Eunok Paek

Strategy for comprehensive identification of post-translational modifications in cellular proteins, including low abundant modifications: application to glyceraldehyde-3-phosphate dehydrogenase.

Post-translational modifications (PTMs) play key roles in the regulation of biological functions of proteins. Although some progress has been made in identifying several PTMs using existing approaches involving a combination of affinity-based enrichment and mass spectrometric analysis, comprehensive identification of PTMs remains a challenging problem in proteomics because of the dynamic complexities of PTMs in vivo and their low abundance. We describe here a strategy for rapid, efficient, and comprehensive identification of PTMs occurring in biological processes in vivo. It involves a selectively excluded mass screening analysis (SEMSA) of unmodified peptides during liquid chromatography-electrospray ionization-quadrupole-time-of-flight tandem mass spectrometry (LC-ESI-q-TOF MS/MS) through replicated runs of a purified protein on two-dimensional gel. A precursor ion list of unmodified peptides with high mass intensities was obtained during the initial run followed by exclusion of these unmodified peptides in subsequent runs. The exclusion list can grow as long as replicate runs are iteratively performed. This enables the identifications of modified peptides with precursor ions of low intensities by MS/MS sequencing. Application of this approach in combination with the PTM search algorithm MODi to GAPDH protein in vivo modified by oxidative stress provides information on multiple protein modifications (19 types of modification on 42 sites) with >92% peptide coverage and the additional potential for finding novel modifications, such as transformation of Cys to Ser. On the basis of the information of precursor ion m/z, quantitative analysis of PTM was performed for identifying molecular changes in heterogeneous protein populations. Our results show that PTMs in mammalian systems in vivo are more complicated and heterogeneous than previously reported. We believe that this strategy has significant potential because it permits systematic characterization of multiple PTMs in functional proteomics.

Isoform-specific regulation of Akt by PDGF-induced reactive oxygen species

Isoform-specific signaling of Akt, a major signaling hub and a prominent therapeutic target, remained poorly defined until recently. Subcellular distribution, tissue-specific expression, substrate specificity, and posttranslational modifications are believed to underlie isoform-specific signaling of Akt. The studies reported here show inhibition of Akt2 activity under physiologically relevant conditions of oxidation created by PDGF-induced reactive oxygen species. Combined MS and functional assays identified Cys124 located in the linker region between the N-terminal pleckstrin homology domain and the catalytic kinase domain as one of the unique regulatory redox sites in Akt2 with functional consequence on PDGF-stimulated glucose uptake. A model is proposed describing the consequence of increased endogenous oxidation induced by extracellular cues such as PDGF on Akt2 activity.

Fast Multi-blind Modification Search through Tandem Mass Spectrometry

With great biological interest in post-translational modifications (PTMs), various approaches have been introduced to identify PTMs using MS/MS. Recent developments for PTM identification have focused on an unrestrictive approach that searches MS/MS spectra for all known and possibly even unknown types of PTMs at once. However, the resulting expanded search space requires much longer search time and also increases the number of false positives (incorrect identifications) and false negatives (missed true identifications), thus creating a bottleneck in high throughput analysis. Here we introduce MODa, a novel “multi-blind” spectral alignment algorithm that allows for fast unrestrictive PTM searches with no limitation on the number of modifications per peptide while featuring over an order of magnitude speedup in relation to existing approaches. We demonstrate the sensitivity of MODa on human shotgun proteomics data where it reveals multiple mutations, a wide range of modifications (including glycosylation), and evidence for several putative novel modifications. Based on the reported findings, we argue that the efficiency and sensitivity of MODa make it the first unrestrictive search tool with the potential to fully replace conventional restrictive identification of proteomics mass spectrometry data.

