Research

Isabelle Hautefort

Postdoctoral Scientist
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Biography

Contact details:

isabelle.hautefort@earlham.ac.uk

Isabelle is a senior post-doc scientist working on the experimental validation and screening of host-microbe interactions in the gut. She specifically focuses on the development of gut organoid systems for high-throughput detection of microbial effects on host intestinal cells.
 
Isabelle graduated in 1993 in Agronomy Engineering, focusing upon human nutrition. She gained her MSc in Gut Microbial Ecology and then her PhD in Gut Microbial Ecology and Pathogen Exclusion at University Paris XI, Pharmacy faculty, Châtenay-Malabry, and INRA, Jouy-en-Josas, France.

For the first ten years of her post-doctoral research with Prof Jay Hinton, Isabelle studied the foodborne pathogen Salmonella enterica serovar Typhimurium - how it adapts to the host intracellular environment during infection - and she published the first intra‑epithelial transcriptomic profile of Salmonella Typhimurium.
 
She then joined the Group of Prof Simon Carding at the Quadram Institute (then known as as the Institute of Food Research) for eight years where she investigated the role that intra-epithelial lymphocytes have on various gut barrier functions, including the production of antimicrobials by Paneth cells and how pathogens or commensals impact on this regulation. In 2014, Isabelle started collaborating with Tamas on one of his research projects that required her expertise in cell culture‑based Salmonella infection models; providing imaging as well as qPCR gene expression assays.
 
Isabelle joined the Korcsmáros Group in 2017 to continue her involvement in experimental validation of network and systems biology‑related projects, focusing on intestinal host-microbe interactions (in particular pathogen and intestinal autophagy regulation) using transcriptomic approaches to monitor gene expression of both the pathogens and the infected host. She is also supervising students and other research associates in designing and performing experimental validation of computational prediction of  host/microbes protein‑protein interactions.