[PhD’s Corner] 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

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, Inra MIA Toulouse
  • Co-supervisors: Rémi Servien, Inra InTheRes Toulouse, Laurence Liaubet, Inra GenPhySE Toulouse, Hélène Quesnel, Inra PEGASE Rennes
  • Funding: #DigitAg – Inra
  • #DigitAg: Axis 5Challenges 2 & 4

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


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.


Contact: gaelle.lefort [AT] inra.fr​

Communications / Publications


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., 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/