Potential of Negative-Ion-Mode Proteomics: An MS1-Only Approach

Current proteomics approaches rely almost exclusivelyon usingthe positive ionization mode, resulting in inefficient ionizationof many acidic peptides. This study investigates protein identificationefficiency in the negative ionization mode using the DirectMS1 method.DirectMS1 is an ultrafast data acquisition method based on accuratepeptide mass measurements and predicted retention times. Our methodachieves the highest rate of protein identification in the negativeion mode to date, identifying over 1000 proteins in a human cell lineat a 1% false discovery rate. This is accomplished using a single-shot10 min separation gradient, comparable to lengthy MS/MS-based analyses.Optimizing separation and experimental conditions was achieved byutilizing mobile buffers containing 2.5 mM imidazole and 3% isopropanol.The study emphasized the complementary nature of data obtained inpositive and negative ion modes. Combining the results from all replicatesin both polarities increased the number of identified proteins to1774. Additionally, we analyzed the method's efficiency usingdifferent proteases for protein digestion. Among the four studiedproteases (LysC, GluC, AspN, and trypsin), trypsin and LysC demonstratedthe highest protein identification yield. This suggests that digestionprocedures utilized in positive-mode proteomics can be effectivelyapplied in the negative ion mode. Data are deposited to ProteomeXchange:PXD040583.

Automated summary

Current proteomics approaches often neglect the negative ionization mode, leading to inefficient identification of acidic peptides. This study introduces the DirectMS1 method, which achieves the highest protein identification rate in the negative ionization mode. By optimizing separation and experimental conditions, over 1000 proteins were identified in a human cell line, comparable to MS/MS-based analyses. The study also highlights the potential of using the same digestion procedures in both positive and negative ion modes.