pr9b00330_si_001.pdf (1014.98 kB)
Improved Protein Inference from Multiple Protease Bottom-Up Mass Spectrometry Data
journal contribution
posted on 2019-08-23, 18:45 authored by Rachel
M. Miller, Robert J. Millikin, Connor V. Hoffmann, Stefan K. Solntsev, Gloria M. Sheynkman, Michael R. Shortreed, Lloyd M. SmithPeptides detected by tandem mass
spectrometry (MS/MS) in bottom-up
proteomics serve as proxies for the proteins expressed in the sample.
Protein inference is a process routinely applied to these peptides
to generate a plausible list of candidate protein identifications.
The use of multiple proteases for parallel protein digestions expands
sequence coverage, provides additional peptide identifications, and
increases the probability of identifying peptides that are unique
to a single protein, which are all valuable for protein inference.
We have developed and implemented a multi-protease protein inference
algorithm in MetaMorpheus, a bottom-up search software program, which
incorporates the calculation of protease-specific q-values and preserves the association of peptide sequences and their
protease of origin. This integrated multi-protease protein inference
algorithm provides more accurate results than either the aggregation
of results from the separate analysis of the peptide identifications
produced by each protease (separate approach) in MetaMorpheus, or
results that are obtained using Fido, ProteinProphet, or DTASelect2.
MetaMorpheus’ integrated multi-protease data analysis decreases
the ambiguity of the protein group list, reduces the frequency of
erroneous identifications, and increases the number of post-translational
modifications identified, while combining multi-protease search and
protein inference into a single software program.