The relative abundance of alkane‐degrading bacteria oscillated similarly to a sinusoidal curve in an artificial ecosystem model from oil‐well products

Summary Microbial phylogenetic diversity and species interactions in natural ecosystems have been investigated extensively, but our knowledge about their ecological roles, community dynamics and succession patterns is far from complete. This knowledge is essential to understand the complicated inter...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Environmental microbiology 2018-10, Vol.20 (10), p.3772-3783
Hauptverfasser: Li, Guoqiang, Gao, Peike, Zhi, Bo, Fu, Bing, Gao, Ge, Chen, Zhaohui, Gao, Mengli, Wu, Mengmeng, Ma, Ting
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Summary Microbial phylogenetic diversity and species interactions in natural ecosystems have been investigated extensively, but our knowledge about their ecological roles, community dynamics and succession patterns is far from complete. This knowledge is essential to understand the complicated interactions of microorganisms in natural ecosystems. Here, an artificial ecosystem model of microorganisms was constructed from oil‐well products and cultivated in a chemostat to investigate the succession pattern of alkane‐degrading bacteria, a functional population in oil reservoirs. Their abundance was quantified by an improved qPCR technique. Our results showed that the phylogenetic structure of this artificial ecosystem model is stable during most of the chemostat cultivation process, while the genotype structure of alkane‐degrading bacteria containing alkB genes shifted and their relative abundance oscillated similarly to a sinusoidal curve, like the succession pattern of producers in the Lotka–Volterra model. These results suggest that some theoretical frameworks of macroecology may work well in microbial ecosystems and be an efficient tool to understand them.
ISSN:1462-2912
1462-2920
DOI:10.1111/1462-2920.14382