Impact of injection solvent composition on protein identification in column-switching chip-liquid chromatography/mass spectrometry

•Appropriate sample dissolution medium is a key parameter in protein identification.•Training set of 6 protein digests was used to determine optimal conditions.•ACN and FA significantly influence identification performance.•6 Protein digests were analysed in E. Coli digested sample. In shotgun prote...

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Veröffentlicht in:Journal of Chromatography A 2016-05, Vol.1445, p.27-35
Hauptverfasser: Houbart, V., Cobraiville, G., Nys, G., Merville, M-P., Fillet, M.
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Sprache:eng
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Zusammenfassung:•Appropriate sample dissolution medium is a key parameter in protein identification.•Training set of 6 protein digests was used to determine optimal conditions.•ACN and FA significantly influence identification performance.•6 Protein digests were analysed in E. Coli digested sample. 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.
ISSN:0021-9673
1873-3778
DOI:10.1016/j.chroma.2016.03.056