Transcriptome fingerprinting analysis: an approach to explore gene expression patterns in marine microbial communities

Coll Lladó, Montserrat; Acinas, Silvia G.; Pujades Corbi, Cristina; Pedrós-Alió, Carles

doi:http://dx.doi.org/10.1371/journal.pone.0022950

Transcriptome fingerprinting analysis: an approach to explore gene expression patterns in marine microbial communities

Citation

Coll-Lladó M, Acinas SG, Pujades C, Pedrós-Alió C. Transcriptome fingerprinting analysis: an approach to explore gene expression patterns in marine microbial communities. PLoS ONE. 2011;6(8):e22950. DOI: 10.1371/journal.pone.0022950

Abstract

Microbial transcriptomics are providing new insights into the functional processes of microbial communities. However, analysis of each sample is still expensive and time consuming. A rapid and low cost method that would allow the identification of the most interesting samples for posterior in-depth metatranscriptomics analysis would be extremely useful. Here we present Transcriptome Fingerprinting Analysis (TFA) as an approach to fulfill this objective in microbial ecology studies. We have adapted the differential display technique for mRNA fingerprinting based on the PCR amplification of expressed transcripts to interrogate natural microbial eukaryotic communities. Unlike other techniques, TFA does not require prior knowledge of the mRNA sequences to be detected. We have used a set of arbitrary primers coupled with a fluorescence labeled primer targeting the poly(A) tail of the eukaryotic mRNA, with further detection of the resulting labeled cDNA products in an automated genetic analyzer. The output represented by electropherogram peak patterns allowed the comparison of a set of genes expressed at the time of sampling. TFA has been optimized by testing the sensitivity of the method for different initial RNA amounts, and the repeatability of the gene expression patterns with increasing time after sampling both with cultures and environmental samples. Results show that TFA is a promising approach to explore the dynamics of gene expression patterns in microbial communities