Protein expression profiling of CLL B cells using replicate off-line strong cation exchange chromatography and LC-MS/MS

In this study we use replicate 2D-LC-MS/MS analyses of crude membranes from B cells derived from a patient with chronic lymphocytic leukemia (CLL) to examine the protein expression profile of CLL B cells. Protein identifications made by replicate 2D-LC-MS/MS analysis of tryptic peptides from detergent solubilized B cell membrane proteins, as well as replicate LC-MS/MS analysis of single off-line strong cation exchange chromatography (SCX) fractions, were analyzed. We show that despite the variance in SCX, capillary LC, and the data-dependent selection of precursor ions, an overlap of 64% between proteins identified in replicate runs was achieved for this system.     

Shotgun proteome analysis utilising mixed mode (reversed phase‐anion exchange chromatography) in conjunction with reversed phase liquid chromatography mass spectrometry analysis

The 2‐D peptide separations employing mixed mode reversed phase anion exchange (MM (RP‐AX)) HPLC in the first dimension in conjunction with RP chromatography in the second dimension were developed and utilised for shotgun proteome analysis. Compared with strong cation exchange (SCX) typically employed for shotgun proteomic analysis, peptide separations using MM (RP‐AX) revealed improved separation efficiency and increased peptide distribution across the elution gradient. In addition, improved sample handling, with no significant reduction in the orthogonality of the peptide separations was observed. The shotgun proteomic analysis of a mammalian nuclear cell lysate revealed additional proteome coverage (2818 versus 1125 unique peptides and 602 versus 238 proteins) using the MM (RP‐AX) compared with the traditional SCX hyphenated to RP‐LC‐MS/MS. The MM analysis resulted in approximately 90% of the unique peptides identified present in only one fraction, with a heterogeneous peptide distribution across all fractions. No clustering of the predominant peptide charge states was observed during the gradient elution. The application of MM (RP‐AX) for 2‐D LC proteomic studies was also extended in the analysis of iTRAQ‐labelled HeLa and cyanobacterial proteomes using nano‐flow chromatography interfaced to the MS/MS. We demonstrate MM (RP‐AX) HPLC as an alternative approach for shotgun proteomic studies that offers significant advantages over traditional SCX peptide separations.     

Equivalence of Protein Inventories Obtained from Formalin-fixed Paraffin-embedded and Frozen Tissue in Multidimensional Liquid Chromatography-Tandem Mass Spectrometry Shotgun Proteomic Analysis

