Unmatched masses in peptide mass fingerprints caused by cross-contamination: an updated statistical result

Unmatched masses are often observed in the experimental peptide mass spectra when database searching is performed with the ProFound program. Comparison between theoretical and experimental mass spectra of standard proteins shows that contamination accounts for most of the unmatched masses. In this retrospective analysis, the top 100 most probable contaminating masses, as listed in order of their probability, are statistically filtered out from 118 different experimental peptide mass fingerprinting (PMF) maps. Most of the interfering masses originate from trypsin autolysis and human keratins. Subtraction of known contaminants from raw data and using cleaner masses for searching can enhance protein identification by PMF.     

Artifacts and unassigned masses encountered in peptide mass mapping

In peptide mass mapping of isolated proteins, a significant number of the observed mass spectral peaks are often uninterpreted. These peaks derive from a number of sources: errors in the genome that give rise to incorrect peptide mass predictions, undocumented post-translational modifications, sample handling-induced modifications, contaminants in the sample, non-standard protein cleavage sites, and non-protein components of the sample. In a study of the stalk organelle of Caulobacter crescentus, roughly one-third (782/2215) of all observed masses could not be assigned to the proteins identified in the gel spots (Karty et al., J. Proteome Res., 1 (2002) 325). By interpreting these masses, this work illuminates a number of phenomena that may arise in the course of peptide mass mapping of electrophoretically separated proteins and presents results from a number of related studies.     

Peptide mass fingerprinting peak intensity prediction: extracting knowledge from spectra

Matrix-assisted laser desorption/ionization-time of flight mass spectrometry has become a valuable tool in proteomics. With the increasing acquisition rate of mass spectrometers, one of the major issues is the development of accurate, efficient and automatic peptide mass fingerprinting (PMF) identification tools. Current tools are mostly based on counting the number of experimental peptide masses matching with theoretical masses. Almost all of them use additional criteria such as isoelectric point, molecular weight, PTMs, taxonomy or enzymatic cleavage rules to enhance prediction performance. However, these identification tools seldom use peak intensities as parameter as there is currently no model predicting the intensities based on the physicochemical properties of peptides. In this work, we used standard datamining methods such as classification and regression methods to find correlations between peak intensities and the properties of the peptides composing a PMF spectrum. These methods were applied on a dataset comprising a series of PMF experiments involving 157 proteins. We found that the C4.5 method gave the more informative results for the classification task (prediction of the presence or absence of a peptide in a spectra) and M5' for the regression methods (prediction of the normalized intensity of a peptide peak). The C4.5 result correctly classified 88% of the theoretical peaks; whereas the M5' peak intensities had a correlation coefficient of 0.6743 with the experimental peak intensities. These methods enabled us to obtain decision and model trees that can be directly used for prediction and identification of PMF results. The work performed permitted to lay the foundations of a method to analyze factors influencing the peak intensity of PMF spectra. A simple extension of this analysis could lead to improve the accuracy of the results by using a larger dataset. Additional peptide characteristics or even PMF experimental parameters can also be taken into account in the datamining process to analyze their influence on the peak intensity. Furthermore, this datamining approach can certainly be extended to the tandem mass spectrometry domain or other mass spectrometry derived methods.     

Peptide mass fingerprinting

Peptide mass fingerprinting by MALDI-MS and sequencing by tandem mass spectrometry have evolved into the major methods for identification of proteins following separation by two-dimensional gel electrophoresis, SDS-PAGE or liquid chromatography. One main technological goal of proteome analyses beside high sensitivity and automation was the comprehensive analysis of proteins. Therefore, the protein species level with the essential information on co- and post-translational modifications must be achieved. The power of peptide mass fingerprinting for protein identification was described here, as exemplified by the identification of protein species with high molecular masses (spectrin alpha and beta), low molecular masses (elongation factor EF-TU fragments), splice variants (alpha A crystallin), aggregates with disulfide bridges (alkylhydroperoxide reductase), and phosphorylated proteins (heat shock protein 27). Helpful tools for these analyses were the use of the minimal protein identifier concept and the software program MS-Screener to remove mass peaks assignable to contaminants and neighbor spots.     

