Reference map for liquid chromatography–mass spectrometry-based quantitative proteomics

The accurate mass and time (AMT) tag strategy has been recognized as a powerful tool for high-throughput analysis in liquid chromatography–mass spectrometry (LC–MS)-based proteomics. Due to the complexity of the human proteome, this strategy requires highly accurate mass measurements for confident identifications. We have developed a method of building a reference map that allows relaxed criteria for mass errors yet delivers high confidence for peptide identifications. The samples used for generating the peptide database were produced by collecting cysteine-containing peptides from T47D cells and then fractionating the peptides using strong cationic exchange chromatography (SCX). LC–tandem mass spectrometry (MS/MS) data from the SCX fractions were combined to create a comprehensive reference map. After the reference map was built, it was possible to skip the SCX step in further proteomic analyses. We found that the reference-driven identification increases the overall throughput and proteomic coverage by identifying peptides with low intensity or complex interference. The use of the reference map also facilitates the quantitation process by allowing extraction of peptide intensities of interest and incorporating models of theoretical isotope distribution.     

Increased proteome coverage by combining PAGE and peptide isoelectric focusing: Comparative study of gel‐based separation approaches

The in‐depth analysis of complex proteome samples requires fractionation of the sample into subsamples prior to LC‐MS/MS in shotgun proteomics experiments. We have established a 3D workflow for shotgun proteomics that relies on protein separation by 1D PAGE, gel fractionation, trypsin digestion, and peptide separation by in‐gel IEF, prior to RP‐HPLC‐MS/MS. Our results show that applying peptide IEF can significantly increase the number of proteins identified from PAGE subfractionation. This method delivers deeper proteome coverage and provides a large degree of flexibility in experimentally approaching highly complex mixtures by still relying on protein separation according to molecular weight in the first dimension.     

Isocratic solid phase extraction-liquid chromatography (SPE-LC) interfaced to high-performance tandem mass spectrometry for rapid protein identification

Reversed-phase liquid chromatography interfaced to electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) allows analysis of very complex peptide mixtures at great sensitivity, but it can be very time-consuming, typically using 60 min, or more, per sample analysis. We recently introduced the isocratic solid phase extraction-liquid chromatography (SPE-LC) technology for rapid separation (~8 min) of simple peptide samples. We now extend these studies to demonstrate the potential of SPE-LC separation in combination with a hybrid linear ion trap-Orbitrap tandem mass spectrometer for efficient analysis of peptide samples in proteomics research. The system performance of SPE-LC-MS/MS was evaluated in terms of sensitivity and efficiency for the analysis of tryptic peptide digests obtained from samples consisting of up to 12 standard proteins. The practical utility of the analytical setup was demonstrated by the analysis of <15 microg depleted human serum proteome by a combination of SDS-PAGE and SPE-LC-MS/MS. A total of 88 unique gene products spanning 3 orders of magnitude in serum protein concentration were identified using stringent database search criteria.     

Proteomic analyses using an accurate mass and time tag strategy

An accurate mass and time (AMT) tag approach for proteomic analyses has been developed over the past several years to facilitate comprehensive high-throughput proteomic measurements. An AMT tag database for an organism, tissue, or cell line is established by initially performing standard shotgun proteomic analysis and, most importantly, by validating peptide identifications using the mass measurement accuracy of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) and liquid chromatography (LC) elution time constraint. Creation of an AMT tag database largely obviates the need for subsequent MS/MS analyses, and thus facilitates high-throughput analyses. The strength of this technology resides in the ability to achieve highly efficient and reproducible one-dimensional reversed-phased LC separations in conjunction with highly accurate mass measurements using FTICR MS. Recent improvements allow for the analysis of as little as picrogram amounts of proteome samples by minimizing sample handling and maximizing peptide recovery. The nanoproteomics platform has also demonstrated the ability to detect >10(6) differences in protein abundances and identify more abundant proteins from subpicogram amounts of samples. The AMT tag approach is poised to become a new standard technique for the in-depth and high-throughput analysis of complex organisms and clinical samples, with the potential to extend the analysis to a single mammalian cell.     