Formalin-fixed paraffin-embedded (FFPE) tissue specimens comprise a potentially valuable resource for retrospective biomarker discovery studies, and recent work indicates the feasibility of using shotgun proteomics to characterize FFPE tissue proteins. A critical question in the field is whether proteomes characterized in FFPE specimens are equivalent to proteomes in corresponding fresh or frozen tissue specimens. Here we compared shotgun proteomic analyses of frozen and FFPE specimens prepared from the same colon adenoma tissues. Following deparaffinization, rehydration, and tryptic digestion under mild conditions, FFPE specimens corresponding to 200 μg of protein yielded ∼400 confident protein identifications in a one-dimensional reverse phase liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The major difference between frozen and FFPE proteomes was a decrease in the proportions of lysine C-terminal to arginine C-terminal peptides observed, but these differences had little effect on the proteins identified. No covalent peptide modifications attributable to formaldehyde chemistry were detected by analyses of the MS/MS datasets, which suggests that undetected, cross-linked peptides comprise the major class of modifications in FFPE tissues. Fixation of tissue for up to 2 days in neutral buffered formalin did not adversely impact protein identifications. Analysis of archival colon adenoma FFPE specimens indicated equivalent numbers of MS/MS spectral counts and protein group identifications from specimens stored for 1, 3, 5, and 10 years. Combination of peptide isoelectric focusing-based separation with reverse phase LC-MS/MS identified 2554 protein groups in 600 ng of protein from frozen tissue and 2302 protein groups from FFPE tissue with at least two distinct peptide identifications per protein. Analysis of the combined frozen and FFPE data showed a 92% overlap in the protein groups identified. Comparison of gene ontology categories of identified proteins revealed no bias in protein identification based on subcellular localization. Although the status of posttranslational modifications was not examined in this study, archival samples displayed a modest increase in methionine oxidation, from ∼17% after one year of storage to ∼25% after 10 years. These data demonstrate the equivalence of proteome inventories obtained from FFPE and frozen tissue specimens and provide support for retrospective proteomic analysis of FFPE tissues for biomarker discovery.Formalin-fixed paraffin-embedded (FFPE)¹ tissue samples are routinely prepared during the pathological characterization of clinical specimens and are abundantly available in pathology archives worldwide. The fixation process yields clinically relevant samples that can be stored at ambient temperature and are suitable for pathological examination by light microscopy even after years in storage. Given the wealth of clinical data associated with specimens collected over a span of decades, such as patient treatment regimens and outcomes, FFPE tissue represents a potentially valuable resource for biomarker discovery through retrospective analysis (1, 2).However, fixation of tissue in formalin leads to significant cross-linking among proteins and other biomolecules, rendering the samples incompatible with many biochemical analyses. Immunohistochemical (IHC) analysis of FFPE tissue has been conducted since the 1970s using either proteolysis or protein denaturants to expose antigenic regions of proteins (3, 4). Since the 1990s, detection of antigens in FFPE tissue has been improved through the development of so-called antigen retrieval techniques (5, 6). These methods involve application of heat in the presence of any of a variety of buffers resulting in the cleavage of methylene bridges formed during the course of fixation (2).Despite their utilization for IHC analysis, FFPE tissue samples have been largely overlooked in proteomics studies, due to the assumption that tissue fixation would make proteomic analysis intractable. Recent work appears to refute this notion. In 2005, Hood et al. (7) first described the successful application of shotgun proteome analysis to FFPE tissue. Using laser capture microdissected cells and an optimized extraction method, hundreds of proteins were identified from a cancerous prostate lesion and benign prostate hyperplasia, thus opening the door to comparative proteomic analyses of FFPE tissue. Moreover, the same study showed that the numbers and identities of proteins observed were remarkably similar when applying the method to frozen and FFPE mouse liver, thus lending support to the use of FFPE tissue in biomarker discovery studies. Since the initial demonstration of its feasibility, FFPE tissues from diverse origins including breast, liver, kidney, lymphoma, and bone successfully have been subjected to proteomic analyses (8–14).Although this work suggests the feasibility of biomarker discovery from FFPE tissue, most of these previous studies have been performed on small amounts of material with one-dimensional reverse phase liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods. The use of multidimensional peptide separations can extend the dynamic range of the LC-MS/MS analyses to detect lower abundance proteins. Recently, the use of capillary isotachophoresis as the first dimension in a multidimensional peptide separation strategy for analyzing FFPE tissue was described (8). In this study, thousands of proteins were identified out of <4 μg of digest from FFPE human liver sections. However, the apparatus used was an in-house, custom-designed system, not readily accessible to other laboratories. In several of these studies, proteins identified by a single peptide were accepted as valid identifications. Use of single peptide-based identifications elevates the probability of false positive protein identifications, and these identifications often constitute the majority of protein identifications (15).The equivalence of fresh/frozen and FFPE tissue proteomes is a critical issue in evaluating the suitability of employing FFPE tissues for biomarker discovery by comparative proteomic analyses. Hood et al. (7) and Guo et al. (14) reported comparisons from analyses of paired fresh and frozen tissue specimens. Guo et al. (14) reported an apparent overlap of 83% in protein identifications between FFPE and frozen brain tissue specimens, whereas Hood et al. (7) did not report the degree of overlap, but found that FFPE mouse liver tissue yielded about 88% of the identifications determined for frozen mouse liver tissue. The majority of protein identifications in both studies were based on single peptide assignments. These investigations did not explicitly address the effect of formaldehyde-derived modifications on the inventories of identified peptides.An unexplored question with FFPE tissue specimens is the extent to which normal variability in fixation process and storage duration affect the proteomes observed. The duration of tissue fixation is not highly standardized and may vary from hours to several days. One of the most attractive features of FFPE specimens is the opportunity for retrospective biomarker discovery, but the effects of storage for many years on tissue proteomes remains unknown.Here, we address these questions through detailed comparative studies of the analysis of fresh frozen and FFPE tissues by LC-MS/MS-based shotgun proteomics. We used the same fresh tissue specimens to prepare both frozen and FFPE samples for paired comparisons. We evaluated conditions for tissue lysis and digestion and the effects of fixation time and storage duration on the number of protein IDs obtained during shotgun proteomic analysis of FFPE tissue. We also characterized the differences in peptides observed between fixed and frozen specimens in an effort to understand the effect of fixation from a practical biomarker discovery standpoint. Furthermore, we compared analyses of fresh frozen and FFPE colon adenoma tissue by multidimensional LC-MS/MS using gel-based isoelectric focusing of peptides (Fig. 1). The results demonstrate a remarkable overlap in the number and identities of proteins between the fixed and frozen tissue and indicate that variations in duration of fixation and storage have a minimal effect on protein inventories obtained by shotgun proteomic analysis. The data indicate essential equivalence between protein inventories obtained from fresh frozen and FFPE tissue specimens by shotgun proteomics and validate the use of FFPE tissue specimens for biomarker discovery.Open in a separate windowFig. 1.Strategy for multidimensional LC-MS/MS analysis of FFPE tissue.     

