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Links between ruminal and plasmatic metabolites, ruminal microbiota and milk production traits of dairy ewes during 3 successive lactations

Job Type:

Supervisors: Annabelle Meynadier & Christel Marie-Etancelin

The ruminal microbiota plays a central role in the nutrition of its host, affecting milk production and animal health, towards production of rumen metabolites. More precisely, the milk contains many components synthesised from absorbed rumen metabolites in the mammary gland: ruminal volatile fatty acids are precursors of lactose and short-medium chain fatty acids, microbial essential amino acids are used for protein synthesis, and some vitamins B from bacterial origin are secreted in milk. So, the variation in rumen microbiome composition has a pronounced influence on the ruminal metabolites produced and exported in animal blood, and at the end could impact milk production and quality. What happens in sheep’s milk at a time in the production cycle where animals have very different energy statuses? The originality of this proposal is to dispose of the information to qualify the ruminal microbiota, the metabolites produced in the rumen as well as those circulating in the blood, and in fine the fine composition of ewe's milk. Moreover, these 4 sources of information were obtained on 60 animals during 3 successive lactations; these animals belonging to 2 divergent lines for milk persistency, which is a good model to study the diversity of ewes’ energy statuses The Master aims to integrate the relationship between ruminal and plasmatic metabolites of the ewes (obtained by NMR without a priori), with production, health and fine milk compositions traits, by modelling of the individual variability of those phenotypes. The characterization of the links between on one hand metabolomic traits (in rumen and blood) and on the other hand fine milk compositions, production/ health traits or ruminal microbiota will contribute to answer the following questions: - In small ruminant, can blood metabolites (other than the well-known β-hydroxybutyrate (BOH), non- esterified fatty acids (NEFA) or glycemia) be identified to characterize the energy status of dairy ewes? - Which is the link between blood metabolites and ruminal metabolites, produced by microbiota in the rumen? - Is there a "typical metabolism" for animals who better manage their energy deficiency? And does this "typical metabolism" last throughout the life of the animal? - How does the composition of the ruminal microbiota affect the amounts of metabolites observed in the rumen and blood of animals? Are they linked with milk production traits? - Is there an evolution of the fine metabolism traits when selection on milk persistence is done?

Dataset of 60 ewes recording during 3 successive lactations (from first to third lactation) belonging to divergent lines for milk persistency: - individual RMN spectra of blood (n=180) and rumen juice (n=180) to predict metabolites - Fine milk compositions (main proteins and fatty acids) predicted from MIR spectra (n=180) - Microbiota analysis (already done) (n=180), - Production traits (milk quantity, Milk fat, Milk protein, somatic cell count) - Main energetic metabolites (Glucose, NEFA, BOH) - Feed intake and bodyweight The stage of Master consists in: 1. Bioinformatic analysis of RMN spectra with ASICs package of R to obtain metabolites’ quantifications. 2. Comparisons of plasmatic and ruminal metabolites 3. Management of metabolites traits and fine milk compositions to test the lines effect and the energy status of animals (variance analysis) 4. Adapted statistical methodologies to compare groups of animals or makes links between groups of traits: principal multivariate analysis such as PCA, PLS-DA, PLS and RDA. The Master will be supervised by Mmes Annabelle Meynadier (INRAE-PHASE department) and Christel Marie-Etancelin (INRAE-GA department). The student will be located in the UMR GenPhySE on the INRAe site of Castanet-Tolosan.

Financial reward: ~ 550 euros/month

Essential skills: knowledge (or marked taste) for statistical and data management analysis; knowledge of R programming language.

Desirable skill: animal physiology and genetics


Christel Marie-Etancelin

Christel dot Marie-Etancelin at inra dot fr