Evaluating the use of diversity indices to distinguish between microbial communities with different traits

Sergey Feranchuk; Natalia Belkova; Ulyana Potapova; Dmitry Kuzmin; Sergei Belikov

doi:10.1016/j.resmic.2018.03.004

Evaluating the use of diversity indices to distinguish between microbial communities with different traits

Res Microbiol. 2018 May-Jun;169(4-5):254-261. doi: 10.1016/j.resmic.2018.03.004. Epub 2018 May 23.

Authors

Sergey Feranchuk¹, Natalia Belkova², Ulyana Potapova³, Dmitry Kuzmin⁴, Sergei Belikov⁵

Affiliations

¹ Limnological Institute, Siberian Branch of Russian Academy of Sciences, 664033, Irkutsk, Russia; Department of Informatics, National Research Technical University, 664074, Irkutsk, Russia. Electronic address: [email protected].
² Limnological Institute, Siberian Branch of Russian Academy of Sciences, 664033, Irkutsk, Russia; Scientific Centre for Family Health and Human Reproduction Problems, 664033, Irkutsk, Russia. Electronic address: [email protected].
³ Limnological Institute, Siberian Branch of Russian Academy of Sciences, 664033, Irkutsk, Russia. Electronic address: [email protected].
⁴ Laboratory of Forest Genomics, Genome Research and Education Center, Siberian Federal University, 660036, Krasnoyarsk, Russia; Department of High Performance Computing, Institute of Space and Information Technologies, Siberian Federal University, 660074, Krasnoyarsk, Russia. Electronic address: [email protected].
⁵ Limnological Institute, Siberian Branch of Russian Academy of Sciences, 664033, Irkutsk, Russia. Electronic address: [email protected].

PMID: 29800679
DOI: 10.1016/j.resmic.2018.03.004

Abstract

Several measures of biodiversity are commonly used to describe microbial communities, analyzed using 16S gene sequencing. A wide range of available experiments on 16S gene sequencing allows us to present a framework for a comparison of various diversity indices. The criterion for the comparison is the statistical significance of the difference in index values for microbial communities with different traits, within the same experiment. The results of the evaluation indicate that Shannon diversity is the most effective measure among the commonly used diversity indices. The results also indicate that, within the present framework, the Gini coefficient as a diversity index is comparable to Shannon diversity, despite the fact that the Gini coefficient, as a diversity estimator, is far less popular in microbiology than several other measures.

Keywords: Ecosystem; Metagenomics; Model; RNA; Ribosomal 16s.

Publication types

Evaluation Study

MeSH terms

Algorithms*
Bacteria / classification*
Bacteria / genetics*
Biodiversity*
Coral Reefs
DNA, Bacterial / genetics
Ecosystem
Metagenomics / methods*
Microbial Consortia / genetics*
RNA, Ribosomal, 16S / genetics
Soil Microbiology

Substances

DNA, Bacterial
RNA, Ribosomal, 16S