Niche partitioning facilitates coexistence of closely related honey bee gut bacteria
- University of Lausanne, Switzerland
- ETH Zürich, Switzerland
- ETH Zurich, Switzerland
Abstract
Ecological processes underlying bacterial coexistence in the gut are not well understood. Here, we disentangled the effect of the host and the diet on the coexistence of four closely related Lactobacillus species colonizing the honey bee gut. We serially passaged the four species through gnotobiotic bees and in liquid cultures in the presence of either pollen (bee diet) or simple sugars. Although the four species engaged in negative interactions, they were able to stably coexist, both in vivo and in vitro. However, coexistence was only possible in the presence of pollen, and not in simple sugars, independent of the environment. Using metatranscriptomics and metabolomics, we found that the four species utilize different pollen-derived carbohydrate substrates indicating resource partitioning as the basis of coexistence. Our results show that despite longstanding host association, gut bacterial interactions can be recapitulated in vitro providing insights about bacterial coexistence when combined with in vivo experiments.
Data availability
The amplicon sequencing data and the RNA sequencing data are available under the NCBI Bioproject PRJNA700984 and the GEO record GSE166724 respectively.All data generated or analysed during this study are included in the manuscript and supporting files. Bacterial abundance data (CFUs) are included into Supplementary File 3, amplicon sequencing processed data are included into Supplementary File 4, RNA sequencing processed data, statistical analysis results (enrichment tests) and transcript per million data are included into Supplementary File 5-9, metabolomics analysis data are included into Supplementary File 10. All differential expression analysis results of this study are included in Supplementary File 11.
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Lactobacillus Firm5 amplicon sequencingNCBI Sequence Read Archive PRJNA700984.
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Lactobacillus Firm5 in vivo and in vitro RNA sequencingNCBI Gene Expression Omnibus GSE166724.
Article and author information
Author details
Funding
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (31003A_160345)
- Philipp Engel
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (31003A_179487)
- Andrew Quinn
- Nicolas Neuschwander
- Philipp Engel
H2020 European Research Council (714804)
- Silvia Brochet
- Philipp Engel
NCCR Microbiomes (51NF40_180575)
- Philipp Engel
Human Frontier Science Program (RGY0077/2016)
- Philipp Engel
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Karina B Xavier, Instituto Gulbenkian de Ciência, Portugal
Version history
- Preprint posted: March 12, 2021 (view preprint)
- Received: March 19, 2021
- Accepted: July 14, 2021
- Accepted Manuscript published: July 19, 2021 (version 1)
- Accepted Manuscript updated: July 22, 2021 (version 2)
- Version of Record published: August 31, 2021 (version 3)
- Version of Record updated: April 1, 2022 (version 4)
Copyright
© 2021, Brochet et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Niche partitioning facilitates coexistence of closely related honey bee gut bacteria
eLife 10:e68583.
https://doi.org/10.7554/eLife.68583
Further reading
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- Computational and Systems Biology
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Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hunting strategy requiring large brains that involve high-level cognition. However, recent findings that collaborative hunting has also been documented in smaller-brained vertebrates have placed this previous belief under strain. Here, using computational multi-agent simulations based on deep reinforcement learning, we demonstrate that decisions underlying collaborative hunts do not necessarily rely on sophisticated cognitive processes. We found that apparently elaborate coordination can be achieved through a relatively simple decision process of mapping between states and actions related to distance-dependent internal representations formed by prior experience. Furthermore, we confirmed that this decision rule of predators is robust against unknown prey controlled by humans. Our computational ecological results emphasize that collaborative hunting can emerge in various intra- and inter-specific interactions in nature, and provide insights into the evolution of sociality.
