Higher-order effects, continuous species interactions, and trait evolution shape microbial spatial dynamics

Costs of antibiotic resistance genes depend on host strain and environment and can influence community composition

Antibiotic resistance genes (ARGs) benefit host bacteria in environments containing corresponding antibiotics, but it is less clear how they are maintained in environments where antibiotic selection is weak or sporadic. In particular, few studies have measured if the direct effect of ARGs on host fitness is fixed or if it depends on the host strain, perhaps marking some ARG-host combinations as selective refuges that can maintain ARGs in the absence of antibiotic selection. We quantified the fitness effects of six ARGs in 11 diverse Escherichia spp. strains. Three ARGs (blaTEM-116, cat and dfrA5, encoding resistance to β-lactams, chloramphenicol, and trimethoprim, respectively) imposed an overall cost, but all ARGs had an effect in at least one host strain, reflecting a significant strain interaction effect. A simulation predicts these interactions can cause the success of ARGs to depend on available host strains, and, to a lesser extent, can cause host strain success to depend on the ARGs present in a community. These results indicate the importance of considering ARG effects across different host strains, and especially the potential of refuge strains to allow resistance to persist in the absence of direct selection, in efforts to understand resistance dynamics.

High immigration rates critical for establishing emigration-driven diversity in microbial communities

Unraveling the mechanisms governing the diversity of ecological communities is a central goal in ecology. Although microbial dispersal constitutes an important ecological process, the effect of dispersal on microbial diversity is poorly understood. Here, we sought to fill this gap by combining a generalized Lotka-Volterra model with experimental investigations. Our model showed that emigration increases the diversity of the community when the immigration rate crosses a defined threshold, which we identified as Ineutral. We also found that at high immigration rates, emigration weakens the relative abundance of fast-growing species and thus enhances the mass effect and increases the diversity. We experimentally confirmed this finding using co-cultures of 20 bacterial strains isolated from the soil. Our model further showed that Ineutral decreases with the increase of species pool size, growth rate, and interspecies interaction. Our work deepens the understanding of the effects of dispersal on the diversity of natural communities.

Understanding the role of neutral species by means of high-order interaction in the rock-paper-scissors dynamics

The existence of neutral species carries profound ecological implications that warrant further investigation. In this paper, we study the impact of neutral species on biodiversity in a spatial tritrophic system of cyclic competition, in which the neutral species are identified as the fourth species that may affect the competition process of the other three species under the rock-paper-scissors (RPS) rule. Extensive simulations showed that neutral species can promote coexistence in a high mobility regime within the system. When coexistence occurs, we found that the state can be maintained by two mechanisms: Species can either (i) adhere to traditional RPS rule or (ii) form patches to resist invasion. Our findings might aid in understanding the impact of neutral species on biodiversity in ecosystems.

Antibiotic-degrading resistance changes bacterial community structure via species-specific responses

Some bacterial resistance mechanisms degrade antibiotics, potentially protecting neighbouring susceptible cells from antibiotic exposure. We do not yet understand how such effects influence bacterial communities of more than two species, which are typical in nature. Here, we used experimental multispecies communities to test the effects of clinically important pOXA-48-plasmid-encoded resistance on community-level responses to antibiotics. We found that resistance in one community member reduced antibiotic inhibition of other species, but some benefitted more than others. Further experiments with supernatants and pure-culture growth assays showed the susceptible species profiting most from detoxification were those that grew best at degraded antibiotic concentrations (greater than zero, but lower than the starting concentration). This pattern was also observed on agar surfaces, and the same species also showed relatively high survival compared to most other species during the initial high-antibiotic phase. By contrast, we found no evidence of a role for higher-order interactions or horizontal plasmid transfer in community-level responses to detoxification in our experimental communities. Our findings suggest carriage of an antibiotic-degrading resistance mechanism by one species can drastically alter community-level responses to antibiotics, and the identities of the species that profit most from antibiotic detoxification are predicted by their intrinsic ability to survive and grow at changing antibiotic concentrations.