A novel four-dimensional strategy combining protein and peptide separation methods enables detection of low-abundance proteins in human plasma and serum proteomes

A novel strategy, termed protein array pixelation, is described for comprehensive profiling of human plasma and serum proteomes. This strategy consists of three sequential high-resolution protein prefractionation methods (major protein depletion, solution isoelectrofocusing, and 1-DE) followed by nanocapillary RP tryptic peptide separation prior to MS/MS analysis. The analysis generates a 2-D protein array where each pixel in the array contains a group of proteins with known pI and molecular weight range. Analysis of the HUPO samples using this strategy resulted in 575 and 2890 protein identifications from plasma and serum, respectively, based on HUPO-approved criteria for high-confidence protein assignments. Most importantly, a substantial number of low-abundance proteins (low ng/mL - pg/mL range) were identified. Although larger volumes were used in initial prefractionation steps, the protein identifications were derived from fractions equivalent to approximately 0.6 microL (45 microg) of plasma and 2.4 microL (204 microg) of serum. The time required for analyzing the entire protein array for each sample is comparable to some published shotgun analyses of plasma and serum proteomes. Therefore, protein array pixelation is a highly sensitive method capable of detecting proteins differing in abundance by up to nine orders of magnitude. With further refinement, this method has the potential for even higher capacity and higher throughput.     

Differential recovery of peptides from sample tubes and the reproducibility of quantitative proteomic data

Differential recovery of peptides due to nonspecific adsorption can seriously compromise reproducibility and quality of proteomic data for peptide analyses by liquid chromatography-mass spectrometry (LC-MS). This study demonstrates large variations in reproducibility and quantitation of LC-MS data for peptides derived from tryptic digests of BSA upon storage in different sample tubes. Notably, we show that highly improved consistency and lower errors in quantitation of BSA tryptic peptides in replicate measurements is achieved with low-retention tubes compared to regular eppendorf tubes. Furthermore, qualitative differences in peptides detected by LC-MS were observed in the two types of storage tubes. These results illustrate the necessity for careful evaluation of storage vessels and conditions to minimize variability in sample quality for LC-MS experiments.     

Evaluation of reproducibility of protein identification results after multidimensional human serum protein separation

We developed a gel- and label-free proteomics platform for comparative studies of human serum. The method involves the depletion of the six most abundant proteins, protein fractionation by Off-Gel IEF and RP-HPLC, followed by tryptic digestion, LC-MS/MS, protein identification, and relative quantification using probabilistic peptide match score summation (PMSS). We evaluated performance and reproducibility of the complete platform and the individual dimensions, by using chromatograms of the RP-HPLC runs, PMSS based abundance scores and abundance distributions as objective endpoints. We were interested if a relationship exists between the quantity ratio and the PMSS score ratio. The complete analysis was performed four times with two sets of serum samples containing different concentrations of spiked bovine beta-lactoglobulin (0.1 and 0.3%, w/w). The two concentrations resulted in significantly differing PMSS scores when compared to the variability in PMSS scores of all other protein identifications. We identified 196 proteins, of which 116 were identified four times in corresponding fractions whereof 73 qualified for relative quantification. Finally, we characterized the PMSS based protein abundance distributions with respect to the two dimensions of fractionation and discussed some interesting patterns representing discrete isoforms. We conclude that combination of Off-Gel electrophoresis (OGE) and HPLC is a reproducible protein fractionation technique, that PMSS is applicable for relative quantification, that the number of quantifiable proteins is always smaller than the number of identified proteins and that reproducibility of protein identifications should supplement probabilistic acceptance criteria.     

