Identification and characterization of the biological functions provided to the plant by the rhizospheric microbiota in response to stress

Organisation/Company

UMR de Génétique Quantitative et évolution, Le Moulon

Research Field

Chemistry » Biochemistry
Biological sciences » Biology

Researcher Profile

Recognised Researcher (R2)
Leading Researcher (R4)
First Stage Researcher (R1)
Established Researcher (R3)

Country

France

Application Deadline

20 Mar 2024 – 22:00 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Offer Starting Date

1 Oct 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The soil hosts a complex microbial ecosystem that is essential for plant growth and health. It can vary depending on plants, terroir and soil type, and environmental conditions. It has been shown that plants influence the microbiota nearby their roots through the production of compounds favouring or excluding the presence of certain microorganisms [1]. In this way, plants recruit biological functions necessary for their growth or the regulation of the pathogens. If the microbiota is selected by the plant to fulfil specific biological functions, it remains to be determined whether these functions are the same or vary among plant species. Although, functional analysis of the rhizosphere microbiota is still underdeveloped for multiple technical and analytical reasons, a better understanding of plant-microbiota interaction and the identification of the associated biological functions is required to highlight of the rhizobiome impact on plant growth. Such information could lead to the development of more sustainable agriculture by promoting plant-microorganism interactions and reducing the use of chemically derived inputs. Therefore, the development of this project, which aims to establish a robust analytical approach of the rhizospheric microbiome, and the determination of the provided proteins functionality in plant stress responses is of great interest to provide more sustainable agriculture.

The objective of this project is firstly to establish a protocol for characterizing the biological functions associated with proteins/peptides extracted from plant rhizosphere through a meta-proteomics approach. It requires overcoming two major methodological hurdles:

Rhizobium protein extraction, facilitated by the expertise of PAPPSO and recent publications [6].

Interpretation of the metaP mass spectrometry databased on approaches reported in the literature [7, 8] and the existing tools available locally.

Secondly, the characterized polypeptides will be used to identify the biological functions associated to the rhizobiote. This necessitates comparing the protein sequences to other protein orthologs already annotated and described in specific databases, as well as performing protein pattern recognition and alignment.

The final step of this project involves applying the methodological development to real samples. To accomplish this, we will utilize natural soil on which peas will be cultivated under various water stress conditions to assess the robustness of this project and highlight the influences of stress in microbiome adaptation.

This Ph D. project aims, initially, to establish a protocol for analyzing the biological functions of the soil microbiome associated with plant roots. Secondly, it will involve determining the biological functions associated with these proteins and assessing the evolution of this pattern under different stresses applied to the plant.

Such information is crucial firstly for understanding the interaction mechanisms between the plant rhizosphere and the surrounding microbiota, and secondly, for integrating this knowledge into the development of sustainable agriculture by manipulating the introduction of bacterial partners to reduce chemical inputs.

The collected samples will be prepared and analysed at the PAPPSO facility which is equipped with cutting edge LC-MS instruments. Part of the cost associated to the production of the samples and their analyses will be covered by a INRAE- BAP grant (MetaP-Rhiz). Additional funding requests are under revision.

This project is related to systems biology investigation and bio-informatics. It requires knowledge in plant biology, biochemistry, proteomics, mass spectrometry, and bio-informatics. The preferred candidate would have a degree in Life Sciences and knowledge in a computation discipline. All candidates should have a good understanding of the R language and quantitative data analysis. Candidates for whom French is not their first language will require an English level of B1 at least.

The student will be located at the “Institut Diversité, Écologie et Évolution du Vivant” (IDEEV) and will be associated to the PAPPSO team at GQE. The development of this project will require plant growing facilities and analytical equipment’s. Plant growth will be performed jointly at IPS2 and IDEEV green-house all years long helped with the technical staff available locally.

Funding category: Contrat doctoral
concours école doctorale SDSV
PHD title: Doctorat es science de la vie et de la santé
PHD Country: France

Requirements
Specific Requirements

This project is related to systems biology investigation and bio-informatics. It requires knowledge in plant biology, biochemistry, proteomics, mass spectrometry, and bio-informatics. The preferred candidate would have a degree in Life Sciences and knowledge in a computation discipline. All candidates should have a good understanding of the R language and quantitative data analysis. Candidates for whom French is not their first language will require an English level of B1 at least

Additional Information
Work Location(s)

Number of offers available

1

Company/Institute

UMR de Génétique Quantitative et évolution, Le Moulon

Country

France

City

Gif sur Yvette

Geofield

Where to apply

Website

https://www.abg.asso.fr/fr/candidatOffres/show/id_offre/121003

Contact

Website

http://moulon.inra.fr/

STATUS: EXPIRED