In-Search Assignment of Monoisotopic Peaks Improves the Identification of Cross-Linked Peptides

Cross-linking/mass
spectrometry has undergone a maturation process
akin to standard proteomics by adapting key methods such as false
discovery rate control and quantification. A poorly evaluated search
setting in proteomics is the consideration of multiple (lighter) alternative
values for the monoisotopic precursor mass to compensate for possible
misassignments of the monoisotopic peak. Here, we show that monoisotopic
peak assignment is a major weakness of current data handling approaches
in cross-linking. Cross-linked peptides often have high precursor
masses, which reduces the presence of the monoisotopic peak in the
isotope envelope. Paired with generally low peak intensity, this generates
a challenge that may not be completely solvable by precursor mass
assignment routines. We therefore took an alternative route by ‘”in-search
assignment of the monoisotopic peak” in the cross-link database
search tool Xi (Xi-MPA), which considers multiple precursor masses
during database search. We compare and evaluate the performance of
established preprocessing workflows that partly correct the monoisotopic
peak and Xi-MPA on three publicly available data sets. Xi-MPA always
delivered the highest number of identifications with ∼2 to
4-fold increase of PSMs without compromising identification accuracy
as determined by FDR estimation and comparison to crystallographic
models.