Abstract
Label free quantitation by measurement of peptide fragment signal intensity (MS2 quantitation) is a technique that has seen limited use due to the stochastic nature of data dependent acquisition (DDA). However, data independent acquisition has the potential to make large scale MS2 quantitation a more viable technique. In this study we used an implementation of data independent acquisition--SWATH--to perform label free protein quantitation in a model bacterium Clostridium stercorarium. Four tryptic digests analyzed by SWATH were probed by an ion library containing information on peptide mass and retention time obtained from DDA experiments. Application of this ion library to SWATH data quantified 1030 proteins with at least two peptides quantified (∼ 40% of predicted proteins in the C. stercorarium genome) in each replicate. Quantitative results obtained were very consistent between biological replicates (R(2) ∼ 0.960). Protein quantitation by summation of peptide fragment signal intensities was also highly consistent between biological replicates (R(2) ∼ 0.930), indicating that this approach may have increased viability compared to recent applications in label free protein quantitation. SWATH based quantitation was able to consistently detect differences in relative protein quantity and it provided coverage for a number of proteins that were missed in some samples by DDA analysis.
Highlights
Mass spectrometry based peptide sequencing has become the key method for protein identification and quantification
Protein quantitation by SWATH demonstrated good reproducibility between biological replicates and the capability to detect the regulation of protein expression in the bacterium grown on different substrates
Analysis by 2D LC-MS and tandem MS (MS/MS) may be unnecessary if the quantitation targets are high abundance proteins detected via 1D data independent acquisition (DIA) analysis as these were reproducibly quantified by SWATH no matter the method of ion library generation
Summary
Mass spectrometry based peptide sequencing has become the key method for protein identification and quantification. The main issue with proteomics data (or with any other “omics” data) is the so-called problem of “high dimensionality low sample size” (HDSS), meaning that several thousand variables can be measured in a single experiment but the number of replicates is usually low (typically on the order of 1-6 for a given condition) for any given state (Dobbin & Simon, 2007) This means that when the test statistic is calculated for thousands of different proteins the odds of encountering at least one false positive is high even for low pvalues. Even just scratching the surface of how these components interact at a systemic level has the potential for widespread application and fundamental understanding in how biochemical systems operate
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Published Version
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