规模化蛋白质鉴定中母离子的准确检测技术研究

蛋白质组学的基础研究之一是蛋白质鉴定.规模化的蛋白质鉴定通常采用"鸟枪法",即选择一些酶切肽段(母离子)碎裂生成二级谱图,通过二级谱图及其母离子质量鉴定肽段,再推断对应的蛋白质.在鉴定过程中,母离子质量是一个关键参数.母离子是否是肽段的单同位素峰决定了正确肽段是否能进入候选,母离子的质量精度决定了候选肽段的数目.本文从判断单同位素峰和系统误差校准这两个角度研究了母离子的准确检测技术.判断单同位素峰的技术在蛋白质上已有研究,包括电荷判断、单同位素峰判断和重叠同位素峰判断.可以借鉴蛋白质水平的技术研究母离子的单同位素峰判断方法.同时母离子的系统误差校准也有较为成熟的方法.这两个角度的研究有助于提高规模化蛋白质的鉴定率.     

Increasing information from shotgun proteomic data by accounting for misassigned precursor ion masses

Although mass spectrometers are capable of providing high mass accuracy data, assignment of true monoisotopic precursor ion mass is complicated during data-dependent ion selection for LC-MS/MS analysis of complex mixtures. The complication arises when chromatographic peak widths for a given analyte exceed the time required to acquire a precursor ion mass spectrum. The result is that many measured monoisotopic masses are misassigned due to calculation from a single mass spectrum with poor ion statistics based on only a fraction of the total available ions for a given analyte. Such data in turn produces errors in automated database searches, where precursor m/z value is one search parameter. We propose here a postacquisition approach to correct misassigned monoisotopic m/z values that involves peak detection over the entire elution profile and correction of the precursor ion monoisotopic mass. As a result of using this approach to reprocess shotgun proteomic data we increased peptide sequence assignments by 10% while reducing the estimated false positive ratio from 1 to 0.2%. We also show that 4% of the salvaged identifications may be accounted for by correction of mixed tandem mass spectra resulting from fragmentation of multiple peptides simultaneously, a situation which we refer to as accidental CID.     

Postexperiment monoisotopic mass filtering and refinement (PE-MMR) of tandem mass spectrometric data increases accuracy of peptide identification in LC/MS/MS

Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor masses that provides highly accurate analyses of massive sets of proteomics data. This method, coined "postexperiment monoisotopic mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all monoisotopic masses observed in a whole LC/MS experiment, 2) clusterization of monoisotopic masses of a peptide into unique mass classes (UMCs) based on their masses and LC elution times, 3) matching the precursor masses of the MS/MS data to a representative mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding monoisotopic masses and refinement of the precursor ion masses by the UMC mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the monoisotopic masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating massive sets of proteomics data.     

MS2‐Deisotoper: A Tool for Deisotoping High‐Resolution MS/MS Spectra in Normal and Heavy Isotope‐Labelled Samples

High‐resolution MS/MS spectra of peptides can be deisotoped to identify monoisotopic masses of peptide fragments. The use of such masses should improve protein identification rates. However, deisotoping is not universally used and its benefits have not been fully explored. Here, MS2‐Deisotoper, a tool for use prior to database search, is used to identify monoisotopic peaks in centroided MS/MS spectra. MS2‐Deisotoper works by comparing the mass and relative intensity of each peptide fragment peak to every other peak of greater mass, and by applying a set of rules concerning mass and intensity differences. After comprehensive parameter optimization, it is shown that MS2‐Deisotoper can improve the number of peptide spectrum matches (PSMs) identified by up to 8.2% and proteins by up to 2.8%. It is effective with SILAC and non‐SILAC MS/MS data. The identification of unique peptide sequences is also improved, increasing the number of human proteoforms by 3.7%. Detailed investigation of results shows that deisotoping increases Mascot ion scores, improves FDR estimation for PSMs, and leads to greater protein sequence coverage. At a peptide level, it is found that the efficacy of deisotoping is affected by peptide mass and charge. MS2‐Deisotoper can be used via a user interface or as a command‐line tool.     

