A fast coarse filtering method for peptide identification by mass spectrometry

MOTIVATION: We reformulate the problem of comparing mass-spectra by mapping spectra to a vector space model. Our search method leverages a metric space indexing algorithm to produce an initial candidate set, which can be followed by any fine ranking scheme. RESULTS: We consider three distance measures integrated into a multi-vantage point index structure. Of these, a semi-metric fuzzy-cosine distance using peptide precursor mass constraints performs the best. The index acts as a coarse, lossless filter with respect to the SEQUEST and ProFound scoring schemes, reducing the number of distance computations and returned candidates for fine filtering to about 0.5% and 0.02% of the database respectively. The fuzzy cosine distance term improves specificity over a peptide precursor mass filter, reducing the number of returned candidates by an order of magnitude. Run time measurements suggest proportional speedups in overall search times. Using an implementation of ProFound's Bayesian score as an example of a fine filter on a test set of Escherichia coli protein fragmentation spectra, the top results of our sample system are consistent with that of SEQUEST.     

Online coupling of capillary electrophoresis with mass spectrometry for the identification of biomarkers for clinical diagnosis

Proteomic screening of complex biologic samples is of increasing importance in clinical research and diagnosis. In the postgenomic area it is evident that changes of the composition of body fluids, as well as post-translational modifications of proteins and peptides, provide more information than genetic typing. The study of these changes allows the state of health or disease of particular organs, and consequently, the whole organism, to be described. This review describes the application of capillary electrophoresis coupled online to an electrospray ionization time-of-flight mass spectrometer to the analysis of body fluids obtained from patients for the identification of biomarkers for diagnostic purposes.     

Pareto-optimal plans as ground truth for validation of a commercial system for knowledge-based DVH-prediction

PurposeTreatment plans manually generated in clinical routine may suffer from variations and inconsistencies in quality. Using such plans for validating a DVH prediction algorithm might obscure its intrinsic prediction accuracy. In this study we used a recently published large database of Pareto-optimal prostate cancer plans to assess the prediction accuracy of a commercial knowledge-based DVH prediction algorithm, RapidPlan. The database plans were consistently generated with automated planning using an independent optimizer, and can be considered as aground truth of plan quality.MethodsPrediction models were generated using training sets with 20, 30, 45, 55 and 114 Pareto-optimal plans. Model-20 and Model-30 were built using 5 groups of randomly selected training patients. For 60 independent Pareto-optimal validation plans, predicted and database DVHs were compared.ResultsFor model-114, differences between predicted and database mean doses of more than ± 10% in rectum, anus and bladder, occurred for 23.3%, 55.0%, and 6.7% of the validation plans, respectively. For rectum V_65Gy and V_75Gy, differences outside the ±10% range were observed in 21.7% and 70.0% of validation plans, respectively. For 61.7% of validation plans, inaccuracies in predicted rectum DVHs resulted in a deviation in predicted NTCP for rectal bleeding outside ±10%. With smaller training sets the DVH prediction performance deteriorated, showing dependence on the selected training patients.ConclusionEven when analysed with Pareto-optimal plans with highly consistent quality, clinically relevant deviations in DVH predictions were observed. Such deviations could potentially result in suboptimal plans for new patients. Further research on DVH prediction models is warranted.     

Development of a combined chemical and enzymatic approach for the mass spectrometric identification and quantification of aberrant N-glycosylation