High pH reversed‐phase chromatography as a superior fractionation scheme compared to off‐gel isoelectric focusing for complex proteome analysis

MS/MS is the technology of choice for analyzing complex protein mixtures. However, due to the intrinsic complexity and dynamic range present in higher eukaryotic proteomes, prefractionation is an important step to maximize the number of proteins identified. Off‐gel IEF (OG‐IEF) and high pH RP (Hp‐RP) column chromatography have both been successfully utilized as a first‐dimension peptide separation technique in shotgun proteomic experiments. Here, a direct comparison of the two methodologies was performed on ex vivo peripheral blood mononuclear cell lysate. In 12‐fraction replicate analysis, Hp‐RP resulted in more peptides and proteins identified than OG‐IEF fractionation. Distributions of peptide pIs and hydropathy did not reveal any appreciable bias in either technique. Resolution, defined here as the ability to limit a specific peptide to one particular fraction, was significantly better for Hp‐RP. This leads to a more uniform distribution of total and unique peptides for Hp‐RP across all fractions collected. These results suggest that fractionation by Hp‐RP over OG‐IEF is the better choice for typical complex proteome analysis.     

Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) versus strong cation exchange (SCX) for fractionation of iTRAQ-labeled peptides

The iTRAQ technique is popular for the comparative analysis of proteins in different complex samples. To increase the dynamic range and sensitivity of peptide identification in shotgun proteomics, SCX chromatography is generally used for the fractionation of iTRAQ-labeled peptides before LC-MS/MS analysis. However, SCX suffers from clustering of similarly charged peptides and the need to desalt fractions. In this report, SCX is compared with the alternative ERLIC method for fractionating iTRAQ-labeled peptides. The simultaneous effect of electrostatic repulsion and hydrophilic interaction in ERLIC results in peptide elution in order of decreasing pI and GRAVY values (increasing polarity). Volatile solvents can be used. We applied ERLIC to iTRAQ-labeled peptides from rat liver tissue, and 2745 proteins and 30,016 unique peptides were identified with high confidence from three technical replicates. This was 12.9 and 49.4% higher, respectively, than was obtained using SCX. In addition, ERLIC is appreciably better at the identification of highly hydrophobic peptides. The results indicate that ERLIC is a more convenient and more effective alternative to SCX for the fractionation of iTRAQ-labeled peptides. Quantification data show that both SCX and ERLIC fractionation have no significant effect on protein quantification by iTRAQ.     

Probability-based evaluation of peptide and protein identifications from tandem mass spectrometry and SEQUEST analysis: the human proteome

Large-scale protein identifications from highly complex protein mixtures have recently been achieved using multidimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) and subsequent database searching with algorithms such as SEQUEST. Here, we describe a probability-based evaluation of false positive rates associated with peptide identifications from three different human proteome samples. Peptides from human plasma, human mammary epithelial cell (HMEC) lysate, and human hepatocyte (Huh)-7.5 cell lysate were separated by strong cation exchange (SCX) chromatography coupled offline with reversed-phase capillary LC-MS/MS analyses. The MS/MS spectra were first analyzed by SEQUEST, searching independently against both normal and sequence-reversed human protein databases, and the false positive rates of peptide identifications for the three proteome samples were then analyzed and compared. The observed false positive rates of peptide identifications for human plasma were significantly higher than those for the human cell lines when identical filtering criteria were used, suggesting that the false positive rates are significantly dependent on sample characteristics, particularly the number of proteins found within the detectable dynamic range. Two new sets of filtering criteria are proposed for human plasma and human cell lines, respectively, to provide an overall confidence of >95% for peptide identifications. The new criteria were compared, using a normalized elution time (NET) criterion (Petritis et al. Anal. Chem. 2003, 75, 1039-1048), with previously published criteria (Washburn et al. Nat. Biotechnol. 2001, 19, 242-247). The results demonstrate that the present criteria provide significantly higher levels of confidence for peptide identifications from mammalian proteomes without greatly decreasing the number of identifications.     

