XPSSurfA: An open collaborative XPS data repository using the CMSShub platform

X‐ray photoelectron spectroscopy (XPS) is a widely used surface analysis technique employed in fundamental research, applied research, service laboratories, and industry. Good‐quality analytical outcomes depend critically on spectral references. Many examples of XPS reference databases exist, including print editions, sets of spectral peak positions drawn from the literature, and digital archives and libraries. We report the development of a new digital XPS database comprising survey spectra and region spectra for a range of materials types, collected under a common set of analytical conditions. Each material is described using spectra collected at multiple pass energies with all photoelectron and X‐ray induced Auger transitions represented. Detailed metadata are provided for each material and each spectrum, presented using a schema that incorporates the ISO 16243 and 14976 standards and extensions developed in this work. Spectra are shared under a Creative Commons International (4.0) attribution, non‐commercial licence (CC BY‐NC) in Kratos (.dset), VAMAS (.vms), and XML (.xml) formats. It is intended that reference spectra be imported directly into XPS data analysis software packages for reference and comparison purposes, matching either the peak or transition of interest and the instrument pass energy. The database is flexible and scalable in structure and has the potential to become a core XPS reference resource.     

Evaluation of mass spectral library search algorithms implemented in commercial software

Performance of several library search algorithms (against EI mass spectral databases) implemented in commercial software products ( acd/specdb , chemstation , gc/ms solution and ms search ) was estimated. Test set contained 1000 mass spectra, which were randomly selected from NIST'08 (RepLib) mass spectral database. It was shown that composite (also known as identity) algorithm implemented in ms search (NIST) software gives statistically the best results: the correct compound occupied the first position in the list of possible candidates in 81% of cases; the correct compound was within the list of top ten candidates in 98% of cases. It was found that use of presearch option can lead to rejection of the correct answer from the list of possible candidates (therefore presearch option should not be used, if possible). Overall performance of library search algorithms was estimated using receiver operating characteristic curves. Copyright © 2015 John Wiley & Sons, Ltd.     

Combination of continuous digestion by peptidase and spectral similarity comparisons for peptide sequencing

Peptide sequencing is critical to the quality control of peptide drugs and functional studies of active peptides. A combination of peptidase digestion and mass spectrometry technology is common for peptide sequencing. However, such methods often cannot obtain the complete sequence of a peptide due to insufficient amino acid sequence information. Here, we developed a method of generating full peptide ladders and comparing their MS² spectral similarities. The peptide ladders, of which each component was different from the next component with one residue, were generated by continuous digestion by peptidase (carboxypeptidase Y and aminopeptidase). Then, based on the characteristics of peptide ladders, complete sequencing was realized by comparing MS² spectral similarity of the generated peptide ladders. The complete amino acid sequences of bivalirudin, adrenocorticotropic hormone, and oxytocin were determined with high accuracy. This approach is beneficial to the quality control of drug peptides as well as the identification of novel bioactive peptides.     

MimoDB: a new repository for mimotope data derived from phage display technology

Peptides selected from phage-displayed random peptide libraries are valuable in two aspects. On one hand, these peptides are candidates for new diagnostics, therapeutics and vaccines. On the other hand, they can be used to predict the networks or sites of protein-protein interactions. MimoDB, a new repository for these peptides, was developed, in which 10,716 peptides collected from 571 publications were grouped into 1,229 sets. Besides peptide sequences, other important information, such as the target, template, library and complex structure, was also included. MimoDB can be browsed and searched through a user-friendly web interface. For computational biologists, MimoDB can be used to derive customized data sets and benchmarks, which are useful for new algorithm development and tool evaluation. For experimental biologists, their results can be searched against the MimoDB database to exclude possible target-unrelated peptides. The MimoDB database is freely accessible at http://immunet.cn/mimodb/.     

MSDCARB — a database and software for mass spectral data of carbohydrates

A special database has been developed for the mass spectral data of carbohydrates and their conjugates (MSDCARB), together with appropriate software which allows one to collect, store, edit, retrieve, search, compare and display mass spectra in table form or in graphic mode. The database contains over 400 electron impact 70 eV and/or 12 eV low resolution mass spectra obtained at the Institute of Chemistry of the Slovak Academy of Sciences. The database can be extended using re-evaluated mass spectral data from other sources. The software described enables the handling of mass spectral data libraries, the creation of sub-libraries, browsing through the libraries according to various criteria and their combination and the comparison of spectra using a variety of parameters.     