Direct mass spectrometric analysis of aberrant protein glycosylation is a challenge to the current analytical techniques. Except lectin affinity chromatography, no other glycosylation enrichment techniques are available for analysis of aberrant glycosylation. In this study, we developed a combined chemical and enzymatic strategy as an alternative for the mass spectrometric analysis of aberrant glycosylation. Sialylated glycopeptides were enriched with reverse glycoblotting, cleaved by endoglycosidase F3 and analyzed by mass spectrometry with both neutral loss triggered MS³ in collision induced dissociation (CID) and electron transfer dissociation (ETD). Interestingly, a great part of resulted glycopeptides were found with fucose attached to the N-acetylglucosamine (N-GlcNAc), which indicated that the aberrant glycosylation that is carrying both terminal sialylation and core fucosylation was identified. Totally, 69 aberrant N-glycosylation sites were identified in sera samples from hepatocellular carcinoma (HCC) patients. Following the identification, quantification of the level of this aberrant glycosylation was also carried out using stable isotope dimethyl labeling and pooled sera sample from liver cirrhosis and HCC was compared. Six glycosylation sites demonstrated elevated level of aberrancy, which demonstrated that our developed strategy was effective in both qualitative and quantitative studies of aberrant glycosylation.     

A computational method for assessing peptide- identification reliability in tandem mass spectrometry analysis with SEQUEST

High-throughput protein identification in mass spectrometry is predominantly achieved by first identifying tryptic peptides by a database search and then by combining the peptide hits for protein identification. One of the popular tools used for the database search is SEQUEST. Peptide identification is carried out by selecting SEQUEST hits above a specified threshold, the value of which is typically chosen empirically in an attempt to separate true identifications from false ones. These SEQUEST scores are not normalized with respect to the composition, length and other parameters of the peptides. Furthermore, there is no rigorous reliability estimate assigned to the protein identifications derived from these scores. Hence, the interpretation of SEQUEST hits generally requires human involvement, making it difficult to scale up the identification process for genome-scale applications. To overcome these limitations, we have developed a method, which combines a neural network and a statistical model, for normalizing SEQUEST scores, and also for providing a reliability estimate for each SEQUEST hit. This method improves the sensitivity and specificity of peptide identification compared to the standard filtering procedure used in the SEQUEST package, and provides a basis for estimating the reliability of protein identifications.     

Development and validation of a spectral library searching method for peptide identification from MS/MS

A notable inefficiency of shotgun proteomics experiments is the repeated rediscovery of the same identifiable peptides by sequence database searching methods, which often are time-consuming and error-prone. A more precise and efficient method, in which previously observed and identified peptide MS/MS spectra are catalogued and condensed into searchable spectral libraries to allow new identifications by spectral matching, is seen as a promising alternative. To that end, an open-source, functionally complete, high-throughput and readily extensible MS/MS spectral searching tool, SpectraST, was developed. A high-quality spectral library was constructed by combining the high-confidence identifications of millions of spectra taken from various data repositories and searched using four sequence search engines. The resulting library consists of over 30,000 spectra for Saccharomyces cerevisiae. Using this library, SpectraST vastly outperforms the sequence search engine SEQUEST in terms of speed and the ability to discriminate good and bad hits. A unique advantage of SpectraST is its full integration into the popular Trans Proteomic Pipeline suite of software, which facilitates user adoption and provides important functionalities such as peptide and protein probability assignment, quantification, and data visualization. This method of spectral library searching is especially suited for targeted proteomics applications, offering superior performance to traditional sequence searching.     

A systematical analysis of tryptic peptide identification with reverse phase liquid chromatography and electrospray ion trap mass spectrometry

In this study we systematically analyzed the elution condition of tryptic peptides and the characteristics of identified peptides in reverse phase liquid chromatography and electrospray tandem mass spectrometry (RPLC-MS/MS) analysis. Following protein digestion with trypsin, the peptide mixture was analyzed by on-line RPLC-MS/MS. Bovine serum albumin (BSA) was used to optimize acetonitrile (ACN) elution gradient for tryptic peptides, and Cytochrome C was used to retest the gradient and the sensitivity of LC-MS/MS. The characteristics of identified peptides were also analyzed. In our experiments, the suitable ACN gradient is 5% to 30% for tryptic peptide elution and the sensitivity of LC-MS/MS is 50 fmol.Analysis of the tryptic peptides demonstrated that longer (more than 10 amino acids) and multi-charge state ( 2, 3) peptides are likely to be identified, and the hydropathicity of the peptides might not be related to whether it is more likely to be identified or not. The number of identified peptides for a protein might be used to estimate its loading amount under the same sample background. Moreover, in this study the identified peptides present three types of redundancy, namely identification, charge, and sequence redundancy, which may repress low abundance protein identification.     