Label-free protein quantification using LC-coupled ion trap or FT mass spectrometry: Reproducibility, linearity, and application with complex proteomes

A critical step in protein biomarker discovery is the ability to contrast proteomes, a process referred generally as quantitative proteomics. While stable-isotope labeling (e.g., ICAT, 18O- or 15N-labeling, or AQUA) remains the core technology used in mass spectrometry-based proteomic quantification, increasing efforts have been directed to the label-free approach that relies on direct comparison of peptide peak areas between LC-MS runs. This latter approach is attractive to investigators for its simplicity as well as cost effectiveness. In the present study, the reproducibility and linearity of using a label-free approach to highly complex proteomes were evaluated. Various amounts of proteins from different proteomes were subjected to repeated LC-MS analyses using an ion trap or Fourier transform mass spectrometer. Highly reproducible data were obtained between replicated runs, as evidenced by nearly ideal Pearson's correlation coefficients (for ion's peak areas or retention time) and average peak area ratios. In general, more than 50% and nearly 90% of the peptide ion ratios deviated less than 10% and 20%, respectively, from the average in duplicate runs. In addition, the multiplicity ratios of the amounts of proteins used correlated nicely with the observed averaged ratios of peak areas calculated from detected peptides. Furthermore, the removal of abundant proteins from the samples led to an improvement in reproducibility and linearity. A computer program has been written to automate the processing of data sets from experiments with groups of multiple samples for statistical analysis. Algorithms for outlier-resistant mean estimation and for adjusting statistical significance threshold in multiplicity of testing were incorporated to minimize the rate of false positives. The program was applied to quantify changes in proteomes of parental and p53-deficient HCT-116 human cells and found to yield reproducible results. Overall, this study demonstrates an alternative approach that allows global quantification of differentially expressed proteins in complex proteomes. The utility of this method to biomarker discovery is likely to synergize with future improvements in the detecting sensitivity of mass spectrometers.     

In-gel isoelectric focusing of peptides as a tool for improved protein identification

In the analysis of proteins in complex samples, pre-fractionation is imperative to obtain the necessary depth in the number of reliable protein identifications by mass spectrometry. Here we explore isoelectric focusing of peptides (peptide IEF) as an effective fractionation step that at the same time provides the added possibility to eliminate spurious peptide identifications by filtering for pI. Peptide IEF in IPG strips is fast and sharply confines peptides to their pI. We have evaluated systematically the contribution of pI filtering and accurate mass measurements on the total number of protein identifications in a complex protein mixture (Drosophila nuclear extract). At the same time, by varying Mascot identification cutoff scores, we have monitored the false positive rate among these identifications by searching reverse protein databases. From mass spectrometric analyses at low mass accuracy using an LTQ ion trap, false positive rates can be minimized by filtering of peptides not focusing at their expected pI. Analyses using an LTQ-FT mass spectrometer delivers low false positive rates by itself due to the high mass accuracy. In a direct comparison of peptide IEF with SDS-PAGE as a pre-fractionation step, IEF delivered 25% and 43% more proteins when identified using FT-MS and LTQ-MS, respectively. Cumulatively, 2190 non redundant proteins were identified in the Drosophila nuclear extract at a false positive rate of 0.5%. Of these, 1751 proteins (80%) were identified after peptide IEF and FT-MS alone. Overall, we show that peptide IEF allows to increase the confidence level of protein identifications, and is more sensitive than SDS-PAGE.     

Characterizing complex peptide mixtures using a multi-dimensional liquid chromatography-mass spectrometry system: Saccharomyces cerevisiae as a model system

A rugged, reproducible, multi-dimensional LC-MS system was developed to identify and characterize proteins involved in protein-protein interactions and/or protein complexes. Our objective was to optimize chromatographic parameters for complex protein mixture analyses using automated peptide sequence recognition as an analytical end-point. The chromatographic system uses orthogonal separation mechanisms by employing strong cation exchange (SCX) in the first dimension and reversed phase (RP) in the second dimension. The system is fully automated and sufficiently robust to handle direct injections of protein digests. This system incorporates a streamlined post analysis results comparison, called DBParser, which permitted comprehensive evaluation of sample loading and chromatographic conditions to optimize the performance and reproducibility. Peptides obtained from trypsin digestion of a yeast soluble extract provided an open-ended model system containing a wide variety and dynamic range of components. Conditions are described that resulted in an average (n = 4) of 1489 unique peptide identifications, corresponding to 459 non-redundant protein sequence database records (SDRs) in the 20 microg soluble fraction digest.     

Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins

Quantitative LC-MS/MS assays were designed for tryptic peptides representing 53 high and medium abundance proteins in human plasma using a multiplexed multiple reaction monitoring (MRM) approach. Of these, 47 produced acceptable quantitative data, demonstrating within-run coefficients of variation (CVs) (n = 10) of 2-22% (78% of assays had CV <10%). A number of peptides gave CVs in the range 2-7% in five experiments (10 replicate runs each) continuously measuring 137 MRMs, demonstrating the precision achievable in complex digests. Depletion of six high abundance proteins by immunosubtraction significantly improved CVs compared with whole plasma, but analytes could be detected in both sample types. Replicate digest and depletion/digest runs yielded correlation coefficients (R(2)) of 0.995 and 0.989, respectively. Absolute analyte specificity for each peptide was demonstrated using MRM-triggered MS/MS scans. Reliable detection of L-selectin (measured at 0.67 microg/ml) indicates that proteins down to the microg/ml level can be quantitated in plasma with minimal sample preparation, yielding a dynamic range of 4.5 orders of magnitude in a single experiment. Peptide MRM measurements in plasma digests thus provide a rapid and specific assay platform for biomarker validation, one that can be extended to lower abundance proteins by enrichment of specific target peptides (stable isotope standards and capture by anti-peptide antibodies (SISCAPA)).     

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.     

Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations

Researchers have several options when designing proteomics experiments. Primary among these are choices of experimental method, instrumentation and spectral interpretation software. To evaluate these choices on a proteome scale, we compared triplicate measurements of the yeast proteome by liquid chromatography tandem mass spectrometry (LC-MS/MS) using linear ion trap (LTQ) and hybrid quadrupole time-of-flight (QqTOF; QSTAR) mass spectrometers. Acquired MS/MS spectra were interpreted with Mascot and SEQUEST algorithms with and without the requirement that all returned peptides be tryptic. Using a composite target decoy database strategy, we selected scoring criteria yielding 1% estimated false positive identifications at maximum sensitivity for all data sets, allowing reasonable comparisons between them. These comparisons indicate that Mascot and SEQUEST yield similar results for LTQ-acquired spectra but less so for QSTAR spectra. Furthermore, low reproducibility between replicate data acquisitions made on one or both instrument platforms can be exploited to increase sensitivity and confidence in large-scale protein identifications.     

P23-M Limit of Quantitation for Low-Abundance Proteins in Plasma by Targeted MS

Biomarker discovery results in the creation of candidate lists of potential markers that must be subsequently verified in plasma.¹ The most mature methods at present require abundant protein depletion and fractionation at the protein/peptide levels in order to detect and quantitate low ng/mL concentrations of plasma proteins by stable isotope dilution mass spectrometry. Sample-processing methods with sufficient throughput, recovery, and reproducibility to enable robust detection and quantitation of candidate bio-marker proteins were evaluated by adding five non-native proteins to immunoaffinity-depleted female plasma at varying concentrations (1000, 100, 50, 25, and 10 ng/mL). Each protein was monitored by one or more representative synthetic tryptic peptides labeled with [¹³C₆]leucine or [¹³C₅] valine. Following reduction, carbamidomethylation, and enzymatic digestion, two separate processing paths were compared. In path 1, digested plasma was diluted 1:10 and [¹³C] internal standards were added just prior to direct analysis by multiple reaction monitoring with LC-MS/MS (MRM LC-MS/MS). In path 2, peptides were separated by strong cation exchange, and [¹³C] internal standards were added to corresponding SCX fractions prior to analysis by MRM LC-MS/MS. Detection and quantitation by MRM used the response of at least two product ions from each of the signature peptides. Using processing path 1, we achieved detection and quantitation down to 50 ng/mL in depleted plasma. However, using processing path 2, we achieved detection and quantitation of all spiked proteins, including the non-native protein at 10 ng/mL. While analysis of non-fractionated plasma achieved higher recovery of those proteins detected in both processes, SCX fractionation at the peptide level clearly increases detection and LOQs for potential biomarker proteins in plasma.     

