Croatica Chemica Acta, Vol. 99 No. 2, 2026.
Izvorni znanstveni članak
https://doi.org/10.5562/cca4235
Systematic Optimization of Micro-flow LC–QTOF Conditions for Data-Dependent Peptide Analysis
Vida Petrušić
; Tapi Croatia Industries d.o.o, Prudnička cesta 54, Savski Marof, 10291 Prigorje Brdovečko, Croatia
Darko Preiner
; Faculty of Agriculture, Department of Viticulture and Enology, Svetošimunska 25, 10000 Zagreb, Croatia
Ana Jeromel
; Faculty of Agriculture, Department of Viticulture and Enology, Svetošimunska 25, 10000 Zagreb, Croatia
Jerko Štambuk
; Genos Ltd., Glycoscience Research Laboratory, Borongajska cesta 83h, 10000 Zagreb, Croatia
Ivana Tomaz
; Faculty of Agriculture, Department of Viticulture and Enology, Svetošimunska 25, 10000 Zagreb, Croatia
Prilozi: cca4235-supplement.pdf
Sažetak
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 µg 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.
Ključne riječi
micro-flow LC-MS/MS; QTOF; bottom-up proteomics; data-dependent acquisition; collision energy optimization
Hrčak ID:
347314
URI
Datum izdavanja:
21.5.2026.
Posjeta: 0 *