Microorganisms are the most abundant, diverse and ubiquitous forms of life on Earth. Although primarily in the public mind as agents of disease, they in fact have much larger global significance by driving all of the biogeochemical cycles that sustain life on this planet and directly influence our climate. Microbial conversions also are pivotal in engineered environments. For example, many wastewater sanitation and all fermentation processes rely on the actions of microorganisms. More recently, microorganisms are being harnessed for energy production such as in microbial fuel cells and biofuels and their beneficial roles in reducing or preventing human disease are beginning to be recognized.
Unfortunately, the great majority of microorganisms cannot be grown in the laboratory due to the limitations of conventional culture-based approaches. As a result, our understanding of microbial diversity and physiology is highly biased to a few model organisms. To begin to understand how microbial ecosystems really function, we need broadly applicable culture-independent techniques to probe microbial communities in situ.
Fortunately, a whole range of culture-independent technologies have emerged in recent years that are revolutionizing our understanding of the microbial biosphere. Chief amongst these are sequence-based methods that rely on cheap high-throughput sequencing of DNA and RNA extracted directly from environmental samples (metagenomics and metatranscriptomics respectively). Similarly, mass spectrometry-based identification of peptides and small molecules has reached the stage that it is now possible to identify many proteins (metaproteomics) and metabolites (metabolomics) in environmental samples. In parallel, cell sorting and whole genome amplification methods are making single cell genomics a reality, providing a natural complement to ‘whole’ community characterization methods. One other important experimental approach, also advancing rapidly, is cell imaging that provides a high-resolution spatial framework on which to overlay molecular data. All of these techniques can be combined into an integrated ecological framework using computational advances and new modelling approaches, which we define as ‘ecogenomics’.