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Non-additive microbial community responses to environmental complexity.

ABSTRACT: Environmental composition is a major, though poorly understood, determinant of microbiome dynamics. Here we ask whether general principles govern how microbial community growth yield and diversity scale with an increasing number of environmental molecules. By assembling hundreds of synthetic consortia in vitro, we find that growth yield can remain constant or increase in a non-additive manner with environmental complexity. Conversely, taxonomic diversity is often much lower than expected. To better understand these deviations, we formulate metrics for epistatic interactions between environments and use them to compare our results to communities simulated with experimentally-parametrized consumer resource models. We find that key metabolic and ecological factors, including species similarity, degree of specialization, and metabolic interactions, modulate the observed non-additivity and govern the response of communities to combinations of resource pools. Our results demonstrate that environmental complexity alone is not sufficient for maintaining community diversity, and provide practical guidance for designing and controlling microbial ecosystems.

SUBMITTER: Pacheco AR

PROVIDER: S-EPMC8062479 | biostudies-literature |

REPOSITORIES: biostudies-literature

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environmental microbial community

Project description:environmental microbial community Genome sequencing and assembly

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Higher-order interactions shape microbial interactions as microbial community complexity increases.

Project description:Non-pairwise interactions, or higher-order interactions (HOIs), in microbial communities have been described as significant drivers of emergent features in microbiomes. Yet, the re-organization of microbial interactions between pairwise cultures and larger communities remains largely unexplored from a molecular perspective but is central to our understanding and further manipulation of microbial communities. Here, we used a bottom-up approach to investigate microbial interaction mechanisms from pairwise cultures up to 4-species communities from a simple microbiome (Hafnia alvei, Geotrichum candidum, Pencillium camemberti and Escherichia coli). Specifically, we characterized the interaction landscape for each species combination involving E. coli by identifying E. coli's interaction-associated mutants using an RB-TnSeq-based interaction assay. We observed a deep reorganization of the interaction-associated mutants, with very few 2-species interactions conserved all the way up to a 4-species community and the emergence of multiple HOIs. We further used a quantitative genetics strategy to decipher how 2-species interactions were quantitatively conserved in higher community compositions. Epistasis-based analysis revealed that, of the interactions that are conserved at all levels of complexity, 82% follow an additive pattern. Altogether, we demonstrate the complex architecture of microbial interactions even within a simple microbiome, and provide a mechanistic and molecular explanation of HOIs.

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MetaSort untangles metagenome assembly by reducing microbial community complexity.

Project description:Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.

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Microbial community and network responses across strong environmental gradients: How do they compare with macroorganisms?

Project description:The way strong environmental gradients shape multispecific assemblages has allowed us to examine a suite of ecological and evolutionary hypotheses about structure, regulation and community responses to fluctuating environments. But whether the highly diverse co-occurring microorganisms are shaped in similar ways as macroscopic organisms across the same gradients has yet to be addressed in most ecosystems. Here, we characterize intertidal biofilm bacteria communities, comparing zonation at both the "species" and community levels, as well as network attributes, with co-occurring macroalgae and invertebrates in the same rocky shore system. The results revealed that the desiccation gradient has a more significant impact on smaller communities, while both desiccation and submersion gradients (surge) affect the larger, macroscopic communities. At the community level, we also confirmed the existence of distinct communities within each intertidal zone for microorganisms, similar to what has been previously described for macroorganisms. But our results indicated that dominant microbial organisms along the same environmental gradient exhibited less differentiation across tidal levels than their macroscopic counterparts. However, despite the substantial differences in richness, size and attributes of co-occurrence networks, both macro- and micro-communities respond to stress gradients, leading to the formation of similar zonation patterns in the intertidal rocky shore.

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Non-proteolytic functions of microbial proteases increase pathological complexity.

Project description:Proteases are enzymes that catalyse hydrolysis of peptide bonds thereby controlling the shape, size, function, composition, turnover and degradation of other proteins. In microbes, proteases are often identified as important virulence factors and as such have been targets for novel drug design. It is emerging that some proteases possess additional non-proteolytic functions that play important roles in host epithelia adhesion, tissue invasion and in modulating immune responses. These additional "moonlighting" functions have the potential to obfuscate data interpretation and have implications for therapeutic design. Moonlighting enzymes comprise a subcategory of multifunctional proteins that possess at least two distinct biological functions on a single polypeptide chain. Presently, identifying moonlighting proteins relies heavily on serendipitous empirical data with clues arising from proteins lacking signal peptides that are localised to the cell surface. Here, we describe examples of microbial proteases with additional non-proteolytic functions, including streptococcal pyrogenic exotoxin B, PepO and C5a peptidases, mycoplasmal aminopeptidases, mycobacterial chaperones and viral papain-like proteases. We explore how these non-proteolytic functions contribute to host cell adhesion, modulate the coagulation pathway, assist in non-covalent folding of proteins, participate in cell signalling, and increase substrate repertoire. We conclude by describing how proteomics has aided in moonlighting protein discovery, focusing attention on potential moonlighters in microbial exoproteomes.