Immunoaffinity techniques coupled to mass spectrometry for the analysis of human peptide hormones: advances and applications

Introduction: The accurate and comprehensive determination of peptide hormones from biological fluids has represented a considerable challenge to analytical chemists for decades. Besides long-established bioanalytical ligand binding assays (or ELISA, RIA, etc.), more and more mass spectrometry-based methods have been developed recently for purposes commonly referred to as targeted proteomics. Eventually the combination of both, analyte extraction by immunoaffinity and subsequent detection by mass spectrometry, has shown to synergistically enhance the test methods’ performance characteristics.

Areas covered: The review provides an overview about the actual state of existing methods and applications concerning the analysis of endogenous peptide hormones. Here, special focus is on recent developments considering the extraction procedures with immobilized antibodies, the subsequent separation of target analytes, and their detection by mass spectrometry.

Expert commentary: Key aspects of procedures aiming at the detection and/or quantification of peptidic analytes in biological matrices have experienced considerable improvements in the last decade, particularly in terms of the assays’ sensitivity, the option of multiplexing target compounds, automatization, and high throughput operation. Despite these advances and progress as expected to be seen in the near future, immunoaffinity purification coupled to mass spectrometry is not yet a standard procedure in routine analysis compared to ELISA/RIA.     

Labeling elastase digests with TMT: informational gain by identification of poorly detectable peptides with MALDI-TOF/TOF mass spectrometry

The applicability of the less specific protease elastase for the identification of membrane and cytosolic proteins has already been demonstrated. MALDI as ionization technique particularly favors the detection of basic and to a lesser extent of weakly acidic peptides, whereas neutral peptides often remain undetected. Moreover, peptides below 700 Da are routinely excluded. In the following study, the advantage of additional information gained from tandem mass tag zero labeled peptides and the resultant increase in sequence coverage was evaluated. Through derivatization with tandem mass tag reagents, peptide measurement within the standard mass range of the MALDI reflector mode is achievable due to the mass increase. Compared to the unlabeled sample, peptides exhibiting relatively low molecular masses, pI values or higher hydrophobicity could be identified.     

Utilization and evaluation of CHO-specific sequence databases for mass spectrometry based proteomics

Recently released sequence information on Chinese hamster ovary (CHO) cells promises to not only facilitate our understanding of these industrially important cell factories through direct analysis of the sequence, but also to enhance existing methodologies and allow new tools to be developed. In this article we demonstrate the utilization of CHO specific sequence information to improve mass spectrometry (MS) based proteomic identification. The use of various CHO specific databases enabled the identification of 282 additional proteins, thus increasing the total number of identified proteins by 40-50%, depending on the sample source and methods used. In addition, a considerable portion of those proteins that were identified previously based on inter-species sequence homology were now identified by a larger number of peptides matched, thus increasing the confidence of identification. The new sequence information offers improved interpretation of proteomic analyses and will, in the years to come, prove vital to unraveling the CHO proteome.     

A two-dimensional liquid-phase separation method coupled with mass spectrometry for proteomic studies of breast cancer and biomarker identification

A two-dimensional liquid-phase separation scheme coupled with mass spectrometry (MS) is presented for proteomic analysis of cell lysates from normal and malignant breast epithelial cell lines. Liquid-phase separations consist of isoelectric focusing as the first dimension and nonporous silica reverse-phase high-performance liquid chromatography (NPS-RP-HPLC) as the second dimension. Protein quantitation and mass measurement are performed using electrospray ionization-time of flight MS (ESI-TOF MS). Proteins are identified by peptide mass fingerprinting using matrix-assisted laser desorption ionization-time of flight MS (MALDI-TOF MS) and MALDI-quadrupole time of flight (QTOF)-tandem mass spectrometry (MS/MS). Two pH regions with 50-60 unique proteins in each pH range were chosen for analysis. Mass maps were created that allowed visualization of protein quantitation differences between normal and malignant breast epithelial cells. Of the approximately 110 unique proteins observed from mass mapping experiments over the limited pH range, 40 (36%) were positively identified by peptide mass fingerprinting and assigned to bands in the mass maps. Of these 40 proteins, 22 were more highly expressed in one or more of the malignant cell lines. These proteins represent potential breast cancer biomarkers that could aid in diagnosis, therapy, or drug development.     

