieries Laboratoire de recherche : LRSV - Laboratoire de Recherche en Sciences Végétales Direction de la thèse : Guillaume MARTI ORCID 0000000263219005 Début de la thèse : 2026-10-01 Date limite de candidature : 2026-06-01T23:59:59 Dans le contexte des changements environnementaux globaux, il est crucial de mieux comprendre l'adaptation et la résilience des communautés microbiennes naturelles, qui jouent un rôle pivot dans les fonctions et services écosystémiques via leur métabolisme. La méta-métabolomique constitue une approche de pointe pour relever ce défi ; cependant, des verrous technologiques majeurs doivent encore être levés avant qu'elle ne puisse offrir une compréhension exhaustive du métabolisme microbien des écosystèmes.
Ce projet de doctorat contribuera à ce domaine en s'attaquant à l'un de ses enjeux principaux : déterminer quels organismes produisent quels métabolites, et sous quelles conditions expérimentales ou environnementales, afin d'approfondir notre connaissance du métabolisme microbien à l'échelle de l'écosystème. Cet objectif global s'articule autour de trois objectifs spécifiques :
(i) améliorer la couverture et l'annotation du métabolome microbien inconnu (la « part d'ombre ») ;
(ii) développer et évaluer des approches innovantes reliant les métabolites aux micro-organismes, à travers un gradient allant de communautés synthétiques à des communautés naturelles complexes ;
(iii) appliquer les approches sélectionnées à des échantillons de communautés périphytiques (récoltés sur le terrain et/ou cultivés en conditions contrôlées) afin de décrypter l'adaptation métabolique aux contraintes environnementales.
Le périphyton, qui abrite des représentants de la plupart des règnes du vivant et joue un rôle central dans la production primaire et les cycles géochimiques des écosystèmes aquatiques, constitue le modèle biologique de ce projet.
En cohérence avec ces objectifs, la méthodologie du projet se structure autour de deux axes de recherche : le premier vise à explorer des approches innovantes pour coupler métabolites et micro-organismes au sein des communautés périphytiques et à éclairer le métabolome microbien inexploré ; le second vise à appliquer ces approches pour élucider l'acclimatation, l'adaptation et la résilience métaboliques de ces communautés face aux fluctuations environnementales (ex : température, nutriments, micropolluants organiques). Microbial communities are ubiquitous as free-living or host-associated consortia, playing a pivotal role in human, animal and environmental health [1]. Especially, in aquatic ecosystems, periphyton are complex assemblages of almost all kingdoms of life supporting critical functions (e.g. nitrogen xation, primary production) and ecosystem services (e.g. biodegradation of particular xenobiotics), strongly intertwined with microbial metabolism [2][3]. As global changes continue to push ecosystems beyond planetary boundaries, there is an urgent need to understand how microbes interact within the microbiome and how communities respond, acclimatize and adapt to environmental perturbations in order to ensure ecosystem resilience and associated services in the One-health perspective[4].
Microbial meta-metabolomics based on high-resolution mass spectrometry (HRMS) is a cutting-edge approach to tackle this challenge by relating a meta-metabolome (i.e.. the metabolome of an entire microbial community) to environmental conditions [5]. Meta-metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within natural or host ecosystems (i.e. endometabolomes) but also include chemical interactions within and outside the consortium (i.e. the exometabolomes) [6,7]. Meta-metabolomics is thus particularly well-suited to trace the limits between the chemistry of entire microbial communities (including both cultivable and uncultivable organisms) at the functional level, the chemistry of microbial interactions, and the effect of environmental changes on these processes [8,9]. Despite its potential to provide a comprehensive picture of community metabolomes, there are still critical barriers before metametabolomics can deliver an accurate understanding of ongoing processes inside consortia (i.e. which organisms do what, when, where and with which other organisms, under what environmental conditions, and to what end?) [10].
