Application of sample displacement batch chromatography for fractionation of proteoforms.

Fractionation of proteoforms is currently the most challenging topic in the field of proteoform analysis. The need for considering the existence of proteoforms in experimental approaches is not only important in Life Science research in general but especially in the manufacturing of therapeutic proteins (TPs) like recombinant therapeutic antibodies (mAbs). Some of the proteoforms of TPs have significantly decreased actions or even cause side effects. The identification and removal of proteoforms differing from the main species, having the desired action, is challenging because the difference in the composition of atoms is often very small and their concentration in comparison to the main proteoform can be low. In this study, we demonstrate that sample displacement batch chromatography (SDBC) is an easy-to-handle, economical, and efficient method for fractionating proteoforms. As a model sample a commercial ovalbumin fraction was used, containing many ovalbumin proteoforms. The most promising parameters for the SDBC were determined by a screening approach and applied for a 10-segment fractionation of ovalbumin with cation exchange chromatography resins. Mass spectrometry of intact proteoforms was used for characterizing the SDBC fractionation process. By SDBC, a significant separation of different proteoforms was obtained.

FLASHDeconv: Ultrafast, High-Quality Feature Deconvolution for Top-Down Proteomics.

Top-down mass spectrometry (TD-MS)-based proteomics analyzes intact proteoforms and thus preserves information about individual protein species. The MS signal of these high-mass analytes is complex and challenges the accurate determination of proteoform masses. Fast and accurate feature deconvolution (i.e., the determination of intact proteoform masses) is, therefore, an essential step for TD data analysis. Here, we present FLASHDeconv, an algorithm achieving higher deconvolution quality, with an execution speed two orders of magnitude faster than existing approaches. FLASHDeconv transforms peak positions (m/z) within spectra into log m/z space. This simple transformation turns the deconvolution problem into a search for constant patterns, thereby greatly accelerating the process. In both simple and complex samples, FLASHDeconv reports more genuine feature masses and substantially fewer artifacts than other existing methods. FLASHDeconv is freely available for download here: https://www.openms.org/flashdeconv/. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.