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In a typical mass spectrometry experiment, the state-of-the-art sequencing algorithms are able to identify only about 10% to 20% of the tandem-MS spectra. Moreover, due to the high dynamic range and complexity of a sample like human plasma, many proteins or peptides do not even lead to a MSn spectra. This list includes the differentially expressed markers in a typical biomarker discovery study, features that follow a particularly interesting trend, time-course studies, etc. While many of such features can be flagged using computational analysis of the MS1 signal, MSn spectra are still required to get an annotation.
Using an in-line post-column split with the TriVersa NanoMate (Advion Biosciences, Ithaca, NY) coupled with the highly sensitive Orbitrap, we have built a system where we collect LC fractions in a 96-well plate, which are then available for direct infusion at a later time. This gives the advantage of direct infusion on a sample of much lower complexity, thus providing longer analysis time, which in turn enables us to (1) perform intelligent and targeted isolation and fragmentation, (2) attempt different fragmentation methodologies, such as CAD, ETD, IRMPD, etc., and (3) perform multi-stage MSn. This analysis is fully automated, and thus capable of targeting hundreds of features. As a result, given a feature list (similar to an inclusion list), which can be built using differential analysis software like Sieve, our workflow provides a targeted and iterative re-analysis in a high-throughput fashion to get high-quality tandem spectra, and thus a much higher chance of getting an annotation.