Computational prediction of structure, substrate binding mode, mechanism, and rate for a malaria protease with a novel type of active site

The histo-aspartic protease (HAP) from the malaria parasite P. falciparum is one of several new promising targets for drug intervention. The enzyme possesses a novel type of active site, but its 3D structure and mechanism of action are still unknown. Here we use a combination of homology modeling, automated docking searches, and molecular dynamics/reaction free energy profile simulations to predict the enzyme structure, conformation of bound substrate, catalytic mechanism, and rate of the peptide cleavage reaction. We find that the computational tools are sufficiently reliable both for identifying substrate binding modes and for distinguishing between different possible reaction mechanisms. It is found that the favored pathway only involves direct participation by the catalytic aspartate, with the neighboring histidine providing critical stabilization (by a factor of approximately 10000) along the reaction. The calculated catalytic rate constant of about 0.1 s(-1) for a hexapeptide substrate derived from the alpha chain of human hemoglobin is in excellent agreement with experimental kinetic data for a similar peptide fragment.     

Interpreting peptide mass spectra by VEMS

Most existing Mass Spectra (MS) analysis programs are automatic and provide limited opportunity for editing during the interpretation. Furthermore, they rely entirely on publicly available databases for interpretation. VEMS (Virtual Expert Mass Spectrometrist) is a program for interactive analysis of peptide MS/MS spectra imported in text file format. Peaks are annotated, the monoisotopic peaks retained, and the b-and y-ion series identified in an interactive manner. The called peptide sequence is searched against a local protein database for sequence identity and peptide mass. The report compares the calculated and the experimental mass spectrum of the called peptide. The program package includes four accessory programs. VEMStrans creates protein databases in FASTA format from EST or cDNA sequence files. VEMSdata creates a virtual peptide database from FASTA files. VEMSdist displays the distribution of masses up to 5000 Da. VEMSmaldi searches singly charged peptide masses against the local database.     

Effects of neighboring sequence environment in predicting cleavage sites of signal peptides

Signal peptide has a pivotal role in the translocation of secretory protein. Some models have been designed to predict its cleavage site. It is reported that the cleavage site has relationship with the neighboring sequence environment, i.e., hydrophobic core h-region, and the specific patterns in c-region. In some studies, this finding does facilitate the prediction of cleavage site. However, in these models, sequence environment information is merely taken account of as model inputs and no detailed investigation into its effect on the prediction of cleavage site has been made. In this work, we analyze the constraint on cleave site placed by the hydrophobic core of signal peptide and then use it to improve the performance of the signal peptide cleavage site prediction. Our model is designed as follows: firstly, a sliding window is used to scan sample and artificial neural network (ANN) is employed to give cleavage site/non-cleavage site scores. Then, based on an estimated hydrophobic h-region a correcting function is proposed to improve the prediction result, in which the sequence environment is taken into account. A trend of cleavage site is indicated by our analysis for each position, which is consistent with experimental findings. Through this correcting step, the improvement of prediction accuracy is over 7%. It therefore demonstrates the neighboring sequence environment is helpful for determination of cleavage site. Program written in Matlab can be downloaded from http://www.scucic.cn/combined model/source code.html.     

Rearrangement of terminal amino acid residues in peptides by protease-catalyzed intramolecular transpeptidation

Protease-catalyzed rearrangements of amino acid residues in peptides are observed during enzymatic digestion of proteins. When two enzyme-specific cleavage sites are within one or two residues of each other in the protein sequence, only one of the two sites usually is hydrolyzed by the protease, resulting in a peptide that contains an extra cleavage site near one of its termini. It is observed that in this type of peptide, the residues between the two cleavage sites often rearrange from one terminus of the peptide to the other terminus, catalyzed by the protease that created the peptide. It is proposed that the rearrangement is caused by protease-catalyzed intramolecular transpeptidation through a cyclic peptide intermediate. Several cases of this type of rearrangement were observed for different peptides generated by different proteases, indicating that this type of rearrangement is a general phenomenon occurring during enzymatic digestion of proteins.     

