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Microbial Communities in Methane Cycle: Modern Molecular Methods Gain Insights into Their Global Ecologyстатья
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 4 июня 2021 г.
- Авторы: Kharitonov Sergey, Semenov Mikhail, Sabrekov Alexander, Kotsyurbenko Oleg, Zhelezova Alena, Schegolkova Natalia
- Журнал: Environments
- Том: 8
- Номер: 2
- Год издания: 2021
- Издательство: University of Waterloo
- Местоположение издательства: Canada
- Первая страница: 1
- Последняя страница: 30
- DOI: 10.3390/environments8020016
- Аннотация: The role of methane as a greenhouse gas in the concept of global climate changes iswell known. Methanogens and methanotrophs are two microbial groups which contribute to thebiogeochemical methane cycle in soil, so that the total emission of CH4is the balance between itsproduction and oxidation by microbial communities. Traditional identification techniques, such asselective enrichment and pure-culture isolation, have been used for a long time to study diversityof methanogens and methanotrophs. However, these techniques are characterized by significantlimitations, since only a relatively small fraction of the microbial community could be cultured. Mod-ern 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 sequencingtogether with different “omics” techniques overcome the limitations imposed by culture-dependentapproaches and provide new insights into the diversity and ecology of microbial communities inthe methane cycle. Here, we review available knowledge concerning the abundances, composition,and activity of methanogenic and methanotrophic communities in a wide range of natural andanthropogenic environments. We suggest that incorporation of microbial data could fill the existingmicrobiological gaps in methane flux modeling, and significantly increase the predictive power ofmodels for different environments.
- Добавил в систему: Щеголькова Наталия Михайловна
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | Environments-08-00016_2021.pdf | Environments-08-00016_2021.pdf | 561,6 КБ | 2 августа 2022 [nshegolkova@mail.ru] | |
| 2. | environments-08-00016-v2.pdf | environments-08-00016-v2.pdf | 467,9 КБ | 26 февраля 2021 [nshegolkova@mail.ru] |