Analysis of MALDI-TOF mass spectrometry data for discovery of peptide and glycan biomarkers of hepatocellular carcinoma

This paper presents computational methods to analyze MALDI-TOF mass spectrometry data for quantitative comparison of peptides and glycans in serum. The methods are applied to identify candidate biomarkers in serum samples of 203 participants from Egypt; 73 hepatocellular carcinoma (HCC) cases, 52 patients with chronic liver disease (CLD) consisting of cirrhosis and fibrosis cases, and 78 population controls. Two complementary sample preparation methods were applied prior to generating mass spectra: (1) low molecular weight (LMW) enrichment of each serum sample was carried out for MALDI-TOF quantification of peptides, and (2) glycans were enzymatically released from proteins in each serum sample and permethylated for MALDI-TOF quantification of glycans. A peak selection algorithm was applied to identify the most useful peptide and glycan peaks for accurate detection of HCC cases from high-risk population of patients with CLD. In addition to global peaks selected by the whole population based approach, where identically labeled patients are treated as a single group, subgroup-specific peaks were identified by searching for peaks that are differentially abundant in a subgroup of patients only. The peak selection process was preceded by peak screening, where we eliminated peaks that have significant association with covariates such as age, gender, and viral infection based on the peptide and glycan spectra from population controls. The performance of the selected peptide and glycan peaks was evaluated in terms of their ability in detecting HCC cases from patients with CLD in a blinded validation set and through the cross-validation method. Finally, we investigated the possibility of using both peptides and glycans in a panel to enhance the diagnostic capability of these candidate markers. Further evaluation is needed to examine the potential clinical utility of the candidate peptide and glycan markers identified in this study.     

Extraction method for analysis of detergent-solubilized bacteriorhodopsin and hydrophobic peptides by electrospray ionization mass spectrometry

The analysis of integral membrane proteins or transmembrane peptides by electrospray ionization mass spectrometry (ESI-MS) is difficult since detergents, used to solubilize these hydrophobic proteins and peptides, severely suppress analyte ion formation. This problem has been addressed previously by precipitating the protein, removing the detergent, and resolubilizing the protein in a nonpolar solvent. Here, we demonstrate a method that avoids protein precipitation and resolubilization. Detergent-solubilized bacteriorhodopsin is extracted into a nonpolar solvent phase by adding a chloroform/methanol/water solvent mixture to the aqueous detergent solution. ESI mass spectra of the nonpolar, chloroform-rich phase were dominated by peaks due to bacterioopsin. Bacterioopsin precursors with partially cleaved leader sequences were seen in all mass spectra. Additional peaks were likely due to intact bacteriorhodopsin, i.e., bacterioopsin with the retinal prosthetic group attached, and to bacterioopsin associated with lipid molecules. A separation process that occurred in the fused-silica capillary leading to the electrospray tip was essential for obtaining ESI mass spectra of bacterioopsin. The extraction-into-chloroform procedure also worked well with hydrophobic, transmembrane-type peptides that were insoluble in other electrospray solvents, including 100% formic acid, and the method has application to transmembrane peptides formed from digests of integral membrane proteins.     

Preprocessing of tandem mass spectrometric data based on decision tree classification

In this study, we present a preprocessing method for quadrupole time-of-flight （Q-TOF） tandem mass spectra to increase the accuracy of database searching for peptide （protein） identification. Based on the natural isotopic information inherent in tandem mass spectra, we construct a decision tree after feature selection to classify the noise and ion peaks in tandem spectra. Furthermore, we recognize overlapping peaks to find the monoisotopic masses of ions for the following identification process. The experimental results show that this preprocessing method increases the search speed and the reliability of peptide identification.     

Detection and identification of protein isoforms using cluster analysis of MALDI-MS mass spectra

We describe an approach to screen large sets of MALDI-MS mass spectra for protein isoforms separated on two-dimensional electrophoresis gels. Mass spectra are matched against each other by utilizing extracted peak mass lists and hierarchical clustering. The output is presented as dendrograms in which protein isoforms cluster together. Clustering could be applied to mass spectra from different sample sets, dates, and instruments, revealed similarities between mass spectra, and was a useful tool to highlight peptide peaks of interest for further investigation. Shared peak masses in a cluster could be identified and were used to create novel peak mass lists suitable for protein identification using peptide mass fingerprinting. Complex mass spectra consisting of more than one protein were deconvoluted using information from other mass spectra in the same cluster. The number of peptide peaks shared between mass spectra in a cluster was typically found to be larger than the number of peaks that matched to calculated peak masses in databases, thus modified peaks are probably among the shared peptides. Clustering increased the number of peaks associated with a given protein.     

