The Combined Use of PLFA, T-RFLP, and Pyrosequencing On Soil and Rhizosphere Samples to Describe Microbial Community Response to Cover Crops in Tomato Production Systems.

A three-year fully replicated field experiment was used to test hypotheses concerning the effects of agricultural management and environmental conditions on soil and rhizosphere microbial biomass and community structure. Bulk soil samples were collected 5 times per year from 36 plots representing 9 treatments replicated in quadruplicate, while tomato rhizosphere samples were collected 3 times each year from the same plots. PLFA was run on all 864 samples, while T-RFLP was used with various primers on 48 samples and pyrosequencing with a universal eubacterial primer pair was run on 12 samples. PLFA data was used for microbial biomass, biomass of individual taxonomic groups, and community composition. T-RFLP was used to determine how the community structure of Archaebacteria, Eubacteria, Bacillus, beta-Proteobacteria, and Planctomycetes responded to treatment, season, and habitat. Pyrosequencing provided detailed data on the community structure and diversity of eubacteria at the genus level. While T-RFLP provided more detailed community structure information than PLFA on these phylogenetic groups, the biomass data provided by PLFA was very useful to understanding the dynamics of the agroecosystem. Each phylogenetic group responded differently to the treatment factors therefore linking total microbial biomass and the biomass of each individual taxonomic group provided additional insight into the microbial community dynamics. The additional detail on community structure, combined with the unique diversity data, made the pyrosequencing data very valuable. In addition, the pyrosequencing data verified some of the biomarkers used in the PLFA method. We suggest that prescreening large numbers of samples with PLFA or TRFLP in order to determine which samples to run by pyrosequencing may be useful in many studies as a means of augmenting the inference domain of traditional biomarker data while keeping experimental costs low. We further suggest that, in experiments where biomass data will aid interpretation, PLFA combined with pyrosequencing has great potential to advance the understanding of soil microbial ecology in response to agricultural treatments.