Using soy protein as a model and deep eutectic solvent as the extraction solvent, the effects of key factors on the extraction of soy protein based on monitoring its molecular properties were systematically studied. The conditions for the recovery of soy protein from deep eutectic solvents were explored and optimized using the response surface methodology. In addition, the influence of the deep eutectic solvent on the structure and physicochemical properties of soy protein was studied using various characterization techniques. The results showed that the hydrogen bonding interaction in the deep eutectic solvent could affect the protein extraction, and the hydrophobic interaction also played an important role in the protein extraction. Moreover, the deep eutectic solvent caused protein denaturation and other changes in the protein, thus affecting the further applications of soy proteins. This study should provide reference and guidance for green extraction of other proteins by deep eutectic solvents in laboratory or industry and provide a basis for the utilization of soy or other proteins extracted from such processes.

In mass analysis of proteins, mass spectrometry directly measures the mass to charge ratios of ionized proteins and promises higher accuracy than that of indirect approaches measuring other physicochemical properties, provided that the charge states of detected ions are determined. Accurate mass determination of heterogeneously glycosylated proteins is often hindered by unreliable charge determination due to the insufficient resolution of signals from different charge states and inconsistency among mass profiles of ions in individual charge states. Limited charge reduction of a subpopulation of proteoforms using electron transfer/capture reactions (ETnoD/ETnoD) solves this problem by narrowing the mass distribution of examined proteoforms and preserving the mass profile of the precursor charge state in the reduced charge states. However, the limited availability of ETnoD/ETnoD function in commercial instruments limits the application of this approach. Here, utilizing a range of charge-dependent and accuracy-affecting spectral features revealed by a systematic evaluation at levels of both the ensemble and subpopulation of proteoforms based on theoretical models and experiments, we developed a limited charge reduction workflow that enables using collision-induced dissociation and higher energy collisional dissociation, two widely available reactions, as alternatives to ETnoD/ETnoD while providing adequate accuracy. Alternatively, substituting proton transfer charge reduction for ETnoD/ETnoD provides higher accuracy of mass determination. Performing mass selection in a window-sliding manner improves the accuracy and allows profiling of the whole proteoform distribution. The proposed workflow may facilitate the development of universal characterization strategies for more complex and heterogeneous protein systems.

RationaleThe profiling of natural urinary peptides is a valuable indicator of kidney condition. While front‐end separation limits the speed of peptidomic profiling, MS1‐based results suffer from limited peptide coverage and specificity. Clinical studies on chronic kidney disease require an effective strategy to balance the trade‐off between identification depth and throughput.MethodsCKD273, a urinary proteome classifier associated with chronic kidney disease, in samples from diabetic nephropathy patients was profiled in parallel using capillary electrophoresis–mass spectrometry (CE–MS), liquid chromatography with mass spectrometry (LC–MS), and matrix‐assisted laser desorption/ionization–mass spectrometry (MALDI‐MS). Through cross‐comparison of results from MS1 of unfractionated peptides and elution‐time‐resolved MS1 as well as MS/MS in LC– and CE–MS approaches, we evaluated the contribution of false‐positive identification to MS1‐based identification and quantitation, and analyzed the benefit of front‐end separation in terms of accuracy and efficiency.ResultsIn LC– and CE–MS, although MS1 data resulted in higher number of identifications than MS/MS, elution‐time‐dependent analysis revealed extensive interference by non‐CKD273 peptides, which would contribute up to 50% to quantitation if they are not separated from genuine CKD273 peptides. In the absence of separation, MS1 data resulted in lower numbers of identifications and abundance pattern that significantly deviated from those by liquid chromatography with tandem mass spectrometry (LC–MS/MS) or capillary electrophoresis with tandem mass spectrometry (CE–MS/MS). CE showed higher identification efficiency even when less sample was used or achieved faster separation.ConclusionsTo ensure the reliability of MS1‐based urinary peptide profiling, front‐end separation should not be omitted, and elution time should be used in addition to intact mass for identification. Including MS/MS in data acquisition does not compromise the speed or identification number, while benefiting data reliability by providing real‐time sequence verification.