Recent advances in mass spectrometry analysis of histone post-translational modifications: potential clinical impact of the PAT-H-MS approach

Histone post-translational modifications (hPTMs) contribute to the regulation of gene expression and increasing evidence links them to the development of various pathologies, highlighting their potential as biomarkers for prognostic, diagnostic and therapeutic applications. Mass spectrometry (MS) has emerged as a powerful analytical tool for hPTM analysis, which has also been applied to the analysis of epigenetic aberrations in diseases. However, the potential offered by the MS-based hPTM analysis of clinical samples for epigenetic biomarker discovery has been left largely unexploited. This article summarizes the contribution of MS-based approaches to clinical epigenetics, with a special focus on the PAThology tissue analysis of Histones by Mass Spectrometry (PAT-H-MS) approach – which represents the first application of MS-based hPTM analysis to formalin-fixed paraffin-embedded clinical samples – discussing its strengths and limitations, as well as possible implementations.     

An in vivo parameter identification method for arteries: numerical validation for the human abdominal aorta

A method for identifying mechanical properties of arterial tissue in vivo is proposed in this paper and it is numerically validated for the human abdominal aorta. Supplied with pressure-radius data, the method determines six parameters representing relevant mechanical properties of an artery. In order to validate the method, 22 finite element arteries are created using published data for the human abdominal aorta. With these in silico abdominal aortas, which serve as mock experiments with exactly known material properties and boundary conditions, pressure-radius data sets are generated and the mechanical properties are identified using the proposed parameter identification method. By comparing the identified and pre-defined parameters, the method is quantitatively validated. For healthy abdominal aortas, the parameters show good agreement for the material constant associated with elastin and the radius of the stress-free state over a large range of values. Slightly larger discrepancies occur for the material constants associated with collagen, and the largest relative difference is obtained for the in situ axial prestretch. For pathological abdominal aortas incorrect parameters are identified, but the identification method reveals the presence of diseased aortas. The numerical validation indicates that the proposed parameter identification method is able to identify adequate parameters for healthy abdominal aortas and reveals pathological aortas from in vivo-like data.     

A proteomic method for the analysis of changes in protein concentrations in response to systemic perturbations using metabolic incorporation of stable isotopes and mass spectrometry

While several techniques exist for assessing quantitative differences among proteomes representing different cell states, methods for assessing how these differences are mediated are largely missing. We present a method that allows one to differentiate between cellular processes, such as protein synthesis, degradation and PTMs which affect protein concentrations. An induced systemic perturbation of a cell culture was coupled to a replacement of the growth medium to one highly enriched in the stable isotope 15N. The relative abundance of the 15N- and 14N-enriched forms of proteins, isolated from cell cultures harvested at time points following the onset of the perturbation, were determined by MS. Alterations in protein synthesis and degradation were quantified by comparing proteins isolated from perturbed and unperturbed cultures, respectively. The method was evaluated by subjecting HeLa cells to heat stress. As expected, a number of known heat shock proteins (Hsp) increased in concentration during heat stress. For Hsp27, increased de novo synthesis accounted for the concentration increase, while for Hsp70, decreased degradation accounted for the increase. A protein that was detected only after prolonged heat stress, vimentin, was not primarily synthesized de novo, but appeared rather as a result of PTM.     