The Generation of a Comprehensive Spectral Library for the Analysis of the Guinea Pig Proteome by SWATH‐MS

Advances in liquid chromatography‐mass spectrometry have facilitated the incorporation of proteomic studies to many biology experimental workflows. Data‐independent acquisition platforms, such as sequential window acquisition of all theoretical mass spectra (SWATH‐MS), offer several advantages for label‐free quantitative assessment of complex proteomes over data‐dependent acquisition (DDA) approaches. However, SWATH data interpretation requires spectral libraries as a detailed reference resource. The guinea pig (Cavia porcellus) is an excellent experimental model for translation to many aspects of human physiology and disease, yet there is limited experimental information regarding its proteome. To overcome this knowledge gap, a comprehensive spectral library of the guinea pig proteome is generated. Homogenates and tryptic digests are prepared from 16 tissues and subjected to >200 DDA runs. Analysis of >250 000 peptide‐spectrum matches resulted in a library of 73 594 peptides from 7666 proteins. Library validation is provided by i) analyzing externally derived SWATH files ( https://doi.org/10.1016/j.jprot.2018.03.023 ) and comparing peptide intensity quantifications; ii) merging of externally derived data to the base library. This furnishes the research community with a comprehensive proteomic resource that will facilitate future molecular‐phenotypic studies using (re‐engaging) the guinea pig as an experimental model of relevance to human biology. The spectral library and raw data are freely accessible in the MassIVE repository (MSV000083199).     

Profiling human brain proteome by multi-dimensional separations coupled with MS

In our initial attempt to analyze the human brain proteome, we applied multi-dimensional protein separation and identification techniques using a combination of sample fractionation, 1-D SDS-PAGE, and MS analysis. The complexity of human brain proteome requires multiple fractionation strategies to extend the range and total number of proteins identified. According to the method of Klose (Methods Mol. Biol. 1999, 112, 67), proteins of the temporal lobe of human brain were fractionated into (i) cytoplasmic and nucleoplasmic, (ii) membrane and other structural, and (iii) DNA-binding proteins. Each fraction was then separated by SDS-PAGE, and the resulting gel line was cut into approximately 50 bands. After trypsin digestion, the resulting peptides from each band were analyzed by RP-LC/ESI-MS/MS using an LTQ spectrometer. The SEQUEST search program, which searched against the IPI database, was used for peptide sequence identification, and peptide sequences were validated by reversed sequence database search and filtered by the Protein Hit Score. Ultimately, 1533 proteins could be detected from the human brain. We classified the identified proteins according to their distribution on cellular components. Among these proteins, 24% were membrane proteins. Our results show that the multiple separation strategy is effective for high-throughput characterization of proteins from complex proteomic mixtures.     

Integration of gel-based proteome data with pProRep

pProRep is a web application integrating electrophoretic and mass spectral data from proteome analyses into a relational database. The graphical web-interface allows users to upload, analyse and share experimental proteome data. It offers researchers the possibility to query all previously analysed datasets and can visualize selected features, such as the presence of a certain set of ions in a peptide mass spectrum, on the level of the two-dimensional gel. AVAILABILITY: The pProRep package and instructions for its use can be downloaded from http://www.ptools.ua.ac.be/pProRep. The application requires a web server that runs PHP 5 (http://www.php.net) and MySQL. Some (non-essential) extensions need additional freely available libraries: details are described in the installation instructions.     

Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.     

Multidimensional protein profiling technology and its application to human plasma proteome

In clinical and diagnostic proteomics, it is essential to develop a comprehensive and robust system for proteome analysis. Although multidimensional liquid chromatography/tandem mass spectrometry (LC/MS/MS) systems have been recently developed as powerful tools especially for identification of protein complexes, these systems still some drawbacks in their application to clinical research that requires an analysis of a large number of human samples. Therefore, in this study, we have constructed a technically simple and high throughput protein profiling system comprising a two-dimensional (2D)-LC/MS/MS system which integrates both a strong cation exchange (SCX) chromatography and a microLC/MS/MS system with micro-flowing reversed-phase chromatography. Using the microLC/MS/MS system as the second dimensional chromatography, SCX separation has been optimized as an off-line first dimensional peptide fractionation. To evaluate the performance of the constructed 2D-LC/MS/MS system, the results of detection and identification of proteins were compared using digests mixtures of 6 authentic proteins with those obtained using one-dimensional microLC/MS/MS system. The number of peptide fragments detected and the coverage of protein sequence were found to be more than double through the use of our newly built 2D-LC/MS/MS system. Furthermore, this multidimensional protein profiling system has been applied to plasma proteome in order to examine its feasibility for clinical proteomics. The experimental results revealed the identification of 174 proteins from one serum sample depleted HSA and IgG which corresponds to only 1 microL of plasma, and the total analysis run time was less than half a day, indicating a fairly high possibility of practicing clinical proteomics in a high throughput manner.     

