An application of statistics to comparative metagenomics.
BACKGROUND
Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments.


RESULTS
Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified.


CONCLUSIONS
The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.
Computational Science Research Center, San Diego State University, San Diego, USA. beltran.rodriguezbrito@gmail.com
Beltran
B
Rodriguez-Brito
Forest
F
Rohwer
Robert A
RA
Edwards
D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D023281:Genomics / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D020543:Proteome / Q000378:metabolism*; D017422:Sequence Analysis, DNA / Q000379:methods*; D015398:Signal Transduction / Q000502:physiology*
D020543:Proteome