Caister Academic Press

Microarray of 16S rRNA Gene Probes for Quantifying Population Differences Across Microbiome Samples

Alexander J. Probst, Pek Yee Lum, Bettina John, Eric A. Dubinsky, Yvette M. Piceno, Lauren M. Tom, Gary L. Andersen, Zhili He and Todd Z. DeSantis
from: Microarrays: Current Technology, Innovations and Applications (Edited by: Zhili He). Caister Academic Press, U.K. (2014)

Abstract

Deciphering microbial communities and their role in Earth's biosphere is crucial for addressing challenges in human health, agriculture, bioremediation and other natural processes. While next-generation sequencing platforms are still under development to improve accuracy, read length and sequencing depth, microarray-based methods have become an attractive alternative for 16S rRNA gene microbial community comparisons. The hybridization method is well-established in the laboratory. Thus main areas of improvement lie with the development of improved bioinformatics and statistical procedures for microarray data, rather than with improvements to the platform itself. In this communication we applied recently-developed bioinformatics tools to re-analyze G3 PhyloChip™ DNA microarray data acquired from deep ocean samples collected during the 2010 Deepwater Horizon oil spill in the Gulf of Mexico. We show that data collected with the G3 PhyloChip™ assay can be analyzed at various stages of resolution, from individual probes to pairs of probes to quartets of probes and finally at the commonly used probe-set level where each probe-set is associated with one operational taxonomic unit (OTU). Our analysis methods comprised topological data analysis to facilitate the detection of outlier bio-specimens and the reconstruction of empirical OTUs (eOTUs) in an unsupervised manner, without the need of pre-defined reference OTUs (rOTUs). We observed that the quartet level provided sufficient resolution for identifying a subtle outlier sample with TDA while the eOTU reconstruction was useful for annotation of the taxa associated with significant population changes in the elevated hydrocarbon waters. The presented methods will improve the deduction of important biological processes from G3 PhyloChip experiments read more ...
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