Evaluation of the sensitivity of the ‘Wiley registry of tandem mass spectral data,MSforID’ with MS/MS data of the ‘NIST/NIH/EPA mass spectral library’

Tandem mass spectral libraries are versatile tools for small molecular identification finding application in forensic science, doping control, drug monitoring, food and environmental analysis, as well as metabolomics. Two important libraries are the ‘Wiley Registry of Tandem Mass Spectral Data, MSforID’ (Wiley Registry MSMS) and the collection of MS/MS spectra part of the 2011 edition of the ‘NIST/NIH/EPA Mass Spectral Library’ (NIST 11 MSMS). Herein, the sensitivity and robustness of the Wiley Registry MSMS were evaluated using spectra extracted from the NIST 11 MSMS library. The sample set was found to be heterogeneous in terms of mass spectral resolution, type of CID, as well as applied collision energies. Nevertheless, sensitive compound identification with a true positive identification rate ≥95% was possible using either the MSforID Search program or the NIST MS Search program 2.0g for matching. To rate the performance of the Wiley Registry MSMS, cross‐validation experiments were repeated using subcollections of NIST 11 MSMS as reference library and spectra extracted from the Wiley Registry MSMS as positive controls. Unexpectedly, with both search algorithms tested, correct results were obtained in less than 88% of cases. We examined possible causes for the results of the cross validation study. The large number of precursor ions represented by a single tandem mass spectrum only was identified as the basic cause for the comparably lower sensitivity of the NIST library. Copyright © 2013 John Wiley & Sons, Ltd.     

Supervised principal components: a new method for multivariate spectral analysis

The supervised principal components (SPC) method was proposed by Bair and Tibshirani for statistics regression problems where the number of variables greatly exceeds the number of samples. This case is extremely common in multivariate spectral analysis. The objective of this research is to apply SPC to near‐infrared and Raman spectral calibration. SPC is similar to traditional principal components analysis except that it selects the most significant part of wavelength from the high‐dimensional spectral data, which can reduce the risk of overfitting and the effect of collinearity in modeling according to a semi‐supervised strategy. In this study, four conventional regression methods, including principal component regression, partial least squares regression, ridge regression, and support vector regression, were compared with SPC. Three evaluation criteria, coefficient of determination (R²), external correlation coefficient (Q²), and root mean square error of prediction, were calculated to evaluate the performance of each algorithm on both near‐infrared and Raman datasets. The comparison results illustrated that the SPC model had a desirable ability of regression and prediction. We believe that this method might be an alternative method for multivariate spectral analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

The evolving field of imaging mass spectrometry and its impact on future biological research

Within the past decade, imaging mass spectrometry (IMS) has been increasingly recognized as an indispensable technique for studying biological systems. Its rapid evolution has resulted in an impressive array of instrument variations and sample applications, yet the tools and data are largely confined to specialists. It is therefore important that at this junction the IMS community begin to establish IMS as a permanent fixture in life science research thereby making the technology and/or the data approachable by non-mass spectrometrists, leading to further integration into biological and clinical research. In this perspective article, we provide insight into the evolution and current state of IMS and propose some of the directions that IMS could develop in order to stay on course to become one of the most promising new tools in life science research.     

An integrated method for metabolite detection and identification using a linear ion trap/Orbitrap mass spectrometer and multiple data processing techniques: application to indinavir metabolite detection

