Awkward microbes? Genomic sequence them!

We are all aware of the diverse communities of microbes found throughout the ocean. We are also aware from lectures that we have a huge blind spot when experimenting on these marine microbes, due to culturing techniques. Iverson et al. (2012) attempted to reveal individual genomes from a soup of DNA, created by sampling water taken from a sound within the US in October 2008 and May 2009. When compared to information of 16S rDNA from the GOS database only 10% had previously been sequenced. Whether this is due to seasonal sampling or the fact that GOS may not have sampled from within that particular sound it is unclear, regardless it supports the idea that we still know very little about the marine microbiological communities.

Iverson et al. (2012) discovered an uncultured class of marine Euryarchaeota within the metagenome from the two samples and reconstructed a closed genome, created by a possible 5 different strains of Euryarchaeota. They then investigated the potential metabolism of this Archaea by comparing the constructed genome to known genes from GenBank and discovered many similarities to bacteria. There were genes for carbon metabolism through glycolysis, gluconeogenesis and the TCA cycle. In addition to this there were many genes for protein and lipid degradation and lipid biosynthesis pathways similar to that found in bacteria. Archaeal flagella genes were also found suggesting motility of the group with rhodopsin genes possibly buffering energy production when searching for metabolites. The newly discovered Euryarchaeota are therefore considered motile photo-heterotrophs, whose closest relative is a thermoacidophile Aciduliprofundum boonei. The drawbacks to this comparison method is that new exciting unique genes will be missed, but it is a valuable technique which allows for further study and adaption of laboratory techniques.

It is emerging that culture based techniques are insufficient when assessing microbial diversity within a community and the genomic techniques used in this paper emphasise this point. Because much of their methods used specific gene programmes and their stats language I haven’t come across before, im restricted in comments to their methods, however I enjoyed the paper as it shows that metabolic inference is capable from direct in situ samples. Although this technique would only show the genomes of abundant bacteria, and low density microbes may be missed.

Vaughn Iverson, Robert M. Morris, Christian D. Frazar, Chris T. Berthiaume, Rhonda L. Morales, E. Virginia Armbrust. (2012) Untangling Genomes from Metagenomes: Revealing an Uncultured Class of Marine Euryarchaeota