Combining low- and high-energy tandem mass spectra for optimized peptide quantification with isobaric tags

Isobaric tagging, via TMT or iTRAQ, is widely used in quantitative proteomics. To date, tandem mass spectrometric analysis of isobarically-labeled peptides with hybrid ion trap–orbitrap (LTQ-OT) instruments has been mainly carried out with higher-energy C-trap dissociation (HCD) or pulsed q dissociation (PQD). HCD provides good fragmentation of the reporter-ions, but peptide sequence-ion recovery is generally poor compared to collision-induced dissociation (CID). Herein, we describe an approach where CID and HCD spectra are combined. The approach ensures efficiently both identification and relative quantification of proteins. Tandem mass tags (TMTs) were used to label digests of human plasma and LC-MS/MS was performed with an LTQ-OT instrument. Different HCD collision energies were tested. The benefits to use CID and HCD with respect to HCD alone were demonstrated in terms of number of identifications, subsequent number of quantifiable proteins, and quantification accuracy. A program was developed to merge the peptide sequence-ion m/z range from CID spectra and the reporter-ion m/z range from HCD spectra, and alternatively to separate both spectral data into different files. As parallel CID in the LTQ almost doesn't affect the analysis duty cycle, the procedure should become a standard for quantitative analyses of proteins with isobaric tagging using LTQ-OT instruments.     

Improving SRM assay development: a global comparison between triple quadrupole, ion trap, and higher energy CID peptide fragmentation spectra

In proteomics, selected reaction monitoring (SRM) is rapidly gaining importance for targeted protein quantification. The triple quadrupole mass analyzers used in SRM assays allow for levels of specificity and sensitivity hard to accomplish by more standard shotgun proteomics experiments. Often, an SRM assay is built by in silico prediction of transitions and/or extraction of peptide precursor and fragment ions from a spectral library. Spectral libraries are typically generated from nonideal ion trap based shotgun proteomics experiments or synthetic peptide libraries, consuming considerable time and effort. Here, we investigate the usability of beam type CID (or "higher energy CID" (HCD)) peptide fragmentation spectra, as acquired using an Orbitrap Velos, to facilitate SRM assay development. Therefore, peptide fragmentation spectra, obtained by ion-trap CID, triple-quadrupole CID (QqQ-CID) and Orbitrap HCD, originating from digested cellular lysates, were compared. Spectral comparison and a dedicated correlation algorithm indicated significantly higher similarity between QqQ-CID and HCD fragmentation spectra than between QqQ-CID and ion trap-CID spectra. SRM transitions generated using a constructed HCD spectral library increased SRM assay sensitivity up to 2-fold, when compared to the use of a library created from more conventionally used ion trap-CID spectra, showing that HCD spectra can assist SRM assay development.     

Use of mass spectrometry to probe the nucleophilicity of cysteinyl residues of prolyl hydroxylase domain 2

Prolyl hydroxylase domain 2 (PHD2) plays an important role in hypoxic sensing in humans. Here we report studies on the reactivity of cysteinyl residues of the catalytic domain of PHD2 using an approach in which nondenaturing electrospray ionization–mass spectrometry (ESI–MS) analyses were combined with the use of a thiol library and residue substitution. Among the seven cysteinyl residues of the PHD2 catalytic domain, Cys201 was found to be predominantly modified by thiols or N-ethylmaleimide. Selective modification of Cys201 was further demonstrated with methanethiosulfonate, a spin-labeled probe. The modified PHD2 will be useful in electron paramagnetic resonance studies on PHD2. The results demonstrate the use of a combined library/residue substitution/ESI–MS approach for analyzing residue reactivity.     

De novo peptide sequencing using CID and HCD spectra pairs

In tandem mass spectrometry (MS/MS), there are several different fragmentation techniques possible, including, collision‐induced dissociation (CID) higher energy collisional dissociation (HCD), electron‐capture dissociation (ECD), and electron transfer dissociation (ETD). When using pairs of spectra for de novo peptide sequencing, the most popular methods are designed for CID (or HCD) and ECD (or ETD) spectra because of the complementarity between them. Less attention has been paid to the use of CID and HCD spectra pairs. In this study, a new de novo peptide sequencing method is proposed for these spectra pairs. This method includes a CID and HCD spectra merging criterion and a parent mass correction step, along with improvements to our previously proposed algorithm for sequencing merged spectra. Three pairs of spectral datasets were used to investigate and compare the performance of the proposed method with other existing methods designed for single spectrum (HCD or CID) sequencing. Experimental results showed that full‐length peptide sequencing accuracy was increased significantly by using spectra pairs in the proposed method, with the highest accuracy reaching 81.31%.     

