Literature DB >> 33664779

Niche-neutral theoretic approach to mechanisms underlying the biodiversity and biogeography of human microbiomes.

Zhanshan Sam Ma1,2.   

Abstract

The human microbiome consists of five major regional biomes distributed in or on our five body sites including skin, oral, lung, gut, and reproductive tract. Its biogeography (the spatial and temporal distribution of its biodiversity) has far-reaching implications to our health and diseases. Nevertheless, we currently have very limited understanding on the mechanisms shaping the biogeography, since it is often rather difficult to determine the relative importance of drift, dispersal, speciation, and selection, the four processes (mechanisms) determining the patterns of microbial biogeography and community dynamics according to a recent synthesis in community ecology and biogeography. To disentangle these mechanisms, I utilize multisite neutral (MSN) model and niche-neutral hybrid (NNH) model to analyze large number of truly multisite microbiome samples covering all five major human microbiome habitats, including 699 metacommunities and 5,420 local communities. Approximately 89% of metacommunities and 92% local communities exhibit patterns indistinguishable from neutral, and 20% indistinguishable from niche-neutral hybrid model, indicating the relative significance of stochastic neutral forces versus deterministic niche selection in shaping the biogeography of human microbiome. These findings cast supporting evidence to van der Gast's revision to classic Bass-Becking doctrine of microbial biogeography: "Some things are everywhere and some things are not. Sometimes the environment selects and sometimes it doesn't," offering the first educated guess for "some" and "sometimes" in the revised doctrine. Furthermore, the logistic/Cox regression models describing the relationships among community neutrality, niche differentiation, and key community/species characteristics (including community diversity, community/species dominance, speciation, and migration rates) were constructed to quantitatively describe the niche-neutral continuum and the influences of community/species properties on the continuum.
© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

Entities:  

Keywords:  Hierarchical Dirichlet process; human microbiome biogeography; multisite neutral (MSN) model; neutral drifts; niche differentiations; niche‐neutral continuum; niche‐neutral hybrid model

Year:  2020        PMID: 33664779      PMCID: PMC7896709          DOI: 10.1111/eva.13116

Source DB:  PubMed          Journal:  Evol Appl        ISSN: 1752-4571            Impact factor:   5.183


  47 in total

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2.  The case for ecological neutral theory.

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3.  A neutral sampling formula for multiple samples and an 'exact' test of neutrality.

Authors:  Rampal S Etienne
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4.  The human microbiome project.

Authors:  Peter J Turnbaugh; Ruth E Ley; Micah Hamady; Claire M Fraser-Liggett; Rob Knight; Jeffrey I Gordon
Journal:  Nature       Date:  2007-10-18       Impact factor: 49.962

5.  Maximum likelihood estimation of neutral model parameters for multiple samples with different degrees of dispersal limitation.

Authors:  Rampal S Etienne
Journal:  J Theor Biol       Date:  2008-12-30       Impact factor: 2.691

6.  Quantification of the relative roles of niche and neutral processes in structuring gastrointestinal microbiomes.

Authors:  Patricio Jeraldo; Maksim Sipos; Nicholas Chia; Jennifer M Brulc; A Singh Dhillon; Michael E Konkel; Charles L Larson; Karen E Nelson; Ani Qu; Lawrence B Schook; Fang Yang; Bryan A White; Nigel Goldenfeld
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-21       Impact factor: 11.205

Review 7.  The unified neutral theory of biodiversity and biogeography at age ten.

Authors:  James Rosindell; Stephen P Hubbell; Rampal S Etienne
Journal:  Trends Ecol Evol       Date:  2011-05-10       Impact factor: 17.712

8.  Hybrid niche-neutral models outperform an otherwise equivalent neutral model for fitting coral reef data.

Authors:  Junfeng Tang; Shurong Zhou
Journal:  J Theor Biol       Date:  2012-10-23       Impact factor: 2.691

9.  Niche versus neutrality: a dynamical analysis.

Authors:  Michael Kalyuzhny; Efrat Seri; Rachel Chocron; Curtis H Flather; Ronen Kadmon; Nadav M Shnerb
Journal:  Am Nat       Date:  2014-08-18       Impact factor: 3.926

10.  Bacteria dispersal by hitchhiking on zooplankton.

Authors:  Hans-Peter Grossart; Claudia Dziallas; Franziska Leunert; Kam W Tang
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-14       Impact factor: 11.205

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  7 in total

1.  Microbiome Transmission During Sexual Intercourse Appears Stochastic and Supports the Red Queen Hypothesis.

Authors:  Zhanshan Sam Ma
Journal:  Front Microbiol       Date:  2022-03-08       Impact factor: 5.640

2.  Stochastic neutral drifts seem prevalent in driving human virome assembly: Neutral, near-neutral and non-neutral theoretic analyses.

Authors:  Zhanshan Sam Ma; Jiandong Mei
Journal:  Comput Struct Biotechnol J       Date:  2022-03-30       Impact factor: 6.155

3.  Shotgun metagenomic sequencing reveals skin microbial variability from different facial sites.

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4.  Shared Species Analysis, Augmented by Stochasticity Analysis, Is More Effective Than Diversity Analysis in Detecting Variations in the Gut Microbiomes.

Authors:  Zhanshan Sam Ma
Journal:  Front Microbiol       Date:  2022-07-19       Impact factor: 6.064

5.  Niche-Neutral Continuum Seems to Explain the Global Niche Differentiation and Local Drift of the Human Digestive Tract Microbiome.

Authors:  Hongju Daisy Chen; Zhanshan Sam Ma
Journal:  Front Microbiol       Date:  2022-07-22       Impact factor: 6.064

6.  Structure and Dynamics of the Breast Tissue Microbiomes Under Tumor Influences: An Approach With Neutral, Near-Neutral, and Niche-Neutral Hybrid Models.

Authors:  Lianwei Li; Ping Ning; Zhanshan Ma
Journal:  Front Microbiol       Date:  2021-07-19       Impact factor: 5.640

7.  Cross-Scale Analyses of Animal and Human Gut Microbiome Assemblies from Metacommunity to Global Landscape.

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Journal:  mSystems       Date:  2021-07-06       Impact factor: 6.496

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