The Identification and Characterisation of Microbes in Complex Environments

The practice of genetically identifying microbes has become increasingly commonplace in recent decades. Since Carl Woese discovered the utility of small subunit ribosomal RNA, for identifying an organism and Frederick Sanger introduced his method for de novo sequencing, the throughput of producing taxonomically relevant sequence information has risen exponentially. Small subunit rRNA has been invaluable in preliminarily identifying microbial organisms. With just a fragment of this single gene sequence, evolutionary distances between organisms can be inferred and microbes identified. A novel software pipeline - SSuMMo - was designed and developed to help identify organisms present in complex microbial communities, using datasets produced by the latest high-throughput sequencing technologies. SSuMMo was stringently tested for accuracy, speed and efficacy on a variety of datasets to assess its utility when analysing real sequence datasets, generated from both 16S rRNA primer-targeted and whole genome shotgun sequencing experiments. Sequence length is often compromised with recent high-throughput sequencing technologies, so simulations were performed to ascertain the best candidate regions for primer design on the 16S rDNA gene. The software is further demonstrated on public sequence datasets generated from sequencing the human oral and gut microbiomes. Our analyses show that SSuMMo is a viable software package for identifying species present in complex communities, particularly with primer-targeted high-throughput sequence datasets.