Web-based MS/MS data analysis

This tutorial focuses on three MS/MS data analysis programs currently available via a web interface: Mascot, Phenyx and X!Tandem. Although these programs process the same input and often produce comparable outputs, subtle differences remain. The use of parameters that are requested in the on-line forms and the subsequent interpretation of results are illustrated and explained via a single example.     

Improving LC-MS sensitivity through increases in chromatographic performance: comparisons of UPLC-ES/MS/MS to HPLC-ES/MS/MS

Recent technological advances have made available reverse phase chromatographic media with a 1.7 microm particle size along with a liquid handling system that can operate such columns at much higher pressures. This technology, termed ultra performance liquid chromatography (UPLC), offers significant theoretical advantages in resolution, speed, and sensitivity for analytical determinations, particularly when coupled with mass spectrometers capable of high-speed acquisitions. This paper explores the differences in LC-MS performance by conducting a side-by-side comparison of UPLC for several methods previously optimized for HPLC-based separation and quantification of multiple analytes with maximum throughput. In general, UPLC produced significant improvements in method sensitivity, speed, and resolution. Sensitivity increases with UPLC, which were found to be analyte-dependent, were as large as 10-fold and improvements in method speed were as large as 5-fold under conditions of comparable peak separations. Improvements in chromatographic resolution with UPLC were apparent from generally narrower peak widths and from a separation of diastereomers not possible using HPLC. Overall, the improvements in LC-MS method sensitivity, speed, and resolution provided by UPLC show that further advances can be made in analytical methodology to add significant value to hypothesis-driven research.     

Mitochondrial phosphoproteome revealed by an improved IMAC method and MS/MS/MS

IMAC in combination with mass spectrometry is a promising approach for global analysis of protein phosphorylation. Nevertheless this approach suffers from two shortcomings: inadequate efficiency of IMAC and poor fragmentation of phosphopeptides in the mass spectrometer. Here we report optimization of the IMAC procedure using (32)P-labeled tryptic peptides and development of MS/MS/MS (MS3) for identifying phosphopeptide sequences and phosphorylation sites. The improved IMAC method allowed recovery of phosphorylated tryptic peptides up to approximately 77% with only minor retention of unphosphorylated peptides. MS3 led to efficient fragmentation of the peptide backbone in phosphopeptides for sequence assignment. Proteomics of mitochondrial phosphoproteins using the resulting IMAC protocol and MS3 revealed 84 phosphorylation sites in 62 proteins, most of which have not been reported before. These results revealed diverse phosphorylation pathways involved in the regulation of mitochondrial functions. Integration of the optimized batchwise IMAC protocol with MS3 offers a relatively simple and more efficient approach for proteomics of protein phosphorylation.     

Protein identification using MS/MS data

The subject of this tutorial is protein identification and characterisation by database searching of MS/MS Data. Peptide Mass Fingerprinting is excluded because it is covered in a separate tutorial. Practical aspects of database searching are emphasised, such as choice of sequence database, effect of mass tolerance, and how to identify post-translational modifications. The relationship between sensitivity and specificity is discussed, as is the challenge of using peptide match information to infer which proteins were present in the sample. Since these tutorials are introductory in nature, most references are to reviews, rather than primary research papers. Some familiarity with mass spectrometry and protein chemistry is assumed. There is an accompanying slide presentation, including speaker notes, and a collection of web-based, practical exercises, designed to reinforce key points. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 6).     

Improved titanium dioxide enrichment of phosphopeptides from HeLa cells and high confident phosphopeptide identification by cross-validation of MS/MS and MS/MS/MS spectra

Enrichment is essential for phosphoproteome analysis because phosphorylated proteins are usually present in cells in low abundance. Recently, titanium dioxide (TiO2) has been demonstrated to enrich phosphopeptides from simple peptide mixtures with high specificity; however, the technology has not been optimized. In the present study, significant non-specific bindings were observed when proteome samples were applied to TiO2 columns. Column wash with an NH4Glu solution after loading peptide mixtures significantly increased the efficiency of TiO2 phosphopeptide enrichment with a recovery of up to 84%. Also, for proteome samples, more than a 2-fold increase in unique phosphopeptide identifications has been achieved. The use of NH4Glu for a TiO2 column wash does not significantly reduce the phosphopeptide recovery. A total of 858 phosphopeptides corresponding to 1034 distinct phosphosites has been identified from HeLa cells using the improved TiO2 enrichment procedure in combination with data-dependent neutral loss nano-RPLC-MS2-MS3 analysis. While 41 and 35% of the phosphopeptides were identified only by MS2 and MS3, respectively, 24% was identified by both MS2 and MS3. Cross-validation of the phosphopeptide assignment by MS2 and MS3 scans resulted in the highest confidence in identification (99.5%). Many phosphosites identified in this study appear to be novel, including sites from antigen Ki-67, nucleolar phosphoprotein p130, and Treacle protein. The study also indicates that evaluation of confidence levels for phosphopeptide identification via the reversed sequence database searching strategy might underestimate the false positive rate.     