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Determinism of microbial community assembly by drastic environmental change.

Project description:Microbial community assembly is shaped by deterministic and stochastic processes, but the relationship between these processes and the environment is not understood. Here we describe a rule for the determinism and stochasticity of microbial community assembly affected by the environment using in silico, in situ, and ex situ experiments. The in silico experiment with a simple mathematical model showed that the existence of essential symbiotic microorganisms caused stochastic microbial community assembly, unless the community was exposed to a non-adapted nutritional concentration. Then, a deterministic assembly occurred due to the low number of microorganisms adapted to the environment. In the in situ experiment in the middle of a river, the microbial community composition was relatively deterministic after the drastic environmental change caused by the treated wastewater contamination, as analyzed by 16S rRNA gene sequencing. Furthermore, by culturing microbial communities collected from the upstream natural area and downstream urban area of the river in test tubes with varying carbon source concentrations, the upstream community assembly became deterministic with high carbon concentrations while the downstream community assembly became deterministic with low carbon concentrations. These results suggest that large environmental changes, which are different from the original environment, result in a deterministic microbial community assembly.

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Transcriptome of a Synthetic Microbial Community

Project description:To explore the ecological basis for multiple bacteria species coexistence, we set up three bacteria (Ruegeria pomeroyi DSS-3, Vibrio hepatarius HF70, and Thalassospira sp. HF15), either in monoculture or in co-cultures (in all combinations) for a 8 day growth-dilution cycles. At ~15h of day 4 (P4) and day 8 (P8) of growth-dilution cycles, we examined transcriptomic responses of these bacteria. Differential gene expressions were used to generate hypothesis about ecological and physiological responses of one in the presence of another/other bacteria.

2022-08-01 | GSE199797 | GEO

Changes in the genetic requirements for microbial interactions with increasing community complexity.

Project description:Microbial community structure and function rely on complex interactions whose underlying molecular mechanisms are poorly understood. To investigate these interactions in a simple microbiome, we introduced E. coli into an experimental community based on a cheese rind and identified the differences in E. coli's genetic requirements for growth in interactive and non-interactive contexts using Random Barcode Transposon Sequencing (RB-TnSeq) and RNASeq. Genetic requirements varied among pairwise growth conditions and between pairwise and community conditions. Our analysis points to mechanisms by which growth conditions change as a result of increasing community complexity and suggests that growth within a community relies on a combination of pairwise and higher-order interactions. Our work provides a framework for using the model organism E. coli as a readout to investigate microbial interactions regardless of the genetic tractability of members of the studied ecosystem.

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Project description:A great challenge facing microbial ecology is how to define ecologically relevant taxonomic units. To address this challenge, we investigated how changing the definition of operational taxonomic units (OTUs) influences the perception of ecological patterns in microbial communities as they respond to a dramatic environmental change. We used pyrosequenced tags of the bacterial V2 16S rRNA region, as well as clone libraries constructed from the cytochrome oxidase C gene ccoN, to provide additional taxonomic resolution for the common freshwater genus Polynucleobacter. At the most highly resolved taxonomic scale, we show that distinct genotypes associated with the abundant Polynucleobacter lineages exhibit divergent spatial patterns and dramatic changes over time, while the also abundant Actinobacteria OTUs are highly coherent. This clearly demonstrates that different bacterial lineages demand different taxonomic definitions to capture ecological patterns. Based on the temporal distribution of highly resolved taxa in the hypolimnion, we demonstrate that change in the population structure of a single genotype can provide additional insight into the mechanisms of community-level responses. These results highlight the importance and feasibility of examining ecological change in microbial communities across taxonomic scales while also providing valuable insight into the ecological characteristics of ecologically coherent groups in this system.

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Project description:What allows interacting, diverse species to coexist in nature has been a central question in ecology, ever since the theoretical prediction that a complex community should be inherently unstable. Although the role of spatiality in species coexistence has been recognized, its application to more complex systems has been less explored. Here, using a meta-community model of food web, we show that meta-community complexity, measured by the number of local food webs and their connectedness, elicits a self-regulating, negative-feedback mechanism and thus stabilizes food-web dynamics. Moreover, the presence of meta-community complexity can give rise to a positive food-web complexity-stability effect. Spatiality may play a more important role in stabilizing dynamics of complex, real food webs than expected from ecological theory based on the models of simpler food webs.

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