Microbial regulation of the soil carbon cycle: evidence from gene–enzyme relationships

• Published in: The ISME Journal Vol. 10; no. 11; pp. 2593 - 2604
• Main Authors: Trivedi, Pankaj, Delgado-Baquerizo, Manuel, Trivedi, Chanda, Hu, Hangwei, Anderson, Ian C, Jeffries, Thomas C, Zhou, Jizhong, Singh, Brajesh K
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.11.2016; Oxford University Press; Nature Publishing Group
• Subjects: 45/23; 45/61; 631/158/2165; 631/158/855; Australia; Bacteria - enzymology; Bacteria - genetics; Bacteria - isolation & purification; Bacteria - metabolism; Bacterial Proteins - genetics; Bacterial Proteins - metabolism; BASIC BIOLOGICAL SCIENCES; Biomedical and Life Sciences; Carbon - metabolism; Carbon Cycle; Community structure; Ecology; Ecosystem; Enzymatic activity; Evolutionary Biology; Life Sciences; Microbial activity; Microbial Ecology; Microbial Genetics and Genomics; Microbiology; Original; original-article; Soil - chemistry; Soil Microbiology; Soil pH; Soils; Australia
• ISSN: 1751-7362; 1751-7370; 1751-7370
• DOI: 10.1038/ismej.2016.65

A lack of empirical evidence for the microbial regulation of ecosystem processes, including carbon (C) degradation, hinders our ability to develop a framework to directly incorporate the genetic composition of microbial communities in the enzyme-driven Earth system models. Herein we evaluated the linkage between microbial functional genes and extracellular enzyme activity in soil samples collected across three geographical regions of Australia. We found a strong relationship between different functional genes and their corresponding enzyme activities. This relationship was maintained after considering microbial community structure, total C and soil pH using structural equation modelling. Results showed that the variations in the activity of enzymes involved in C degradation were predicted by the functional gene abundance of the soil microbial community ( R 2 >0.90 in all cases). Our findings provide a strong framework for improved predictions on soil C dynamics that could be achieved by adopting a gene-centric approach incorporating the abundance of functional genes into process models.