Autopilot: An Online Data Acquisition Control System for the Enhanced High-Throughput Characterization of Intact Proteins

The ability to study organisms by
direct analysis of their proteomes
without digestion via mass spectrometry has benefited greatly from
recent advances in separation techniques, instrumentation, and bioinformatics.
However, improvements to data acquisition logic have lagged in comparison.
Past workflows for Top Down Proteomics (TDPs) have focused on high
throughput at the expense of maximal protein coverage and characterization.
This mode of data acquisition has led to enormous overlap in the identification
of highly abundant proteins in subsequent LC-MS injections. Furthermore,
a wealth of data is left underutilized by analyzing each newly targeted
species as unique, rather than as part of a collection of fragmentation
events on a distinct proteoform. Here, we present a major advance
in software for acquisition of TDP data that incorporates a fully
automated workflow able to detect intact masses, guide fragmentation
to achieve maximal identification and characterization of intact protein
species, and perform database search online to yield real-time protein
identifications. On Pseudomonas aeruginosa, the software
combines fragmentation events of the same precursor with previously
obtained fragments to achieve improved characterization of the target
form by an average of 42 orders of magnitude in confidence. When HCD
fragmentation optimization was applied to intact proteins ions, there
was an 18.5 order of magnitude gain in confidence. These improved
metrics set the stage for increased proteome coverage and characterization
of higher order organisms in the future for sharply improved control
over MS instruments in a project- and lab-wide context.