Longitudinal linked read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment

Abstract

Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal dynamics of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We find that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. Interestingly, genetic changes frequently occur in species without obvious changes in relative species abundance, emphasizing the importance of monitoring diversity below the species level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.

Repeatable ecological dynamics govern response of experimental community to antibiotic pulse perturbation

“…However, connecting these processes may not always be straightforward. 39 Similar to our finding, in a recent analysis of longitudinal linked-read sequencing data from human gut microbiota subjected to antibiotic treatment, antibiotic resistance mutations were found to sweep to high frequencies in the populations of single species without necessarily resulting in an increased abundance of the species in the community 18 . In a microbial community, species sorting and adaptive mutations occur simultaneously in multiple species, and all these factors have the potential to interact, making it challenging to disentangle ecological from evolutionary processes.…”

“…Intriguingly, in the case of antibiotics, while there is an extensive number of studies on both the species compositional effects of antibiotic perturbation on the microbiome and the genetics of antibiotic resistance in individual species, both aspects have rarely been analyzed together. Furthermore, high-throughput sequencing based approaches allowing the investigation of mutations in longitudinal microbiome data have focused on in vivo and field samples where the species are uncultured and the pre-existing traits of the species cannot be explicitly estimated 18 . This confounds the ability to assess the importance of evolution relative to species sorting.…”

Understanding the impact of antibiotic perturbation on the human microbiome

“…They found that antibiotic-naive children harbored increased strain-level diversity of Bacteroides fragilis, a key commensal important for immune education and bacterial tolerance [28,89]. Harboring more strains of the same species is believed to be a component of a resilient microbiome as well as providing different functions [37,90,91]. It is likely possible to achieve microbiome health and resilience to perturbation either by increased strain-level diversity within a species or by maintenance of a diverse array of different species.…”

Uniting Community Ecology and Evolutionary Rescue Theory: Community-Wide Rescue Leads to a Rapid Loss of Rare Species

“…Experimentalists are examining evolutionary rescue in a community context. The examples include microbiomes adapting to antibiotic treatment (Roodgar et al, 2019); soil microbial communities adapting to herbicides (Low-Décarie et al, 2015) and lacustrine plankton communities adapting to acidification (Bell et al, 2019). There are many more situations in which CWR could be considered as a potential mechanism for rare species loss, as many ecosystems face irreversible human induced environmental change on a community-wide level (Vitousek et al, 1997).…”

“…Whilst many models exist that study how a population of a single species, or a community composed of two species, adapts to environmental change (Hoffmann and Sgrò, 2011;Martin et al, 2013;Northfield and Ives, 2013;Osmond and De Mazancourt, 2013;Cortez and Yamamichi, 2019), fewer models exist that describe the response of an entire community composed of multiple species to an altered environment, although there are some examples (De Mazancourt et al, 2008;Bell, 2017;Lasky, 2019). Furthermore, empirical results, describing community wide adaptation, such as those presented by Bell and Gonzalez (2011), Low-Décarie et al (2015), Bell et al (2019), and Roodgar et al (2019), are clearly calling for such models.…”