Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping
Abstract A microbiome’s composition, stability, and response to perturbations are governed by its community interaction matrix, typically quantified through pairwise competition. However, in natural environments, microbes encounter multispecies interactions, complex conditions, and unculturable memb...
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61368-y |
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| author | Melis Gencel Gisela Marrero Cofino Cang Hui Zahra Sahaf Louis Gauthier Chloé Matta David Gagné-Leroux Derek K. L. Tsang Dana P. Philpott Sheela Ramathan Alfredo Menendez Shimon Bershtein Adrian W. R. Serohijos |
| author_facet | Melis Gencel Gisela Marrero Cofino Cang Hui Zahra Sahaf Louis Gauthier Chloé Matta David Gagné-Leroux Derek K. L. Tsang Dana P. Philpott Sheela Ramathan Alfredo Menendez Shimon Bershtein Adrian W. R. Serohijos |
| author_sort | Melis Gencel |
| collection | DOAJ |
| description | Abstract A microbiome’s composition, stability, and response to perturbations are governed by its community interaction matrix, typically quantified through pairwise competition. However, in natural environments, microbes encounter multispecies interactions, complex conditions, and unculturable members. Moreover, evolutionary and ecological processes occur on overlapping timescales, making intra-species clonal diversity a critical but poorly understood factor influencing community interactions. Here, we present Dynamic Covariance Mapping (DCM), a general approach to infer microbiome interaction matrices from abundance time-series data. By combining DCM with high-resolution chromosomal barcoding, we quantify inter- and intra-species interactions during E. coli colonization in the mouse gut under three contexts: germ-free, antibiotic-perturbed, and innate microbiota. We identify distinct temporal phases in susceptible communities: (1) destabilization upon E. coli invasion, (2) partial recolonization of native bacteria, and (3) a quasi-steady state where E. coli sub-lineages coexist with resident microbes. These phases are shaped by specific interactions between E. coli clones and community members, emphasizing the dynamic and lineage-specific nature of microbial networks. Our results reveal how ecological and evolutionary dynamics jointly shape microbiome structure over time. The DCM framework provides a scalable method to dissect complex community interactions and is broadly applicable to bacterial ecosystems both in vitro and in situ. |
| format | Article |
| id | doaj-art-eb9ab512e4cb461f8281caf77c4d77f7 |
| institution | DOAJ |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-eb9ab512e4cb461f8281caf77c4d77f72025-08-20T03:05:05ZengNature PortfolioNature Communications2041-17232025-07-0116112010.1038/s41467-025-61368-yQuantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mappingMelis Gencel0Gisela Marrero Cofino1Cang Hui2Zahra Sahaf3Louis Gauthier4Chloé Matta5David Gagné-Leroux6Derek K. L. Tsang7Dana P. Philpott8Sheela Ramathan9Alfredo Menendez10Shimon Bershtein11Adrian W. R. Serohijos12Department of Biochemistry, Université de MontréalDépartement de microbiologie et d’infectiologie, Université de SherbrookeCentre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch UniversityDepartment of Biochemistry, Université de MontréalDepartment of Biochemistry, Université de MontréalDepartment of Biochemistry, Université de MontréalDepartment of Biochemistry, Université de MontréalDepartment of Immunology, University of TorontoDepartment of Immunology, University of TorontoDépartement d’immunologie et biologie cellulaire, Université de SherbrookeDépartement de microbiologie et d’infectiologie, Université de SherbrookeDepartment of Life Sciences, Ben-Gurion University of the NegevDepartment of Biochemistry, Université de MontréalAbstract A microbiome’s composition, stability, and response to perturbations are governed by its community interaction matrix, typically quantified through pairwise competition. However, in natural environments, microbes encounter multispecies interactions, complex conditions, and unculturable members. Moreover, evolutionary and ecological processes occur on overlapping timescales, making intra-species clonal diversity a critical but poorly understood factor influencing community interactions. Here, we present Dynamic Covariance Mapping (DCM), a general approach to infer microbiome interaction matrices from abundance time-series data. By combining DCM with high-resolution chromosomal barcoding, we quantify inter- and intra-species interactions during E. coli colonization in the mouse gut under three contexts: germ-free, antibiotic-perturbed, and innate microbiota. We identify distinct temporal phases in susceptible communities: (1) destabilization upon E. coli invasion, (2) partial recolonization of native bacteria, and (3) a quasi-steady state where E. coli sub-lineages coexist with resident microbes. These phases are shaped by specific interactions between E. coli clones and community members, emphasizing the dynamic and lineage-specific nature of microbial networks. Our results reveal how ecological and evolutionary dynamics jointly shape microbiome structure over time. The DCM framework provides a scalable method to dissect complex community interactions and is broadly applicable to bacterial ecosystems both in vitro and in situ.https://doi.org/10.1038/s41467-025-61368-y |
| spellingShingle | Melis Gencel Gisela Marrero Cofino Cang Hui Zahra Sahaf Louis Gauthier Chloé Matta David Gagné-Leroux Derek K. L. Tsang Dana P. Philpott Sheela Ramathan Alfredo Menendez Shimon Bershtein Adrian W. R. Serohijos Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping Nature Communications |
| title | Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping |
| title_full | Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping |
| title_fullStr | Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping |
| title_full_unstemmed | Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping |
| title_short | Quantifying the intra- and inter-species community interactions in microbiomes by dynamic covariance mapping |
| title_sort | quantifying the intra and inter species community interactions in microbiomes by dynamic covariance mapping |
| url | https://doi.org/10.1038/s41467-025-61368-y |
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