多维液相色谱分离技术在复杂蛋白质组学样品鉴定中的应用

目的：随着蛋白组学技术的发展,液相色谱-串联质谱的联用技术（液质联用）逐渐成为蛋白组学的主流技术。方法：通过结合各种不同原理的色谱分离类型,多维液相色谱分离技术能够极大的提高分离系统的峰容量,达到有效分离复杂程度很高的蛋白质组学样品的目的。结果：最广泛使用的多维液相色谱分离系统是离子交换色谱（IEX）和反相色谱（RP）的二维结合,近年来又发展出了分离能力更强的三维液相色谱分离系统,并且已经在蛋白质组学研究中得到了应用。结论：本文综述了多种多维液相色谱分离方法,在这些方法中,不同的分离原理的色谱类型被用于肽段或蛋白混合物的预分离中,有效促进了样品的充分分离,极大地提高了复杂样品的蛋白组学鉴定能力。     

Using ion mobility data to improve peptide identification: intrinsic amino acid size parameters

A new method for enhancing peptide ion identification in proteomics analyses using ion mobility data is presented. Ideally, direct comparisons of experimental drift times (t(D)) with a standard mobility database could be used to rank candidate peptide sequence assignments. Such a database would represent only a fraction of sequences in protein databases and significant difficulties associated with the verification of data for constituent peptide ions would exist. A method that employs intrinsic amino acid size parameters to obtain ion mobility predictions that can be used to rank candidate peptide ion assignments is proposed. Intrinsic amino acid size parameters have been determined for doubly charged peptide ions from an annotated yeast proteome. Predictions of ion mobilities using the intrinsic size parameters are more accurate than those obtained from a polynomial fit to t(D) versus molecular weight data. More than a 2-fold improvement in prediction accuracy has been observed for a group of arginine-terminated peptide ions 12 residues in length. The use of this predictive enhancement as a means to aid peptide ion identification is discussed, and a simple peptide ion scoring scheme is presented.     

Chromatographic isolation of methionine-containing peptides for gel-free proteome analysis: identification of more than 800 Escherichia coli proteins

A novel gel-free proteomic technology was used to identify more than 800 proteins from 50 million Escherichia coli K12 cells in a single analysis. A peptide mixture is first obtained from a total unfractionated cell lysate, and only the methionine-containing peptides are isolated and identified by mass spectrometry and database searching. The sorting procedure is based on the concept of diagonal chromatography but adapted for highly complex mixtures. Statistical analysis predicts that we have identified more than 40% of the expressed proteome, including soluble and membrane-bound proteins. Next to highly abundant proteins, we also detected low copy number components such as the E. coli lactose operon repressor, illustrating the high dynamic range. The method is about 100 times more sensitive than two-dimensional gel-based methods and is fully automated. The strongest point, however, is the flexibility in the peptide sorting chemistry, which may target the technique toward quantitative proteomics of virtually every class of peptides containing modifiable amino acids, such as phosphopeptides, amino-terminal peptides, etc., adding a new dimension to future proteome research.     

Analysis of the urine proteome via a combination of multi-dimensional approaches

Urine is a biological fluid that is non-invasively and easily harvested, and exhibits high stability from the proteomics point of view. At the downside, the overall low protein content of urine as well as the presence of low- and high-abundance proteins underscores the need for protein enrichment. As a continuation of previous efforts towards the comprehensive characterization of the urine proteome, the current study targeted the mining of urine proteins through the combined application of different protein separation methodologies, specifically, liquid chromatography and preparative electrophoresis along with 1D gel electrophoresis and protein identification by mass spectrometry. In order to enhance comparison and integration of different experimental data sets, the "standard" urine sample developed within the European Kidney and Urine Proteomics (EuroKUP) COST Action, was employed. As a contribution to the existing knowledge, we focused on maintaining and providing information about experimental mass of the identified proteins as well as information pertaining to their relative abundance--as allowed by technical limitations--thus providing an initial view of different isoforms representation and facilitating their future characterization. The difficulties in comparing proteome mining data sets become once more evident, underscoring the need for adopting standardized ways for data reporting as well as for potential new approaches for data analysis involving a thorough investigation of received information at the peptide level.     

Web-accessible proteome databases for microbial research

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.     

