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Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture. Significance Although metabolic interactions have long been implicated in the assembly of microbial communities, their general prevalence has remained largely unknown. In this study, we systematically survey, by using a metabolic modeling approach, the extent of resource competition and metabolic cross-feeding in over 800 microbial communities from diverse habitats. We show that interspecies metabolic exchanges are widespread in natural communities, and that such exchanges can provide group advantage under nutrient-poor conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence. The presented methodology and mechanistic insights have broad implications for understanding compositional variation in natural communities as well as for facilitating the design of synthetic microbial communities.

Microbial consortia are emerging as potential platforms for biochemicals production with complex metabolic pathways.Elimination of the carbon competition has been adopted to avoid the competition interaction within microbial cocultures.Elimination of inhibitors from metabolic byproducts can promote the cooperation between members.Crossfeeding and quorum-sensing circuit design can improve the stability and controllability of microbial population.Spatial segregation can easily alter the microbial composition and create individual ecological niches in microbial consortia. Microbial consortia can complete otherwise arduous tasks through the cooperation of multiple microbial species. This concept has been applied to produce commodity chemicals, natural products, and biofuels. However, metabolite incompatibility and growth competition can make the microbial composition unstable, and fluctuating microbial populations reduce the efficiency of chemical production. Thus, controlling the populations and regulating the complex interactions between different strains are challenges in constructing stable microbial consortia. This Review discusses advances in synthetic biology and metabolic engineering to control social interactions within microbial cocultures, including substrate separation, byproduct elimination, crossfeeding, and quorum-sensing circuit design. Additionally, this Review addresses interdisciplinary strategies to improve the stability of microbial consortia and provides design principles for microbial consortia to enhance chemical production.

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR. Obtaining data on antimicrobial resistance (AMR) from healthy human populations is difficult. Here, Hendriksen et al. use metagenomic analysis to obtain AMR data from untreated sewage from 79 sites in 60 countries, finding correlations with socio-economic, health and environmental factors.

We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.

Cellular interactions are a major driver for the assembly and functioning of microbial communities. Their strengths are shown to be highly variable in nature; however, it is unclear how such variations regulate community behaviors. Here we construct synthetic Lactococcus lactis consortia and mathematical models to elucidate the role of interaction variability in ecosystem succession and to further determine if casting variability into modeling empowers bottom-up predictions. For a consortium of bacteriocin-mediated cooperation and competition, we find increasing the variations of cooperation, from either altered labor partition or random sampling, drives the community into distinct structures. When the cooperation and competition are additionally modulated by pH, ecosystem succession becomes jointly controlled by the variations of both interactions and yields more diversified dynamics. Mathematical models incorporating variability successfully capture all of these experimental observations. Our study demonstrates interaction variability as a key regulator of community dynamics, providing insights into bottom-up predictions of microbial ecosystems. Cellular interactions are a major driver of microbial communities and shown highly variable in strength. Here the authors construct synthetic consortia and mathematical models to elucidate the role of interaction variability in driving ecosystem succession.

Background Endosymbiotic bacteria inhabit a variety of arthropods including ticks and may have multiple effects on the host’s survival, reproduction or pathogen acquisition and transmission. Rhipicephalus haemaphysaloides is one of the most widely distributed tick species in China. The symbiotic bacteria composition and their impacts to R. haemaphysaloides ticks have not been studied. The present study investigated the composition of microbial community in R. haemaphysaloides ticks and then assessed the effects of endosymbionts on the host’s fecundity by antibiotic treatment experiments. Methods The microbial population of female and male R. haemaphysaloides ticks was analyzed using Illumina Miseq sequencing of 16S rRNA gene. Thirty engorged female ticks were then randomly divided into five groups and injected with ampicillin, ciprofloxacin, kanamycin, tetracycline, or phosphate-buffered solution (PBS), respectively. Effects of antibiotic treatments on maternal oviposition, egg hatching and density of endosymbionts were evaluated. Results Illumina Miseq sequencing showed that Coxiella and Rickettsia were the predominant bacterial genera inhabiting R. haemaphysaloides ticks. Antibiotic treatment experiments found that kanamycin reduced the density of Coxiella -like endosymbiont ( Coxiella -LE hereafter) in eggs, ciprofloxacin reduced the density of Rickettsia -like endosymbiont ( Rickettsia -LE), and tetracycline had effect on both endosymbionts, while ampicillin affected neither. Meanwhile hatching rates of eggs were observed to decrease greatly in the kanamycin or tetracycline-treated group but maintained in the ampicillin or ciprofloxacin-treated group. Furthermore, the reduced hatching rates were found to be associated with density of Coxiella -LE in eggs. Conclusions The findings indicate that Coxiella -LE is essential for the reproduction of R. haemaphysaloides ticks, and that kanamycin can be used to study the role of Coxiella -LE on ticks.

