Dataset Information

Community interactions and spatial structure shape selection on antibiotic resistant lineages.

ABSTRACT: Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.

SUBMITTER: Estrela S

PROVIDER: S-EPMC6013025 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Community interactions and spatial structure shape selection on antibiotic resistant lineages.

Estrela Sylvie S Brown Sam P SP

PLoS computational biology 20180621 6

Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing ...[more]

PMID: 29927925

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Project description:A central goal of microbial ecology is to identify and quantify the forces that lead to observed population distributions and dynamics. However, these forces, which include environmental selection, dispersal, and organism interactions, are often difficult to assess in natural environments. Here, we present a method that links microbial community structures with selective and stochastic forces through highly replicated subsampling and enrichment of a single environmental inoculum. Specifically, groundwater from a well-studied natural aquifer was serially diluted and inoculated into nearly 1,000 aerobic and anaerobic nitrate-reducing cultures, and the final community structures were evaluated with 16S rRNA gene amplicon sequencing. We analyzed the frequency and abundance of individual operational taxonomic units (OTUs) to understand how probabilistic immigration, relative fitness differences, environmental factors, and organismal interactions contributed to divergent distributions of community structures. We further used a most probable number (MPN) method to estimate the natural condition-dependent cultivable abundance of each of the nearly 400 OTU cultivated in our study and infer the relative fitness of each. Additionally, we infer condition-specific organism interactions and discuss how this high-replicate culturing approach is essential in dissecting the interplay between overlapping ecological forces and taxon-specific attributes that underpin microbial community assembly.IMPORTANCE Through highly replicated culturing, in which inocula are subsampled from a single environmental sample, we empirically determine how selective forces, interspecific interactions, relative fitness, and probabilistic dispersal shape bacterial communities. These methods offer a novel approach to untangle not only interspecific interactions but also taxon-specific fitness differences that manifest across different cultivation conditions and lead to the selection and enrichment of specific organisms. Additionally, we provide a method for estimating the number of cultivable units of each OTU in the original sample through the MPN approach.

Project description:BackgroundRiverine ecosystems are one of the most important reservoirs of antibiotic resistance genes (ARGs) in the environment, but the occurrence and controlling factors of ARG distribution in different habitats of riverine ecosystems remain poorly understood. In this study, a metagenomic approach was used to characterize ARG types and their abundance in different habitats (rhizosphere soil, surface bulk soil, bottom bulk soil, and sediment) of riverine ecosystems in eastern China. Sampling sites were located along different rivers of eastern China, which are geographically isolated. Differences in bacterial communities, mobile genetic elements (MGEs), pattern and intensity of human activities, climate, and other environmental factors at the sampling sites and habitats were expected to affect ARG occurrence.ResultsARGs were observed with high variations in diversity (44-206 subtypes) and abundance (6.85-105.68 ×/Gb). There were significant south-north differences in ARG occurrence in the same habitat, except for surface bulk soil. And the significant difference was found in ARGs among four southern habitats. South-north differences in ARGs of the same habitat were mainly attributed to the combination of different occurrence frequencies and habitat selections of ARGs. Differences in ARG profiles among the four habitats in the south and the north were both mainly attributed to the different occurrence frequencies of ARGs. Bacterial communities and MGEs (Mobile genetic elements) could account for the observed variance in the resistome of riverine ecosystems across eastern China. The co-occurrences of specific ARGs with bacterial communities and MGEs were more frequent at the northern sampling sites than in the south, and co-occurrence patterns (i.e. ARGs and bacterial communities or ARGs and MGEs) varied between the habitats. Moreover, building land in all habitats, except bulk soils, showed significant positive correlations with ARG abundance.ConclusionThis study reveals a high variance in the resistome of riverine ecosystems in eastern China and its controlling factors. We appeal to the importance of assessment of ARGs in the riverine ecosystem and the need for future prevention and intervention of ARG spread.

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Community interactions and spatial structure shape selection on antibiotic resistant lineages.

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Community interactions and spatial structure shape selection on antibiotic resistant lineages.

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