Identifying Keystone Species in the Human Gut Microbiome from Metagenomic Timeseries Using Sparse Linear Regression

By Charles K. Fisher, Pankaj Mehta. PLoS ONE, 2014

328 citations recorded by the source corpus.

Human associated microbial communities exert tremendous influence over human health and disease. With modern metagenomic sequencing methods it is now possible to follow the relative abundance of microbes in a community over time. These microbial communities exhibit rich ecological dynamics and an important goal of microbial ecology is to infer the ecological interactions between species directly from sequence data. Any algorithm for inferring ecological interactions must overcome three major obstacles: 1) a correlation between the abundances of two species does not imply that those species are interacting, 2) the sum constraint on the relative abundances obtained from metagenomic studies makes it difficult to infer the parameters in timeseries models, and 3) errors due to experimental uncertainty, or mis-assignment of sequencing reads into operational taxonomic units, bias inferences of species interactions due to a statistical problem called “errors-in-variables”. Here we introduce an approach, Learning Interactions from MIcrobial Time Series (LIMITS), that overcomes these obstacles. LIMITS uses sparse linear regression with boostrap aggregation to infer a discrete-time Lotka-Volterra model for microbial dynamics. We tested LIMITS on synthetic data and showed that it could reliably infer the topology of the inter-species ecological interactions. We then used LIMITS to characterize the species interactions in the gut microbiomes of two individuals and found that the interaction networks varied significantly between individuals. Furthermore, we found that the interaction networks of the two individuals are dominated by distinct “keystone species”, Bacteroides fragilis and Bacteroided stercosis, that have a disproportionate influence on the structure of the gut microbiome even though they are only found in moderate abundance. Based on our results, we hypothesize that the abundances of certain keystone species may be responsible for individuality in the human gut microbiome.

Subfields: Molecular Biology, Physiology

View Paper: https://www.semanticscholar.org/paper/84aac1ad5be349f50b54abe634a9d68d7ab894b6

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Citations in the corpus

Ecology and exploration of the rare biosphere (2015, background): “Researchers observed that two moderately abundant species, Bacteroides fragilis and Bacteroides ster-coris , had a disproportionate influence on the structure of the human gut microbiome 102 .”
The Classification and Evolution of Bacterial Cross-Feeding (2019, background): “Several studies have identified and discussed candidate keystone species in the gut microbiota, often Bacteroides strains with broad metabolic capabilities, but not always strains that are at high abundances in the gut (Bäckhed et al., 2005; Ze et al., 2012, 2013; Fisher and Mehta, 2014; Cockburn an”
Holobionts as Units of Selection and a Model of Their Population Dynamics and Evolution (2018, background): “In the same vein, Fisher and Mehta (2014) estimated Lotka-Volterra interaction coefficients for the microbiomes in the guts of two persons, and presented graphs of the interaction webs of 14 microbial species.”
Microbial Hub Taxa Link Host and Abiotic Factors to Plant Microbiome Variation (2016, background): “Both indirect (via host [71]) and direct effects (via metabolites [72]) have been suggested for mechanisms of action of some microbes that cause abnormal human microbiomes.”