Metatranscriptomic analyses of chlorophototrophs of a hot-spring microbial mat

Zhenfeng Liu, Christian G. Klatt, Jason M. Wood, Douglas B. Rusch, Marcus Ludwig, Nicola Wittekindt, Lynn P. Tomsho, Stephan C. Schuster, David M. Ward, Donald A. Bryant

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


The phototrophic microbial mat community of Mushroom Spring, an alkaline siliceous hot spring in Yellowstone National Park, was studied by metatranscriptomic methods. RNA was extracted from mat specimens collected at four timepoints during light-to-dark and dark-to-light transitions in one diel cycle, and these RNA samples were analyzed by both pyrosequencing and SOLiD technologies. Pyrosequencing was used to assess the community composition, which showed that 84% of the rRNA was derived from members of four kingdoms Cyanobacteria, Chloroflexi, Chlorobi and Acidobacteria. Transcription of photosynthesis-related genes conclusively demonstrated the phototrophic nature of two newly discovered populations; these organisms, which were discovered through metagenomics, are currently uncultured and previously undescribed members of Chloroflexi and Chlorobi. Data sets produced by SOLiD sequencing of complementary DNA provided 100-fold greater sequence coverage. The much greater sequencing depth allowed transcripts to be detected from 15 000 genes and could be used to demonstrate statistically significant differential transcription of thousands of genes. Temporal differences for in situ transcription patterns of photosynthesis-related genes suggested that the six types of chlorophototrophs in the mats may use different strategies for maximizing their solar-energy capture, usage and growth. On the basis of both temporal pattern and transcript abundance, intra-guild gene expression differences were also detected for two populations of the oxygenic photosynthesis guild. This study showed that, when community-relevant genomes and metagenomes are available, SOLiD sequencing technology can be used for metatranscriptomic analyses, and the results suggested that this method can potentially reveal new insights into the ecophysiology of this model microbial community.

Original languageEnglish (US)
Pages (from-to)1279-1290
Number of pages12
JournalISME Journal
Issue number8
StatePublished - Aug 2011

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics


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