Literature DB >> 29985552

Measuring metagenome diversity and similarity with Hill numbers.

Zhanshan Sam Ma1,2, Lianwei Li1.   

Abstract

The first step of any metagenome sequencing project is to get the inventory of OTU abundances (operational taxonomic units) and/or metagenomic gene abundances. The former is generated with 16S-rRNA-tagged amplicon sequencing technology, and the latter can be generated from either gene-targeted or whole-sample shotgun metagenomics technologies. With 16S-rRNA data sets, measuring community diversity with diversity indexes such as species richness and Shannon's index has been a de facto standard analysis; nevertheless, similarly comprehensive approaches to metagenomic gene abundances are still largely missing, despite that both OTU and gene abundances are DNA reads. Here, we adapt the Hill numbers, which were reintroduced to macrocommunity ecology recently and are now widely regarded as a most appropriate measure system for ecological diversity, for measuring metagenome alpha-, beta- and gamma-diversities, and similarity. Our proposal includes the following: (a) Metagenomic gene (MG) diversity measures the single-gene-level metagenome diversity; (b) Type-I metagenome functional gene cluster (MFGC) diversity measures the diversity of functional gene clusters but ignoring within-cluster gene abundance information; (c) Type-II MFGC diversity considers within-cluster gene abundances information and integrates gene-cluster-level metagenome diversity and functional gene redundancy information; and (d) Four classes of Hill-numbers-based similarity metrics, including local gene overlap, regional gene overlap, gene homogeneity measure and gene turnover complement, were introduced in terms of MG and MFGC, respectively. We demonstrate the proposal with the gut metagenomes from healthy and IBD (inflammatory bowel disease) cohorts. The Hill numbers offer a unified approach to cohesively and comprehensively measuring the ecological and metagenome diversities of microbiomes.
© 2018 John Wiley & Sons Ltd.

Entities:  

Keywords:  Hill numbers; medical ecology; metagenome diversity; metagenome functional gene cluster diversity; metagenome similarity; metagenomic gene diversity

Mesh:

Substances:

Year:  2018        PMID: 29985552     DOI: 10.1111/1755-0998.12923

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


  12 in total

1.  Application of young maize plant residues alters the microbiome composition and its functioning in a soil under conservation agriculture: a metagenomics study.

Authors:  Mario Hernández-Guzmán; Valentín Pérez-Hernández; Selene Gómez-Acata; Norma Jiménez-Bueno; Nele Verhulst; Ligia Catalina Muñoz-Arenas; Yendi E Navarro-Noya; Marco L Luna-Guido; Luc Dendooven
Journal:  Arch Microbiol       Date:  2022-07-05       Impact factor: 2.552

2.  The Power of Microbiome Studies: Some Considerations on Which Alpha and Beta Metrics to Use and How to Report Results.

Authors:  Jannigje Gerdien Kers; Edoardo Saccenti
Journal:  Front Microbiol       Date:  2022-03-03       Impact factor: 5.640

3.  Diverse methanogens, bacteria and tannase genes in the feces of the endangered volcano rabbit (Romerolagus diazi).

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Journal:  PeerJ       Date:  2021-08-17       Impact factor: 2.984

4.  Critical Network Structures and Medical Ecology Mechanisms Underlying Human Microbiome-Associated Diseases.

Authors:  Zhanshan Sam Ma
Journal:  iScience       Date:  2020-05-23

5.  Assessing and Interpreting the Metagenome Heterogeneity With Power Law.

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Journal:  Front Microbiol       Date:  2020-05-06       Impact factor: 5.640

6.  Dietary effects on gut microbiota of the mesquite lizard Sceloporus grammicus (Wiegmann, 1828) across different altitudes.

Authors:  Nina Montoya-Ciriaco; Selene Gómez-Acata; Ligia Catalina Muñoz-Arenas; Luc Dendooven; Arturo Estrada-Torres; Aníbal H Díaz de la Vega-Pérez; Yendi E Navarro-Noya
Journal:  Microbiome       Date:  2020-01-24       Impact factor: 14.650

7.  Testing the Anna Karenina Principle in Human Microbiome-Associated Diseases.

Authors:  Zhanshan Sam Ma
Journal:  iScience       Date:  2020-03-25

8.  Application of ammonium to a N limited arable soil enriches a succession of bacteria typically found in the rhizosphere.

Authors:  Mario Hernández-Guzmán; Valentín Pérez-Hernández; Yendi E Navarro-Noya; Marco L Luna-Guido; Nele Verhulst; Bram Govaerts; Luc Dendooven
Journal:  Sci Rep       Date:  2022-03-08       Impact factor: 4.379

9.  Bacterial Communities in the Rhizosphere at Different Growth Stages of Maize Cultivated in Soil Under Conventional and Conservation Agricultural Practices.

Authors:  Yendi E Navarro-Noya; Yosef Chávez-Romero; Stephanie Hereira-Pacheco; Arit Seleny de León Lorenzana; Bram Govaerts; Nele Verhulst; Luc Dendooven
Journal:  Microbiol Spectr       Date:  2022-03-07

10.  Bacterial Communities in Alkaline Saline Soils Amended with Young Maize Plants or Its (Hemi)Cellulose Fraction.

Authors:  Valentín Pérez-Hernández; Mario Hernández-Guzmán; Marco Luna-Guido; Yendi E Navarro-Noya; Elda M Romero-Tepal; Luc Dendooven
Journal:  Microorganisms       Date:  2021-06-15
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