Comparison of alternative analytical techniques for the characterisation of the human serum proteome in HUPO Plasma Proteome Project

Based on the same HUPO reference specimen (C1-serum) with the six proteins of highest abundance depleted by immunoaffinity chromatography, we have compared five proteomics approaches, which were (1) intact protein fractionation by anion-exchange chromatography followed by 2-DE-MALDI-TOF-MS/MS for protein identification (2-DE strategy); (2) intact protein fractionation by 2-D HPLC followed by tryptic digestion of each fraction and microcapillary RP-HPLC/microESI-MS/MS identification (protein 2-D HPLC fractionation strategy); (3) protein digestion followed by automated online microcapillary 2-D HPLC (strong cation-exchange chromatography (SCX)-RPC) with IT microESI-MS/MS; (online shotgun strategy); (4) same as (3) with the SCX step performed offline (offline shotgun strategy) and (5) same as (4) with the SCX fractions reanalysed by optimised nanoRP-HPLC-nanoESI-MS/MS (offline shotgun-nanospray strategy). All five approaches yielded complementary sets of protein identifications. The total number of unique proteins identified by each of these five approaches was (1) 78, (2) 179, (3) 131, (4) 224 and (5) 330 respectively. In all, 560 unique proteins were identified. One hundred and sixty-five proteins were identified through two or more peptides, which could be considered a high-confidence identification. Only 37 proteins were identified by all five approaches. The 2-DE approach yielded more information on the pI-altered isoforms of some serum proteins and the relative abundance of identified proteins. The protein prefractionation strategy slightly improved the capacity to detect proteins of lower abundance. Optimising the separation at the peptide level and improving the detection sensitivity of ESI-MS/MS were more effective than fractionation of intact proteins in increasing the total number of proteins identified. Overall, electrophoresis and chromatography, coupled respectively with MALDI-TOF/TOF-MS and ESI-MS/MS, identified complementary sets of serum proteins.     

Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications

Recent advances in proteomics technologies provide tremendous opportunities for biomarker-related clinical applications; however, the distinctive characteristics of human biofluids such as the high dynamic range in protein abundances and extreme complexity of the proteomes present tremendous challenges. In this review we summarize recent advances in LC-MS-based proteomics profiling and its applications in clinical proteomics as well as discuss the major challenges associated with implementing these technologies for more effective candidate biomarker discovery. Developments in immunoaffinity depletion and various fractionation approaches in combination with substantial improvements in LC-MS platforms have enabled the plasma proteome to be profiled with considerably greater dynamic range of coverage, allowing many proteins at low ng/ml levels to be confidently identified. Despite these significant advances and efforts, major challenges associated with the dynamic range of measurements and extent of proteome coverage, confidence of peptide/protein identifications, quantitation accuracy, analysis throughput, and the robustness of present instrumentation must be addressed before a proteomics profiling platform suitable for efficient clinical applications can be routinely implemented.     

Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins

Prefractionations of proteins prior to their proteolysis, chromatography, and MS/MS analyses help reduce complexity and increase the yield of protein identifications. A number of methods were evaluated here for prefractionating serum samples distributed to the participating laboratories as part of the human Plasma Proteome Project. These methods include strong cation exchange (SCX) chromatography, slicing of SDS-PAGE gel bands, and liquid-phase IEF of the proteins. The fractionated proteins were trypsinized and the resulting peptides were resolved and analyzed by multidimensional protein identification technology coupled to IT MS/MS. The MS/MS spectra were clustered, combined, and searched against the IPI protein databank using Pep-Miner. The identification results were evaluated for the efficacy of the different prefractionation methodologies to identify larger numbers of proteins at higher confidence and to achieve the best coverage of the proteins with the identified peptides. Prefractionation based on SCX resulted in the largest number of identified proteins, followed by gel slices and then the liquid-phase IEF. An important observation was that each of the methods revealed a set of unique proteins, some identified with high confidence. Therefore, for comprehensive identification of the serum proteins, several different prefractionation approaches should be used in parallel.