2019
DOI: 10.1021/acs.analchem.9b03162
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mTMT: An Alternative, Nonisobaric, Tandem Mass Tag Allowing for Precursor-Based Quantification

Abstract: Stable isotope labeling of peptides is the basis for numerous mass-spectrometry-based quantification strategies. Isobaric tagging and metabolic labeling, namely, tandem mass tagging (TMT) and SILAC, are among the most widely used techniques for relative protein quantification.Here we report an alternative, precursor-based quantification method using nonisobaric TMT variants: TMTzero (TMT0) and superheavy TMT (shTMT). We term this strategy mass difference tandem mass tagging (mTMT). These TMT variants differ by… Show more

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Cited by 9 publications
(12 citation statements)
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“… 10 12 In the widely used data-dependent acquisition (DDA) mode, where a certain number of precursor ions are selected for fragmentation during a liquid chromatography–mass spectrometry (LC–MS) run in the order of decreasing intensity, 13 current MS1-based quantification methods analyze up to three samples in a single experiment since higher multiplexing is constrained by the increasing complexity of MS1 spectra and the need for a mass difference of at least 4 Da between labeling channels to avoid overlap of isotope envelopes. 14 In addition, the stochastic nature of selecting precursor ions for tandem MS in DDA leads to an imperfect overlap in peptide identifications, which means that there is a considerable likelihood that some peptides might be missed in some LC–MS runs depending on their relative abundance in given samples. 15 Since only the peptides that are measured in all runs can be reliably quantified and thus compared across many runs in studies comprising hundreds of samples, it would be beneficial to use a strategy that is not data-dependent and thus avoids the stochastic precursor ion selection.…”
Section: Introductionmentioning
confidence: 99%
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“… 10 12 In the widely used data-dependent acquisition (DDA) mode, where a certain number of precursor ions are selected for fragmentation during a liquid chromatography–mass spectrometry (LC–MS) run in the order of decreasing intensity, 13 current MS1-based quantification methods analyze up to three samples in a single experiment since higher multiplexing is constrained by the increasing complexity of MS1 spectra and the need for a mass difference of at least 4 Da between labeling channels to avoid overlap of isotope envelopes. 14 In addition, the stochastic nature of selecting precursor ions for tandem MS in DDA leads to an imperfect overlap in peptide identifications, which means that there is a considerable likelihood that some peptides might be missed in some LC–MS runs depending on their relative abundance in given samples. 15 Since only the peptides that are measured in all runs can be reliably quantified and thus compared across many runs in studies comprising hundreds of samples, it would be beneficial to use a strategy that is not data-dependent and thus avoids the stochastic precursor ion selection.…”
Section: Introductionmentioning
confidence: 99%
“…Multiplexing with isotopic labels is an attractive alternative to label-free quantification in mass spectrometry-based proteomics since it increases throughput and reduces run-to-run variability . Remarkable advancements have been made in terms of multiplexing capacity over the last decades. , Current multiplexing approaches can be classified into MS1-based methods , that rely on isotopic labeling and quantify peptides based on distinct precursor ion masses and MS2-based methods that rely on isobaric labeling strategies and quantify peptides based on reporter ions, , fragments of the peptide backbone, , or peptide-coupled reporter ions. In the widely used data-dependent acquisition (DDA) mode, where a certain number of precursor ions are selected for fragmentation during a liquid chromatography–mass spectrometry (LC–MS) run in the order of decreasing intensity, current MS1-based quantification methods analyze up to three samples in a single experiment since higher multiplexing is constrained by the increasing complexity of MS1 spectra and the need for a mass difference of at least 4 Da between labeling channels to avoid overlap of isotope envelopes . In addition, the stochastic nature of selecting precursor ions for tandem MS in DDA leads to an imperfect overlap in peptide identifications, which means that there is a considerable likelihood that some peptides might be missed in some LC–MS runs depending on their relative abundance in given samples .…”
Section: Introductionmentioning
confidence: 99%
“…Techniques such as TOMAHAQ and TOMAHTO use relatively high amounts (at times, 100× or greater) of trigger peptides to quantify low amounts of target peptides. These trigger peptides are labeled with chromatographically indistinguishable, isotopologue variants of isobaric tags, such as TMTzero and Super Heavy TMT reagents, collectively known as mTMT, , which are variants of the original TMT molecule . Here we introduce the Super Heavy TMTpro (shTMTpro) reagent, aptly named as it incorporates nine more stable isotopes than the TMTpro16 reagents that are used in isobaric tagging experiments.…”
mentioning
confidence: 99%
“…However, if the TMTproZero reagent must be used, then we recommend narrowing the isolation window or using an m / z window offset, which may concomitantly decrease the signal and thereby be detrimental to the quantification of lower abundance peptide species. As an alternative application, Super Heavy TMTpro may be used in conjunction with its nonisobaric and chromatographically indistinguishable counterparts, TMTproZero and a TMTpro16 tag, for MS1-based quantification that is akin to SILAC, reductive dimethylation, mTRAQ, or mTMT . In summary, the Super Heavy TMTpro tag is a promising and highly versatile chemical-labeling reagent for quantitative mass-spectrometry applications.…”
mentioning
confidence: 99%
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