A label-free mass spectrometry method for the quantification of protein isotypes

Successful quantitative mass spectrometry (MS) requires strategies to link the mass spectrometer response to the analyte abundance, with the response being dependent on more factors than just analyte abundance. Label-dependent strategies rely on the incorporation of an isotopically labeled internal standard into the sample. Current label-free strategies (performed without internal standards) are useful for analyzing samples that are unsuitable for isotopic labeling but are less accurate. Here we describe a label-free technique applicable to analysis of products from related genes (isotypes). This approach enables the invariant tryptic peptide sequences within the family to serve as “built-in” internal standards and the isotype-specific peptide sequences to report the amount of the various isotypes. A process of elimination segregates reliably trypsin-released standard and reporter peptides from unreliably released peptides. The specific MS response factors for these reporter and standard peptides can be determined using synthetic peptides. Analysis of HeLa tubulin digests revealed peptides from βI-, βII-, βIII-, βIVb-, and βV-tubulin, eight of which were suitable; along with five standard peptides for quantification of the β-tubulin isotypes. To show the utility of this method, we determined that βI-tubulin represented 77% and βIII-tubulin represented 3.2% of the total HeLa β-tubulin.     

Large-scale identification of proteins in human salivary proteome by liquid chromatography/mass spectrometry and two-dimensional gel electrophoresis-mass spectrometry

Human saliva contains a large number of proteins and peptides (salivary proteome) that help maintain homeostasis in the oral cavity. Global analysis of human salivary proteome is important for understanding oral health and disease pathogenesis. In this study, large-scale identification of salivary proteins was demonstrated by using shotgun proteomics and two-dimensinal gel electrophoresis-mass spectrometry (2-DE-MS). For the shotgun approach, whole saliva proteins were prefractionated according to molecular weight. The smallest fraction, presumably containing salivary peptides, was directly separated by capillary liquid chromatography (LC). However, the large protein fractions were digested into peptides for subsequent LC separation. Separated peptides were analyzed by on-line electrospray tandem mass spectrometry (MS/MS) using a quadrupole-time of flight mass spectrometer, and the obtained spectra were automatically processed to search human protein sequence database for protein identification. Additionally, 2-DE was used to map out the proteins in whole saliva. Protein spots 105 in number were excised and in-gel digested; and the resulting peptide fragments were measured by matrix-assisted laser desorption/ionization-mass spectrometry and sequenced by LC-MS/MS for protein identification. In total, we cataloged 309 proteins from human whole saliva by using these two proteomic approaches.     

A liquid chromatography-tandem mass spectrometry method for measurement of N-modified phosphatidylethanolamines

N-Acyl phosphatidylethanolamines (NAPEs) are synthesised in response to stress in a variety of organisms from bacteria to humans. More recently, nonenzymatic modification of the ethanolamine headgroup of phosphatidylethanolamine (PE) by various aldehydes, including levuglandins/isoketals (which are γ-ketoaldehydes [γKAs] derived from arachidonic acid), has also been demonstrated. The levels of these various N-modified PEs formed during stress and their biological significance remain to be fully characterized. Such studies require an accurate, facile, and cost-effective method for quantifying N-modified PEs. Previously, NAPE and some of the nonenzymatically N-modified PE species have been quantified by mass spectrometry after hydrolysis to their constituent N-acylethanolamine by enzymatic hydrolysis, most typically with Streptomyces chromofuscus phospholipase D. However, enzymatic hydrolysis is not cost-effective for routine analysis of a large number of samples, and hydrolytic efficiency may vary for different N-modified PEs, making quantitation more difficult. Therefore, we sought a robust and inexpensive chemical hydrolysis approach. Methylamine (CH₃NH₂)-mediated deacylation has previously been used in headgroup analysis of phosphatidylinositol phosphates. Therefore, we developed an accurate assay for NAPEs and γKA-PEs using CH₃NH₂-mediated deacylation and quantitation of the resulting glycerophospho-N-modified ethanolamines by liquid chromatography-tandem mass spectrometry.