Merging metagenomics and geochemistry reveals environmental controls on biological diversity and evolution

Annals of Occupational and Environmental Medicine

Jason Raymond¹  Eric S Boyd²  Eric B Alsop¹ 

[1]School of Earth and Space Exploration, Arizona State University, ISTB4, Room 795, 781 E. Terrace Rd, Tempe, AZ 85287, USA

[2]Wisconsin Astrobiology Research Consortium, University of Wisconsin, Weeks Hall, Madison, WI 53706, USA

关键词: Markov clustering;    Geochemistry;    Hydrothermal ecosystems;    Microbial ecology;    Metagenomics;   

Others  :  834671
DOI  :  10.1186/1472-6785-14-16

 received in 2014-01-29, accepted in 2014-05-16,  发布年份 2014

【 摘 要 】

Background

The metabolic strategies employed by microbes inhabiting natural systems are, in large part, dictated by the physical and geochemical properties of the environment. This study sheds light onto the complex relationship between biology and environmental geochemistry using forty-three metagenomes collected from geochemically diverse and globally distributed natural systems. It is widely hypothesized that many uncommonly measured geochemical parameters affect community dynamics and this study leverages the development and application of multidimensional biogeochemical metrics to study correlations between geochemistry and microbial ecology. Analysis techniques such as a Markov cluster-based measure of the evolutionary distance between whole communities and a principal component analysis (PCA) of the geochemical gradients between environments allows for the determination of correlations between microbial community dynamics and environmental geochemistry and provides insight into which geochemical parameters most strongly influence microbial biodiversity.

Results

By progressively building from samples taken along well defined geochemical gradients to samples widely dispersed in geochemical space this study reveals strong links between the extent of taxonomic and functional diversification of resident communities and environmental geochemistry and reveals temperature and pH as the primary factors that have shaped the evolution of these communities. Moreover, the inclusion of extensive geochemical data into analyses reveals new links between geochemical parameters (e.g. oxygen and trace element availability) and the distribution and taxonomic diversification of communities at the functional level. Further, an overall geochemical gradient (from multivariate analyses) between natural systems provides one of the most complete predictions of microbial taxonomic and functional composition.

Conclusions

Clustering based on the frequency in which orthologous proteins occur among metagenomes facilitated accurate prediction of the ordering of community functional composition along geochemical gradients, despite a lack of geochemical input. The consistency in the results obtained from the application of Markov clustering and multivariate methods to distinct natural systems underscore their utility in predicting the functional potential of microbial communities within a natural system based on system geochemistry alone, allowing geochemical measurements to be used to predict purely biological metrics such as microbial community composition and metabolism.

【 授权许可】

   
2014 Alsop et al.; licensee BioMed Central Ltd.

【 图 表 】

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