Characterization of betaines using electrospray MS/MS

Betaines are an important class of naturally occurring compounds that function as compatible solutes or osmoprotectants. Because of the permanent positive charge on the quaternary ammonium moiety, mass spectrometric analysis has been approached by desorption methods, including fast atom bombardment and plasma desorption mass spectrometry. Here we show that electrospray ionization MS gives comparable results to plasma desorption MS for a range of authentic betaine standards and betaines purified from plant extracts by ion exchange chromatography. A distinct advantage of electrospray ionization MS over plasma desorption MS is the capability of obtaining product ion spectra via MS/MS of selected parent ions, and hence structural information to discriminate between ions of identical mass.     

Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS

An overview is presented of gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS), the two major hyphenated techniques employed in metabolic profiling that complement direct 'fingerprinting' methods such as atmospheric pressure ionization (API) quadrupole time-of-flight MS, API Fourier transform MS, and NMR. In GC/MS, the analytes are normally derivatized prior to analysis in order to reduce their polarity and facilitate chromatographic separation. The electron ionization mass spectra obtained are reproducible and suitable for library matching, mass spectral collections being readily available. In LC/MS, derivatization and library matching are at an early stage of development and mini-reviews are provided. Chemical derivatization can dramatically increase the sensitivity and specificity of LC/MS methods for less polar compounds and provides additional structural information. The potential of derivatization for metabolic profiling in LC/MS is demonstrated by the enhanced analysis of plant extracts, including the potential to measure volatile acids such as formic acid, difficult to achieve by GC/MS. The important role of mass spectral library creation and usage in these techniques is discussed and illustrated by examples.     

Accelerating high quality bioanalytical LC/MS/MS assays using fused-core columns

High quality, ultra-fast bioanalytical LC/MS/MS methods were developed using short columns packed with fused-core particles and high (1.0–3.0 mL/min) flow rates. For more than two years, at flow rates up to 3.0 mL/min, using 0.33 min non-ballistic gradients, these methods were shown to provide comparable or better performance than slower assays for accuracy, precision, sensitivity, specificity, and ruggedness, and met all criteria required by the bioanalytical regulatory guidance.     

Identifying citrus limonoid aglycones by HPLC-EI/MS and HPLC-APCI/MS techniques

HPLC coupled with normal phase electron ionisation (EI) and atmospheric pressure chemical ionisation (APCI)/ mass spectrometry methods has been applied to identify 17 known neutral limonoid aglycones from Citrus sources. The HPLC-MS data from the known limonoids provided chromatographic characteristics, APCI-derived molecular weight data and EI fragmentation data for each limonoid. EI fragmentation patterns for the limonoids were correlated with structural characteristics. The EI fragmentation patterns coupled with APCI-derived molecular weights were utilised as a potential method by which to discern the structural character of unknown citrus limonoids.     

New dibenzotropolone derivatives characterized from black tea using LC/MS/MS

Theaflavins and thearubigins are major pigments in black tea, and it is generally accepted that they are produced by oxidation of flavan-3-ols (catechins) during tea fermentation. In the course of studies on the oxidation mechanism of tea polyphenols, especially the formation of thearubigins, a method combining the enzymatic synthesis and LC/ESI-MS/MS analysis was developed to search for new higher molecular weight polymers from black tea. Three new dibenzotropolones, theadibenzotropolone A, B, and C, together with one new tribenzotropolone, theatribenzotropolone A, were formed by the reaction of theaflavins and tea catechins with horseradish peroxidase in the presence of H(2)O(2). The structures of these new benzotropolone derivatives were elucidated on the basis of MS and 2D NMR spectroscopic analyses. The existence of these compounds in black tea was characterized by LC/ESI-MS/MS. Theadibenzotropolone A and B were the first benzotropolone-type trimers of catechins found in the black tea extract. The observation that galloyl ester groups of theaflavins can be oxidized to form di- or tri-benzotropolone skeletons strongly implied that this type of oxidation is an important pathway to extend the molecular size of thearubigins.     