Evaluation of infrared spectroscopy as a bacterial identification method

Summary A study motivated by the recent revival of interest in the use of IR spectroscopy to identify bacteria is reported. A library of FT-IR spectra of dried bacterial films was compled using 16 different strains. A test set was complied from spectra of the same strains grown several months later. The test set was quantitatively compared with the library on the basis of spectral similarity in the region 980–1190 cm^–1. Six of the strains in the test set were not matched with the correct strain in the library despite efforts to reproduce the conditions under which cells were grown and prepared. The results suggest that reproducibility of the bacterial spectra is a potential difficulty that must be addressed by any attempts to develop FT-IR spectroscopy as a bacterial identification method.     

Strategy for simulation of CID spectra of N-linked oligosaccharides toward glycomics

To develop a novel glycomics tool that can enable anyone to identify oligosaccharides very easily and quickly, we have recently constructed a library of observed multistage tandem mass (MS(n)) spectra for oligosaccharides. However, this approach requires the preparation of a large variety of structurally defined oligosaccharides. Therefore, simulation of the tandem mass spectrum for any given structure would be another powerful approach with which to improve the above method. By performing collision-induced dissociation (CID) experiments of sets of oligosaccharides complementarily labeled with (13)C(6)-D-galactose, we identified characteristic fragment patterns for each branch type of N-linked oligosaccharides. On the basis of these characteristic fragment patterns, we could simulate CID spectra for three isomeric oligosaccharides. In addition, we successfully demonstrated the identification of an oligosaccharide by matching its CID spectrum against the library of simulated tandem mass spectra. This strategy will be a useful tool for glycomics, as well as for approaches based on the library of observed MS(n) spectra.     

The fate of b-ions in the two worlds of collision-induced dissociation

Fragment analysis of proteins and peptides by mass spectrometry using collision-induced dissociation (CID) revealed that the pairwise generated N-terminal b- and C-terminal y-ions have different stabilities resulting in underrepresentation of b-ions. Detailed analyses of large-scale spectra databases and synthetic peptides underlined these observations and additionally showed that the fragmentation pattern depends on utilized CID regime. To investigate this underrepresentation further we systematically compared resonant excitation energy and beam-type CID facilitated on different mass spectrometer platforms: (i) quadrupole time-of-flight, (ii) linear ion trap and (iii) three-dimensional ion trap. Detailed analysis of MS/MS data from a standard tryptic protein digest revealed that b-ions are significantly underrepresented on all investigated mass spectrometers. By N-terminal acetylation of tryptic peptides we show for the first time that b-ion cyclization reaction significantly contributes to b-ion underrepresentation even on ion trap instruments and accounts for at most 16% of b-ion loss.     

Spectrally Resolved Morphometry of the Nucleus in Hepatocytes Stained by Four Histological Methods

A novel concept of spectrally resolved morphometry for histological specimens was developed using light microscopy combined with spectrally resolved imaging. The spectroscopic characteristics of rat hepatocytes stained by Haematoxylin and Eosin, Romanowsky–Giemsa, periodic acid–Schiff and Masson's trichrome were assessed. Light intensity in the range 450–850 nm was recorded from 10000 pixels of nuclear domains of each stained cell and represented as light transmittance spectra and optical density. In order to identify spectral shifts caused by stain– macromolecule interactions, we compared the spectra of individual stain components with those of DNA and bovine serum albumin. Chromatin and interchromatin areas were classified spectrally using a chosen spectral library followed by morphometric calculations of nuclear domains for each staining method. The spectral fingerprints of Masson's trichrome stain distinguished the nucleolus from the rest of the nuclear c hromatin, enabling the demarcation and calculation of the nucleolar area. Spectrally resolved imaging of human hepatocytes stained by Masson's trichrome stain revealed marked differences between the nucleolar area in normal human hepatocytes compared with hepatocellular carcinoma. Masson's trichrome stain also distinguished the nucleolar area in human breast carcinoma cells and keratinocytes.     

