Modern microbial mats are potential analogues of some of Earth’s earliest ecosystems. Excellent
examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our
understanding of the functional genetic potential of these complex microbial ecosystems, we
conducted for the first time shotgun metagenomic analyses. We assembled metagenomic nextgeneration
sequencing data to classify the taxonomic and metabolic potential across diverse
morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications
using protein-coding and small subunit rRNA genes directly extracted from the metagenomes
suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats.
However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas)
marine systems appears to be distinct from each other. The metabolic potential (based on SEED
subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also
distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic
and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively
by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive
TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay
metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming
ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as
well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are
highly represented in Shark Bay and may have critical roles in overall ecosystem function in these
modern microbial mats.
Revised: March 3, 2020 |
Published: May 29, 2015
Citation
Ruvindy R., R.A. White, B.A. Neilan, and B.P. Burns. 2015.Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics.The ISME Journal 10.PNNL-SA-120477.doi:10.1038/ismej.2015.87