Abstract
Data independent acquisition–mass spectrometry (DIA–MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA–MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on an Arabidopsis sample with spike-in known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400–1200 m/z. When combining several DIA–MS analyses with narrow precursor ranges (i.e., 400–650, 650–900 and 900–1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 54.7% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the six-protein mix spike-in. In cDIA only five out of the six-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.
Highlights
We show here that it is possible to obtain a 34.7% increase in the number of protein groups quantified from a single injection with narrow precursor mass range and a 54.7% increase
In the Arabidopsis library, the precursors are distributed along the mass-to-charge range (m/z) of 375–1400 with approximately 60% of precursors concentrated within the narrow region of 400–700 m/z
Through systematic assessment of the effect of precursor mass range on the extent of protein identification and quantitative accuracy, we reported a data independent acquisition (DIA) workflow of using a narrow precursor mass range that outperformed conventional DIA with a wider precursor mass range
Summary
Common quantitative proteomics strategies include isotopic labeling [7,8,9] and label-free approaches [1,10] In these approaches, data dependent acquisition (DDA) is often used to isolate and fragment peptides of top-ranked intensity (e.g., top 20) as they elute from the liquid chromatography (LC) separation column directly into the MS sampling region. The peptide ions are selected for fragmentation using isolation windows of less than two Thomson depending on the instrument capabilities Such methods are generally high-throughput but suffer from limited reproducibility of measurement, especially for peptides of relatively low abundance. This is due to the nature of DDA experiments, where peptide selection is largely stochastic.
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