Determination of the disulfide structure of sillucin, a highly knotted, cysteine-rich peptide, by cyanylation/cleavage mass mapping

The disulfide structure of sillucin, a highly knotted, cysteine-rich, antimicrobial peptide, isolated from Rhizomucor pusillus, has been determined to be Cys2--Cys7, Cys12--Cys24, Cys13--Cys30, and Cys14--Cys21 by disulfide mass mapping based on partial reduction and CN-induced cleavage enabled by cyanylation. The denatured 30-residue peptide was subjected to partial reduction by tris(2-carboxyethyl)phosphine hydrochloride at pH 3 to produce a mixture of partially reduced sillucin species; the nascent sulfhydryl groups were immediately cyanylated by 1-cyano-4-(dimethylamino)pyridinium tetrafluoroborate. The cyanylated species, separated and collected during reversed phase high-performance liquid chromatography, were treated with aqueous ammonia, which cleaved the peptide chain on the N-terminal side of cyanylated cysteine residues. The CN-induced cleavage mixture was analyzed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry before and after complete reduction of residual disulfide bonds in partially reduced and cyanylated species to mass map the truncated peptides to the sequence. Because the masses of the CN-induced cleavage fragments of both singly and doubly reduced and cyanylated sillucin are related to the linkages of the disulfide bonds in the original molecule, the presence of certain truncated peptide(s) can be used to positively identify the linkage of a specific disulfide bond or exclude the presence of other possible linkages.     

Variable context Markov chains for HIV protease cleavage site prediction

Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.     

Prediction of neuropeptide prohormone cleavages with application to RFamides

Genomic information is becoming available for an ever-wider range of animals with the genes for several well-characterized peptide families, such as the RFamides, detected in a surprisingly diverse set of these animals. While bioinformatic tools allow the prediction of the RFamide-related prohormones from genetic information, it is more difficult to accurately predict the final processed peptides because of the large number of processing steps required to convert a prohormone into mature bioactive peptides. Several statistical-based methods for predicting basic site cleavages in prohormones are described, and their ability to predict the basic site cleavages in a variety of RFamide-related peptides from vertebrates and invertebrates is reported. Specifically, the cleavages in the invertebrate FMRFamides, and the vertebrate NPFFa, RFRPa, and PrRPa peptide families are modeled. The three models compared here are based on known cleavage motifs, a logistic regression, and artificial neural networks. Improvements in the accuracy and precision of the cleavage estimates will lead to increased utilization of these models for predicting bioactive neuropeptides before experimental verification is available.     

Characterization of disulfide bond position in proteins and sequence analysis of cystine-bridged peptides by tandem mass spectrometry.

Tandem mass spectrometry employing high-energy, collisionally activated dissociation (CAD) is shown to be a useful method for sequencing through the cystine bridge of intermolecularly disulfide-bonded peptides. A characteristic triplet of intense fragment ions is observed corresponding to cleavage through and to either side of the disulfide bridge. These fragments define the masses of the linked peptides. Fragments due to peptide chain cleavage are also observed at lower abundance in the product-ion spectra and can be sufficient to sequence both of the disulfide-linked peptides without any prior knowledge of the peptide or protein sequence. Even in cases where the peptide sequence-related product-ion yields are poor, the intensities of the disulfide cleavage ions are usually sufficient to determine the molecular weights of the component cystine-bridged peptides. In this paper we demonstrate that the high-energy CAD tandem MS approach may be used to characterize disulfide-bonded peptides directly in complex enzymatic or chemical digests of native proteins. This obviates the need for individual purification of intermolecularly disulfide-linked peptides prior to analysis. The techniques are illustrated here for synthetic, inter- and intramolecularly disulfide-linked peptides and for human transforming growth factor-alpha (des-Val-Val-TGF-alpha), a compact protein containing 48 residues and three disulfides.     

Characterizing Protease Specificity: How Many Substrates Do We Need?

Calculation of cleavage entropies allows to quantify, map and compare protease substrate specificity by an information entropy based approach. The metric intrinsically depends on the number of experimentally determined substrates (data points). Thus a statistical analysis of its numerical stability is crucial to estimate the systematic error made by estimating specificity based on a limited number of substrates. In this contribution, we show the mathematical basis for estimating the uncertainty in cleavage entropies. Sets of cleavage entropies are calculated using experimental cleavage data and modeled extreme cases. By analyzing the underlying mathematics and applying statistical tools, a linear dependence of the metric in respect to 1/n was found. This allows us to extrapolate the values to an infinite number of samples and to estimate the errors. Analyzing the errors, a minimum number of 30 substrates was found to be necessary to characterize substrate specificity, in terms of amino acid variability, for a protease (S4-S4’) with an uncertainty of 5 percent. Therefore, we encourage experimental researchers in the protease field to record specificity profiles of novel proteases aiming to identify at least 30 peptide substrates of maximum sequence diversity. We expect a full characterization of protease specificity helpful to rationalize biological functions of proteases and to assist rational drug design.     

