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.

无需酶解即可通过质谱直接分析蛋白质组以研究生物体的能力，近年来得益于分离技术、仪器设备及生物信息学的长足进步而得到极大发展。然而，数据采集逻辑的改进却相对滞后。过往的自上而下蛋白质组学（Top Down Proteomics, TDP）工作流往往以牺牲最大程度的蛋白质覆盖度与表征能力为代价，追求高通量。这种数据采集模式导致在后续的液相色谱-质谱（Liquid Chromatography-Mass Spectrometry, LC-MS）进样中，高丰度蛋白质的鉴定结果存在大量重叠。此外，将每一个新靶向的物种视为独立个体进行分析，而非将其视作特定蛋白质变体的一系列断裂事件的集合，导致大量数据未能得到充分利用。本文介绍了一款自上而下蛋白质组学数据采集软件的重大进展，该软件集成了全自动化工作流：能够检测完整蛋白质质量、指导碎裂以实现完整蛋白质物种的最大程度鉴定与表征，并可在线进行数据库检索以实时输出蛋白质鉴定结果。在铜绿假单胞菌（Pseudomonas aeruginosa）样本中，该软件将同一前体的碎裂事件与已获得的片段信息相结合，使目标蛋白质变体的鉴定置信度平均提升了42个数量级。当高能量碰撞解离（High-energy Collisional Dissociation, HCD）碎裂优化应用于完整蛋白质离子时，置信度提升幅度达到18.5个数量级。这些改进后的指标为未来实现更高阶生物体的蛋白质组覆盖度与表征能力奠定了基础，同时可在项目及实验室范围内实现对质谱仪器的更精准管控。