PCR Amplification-Independent Methods for Detection of Microbial Communities by the High-Density Microarray PhyloChip

Abstract

Environmental microbial community analysis typically involves amplification by PCR, despite well-documented biases. We have developed two methods of PCR-independent microbial community analysis using the high-density microarray PhyloChip: direct hybridization of 16S rRNA (dirRNA) or rRNA converted to doublestranded cDNA (dscDNA). We compared dirRNA and dscDNA communities to PCR-amplified DNA communities using a mock community of eight taxa, as well as experiments derived from three environmental sample types: chromium-contaminated aquifer groundwater, tropical forest soil, and secondary sewage in seawater. Community profiles by both direct hybridization methods showed differences that were expected based on accompanying data but that were missing in PCR-amplified communities. Taxon richness decreased in RNA compared to that in DNA communities, suggesting a subset of 20% in soil and 60% in groundwater that is active; secondary sewage showed no difference between active and inactive populations. Direct hybridization of dscDNA and RNA is thus a viable alternative to PCR-amplified microbial community analysis, providing identification of the active populations within microbial communities that attenuate pollutants, drive global biogeochemical cycles, or proliferate disease states.

Library preparation methodology can influence genomic and functional predictions in human microbiome research

“…Previously published studies report a potential bias in the %G+C in XT libraries sequenced on the Roche 454 Titanium platform (14) and on the MiSeq platform (15). Using the mock community, we analyzed the relative measurements of species abundance for each library protocol with respect to %G+C.…”

Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses

“…Historically, rRNA analyses have been used to quantify populations' growth rates in mixed microbial communities (for example, Poulsen et al, 1993;Muttray et al, 2001), but recent application has shifted toward the more qualitative approach using rRNA to identify currently active microbial populations in a mixed community (for example, Jones and Lennon, 2010;Kamke et al, 2010;Campbell et al, 2011;DeAngelis et al, 2011;Gaidos et al, 2011;Reid et al, 2011;Baldrian et al, 2012;Mannisto et al, 2012;Mattila et al, 2012;Simister et al, 2012;Campbell and Kirchman, 2013;Hunt et al, 2013;Yarwood et al, 2013). Two principal lines of evidence used to support rRNA as an indicator of current activity originate from earlier studies testing how rRNA scales with growth rate.…”

“…The issue of dormant cells containing measurable rRNA concentrations can be especially problematic when using rRNA data to identify currently active organisms in environments likely to contain many dormant organisms such as soil, deep subsurface, frozen environments or the atmosphere. One approach to discounting rRNA in dormant cells is to estimate the rRNA concentration per cell for specific taxa by calculating rRNA:rRNA gene ratios, then defining a minimum cutoff value for activity (for example, DeAngelis et al, 2011;Jones and Lennon, 2010). However, rRNA:rRNA gene ratios have been characterized for very few bacteria in dormant state.…”

New perspectives on viable microbial communities in low-biomass cleanroom environments

“…In such cases, however, there is inherent risk of overestimating the total number of viable cells in samples because of variation in binding affinities of the dyes used. Methods probing RNA as an alternative to DNA have also been developed for assessing viability (DeAngelis et al, 2011), but these too come with complications as RNA is difficult to purify, less stable, prone to degradation and often isolated in quantities insufficient for analysis (Hierro et al, 2006;Andorra et al, 2010).…”