Mineral oil-, glycerol-, and Vaseline-coated plates as matrix-assisted laser desorption/ionization sample supports for high-throughput peptide analysis

A novel protocol for rapid and high-quality sample preparation prior to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been developed by coating bare stainless steel plates with one of three adhesives: mineral oil, glycerol, or Vaseline. The advantages of these three adhesive coats are that they take little time to both prepare and wipe away, hold the matrices to prevent them from flying from the support, reduce the background matrix, and affect neither the resolution of the peptide peaks nor the accuracy of their determined molecular masses. Consequently, the signal intensity, detection limit, and tolerance of the analytes to contaminants on the three adhesive-coated plates are improved. In the two strategies of on-plate desalting and concentration of the peptide mixture, all three adhesives reduced the loss of peptides, especially in the case of larger molecular mass peptides. The microscope and stereomicroscope images of the deposited droplets showed that after dropping onto the adhesive coats, the droplets formed a reduced spot size, were more homogeneous, and showed sticky crystallization. Therefore, this is an easy-to-use, reproducible, highly sensitive, tolerant (to salts), and high-throughput method of peptide sample preparation for MALDI-TOF MS analysis.     

Multi-spectra peptide sequencing and its applications to multistage mass spectrometry

Despite a recent surge of interest in database-independent peptide identifications, accurate de novo peptide sequencing remains an elusive goal. While the recently introduced spectral network approach resulted in accurate peptide sequencing in low-complexity samples, its success depends on the chance of presence of spectra from overlapping peptides. On the other hand, while multistage mass spectrometry (collecting multiple MS 3 spectra from each MS 2 spectrum) can be applied to all spectra in a complex sample, there are currently no software tools for de novo peptide sequencing by multistage mass spectrometry. We describe a rigorous probabilistic framework for analyzing spectra of overlapping peptides and show how to apply it for multistage mass spectrometry. Our software results in both accurate de novo peptide sequencing from multistage mass spectra (despite the inferior quality of MS 3 spectra) and improved interpretation of spectral networks. We further study the problem of de novo peptide sequencing with accurate parent mass (but inaccurate fragment masses), the protocol that may soon become the dominant mode of spectral acquisition. Most existing peptide sequencing algorithms (based on the spectrum graph approach) do not track the accurate parent mass and are thus not equipped for solving this problem. We describe a de novo peptide sequencing algorithm aimed at this experimental protocol and show that it improves the sequencing accuracy on both tandem and multistage mass spectrometry.     

Gaining knowledge from previously unexplained spectra-application of the PTM-Explorer software to detect PTM in HUPO BPP MS/MS data

A novel software tool named PTM-Explorer has been applied to LC-MS/MS datasets acquired within the Human Proteome Organisation (HUPO) Brain Proteome Project (BPP). PTM-Explorer enables automatic identification of peptide MS/MS spectra that were not explained in typical sequence database searches. The main focus was detection of PTMs, but PTM-Explorer detects also unspecific peptide cleavage, mass measurement errors, experimental modifications, amino acid substitutions, transpeptidation products and unknown mass shifts. To avoid a combinatorial problem the search is restricted to a set of selected protein sequences, which stem from previous protein identifications using a common sequence database search. Prior to application to the HUPO BPP data, PTM-Explorer was evaluated on excellently manually characterized and evaluated LC-MS/MS data sets from Alpha-A-Crystallin gel spots obtained from mouse eye lens. Besides various PTMs including phosphorylation, a wealth of experimental modifications and unspecific cleavage products were successfully detected, completing the primary structure information of the measured proteins. Our results indicate that a large amount of MS/MS spectra that currently remain unidentified in standard database searches contain valuable information that can only be elucidated using suitable software tools.     

