Starting Research Position F/m: Metabolic Modelling of The Rumen Microbiome for Guiding Strategies of Methane Reduction

Le descriptif de l’offre ci-dessous est en Anglais_

**Type de contrat**: CDD

**Contrat renouvelable**: Oui

**Niveau de diplôme exigé**: Thèse ou équivalent

**Fonction**: Chercheur contractuel

**A propos du centre ou de la direction fonctionnelle**:
The Inria center at the University of Bordeaux is one of the nine Inria centers in France and has about twenty research teams.. The Inria centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative SMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute...

**Contexte et atouts du poste**:
The fellowship is associated to the ANR-funded H2Rumen project, led by Rafael Muñoz-Tamayo.

The fellowship is organised in two parts: this 18-months contract, hosted at Bordeaux (Inria PLEIADE), followed by a 14-month extension at Paris Saclay (INRAE, AgroParisTech).

The research fellow will collaborate with Clémence Frioux, Simon Labarthe and David James Sherman from the PLEIADE team (Inria, INRAE, Bordeaux) and with Rafael Muñoz-Tamayo from the MoSAR team (INRAE, AgroParisTech, Université Paris-Saclay). Pleiade hosts researchers in mathematics, computer science and computational biology working on developing approaches for microbial community characterisation.

**Project description**. Ruminants play a significant role in human nutrition and food security. Ruminants can harvest nutrients from forage diets rich in fibres and transform them into human-edible products with high-quality proteins. Feed transformation occurs mainly in the rumen through a metabolic cascade of hydrolytic and fermentative reactions carried out by a complex microbial community (rumen microbiota) constituted by hundreds of species that include bacteria, archaea and eukaryotes. During rumen fermentation, methane (CH4) is produced and eructed by the animal. This CH4 contributes to 44% of greenhouse gas emissions from the livestock sector.

Reducing methane (CH4) emissions from ruminants is a major challenge for the livestock sector. An optimal CH4 mitigation strategy should also induce co-benefits such as enhanced animal productivity and health. CH4 is produced during the fermentation of feeds in the rumen. This process is carried out by a complex microbial community (rumen microbiota) and mediated by hydrogen (H2) in the rumen ecosystem. Our knowledge on the drivers that shape H2 flows is still incomplete. **H**2**Rumen aims to generate fundamental knowledge on H**2** flows in the rumen ecosystem and to translate this knowledge into predictive mathematical models of rumen fermentation**. Our scientific outputs will be of high value for the optimal design of CH4 mitigation strategies with co-benefit for the animal. Our hypothesis is that thermodynamics and microbial interactions jointly control hydrogen transactions in the rumen ecosystem. H2Rumen addresses the following fundamental scientific question: Where does H2 go? We will answer this question with an integrative approach that combines _in vitro_ experiments, _in silico_ modelling and omics approaches. In addition to the impact on ruminant livestock, our methods might be applicable to other ecosystems such as the human gut, engineering bioreactors and fermented food ecosystems.

**Mission confiée**:
**The postdoc project aims at developing metabolic models of rumen microbiota with capabilities for designing microbial strategies for reducing methane emissions and improving rumen fermentation**. It will contribute to fill the existing gap on how to integrate microbial genomic information into rumen fermentation models [1].

Genome-scale network reconstructions will be done with state-of-the-art methods and pipelines developed in PLEIADE. Metabolic capabilities of rumen microbial communities will be explored using Metage2Metabo [2]. Kinetic models will be built on the basis of existing models developed at MoSAR [3,4]. Models will be constructed using experimental data produced by our partners at UMRH and MoSAR.

[1] Muñoz-Tamayo R, Davoudkhani M, Fakih I, Robles-Rodriguez CE, Rubino F, Creevey CJ, et al. Review: Towards the next-generation models of the rumen microbiome for enhancing predictive power and guiding sustainable production strategies. animal. 2023;17: 100984. doi:10.1016/J.ANIMAL.2023.100984

[2] Belcour A, Frioux C, Aite M, Bretaudeau A, Hildebrand F, Siegel A. Metage2metabo, microbiota-scale metabolic complementarity for the identification of key species. Elife. 2020;9: e61968. doi:10.7554/eLife.61968

[3] Muñoz-Tamayo R, Chagas JC, Ramin M, Krizsan SJ. Modelling the impact of the macroalgae Asparagopsis taxiformis on rumen microbial fermentation and methane production. Peer Community J. 2021;1: e7. doi:10.24072/PCJOURNAL.11

[4] Fakih I, Got J, Robles-Rodriguez CE, Siegel A, Forano E, Muñoz-Tamayo R. Dynamic genome-based metabolic modeling of