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Analysis of microbial gene transcripts in environmental samples.

ABSTRACT: We analyzed gene expression in marine and freshwater bacterioplankton communities by the direct retrieval and analysis of microbial transcripts. Environmental mRNA, obtained from total RNA by subtractive hybridization of rRNA, was reverse transcribed, amplified with random primers, and cloned. Approximately 400 clones were analyzed, of which approximately 80% were unambiguously mRNA derived. mRNAs appeared to be from diverse taxonomic groups, including both Bacteria (mainly alpha- and gamma-Proteobacteria) and Archaea (mainly Euryarchaeota). Many transcripts could be linked to environmentally important processes such as sulfur oxidation (soxA), assimilation of C1 compounds (fdh1B), and acquisition of nitrogen via polyamine degradation (aphA). Environmental transcriptomics is a means of exploring functional gene expression within natural microbial communities without bias toward known sequences, and provides a new approach for obtaining community-specific variants of key functional genes.

SUBMITTER: Poretsky RS

PROVIDER: S-EPMC1168992 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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Analysis of microbial gene transcripts in environmental samples.

Poretsky Rachel S RS Bano Nasreen N Buchan Alison A LeCleir Gary G Kleikemper Jutta J Pickering Maria M Pate Whitney M WM Moran Mary Ann MA Hollibaugh James T JT

Applied and environmental microbiology 20050701 7

We analyzed gene expression in marine and freshwater bacterioplankton communities by the direct retrieval and analysis of microbial transcripts. Environmental mRNA, obtained from total RNA by subtractive hybridization of rRNA, was reverse transcribed, amplified with random primers, and cloned. Approximately 400 clones were analyzed, of which approximately 80% were unambiguously mRNA derived. mRNAs appeared to be from diverse taxonomic groups, including both Bacteria (mainly alpha- and gamma-Prot ...[more]

PMID: 16000831

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Project description:RNA-seq-based SSU (small subunit) rRNA (ribosomal RNA) analysis has provided a better understanding of potentially active microbial community within environments. However, for RNA-seq library construction, high quantities of purified RNA are typically required. We propose a modified RNA-seq method for SSU rRNA-based microbial community analysis that depends on the direct ligation of a 5' adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10-100 ng) and does not require a DNA removal step. The method was initially tested on three mock communities synthesized with enriched SSU rRNA of archaeal, bacterial and fungal isolates at different ratios, and was subsequently used for environmental samples of high or low biomass. For high-biomass salt-marsh sediments, enriched SSU rRNA and total nucleic acid-derived RNA-seq datasets revealed highly consistent community compositions for all of the SSU rRNA sequences, and as much as 46.4%-59.5% of 16S rRNA sequences were suitable for OTU (operational taxonomic unit)-based community and diversity analyses with complete coverage of V1-V2 regions. OTU-based community structures for the two datasets were also highly consistent with those determined by all of the 16S rRNA reads. For low-biomass samples, total nucleic acid-derived RNA-seq datasets were analyzed, and highly active bacterial taxa were also identified by the OTU-based method, notably including members of the previously underestimated genus Nitrospira and phylum Acidobacteria in tap water, members of the phylum Actinobacteria on a shower curtain, and members of the phylum Cyanobacteria on leaf surfaces. More than half of the bacterial 16S rRNA sequences covered the complete region of primer 8F, and non-coverage rates as high as 38.7% were obtained for phylum-unclassified sequences, providing many opportunities to identify novel bacterial taxa. This modified RNA-seq method will provide a better snapshot of diverse microbial communities, most notably by OTU-based analysis, even communities with low-biomass samples.

Dataset Information

Analysis of microbial gene transcripts in environmental samples.

Publications

Analysis of microbial gene transcripts in environmental samples.

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