Systematic Optimization of Micro-flow LC–QTOF Conditions for Data-Dependent Peptide Analysis

This study describes the systematic optimization of a micro-flow LC-MS / MS method on a QTOF platform for bottom-up protein analysis.Key chromatographic parameters were evaluated, and an injection mass of 2 g combined with a shallow 3 -30 % B gradient provided the best separation efficiency and retention time reproducibility.Fragmentation performance was optimized by scaling the vendor-provided CE table to 80 %, which produced the most informative spectra under the argon collision gas conditions used in this study.Under the tested acquisition settings, dynamic MS / MS acquisition yielded a higher number of MS / MS spectra, peptide identifications, and sequence coverage than the fixed acquisition mode.The final method was validated using BSA, phosphorylase b, alcohol dehydrogenase, and their ternary mixture, demonstrating high sequence coverage and consistent chromatographic peak profiles across all samples.These results confirm that the optimized workflow is robust, reproducible, and suitable for routine proteomic applications, with future work aimed at evaluating its performance on complex proteomes such as yeast and HeLa.