Cross-Correlation of Spectral Count Ranking to Validate Quantitative Proteome Measurements

The measurement of change in biological
systems through protein
quantification is a central theme in modern biosciences and medicine.
Label-free MS-based methods have greatly increased the ease and throughput
in performing this task. Spectral counting is one such method that
uses detected MS2 peptide fragmentation ions as a measure of the protein
amount. The method is straightforward to use and has gained widespread
interest. Additionally reports on new statistical methods for analyzing
spectral count data appear at regular intervals, but a systematic
evaluation of these is rarely seen. In this work, we studied how similar
the results are from different spectral count data analysis methods,
given the same biological input data. For this, we chose the algorithms
Beta Binomial, PLGEM, QSpec, and PepC to analyze three biological
data sets of varying complexity. For analyzing the capability of the
methods to detect differences in protein abundance, we also performed
controlled experiments by spiking a mixture of 48 human proteins in
varying concentrations into a yeast protein digest to mimic biological
fold changes. In general, the agreement of the analysis methods was
not particularly good on the proteome-wide scale, as considerable
differences were found between the different algorithms. However,
we observed good agreements between the methods for the top abundance
changed proteins, indicating that for a smaller fraction of the proteome
changes are measurable, and the methods may be used as valuable tools
in the discovery-validation pipeline when applying a cross-validation
approach as described here. Performance ranking of the algorithms
using samples of known composition showed PLGEM to be superior, followed
by Beta Binomial, PepC, and QSpec. Similarly, the normalized versions
of the same method, when available, generally outperformed the standard
ones. Statistical detection of protein abundance differences was strongly
influenced by the number of spectra acquired for the protein and,
correspondingly, its molecular mass.