Genome

The prevailing ethos in the emerging field of synthetic biology is to understand biology through engineering and re-design. This approach has been directed towards the construction of novel genetic regulatory circuits, altered metabolic pathways, and even whole genomes. The ‘Yeast 2.0’ project is an international synthetic biology collaboration aimed at building a fully synthetic Saccharomyces cerevisiae genome by 2017. Although only modest changes are being made to the natural genome sequence, an inducible evolution system in being incorporated into the synthetic genome that can result in large-scale genomic rearrangements. This ‘Synthetic Chromosome recombination and Modification by LoxP Mediated Evolution’ (SCRaMbLE) system will be used to generate millions of unique genomes with varied architecture and gene content. By placing appropriate selection pressure on SCRaMbLEd populations, cells with minimal genomes or superior industrial properties can be recovered. Sequencing the genomes of these isolates will then be carried out with the goal of revealing novel ‘design principles’ for rational engineering, fulfilling the synthetic biology mandate to learn by building.

Since 2004 technological advances have enabled us to sequence more nucleic acid and generate more data in a shorter amount of time. Decreases in cost per nucleotide sequenced, the initial price of sequencing machines and the complexity of library construction means that whole genome sequencing (WGS) is available in many research labs and an increasing number of public health microbiology labs. I will examine the use of WGS in public health microbiology, particularly the possibility of investigating organisms without culture, the interrogation of genomes where PCR may be unavailable, outbreak investigation, tracking resistance mutations and novel pathogen discovery.

Metagenomics is a valuable tool for the study of microbial communities but has been limited by the difficulty of “binning” the resulting sequences into groups corresponding to the individual species and strains that constitute the community. Moreover, there are presently no methods to track the flow of mobile DNA elements such as plasmids through communities or to determine which of these are co-localized within the same cell. We address these limitations by applying Hi-C, a technology originally designed for the study of three-dimensional genome structure in eukaryotes, to measure the cellular co-localization of DNA sequences. We leveraged Hi-C data generated from a synthetic metagenome sample to accurately cluster metagenome assembly contigs into a small number of groups that differentiated the genomes of each species. The Hi-C data also associated plasmids with the chromosomes of their host and with each other orders of magnitude more frequently than to other species. We further demonstrated that Hi-C data is highly informative for resolving strain-specific genes and nucleotide substitutions between two closely related E. coli strains, K12 DH10B and BL21 (DE3), indicating such data may be useful for high-resolution genotyping of microbial populations. Our work demonstrates that Hi-C sequencing data provide valuable information for metagenome analyses that are not currently obtainable by other methods. This application of Hi-C has the potential to provide new perspective in the study of thefine-scale population structure of microbes, how antibiotic resistance plasmids (or other genetic elements) mobilize in microbial communities, and the genetic architecture ofheterogeneous tumor clone populations.

Bacterial communities growing as biofilms are subject to a distinct lifecyle, featuring initial surface attachment, microcolony formation and dispersal of cells. Bacterial biofilms are sometimes characterised by high levels of heritable phenotypic variants, presumably resulting from genetic diversification during the biofilm lifecyle. As biofilms are a favoured lifestyle of many environmental and pathogenic bacteria, identifying the evolutionary processes responsible for this diversification has important implications, both for our understanding of ecological processes, such as niche adaptation, and to clinically relevant questions, such as the evolution of antibiotic resistance.
I've used longitudinal genome-wide deep sequencing to reveal the underlying genetic structure of bacterial populations growing as biofilms, for the model organisms Phaeobacter gallaeciensis 2.10 (an abundant marine bacterium) and Pseudomonas aeruginosa 18A (a clinical Cystic Fibrosis isolate). Biofilms were grown under defined laboratory conditions known to generate reproducible phenotypic diversification. Samples from different stages of biofilm development were then sequenced to very high coverage (>800x). By accounting for sequencing errors using a matched-sample approach, variants with population frequencies as low as 0.5% could be accurately identified.
In general, the extent and nature of genetic variation was comparable for biofilms of both model organisms, being driven by selection for a small number of non-synonymous variants within key genes involved in biofilm- and competition-related pathways. These results also demonstrate that genome-wide deep sequencing can rapidly, accurately and comprehensively describe genetic variation within evolving populations.

The recent application of next-generation DNA sequencing tools has provided a wealth of new information about the diversity of microbial life, however the ecological factors which determine spatial patterns in prokaryotic gene abundance remain elusive. Using metagenomics and high-throughput sequencing of taxonomic marker genes, we have demonstrated shifts in microbial taxonomy and function along a salinity and nutrient gradient in the Coorong lagoon, South Australia. Functionally, genes showing the greatest response to physiochemical variability are related to salinity tolerance and photosynthesis. Taxonomically, Cyanobacteria and Archaea showed the greatest shifts in abundance along the gradient. Despite this variability however, the overall signature of metagenomic profiles remained remarkably conserved between sampling sites, and when compared to metagenomes from diverse habitats clustered with diverse sediment and soil habitats, regardless of salinity. This data indicates that the substrate type of the sample, fluid or porous, is a fundamental determinant of patterns in microbial community function globally, regardless of local chemical conditions. Whilst microbial community structure is determined on varying global and local scales, as demonstrated by the above data, the behaviour of microorganisms is determined on the microscale, with individual cells responding to gradients in specific nutrients in a patchy ecosystem. Using novel in situ sampling devices, and next-generation DNA sequencing techniques, our future work will focus on describing the microscale interactions between cells and nutrients in the ocean and how this relationship relates to ocean scale biogeochemical processes within the Carbon, Nitrogen and Sulfur cycles.