Quantification of Proteins by Label-Free LC-MS/MS - LC-MS/MS in Proteomics: Methods and Applications - page 223

Fig. 13.2. The table shows partial and hypothetical data matrices before and after normalization. The rows are the
detected features (peptides) and the columns include the mass, retention time, and intensity in all injections of all
samples. In this example, sample 1_02 had the highest sum of intensities; therefore, its normalization factor was set to
1. All the other samples are referenced to it. In actual practice the sum includes all detected features.

corresponding area for any given monoisotopic ion is reported as
the summed area from all contributing charge states. The reten-
tion time is determined for each reported monoisotopic ion at the
moment it reaches its maximum intensity (apex). This process is
performed for both the low collision energy and the high-energy
scans (saved as separate channels). The ion detection thresholds
are set as follows: Low-energy ion detection threshold of 250
counts; high-energy ion detection threshold was set to 100.

Proteinlynx Global Server version 2.3 (Identity E )isalsousedfor
database searches. The database should be chosen based on the
biological samples being analyzed. The database should contain
species-specific non-redundant sequence entries.
The database search algorithm of the software was described
by Li et al. ( 13 ) . Briefly, the software detects the 250 most abun-
dant peptides and performs an initial pass through the database in
order to identify those peptides (with mass tolerance of 10 ppm of
precursor ions and 20 ppm for fragment ions). It then calculates
the precursor ion mass tolerance, fragment ion mass tolerance,
and chromatographic peak widths for these 250 peptides. These
peptides are then depleted from the database and the remaining
peptides are searched based on these criteria. The cycle contin-
ues to the next abundant peptides, which are identified and then
temporarily deleted from the database. These tentative peptide
identifications are ranked and scored by how well they conform to

3.2.2.Protein
Identification