Sensitive assay for determining plasma tenofovir concentrations by LC/MS/MS

An LC/MS/MS assay for the determination of tenofovir (TNF) was developed and validated for use with the EDTA anticoagulated human plasma matrix. Heparin-treated plasma and serum matrices were also validated. After addition of adefovir as an internal standard, trifluoroacetic acid was used to produce a protein-free extract. Chromatographic separation was achieved with a Polar-RP Synergi, 2.0 mm x 150 mm, reversed-phase analytical column. The mobile phase was 3% acetonitrile/1% acetic acid, aq. Detection of TNF and the internal standard was achieved by ESI MS/MS in the positive ion mode using 288/176 and 274/162 transitions, respectively. The method was linear from 10 to 750 ng/ml with a minimum quantifiable limit of 10 ng/ml when 250 microl aliquots were analyzed. The usefulness of this LC/MS/MS method to routinely monitor plasma concentrations of TNF was demonstrated along with its ability to assist in the performance of pharmacokinetic studies.     

Biological monitoring of bisphenol A with HLPC/FLD and LC/MS/MS assays

Biological monitoring is a necessary process for risk assessment of endocrine disrupting chemicals (EDCs), particularly, bisphenol A (BPA), in breast milk, because its human risks are not clear yet, and infants, who feed on breast milk, are highly susceptible for EDCs. Concerning biological monitoring of BPA, the HPLC/FLD has been widely used before the LC/MS/MS. However, there was no report, which simultaneously evaluated the two methods in real analyses. Therefore, we analyzed BPA with LC/MS/MS and HPLC/FLD in human breast milk and conducted comparison of two methods in analyzed BPA levels. After establishing optimal condition, e.g. linearity, recovery, reproducibility and free BPA system, we analyzed BPA levels in human breast milk samples (N = 100). The LOQs were similar in the two methods, i.e. 1.8 and 1.3 ng/mL for the HPLC/FLD and LC/MS/MS assays, respectively. There were strong associations between total BPA levels with the two methods (R² = 0.40, p < 0.01), however, only 11% of them were analyzed as similar levels with 15% CVs. In addition, the detection range of BPA was broader in the HPLC method than the LC/MS/MS method. However, the BPA levels in the HPLC/FLD analysis were lower than those in the LC/MS/MS analysis (p < 0.01). Thus, the differences in BPA levels between the two methods may come from mainly over-estimation with the LC/MS/MS method in low BPA samples and some of poor resolution with the HPLC/FLD in high BPA samples.     