Hyphenated liquid chromatographic techniques in forensic toxicology

The prerequisite of applicability of hyphenated methods in forensic analysis is the achievement of a stage of “final maturity”. In the field of liquid chromatography, HPLC coupled with diode array detection (DAD) seems to fulfill this criterion, whilst the combination with atmospheric pressure ionization mass spectrometry (HPLC–API-MS) is still in a development stage. HPLC–DAD is broadly used as identification tool in forensic and in emergency toxicology. Two main approaches were observed; development of retention index scales for intra-laboratory exchange of data and establishing of databases only for intra-laboratory use. Using these approaches, several databases were established for toxicological relevant substances (illicit and therapeutic drugs and their metabolites, environmental poisons etc.) in biological fluids. Also, complete HPLC–DAD identification systems are commercially available. Further possibility of progress depends on the on-line combination (“triple hyphenation”) with other detection methods, preferably API-MS. HPLC–API-MS, both in electrospray (ESI) and atmospheric pressure chemical ionization (APCI) options, underwent dramatic development in the last decade and is reaching its final shape. The method was broadly applied for various groups of toxicologically relevant substances, a lot of them unaccessible for other techniques, including GC–MS. Particularly important was application of HPLC–API-MS for detection and quantitation of active, polar metabolites of various drugs and for analysis of macromolecules. APCI seems to be more useful for analysis of less polar compounds, whereas ESI is particularly valuable for determination of polar, large molecules (e.g., toxic peptides, polar metabolites etc.) Up to now, HPLC–API-MS has been mainly applied for dedicated analyses, but the introduction of APCI or ESI in systematic toxicological screening may be expected in the near future.     

The Generating Function of CID,ETD, and CID/ETD Pairs of Tandem Mass Spectra: Applications to Database Search

