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Heumel S, de Rezende Rodovalho V, Urien C, Specque F, Brito Rodrigues P, Robil C, Delval L, Sencio V, Descat A, Deruyter L, Ferreira S, Gomes Machado M, Barthelemy A, Angulo FS, Haas JT, Goosens JF, Wolowczuk I, Grangette C, Rouillé Y, Grimaud G, Lenski M, Hennart B, Ramirez Vinolo MA, Trottein F. Shotgun metagenomics and systemic targeted metabolomics highlight indole-3-propionic acid as a protective gut microbial metabolite against influenza infection. Gut Microbes 2024; 16:2325067. [PMID: 38445660 PMCID: PMC10936607 DOI: 10.1080/19490976.2024.2325067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 02/26/2024] [Indexed: 03/07/2024] Open
Abstract
The gut-to-lung axis is critical during respiratory infections, including influenza A virus (IAV) infection. In the present study, we used high-resolution shotgun metagenomics and targeted metabolomic analysis to characterize influenza-associated changes in the composition and metabolism of the mouse gut microbiota. We observed several taxonomic-level changes on day (D)7 post-infection, including a marked reduction in the abundance of members of the Lactobacillaceae and Bifidobacteriaceae families, and an increase in the abundance of Akkermansia muciniphila. On D14, perturbation persisted in some species. Functional scale analysis of metagenomic data revealed transient changes in several metabolic pathways, particularly those leading to the production of short-chain fatty acids (SCFAs), polyamines, and tryptophan metabolites. Quantitative targeted metabolomics analysis of the serum revealed changes in specific classes of gut microbiota metabolites, including SCFAs, trimethylamine, polyamines, and indole-containing tryptophan metabolites. A marked decrease in indole-3-propionic acid (IPA) blood level was observed on D7. Changes in microbiota-associated metabolites correlated with changes in taxon abundance and disease marker levels. In particular, IPA was positively correlated with some Lactobacillaceae and Bifidobacteriaceae species (Limosilactobacillus reuteri, Lactobacillus animalis) and negatively correlated with Bacteroidales bacterium M7, viral load, and inflammation markers. IPA supplementation in diseased animals reduced viral load and lowered local (lung) and systemic inflammation. Treatment of mice with antibiotics targeting IPA-producing bacteria before infection enhanced viral load and lung inflammation, an effect inhibited by IPA supplementation. The results of this integrated metagenomic-metabolomic analysis highlighted IPA as an important contributor to influenza outcomes and a potential biomarker of disease severity.
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Affiliation(s)
- Séverine Heumel
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | | | | | - Florian Specque
- Biomathematica, Rue des Aloes, Quartier Balestrino, Ajaccio, France
| | - Patrícia Brito Rodrigues
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
- Laboratory of Immunoinflammation, Institute of Biology, University of Campinas (UNICAMP), Campinas, Brazil
| | - Cyril Robil
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Lou Delval
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Valentin Sencio
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Amandine Descat
- Univ. Lille, CHU Lille, EA 7365 – GRITA – Groupe de Recherche sur les formes Injectables et les Technologies Associées, Lille, France
| | - Lucie Deruyter
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | | | - Marina Gomes Machado
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Adeline Barthelemy
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Fabiola Silva Angulo
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Joel. T Haas
- Univ. Lille, INSERM, CHU Lille, Institut Pasteur de Lille, Lille, France
| | - Jean François Goosens
- Univ. Lille, CHU Lille, EA 7365 – GRITA – Groupe de Recherche sur les formes Injectables et les Technologies Associées, Lille, France
| | - Isabelle Wolowczuk
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Corinne Grangette
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Yves Rouillé
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
| | - Ghjuvan Grimaud
- Biomathematica, Rue des Aloes, Quartier Balestrino, Ajaccio, France
| | - Marie Lenski
- Univ. Lrille, CHU Lille, Service de toxicologie et Génopathies, ULR 4483 – IMPECS – IMPact de l’Environnement Chimique sur la Santé humaine, Lille, France
| | - Benjamin Hennart
- Univ. Lrille, CHU Lille, Service de toxicologie et Génopathies, ULR 4483 – IMPECS – IMPact de l’Environnement Chimique sur la Santé humaine, Lille, France
| | | | - François Trottein
- Univ. Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 – UMR 9017 – CIIL – Center for Infection and Immunity of Lille, Lille, France
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Delval L, Hantute-Ghesquier A, Sencio V, Flaman JM, Robil C, Angulo FS, Lipskaia L, Çobanoğlu O, Lacoste AS, Machelart A, Danneels A, Corbin M, Deruyter L, Heumel S, Idziorek T, Séron K, Sauve F, Bongiovanni A, Prévot V, Wolowczuk I, Belouzard S, Saliou JM, Gosset P, Bernard D, Rouillé Y, Adnot S, Duterque-Coquillaud M, Trottein F. Removal of senescent cells reduces the viral load and attenuates pulmonary and systemic inflammation in SARS-CoV-2-infected, aged hamsters. Nat Aging 2023; 3:829-845. [PMID: 37414987 PMCID: PMC10353934 DOI: 10.1038/s43587-023-00442-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 05/24/2023] [Indexed: 07/08/2023]
Abstract
Older age is one of the strongest risk factors for severe COVID-19. In this study, we determined whether age-associated cellular senescence contributes to the severity of experimental COVID-19. Aged golden hamsters accumulate senescent cells in the lungs, and the senolytic drug ABT-263, a BCL-2 inhibitor, depletes these cells at baseline and during SARS-CoV-2 infection. Relative to young hamsters, aged hamsters had a greater viral load during the acute phase of infection and displayed higher levels of sequelae during the post-acute phase. Early treatment with ABT-263 lowered pulmonary viral load in aged (but not young) animals, an effect associated with lower expression of ACE2, the receptor for SARS-CoV-2. ABT-263 treatment also led to lower pulmonary and systemic levels of senescence-associated secretory phenotype factors and to amelioration of early and late lung disease. These data demonstrate the causative role of age-associated pre-existing senescent cells on COVID-19 severity and have clear clinical relevance.