An adaptive approach to denoising tandem mass spectra

In our recent work on denoising, a linear combination of five features was used to adjust the peak intensities in tandem mass spectra. Although the method showed a promise, the coefficients (weights) of the linear combination were fixed and determined empirically. In this paper, we proposed an adaptive approach for estimating these weights. The proposed approach: (i) calculates the score for each peak in a data set with the previous empirically determined weights, (ii) selects the training data set based on the scores of peaks, (iii) applies the linear discriminant analysis to the training data set and takes the solution of linear discriminant analysis as the new weights, (iv) calculates the score again with the new weights, (v) repeats (ii)-(iv) until the weights have no significant change. After getting the final weights, the proposed approach follows the previous methods. The proposed approach was applied to two tandem mass spectra data sets: ISB (with low resolution) and TOV-Q (with high resolution) to evaluate its performance. The results show that about 66% of peaks (likely noise peaks) can be removed and that the number of peptides identified by MASCOT increases by 14 and 23.4% for ISB and TOV-Q data set, respectively, compared to the previous work.     

Brain endopeptidase generates enkephalin from striatal precursors

An enzyme capable of converting putative opioid peptide intermediates to free enkephalin has been purified 300-fold from washed rat brain membranes. The action of this enzyme, an enkephalin-generating endopeptidase (EGE), was compared with the action of carboxypeptidase B after trypsin treatment on enkephalin precursor peptides present in rat striata. After Sephadex G-100 gel filtration of striatal material, fractions were radioimmunoassayed for enkephalin content using an antiserum specific for the carboxyl terminal of enkephalin. Additionally, aliquots of the column fractions were treated with either trypsin and carboxypeptidase B, trypsin and EGE, or EGE alone. The peak of enkephalin immunoreactivity increased with the enzymes' treatment indicating the conversion of the low molecular weight proenkephalin precursor peptides to enkephalin. Trypsin and EGE generated almost as much enkephalin as trypsin and carboxypeptidase B in the conditions of the experiment. Thus EGE is capable of processing precursors to enkephalin after the action of trypsin-like enzyme(s) in the brain. The gel filtration fractions containing enkephalin and its low molecular weight precursors were pooled and one-half treated with EGE. The contents were analyzed by HPLC and the increase in immunoreactivity co-eluted with enkephalin and Leu-enkephalin. Small peptides found to be the most potent competitive inhibitors of this enzyme are Met-Arg-Phe-Ala, and Met-Arg-Phe.     

Two new 4-Cys conotoxins (framework 14) of the vermivorous snail Conus austini from the Gulf of Mexico with activity in the central nervous system of mice

As part of continuing studies of the venom components present in Conus austini (syn.: Conus cancellatus), a vermivorous cone snail collected in the western Gulf of Mexico, Mexico, two major peptides, as14a and as14b, were purified and characterized. Their amino acid sequences were determined by automatic Edman sequencing after reduction and alkylation. Their molecular masses, established by matrix-assisted laser desorption ionization time-of-flight mass spectrometry, confirmed the chemical analyses and indicated that as14a and as14b have free C-termini. Each peptide contains 4-Cys residues arranged in a pattern (C-C-C-C, framework 14). The primary structure of as14a is GGVGRCIYNCMNSGGGLNFIQCKTMCY (experimental monoisotopic mass 2883.92Da; calculated monoisotopic mass 2884.20Da), whereas that of as14b is RWDVDQCIYYCLNGVVGYSYTECQTMCT (experimental monoisotopic mass 3308.63Da; calculated monoisotopic mass 3308.34Da). Both purified peptides elicited scratching and grooming activity in mice, and as14b also caused body and rear limb extension and tail curling immediately upon injection. The high sequence similarity of peptide as14a with peptide vil14a from the vermivorous C. villepinii suggests that the former might block K+ channels.     

Mutation-tolerant protein identification by mass spectrometry.

