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emerged. Here, in contrast to other approaches, such as classical proteomics,
shot-gun proteomics or targeted proteomics relying on SRM, datasets of the highest
complexity are generated in a completely unbiased and untargeted mode of acquisi-
tion ( Bensimon et al. , 2012 ). Here, conceptually, two approaches for data generation
exist: the first, MS E , is a vendor-specific acquisition mode, whilst the second
approach relies on mass spectrometric equipment being capable of fast acquisitions
of larger m / z windows for triggering tandem mass spectra.
MS E is characterized by alternating scan modes: overview scans targeting the
intact peptide masses eluting from a reversed-phase column are constantly alternated
with collision-induced dissociation scans, fragmenting all precursor ions simulta-
neously ( Bateman et al. , 2002 ). The bioinformatic post-processing of the data from
this mode of acquisition is strictly dependent on a highly reproducible LC-MS
set-up. This ensures that the retention times are stable enough to facilitate the
reassignment of the elution profiles of peptide fragment masses to their respective
precursors in the overview scan ( Silva et al. , 2006a,b ).
The second group of acquisition strategies bypasses the decision step of selecting
precursor masses suitable for fragmentation, thereby allowing for a bias-free mode of
data acquisition ( Venable et al. , 2004; Panchaud et al. , 2009; Geiger et al. , 2010;
Panchaud et al. , 2011; Gillet et al. ,2012 ). Technically, overview scans are followed
by collision-induced dissociation scans fragmenting sections of the gas phase of
different size and number. Most popular are the methods of precursor acquisition that
are independent of ion count ( Panchaud et al. , 2011 ) and the more recent develop-
ment SWATH TM MS ( Gillet et al. , 2012 ). Analyses of this type are heavily depen-
dent on the large amount of identification data that has been previously generated by
data-dependent mass spectrometry-based proteomics and which is stored in publicly
available repositories ( Gillet et al. , 2012 ).
In addition to the evident advantage of the data-independent methods to avoid
discrimination of certain peptide ion species in terms of abundance or physico-
chemical properties, the datasets generated are ready to use for screening, for exam-
ple, for unusual PTM or peptides which should be covered in these comprehensive
datasets both at the MS1 (overview scan) and MS2 (fragment ions) levels.
2 ABSOLUTE QUANTIFICATION WORKFLOWS IN PROTEOMICS
2.1 Fusion protein-based global scale protein quantification
The need for absolute quantification data for systems biology approaches has led to a
number of protocols for generation of such data in different organisms and the appli-
cation of a range of technologies. In microbiology, groundbreaking work has been
published on the cellular level quantification of all proteins of Saccharomyces
cerevisiae . Early approaches to the determination of absolute protein abundances at
a proteome-wide scale relied on GFP-tagging or immuno-affinity approaches
targeting the specific epitope tags ( Ghaemmaghami et al. , 2003; Huh et al. , 2003 ).
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