Novel Oxidative Modifications in Redox-Active Cysteine Residues

Redox-active cysteine, a highly reactive sulfhydryl, is one of the major targets of ROS. Formation of disulfide bonds and other oxidative derivatives of cysteine including sulfenic, sulfinic, and sulfonic acids, regulates the biological function of various proteins. We identified novel low-abundant cysteine modifications in cellular GAPDH purified on 2-dimensional gel electrophoresis (2D-PAGE) by employing selectively excluded mass screening analysis for nano ultraperformance liquid chromatography-electrospray-quadrupole-time of flight tandem mass spectrometry, in conjunction with MODi and MODmap algorithm. We observed unexpected mass shifts (Δm = −16, −34, +64, +87, and +103 Da) at redox-active cysteine residue in cellular GAPDH purified on 2D-PAGE, in oxidized NDP kinase A, peroxiredoxin 6, and in various mitochondrial proteins. Mass differences of −16, −34, and +64 Da are presumed to reflect the conversion of cysteine to serine, dehydroalanine (DHA), and Cys-SO2-SH respectively. To determine the plausible pathways to the formation of these products, we prepared model compounds and examined the hydrolysis and hydration of thiosulfonate (Cys-S-SO2-Cys) either to DHA (Δm = −34 Da) or serine along with Cys-SO2-SH (Δm = +64 Da). We also detected acrylamide adducts of sulfenic and sulfinic acids (+87 and +103 Da). These findings suggest that oxidations take place at redox-active cysteine residues in cellular proteins, with the formation of thiosulfonate, Cys-SO2-SH, and DHA, and conversion of cysteine to serine, in addition to sulfenic, sulfinic and sulfonic acids of reactive cysteine.

MODi : a powerful and convenient web server for identifying multiple post-translational peptide modifications from tandem mass spectra

MODi () is a powerful and convenient web service that facilitates the interpretation of tandem mass spectra for identifying post-translational modifications (PTMs) in a peptide. It is powerful in that it can interpret a tandem mass spectrum even when hundreds of modification types are considered and the number of potential PTMs in a peptide is large, in contrast to most of the methods currently available for spectra interpretation that limit the number of PTM sites and types being used for PTM analysis. For example, using MODi, one can consider for analysis both the entire PTM list published on the unimod webpage () and user-defined PTMs simultaneously, and one can also identify multiple PTM sites in a spectrum. MODi is convenient in that it can take various input file formats such as .mzXML, .dta, .pkl and .mgf files, and it is equipped with a graphical tool called MassPective developed to display MODis output in a user-friendly manner and helps users understand MODis output quickly. In addition, one can perform manual de novo sequencing using MassPective.

Unrestrictive Identification of Multiple Post-translational Modifications from Tandem Mass Spectrometry Using an Error-tolerant Algorithm Based on an Extended Sequence Tag Approach

Identification of post-translational modifications (PTMs) is important to understanding the biological functions of proteins. MS/MS is a useful tool to identify PTMs. Most existing search tools are restricted to take only a few types of PTMs as input. Here we describe a new algorithm, called MODi (pronounced “mod eye”), that rapidly searches for all known types of PTMs at once without limiting a multitude of modified sites in a peptide. MODi introduces the notion of a tag chain, a combination structure made from multiple sequence tags, that effectively localizes modified regions within a spectrum and overcomes de novo sequencing errors common in tag-based approaches. MODi showed its performance competence by identifying various types of PTMs in analysis of PTM-rich proteins such as glyceraldehyde-3-phosphate dehydrogenase and lens protein. We demonstrated that MODi innovatively manages the computational complexity of identifying multiple PTMs in a peptide, which may exist in a greater variety than usually expected. In addition, it is suggested that MODi has great potential to discover novel modifications.

Isotopic Peak Intensity Ratio Based Algorithm for Determination of Isotopic Clusters and Monoisotopic Masses of Polypeptides from High-Resolution Mass Spectrometric Data