Database search in tandem mass spectrometry is a powerful tool for protein identification. High-throughput spectral acquisition raises the problem of dealing with genetic variation and peptide modifications within a population of related proteins. A method that cross-correlates and clusters related spectra in large collections of uncharacterized spectra (i.e., from normal and diseased individuals) would be very valuable in functional proteomics. This problem is far from being simple since very similar peptides may have very different spectra. We introduce a new notion of spectral similarity that allows one to identify related spectra even if the corresponding peptides have multiple modifications/mutations. Based on this notion, we developed a new algorithm for mutation-tolerant database search as well as a method for cross-correlating related uncharacterized spectra.     

Modification of amyloid-beta(1-40) by a protease inhibitor creates risk of error in mass spectrometric quantitation of amyloid-beta(1-42)

Matrix-assisted laser desorption mass spectrometry successfully analyzes mixed populations of amyloid-β (Aβ) peptides, providing a profile in which changes caused by drug action are directly observed. A spectrum of Aβ immunocaptured from guinea pig brain included a novel component with monoisotopic [M + H]⁺ at 4511.22, close to the monoisotopic value of [M + H]⁺ for Aβ(1-42) of 4512.27 and overlapping and interfering with the authentic Aβ(1-42) peak. Hypothesis and experiment led to the conclusion that modification of Aβ(1-40) by the protease inhibitor aminoethylbenzenesulfonyl fluoride generates a product with monoisotopic [M + H]⁺ at 4511.19, and that this accounts for the interfering peak.     

Signal detection in high-resolution mass spectrometry data

Mass spectrometry data from high-resolution time-of-flight instruments often contain a vast number of noninformative background-ion peaks whose signal is similar to that of peptide peaks. Consequently, seeking peptide signal in these spectra based on a signal-to-noise ratio will remove signal peaks as well as noise. This work characterizes the background as a precursor to seeking peptide-related features. Robust-regression methods are used to estimate distributions for null (background) peak intensities and locations. Defining signal peaks as outliers with respect to these distributions leads to more precision in detecting the isotopic envelope of peaks from low-abundance peptides in high-resolution spectra.     

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptide's parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.     

Mass Spectrometric Amino Acid Sequencing of Short and Mid-Sized Peptides in a ESI-O-TOF System as an Alternative to MS/MS: I. Selective Fragmentation of Peptides with <Emphasis Type="Italic">y</Emphasis>-Ion Formation

The possibility of mass spectrometric sequencing of peptides without the need for the conventional MS/MS analysis has been demonstrated experimentally. The peptide hydrolysate was fractionated by reversephase chromatography on a microbore column. The eluate fraction was injected into the mass spectrometer via an electrospray ion source that directly coupled a liquid chromatography instrument to a time-of-flight mass spectrometer (HPLC-MS). Fragmentation of the peptides eluted from the column was performed in the mass spectrometer interface by varying the voltage difference between the mass spectrometer nozzle and skimmer. A restricted set of intensive peaks of y-ions, which corresponded to sequential cleavage of all amino acids from the peptide, was obtained. The ratios of the y-ion peak intensities to the background were (5?100)/1. The presence of Lys and Arg in the peptides provided for a substantial increase of informative peak intensity in the mass spectra. The mass spectra of short peptides (up to 10 residues) were processed manually, whereas the Proteos hardware and software system was used to process the fragmentation results for a long N-terminal peptide of the human hemoglobin α-chain.     

A suffix tree approach to the interpretation of tandem mass spectra: applications to peptides of non-specific digestion and post-translational modifications

MOTIVATION: Tandem mass spectrometry combined with sequence database searching is one of the most powerful tools for protein identification. As thousands of spectra are generated by a mass spectrometer in one hour, the speed of database searching is critical, especially when searching against a large sequence database, or when the peptide is generated by some unknown or non-specific enzyme, even or when the target peptides have post-translational modifications (PTM). In practice, about 70-90% of the spectra have no match in the database. Many believe that a significant portion of them are due to peptides of non-specific digestions by unknown enzymes or amino acid modifications. In another case, scientists may choose to use some non-specific enzymes such as pepsin or thermolysin for proteolysis in proteomic study, in that not all proteins are amenable to be digested by some site-specific enzymes, and furthermore many digested peptides may not fall within the rang of molecular weight suitable for mass spectrometry analysis. Interpreting mass spectra of these kinds will cost a lot of computational time of database search engines. OVERVIEW: The present study was designed to speed up the database searching process for both cases. More specifically speaking, we employed an approach combining suffix tree data structure and spectrum graph. The suffix tree is used to preprocess the protein sequence database, while the spectrum graph is used to preprocess the tandem mass spectrum. We then search the suffix tree against the spectrum graph for candidate peptides. We design an efficient algorithm to compute a matching threshold with some statistical significance level, e.g. p = 0.01, for each spectrum, and use it to select candidate peptides. Then we rank these peptides using a SEQUEST-like scoring function. The algorithms were implemented and tested on experimental data. For post-translational modifications, we allow arbitrary number of any modification to a protein. AVAILABILITY: The executable program and other supplementary materials are available online at: http://hto-c.usc.edu:8000/msms/suffix/.     

