Shotgun metagenomics and systemic targeted metabolomics highlight indole-3-propionic acid as a protective gut microbial metabolite against influenza infection

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.

KEYWORDS:

• Influenza
• gut microbiota
• shotgun metagenomics
• metabolomics
• indole-3-propionic acid
• disease severity

Abbreviations

IAV, influenza A virus; LBP, lipopolysaccharide-binding protein; SCFAs, short-chain fatty acids; RT-PCR, reverse transcription polymerase chain reaction; IL, interleukin; TMAO, trimethylamine N-oxide; IPA, indole-3-propionic acid; IAA, indole-3-acetic acid.

Acknowledgments

We would like to thank the members of the animal facility (PLETHA) for their assistance. GenoScreen (Lille, France) and Biomnigen (Besançon, France) are acknowledged for shotgun and 16S rRNA sequencing, respectively. Téo Fournier (GenoScreen) and Fabrice Bouilloux (Biomnigen) are acknowledged for submitting raw sequence data from the National Center for Biotechnology Information. Aurore Desmons and Antonin Lamaziere (AHP Paris) are acknowledged for discussion on IPA quantification assays. Jerome Breton (4P-Pharma, Lille) is acknowledged for the gift of the body temperature receivers.

Author contributions

FT conceived and supervised the study. VS and FT designed the experiment. VS and SH performed animal experiments. AD, JTH, and JFG supervised the metabolomic analysis, and VRR, CU, FS, SF, CG, GG, and MARV supervised the gut microbiota composition analysis. ML and BH quantified tryptophan metabolites using LC-MS/MS. VS, NB, CR, LD, SH, CG, HS, IW, and FT analyzed the data. SH, LD, and CR performed the RT-PCR and ELISA, respectively. PBR, FSA. VS, VRR, CU, PBR and FT designed the figures. FT: drafted the manuscript. All authors revised the manuscript and provided critical comments. FT obtained funding.

Disclosure statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Data availability statement

The sequence datasets generated in this study are publicly available at https://www.ncbi.nlm.nih.gov/bioproject/PRJNA908759 and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA105451. iMGMC (https://zenodo.org/record/3631711 and https://github.com/tillrobin/iMGMC). The file used was called “GeneID,” and the KOs annotations are available from the github (KEGG KofamScan 03/20). Reference genome (for decontamination): Assembly GCF_000001635.26, available at https://www.ncbi.nlm.nih.gov/assembly/GCF_000001635.26/.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/19490976.2024.2325067

Additional information

Funding

This work was supported in part by the Institut National de la Santé et de la Recherche Médicale (Inserm), Centre National de la Recherche Scientifique (CNRS), University of Lille, Pasteur Institute of Lille. This project was cofounded by the French National Research Agency (Agence Nationale de la Recherche, ANR): AAP générique 2022, ANR-23-CE15-0014-01, GUTSY) (FT), the React-EU COVID2I (programme opérationnel FEDER/FSE/IEJ Nord-Pas de Calais) (FT), and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, 2018/15313-8) (MARV).VS and AB received salary support (PhD fellowship) from Lille University and Fondation pour la Recherche Médicale (FRM, France). PBR received fellowships from FAPESP (2019/14342-7 and 2022/02058-5). JTH is a recipient of an ERC Starting Grant (Metabo3DC-101042759) and received support from ANR (LabEx EGID ANR-10-LABX-0046). FT received salary support from the CNRS.