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Affiliation(s)
- Lou Delval
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Aline Hantute-Ghesquier
- Université de Lille, CNRS, INSERM, CHU Lille, UMR9020-U1277, Institut Pasteur de Lille-CANTHER, Lille, France
| | - Valentin Sencio
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Jean Michel Flaman
- Université de Lyon, CNRS, INSERM, U1052-UMR 5286, Centre de Recherche en Cancérologie de Lyon, Centre Léon Bérard, Lyon, France
| | - Cyril Robil
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Fabiola Silva Angulo
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Larissa Lipskaia
- Université de Paris-Est Créteil, INSERM U955, Institut Mondor de Recherche Biomédicale, Créteil, France
| | - Ozmen Çobanoğlu
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Anne-Sophie Lacoste
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41-UAR 2014, Platforms Lille in Biology & Health, Lille, France
| | - Arnaud Machelart
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Adeline Danneels
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Mathieu Corbin
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Lucie Deruyter
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Séverine Heumel
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Thierry Idziorek
- Université de Lille, CNRS, INSERM, CHU Lille, UMR9020-U1277, Institut Pasteur de Lille-CANTHER, Lille, France
| | - Karin Séron
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Florent Sauve
- Université de Lille, INSERM, CHU Lille, U1172-UMR 9017, Lille Neuroscience & Cognition Research Center, Lille, France
| | - Antonino Bongiovanni
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41-UAR 2014, Platforms Lille in Biology & Health, Lille, France
| | - Vincent Prévot
- Université de Lille, INSERM, CHU Lille, U1172-UMR 9017, Lille Neuroscience & Cognition Research Center, Lille, France
| | - Isabelle Wolowczuk
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Sandrine Belouzard
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Jean-Michel Saliou
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, US 41-UAR 2014, Platforms Lille in Biology & Health, Lille, France
| | - Philippe Gosset
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - David Bernard
- Université de Lyon, CNRS, INSERM, U1052-UMR 5286, Centre de Recherche en Cancérologie de Lyon, Centre Léon Bérard, Lyon, France
| | - Yves Rouillé
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France
| | - Serge Adnot
- Université de Paris-Est Créteil, INSERM U955, Institut Mondor de Recherche Biomédicale, Créteil, France
| | - Martine Duterque-Coquillaud
- Université de Lille, CNRS, INSERM, CHU Lille, UMR9020-U1277, Institut Pasteur de Lille-CANTHER, Lille, France
| | - François Trottein
- Université de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR 9017, Center for Infection and Immunity of Lille, Lille, France.
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Bickett TE, McLean J, Creissen E, Izzo L, Hagan C, Izzo AJ, Silva Angulo F, Izzo AA. Characterizing the BCG Induced Macrophage and Neutrophil Mechanisms for Defense Against Mycobacterium tuberculosis. Front Immunol 2020; 11:1202. [PMID: 32625209 PMCID: PMC7314953 DOI: 10.3389/fimmu.2020.01202] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Accepted: 05/14/2020] [Indexed: 12/16/2022] Open
Abstract
The live attenuated Mycobacterium bovis strain, Bacille Calmette Guérin (BCG) is a potent innate immune stimulator. In the C57BL/6 mouse model of tuberculosis, BCG vaccination leads to a significant reduction of Mycobacterium tuberculosis burden after aerogenic infection. Our studies indicated that BCG induced protection against pulmonary tuberculosis was independent of T cells and present as early as 7 days after vaccination. This protection showed longevity, as it did not wane when conventional T cell and TNF-α deficient mice were infected 30 days post-vaccination. As BCG induced mycobacterial killing after 7 days, this study investigated the contributions of the innate immune system after BCG vaccination to better understand mechanisms required for mycobacterial killing. Subcutaneous BCG inoculation resulted in significant CD11b+F4/80+ monocyte subset recruitment into the lungs within 7 days. Further studies revealed that killing of mycobacteria was dependent on the viability of BCG, because irradiated BCG did not have the same effect. Although others have identified BCG as a facilitator of trained innate immunity, we found that BCG reduced the mycobacterial burden in the absence of mechanisms required for trained innate immunity, highlighting a role for macrophages and neutrophils for vaccine induced killing of M. tuberculosis.
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Affiliation(s)
- Thomas E Bickett
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Jennifer McLean
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Elizabeth Creissen
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Linda Izzo
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Cassidy Hagan
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Antonio J Izzo
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Fabiola Silva Angulo
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
| | - Angelo A Izzo
- Department of Microbiology Immunology and Pathology, Cell and Molecular Biology, Colorado State University, Fort Collins, CO, United States
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