Data extraction from proteomics raw data: an evaluation of nine tandem MS tools using a large Orbitrap data set

In shot-gun proteomics raw tandem MS data are processed with extraction tools to produce condensed peak lists that can be uploaded to database search engines. Many extraction tools are available but to our knowledge, a systematic comparison of such tools has not yet been carried out. Using raw data containing more than 400,000 tandem MS spectra acquired using an Orbitrap Velos we compared 9 tandem MS extraction tools, freely available as well as commercial. We compared the tools with respect to number of extracted MS/MS events, fragment ion information, number of matches, precursor mass accuracies and agreement in-between tools. Processing a primary data set with 9 different tandem MS extraction tools resulted in a low overlap of identified peptides. The tools differ by assigned charge states of precursors, precursor and fragment ion masses, and we show that peptides identified very confidently using one extraction tool might not be matched when using another tool. We also found a bias towards peptides of lower charge state when extracting fragment ion data from higher resolution raw data without deconvolution. Collecting and comparing the extracted data from the same raw data allow adjusting parameters and expectations and selecting the right tool for extraction of tandem MS data.     

Identification of <Emphasis Type="BoldItalic">b</Emphasis>-/<Emphasis Type="BoldItalic">y</Emphasis>-ions in MS/MS spectra using a two stage neural network

Independent of the approach used, the ability to correctly interpret tandem MS data depends on the quality of the original spectra. Even in the case of the highest quality spectra, the majority of spectral peaks can not be reliably interpreted. The accuracy of sequencing algorithms can be improved by filtering out such 'noise' peaks. Preprocessing MS/MS spectra to select informative ion peaks increases accuracy and reduces the processing time. Intuitively, the mix of informative versus non-informative peaks has a direct effect on the quality and size of the resulting candidate peptide search space. As the number of selected peaks increases, the corresponding search space increases exponentially. If we select too few peaks then the ion-ladder interpretation of the spectrum will contain gaps that can only be explained by permutations of combinations of amino acids. This will result in a larger candidate peptide search space and poorer quality candidates. The dependency that peptide sequencing accuracy has on an initial peak selection regime makes this preprocessing step a crucial facet of any approach, whether de novo or not, to MS/MS spectra interpretation.We have developed a novel approach to address this problem. Our approach uses a staged neural network to model ion fragmentation patterns and estimate the posterior probability of each ion type. Our method improves upon other preprocessing techniques and shows a significant reduction in the search space for candidate peptides without sacrificing candidate peptide quality.     

On the relevance of peptide sequence permutations in shotgun proteomics studies

In collision-induced dissociation (CID) of peptides, it has been observed that rearrangement processes can take place that appear to permute/scramble the original primary structure, which may in principle adversely affect peptide identification. Here, an analysis of sequence permutation in tandem mass spectra is presented for a previously published proteomics study on P. aeruginosa (Scherl et al., J. Am. Soc. Mass Spectrom.2008, 19, 891) conducted using an LTQ-orbitrap. Overall, 4878 precursor ions are matched by considering the accurate mass (i.e., <5 ppm) of the precursor ion and at least one fragment ion that confirms the sequence. The peptides are then grouped into higher- and lower-confidence data sets, using five fragment ions as a cutoff for higher-confidence identification. It is shown that the propensity for sequence permutation increases with the length of the tryptic peptide in both data sets. A higher charge state (i.e., 3+ vs 2+) also appears to correlate with a higher appearance of permuted masses for larger peptides. The ratio of these permuted sequence ions, compared to all tandem mass spectral peaks, reaches ～25% in the higher-confidence data set, compared to an estimated incidence of false positives for permuted masses (maximum ～8%), based on a null-hypothesis decoy data set.