One major challenge is to determine which microorganisms produce what metabolites under which environmental or experimental conditions, since metabolites do not carry taxonomic information, unlike other omic markers. To this end, various approaches have been proposed, aiming (i) to reduce biological complexity using separation techniques (e.g. cell sorting), (ii) to investigate the spatial co-occurrence of taxa and metabolites (e.g. combination of FISH and mass spectrometry imaging), and (iii) to implement statistics-based approaches on large datasets (e.g. co-occurrence networks) [10].
The recent literature has also highlighted that a large fraction of microbial metabolites are structurally unknown or of unknown biological function (i.e., only 2-20% of signals can be annotated in untargeted metabolomics experiments - the so-called dark microbial metabolome, which is largely related to specialized metabolism [11]. Although recent initiatives are promising in expanding the biochemical space of microbial consortia [10, 12, 13, 14], the proportion of unannotated signals is expected to be even higher in complex microbial ecosystems, as specific metabolic pathways are activated during microbial interactions [15]. This underscores the need to study microorganisms as communities rather than individual species in order to fully comprehend microbial ecosystem metabolism.
The specific objectives of this PhD project are :
(i) To improve the coverage and annotation of the dark microbial metabolome;
(ii) To develop and evaluate cutting-edge approaches to link metabolites and micro-organisms across a gradient from synthetic to complex natural communities;
(iii) To apply the selected approaches to periphytic community samples (previously collected and/or newly acquired in the field and/or cultivated under controlled conditions) to unravel the adaptation of functional biodiversity to environmental constraints.
The overall methodology of this PhD project is organized around two research axes: (i) exploring innovative approaches to link metabolites and micro-organisms in periphytic communities and to illuminate the dark microbial metabolome, and (ii) applying these approaches to unravel the metabolic acclimatization, adaptation, and resilience of these communities to environmental fluctuation (e.g. temperature, nutrients, organic chemicals).
In axis 1, regarding the coverage and annotation of the meta-metabolome, new chromatographic methods (e.g. mixed-mode liquid chromatography with ternary gradient elution) and advanced fragmentation techniques (i.e. Electron-Activated Dissociation) will be explored and further multiplexed to ensure broad coverage of the meta-metabolome and to improve structural elucidation, respectively. In addition, MS-Net2 [14], the new version of MS-Net currently under development, will be used to process, curate, multiplex, and annotate the resulting datasets.
The new version of MS-Net (MS-Net2) will be specifically benchmarked using periphyton as a multi-species model system to evaluate its capacity to generate and annotate multi-species metabolomic profiles. This benchmark will assess the ability of MS-Net2 to disentangle species-specific metabolic contributions within complex community matrices, exploiting the unique taxonomic and metabolic diversity of periphytic assemblages. A multi-block analysis approach (e.g. consensus OPLS, DIABLO) will highlight main correlative biomarkers.
In parallel, MiBIG entries derived from paired metagenomics data will be integrated to improve the matching between biosynthetic gene cluster predictions and metabolite annotations, thereby expanding the coverage of the annotated chemical space. This integrative genomics-metabolomics approach will be further developed in collaboration with INRIA and MetExplore teams specializing in genome-scale metabolic network reconstruction and microbial interaction modelling (INRAE/TOXALIM, INRIA).
To cross-validate metabolites/species links, the combination of mass spectrometry imaging (MSI) and fluorescence in situ hybridization (FISH) will be used as a means of co-localizing taxa and metabolites.

In axis 2, by applying the new approaches, methods and tools developed in Axis 1, both existing environmental and experimental samples or datasets from previous projects (internal: ANSES-COMBO, INRAE-MICROBIOMIQ, ANR-MEMENTO, INRAE-COMIC; external: the MICROBEMASST repository) will be used to investigate (i) the environmental drivers of the spatio-temporal dynamics of periphyton metabolism through in situ surveys, and (ii) the acclimative and adaptive metabolic mechanisms in response to cumulative stressors associated with global change (e.g., nutrients, temperature, organic micropollutants) under controlled experimental conditions.

Master en environnement, plantes et microbiologie