The clearest phenotypic characteristic of microbial cells is their shape, but we do not understand how cell shape affects the dense communities, known as biofilms, where many microbes live. Here, we use individual-based modeling to systematically vary cell shape and study its impact in simulated communities. We compete cells with different cell morphologies under a range of conditions and ask how shape affects the patterning and evolutionary fitness of cells within a community. Our models predict that cell shape will strongly influence the fate of a cell lineage: we describe a mechanism through which coccal (round) cells rise to the upper surface of a community, leading to a strong spatial structuring that can be critical for fitness. We test our predictions experimentally using strains of Escherichia coli that grow at a similar rate but differ in cell shape due to single amino acid changes in the actin homolog MreB. As predicted by our model, cell types strongly sort by shape, with round cells at the top of the colony and rod cells dominating the basal surface and edges. Our work suggests that cell morphology has a strong impact within microbial communities and may offer new ways to engineer the structure of synthetic communities.

Experiments in mice colonized with Escherichia coli have shown clonal interference and parallel phenotypic evolution in the gut, occurring from the emergence of several adaptive genetic variants that reach intermediate frequencies, rather than reaching fixation (i.e., maximum frequency), within individual bacterial species. Screening a library of mutant E. coli for effects on nematode worm survival and aging has shown that a set of mutant strains beneficially affect host mitochondrial unfolded protein responses via the secretion of the polysaccharide colanic acid, resulting in increased worm life span [47]. [...]while experimental nematodes are generally fed a specific E. coli strain (OP50) [48], complex microbiota likely mask the impact on host fitness of individual bacterial strains emerging within specific bacterial species. Since during aging and frailty the overall microbial taxonomic diversity declines, it may indeed become more likely for new strains within dominant taxa to sweep to high frequency and affect the host.

The anammox activity of a freshwater anammox consortium was strongly inhibited at low-salinity level. Stepwise adaptation from 0 to 3 g NaCl L −1 took 153 days. Further adaptation to high-salinity concentration (from 3 to 30 g L −1 ) took only 40 days, and no inhibition was observed. A comprehensive insight into the salinity-induced successions of the total and the anammox communities was obtained by 454 pyrosequencing of 16S rRNA gene amplicons and statistical analysis. A major succession in the anammox community was observed at 3 g L −1 where the dominating population shifted from Candidatus Brocadia fulgida to Ca. Kuenenia stuttgartiensis. The latter dominated at high salinity and seemed to be essential for the high (˃96%) ammonium and nitrite removal efficiencies achieved. SIMPER analysis indicated that these two dominating anammox species explained most to the differences in community structure among samples and helped in identifying other important members at different salinities.

Background Excesses of antibiotic resistance genes (ARGs), which are regarded as emerging environmental pollutants, have been observed in various environments. The incidence of ARGs in drinking water causes potential risks to human health and receives more attention from the public. However, ARGs harbored in drinking water remain largely unexplored. In this study, we aimed at establishing an antibiotic resistome catalogue in drinking water samples from a wide range of regions and to explore the potential hosts of ARGs. Results A catalogue of antibiotic resistome in drinking water was established, and the host-tracking of ARGs was conducted through a large-scale survey using metagenomic approach. The drinking water samples were collected at the point of use in 25 cities in mainland China, Hong Kong, Macau, Taiwan, South Africa, Singapore and the USA. In total, 181 ARG subtypes belonging to 16 ARG types were detected with an abundance range of 2.8 × 10 −2 to 4.2 × 10 −1 copies of ARG per cell. The highest abundance was found in northern China (Henan Province). Bacitracin, multidrug, aminoglycoside, sulfonamide, and beta-lactam resistance genes were dominant in drinking water. Of the drinking water samples tested, 84% had a higher ARG abundance than typical environmental ecosystems of sediment and soil. Metagenomic assembly-based host-tracking analysis identified Acidovorax , Acinetobacter , Aeromonas , Methylobacterium , Methyloversatilis , Mycobacterium , Polaromonas , and Pseudomonas as the hosts of ARGs. Moreover, potential horizontal transfer of ARGs in drinking water systems was proposed by network and Procrustes analyses. Conclusions The antibiotic resistome catalogue compiled using a large-scale survey provides a useful reference for future studies on the global surveillance and risk management of ARGs in drinking water. Graphical abstract .