A new strategy using a hybrid linear ion trap/Orbitrap mass spectrometer and multiple post-acquisition data mining techniques was evaluated and applied to the detection and characterization of in vitro metabolites of indinavir. Accurate-mass, full-scan MS and MS/MS data sets were acquired with a generic data-dependent method and processed with extracted-ion chromatography (EIC), mass-defect filter (MDF), product-ion filter (PIF), and neutral-loss filter (NLF) techniques. The high-resolution EIC process was shown to be highly effective in the detection of common metabolites with predicted molecular weights. The MDF process, which searched for metabolites based on the similarity of mass defects of metabolites to those of indinavir and its core substructures, was able to find uncommon metabolites not detected by the EIC processing. The high-resolution PIF and NLF processes selectively detected metabolites that underwent fragmentation pathways similar to those of indinavir or its known metabolites. As a result, a total of 15 metabolites including two new indinavir metabolites were detected and characterized in a rat liver S9 incubation sample. Overall, these data mining techniques, which employed distinct metabolite search mechanisms, were complementary and effective in detecting both common and uncommon metabolites. In summary, the results demonstrated that this analytical strategy enables the high-throughput acquisition of accurate-mass LC/MS data sets, comprehensive search of a variety of metabolites through the post-acquisition processes, and effective structural characterization based on elemental compositions of metabolite molecules and their product ions.     

Swarm intelligence based wavelet coefficient feature selection for mass spectral classification: An application to proteomics data

This paper introduces the ant colony algorithm, a novel swarm intelligence based optimization method, to select appropriate wavelet coefficients from mass spectral data as a new feature selection method for ovarian cancer diagnostics. By determining the proper parameters for the ant colony algorithm (ACA) based searching algorithm, we perform the feature searching process for 100 times with the number of selected features fixed at 5. The results of this study show: (1) the classification accuracy based on the five selected wavelet coefficients can reach up to 100% for all the training, validating and independent testing sets; (2) the eight most popular selected wavelet coefficients of the 100 runs can provide 100% accuracy for the training set, 100% accuracy for the validating set, and 98.8% accuracy for the independent testing set, which suggests the robustness and accuracy of the proposed feature selection method; and (3) the mass spectral data corresponding to the eight popular wavelet coefficients can be located by reverse wavelet transformation and these located mass spectral data still maintain high classification accuracies (100% for the training set, 97.6% for the validating set, and 98.8% for the testing set) and also provide sufficient physical and medical meaning for future ovarian cancer mechanism studies. Furthermore, the corresponding mass spectral data (potential biomarkers) are in good agreement with other studies which have used the same sample set. Together these results suggest this feature extraction strategy will benefit the development of intelligent and real-time spectroscopy instrumentation based diagnosis and monitoring systems.     

Rapid characterization of chlorogenic acids in Duhaldea nervosa based on ultra‐high‐performance liquid chromatography–linear trap quadropole‐Orbitrap‐mass spectrometry and mass spectral trees similarity filter technique

Duhaldea nervosa (Wallich ex Candolle) A. Anderberg has been traditionally used as a food spice and also in folk medicine for treating traumatic injury and relieving rheumatism, especially accelerating the healing of a fracture. However, so far as we are aware, the chemical constituents have not been fully investigated. In this study, a practical method of mass spectral trees similarity filter, a data‐mining technique, was developed and evaluated for the rapid detection and identification complicated constituents based on ultra‐high‐performance liquid chromatography–linear trap quadropole‐Orbitrap‐mass spectrometry. Finally, a total of 47 chlorogenic acids, including 19 monoacyl‐quinic acids, 22 diacyl‐quinic acids, and six triacyl‐quinic acids, were unambiguously or tentatively identified based on their accurate mass measurement, chromatographic retention, MSⁿ spectra, and bibliography data. To our best knowledge, it is the first time to report the chlorogenic acids of D. nervosa, which would be beneficial for the further material basis and quality research. Meanwhile, this mass spectral trees similarity filter method could be envisioned to exhibit a wide application for the identification of complicated components from botanical extracts.     

An algorithm for thorough background subtraction from high-resolution LC/MS data: application for detection of glutathione-trapped reactive metabolites

