High sensitivity and high-confidence compound identification with a flexible BoxCar acquisition method

Abstract

Liquid chromatography-mass spectrometry (LC-MS) is in wide use for compound identification and quantification in complex matrices. While advances in mass spectrometry and the incorporation of new acquisition methods have resulted in greatly improved detection, there is an ongoing need to expand the limits of highly sensitive and confident identification of low abundance species in complex samples. The data acquisition method known as “BoxCar” was originally designed to achieve in-depth proteome profiling on an Orbitrap mass analyzer by decomposing ions into segments with narrow m/z windows. Using this method, selected segments are packaged in C-trap and all ions are then sent to Orbitrap for detection. In this study, we developed a flexible BoxCar acquisition method by placing more segments in the low m/z range for small molecule profiling. This new MS1 acquisition method was successfully integrated with iterative data dependent MS/MS acquisition by generating an inclusion list of ions detected in the flexible BoxCar to trigger the fragmentation of parent ions. The developed acquisition method was applied to the analysis of cell culture media, which plays a key role in antibody production. This challenging goal is of critical importance, as none of the currently available methods provide a comprehensive understanding of how individual components, metabolites, and impurities associated with the cell culture process might influence recombinant antibody production. Even when present at relatively low abundance, some components or impurities in the cell culture medium could have a profound impact on the quality and titer of the antibodies produced. The complex soy hydrolysate cell culture medium used in antibody generation has not been fully characterized. Using the developed flexible BoxCar acquisition method, we achieved 90 % higher sensitivity in experiments designed to detect spiked chemical substances at low abundance at the MS1 level compared to the full scan method. Iterative data-dependent acquisition (DDA) based on the targeted inclusion list generated much higher quality MS2 spectra and facilitated confident identification of low-abundance compounds. Our method achieved a 50 % increase in MS2 coverage of compounds present at low concentrations compared to conventional DDA methods. The results of our study demonstrate that this data acquisition workflow can be easily operated on Orbitrap mass spectrometers and used as a highly effective approach to improve sensitivity and high-confidence small molecule profiling in soy hydrolysate-based cell culture medium and thus provides significant support for therapeutic monoclonal antibody production.