Microbial Communities in Methane Cycle: Modern Molecular Methods Gain Insights into Their Global Ecology

The role of methane as a greenhouse gas in the concept of global climate changes is well known. Methanogens and methanotrophs are two microbial groups which contribute to the biogeochemical methane cycle in soil, so that the total emission of CH<sub>4</sub> is the balance between its pro...

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Bibliographic Details
Main Authors: Sergey Kharitonov, Mikhail Semenov, Alexander Sabrekov, Oleg Kotsyurbenko, Alena Zhelezova, Natalia Schegolkova
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Environments
Subjects:
Online Access:https://www.mdpi.com/2076-3298/8/2/16
Description
Summary:The role of methane as a greenhouse gas in the concept of global climate changes is well known. Methanogens and methanotrophs are two microbial groups which contribute to the biogeochemical methane cycle in soil, so that the total emission of CH<sub>4</sub> is the balance between its production and oxidation by microbial communities. Traditional identification techniques, such as selective enrichment and pure-culture isolation, have been used for a long time to study diversity of methanogens and methanotrophs. However, these techniques are characterized by significant limitations, since only a relatively small fraction of the microbial community could be cultured. Modern molecular methods for quantitative analysis of the microbial community such as real-time PCR (Polymerase chain reaction), DNA fingerprints and methods based on high-throughput sequencing together with different “omics” techniques overcome the limitations imposed by culture-dependent approaches and provide new insights into the diversity and ecology of microbial communities in the methane cycle. Here, we review available knowledge concerning the abundances, composition, and activity of methanogenic and methanotrophic communities in a wide range of natural and anthropogenic environments. We suggest that incorporation of microbial data could fill the existing microbiological gaps in methane flux modeling, and significantly increase the predictive power of models for different environments.
ISSN:2076-3298