Literature DB >> 30351145

Evaluation of Advanced Precursor Determination for Tandem Mass Tag (TMT)-Based Quantitative Proteomics across Instrument Platforms.

Samuel A Myers1, Susan Klaeger1, Shankha Satpathy1, Rosa Viner2, Jae Choi3, John Rogers3, Karl Clauser1, Namrata D Udeshi1, Steven A Carr1.   

Abstract

Tandem mass tag (TMT)-based quantitation is a strong modality for quantitative proteomics, as samples can be multiplexed, creating large-scale data sets with high precision and minimal missing values. However, coisolation/cofragmentation of near isobaric, coeluting precursor peptide analytes has been well-documented to show ratio compression, compromising the accuracy of peptide/protein quantitation. Advanced peak determination (APD) is a new peak-picking algorithm that shows improved identification of peak detection in survey scans (MS1) to increase the number of precursors selected for unimolecular dissociation (MS2). To increase the number of these "features" selected for MS2 APD purposefully selects multiple peptide precursors of very similar m/ z that often derive from different proteins-a major source of ratio compression in TMT quantification. Here, we evaluate the effects of various data acquisition parameters combined with APD on ratio compression. We find that data acquisition with APD enabled results in more coisolated precursors, more mixed spectra, and in turn, fewer peptide spectral matches, especially at standard on-column loads. We conclude that APD should not be utilized for isobaric tagging, MS2-based experiments.

Entities:  

Keywords:  TMT; advanced peak determination; isobaric tagging; precursor ion purity; ratio compression

Mesh:

Substances:

Year:  2018        PMID: 30351145     DOI: 10.1021/acs.jproteome.8b00611

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  10 in total

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Review 3.  Sample Multiplexing Strategies in Quantitative Proteomics.

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10.  Rapid and deep-scale ubiquitylation profiling for biology and translational research.

Authors:  Namrata D Udeshi; Deepak C Mani; Shankha Satpathy; Shaunt Fereshetian; Jessica A Gasser; Tanya Svinkina; Meagan E Olive; Benjamin L Ebert; Philipp Mertins; Steven A Carr
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  10 in total

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