Analysis of the xylem sap proteome of Brassica oleracea reveals a high content in secreted proteins

Xylem plays a major role in plant development and is considered part of the apoplast. Here, we studied the proteome of Brassica oleracea cv Bartolo and compared it to the plant cell wall proteome of another Brassicaceae, the model plant Arabidopsis thaliana. B. oleracea was chosen because it is technically difficult to harvest enough A. thaliana xylem sap for proteomic analysis. We studied the whole proteome and an N-glycoproteome obtained after Concanavalin A affinity chromatography. Altogether, 189 proteins were identified by LC-MS/MS using Brassica EST and cDNA sequences. A predicted signal peptide was found in 164 proteins suggesting that most proteins of the xylem sap are secreted. Eighty-one proteins were identified in the N-glycoproteome, with 25 of them specific of this fraction, suggesting that they were concentrated during the chromatography step. All the protein families identified in this study were found in the cell wall proteomes. However, proteases and oxido-reductases were more numerous in the xylem sap proteome, whereas enzyme inhibitors were rare. The origin of xylem sap proteins is discussed. All the experimental data including the MS/MS data were made available in the WallProtDB cell wall proteomic database.     

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.     

Recent development of multi-dimensional chromatography strategies in proteome research

As a complementary approach to two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), multi-dimensional chromatography separation methods have been widely applied in all kinds of biological sample investigations. Multi-dimensional liquid chromatography (MDLC) coupled with bio-mass spectrometry (MS) is playing important roles in proteome research due to its high speed, high resolution and high sensitivity. Proteome analysis strategies mainly include bottom-up and top-down approaches which carry out biological sample separation based on peptide and protein levels, respectively. Electrophoretic methods combined with liquid chromatography like IEF-HPLC and HPLC-SDS-PAGE have been successful applied for protein separations. As for MDLC strategy, ion-exchange chromatography (IEX) together with reversed phase liquid chromatography (RPLC) is still a most widely used chromatography in proteome analysis, other chromatographic methods are also frequently used in protein pre-fractionations, while affinity chromatography is usually adopted for specific functional protein analysis. Recent MDLC technologies and applications to variety of proteome analysis have been achieved great development. A digest peptide-based approach as so-called "bottom-up" and intact protein-based approach "top-down" analysis of proteome samples were briefly reviewed in this paper. The diversity of combinations of different chromatography modes to set up MDLC systems was demonstrated and discussed. Novel developments of MDLC techniques such as high-abundance protein depletion and chromatography array were also included in this review.     

Expanding the subproteome of the inner mitochondria using protein separation technologies: one- and two-dimensional liquid chromatography and two-dimensional gel electrophoresis

Currently no single proteomics technology has sufficient analytical power to allow for the detection of an entire proteome of an organelle, cell, or tissue. One approach that can be used to expand proteome coverage is the use of multiple separation technologies especially if there is minimal overlap in the proteins observed by the different methods. Using the inner mitochondrial membrane subproteome as a model proteome, we compared for the first time the ability of three protein separation methods (two-dimensional liquid chromatography using the ProteomeLab PF 2D Protein Fractionation System from Beckman Coulter, one-dimensional reversed phase high performance liquid chromatography, and two-dimensional gel electrophoresis) to determine the relative overlap in protein separation for these technologies. Data from these different methods indicated that a strikingly low number of proteins overlapped with less than 24% of proteins common between any two technologies and only 7% common among all three methods. Utilizing the three technologies allowed the creation of a composite database totaling 348 non-redundant proteins. 82% of these proteins had not been observed previously in proteomics studies of this subproteome, whereas 44% had not been identified in proteomics studies of intact mitochondria. Each protein separation method was found to successfully resolve a unique subset of proteins with the liquid chromatography methods being more suited for the analysis of transmembrane domain proteins and novel protein discovery. We also demonstrated that both the one- and two-dimensional LC allowed for the separation of the alpha-subunit of F1F0 ATP synthase that differed due to a change in pI or hydrophobicity.     

Protein and peptide fractionation, enrichment and depletion: tools for the complex proteome

The identification, quantitation and global characterisation of all proteins within a given proteome are extremely challenging. This is due to the absolute detection limits of technology as well as the dynamic range in expression of proteins; and the extreme diversity and heterogeneity of the proteome. To overcome such issues, the use of separation technologies has played a critical role in reducing sample complexity. To date, a plethora of chromatographic and electrophoretic fractionation tools have evolved over the years assisting in simplifying complex protein and peptide mixtures. Here, we review a range of these technologies highlighting the challenges of protein and peptide analysis in the context of proteome research and some of the advantages and disadvantages of present techniques.