Dataset Information

Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments.

ABSTRACT: A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family level. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar-one organic acid). Furthermore, sugar-acid communities are generally more similar to the sugar than the acid community, which may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict community responses to dietary changes.

SUBMITTER: Estrela S

PROVIDER: S-EPMC8057819 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments.

Estrela Sylvie S Sanchez-Gorostiaga Alicia A Vila Jean Cc JC Sanchez Alvaro A

eLife 20210420

A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviati ...[more]

PMID: 33877964

Similar Datasets

Project description:Different habitats harbor different microbial communities with elusive assembly mechanisms. This study comprehensively investigated the global assembly mechanisms of microbial communities and effects of community-internal influencing factors using the Earth Microbiome Project (EMP) data set. We found that deterministic and stochastic processes contribute approximately equally to global microbial community assembly, and, specifically, deterministic processes generally play a major role in free-living and plant-associated (but not plant corpus) environments, while stochastic processes are the major contributor in animal-associated environments. In contrast with the assembly of microorganisms, the assembly of functional genes, predicted from PICRUSt, is mainly attributed to deterministic processes in all microbial communities. The sink and source microbial communities are normally assembled using similar mechanisms, and the core microorganisms are specific to different environment types. On a global scale, deterministic processes are positively related to the community alpha diversity, microbial interaction degree and bacterial predatory-specific gene abundance. Our analysis provides a panoramic picture and regularities of global and environment-typical microbial community assemblies. IMPORTANCE With the development of sequencing technologies, the research topic of microbial ecology has evolved from the analysis of community composition to community assembly, including the relative contribution of deterministic and stochastic processes for the formation and maintenance of community diversity. Many studies have reported the microbial assembly mechanisms in various habitats, but the assembly regularities of global microbial communities remain unknown. In this study, we analyzed the EMP data set using a combined pipeline to explore the assembly mechanisms of global microbial communities, microbial sources to construct communities, core microbes in different environment types, and community-internal factors influencing assembly. The results provide a panoramic picture and rules of global and environment-typical microbial community assemblies, which enhances our understandings of the mechanisms globally controlling community diversity and species coexistence.

Project description:Hitherto, the main goal of metaproteomic analyses has been to characterize the functional role of particular microorganisms in the microbial ecology of various microbial communities. Recently, it has been suggested that metaproteomics could be used for bioprospecting microbial communities to query for the most active enzymes to improve the selection process of industrially relevant enzymes. In the present study, to reduce the complexity of metaproteomic samples for targeted bioprospecting of novel enzymes, a microbial community capable of producing cellulases was maintained on a chemically defined medium in an enzyme suppressed metabolic steady state. From this state, it was possible to specifically and distinctively induce the desired cellulolytic activity. The extracellular fraction of the protein complement of the induced sample could thereby be purified and compared to a non-induced sample of the same community by differential gel electrophoresis to discriminate between constitutively expressed proteins and proteins upregulated in response to the inducing substance.Using the applied approach, downstream analysis by mass spectrometry could be limited to only proteins recognized as upregulated in the cellulase-induced sample. Of 39 selected proteins, the majority were found to be linked to the need to degrade, take up, and metabolize cellulose. In addition, 28 (72%) of the proteins were non-cytosolic and 17 (44%) were annotated as carbohydrate-active enzymes. The results demonstrated both the applicability of the proposed approach for identifying extracellular proteins and guiding the selection of proteins toward those specifically upregulated and targeted by the enzyme inducing substance. Further, because identification of interesting proteins was based on the regulation of enzyme expression in response to a need to hydrolyze and utilize a specific substance, other unexpected enzyme activities were able to be identified.The described approach created the conditions necessary to be able to select relevant extracellular enzymes that were extracted from the enzyme-induced microbial community. However, for the purpose of bioprospecting for enzymes to clone, produce, and characterize for practical applications, it was concluded that identification against public databases was not sufficient to identify the correct gene or protein sequence for cloning of the identified novel enzymes.

Dataset Information

Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments.

Publications

Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets