Enrichment of N-terminal cysteinyl-peptides by covalent capture

The detection of low abundance proteins in complex biological samples is still a challenge in proteomics. To circumvent this obstacle a number of strategies involving the targeting of subsets of proteins or peptides were developed.The following work describes a new approach to simplify peptide mixtures by enrichment of N-terminal cysteinyl peptides (and to some extent N-terminal threonine peptides). The strategy is based on the use of an isolation method, so-called covalent capture (CC), which relies on the formation of a covalent bond between an N-terminal free cysteine or N-terminal free threonine and an aldehyde fixed on a solid support. The CC is highly selective. It permits extensive washes of the resin for the elimination of non-specific moieties before the release of the captured peptides. The application of the CC to proteomics was evaluated on tryptic peptides of standard proteins and test protein mixtures. The procedure demonstrated a significant reduction in sample complexity, while allowing the identification of N-terminal cysteinyl peptides hidden in the non-fractionated samples.This new strategy provides an efficient tool to existing proteomics approaches to reduce sample complexity and potentially identify less abundance proteins.     

Quantitative analysis of human cerebrospinal fluid proteins using a combination of cysteine tagging and amine-reactive isobaric labeling

Highly complex and dynamic protein mixtures are hardly comprehensively resolved by direct shotgun proteomic analysis. As many proteins of biological interest are of low abundance, numerous analytical methodologies have been developed to reduce sample complexity and go deeper into proteomes. The present work describes an analytical strategy to perform cysteinyl-peptide subset enrichment and relative quantification through successive cysteine and amine-isobaric tagging. A cysteine-reactive covalent capture tag (C3T) allowed derivatization of cysteines and specific isolation on a covalent capture (CC) resin. The 6-plex amine-reactive tandem mass tags (TMT) served for relative quantification of the targeted peptides. The strategy was first evaluated on a model protein mixture with increasing concentrations to assess the specificity of the enrichment and the quantitative performances of the workflow. It was then applied to human cerebrospinal fluid (CSF) from post-mortem and ante-mortem samples. These studies confirmed the specificity of the C3T and the CC technique to cysteine-containing peptides. The model protein mixture analysis showed high precision and accuracy of the quantification with coefficients of variation and mean absolute errors of less than 10% on average. The CSF experiments demonstrated the potential of the strategy to study complex biological samples and identify differential brain-related proteins. In addition, the quantification data were highly correlated with a classical TMT experiment (i.e., without C3T cysteine-tagging and enrichment steps). Altogether, these results legitimate the use of this quantitative C3T strategy to enrich and relatively quantify cysteine-containing peptides in complex mixtures.     

Positional proteomics: selective recovery and analysis of N-terminal proteolytic peptides

Bottom-up proteomics is the analysis of peptides derived from single proteins or protein mixtures, and because each protein generates tens of peptides, there is scope for controlled reduction in complexity. We report here a new strategy for selective isolation of the N-terminal peptides of a protein mixture, yielding positionally defined peptides. The method is tolerant of several fragmentation methods, and the databases that must be searched are substantially less complex.     

High dynamic range characterization of the trauma patient plasma proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this "divide-and-conquer" strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3,654 different proteins with 1,494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 "classic" cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2,910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1,553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.     

Capture of peptides with N-terminal serine and threonine: a sequence-specific chemical method for Peptide mixture simplification

The objective of this study was to evaluate a sequence-specific chemistry for the ability to specifically capture peptides that contain N-terminal serine or threonine residues from mixtures. The first step is the oxidation of the 1,2-amino alcohol structure -CH(NH(2))CH(OH)- of peptides containing N-terminal serine or threonine with periodate. The newly formed aldehyde reacts with a labeling reagent containing a hydrazide, RCONHNH(2), to form a hydrazone-peptide conjugate, RCONHN=CH-peptide. Biotin-labeled conjugates can then be isolated by affinity purification with streptavidin. The method described in this report can be useful in simplifying the complex mixtures of peptides that are generated in typical proteomic analysis, where proteins are digested with trypsin and analyzed using liquid chromatography mass spectrometry data. The sequence-specific peptide selection not only reduces the complexity of digest mixtures, but also provides additional information for peptide identification. The targeted peptides are those that have either serine or threonine adjacent to a protease cleavage site. The sequence information should greatly aid in both database matching for protein identification and for de novo sequence determination.     

Exploring proteomes and analyzing protein processing by mass spectrometric identification of sorted N-terminal peptides

Current non-gel techniques for analyzing proteomes rely heavily on mass spectrometric analysis of enzymatically digested protein mixtures. Prior to analysis, a highly complex peptide mixture is either separated on a multidimensional chromatographic system or it is first reduced in complexity by isolating sets of representative peptides. Recently, we developed a peptide isolation procedure based on diagonal electrophoresis and diagonal chromatography. We call it combined fractional diagonal chromatography (COFRADIC). In previous experiments, we used COFRADIC to identify more than 800 Escherichia coli proteins by tandem mass spectrometric (MS/MS) analysis of isolated methionine-containing peptides. Here, we describe a diagonal method to isolate N-terminal peptides. This reduces the complexity of the peptide sample, because each protein has one N terminus and is thus represented by only one peptide. In this new procedure, free amino groups in proteins are first blocked by acetylation and then digested with trypsin. After reverse-phase (RP) chromatographic fractionation of the generated peptide mixture, internal peptides are blocked using 2,4,6-trinitrobenzenesulfonic acid (TNBS); they display a strong hydrophobic shift and therefore segregate from the unaltered N-terminal peptides during a second identical separation step. N-terminal peptides can thereby be specifically collected for further liquid chromatography (LC)-MS/MS analysis. Omitting the acetylation step results in the isolation of non-lysine-containing N-terminal peptides from in vivo blocked proteins.     

The implications of proteolytic background for shotgun proteomics

The analysis by liquid chromatography coupled to tandem mass spectrometry of complex peptide mixtures, generated by proteolysis of protein samples, is the main proteomics method used today. The approach is based on the assumption that each protein present in a sample reproducibly and predictably generates a relatively small number of peptides that can be identified by mass spectrometry. In this study this assumption was examined by a targeted peptide sequencing strategy using inclusion lists to trigger peptide fragmentation attempts. It was found that the number of peptides observed from a single protein is at least one order of magnitude greater than previously assumed. This unexpected complexity of proteomics samples implies substantial technical challenges, explains some perplexing results in the proteomics literature, and prompts the need for developing alternative experimental strategies for the rapid and comprehensive analysis of proteomes.     

CysTRAQ - A combination of iTRAQ and enrichment of cysteinyl peptides for uncovering and quantifying hidden proteomes

Shotgun proteomics is capable of characterizing differences in both protein quality and quantity, and has been applied in various biomedical applications. Unfortunately, the high complexity and dynamic range of proteins in studied samples, clinical in particular, often hinders the identification of relevant proteins. Indeed, information-rich, low abundance proteins often remain undetected, whereas repeatedly reported altered concentrations in high abundance proteins are often ambiguous and insignificant. Several techniques have therefore been developed to overcome this obstacle and provide a deeper insight into the proteome. Here we report a novel approach, which enables iTRAQ reagent quantitation of peptides fractionated based on presence of a cysteine residue (thus CysTRAQ). For the first time, we prove that iTRAQ quantitation is fully compatible with cysteinyl peptide enrichment and is not influenced by the fractionation process. Moreover, the employment of the method combined with high-resolution TripleTOF 5600 mass spectrometer for very fast MS/MS acquisition in human amniotic fluid analysis significantly increased the number of identified proteins, which were simultaneously quantified owing to the introduction of iTRAQ labeling. We herein show that CysTRAQ is a robust and straightforward method with potential application in quantitative proteomics experiments, i.e. as an alternative to the ICAT reagent approach.     

Improved proteome coverage by using high efficiency cysteinyl peptide enrichment: the human mammary epithelial cell proteome

Automated multidimensional capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been increasingly applied in various large scale proteome profiling efforts. However, comprehensive global proteome analysis remains technically challenging due to issues associated with sample complexity and dynamic range of protein abundances, which is particularly apparent in mammalian biological systems. We report here the application of a high efficiency cysteinyl peptide enrichment (CPE) approach to the global proteome analysis of human mammary epithelial cells (HMECs) which significantly improved both sequence coverage of protein identifications and the overall proteome coverage. The cysteinyl peptides were specifically enriched by using a thiol-specific covalent resin, fractionated by strong cation exchange chromatography, and subsequently analyzed by reversed-phase capillary LC-MS/MS. An HMEC tryptic digest without CPE was also fractionated and analyzed under the same conditions for comparison. The combined analyses of HMEC tryptic digests with and without CPE resulted in a total of 14 416 confidently identified peptides covering 4294 different proteins with an estimated 10% gene coverage of the human genome. By using the high efficiency CPE, an additional 1096 relatively low abundance proteins were identified, resulting in 34.3% increase in proteome coverage; 1390 proteins were observed with increased sequence coverage. Comparative protein distribution analyses revealed that the CPE method is not biased with regard to protein M(r) , pI, cellular location, or biological functions. These results demonstrate that the use of the CPE approach provides improved efficiency in comprehensive proteome-wide analyses of highly complex mammalian biological systems.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

Application of Mass Spectrometry in Proteomics

Mass spectrometry has arguably become the core technology in proteomics. The application of mass spectrometry based techniques for the qualitative and quantitative analysis of global proteome samples derived from complex mixtures has had a big impact in the understanding of cellular function. Here, we give a brief introduction to principles of mass spectrometry and instrumentation currently used in proteomics experiments. In addition, recent developments in the application of mass spectrometry in proteomics are summarised. Strategies allowing high-throughput identification of proteins from highly complex mixtures include accurate mass measurement of peptides derived from total proteome digests and multidimensional peptide separations coupled with mass spectrometry. Mass spectrometric analysis of intact proteins permits the characterisation of protein isoforms. Recent developments in stable isotope labelling techniques and chemical tagging allow the mass spectrometry based differential display and quantitation of proteins, and newly established affinity procedures enable the targeted characterisation of post-translationally modified proteins. Finally, advances in mass spectrometric imaging allow the gathering of specific information on the local molecular composition, relative abundance and spatial distribution of peptides and proteins in thin tissue sections.     

Thermodynamic analysis of protein-ligand interactions in complex biological mixtures using a shotgun proteomics approach

Shotgun proteomics protocols are widely used for the identification and/or quantitation of proteins in complex biological samples. Described here is a shotgun proteomics protocol that can be used to identify the protein targets of biologically relevant ligands in complex protein mixtures. The protocol combines a quantitative proteomics platform with a covalent modification strategy, termed Stability of Proteins from Rates of Oxidation (SPROX), which utilizes the denaturant dependence of hydrogen peroxide-mediated oxidation of methionine side chains in proteins to assess the thermodynamic properties of proteins and protein-ligand complexes. The quantitative proteomics platform involves the use of isobaric mass tags and a methionine-containing peptide enhancement strategy. The protocol is evaluated in a ligand binding experiment designed to identify the proteins in a yeast cell lysate that bind the well-known enzyme cofactor, β-nicotinamide adenine dinucleotide (NAD+). The protocol is also used to investigate the protein targets of resveratrol, a biologically active ligand with less well-understood protein targets. A known protein target of resveratrol, cytosolic aldehyde dehydrogenase, was identified in addition to six other potential new proteins targets including four that are associated with the protein translation machinery, which has previously been implicated as a target of resveratrol.     

Selective enrichment of tryptophan-containing peptides from protein digests employing a reversible derivatization with malondialdehyde and solid-phase capture on hydrazide beads

A method for the selective enrichment of tryptophan-containing peptides from complex peptide mixtures such as protein digests is presented. It is based on the reversible reaction of tryptophan with malondialdehyde and trapping of the derivatized Trp-peptides on hydrazide beads via the free aldehyde group of the modified peptides. The peptides are subsequently recovered in their native form by specific cleavage reactions for further (mass spectrometric) analysis. The method was optimized and evaluated using a tryptic digest of a mixture of 10 model proteins, demonstrating a significant reduction in sample complexity while still allowing the identification of all proteins. The applicability of the tryptophan-specific enrichment procedure to complex biological samples is demonstrated for a total yeast cell lysate. Analysis of the processed fraction by 1D-LC-MS/MS confirms the specificity of the enrichment procedure, as more than 85% of the peptides recovered from the enrichment step contained tryptophan. The reduction in sample complexity also resulted in the identification of additional proteins in comparison to the untreated lysate.     

The proteomic analysis improved by cleavage kinetics‐based fractionation of tryptic peptides

Selective enrichment of specific peptides is an effective way to identify low abundance proteins. Fractionation of peptides prior to mass spectrometry is another widely used approach to reduce sample complexity in order to improve proteome coverage.In this study, we designed a multi‐stage digestion strategy to generate peptides with different trypsin cleavage kinetics. It was found that each of the collected peptide fractions yielded many new protein identifications compared to the control group due to the reduced complexity. The overlapping peptides identified between adjacent fractions were very low, indicating that each fraction had different sets of peptides. The multi‐stage digestion strategy separates tryptic peptides with different cleavage kinetics while RPLC separates peptides with different hydrophobicity. These two separation strategies were highly orthogonal, and showed an effective multidimensional separation to improve proteome coverage.     

Characterization of low abundant membrane proteins using the protein sequence tag technology

About 25% of open reading frames in fully sequenced genomes are estimated to encode transmembrane proteins that represent valuable targets for drugs. However, the global analysis of membrane proteins has been proven to be problematic, e.g., because of their very amphiphilic nature. In this paper, we show that the recently published Protein Sequence Tag (PST) technology combined with an efficient sample preparation is a powerful method to perform protein analysis of highly enriched membrane fractions. The PST approach is a gel-free proteomics tool for the analysis of proteins, which relies on a "sampling" strategy by isolating N-terminal protein sequence tags from cyanogen bromide cleaved proteins. The identification of these N-terminal PST peptides is based on LC-MS/MS. The effectiveness of the technology is demonstrated for a membrane fraction, which was isolated from crude mitochondria of yeast after alkaline sodium carbonate treatment. The PST approach performed on this fraction analyzed 148 proteins, whereas 84% are identified as membrane proteins. More interestingly, among these membrane proteins 56% are predicted to be of low abundance. These encouraging results are an important step toward the development of a quantitative PST approach (qPST) for the differential display of membrane protein analysis.     

Technologies and methods for sample pretreatment in efficient proteome and peptidome analysis

Although great progresses have been made in proteomics during the last decade, proteomics is still in its infancy. Extreme complexity of proteome sample and large dynamic range of protein abundance overwhelm the capability of all currently available analytical platforms. Sample pretreatment is a good approach to reduce the complexity of proteome sample and decrease the dynamic range. In this article, we present an overview of different technologies and methods for sample pretreatment in efficient proteome and peptidome analysis. Methods for isolation of rare amino acid-containing peptides, terminal peptides, PTM peptides and endogenous peptides are reviewed. In addition, two automated sample pretreatment technologies, i.e. automated sample injection and on-line digestion, are also covered.     

Fractionation of complex protein mixture by virtual three-dimensional liquid chromatography based on combined pH and salt steps

The complexity and diversity of biological samples in proteomics require intensive fractionation ahead of mass spectrometry identification. This work developed a chromatographic method called virtual three-dimensional chromatography to fractionate complex protein mixtures. By alternate elution with different pHs and salt concentrations, we implemented pH and salt steps by turns on a single strong cation exchange column to fully exploit its chromatographic ability. Given standard proteins that were not resolved solely by pH or salt gradient elution could be successfully separated using this combined mode. With a reversed phase column tandem connected behind, we further fractionated as well as desalted proteins as the third dimension. This present strategy could readily be adapted with respect to special complexity of biological samples. Crude plasma without depleting high abundance proteins were fractionated by this three-dimensional mode and then analyzed by reversed phase liquid chromatography coupled with LTQ mass spectrometry. In total, 1933 protein groups with wide dynamic ranges were identified from a single experiment. Some characteristics that correlated to the behavior of proteins on strong cation exchange columns are also discussed.     