Determining isotopic clusters and their monoisotopic masses is a first step in interpreting complex mass spectra generated by high-resolution mass spectrometers. We propose a mathematical model for isotopic distributions of polypeptides and an effective interpretation algorithm. Our model uses two types of ratios: intensity ratio of two adjacent peaks and intensity ratio product of three adjacent peaks in an isotopic distribution. These ratios can be approximated as simple functions of a polypeptide mass, the values of which fall within certain ranges, depending on the polypeptide mass. Given a spectrum as a peak list, our algorithm first finds all isotopic clusters consisting of two or more peaks. Then, it scores clusters using the ranges of ratio functions and computes the monoisotopic masses of the identified clusters. Our method was applied to high-resolution mass spectra obtained from a Fourier transform ion cyclotron resonance (FTICR) mass spectrometer coupled to reverse-phase liquid chromatography (RPLC). For polypeptides whose amino acid sequences were identified by tandem mass spectrometry (MS/MS), we applied both THRASH-based software implementations and our method. Our method was observed to find more masses of known peptides when the numbers of the total clusters identified by both methods were fixed. Experimental results show that our method performed better for isotopic mass clusters of weak intensity where the isotopic distributions deviate significantly from their theoretical distributions. Also, it correctly identified some isotopic clusters that were not found by THRASH-based implementations, especially those for which THRASH gave 1 Da mismatches. Another advantage of our method is that it is very fast, much faster than THRASH that calculates the least-squares fit.

Software eyes for protein post-translational modifications

Post-translational modifications (PTMs) are critical to almost all aspects of complex processes of the cell. Identification of PTMs is one of the biggest challenges for proteomics, and there have been many computational studies for the analysis of PTMs from tandem mass spectrometry (MS/MS). Most early PTM identification studies have been performed by matching MS/MS data to protein databases, using database search tools, but they are prohibitively slow when a large number of PTMs is given as a search parameter. In this article, we present recent developments to search for more types of PTMs and to speed up the search, and discuss many computational issues and solutions in terms of identifying multiply modified peptides or searching for all possible modifications at once in unrestrictive mode. Apart from the most common type of PTMs involving covalent addition of functional groups to proteins, PTMs such as disulfide linkage require dedicated software for the analysis because they may involve cross-linking between two different parts of proteins. Finally, methods for identification of protein disulfide bonds are presented.

Prediction of novel modifications by unrestrictive search of tandem mass spectra.

Post-translational modifications (PTMs) greatly increase the complexity and diversity of the proteome so that a protein can carry out a wide variety of functions. PTM prediction on proteins is one of the major challenges in proteomics research. Various approaches have been developed for an unrestrictive search of PTMs in proteins using tandem mass spectrometry (MS/MS). However, most tools usually addressed frequent modifications despite the fact that critical biological modifications may be rare. Here, we present MODmap for exploring potentially important rare and unknown modifications from MS/MS spectra. Extended sequence tag-based spectral alignment is proposed. It is highly sensitive to modified regions in an MS/MS spectrum and is tolerant of multiple modifications per peptide. We have developed an unrestrictive algorithm (MOD(i)), which rapidly searches for all known types of PTMs at once, without limiting a multitude of modified sites in a peptide. After MOD(i) produces spectral alignment results using all known types of PTMs, high-quality spectral alignments are subject to MODmap and are re-estimated. New mass offsets are reported via local alignment and MODmap determines novel modification candidates. In analyses of PTM-rich lens proteins, our methodology was demonstrated to be sensitive to rare modifications and suggested several confident novel modification candidates.

High-throughput peptide quantification using mTRAQ reagent triplex

BackgroundProtein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents.Methods and resultsHere we propose a novel data analysis algorithm for peptide quantification in triplex mTRAQ experiments. It improved the accuracy of quantification in two features. First, it identified and separated triplex isotopic clusters of a peptide in each full MS scan. We designed a schematic model of triplex overlapping isotopic clusters, and separated triplex isotopic clusters by solving cubic equations, which are deduced from the schematic model. Second, it automatically determined the elution areas of peptides. Some peptides have similar atomic masses and elution times, so their elution areas can have overlaps. Our algorithm successfully identified the overlaps and found accurate elution areas. We validated our algorithm using standard protein mixture experiments.ConclusionsWe showed that our algorithm was able to accurately quantify peptides in triplex mTRAQ experiments. Its software implementation is compatible with Trans-Proteomic Pipeline (TPP), and thus enables high-throughput analysis of proteomics data.