Interactions between strains govern the eco-evolutionary dynamics of microbial communities

  1. Akshit Goyal
  2. Leonora S Bittleston
  3. Gabriel E Leventhal
  4. Lu Lu
  5. Otto Cordero  Is a corresponding author
  1. Massachusetts Institute of Technology, United States

Abstract

Genomic data has revealed that genotypic variants of the same species, i.e., strains, coexist and are abundant in natural microbial communities. However, it is not clear if strains are ecologically equivalent, and at what characteristic genetic distance they might exhibit distinct interactions and dynamics. Here, we address this problem by tracking 10 taxonomically diverse microbial communities from the pitcher plant Sarracenia purpurea in the laboratory for more than 300 generations. Using metagenomic sequencing, we reconstruct their dynamics over time and across scales, from distant phyla to closely related genotypes. We find that most strains are not ecologically equivalent and exhibit distinct dynamical patterns, often being significantly more correlated with strains from another species than their own. Although even a single mutation can affect laboratory strains, on average, natural strains typically decouple in their dynamics beyond a genetic distance of 100 base pairs. Using mathematical consumer-resource models, we show that these taxonomic patterns emerge naturally from ecological interactions between community members, but only if the interactions are coarse-grained at the level of strains, not species. Finally, by analyzing genomic differences between strains, we identify major functional hubs such as transporters, regulators, and carbohydrate-catabolizing enzymes, which might be the basis for strain-specific interactions. Our work suggests that fine-scale genetic differences in natural communities could be created and stabilized via the rapid diversification of ecological interactions between strains.

Data availability

Raw sequencing reads are available in the NCBI Sequence Read Archive (BioSample SAMN17005333). Assembled genomes have been deposited in the NCBI GenBank database (BioProject PRJNA682646). Genome metadata and accession numbers are provided in Supplementary Table S1.

The following data sets were generated

Article and author information

Author details

  1. Akshit Goyal

    Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Leonora S Bittleston

    Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Gabriel E Leventhal

    Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Lu Lu

    Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Otto Cordero

    Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    ottox@mit.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2695-270X

Funding

Gordon and Betty Moore Foundation (GBMF4513)

  • Akshit Goyal

Human Frontiers Science Program (LT000643/2016-L)

  • Gabriel E Leventhal

James S. McDonnell Foundation (220020477)

  • Leonora S Bittleston

National Science Foundation (1655983)

  • Otto Cordero

Simons Foundation (542395)

  • Otto Cordero

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Goyal 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.

Metrics

  • 3,966
    views
  • 618
    downloads
  • 55
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Akshit Goyal
  2. Leonora S Bittleston
  3. Gabriel E Leventhal
  4. Lu Lu
  5. Otto Cordero
(2022)
Interactions between strains govern the eco-evolutionary dynamics of microbial communities
eLife 11:e74987.
https://doi.org/10.7554/eLife.74987

Share this article

https://doi.org/10.7554/eLife.74987

Further reading

    1. Ecology
    2. Neuroscience
    Kathleen T Quach, Gillian A Hughes, Sreekanth H Chalasani
    Research Article

    Prey must balance predator avoidance with feeding, a central dilemma in prey refuge theory. Additionally, prey must assess predatory imminence—how close threats are in space and time. Predatory imminence theory classifies defensive behaviors into three defense modes: pre-encounter, post-encounter, and circa-strike, corresponding to increasing levels of threat—–suspecting, detecting, and contacting a predator. Although predatory risk often varies in spatial distribution and imminence, how these factors intersect to influence defensive behaviors is poorly understood. Integrating these factors into a naturalistic environment enables comprehensive analysis of multiple defense modes in consistent conditions. Here, we combine prey refuge and predatory imminence theories to develop a model system of nematode defensive behaviors, with Caenorhabditis elegans as prey and Pristionchus pacificus as predator. In a foraging environment comprised of a food-rich, high-risk patch and a food-poor, low-risk refuge, C. elegans innately exhibits circa-strike behaviors. With experience, it learns post- and pre-encounter behaviors that proactively anticipate threats. These defense modes intensify with predator lethality, with only life-threatening predators capable of eliciting all three modes. SEB-3 receptors and NLP-49 peptides, key stress regulators, vary in their impact and interdependence across defense modes. Overall, our model system reveals fine-grained insights into how stress-related signaling regulates defensive behaviors.

    1. Ecology
    Laura Fargeot, Camille Poesy ... Blanchet Simon
    Research Article

    Understanding the relationships between biodiversity and ecosystem functioning stands as a cornerstone in ecological research. Extensive evidence now underscores the profound impact of species loss on the stability and dynamics of ecosystem functions. However, it remains unclear whether the loss of genetic diversity within key species yields similar consequences. Here, we delve into the intricate relationship between species diversity, genetic diversity, and ecosystem functions across three trophic levels – primary producers, primary consumers, and secondary consumers – in natural aquatic ecosystems. Our investigation involves estimating species diversity and genome-wide diversity – gauged within three pivotal species – within each trophic level, evaluating seven key ecosystem functions, and analyzing the magnitude of the relationships between biodiversity and ecosystem functions (BEFs). We found that, overall, the absolute effect size of genetic diversity on ecosystem functions mirrors that of species diversity in natural ecosystems. We nonetheless unveil a striking dichotomy: while genetic diversity was positively correlated with various ecosystem functions, species diversity displays a negative correlation with these functions. These intriguing antagonist effects of species and genetic diversity persist across the three trophic levels (underscoring its systemic nature), but were apparent only when BEFs were assessed within trophic levels rather than across them. This study reveals the complexity of predicting the consequences of genetic and species diversity loss under natural conditions, and emphasizes the need for further mechanistic models integrating these two facets of biodiversity.