While tims-ToF mass spectrometer is an excellent platform for bottom–up proteomics studies due to its rapid acquisition with high sensitivity, still achieving a 100% coverage is a challenge and a liquid-chromatography step is required to separate peptides prior to MS analysis. The gradient type and time can have influence on the results and their effect have been studied in this manuscript. Five gradient types (linear, logarithm-like, exponent-like, stepwise, and step-linear), three different gradient lengths (22 min, 44 min, and 66 min), two sample loading amounts (100 ng and 200 ng), and two loading conditions (the use of trap column and no trap column) were studied in order to optimise the LC step.
It was found that a step-linear gradient performs best among tested gradients. The time was found to be dependent on the sample loaded amount. a 44 min gradient (62 min run time) worked best for 100 ng HeLa digest analysis (>3600 protein groups identified), while a 66 min gradient (90 min run time) was optimal for a 200 ng peptide analysis (>4000 protein groups identified). The use of trap enhanced the protein identification (especially for low abundant peptides). In this study only gradient was varied, by keeping other parameters (MS settings, chromatographic material, solvents, …) constant and it was shown that gradient can improve the proteome coverage.
How was PEAKS used?
Raw data were searched against the Uniprot human database (20,577 entries, 3 August 2021) using both PEAKS Studio (PEAKS Xpro) search engines with consensus search parameters. Mass tolerances on precursor and fragment were 20 ppm and 0.1 Da, respectively; protein cleavage was set at semi-specific with trypsin and a maximum of 2 missed cleavages per peptide. Data type was DDA. For post translational modification (PTM), carbamidomethylation (C) was the fixed PTM and oxidation (M) and acetylation (protein N-terminal) were set as variable modifications.
Wei, Xing, et al. “A Comprehensive Study of Gradient Conditions for Deep Proteome Discovery in a Complex Protein Matrix.” International Journal of Molecular Sciences 23.19 (2022): 11714. https://doi.org/10.3390/ijms231911714
Abstract
Bottom–up mass-spectrometry-based proteomics is a well-developed technology based on complex peptide mixtures from proteolytic cleavage of proteins and is widely applied in protein identification, characterization, and quantitation. A tims-ToF mass spectrometer is an excellent platform for bottom–up proteomics studies due to its rapid acquisition with high sensitivity. It remains challenging for bottom–up proteomics approaches to achieve 100% proteome coverage. Liquid chromatography (LC) is commonly used prior to mass spectrometry (MS) analysis to fractionate peptide mixtures, and the LC gradient can affect the peptide fractionation and proteome coverage. We investigated the effects of gradient type and time duration to find optimal gradient conditions. Five gradient types (linear, logarithm-like, exponent-like, stepwise, and step-linear), three different gradient lengths (22 min, 44 min, and 66 min), two sample loading amounts (100 ng and 200 ng), and two loading conditions (the use of trap column and no trap column) were studied. The effect of these chromatography variables on protein groups, peptides, and spectral counts using HeLa cell digests was explored. The results indicate that (1) a step-linear gradient performs best among the five gradient types studied; (2) the optimal gradient duration depends on protein sample loading amount; (3) the use of a trap column helps to enhance protein identification, especially low-abundance proteins; (4) MSFragger and PEAKS Studio have high similarity in protein group identification; (5) MSFragger identified more protein groups among the different gradient conditions compared to PEAKS Studio; and (6) combining results from both database search engines can expand identified protein groups by 9–11%.