Utility of mass spectrometry for proteome ana lysis: part I. Conceptual and experimental approaches

This article is the first in a series of reviews intended as a tutorial providing the inexperienced, as well as the experienced, reader with an overview of principles of peptide and protein fragmentation in mass spectrometers for protein identification, surveying of the different types of instrument configurations and their combinations for protein identification. The first mass spectrometer was developed in 1899, but it took almost a century for the instrument to become a routine analytical method in proteomic research when fast atom bombardment ionization was developed, followed shortly by soft desorption/ionization methods, such as MALDI and electrospray ionization, to volatize biomolecules with masses of tens of kiloDaltons into the gas phase under vacuum pressure without destroying them. Thereafter, other soft ionization techniques that offered ambient conditions were also introduced, such as atmospheric pressure MALDI, direct analysis in real time, atmospheric-pressure solid analysis probe and hybrid ionization, sources of MALDI and electrospray ionization (e.g., two-step fused droplet electrospray ionization, laser desorption atmospheric-pressure chemical ionization, electrosonic spray ionization, desorption electrospray ionization, and electrospray-assisted laser desorption/ionization). The five basic types of mass analyzers currently used in proteomic research are the quadrupole, ion trap, orbitrap, Fourier transform ion cyclotron resonance and TOF instruments, which differ in how they determine the mass-to-charge ratios of the peptides. They have very different design and performance characteristics. These analyzers can be stand alone or, in some cases, put together in tandem or in conjunction with ion mobility mass spectrometry to take advantage of the strengths of each. Several singly or multiply charged fragment ion types, such as b, y, a, c, z, v, y and immonium ions are produced in the gas phase of the spectrometer. In the bottom-up sequencing approach for protein identification in a shotgun proteomic experiment, proteolytic digestion of proteins is accomplished by cleavage of the different bonds along the peptide backbone and/or side chain through a charge-directed transfer to the vicinity of the cleavage side. These various mass spectrometers and the types of ions produced have become important analytical tools for studying and analyzing proteins, peptides and amino acids.     

Expression of recombinant hybrid peptide hinnavin II/α-melanocyte-stimulating hormone in <Emphasis Type="Italic">Escherichia coli</Emphasis>: Purification and characterization

The increasing problem of antibiotic resistance among pathogenic bacteria requires novel strategies for the construction of multiple, joined genes of antimicrobial agents. The strategy used in this study involved synthesis of a cDNA-encoding hinnavin II/α-melanocyte-stimulating hormone (hin/MSH) hybrid peptide, which was cloned into the pET32a (+) vector to allow expression of the hybrid peptide as a fusion protein in Escherichia coli BL21 (DE3). The resulting expression of fusion protein Trx-hin/MSH could reach up to 20% of the total cell proteins. More than 50% of the target protein was in a soluble form. The target fusion protein from the soluble fraction, Trx-hin/MSH, was easily purified by Ni²⁺-chelating chromatography. Then, enterokinase cleavage effectively cleaved the Trx-hin/MSH to release the recombinant hin/MSH (rhin/MSH) hybrid peptide. After removing the contaminants, we purified the recombinant hybrid peptide to homogeneity by reversed-phase FPLC and obtained 210 mg of pure, active rhin/MSH from 800 ml of culture medium. Antimicrobial activity assay demonstrated that rhin/MSH had a broader spectrum of activity than did the parental hinnavin II or MSH against fungi and Gram-positive and Gram-negative bacteria. These results suggest an efficient method for producing high-level expression of various kinds of antimicrobial peptides that are toxic to the host, a reliable and simple method for producing different hybrid peptides for biological studies.     

Studies on cleavage of DNA by N-phosphoryl branched peptides

It was found that Nalpha,Nepsilon-di[N-(O,O-diisopropyl)phosphoryl-L-leucy]-L-lysyl-methyl ester (1) and Nalpha,Nepsilon-di[N-(O,O-diisopropyl)phosphoryl-L-phenylalanyl]-L-lysyl-methyl ester (2) could cleave supercoiled DNA such as PUC19 efficiently in 40 mM Britton-Robinson buffer. The cleavage activities for both were investigated by agarose gel electrophoresis. The T4 ligase experiments implied that the cleavage of DNA occurs via a hydrolytic path. The results showed that the cleavage reaction of DNA is dependent on the value of pH and ionic strength in the solution. DNA cleavage is more efficient by N-phosphoryl branched peptide 2 than by N-phosphoryl branched peptide 1. The experiments also show that hydrolysis of DNA by N-phosphoryl branched peptide 1 was accelerated in the presence of Mg2+ or Zn2+ ions. The interactions of DNA with N-phosphoryl branched peptides were also characterized by melting temperature measurements and circular dichroism (CD) techniques. On the basis of experimental data, the possible mechanism of interactions between DNA with N-phosphoryl branched peptides was discussed.     

The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry

We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.