Recent emergence of new mass spectrometry techniques (e.g. electron transfer dissociation, ETD) and improved availability of additional proteases (e.g. Lys-N) for protein digestion in high-throughput experiments raised the challenge of designing new algorithms for interpreting the resulting new types of tandem mass (MS/MS) spectra. Traditional MS/MS database search algorithms such as SEQUEST and Mascot were originally designed for collision induced dissociation (CID) of tryptic peptides and are largely based on expert knowledge about fragmentation of tryptic peptides (rather than machine learning techniques) to design CID-specific scoring functions. As a result, the performance of these algorithms is suboptimal for new mass spectrometry technologies or nontryptic peptides. We recently proposed the generating function approach (MS-GF) for CID spectra of tryptic peptides. In this study, we extend MS-GF to automatically derive scoring parameters from a set of annotated MS/MS spectra of any type (e.g. CID, ETD, etc.), and present a new database search tool MS-GFDB based on MS-GF. We show that MS-GFDB outperforms Mascot for ETD spectra or peptides digested with Lys-N. For example, in the case of ETD spectra, the number of tryptic and Lys-N peptides identified by MS-GFDB increased by a factor of 2.7 and 2.6 as compared with Mascot. Moreover, even following a decade of Mascot developments for analyzing CID spectra of tryptic peptides, MS-GFDB (that is not particularly tailored for CID spectra or tryptic peptides) resulted in 28% increase over Mascot in the number of peptide identifications. Finally, we propose a statistical framework for analyzing multiple spectra from the same precursor (e.g. CID/ETD spectral pairs) and assigning p values to peptide-spectrum-spectrum matches.Since the introduction of electron capture dissociation (ECD)1 in 1998 (1), electron-based peptide dissociation technologies have played an important role in analyzing intact proteins and post-translational modifications (2). However, until recently, this research-grade technology was available only to a small number of laboratories because it was commercially unavailable, required experience for operation, and could be implemented only with expensive FT-ICR instruments. The discovery of electron-transfer dissociation (ETD) (3) enabled an ECD-like technology to be implemented in (relatively cheap) ion-trap instruments. Nowadays, many researchers are employing the ETD technology for tandem mass spectra generation (4–9).Although the hardware technologies to generate ETD spectra are maturing rapidly, software technologies to analyze ETD spectra are still in infancy. There are two major approaches to analyzing tandem mass spectra: de novo sequencing and database search. Both approaches find the best-scoring peptide either among all possible peptides (de novo sequencing) or among all peptides in a protein database (database search). Although de novo sequencing is emerging as an alternative to database search, database search remains a more accurate (and thus preferred) method of spectral interpretation, so here we focus on the database search approach.Numerous database search engines are currently available, including SEQUEST (10), Mascot (11), OMSSA (12), X!Tandem (13), and InsPecT (14). However, most of them are inadequate for the analysis of ETD spectra because they are optimized for collision induced dissociation (CID) spectra that show different fragmentation propensities than those of ETD spectra. Additionally, the existing tandem mass spectrometry (MS/MS) tools are biased toward the analysis of tryptic peptides because trypsin is usually used for CID, and thus not suitable for the analysis of nontryptic peptides that are common for ETD. Therefore, even though some database search engines support the analysis of ETD spectra (e.g. SEQUEST, Mascot, and OMSSA), their performance remains suboptimal when it comes to analyzing ETD spectra. Recently, an ETD-specific database search tool (Z-Core) was developed; however it does not significantly improve over OMSSA (15).We present a new database search tool (MS-GFDB) that significantly outperforms existing database search engines in the analysis of ETD spectra, and performs equally well on nontryptic peptides. MS-GFDB employs the generating function approach (MS-GF) that computes rigorous p values of peptide-spectrum matches (PSMs) based on the spectrum-specific score histogram of all peptides (16).² MS-GF p values are dependent only on the PSM (and not on the database), thus can be used as an alternative scoring function for the database search.Computing p values requires a scoring model evaluating qualities of PSMs. MS-GF adopts a probabilistic scoring model (MS-Dictionary scoring model) described in Kim et al., 2009 (17), considering multiple features including product ion types, peak intensities and mass errors. To define the parameters of this scoring model, MS-GF only needs a set of training PSMs.³ This set of PSMs can be obtained in a variety of ways: for example, one can generate CID/ETD pairs and use peptides identified by CID to form PSMs for ETD. Alternatively, one can generate spectra from a purified protein (when PSMs can be inferred from the accurate parent mass alone) or use a previously developed (not necessary optimal) tool to generate training PSMs. From these training PSMs, MS-GF automatically derives scoring parameters without assuming any prior knowledge about the specifics of a particular peptide fragmentation method (e.g. ETD, CID, etc.) and/or proteolytic origin of the peptides. MS-GF was originally designed for the analysis of CID spectra, but now it has been extended to other types of spectra generated by various fragmentation techniques and/or various enzymes. We show that MS-GF can be successfully applied to novel types of spectra (e.g. ETD of Lys-N peptides (18, 19)) by simply retraining scoring parameters without any modification. Note that although the same scoring model is used for different types of spectra, the parameters derived to score different types of spectra are dissimilar.We compared the performance of MS-GFDB with Mascot on a large ETD data set and found that it generated many more peptide identifications for the same false discovery rates (FDR). For example, at 1% peptide level FDR, MS-GFDB identified 9450 unique peptides from 81,864 ETD spectra of Lys-N peptides whereas Mascot only identified 3672 unique peptides, ≈160% increase in the number of peptide identifications (a similar improvement is observed for ETD spectra of tryptic peptides).⁴ MS-GFDB also showed a significant 28% improvement in the number of identified peptides from CID spectra of tryptic peptides (16,203 peptides as compared with 12,658 peptides identified by Mascot).The ETD technology complements rather than replaces CID because both technologies have some advantages: CID for smaller peptides with small charges, ETD for larger and multiply charged peptides (20, 21). An alternative way to utilize ETD is to use it in conjunction with CID because CID and ETD generate complementary sequence information (20, 22, 23). ETD-enabled instruments often support generating both CID and ETD spectra (CID/ETD pairs) for the same peptide. Although the CID/ETD pairs promise a great improvement in peptide identification, the full potential of such pairs has not been fully realized yet. In the case of de novo sequencing, de novo sequencing tools utilizing CID/ETD pairs indeed result in more accurate de novo peptide sequencing than traditional CID-based algorithms (23, 24, 25). However, in the case of database search, the argument that the use of CID/ETD pairs improves peptide identifications remains poorly substantiated. A few tools are developed to use CID/ETD (or CID/ECD) pairs for the database search but they are limited to preprocessing/postprocessing of the spectral data before or following running a traditional database search tool (26, 27). Nielsen et al., 2005 (22) pioneered the combined use of CID and ECD for the database search. Given a CID/ECD pair, they generated a combined spectrum comprised only of complementary pairs of peaks, and searched it with Mascot.⁵ However, this approach is hard to generalize to less accurate CID/ETD pairs generated by ion-trap instruments because there is a higher chance that the identified complementary pairs of peaks are spurious. More importantly, using traditional MS/MS tools (such as Mascot) for the database search of the combined spectrum is inappropriate, because they are not optimized for analyzing such combined spectra; a better approach would be to develop a new database search tool tailored for the combined spectrum. Recently, Molina et al., 2008 (26) studied database search of CID/ETD pairs using Spectrum Mill (Agilent Technologies, Santa Clara, CA) and came to a counterintuitive conclusion that using only CID spectra identifies 12% more unique peptides than using CID/ETD pairs. We believe that it is an acknowledgment of limitations of the traditional MS/MS database search tools for the analysis of multiple spectra generated from a single peptide.In this paper, we modify the generating function approach for interpreting CID/ETD pairs and further apply it to improve the database search with CID/ETD pairs. In contrast to previous approaches, our scoring is specially designed to interpret CID/ETD pairs and can be generalized to analyzing any type of multiple spectra generated from a single peptide. When CID/ETD pairs from trypsin digests are used, MS-GFDB identified 13% and 27% more peptides compared with the case when only CID spectra and only ETD spectra are used, respectively. The difference was even more prominent when CID/ETD pairs from Lys-N digests were used, with 41% and 33% improvement over CID only and ETD only, respectively.Assigning a p value to a PSM greatly helped researchers to evaluate the quality of peptide identifications. We now turn to the problem of assigning a p value to a peptide-spectrum-spectrum match (PS²M) when two spectra in PS²M are generated by different fragmentation technologies (e.g. ETD and CID). We argue that assigning statistical significance to a PS²M (or even PSⁿM) is a prerequisite for rigorous CID/ETD analyses. To our knowledge, MS-GFDB is the first tool to generate statistically rigorous p values of PSⁿMs.The MS-GFDB executable and source code is available at the website of Center for Computational Mass Spectrometry at UCSD (http://proteomics.ucsd.edu). It takes a set of spectra (CID, ETD, or CID/ETD pairs) and a protein database as an input and outputs peptide matches. If the input is a set of CID/ETD pairs, it outputs the best scoring peptide matches and their p values (1) using only CID spectra, (2) using only ETD spectra, and (3) using combined spectra of CID/ETD pairs.     

A Novel Spectral Annotation Strategy Streamlines Reporting of Mono-ADP-ribosylated Peptides Derived from Mouse Liver and Spleen in Response to IFN-γ

Mass-spectrometry-enabled ADP-ribosylation workflows are developing rapidly, providing researchers a variety of ADP-ribosylome enrichment strategies and mass spectrometric acquisition options. Despite the growth spurt in upstream technologies, systematic ADP-ribosyl (ADPr) peptide mass spectral annotation methods are lacking. HCD-dependent ADP-ribosylome studies are common, but the resulting MS2 spectra are complex, owing to a mixture of b/y-ions and the m/p-ion peaks representing one or more dissociation events of the ADPr moiety (m-ion) and peptide (p-ion). In particular, p-ions that dissociate further into one or more fragment ions can dominate HCD spectra but are not recognized by standard spectral annotation workflows. As a result, annotation strategies that are solely reliant upon the b/y-ions result in lower spectral scores that in turn reduce the number of reportable ADPr peptides. To improve the confidence of spectral assignments, we implemented an ADPr peptide annotation and scoring strategy. All MS2 spectra are scored for the ADPr m-ions, but once spectra are assigned as an ADPr peptide, they are further annotated and scored for the p-ions. We implemented this novel workflow to ADPr peptides enriched from the liver and spleen isolated from mice post 4 h exposure to systemic IFN-γ. HCD collision energy experiments were first performed on the Orbitrap Fusion Lumos and the Q Exactive, with notable ADPr peptide dissociation properties verified with CID (Lumos). The m-ion and p-ion series score distributions revealed that ADPr peptide dissociation properties vary markedly between instruments and within instrument collision energy settings, with consequences on ADPr peptide reporting and amino acid localization. Consequentially, we increased the number of reportable ADPr peptides by 25% (liver) and 17% (spleen) by validation and the inclusion of lower confidence ADPr peptide spectra. This systematic annotation strategy will streamline future reporting of ADPr peptides that have been sequenced using any HCD/CID-based method.     

