Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean

Abstract

Data-dependent precursor ion selection is widely used in shotgun proteomics to profile the protein components of complex samples. Although very popular, this bottom-up method presents major drawbacks in terms of detectable dynamic range. Here, we demonstrate the superior performance of a data-independent method we term precursor acquisition independent from ion count (PAcIFIC). Our results show that almost the entire, predicted, soluble bacterial proteome can be thoroughly analyzed by PAcIFIC without the need for any sample fractionation other than the C18-based liquid chromatograph used to introduce the peptide mixture into the mass spectrometer. Importantly, we also show that PAcIFIC provides unique performance for analysis of human plasma in terms of the number of proteins identified (746 at FDR < or = 0.5%) and achieved dynamic range (8 orders of magnitude at FDR < or = 0.5%), without any fractionation other than immuno-depletion of the seven most abundant proteins.

Figure 1

Principle of PAcIFIC. With this method, the sample is repeatedly analyzed by LCMS/MS. A) During each injection, a different precursor-ion m/z range is selected for tandem mass spectrometry independent of precursor ion measurement. B) In each narrow m/z range all precursor-ions are isolated in the ion trap and subjected to collision induced dissociation until the desired m/z range is achieved. C) Each spectra is then searched against a database using the center of the window as the precursor mass and a tolerance corresponding to: maximum charge state allowed times the isolation width divided by two, e.g. 3 × (2.5/2) = 3.75 Da.

Figure 2

Cumulative protein identification after sequential m/z analysis with PacIFIC. The number of unique protein identifications grows rapidly with each cumulative analysis, until a plateau is reached.

Figure 3

Protein results obtained from analysis of human plasma sample depleted of top-7 proteins via both acquisitions (PAcIFIC and genome-based Gas Phase Fractionation). Each dataset is represented as an average of the duplicate analysis at different filtering probabilities with their corresponding FDR. A) PAcIFIC and, B) genome-based Gas Phase Fractionation.

Figure 4

Dynamic range achieved for both acquisition methods (PAcIFIC and genome-based Gas Phase Fractionation) based on known plasma protein concentration from Haab and colleagues. All protein hits are used to calculate the dynamic range.