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The shotgun approach to proteomics is an alternative to the electrophoretic meth-
ods discussed above. In this method, complex mixtures of proteins are analyzed using
some of the many methods described earlier in this chapter, including LC/MS and
LC/MS/MS. Protein quantitation can be a drawback to this methodology. In addition,
1D-GE can be combined with LC separation whereby a mixture of proteins is sepa-
rated on a 1D gel and individual bands are digested with trypsin. The tryptic peptides
are, in turn, analyzed on LC/MS and MS/MS. There are numerous commercial soft-
ware packages available to analyze the resultant data ( Hayes and Krieger, 2010 ).
Quantification of proteins is an active area of proteomics research and can be
achieved through the use of stable isotope probes. Labeling techniques, such as the iso-
tope-coded affinity tag or the cleavable isotope-coded affinity tag, allow proteins to be
separated on avidin/biotin columns but label cysteine residues exclusively. Isobaric tags
for relative and absolute quantitation allow for amine-specific isobaric tagging and thus
are suitable for simultaneous analysis of proteins regardless of the presence of cysteine
residues. One novel method can label arginine and lysine in vivo, stable isotope label-
ing by essential amino acid culture.
All of these techniques rely heavily on bioinformatics. Tools for bioinformatics
include software packages to analyze the extremely large data sets that are derived from
2D-GE and MS analysis. Software packages are available to analyze 2D-GE images for
the detection and semiquantification of protein spots on 2D gels, the localization of
protein spots within a gel, the matching of corresponding spots between gels, and the
differential comparison of protein expression. For a more complete list of the various
models, databases, and software packages available, the reader is directed to Chapter 21
in Hayes and Krieger (2010).
METABOLOMICS
Metabolomics is the systematic study of a metabolome, the entirety of metabolites, or a
set of metabolites, forming an extensive network of metabolic reactions in which one
metabolite from a specific pathway will affect one or more biochemical reactions, or
a comprehensive and quantitative analysis of all metabolites. Arguably, metabolomics
is the least well characterized of all the omics in systems biology, as well as the most
complex and dynamic. Consequently, it is perhaps less well defined. Indeed the term
“metabolomics” was first proposed only in 1998, although various forms of research in
metabolic profiling have been undertaken for many years. Given the wide variation in
the possible metabolites of a given chemical such as a pesticide, there is no one unified
method to determine the metabolome. In general terms, the three primary methods
used in metabolomics studies include MS, nuclear magnetic resonance (NMR), and
deconvolution and structure identification. As with proteomics, there is also significant
reliance on bioinformatics and data mining.
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