Salt stress altered anaerobic microbial community and carbon metabolism characteristics: The trade-off between methanogenesis and chain elongation

Discharge of saline organic wastewater is increasing worldwide, yet how salt stress disrupts the microbial community's structure and metabolism in bioreactors has not been systematically investigated. The non-adapted anaerobic granular sludge was inoculated into wastewater with varying salt concentration (ranging from 0% to 5%) to examine the effects of salt stress on the structure and function of the anaerobic microbial community. Result indicated that salt stress had a significant impact on the metabolic function and community structure of the anaerobic granular sludge. Specifically, we observed a notable reduction in methane production in response to all salt stress treatments (r = -0.97, p < 0.01), while an unexpected increase in butyrate production (r = 0.91, p < 0.01) under moderate salt stress (1-3%) with ethanol and acetate as carbon sources. In addition, analysis of microbiome structures and networks demonstrated that as the degree of salt stress increased, the networks exhibited lower connectance and increased compartmentalization. The abundance of interaction partners (methanogenic archaea and syntrophic bacteria) decreased under salt stress. In contrast, the abundance of chain elongation bacteria, specifically Clostridium kluyveri, increased under moderate salt stress (1-3%). As a consequence, the microbial carbon metabolism patterns shifted from cooperative mode (methanogenesis) to independent mode (carbon chain elongation) under moderate salt stress. This study provides evidence that salt stress altered the anaerobic microbial community and carbon metabolism characteristics, and suggests potential guidance for steering the microbiota to promote resource conversion in saline organic wastewater treatment.

QCMI: A method for quantifying putative biotic associations of microbes at the community level

A workflow has been compiled as "qcmi" R package-the quantifying community-level microbial interactions-to identify and quantify the putative biotic associations of microbes at the community level from ecological networks.

Investigating the eco-evolutionary tunnels for establishing cooperative communities

Diversity is abundant among microbial communities. Understanding the assembly of diverse microbial communities is a significant challenge. One of the recent plausible explanations for the assembly involves eco-evolutionary tunnels, where species interact in the same timescale with the mutational rate. Analysis of data generated by agent-based models was used to understand these tunnels. However, modeling the interactions explicitly by dynamic models is lacking. Here, we present the modeling and characterization of eco-evolutionary tunnels that give rise to cooperative evolutionary stable communities (ESC). We find that higher order, but common interactions are sufficient for eco-evolutionary tunnels. We identify three distinct scenarios: evolution of costly cooperation, mutationally inaccessible assembly, and bistability. Biological interpretations of the models are shedding light on the evolution of cooperation. One of the important findings is that if species maximize their benefit by preying on the other strain when dominant and cooperating at intermediate abundances, the assembly process needs eco-evolutionary tunneling. In addition, we characterize the importance of genetic drift with respect to eco-evolutionary tunnels, intermittently stable communities, and the effect of high population limits on the tunnels.

A Transcriptomic Analysis of Higher-Order Ecological Interactions in a Eukaryotic Model Microbial Ecosystem

Nonlinear ecological interactions within microbial ecosystems and their contribution to ecosystem functioning remain largely unexplored. Higher-order interactions, or interactions in systems comprised of more than two members that cannot be explained by cumulative pairwise interactions, are particularly understudied, especially in eukaryotic microorganisms. The wine fermentation ecosystem presents an ideal model to study yeast ecosystem establishment and functioning. Some pairwise ecological interactions between wine yeast species have been characterized, but very little is known about how more complex, multispecies systems function. Here, we evaluated nonlinear ecosystem properties by determining the transcriptomic response of Saccharomyces cerevisiae to pairwise versus tri-species culture. The transcriptome revealed that genes expressed during pairwise coculture were enriched in the tri-species data set but also that just under half of the data set comprised unique genes attributed to a higher-order response. Through interactive protein-association network visualizations, a holistic cell-wide view of the gene expression data was generated, which highlighted known stress response and metabolic adaptation mechanisms which were specifically activated during tri-species growth. Further, extracellular metabolite data corroborated that the observed differences were a result of a biotic stress response. This provides exciting new evidence showing the presence of higher-order interactions within a model microbial ecosystem. IMPORTANCE Higher-order interactions are one of the major blind spots in our understanding of microbial ecosystems. These systems remain largely unpredictable and are characterized by nonlinear dynamics, in particular when the system is comprised of more than two entities. By evaluating the transcriptomic response of S. cerevisiae to an increase in culture complexity from a single species to two- and three-species systems, we were able to confirm the presence of a unique response in the more complex setting that could not be explained by the responses observed at the pairwise level. This is the first data set that provides molecular targets for further analysis to explain unpredictable ecosystem dynamics in yeast.