Denitrification in the Sediments of Chesapeake Bay:  Comparing DNA and mRNA microarrays to Understand nirS Gene Expression

The purpose of this project is to understand how the community composition and activity of denitrifying bacteria in sediments vary along a natural nutrient and salinity gradient.  We applied the microbial diagnostic microarray method to study nirS gene expression in natural assemblages. On each feature (spot) of the microarray, PCR-amplified environmental DNA or cDNA hybridizes to probes designed specifically to target nirS archetypes, developed from clone libraries of nirS previously obtained from the same Chesapeake Bay sites.  The DNA microarray method proved useful in detecting diversity of the functional gene nirS, thus characterizing the community composition in Chesapeake Bay sediment.  To move beyond a semi-quantitative measure of presence/absence, however requires applying the technology to messenger RNA. Using mRNA allows identification and semi-quantification of expression of individual nirS phylotypes at the community level. The DNA microarray results were consistent with the clone library results; both detected the same groups as most abundant at the three sites, and both detected the same trend of decreasing nirS diversity along the freshwater to marine gradient (CB1 = freshwater, CB2 = mid Bay, CB3 = marine end of the Bay).  mRNA microarrays indicated that the dominant denitrifying groups as detected by DNA arrays and in the clone libraries, also dominate expression of nirS in the environment.  The mRNA microarray has proved to be a powerful tool in comparing the composition and gene expression of natural microbial communities to a previously unavailable level.

The symbols indicate the presence or absence of a given OTU at each site in the Chesapeake Bay as determined by the DNA microarray procedure. The circled symbols represent probes for which the mRNA is expressed. The most abundant isolate in the clone libraries, CB2-S-138, was present and abundant at all three sites.

Ward Lab Participants: Silvia Newell