ArticleMicrobiome2019
A conceptual framework for the phylogenetically constrained assembly of microbial communities.
Article in Microbiome, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Ecological drift simulations reveal key factors influencing minimal microbiome engineering and community assembly.ISME communications · 2026Article
- Inference of causal interaction networks of gut microbiota using transfer entropy.BMC genomics · 2025Article
- Rationally designed microbial communities in agri-food production systems: from research to market.ISME communications · 2025Article
- Beyond traditional screening: Unveiling antibiotic potentials of actinomycetes in extreme environments.Heliyon · 2024Article
- Article
- Effects of Deep Tillage on Wheat Regarding Soil Fertility and Rhizosphere Microbial Community.Microorganisms · 2024Article
- Microecological Shifts in the Rhizosphere of Perennial Large Trees and Seedlings in Continuous Cropping of Poplar.Microorganisms · 2023Article
- Metabolic similarity and the predictability of microbial community assembly.bioRxiv : the preprint server for biology · 2023Article
- Effects of a Microbial Restoration Substrate on Plant Growth and Rhizosphere Microbial Community in a Continuous Cropping Poplar.Microorganisms · 2023Article
- Impact of soil inorganic nitrogen on bacterial phylogeny in estuarine intertidal zones: a study of nitrogen metabolism.Frontiers in microbiology · 2023Article
- Leveraging phylogenetic signal to unravel microbiome function and assembly rules.Computational and structural biotechnology journal · 2023Article
- Multi-genome metabolic modeling predicts functional inter-dependencies in the Arabidopsis root microbiome.Microbiome · 2022Article
- Microbial risk score for capturing microbial characteristics, integrating multi-omics data, and predicting disease risk.Microbiome · 2022Article
- Microbial Risk Score for Capturing Microbial Characteristics, Integrating Multi-omics Data, and Predicting Disease Risk.bioRxiv : the preprint server for biology · 2022Article
- Aridity Threshold Induces Abrupt Change of Soil Abundant and Rare Bacterial Biogeography in Dryland Ecosystems.mSystems · 2022Article
- Functional attractors in microbial community assembly.Cell systems · 2022Article
- Islands Within Islands: Bacterial Phylogenetic Structure and Consortia in Hawaiian Lava Caves and Fumaroles.Frontiers in microbiology · 2022Article
- Why Do Antibiotics Exist?mBio · 2021Review
- Assessment of phylo-functional coherence along the bacterial phylogeny and taxonomy.Scientific reports · 2021Article
- Article
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1 author.
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No grant is acknowledged in the PubMed record.
Abstract
Microbial communities play essential and preponderant roles in all ecosystems. Understanding the rules that govern microbial community assembly will have a major impact on our ability to manage microbial ecosystems, positively impacting, for instance, human health and agriculture. Here, I present a phylogenetically constrained community assembly principle grounded on the well-supported facts that deterministic processes have a significant impact on microbial community assembly, that microbial communities show significant phylogenetic signal, and that microbial traits and ecological coherence are, to some extent, phylogenetically conserved. From these facts, I derive a few predictions which form the basis of the framework. Chief among them is the existence, within most microbial ecosystems, of phylogenetic core groups (PCGs), defined as discrete portions of the phylogeny of varying depth present in all instances of the given ecosystem, and related to specific niches whose occupancy requires a specific phylogenetically conserved set of traits. The predictions are supported by the recent literature, as well as by dedicated analyses. Integrating the effect of ecosystem patchiness, microbial social interactions, and scale sampling pitfalls takes us to a comprehensive community assembly model that recapitulates the characteristics most commonly observed in microbial communities. PCGs' identification is relatively straightforward using high-throughput 16S amplicon sequencing, and subsequent bioinformatic analysis of their phylogeny, estimated core pan-genome, and intra-group co-occurrence should provide valuable information on their ecophysiology and niche characteristics. Such a priori information for a significant portion of the community could be used to prime complementing analyses, boosting their usefulness. Thus, the use of the proposed framework could represent a leap forward in our understanding of microbial community assembly and function.
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