[Thesis defended] Gaëlle Lefort: Integrating metabolomic data by quantification of high throughput data. Application to perinatal mortality in pigs

Gaëlle is one of the #DigitAg co-funded PhDs

Gaëlle defended her thesis on Friday 2nd July at 9.15 (local time) .


Integrating metabolomic data by quantification of high throughput data. Application to perinatal mortality in pigs

  • Start Date: September 2018
  • University: Toulouse University 1 Capitole
  • PhD School: MITT (Mathématiques, Informatique, Télécommunications de Toulouse)
  • Field(s): Mathematics and applications
  • Doctoral Thesis Advisor: Nathalie Vialaneix, Inrae, UR MIAT
  • Co-supervisors: Rémi Servien, Inrae, InTheRes Toulouse, Laurence Liaubet, Inrae, GenPhySE Toulouse, Hélène Quesnel, Inrae, PEGASE Rennes
  • Funding: #DigitAg – Inrae
  • #DigitAg: Axis 5Challenges 2 & 4

Keywords: Metabolomics, Variable selection, Multiple testing, Data integration

Abstract:

Metabolomics data are an affordable way to access fine phenotyping information. They can be acquired from simple blood (plasma), amniotic fluid or urine samples using NMR (Nuclear Magnetic Resonance) high throughput technic. However, due to a lack of method to properly link acquired spectra to metabolite quantification, they are largely underexploited. This PhD proposes to develop a new fast and efficient approach to use metabolomics NMR spectra for metabolite quantification. The results will be validated with direct quantification of metabolites already available (as well as metabolite spectra) from the ANR project PORCINET ANR-09-GENM-005. This project addresses the issue of perinatal mortality in pigs and the numerous datasets acquired during the project provide a rich framework to prove the efficiency of our approach for precision farming. In particular, metabolite quantification will be integrated with many phenotypes (morphology, allometry, and physiology), proteomic and transcriptomic data obtained in a complex experimental design (4 genotypes x 2 late gestational stages) in order to better understand the biological processes involved in perinatal survival of pigs.

Jury compound:

​​​​M. Patrick GIRAUDEAU ​Université de Nantes ​Rapporteur
​​Mme Kim-Anh LE CAO ​University of Melbourne ​Rapporteure
​Mme Laurence LIAUBET ​​INRAE ​Co-directrice de thèse
​Mme Hélène QUESNEL ​​​INRAE ​​Invitée
​Mme Anne RUIZ-GAZEN ​​Toulouse School of Economics ​Examinatrice
​​M. Rémi SERVIEN ​​INRAE ​Co-directeur de thèse
​​M. Etienne THEVENOT ​CEA ​​Examinateur
​M. Jaap VAN MILGEN ​​​INRAE ​​Examinateur
​Mme Nathalie VIALANEIX ​​INRAE

​Directrice de thèse

Contact: gaelle.lefort [AT] inrae.fr​


Communications / Publications

Articles

Tardivel, P., Canlet, C., Lefort, G., Tremblay-Franco, M., Debrauwer, L., Concordet, D., Servien, R. (2017). ASICS : an automatic method for identification and quantification of metabolites in NMR 1D 1H spectra. Metabolomics. https://doi.org/10.1007/s11306-017-1244-5

Lefort, G., Servien, R., Quesnel, H. et al. (2020), The maturity in fetal pigs using a multi-fluid metabolomic approach, https://doi.org/10.1038/s41598-020-76709-8

Lefort G., Liaubet L., Marty-Gasset N., Canlet C., Vialaneix N., Servien R. (2021) Joint Automatic Metabolite Identification and Quantification of a Set of 1H NMR Spectra

Conferences

Lefort, G., Liaubet, L., Canlet, C., Villa-Vialaneix, N., Servien, R. (2018). ASICS identifier et quantifier des métabolites à partir d’un spectre RMN 1H, 51èmes Journées de Statistique de la SFdS – https://hal.inrae.fr/hal-02737497/document

Lefort, G., Liaubet, L., Canlet, C., Vialaneix, N., Servien, R. (2018). ASICS identification and quantification of metabolites in complex 1H NMR spectra. European Conference on Computational Biology (ECCB 2018). Poster.

Gaëlle Lefort, Nathalie Vialaneix, Helene Quesnel, Marie–Christine Pere, Yvon Billon, et al (2020) Étude de la maturité des porcelets en fin de gestation par une approche métabolomique multifluide, 52. Journées de la Recherche Porcine, Feb 2020, Paris, France. IFIP – Institut du Porc – https://hal.archives-ouvertes.fr/hal-02479994/