In shotgun proteomics, the gold standard technique is reversed-phase liquid chromatography coupled to mass spectrometry. Many researches have been carried out to study the effects on identification performances of chromatographic parameters such as the stationary phase and column dimensions, mobile phase composition and flow rate, as well as the gradient slope and length. However, little attention is usually paid to the injection solvent composition. In this study, we investigated the effect of the injection solvent on protein identification parameters (number of distinct peptides, amino acid coverage and MS/MS search score) as well as sensitivity. Tryptic peptides from six different proteins, covering a wide range of physicochemical properties, were employed as training set. Design of experiments was employed as a tool to highlight the factors related to the composition of the injection solvent that significantly influenced the obtained results. Optimal results for the training set were applied to analysis of more complex samples. The experiments pointed out optimising the composition of the injection solvent had a strong beneficial effect on all the considered responses. On the basis of these results, an approach to determine optimal conditions was proposed to maximise the protein identification performances and detection sensitivity.
Keywords: Injection solvent; Protein identification; RP-LC–MS; Sensitivity.
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