227
multiple genes from multiple organisms present in the community. Metagenomics
has been extensively applied to various environments across multiple spatial and
temporal scales (see review Sharpton 2014; Thomas et al. 2012). This is a powerful
technique that provides information about not just the microbial community
composition and structure, but also their functional potential. This approach enables
the identification of novel genes and biomarkers from uncultured organisms.
Allen et al. (2012) used a metagenomic approach to investigate microbial
responses to upwelling in Californian coastal waters, demonstrating that oligotrophic waters were dominated by alpha-proteobacteria (primarily Pelagibacter sp.)
and Prochlorococcus sp., with upwelled and aged upwelled water having distinctly
different microbial communities. Sites from oligotrophic waters had a greater number of genomes and lower estimated genome size, whereas sites from upwelling
regions had a smaller number of genomes and greater genome size (Allen et al.
2012). Upwelling sites were enriched in diatom sequences in the largest size class
(3.0–200 μm), as well as the picoeukaryotic prasinophytes, Micromonas sp. and
Ostreococcus sp. In contrast, offshore oligotrophic sites, particularly in the case of
the largest size class, were enriched in sequences classified as dinoflagellates or
other Alveolata. Within the picoeukaryotic size class (0.8–3.0 μm), the prasinophytes were more abundant at upwelling sites, whereas pelagophytes and ciliates
were more abundant at oligotrophic sites.
Whilst such genomic datasets are more comprehensive, faster to produce and
less dependent on taxonomic expertise, they rely on comparison with reference
sequences from known taxa. This has necessitated sequencing of key microbial taxa
to achieve representation of virus, bacteria and archaea genomes in reference databases, as well as a growing number of eukaryotes (Keeling et al. 2014).
Despite our increasing understanding of how microbes are distributed between
and within ocean basins, across depth and over time, there is still no consensus on
the role of environmental factors in regulating community assembly or whether
biotic interactions are more important (Giovannoni and Vergin 2012). Furthermore,
whilst genomic approaches provide a blueprint of the genetic diversity within communities, they lack information on gene expression dynamics and changes in microbial activity. To progress understanding of how microbes respond to different
aspects of their growth environment, we therefore need to go beyond genomic
approaches.
11.3 Influence of Oceanographic Processes on Microbial
Gene Expression
Transcriptomics involves the exploration of genes that are expressed at a given time
and place and how expression changes under different conditions. Whilst transcriptomics focuses on a single organism, metatranscriptomics is the sequencing of
expressed genes within a whole community. Gene expression changes reveal active
metabolic pathways and the molecular adjustment of cells in response to changing
growth conditions. This approach is useful in determining the molecular mechanisms
11 Application of ‘Omics’ Approaches to Microbial Oceanography
multiple genes from multiple organisms present in the community. Metagenomics
has been extensively applied to various environments across multiple spatial and
temporal scales (see review Sharpton 2014; Thomas et al. 2012). This is a powerful
technique that provides information about not just the microbial community
composition and structure, but also their functional potential. This approach enables
the identification of novel genes and biomarkers from uncultured organisms.
Allen et al. (2012) used a metagenomic approach to investigate microbial
responses to upwelling in Californian coastal waters, demonstrating that oligotrophic waters were dominated by alpha-proteobacteria (primarily Pelagibacter sp.)
and Prochlorococcus sp., with upwelled and aged upwelled water having distinctly
different microbial communities. Sites from oligotrophic waters had a greater number of genomes and lower estimated genome size, whereas sites from upwelling
regions had a smaller number of genomes and greater genome size (Allen et al.
2012). Upwelling sites were enriched in diatom sequences in the largest size class
(3.0–200 μm), as well as the picoeukaryotic prasinophytes, Micromonas sp. and
Ostreococcus sp. In contrast, offshore oligotrophic sites, particularly in the case of
the largest size class, were enriched in sequences classified as dinoflagellates or
other Alveolata. Within the picoeukaryotic size class (0.8–3.0 μm), the prasinophytes were more abundant at upwelling sites, whereas pelagophytes and ciliates
were more abundant at oligotrophic sites.
Whilst such genomic datasets are more comprehensive, faster to produce and
less dependent on taxonomic expertise, they rely on comparison with reference
sequences from known taxa. This has necessitated sequencing of key microbial taxa
to achieve representation of virus, bacteria and archaea genomes in reference databases, as well as a growing number of eukaryotes (Keeling et al. 2014).
Despite our increasing understanding of how microbes are distributed between
and within ocean basins, across depth and over time, there is still no consensus on
the role of environmental factors in regulating community assembly or whether
biotic interactions are more important (Giovannoni and Vergin 2012). Furthermore,
whilst genomic approaches provide a blueprint of the genetic diversity within communities, they lack information on gene expression dynamics and changes in microbial activity. To progress understanding of how microbes respond to different
aspects of their growth environment, we therefore need to go beyond genomic
approaches.
11.3 Influence of Oceanographic Processes on Microbial
Gene Expression
Transcriptomics involves the exploration of genes that are expressed at a given time
and place and how expression changes under different conditions. Whilst transcriptomics focuses on a single organism, metatranscriptomics is the sequencing of
expressed genes within a whole community. Gene expression changes reveal active
metabolic pathways and the molecular adjustment of cells in response to changing
growth conditions. This approach is useful in determining the molecular mechanisms
11 Application of ‘Omics’ Approaches to Microbial Oceanography