SWATH enables precise label‐free quantification on proteome scale

MS‐based proteomics has emerged as a powerful tool in biological studies. The shotgun proteomics strategy, in which proteolytic peptides are analyzed in data‐dependent mode, enables a detection of the most comprehensive proteome (>10 000 proteins from whole‐cell lysate). The quantitative proteomics uses stable isotopes or label‐free method to measure relative protein abundance. The isotope labeling strategies are more precise and accurate compared to label‐free methods, but labeling procedures are complicated and expensive, and the sample number and types are also limited. Sequential window acquisition of all theoretical mass spectra (SWATH) is a recently developed technique, in which data‐independent acquisition is coupled with peptide spectral library match. In principle SWATH method is able to do label‐free quantification in an MRM‐like manner, which has higher quantification accuracy and precision. Previous data have demonstrated that SWATH can be used to quantify less complex systems, such as spiked‐in peptide mixture or protein complex. Our study first time assessed the quantification performance of SWATH method on proteome scale using a complex mouse‐cell lysate sample. In total 3600 proteins got identified and quantified without sample prefractionation. The SWATH method shows outstanding quantification precision, whereas the quantification accuracy becomes less perfect when protein abundances differ greatly. However, this inaccuracy does not prevent discovering biological correlates, because the measured signal intensities had linear relationship to the sample loading amounts; thus the SWATH method can predict precisely the significance of a protein. Our results prove that SWATH can provide precise label‐free quantification on proteome scale.     

Two‐step OFFGEL approach for effective peptide separation compatible with iTRAQ labeling

Shotgun proteomic analyses are increasingly becoming methods of choice for complex samples. The development of effective methods for fractionating peptides to reduce the complexity of the sample before mass analysis is a key point in this strategy. The OFFGEL technology has recently become a tool of choice in proteomic analysis at peptide level. This OFFGEL electrophoresis (OGE) approach allows the in‐solution separation of peptides from various biological sources by isoelectric focusing in highly resolved 24 fractions. It was also demonstrated that OGE technology is a filtering tool for pI‐based validation of peptide identification. As peptide OGE is compatible with iTRAQ labeling, OGE is finding valuable applications in quantitative proteomics as well. The aim of this study is to explain a new 2D‐OGE approach that improves the proteomic coverage of complex mixtures such as colorectal cell line lysates, and which is compatible with iTRAQ labeling.     

Application of targeted quantitative proteomics analysis in human cerebrospinal fluid using a liquid chromatography matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (LC MALDI TOF/TOF) platform

Targeted quantitative proteomics by mass spectrometry aims to selectively detect one or a panel of peptides/proteins in a complex sample and is particularly appealing for novel biomarker verification/validation because it does not require specific antibodies. Here, we demonstrated the application of targeted quantitative proteomics in searching, identifying, and quantifying selected peptides in human cerebrospinal spinal fluid (CSF) using a matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometer (MALDI TOF/TOF)-based platform. The approach involved two major components: the use of isotopic-labeled synthetic peptides as references for targeted identification and quantification and a highly selective mass spectrometric analysis based on the unique characteristics of the MALDI instrument. The platform provides high confidence for targeted peptide detection in a complex system and can potentially be developed into a high-throughput system. Using the liquid chromatography (LC) MALDI TOF/TOF platform and the complementary identification strategy, we were able to selectively identify and quantify a panel of targeted peptides in the whole proteome of CSF without prior depletion of abundant proteins. The effectiveness and robustness of the approach associated with different sample complexity, sample preparation strategies, as well as mass spectrometric quantification were evaluated. Other issues related to chromatography separation and the feasibility for high-throughput analysis were also discussed. Finally, we applied targeted quantitative proteomics to analyze a subset of previously identified candidate markers in CSF samples of patients with Parkinson's disease (PD) at different stages and Alzheimer's disease (AD) along with normal controls.