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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.

SUBMITTER: Panchaud A

PROVIDER: S-EPMC3086478 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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

Panchaud Alexandre A Scherl Alexander A Shaffer Scott A SA von Haller Priska D PD Kulasekara Hemantha D HD Miller Samuel I SI Goodlett David R DR

Analytical chemistry 20090801 15

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 wi ...[more]

PMID: 19572557

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Project description:The ultimate aim of proteomics is to fully identify and quantify the entire complement of proteins and post-translational modifications in biological samples of interest. For the last 15 years, liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-dependent acquisition (DDA) mode has been the standard for proteomics when sampling breadth and discovery were the main objectives; multiple reaction monitoring (MRM) LC-MS/MS has been the standard for targeted proteomics when precise quantification, reproducibility, and validation were the main objectives. Recently, improvements in mass spectrometer design and bioinformatics algorithms have resulted in the rediscovery and development of another sampling method: data-independent acquisition (DIA). DIA comprehensively and repeatedly samples every peptide in a protein digest, producing a complex set of mass spectra that is difficult to interpret without external spectral libraries. Currently, DIA approaches the identification breadth of DDA while achieving the reproducible quantification characteristic of MRM or its newest version, parallel reaction monitoring (PRM). In comparative de novo identification and quantification studies in human cell lysates, DIA identified up to 89% of the proteins detected in a comparable DDA experiment while providing reproducible quantification of over 85% of them. DIA analysis aided by spectral libraries derived from prior DIA experiments or auxiliary DDA data produces identification and quantification as reproducible and precise as that achieved by MRM/PRM, except on low?abundance peptides that are obscured by stronger signals. DIA is still a work in progress toward the goal of sensitive, reproducible, and precise quantification without external spectral libraries. New software tools applied to DIA analysis have to deal with deconvolution of complex spectra as well as proper filtering of false positives and false negatives. However, the future outlook is positive, and various researchers are working on novel bioinformatics techniques to address these issues and increase the reproducibility, fidelity, and identification breadth of DIA.

Dataset Information

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

Publications

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

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