Spectral sensitivity of photoreceptors in the compound eye of the locust

Three types of receptor with different _max of 360, 430, and 530 nm were found in the locust retina by extracellular recording. Their spectral sensitivity curves were considerably broader than the absorption curves of the corresponding pigments. Possible coefficients of electrical coupling between different receptor types in ommatidia were calculated on the basis of the spectral sensitivity curves obtained for photoreceptors, assuming that each receptor contains only one light-sensitive pigment. The resulting values resembled coefficients measured in the locust by Shaw and Lillywhite. The way in which spectral sensitivity curves spread in comparison with pigment absorption curves may thus be caused by electrical coupling between cells.Institute of Problems in Information Transmission, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 18, No. 1, pp. 69–76, January–February, 1986.     

基于数据非依赖采集的蛋白质组质谱数据解析方法研究进展

数据非依赖采集（DIA）是蛋白质组学领域近年来快速发展的质谱采集技术，其通过无偏碎裂隔离窗口内的所有母离子采集二级谱图，理论上可实现蛋白质样品的深度覆盖，同时具有高通量、高重现性和高灵敏度的优点。现有的DIA数据采集方法可以分为全窗口碎裂方法、隔离窗口序列碎裂方法和四维DIA数据采集方法（4D-DIA）3大类。针对DIA数据的不同特点，主要数据解析方法包括谱库搜索方法、蛋白质序列库直接搜索方法、伪二级谱图鉴定方法和从头测序方法4大类。解析得到的肽段鉴定结果需要进行可信度评估，包括使用机器学习方法的重排序和对报告结果集合的假发现率估计两个步骤，实现对数据解析结果的质控。本文对DIA数据的采集方法、数据解析方法及软件和鉴定结果可信度评估方法进行了整理和综述，并展望了未来的发展方向。     

High-temperature solid-phase microextraction procedure for the detection of drugs by gas chromatography–mass spectrometry

High-temperature headspace solid-phase microextraction (SPME) with simultaneous (“in situ”) derivatisation (acetylation or silylation) is a new sample preparation technique for the screening of illicit drugs in urine and for the confirmation analysis in serum by GC–MS. After extraction of urine with a small portion of an organic solvent mixture (e.g., 2 ml of hexane–ethyl acetate) at pH 9, the organic layer is separated and evaporated to dryness in a small headspace vial. A SPME-fiber (e.g., polyacrylate) doped with acetic anhydride–pyridine (for acetylation) is exposed to the vapour phase for 10 min at 200°C in a blockheater. The SPME fiber is then injected into the GC–MS for thermal desorption and analysis. After addition of perchloric acid and extraction with n-hexane to remove lipids, the serum can be analysed after adjusting to pH 9 as described for urine. Very clean extracts are obtained. The various drugs investigated could be detected and identified in urine by the total ion current technique at the following concentrations: amphetamines (200 μg/l), barbiturates (500 μg/l), benzodiazepines (100 μg/l), benzoylecgonine (150 μg/l), methadone (100 μg/l) and opiates (200 μg/l). In serum all drugs could be detected by the selected ion monitoring technique within their therapeutic range. As compared to liquid–liquid extraction only small amounts of organic solvent are needed and larger amounts of the pertinent analytes could be transferred to the GC column. In contrast to solid-phase extraction (SPE), the SPME-fiber is reusable several times (as there is no contamination by endogenous compounds). The method is time-saving and can be mechanised by the use of a dedicated autosampler.     

Assessing data quality of peptide mass spectra obtained by quadrupole ion trap mass spectrometry

An algorithm is introduced to assess spectral quality for peptide CID spectra acquired by a quadrupole ion trap mass spectrometer. The method employs a quadratic discriminant function calibrated with manually classified 'bad' and 'good' quality spectra, producing a single 'spectral quality' score. Many spectra examined that do not have significant matches are assessed to have good spectral quality, indicating that advances in search methods may yield substantial improvements in results.     

Fluorescence-Based Classification of Caribbean Coral Reef Organisms and Substrates

A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.     

