A hallmark
of protein N-glycosylation is extensive heterogeneity
associated with each glycosylation site. In human cells, the constituent
glycoforms differ mostly in numerous ways of extensions from an invariable
trimannosyl core and terminal modifications. The efficient identification
of these glycoforms at the glycopeptide level by mass spectrometry
(MS) requires a precursor sampling technique that is not dictated
by signal intensity or by preset targets during MS2 data acquisition.
We show here that the recently developed data-independent acquisition
(DIA) approach is best suited to this demanding task. It allows postacquisition
extraction of glycopeptide-specific fragment-ion chromatograms to
be aligned with that of precursor MS1 ion by nanoLC elution time.
For any target glycoprotein, judicious selection of the most favorable
MS1/MS2 transitions can first be determined from prior analysis of
a purified surrogate standard that carries similar site-specific glycosylation
but may differ in its exact range of glycoforms. Since the MS2 transitions
to be used for extracting DIA data is common to that glycosylation
site and not dictated by a specific MS1 value, our workflow applies
equally well to the identification of both targeted and unexpected
glycoforms. Using a case example, we show that, in targeted mode,
it identified more site-specific glycoforms than the more commonly
used data-dependent acquisition method when the amount of the target
glycoprotein was limited in a sample of high complexity. In discovery
mode, it allows detection, with supporting MS2 evidence, of under-sampled
glycoforms and of those that failed to be identified by searching
against a predefined glycan library owing to unanticipated modifications