Metagenomic Approach to Understanding Microbial Environmental Adaptation

Microbes evolve to adapt to their surroundings and react to long- and short- term environmental changes. Both physical and chemical changes may affect the composition of the microbial community and/or be presented as shifts in... [ view full abstract ]

Microbes evolve to adapt to their surroundings and react to long- and short- term environmental changes. Both physical and chemical changes may affect the composition of the microbial community and/or be presented as shifts in genetic makeups. These changes can potentially be measurable, and may indicate current or past physical or chemical conditions in the surrounding environment.

We are interested in gaining insight into genetic and metabolic changes in microbial networks responding to low level radiation and chemical variations.  Previous observations are derived largely from incidents or controlled exposure experiments on bacterial isolates, which is a poor reflection of a microbial community behavior. We aim to examine microbial metagenomic and transcriptomic profiles from an environment with a low background level of chemicals and/or radiation. A systematic study in a canonical environment where background measurements can potentially be available may reveal taxonomic network within a microbial community, and traits conferring fitness. Such study will help further understand sensing and regulatory mechanisms including receptors sensing ecological factors, transcriptional and translational control mechanisms, metabolic modulation of enzymes, and signal relay deviations.

 Microbial community structure will be clustered by operational taxonomic units (OTU).  Under each environmental location, data representing OTU cluster distances will be defined in dissimilarity matrices.  Spatial Analysis through mantel tests will correlate the dissimilarity matrices to explain the distribution within a community in terms of environmental variables.  Other statistical tests will be used to correlate environmental variables against microbial community architecture.