Mobilize a Proton to Transform the Collision-Induced Dissociation Spectral Pattern of a Cyclic Peptide
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ABSTRACT:
SUBMITTER: Nakamura T
PROVIDER: S-EPMC10904930 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:Electron transfer dissociation (ETD) is a recently introduced mass spectrometric technique which has proven to be an excellent tool for the elucidation of labile post-translational modifications such as phosphorylation and O-GlcNAcylation of serine and threonine residues. However, unlike collision induced dissociation (CID), which has been studied for decades, the intricacies of ETD-based fragmentation have not yet been firmly established or systematically addressed. In this analysis, we have systematically compared the CID and ETD fragmentation patterns for the large majority of the peptides that do not contain such labile modifications. Using a standard 48 protein mix, we were able to measure false-positive rates for the experiments and also assess a large number of peptides for a detailed comparison of CID and ETD fragmentation pattern. Analysis of approximately 19,000 peptides derived from both standard proteins and complex protein samples revealed that (i) CID identified 50% more peptides than ETD; (ii) ETD resulted in approximately 20% increase in amino acid sequence coverage over CID; and (iii) combining CID and ETD fragmentation increased the sequence coverage for an average tryptic peptide to 92%. Interestingly, our analysis revealed that nearly 60% of all ETD-identified peptides carried two positive charges, which is in sharp contrast to what has been generally accepted. We also present a novel strategy for automatic validation of peptide assignments based on identification of a peptide by consecutive CID and ETD fragmentation in an alternating mode.
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Project description:Quantifying peptides based on unique peptide fragment ions avoids the issue of ratio distortion that is commonly observed for reporter ion-based quantification approaches. Herein, we present a collision-induced dissociation-cleavable, isobaric acetyl-isoleucine-proline-glycine (Ac-IPG) tag, which conserves the merits of quantifying peptides based on unique fragments while reducing the complexity of the b-ion series compared to conventional fragment ion-based quantification methods thus facilitating data processing. Multiplex labeling is based on selective N-terminal dimethylation followed by derivatization of the ε-amino group of the C-terminal Lys residue of LysC peptides with isobaric Ac-IPG tags having complementary isotope distributions on Pro-Gly and Ac-Ile. Upon fragmentation between Ile and Pro, the resulting y ions, with the neutral loss of Ac-Ile, can be distinguished between the different labeling channels based on different numbers of isotope labels on the Pro-Gly part and thus contain the information for relative quantification, while b ions of different labeling channels have the same m/z values. The proteome quantification capability of this method was demonstrated by triplex labeling of a yeast proteome spiked with bovine serum albumin (BSA) over a 10-fold dynamic range. With the yeast proteins as the background, BSA was detected at ratios of 1.14:5.06:9.78 when spiked at 1:5:10 ratios. The raw mass data is available on the ProteomeXchange with the identifier PXD 018790.
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Project description:Electron transfer dissociation (ETD) and collision-induced dissociation (CID) were used to investigate underivatized, metal-cationized oligosaccharides formed via electrospray ionization (ESI). Reducing and non-reducing sugars were studied including the tetrasaccharides maltotetraose, 3α,4β,3α-galactotetraose, stachyose, nystose, and a heptasaccharide, maltoheptaose. Univalent alkali, divalent alkaline earth, divalent and trivalent transition metal ions, and a boron group trivalent metal ion were adducted to the non-permethylated oligosaccharides. ESI generated [M + Met]+, [M + 2Met]2+, [M + Met]2+, [M + Met - H]+, and [M + Met - 2H]+ most intensely along with low intensity nitrate adducts, depending on the metal and sugar ionized. The ability of these metal ions to produce oligosaccharide adduct ions by ESI had the general trend: Ca(II) > Mg(II) > Ni(II) > Co(II) > Zn(II) > Cu(II) > Na(I) > K(I) > Al(III) ≈ Fe(III) ≈ Cr(III). Although trivalent metals were utilized, no triply charged ions were formed. Metal cations allowed for high ESI signal intensity without permethylation. ETD and CID on [M + Met]2+ produced various glycosidic and cross-ring cleavages, with ETD producing more cross-ring and internal ions, which are useful for structural analysis. Product ion intensities varied based on glycosidic-bond linkage and identity of monosaccharide sub-unit, and metal adducts. ETD and CID showed high fragmentation efficiency, often with complete precursor dissociation, depending on the identity of the adducted metal ion. Loss of water was occasionally observed, but elimination of small neutral molecules was not prevalent. For both ETD and CID, [M + Co]2+ produced the most uniform structurally informative dissociation with all oligosaccharides studied. The ETD and CID spectra were complementary. Graphical Abstract ᅟ.
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Project description:We present a workflow using an ETD-optimised version of Mascot Percolator and a modified version of SLoMo (turbo-SLoMo) for analysis of phosphoproteomic data. We have benchmarked this against several database searching algorithms and phosphorylation site localisation tools and show that it offers highly sensitive and confident phosphopeptide identification and site assignment with PSM-level statistics, enabling rigorous comparison of data acquisition methods. We analysed the Plasmodium falciparum schizont phosphoproteome using for the first time, a data-dependent neutral loss-triggered-ETD (DDNL) strategy and a conventional decision-tree method. At a posterior error probability threshold of 0.01, similar numbers of PSMs were identified using both methods with a 73% overlap in phosphopeptide identifications. The false discovery rate associated with spectral pairs where DDNL CID/ETD identified the same phosphopeptide was <1%. 72% of phosphorylation site assignments using turbo-SLoMo without any score filtering, were identical and 99.8% of these cases are associated with a false localisation rate of <5%. We show that DDNL acquisition is a useful approach for phosphoproteomics and results in an increased confidence in phosphopeptide identification without compromising sensitivity or duty cycle. Furthermore, the combination of Mascot Percolator and turbo-SLoMo represents a robust workflow for phosphoproteomic data analysis using CID and ETD fragmentation.Biological significanceProtein phosphorylation is a ubiquitous post-translational modification that regulates protein function. Mass spectrometry-based approaches have revolutionised its analysis on a large-scale but phosphorylation sites are often identified by single phosphopeptides and therefore require more rigorous data analysis to unsure that sites are identified with high confidence for follow-up experiments to investigate their biological significance. The coverage and confidence of phosphoproteomic experiments can be enhanced by the use of multiple complementary fragmentation methods. Here we have benchmarked a data analysis pipeline for analysis of phosphoproteomic data generated using CID and ETD fragmentation and used it to demonstrate the utility of a data-dependent neutral loss triggered ETD fragmentation strategy for high confidence phosphopeptide identification and phosphorylation site localisation.
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