Contributions des microbiotes dans l'apparition de pathologies de la prématurité // Contributions of microbiota to the onset of prematurity pathologies
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ABG-137807
ADUM-72079 |
Thesis topic | |
| 2026-04-08 | Public funding alone (i.e. government, region, European, international organization research grant) |
Université Clermont Auvergne
CLERMONT-FERRAND - Auvergne-Rhône-Alpes - France
Contributions des microbiotes dans l'apparition de pathologies de la prématurité // Contributions of microbiota to the onset of prematurity pathologies
- Biology
Microbiote, Santé, Prématurité, Bioinformatique, Entérocolite ulcéro-nécrosante, Diagnostic
Microbiota, Health, Prematurity, Bioinformatics, Necrotizing Enterocolitis, Diagnostic
Microbiota, Health, Prematurity, Bioinformatics, Necrotizing Enterocolitis, Diagnostic
Topic description
Les microbiotes associés au corps humain se mettent en place progressivement à partir de la naissance, avec une forte dynamique durant la période des 1000 premiers jours de vie. Les périodes « d'opportunités » d'acquisition des microbiotes et d'apprentissage du système immunitaire vont conditionner le bien-être et la santé tout au long de la vie. La complexité des microbiotes rend souvent difficile l'établissement de liens directs de cause à effet de l'apparition de différentes pathologies lors de dysbiose ou de perturbation du dialogue mère-enfant et enfant-environnement. L'entérocolite ulcéro-nécrosante (ECUN) est une complication digestive des nouveau-nés prématurés qui survient de manière imprévisible avec une progression fulgurante. L'ECUN a des graves conséquences, avec une mortalité entre 15 et 40% et une morbidité digestive et neurodéveloppementale à moyen et long terme. Le microbiote intestinal pourrait jouer un rôle majeur. L'objectif de la thèse est d'évaluer la contribution des microbiotes dans des pathologies de la prématurité, pour une meilleure compréhension de la pathophysiologie de ces maladies. Les échantillons qui seront analysés par des approches de métagénomique proviennent de cohortes mère-enfant constituée en collaboration avec les cliniciens des services du CHU de Clermont-Fd.
Chakoory O, Barra V, Rochette E, Blanchon L, Sapin V, Merlin E, Pons M, Gallot D, Comtet-Marre S, Peyret P. 2024. DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction. Biomark Res 12:25.
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The microbiota associated with different parts of the human body are gradually established from birth, with a strong dynamic during the first 1000 days of life. Several 'windows of opportunity' for microbiota acquisition and immune system training will condition well-being and health throughout life. The complexity of microbiota often makes it difficult to establish direct causal links between the onset of different pathologies during dysbiosis or disruption of the mother-child and child-environment dialogue. Necrotizing enterocolitis (NEC) is a digestive complication of premature newborns that occurs unpredictably with fulminant progression. NEC has serious consequences, with a mortality rate between 15 and 40% and medium- and long-term digestive and neurodevelopmental morbidity. The intestinal microbiota could play a major role. The objective of the thesis is to evaluate the contributions of the microbiota in prematurity pathologies, for a better understanding of the pathophysiology of the diseases. The samples that will be analyzed by metagenomics come from a mother-child cohort established in collaboration with the clinicians of the Clermont-Ferrand University Hospital.
Chakoory O, Barra V, Rochette E, Blanchon L, Sapin V, Merlin E, Pons M, Gallot D, Comtet-Marre S, Peyret P. 2024. DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction. Biomark Res 12:25.
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Début de la thèse : 01/10/2026
Chakoory O, Barra V, Rochette E, Blanchon L, Sapin V, Merlin E, Pons M, Gallot D, Comtet-Marre S, Peyret P. 2024. DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction. Biomark Res 12:25.
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The microbiota associated with different parts of the human body are gradually established from birth, with a strong dynamic during the first 1000 days of life. Several 'windows of opportunity' for microbiota acquisition and immune system training will condition well-being and health throughout life. The complexity of microbiota often makes it difficult to establish direct causal links between the onset of different pathologies during dysbiosis or disruption of the mother-child and child-environment dialogue. Necrotizing enterocolitis (NEC) is a digestive complication of premature newborns that occurs unpredictably with fulminant progression. NEC has serious consequences, with a mortality rate between 15 and 40% and medium- and long-term digestive and neurodevelopmental morbidity. The intestinal microbiota could play a major role. The objective of the thesis is to evaluate the contributions of the microbiota in prematurity pathologies, for a better understanding of the pathophysiology of the diseases. The samples that will be analyzed by metagenomics come from a mother-child cohort established in collaboration with the clinicians of the Clermont-Ferrand University Hospital.
Chakoory O, Barra V, Rochette E, Blanchon L, Sapin V, Merlin E, Pons M, Gallot D, Comtet-Marre S, Peyret P. 2024. DeepMPTB: a vaginal microbiome-based deep neural network as artificial intelligence strategy for efficient preterm birth prediction. Biomark Res 12:25.
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Début de la thèse : 01/10/2026
Funding category
Public funding alone (i.e. government, region, European, international organization research grant)
Funding further details
Concours pour un contrat doctoral
Presentation of host institution and host laboratory
Université Clermont Auvergne
Institution awarding doctoral degree
Université Clermont Auvergne
Graduate school
65 Sciences de la Vie, Santé, Agronomie, Environnement
Candidate's profile
Microbiologie
Caractérisation des microbiotes
Analyse des Microbiotes
Bioinformatique
Microbiology Microbiota characterization Microbiota analyses Bioinformatics
Microbiology Microbiota characterization Microbiota analyses Bioinformatics
2026-06-19
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