Expert System for Computer-assisted Annotation of MS/MS Spectra

An important step in mass spectrometry (MS)-based proteomics is the identification of peptides by their fragment spectra. Regardless of the identification score achieved, almost all tandem-MS (MS/MS) spectra contain remaining peaks that are not assigned by the search engine. These peaks may be explainable by human experts but the scale of modern proteomics experiments makes this impractical. In computer science, Expert Systems are a mature technology to implement a list of rules generated by interviews with practitioners. We here develop such an Expert System, making use of literature knowledge as well as a large body of high mass accuracy and pure fragmentation spectra. Interestingly, we find that even with high mass accuracy data, rule sets can quickly become too complex, leading to over-annotation. Therefore we establish a rigorous false discovery rate, calculated by random insertion of peaks from a large collection of other MS/MS spectra, and use it to develop an optimized knowledge base. This rule set correctly annotates almost all peaks of medium or high abundance. For high resolution HCD data, median intensity coverage of fragment peaks in MS/MS spectra increases from 58% by search engine annotation alone to 86%. The resulting annotation performance surpasses a human expert, especially on complex spectra such as those of larger phosphorylated peptides. Our system is also applicable to high resolution collision-induced dissociation data. It is available both as a part of MaxQuant and via a webserver that only requires an MS/MS spectrum and the corresponding peptides sequence, and which outputs publication quality, annotated MS/MS spectra (www.biochem.mpg.de/mann/tools/). It provides expert knowledge to beginners in the field of MS-based proteomics and helps advanced users to focus on unusual and possibly novel types of fragment ions.In MS-based proteomics, peptides are matched to peptide sequences in databases using search engines (1–3). Statistical criteria are established for accepted versus rejected peptide spectra matches based on the search engine score, and usually a 99% certainty is required for reported peptides. The search engines typically only take sequence specific backbone fragmentation into account (i.e. a, b, and y ions) and some of their neutral losses. However, tandem mass spectra—especially of larger peptides—can be quite complex and contain a number of medium or even high abundance peptide fragments that are not annotated by the search engine result. This can result in uncertainty for the user—especially if only relatively few peaks are annotated—because it may reflect an incorrect identification. However, the most common cause of unlabeled peaks is that another peptide was present in the precursor selection window and was cofragmented. This has variously been termed “chimeric spectra” (4–6), or the problem of low precursor ion fraction (PIF)¹ (7). Such spectra may still be identifiable with high confidence. The Andromeda search engine in MaxQuant, for instance, attempts to identify a second peptide in such cases (8, 9). However, even “pure” spectra (those with a high PIF) often still contain many unassigned peaks. These can be caused by different fragment types, such as internal ions, single or combined neutral losses as well as immonium and other ion types in the low mass region. A mass spectrometric expert can assign many or all of these peaks, based on expert knowledge of fragmentation and manual calculation of fragment masses, resulting in a higher degree of confidence for the identification. However, there are more and more practitioners of proteomics without in depth training or experience in annotating MS/MS spectra and such annotation would in any case be prohibitive for hundreds of thousands of spectra. Furthermore, even human experts may wrongly annotate a given peak—especially with low mass accuracy tandem mass spectra—or fail to consider every possibility that could have resulted in this fragment mass.Given the desirability of annotating fragment peaks to the highest degree possible, we turned to “Expert Systems,” a well-established technology in computer science. Expert Systems achieved prominence in the 1970s and 1980s and were meant to solve complex problems by reasoning about knowledge (10, 11). Interestingly, one of the first examples was developed by Nobel Prize winner Joshua Lederberg more than 40 years ago, and dealt with the interpretation of mass spectrometric data. The program''s name was Heuristic DENTRAL (12), and it was capable of interpreting the mass spectra of aliphatic ethers and their fragments. The hypotheses produced by the program described molecular structures that are plausible explanations of the data. To infer these explanations from the data, the program incorporated a theory of chemical stability that provided limiting constraints as well as heuristic rules.In general, the aim of an Expert System is to encode knowledge extracted from professionals in the field in question. This then powers a rule-based system that can be applied broadly and in an automated manner. A rule-based Expert System represents the information obtained from human specialists in the form of IF-THEN rules. These are used to perform operations on input data to reach appropriate conclusion. A generic Expert System is essentially a computer program that provides a framework for performing a large number of inferences in a predictable way, using forward or backward chains, backtracking, and other mechanisms (13). Therefore, in contrast to statistics based learning, the “expert program” does not know what it knows through the raw volume of facts in the computer''s memory. Instead, like a human expert, it relies on a reasoning-like process of applying an empirically derived set of rules to the data.Here we implemented an Expert System for the interpretation for high mass accuracy tandem mass spectrometry data of peptides. It was developed in an iterative manner together with human experts on peptide fragmentation, using the published literature on fragmentation pathways as well as large data sets of higher-energy collisional dissociation (HCD) (14) and collision-induced dissociation (CID) based peptide identifications. Our goal was to achieve an annotation performance similar or better than experienced mass spectrometrists (15), thus making comprehensively annotated peptide spectra available in large scale proteomics.     

PRIMA: peptide robust identification from MS/MS spectra

In proteomics, tandem mass spectrometry is the key technology for peptide sequencing. However, partially due to the deficiency of peptide identification software, a large portion of the tandem mass spectra are discarded in almost all proteomics centers because they are not interpretable. The problem is more acute with the lower quality data from low end but more popular devices such as the ion trap instruments. In order to deal with the noisy and low quality data, this paper develops a systematic machine learning approach to construct a robust linear scoring function, whose coefficients are determined by a linear programming. A prototype, PRIMA, was implemented. When tested with large benchmarks of varying qualities, PRIMA consistently has higher accuracy than commonly used software MASCOT, SEQUEST and X! Tandem.     

MassSieve: Panning MS/MS peptide data for proteins

We present MassSieve, a Java‐based platform for visualization and parsimony analysis of single and comparative LC‐MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC‐MS/MS‐based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments.