Protein identification assisted by the prediction of retention time in liquid chromatography/tandem mass spectrometry

Two-dimensional liquid chromatography (2D-LC) coupled on-line with electrospray ionization tandem mass spectrometry (2D-LC-ESI-MS/MS) is a new platform for analysis and identification of proteome. Peptides are separated by 2D-LC and then performed MS/MS analysis by tandem MS/MS. The MS/MS data are searched against database for protein identification. In one 2D-LC-ESI-MS/MS run, we obtained not only the structural information of peptides directly from MS/MS, but also the retention time of peptides eluted from LC. Information on the chromatographic behavior of peptides can assist protein identification in the new platform for proteomics. The retention time of the matching peptides of the identified protein was predicted by the hydrophobic contribute of each amino acid on reversed-phase liquid chromatography (RPLC). By using this strategy proteins were identified by four types of information: peptide mass fingerprinting (PMF), sequence query, and MS/MS ions searched and the predicted retention time. This additional information obtained from LC could assist protein identification with no extra experimental cost.     

Prediction of peptide retention volumes in gradient reversed phase HPLC

A method of computation of retention volumes of linear peptides of known composition that contain no more than 25 amino acids in gradient reversed phase HPLC was developed. Tha method is suitable for various acetonitrile gradient profiles. The calculations were carried out on the basis of a statistical model, the parameters of which were experimental dependences of the retention of individual amino acids on acetonitrile concentration. The method developed was used to predict the chromatographic behavior of 34 peptides in four different acetonitrile gradients. The correlation coefficients between the predicted and experimental retention volumes were more than 0.9, and the average relative error of prediction was less than 15%.     

An improved model for prediction of retention times of tryptic peptides in ion pair reversed-phase HPLC: its application to protein peptide mapping by off-line HPLC-MALDI MS

The proposed model is based on the measurement of the retention times of 346 tryptic peptides in the 560- to 4,000-Da mass range, derived from a mixture of 17 protein digests. These peptides were measured in HPLC-MALDI MS runs, with peptide identities confirmed by MS/MS. The model relies on summation of the retention coefficients of the individual amino acids, as in previous approaches, but additional terms are introduced that depend on the retention coefficients for amino acids at the N-terminal of the peptide. In the 17-protein mixture, optimization of two sets of coefficients, along with additional compensation for peptide length and hydrophobicity, yielded a linear dependence of retention time on hydrophobicity, with an R2 value about 0.94. The predictive capability of the model was used to distinguish peptides with close m/z values and for detailed peptide mapping of selected proteins. Its applicability was tested on columns of different sizes, from nano- to narrow-bore, and for direct sample injection, or injection via a pre-column. It can be used for accurate prediction of retention times for tryptic peptides on reversed-phase (300-A pore size) columns of different sizes with a linear water-ACN gradient and with TFA as the ion-pairing modifier.     

Aligning LC peaks by converting gradient retention times to retention index of peptides in proteomic experiments

MOTIVATION: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a powerful tool in proteomics studies, but when peptide retention information is used for identification purposes, it remains challenging to compare multiple LC-MS/MS runs or to match observed and predicted retention times, because small changes of LC conditions unavoidably lead to variability in retention times. In addition, non-contiguous retention data obtained with different LC-MS instruments or in different laboratories must be aligned to confirm and utilize rapidly accumulating published proteomics data. RESULTS: We have developed a new alignment method for peptide retention times based on linear solvent strength (LSS) theory. We found that log k(0) (logarithm of retention factor for a given organic solvent) in the LSS theory can be utilized as a 'universal' retention index of peptides (RIP) that is independent of LC gradients, and depends solely on the constituents of the mobile phase and the stationary phases. We introduced a machine learning-based scheme to optimize the conversion function of gradient retention times (t(g)) to log k(0). Using the optimized function, t(g) values obtained with different LC-MS systems can be directly compared with each other on the RIP scale. In an examination of Arabidopsis proteomic data, the vast majority of retention time variability was removed, and five datasets obtained with various LC-MS systems were successfully aligned on the RIP scale.     

A new method for normalization of the peptide retention times in chromatographic/mass-spectrometric experiments

Proteomic studies with the use of mass spectrometry required comparison of different experimental data (for example, control with a pathology or labeled and unlabeled samples). Identification of chromatographic peaks of the same substance in different chromatograms (time normalization of chromatograms) is complicated if peptides are identified in different experiments according only to their exactly evaluated masses and retention times on a chromatographic column. Retention times of the same peptides would vary from one experiment to another due to inevitable differences in experimental chromatographic conditions (replacement of chromatographic columns, slight changes in flow rates of a mobile phase or in a solvent concentration, or in other conditions). We proposed a reliable method for selection of peaks that corresponded to the same peptides from chromatography/mass spectra for the subsequent alignment of retention times (both a linear and some other monotone function).     

Prediction of peptide retention volumes in the gradient reversed phase HPLC

A method of computation of retention volumes of linear peptides of known composition that contain no more than 25 amino acids in gradient reversed phase HPLC was developed. The method is suitable for various acetonitrile gradient profiles. The calculations were carried out on the basis of a statistical model, the parameters of which were experimental dependences of the retention of individual amino acids on acetonitrile concentration. The method developed was used to predict the chromatographic behavior of 34 peptides in four different acetonitrile gradients. The correlation coefficients between the predicted and experimental retention volumes were more than 0.9, and the average relative error of prediction was less than 15%. The English version of the paper: Russiatn .lournal of Bioorganic Chemistry, 2008, vol. 34, no. 2; see also http://www.maik.ru.     

Induced conformational states of amphipathic peptides in aqueous/lipid environments.

Specific conformational effects have been reported for amphipathic model peptides upon binding of defined hydrophobic domains to nonpolar stationary phases during reversed-phase high performance liquid chromatography (RP-HPLC). Such induced conformations are found to be especially pronounced for peptides that are amphipathic in an alpha-helical conformation. Such induced amphipathic conformations resulted in substantially later elution than predicted using amino acid-based retention coefficients. In the present study, the induced conformational behavior of model peptides observed during RP-HPLC was correlated with their secondary structure as determined by circular dichroism (CD) spectroscopy in both aqueous solution and C18-mimetic environments. The experimental retention times of the peptides studied were found to correlate with their CD spectra in the presence of lipids, whereas a poor correlation was observed with their CD spectra in the presence of trifluoroethanol. A new approach was developed to evaluate the induction of secondary structure in peptides due to interactions at aqueous/lipid interfaces, which involves the measurement of the CD ellipticities of peptides bound to a set of C18-coated quartz plates. An excellent correlation was found in this environment between the RP-HPLC retention times and CD ellipticities of the bound peptides.     

Data filtration for more robust alignment of chromatograms of complex peptide mixtures

In carrying out proteomic researches using mass-spectrometry there often arises a need to compare experimental data with each other (e.g. control of pathology, the labeled to unlabelled samples). If for peptide identification in different experiments one uses only their exact mass measurements and the retention time in the chromatographic column, difficulties with the identification of chromatographic peaks belonging to the same substances in different chromatograms come up (retention time normalization). Due to inevitable discrepancies in chromatographic conditions of experiments (replacement of chromatographic columns, small changes in mobile phase flow rate or solvent concentration) retention times of the same peptides will diverge from experiment to experiment. In this paper we offer a reliable method for selecting peaks from mass-chromatograms corresponding to the same peptides, which can later be used for retention time normalization (either linear or any other monotone function).     

Prediction of retention volumes and UV spectra of peptides in reversed phase HPLC

A method for calculating retention volumes of linear peptides with known primary structures and the values of their UV absorption at chosen wavelengths in reversed phase HPLC are described. These parameters are calculated for every peptide on the basis of the contributions of its amino acid residues determining its degree of retention and its UV spectrum. The contribution values are experimentally found from chromatograms of the free amino acids obtained by multiwavelength photometric detection under the conditions of the peptide chromatography. Thirty peptides have been chromatographed for the evaluation of the proposed method, and the correlation coefficients between the calculated and the experimental retention volumes have been found to be 0.95.     

Prediction of retention volumes and UV spectra of peptides in reversed phase HPLC

A method for calculating retention volumes of linear peptides with known primary structures and the values of their UV absorption at chosen wavelengths in reversed phase HPLC are described. These parameters are calculated for every peptide on the basis of the contributions of its amino acid residues determining its degree of retention and its UV spectrum. The contribution values are experimentally found from chromatograms of the free amino acids obtained by multiwavelength photometric detection under the conditions of the peptide chromatography. Thirty peptides have been chromatographed for the evaluation of the proposed method, and the correlation coefficients between the calculated and the experimental retention volumes have been found to be 0.95.     

Individuation of monoclonal anti-HPV16 E7 antibody linear peptide epitope by computational biology

We applied computational biology to identify the linear amino acid sequence recognized by a mouse monoclonal antibody raised against the full length HPV16 E7 oncoprotein. Computer-assisted search for the epitopic peptide used two parameters: the capability of E7 peptides to bind to MHC class II molecules, and the similarity level of the oncoprotein sequence to the mouse proteome. We report that anti-E7 mAb recognized the peptide having both high binding potential to MHC II molecules and low level of molecular mimicry to mouse proteome. Peptide ability to bind to MHC II molecules appears a necessary but not sufficient condition to determine peptide immunodominance, by needing to be supported by a low degree of peptide similarity to the host’s proteome.     

Chromatographic retention time prediction for posttranslationally modified peptides

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for mass spectrometry-based proteomics, especially in designing more efficient procedures for state-of-the-art targeted workflows. Additionally, accurate retention time predictions can also be used to increase confidence in identifications in shotgun experiments. Despite these obvious benefits, the use of such methods has so far not been extended to (posttranslationally) modified peptides due to the absence of efficient predictors for such peptides. We here therefore describe a new retention time predictor for modified peptides, built on the foundations of our existing Elude algorithm. We evaluated our software by applying it on five types of commonly encountered modifications. Our results show that Elude now yields equally good prediction performances for modified and unmodified peptides, with correlation coefficients between predicted and observed retention times ranging from 0.93 to 0.98 for all the investigated datasets. Furthermore, we show that our predictor handles peptides carrying multiple modifications as well. This latest version of Elude is fully portable to new chromatographic conditions and can readily be applied to other types of posttranslational modifications. Elude is available under the permissive Apache2 open source License at http://per-colator.com or can be run via a web-interface at http://elude.sbc.su.se.     

Highly informative proteome analysis by combining improved N-terminal sulfonation for de novo peptide sequencing and online capillary reverse-phase liquid chromatography/tandem mass spectrometry

Recently, various chemical modifications of peptides have been incorporated into mass spectrometric analyses of proteome samples, predominantly in conjunction with matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS), to facilitate de novo sequencing of peptides. In this work, we investigate systematically the utility of N-terminal sulfonation of tryptic peptides by 4-sulfophenyl isothiocyanate (SPITC) for proteome analysis by capillary reverse-phase liquid chromatography/tandem mass spectrometry (cRPLC/MS/MS). The experimental conditions for the sulfonation were carefully adjusted so that SPITC reacts selectively with the N-terminal amino groups, even in the presence of the epsilon-amino groups of lysine residues. Mass spectrometric analyses of the modified peptides by cRPLC/MS/MS indicated that SPITC derivatization proceeded toward near completion under the experimental conditions employed here. The SPITC-derivatized peptides underwent facile fragmentation, predominantly resulting in y-series ions in the MS/MS spectra. Combining SPITC derivatization and cRPLC/MS/MS analyses facilitated the acquisition of sequence information for lysine-terminated tryptic peptides as well as arginine-terminated peptides without the need for additional peptide pretreatment, such as guanidination of lysine amino group. This process alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI MS experiments. We will discuss the utility of the technique as a viable method for proteome analyses and present examples of its application in analyzing samples having different levels of complexity.     

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.     

Analysis of the mouse liver proteome using advanced mass spectrometry

We report a large-scale analysis of mouse liver tissue comprising a novel fractionation approach and high-accuracy mass spectrometry techniques. Two fractions enriched for soluble and membrane proteins from 20 mg of frozen tissue were separated by one-dimensional electrophoresis followed by LC-MS/MS on the hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer. Confident identification of 2210 proteins relied on at least two peptides. We combined this proteome with our previously reported organellar map (Foster et al. Cell 2006, 125, 187-199) to generate a very high confidence mouse liver proteome of 3244 proteins. The identified proteins represent the liver proteome with no discernible bias due to protein physicochemical properties, subcellular distribution, or biological function. Forty-seven percent of identified proteins were annotated as membrane-bound, and for 35.3%, transmembrane domains were predicted. For potential application in toxicology or clinical studies, we demonstrate that it is possible to consistently identify more than 1000 proteins in a single run.     

Informatics for peptide retention properties in proteomic LC-MS

Retention times in HPLC yield valuable information for the identification of various analytes and the prediction of peptide retention is useful for the identification of peptides/proteins in LC-MS-based proteomics. Informatics methods such as artificial neural networks and support vector machines capable of solving nonlinear problems made possible the accurate modeling of quantitative structure-retention relationships of peptides (including large polymers) up to 5 kDa to which classical linear models cannot be applied, as well as the proteome-wide prediction of peptide retention. Proteome-wide retention prediction and accurate mass-information facilitate the identification of peptides in complex proteomic samples. In this review, we address recent developments in solid informatics methods and their application to peptide-retention properties in 'bottom-up' shotgun proteomics. We also describe future prospects for the standardization and application of retention times.     

Observed peptide p<Emphasis Type="Italic">I</Emphasis> and retention time shifts as a result of post-translational modifications in multidimensional separations using narrow-range IPG-IEF

Modified peptides constitute a sub-population among the tryptic peptides analyzed in LC–MS based shotgun proteomics experiments. For larger proteomes including the human proteome, the tryptic peptide pool is very large, which necessitates some form of sample fractionation. By carefully choosing the sample fractionation and separation methods applied as shown here for the combination of narrow-range immobilized pH gradient isoelectric focusing (IPG-IEF) and nanoUPLC–MS, significantly increased information content can be achieved. Relatively low standard deviations were obtained for such multidimensional separations in terms of peptide pI (<0.05 pI units) and retention time (<0.3 min for a 350 min gradient) for a selection of highly complex proteomics samples. Using narrow-range IPG-IEF, experimental and predicted pI were in relative good agreement. However, based on our data, retention time prediction algorithms need further improvements in accuracy to match state-of-the-art reversed-phase chromatography performance. General trends of peptide pI shifts induced by common modifications including deamidations and N-terminal modifications are described. Deamidations of glutamine and asparagines shift peptide pI by approximately 1.5 pI units, making the peptides more acidic. Additionally, a novel pI shift (+~0.4 pI units) was found associated with dethiomethyl Met modifications. Further, the effects of these modifications as well as methionine oxidation were investigated in terms of experimentally observed retention time shifts in the chromatographic separation step. Clearly, post-translational modification-induced influences on peptide pI and retention time can be accurately and reproducibly measured using narrow-range IPG-IEF and high-performance nanoLC–MS. Even at modest mass accuracy (±50 ppm), the inclusion of peptide pI (±0.2 pI units) and/or retention time (±20 min) criteria are highly informative for human proteome analyses. The applications of using this information to identify post-translationally modified peptides and improve data analysis workflows are discussed.     

The epitope space of the human proteome

In the post-genome era, there is a great need for protein-specific affinity reagents to explore the human proteome. Antibodies are suitable as reagents, but generation of antibodies with low cross-reactivity to other human proteins requires careful selection of antigens. Here we show the results from a proteome-wide effort to map linear epitopes based on uniqueness relative to the entire human proteome. The analysis was based on a sliding window sequence similarity search using short windows (8, 10, and 12 amino acid residues). A comparison of exact string matching (Hamming distance) and a heuristic method (BLAST) was performed, showing that the heuristic method combined with a grid strategy allows for whole proteome analysis with high accuracy and feasible run times. The analysis shows that it is possible to find unique antigens for a majority of the human proteins, with relatively strict rules involving low sequence identity of the possible linear epitopes. The implications for human antibody-based proteomics efforts are discussed.