Deadline for full application: December 15th, 2013
Interviews: March, 2014
Start of the Ph.D.: October 1st, 2014
Department: Infection and Epidemiology
Title of the PhD project: Mechanisms of maternal-fetal infection by Listeria monocytogenes
Name of the lab: Biology of Infection Unit
Head of the lab: Marc Lecuit, MD PhD
PhD advisor: Marc Lecuit
Email address: firstname.lastname@example.org
Web site address of the lab: http://www.pasteur.fr/research/biu
Doctoral school affiliation and University: B3MI doctoral school, Paris-Diderot University
Presentation of the laboratory and its research topics: Our laboratory studies the biology of infection. One of our main objectives is to decipher the molecular mechanisms underlying microbial targeting and crossing of host barriers, such as the intestinal, blood-brain and placental barriers. Our approaches combine in vitro, ex vivo and in vivo models to study three different microorganisms associated with CNS and neonatal infections: Listeria monocytogenes (Lm), Streptococcus agalactiae and Chikungunya virus. Using these model microorganisms, we have discovered new mechanisms accounting for their pathogenicity in human and revealed new biological principles underlying host-microbe interactions.
Description of the project: Human maternal-fetal (MF) listeriosis is a deadly infection for the fetus and a major cause of neonatal sepsis. Our laboratory has discovered the key roles of InlA and InlB, two proteins of Lm, in placental targeting and neonatal listeriosis (Lecuit et al., PNAS 2004; Disson et al., Nature 2008). We have also recently identified a specific Lm clinical clone that is associated with human MF infection. The first goal of this project will be to characterize the bacterial factors that confer to this clone its enhanced MF tropism. A recent study (Koren et al, Cell 2012) has shown that gut microbiota changes during human pregnancy modify host metabolism and immunity. The second and complementary goal of this project will therefore be to study the role of microbiota changes on host susceptibility to MF listeriosis. The PhD student will first confirm experimentally in a humanized mouse model we have generated the enhanced MF tropism of the Lm clinical clone associated with human MF listeriosis, compared to that of a reference strain. He/She will generate a bacterial mutant library derived from the MF clinical clone and identify the Lm genes involved in MF infection by next generation sequencing. Isogenic deletion mutants will then be generated and tested for their ability to target and cross the placenta. They will be studied in in vivo, ex vivo and in vitro models of infection and compared to the wild type parental strain. He/She will analyze placental infection by bacterial quantification and tissue imaging, and analyze placental barrier crossing by real-time microscopy. The contribution of microbiota changes on the pregnant host susceptibility to MF infection will be studied by associating germfree pregnant animals with bacteria representative of first or third trimester microbiota, and challenging them orally with Lm. Both immune responses and placental infection will be assessed and functionally correlated to microbiota changes. This project will allow deciphering the precise mechanisms of Lm MF tropism, both from the bacterial and host sides, as well as better understanding the physiology of pregnancy and the susceptibility of the pregnant host to infection.
- Disson O, Grayo S, Huillet E, Nikitas G, Langa-Vives F, Dussurget O, Ragon M, Le Monnier A, Babinet C, Cossart P, Lecuit M*. Conjugated action of two species-specific invasion proteins for fetoplacental listeriosis. Nature 2008 Oct 23;455(7216):1114-8
- Lecuit M*, Nelson DM, Smith SD, Khun H, Huerre M, Vacher-Lavenu MC, Gordon JI, Cossart P. Targeting and crossing of the human maternofetal barrier by Listeria monocytogenes: role of internalin interaction with trophoblast E-cadherin. Proc Natl Acad Sci USA 2004 Apr 20;101(16):6152-7
Keywords: Listeria, placenta, microbiology, cell biology, mutagenesis, real-time imaging, microbiota