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endogenous proteins, either at a small scale involving one
or a few different proteins or involving entire cellular
proteomes. It provides a crucial layer of information on the
proteins that previously had to be inferred indirectly from
other measurements, or was absent altogether.
Given the increasingly mature proteomics toolbox, an
ever larger set of cell biological and biomedical problems
can now be tackled. For instance, we expect many more
reports of essentially complete proteome measurements, as
well as highly accurate comparative transcriptome and
proteome studies. It will be interesting to see whether MS-
based proteomics can make inroads into the clinical area,
for instance in classifying cancer patients by their protein
expression patterns.
Despite these promises, major challenges with MS-
based proteomics remain. Foremost among these is the
limited community access to high-accuracy in-depth pro-
teomics. Compared to transcriptomics and the current
massive investments into deep-sequencing based technol-
ogies, the area of MS-based proteomics remains tiny. There
are also entire areas, such as body fluid-based biomarker
discovery, where MS-based proteomics could in principle
make a revolutionary impact but where our current tech-
nology fails woefully to live up to expectations. On the
other hand, this means that MS-based proteomics will offer
exciting opportunities for young researchers for years to
come.
From a systems biology perspective, the ability of
proteomics to detect not only the presence of but to also to
estimate copy numbers of virtually all proteins in a pro-
teome will be crucial in modeling the cellular proteome.
Equally important, proteomics is now poised to deliver
increasingly comprehensive lists of the major PTMs,
including phosphorylation, ubiquitylation, acetylation,
glycosylation and many more. This is a precondition for
determining their function, which will be a monumental
task for the years ahead, and for accurate models of
information processing in the cell. Identification and
quantification of protein isoforms is still a challenge for
MS-based proteomics, but it is becoming increasingly
accessible due to more extensive sequence coverage of the
identified proteins. The direct analysis of undigested
proteins by MS ('top-down' proteomics) will
contribute tremendously to accurate and comprehensive
mapping of the abundance of mRNA molecules, an early
step in the gene expression program. However, this is still
only half of the story. Proteomics can give us a detailed
picture of the end product of the gene expression cascade,
the mature, active and fully modified protein form. It also
measures regulation directly at the expression level of all
proteins, which cannot be predicted from transcript levels.
In contrast to genomics and transcriptomics, it can char-
acterize gene expression at subcellular resolution, i.e., by
analyzing the proteomes of different cellular compart-
ments. Furthermore, the interactions and dynamics of the
proteome can likewise be studied either at a whole cell level
or in individual subcellular compartments. In conclusion,
despite the technological challenges it faces, MS-based
proteomics is crucial to a systems-level understanding of
cellular function, and is ready to make even more extensive
contributions to the field in the future.
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e
also
contribute to this question.
Figure 1.6
summarizes the indispensable role of pro-
teomics in the context of other large-scale methods of
genomics and gene expression analysis. Both genomics and
transcriptomics benefit from the current revolution in next-
generation sequencing methods. We expect deep-
sequencing data to be readily accessible for essentially
every situation of interest in systems biology in the near
future. This includes the genomes of different individuals
as well as differences between normal and cancer genomes
in the same individuals. Likewise, deep sequencing will
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