基于谱图库的蛋白质鉴定策略研究进展

基于质谱的蛋白质组学快速发展,蛋白质质谱数据也呈指数式增长。寻找速度快、准确度高以及重复性好的鉴定方法是该领域的一项重要任务。谱图库搜索策略直接比较实验谱图与谱图库中的真实谱图,充分利用了谱图中的丰度、非常规碎裂模式和其他的一些特征,使得搜索更加快速和准确,成为蛋白质组学的主流鉴定方法之一。文中介绍基于谱图库的蛋白质组质谱数据鉴定策略,并针对其中两个关键步骤——谱图库构建方法和谱图库搜索方法进行深入介绍,探讨了谱图库策略的进展和挑战。     

Negative ion electrospray mass spectrometry of neoflavonoids

The electrospray ionisation mass spectra of the neoflavanoids brazilin and hematoxylin are reported in both their reduced (1 and 2, respectively) and their oxidised forms (3 and 4, respectively). In the reduced forms, breakdown pathways under collision induced decomposition (CID) conditions produce fragments characteristic of rings A and C; in their oxidised forms, the fragments are characteristic of rings B and D. The structural assignments of the fragments are substantiated by recording the spectra after deuterium exchange at the hydroxyl groups.     

Enhanced peptide identification by electron transfer dissociation using an improved Mascot Percolator

Peptide identification using tandem mass spectrometry is a core technology in proteomics. Latest generations of mass spectrometry instruments enable the use of electron transfer dissociation (ETD) to complement collision induced dissociation (CID) for peptide fragmentation. However, a critical limitation to the use of ETD has been optimal database search software. Percolator is a post-search algorithm, which uses semi-supervised machine learning to improve the rate of peptide spectrum identifications (PSMs) together with providing reliable significance measures. We have previously interfaced the Mascot search engine with Percolator and demonstrated sensitivity and specificity benefits with CID data. Here, we report recent developments in the Mascot Percolator V2.0 software including an improved feature calculator and support for a wider range of ion series. The updated software is applied to the analysis of several CID and ETD fragmented peptide data sets. This version of Mascot Percolator increases the number of CID PSMs by up to 80% and ETD PSMs by up to 60% at a 0.01 q-value (1% false discovery rate) threshold over a standard Mascot search, notably recovering PSMs from high charge state precursor ions. The greatly increased number of PSMs and peptide coverage afforded by Mascot Percolator has enabled a fuller assessment of CID/ETD complementarity to be performed. Using a data set of CID and ETcaD spectral pairs, we find that at a 1% false discovery rate, the overlap in peptide identifications by CID and ETD is 83%, which is significantly higher than that obtained using either stand-alone Mascot (69%) or OMSSA (39%). We conclude that Mascot Percolator is a highly sensitive and accurate post-search algorithm for peptide identification and allows direct comparison of peptide identifications using multiple alternative fragmentation techniques.     

Spectrum-to-spectrum searching using a proteome-wide spectral library

The unambiguous assignment of tandem mass spectra (MS/MS) to peptide sequences remains a key unsolved problem in proteomics. Spectral library search strategies have emerged as a promising alternative for peptide identification, in which MS/MS spectra are directly compared against a reference library of confidently assigned spectra. Two problems relate to library size. First, reference spectral libraries are limited to rediscovery of previously identified peptides and are not applicable to new peptides, because of their incomplete coverage of the human proteome. Second, problems arise when searching a spectral library the size of the entire human proteome. We observed that traditional dot product scoring methods do not scale well with spectral library size, showing reduction in sensitivity when library size is increased. We show that this problem can be addressed by optimizing scoring metrics for spectrum-to-spectrum searches with large spectral libraries. MS/MS spectra for the 1.3 million predicted tryptic peptides in the human proteome are simulated using a kinetic fragmentation model (MassAnalyzer version2.1) to create a proteome-wide simulated spectral library. Searches of the simulated library increase MS/MS assignments by 24% compared with Mascot, when using probabilistic and rank based scoring methods. The proteome-wide coverage of the simulated library leads to 11% increase in unique peptide assignments, compared with parallel searches of a reference spectral library. Further improvement is attained when reference spectra and simulated spectra are combined into a hybrid spectral library, yielding 52% increased MS/MS assignments compared with Mascot searches. Our study demonstrates the advantages of using probabilistic and rank based scores to improve performance of spectrum-to-spectrum search strategies.