A control sample background-subtraction algorithm was developed for thorough subtraction of background and matrix-related signals in high-resolution, accurate mass liquid chromatography/mass spectrometry (LC/MS) data to reveal ions of interest in an analyte sample. This algorithm checked all ions in the control scans within a specified time window around the analyte scan for potential subtraction of ions found in that analyte scan. Applying this method, chromatographic fluctuations between runs were dealt with and background and matrix-related signals in the sample could be thoroughly subtracted. The effectiveness of this algorithm was demonstrated using four test compounds, clozapine, diclofenac, imipramine, and tacrine, to reveal glutathione (GSH)-trapped reactive metabolites after incubation with human liver microsomes supplemented with GSH (30 microM compound, 45-min incubation). Using this algorithm with a +/- 1.0 min control scan time window, a +/- 5 ppm mass error tolerance, and appropriate control samples, the GSH-trapped metabolites were revealed as the major peaks in the processed LC/MS profiles. Such profiles allowed for comprehensive and reliable identification of these metabolites without the need for any presumptions regarding their behavior or properties with respect to mass spectrometric detection. The algorithm was shown to provide superior results when compared to several commercially available background-subtraction algorithms. Many of the metabolites detected were doubly charged species which would be difficult to detect with traditional GSH adduct screening techniques, and thus, some of the adducts have not previously been reported in the literature. Copyright (c) 2008 John Wiley & Sons, Ltd.     

完整糖基化肽段的富集与质谱解析新技术研究进展

蛋白质糖基化是生物体内最重要的翻译后修饰之一,在蛋白质稳定性、细胞内和细胞间信号转导、激素活化或失活和免疫调节等生理过程和病理进程中发挥重要作用.而异常的蛋白质糖基化往往和多种疾病的发生发展密切相关,目前应用于临床检测的多种肿瘤生物标志物大多属于糖蛋白或者糖抗原.因此在组学层次系统分析蛋白质糖基化的变化对阐明生物体内糖...     

Restricted spectral accuracy analysis to identify the single correct organic compound elemental‐composition from Orbitrap accurate mass data lists obtained at very high resolution

Restricted spectral accuracy is applied to Orbitrap data (240 000 resolution at m/z 400) to more clearly break out the scoring and ranking of allowable elemental compositions (ECs) in a candidate list. The correct EC is usually top ranked and separated from other answers by 10 to 40% within the dimensionless 0 to 100% scale, providing a single, definitive EC. The A + 2 position (where A denotes the monoisotopic line position) is especially advantageous in restricted spectral accuracy. It has enough intensity and more complexity than (A + 1) fine lines and is like a fingerprint. Avoidance of coalescence phenomena and careful ion population control are essential.     

Assignments of 1H and 13C NMR spectral data for ondansetron and its two novel metabolites, 1-hydroxy-ondansetron diastereoisomers

Assignments of 1H and 13C NMR chemical shifts were made by means of heteronuclear single quantum coherence (HSQC) and heteronuclear multiple bond correlation (HMBC) experiments for ondansetron, and by means of 1H-1H correlation spectroscopy (1H-1H COSY) and two-dimensional nuclear Overhauser effect spectroscopy (NOESY) experiments for two novel metabolites (M1 and M2) of ondansetron. These two metabolites were isolated for the first time from Mucor circinelloides.     

A new strategy for the discovery of epimedium metabolites using high-performance liquid chromatography with high resolution mass spectrometry

In this paper, a new strategy of drug metabolite discovery and identification was established using high-performance liquid chromatography with high resolution mass spectrometry (HPLC–HRMS) and a mass spectral trees similarity filter (MTSF) technique. The MTSF technique was developed as a means to rapidly discover comprehensive metabolites from multiple active components in a complicated biological matrix. Using full-scan mass spectra as the stem and data-dependent subsequent stage mass spectra to form branches, the HRMS and multiple-stage mass spectrometric data from detected compounds were converted to mass spectral trees data. Potential metabolites were discovered based on the similarity between their mass spectral trees and that known compounds or metabolites in a mass spectra trees library. The threshold value for match similarity scores was set at above 200, allowing approximately 80% of interference to be filtered out. A total of 115 metabolites of five flavonoid monomers (epimedin A, epimedin B, epimedin C, icariin, and baohuoside I) and herbal extract of epimedium were discovered and identified in rats via this new strategy. As a result, a metabolic profile for epimedium was obtained and a metabolic pathway was proposed. In addition, comparing to the widely used neutral loss filter (NLF), product ion filter (PIF), and mass defect filter (MDF) techniques, the MTSF technique was shown superior efficiency and selectivity for discovering and identifying metabolites in traditional Chinese medicine (TCM).