Proteomics is the study of the entire complement of proteins in a cell or tissue—the proteome. The proteome is much more complicated than the genome because the proteome differs from cell to cell and from time to time, whereas the genome of an organism is largely unchanged between cells and over time. Furthermore, most proteins in a cell undergo posttranslational modifications (for example, phosphorylation, glycosylation, methylation, and ubiquination), which can result in several functional forms of the same protein. The proteome is potentially far more informative than the genome with respect to environmental response. Measuring and understanding changes in the proteome after environmental perturbations are therefore increasingly important in many fields of environmental science and engineering. Proteomic technologies and approaches will have an increasingly important role in environmental monitoring and health risk assessment of relevance to EPA. For example, proteome-based biomarkers may be useful in deciphering the associations between pesticide exposure and cancer and will perhaps lead to potential predictive biomarkers of pesticide-induced carcinogenesis (George and Shukla 2011).
Proteomics has been used to explore “a multitude of bacterial processes, ranging from the analysis of environmental communities [and the] identification of virulence factors to the proteome-guided optimization of production strains” (Chao and Hansmeier 2012). Proteomics has become a valuable tool for the global analysis of bacterial physiology and pathogenicity, although many challenges remain, especially in the accurate prediction of phenotypic consequences based on a given proteome composition (Chao and Heinsmeyer 2012). Lemos et al. (2010) have discussed the advantages of and challenges to using proteomics in ecosystems research.
Substantial improvements in instrumentation, especially nuclear magnetic resonance spectroscopy (Serkova and Niemann 2006) and mass spectrometry (Dettmer et al. 2007), provide increasingly sensitive approaches to measuring hundreds or even thousands of small molecules in a cell in a matter of minutes. The new technologies have given rise to a promising new -omics technology referred to as metabolomics—the “systematic study of the unique chemical fingerprints that specific cellular processes leave behind” (Bennett 2005) or, more specifically, the study of their small-molecule metabolite profiles. “In analogy to the genome, which is used as synonym for the entirety of all genetic information, the metabolome represents the entirety of the metabolites within a biological system” (Oldiges et al. 2007). The total number of metabolites in a single cell, tissue, or organism is, of course, highly variable and depends on the biologic system investigated. Hundreds of distinct metabolites have been identified in microorganisms. For example, the Escherichia coli database EcoCYC contains over 2,000 metabolite entries (Keseler et al. 2011), and the metabolome of