Analysis of human liver proteome using replicate shotgun strategy

In this study, a liquid-based shotgun strategy was used to comprehensively identify the expression of human liver proteome. Proteins were extracted from human liver tissue and digested in-solution. The tryptic digest mixture was desalted and separated by off-line strong cation exchange (SCX) chromatography with a 60-min elution. The MS/MS spectra were acquired in data-dependent mode after an RP chromatographic separation combined with linear IT MS analysis. To obtain the most comprehensive human liver proteome, each SCX fraction was run six times in RPLC MS/MS manner. Finally, more than 6,000,000 MS/MS spectra were collected. Using a relatively strict filter criteria, 24,311 proteins (48.42% of the predicted human proteome from human International Protein Index (IPI) protein database 3.07) corresponding to 13,150 nonredundant proteins were successfully identified, in which 7001 proteins (53.24%) were identified by two or more peptides, which could be considered as a high-confident dataset. Among the 6149 proteins (46.76%) identified by single peptide, 3812 proteins (61.99%) were detected more than twice in six repeated runs. Comparative analysis between different runs shows that the overlap of identified proteins between any two runs ranged from 25 to 44%. Of the nonredundant proteins identified, 8919 proteins (67.83%) were detected more than twice and 4231 proteins (32.17%) were detected only once in six RPLC MS/MS runs. The Gene Ontology annotation shows that the identified proteins come from various subcellular components. In addition, a large number of low abundant proteins were identified. The dynamic range of the approach reached at least nine orders of magnitude by estimating the concentration of proteins.     

Clinical-scale high-throughput human plasma proteome analysis: lung adenocarcinoma

Clinical proteomics requires the stable and reproducible analysis of a large number of human samples. We report a high-throughput comprehensive protein profiling system comprising a fully automated, on-line, two-dimensional microflow liquid chromatography/tandem mass spectrometry (2-D microLC-MS/MS) system for use in clinical proteomics. A linear ion-trap mass spectrometer (ITMS) also known as a 2-D ITMS instrument, which is characterized by high scan speed, was incorporated into the microLC-MS/MS system in order to obtain highly improved sensitivity and resolution in MS/MS acquisition. This system was used to evaluate bovine serum albumin and human 26S proteasome. Application of these high-throughput microLC conditions and the 2-D ITMS resulted in a 10-fold increase in sensitivity in protein identification. Additionally, peptide fragments from the 26S proteasome were identified three-fold more efficiently than by the conventional 3-D ITMS instrument. In this study, the 2-D microLC-MS/MS system that uses linear 2-D ITMS has been applied for the plasma proteome analysis of a few samples from healthy individuals and lung adenocarcinoma patients. Using the 2-D and 1-D microLC-MS/MS analyses, approximately 250 and 100 different proteins were detected, respectively, in each HSA- and IgG-depleted sample, which corresponds to only 0.4 microL of blood plasma. Automatic operation enabled the completion of a single run of the entire 1-D and 2-D microLC-MS/MS analyses within 11 h. Investigation of the data extracted from the protein identification datasets of both healthy and adenocarcinoma groups revealed that several of the group-specific proteins could be candidate protein disease markers expressed in the human blood plasma. Consequently, it was demonstrated that this high-throughput microLC-MS/MS protein profiling system would be practically applicable to the discovery of protein disease markers, which is the primary objective in clinical plasma proteome projects.     

Validation of peptide MS/MS spectra using metabolic isotope labeling for spectral matching-based shotgun proteome analysis

We report an isotope labeling shotgun proteome analysis strategy to validate the spectrum-to-sequence assignments generated by using sequence-database searching for the construction of a more reliable MS/MS spectral library. This strategy is demonstrated in the analysis of the E. coli K12 proteome. In the workflow, E. coli cells were cultured in normal and (15)N-enriched media. The differentially labeled proteins from the cell extracts were subjected to trypsin digestion and two-dimensional liquid chromatography quadrupole time-of-flight tandem mass spectrometry (2D-LC QTOF MS/MS) analysis. The MS/MS spectra of the two samples were individually searched using Mascot against the E. coli proteome database to generate lists of peptide sequence matches. The two data sets were compared by overlaying the spectra of unlabeled and labeled matches of the same peptide sequence for validation. Two cutoff filters, one based on the number of common fragment ions and another one on the similarity of intensity patterns among the common ions, were developed and applied to the overlaid spectral pairs to reject the low quality or incorrectly assigned spectra. By examining 257,907 and 245,156 spectra acquired from the unlabeled and (15)N-labeled samples, respectively, an experimentally validated MS/MS spectral library of tryptic peptides was constructed for E. coli K12 that consisted of 9,302 unique spectra with unique sequence and charge state, representing 7,763 unique peptide sequences. This E. coli spectral library could be readily expanded, and the overall strategy should be applicable to other organisms. Even with this relatively small library, it was shown that more peptides could be identified with higher confidence using the spectral search method than by sequence-database searching.     

膜整合蛋白质的“鸟枪法”蛋白质组学分析策略

疾病状态下生物膜表面蛋白质分子标记的表达量和修饰状态会发生改变。但由于其低丰度和不易溶解等特性,制约了膜蛋白质组学的研究,同时也制约了相关药物靶标的设计。近年来,为克服这些困难,学者们提出了"鸟枪法"的膜蛋白质组学研究策略。基于此,本文论述了"鸟枪法"的蛋白质组学分析的基本过程及其后续的部分改进工作。随着新的策略不断被采用,更多膜蛋白质的拓扑学特征和功能的相关研究一定会走上新的台阶。     

Analysis of the human serum proteome

Changes in serum proteins that signal histopathological states, such as cancer, are useful diagnostic and prognostic biomarkers. Unfortunately, the large dynamic concentration range of proteins in serum makes it a challenging proteome to effectively characterize. Typically, methods to deplete highly abundant proteins to decrease this dynamic protein concentration range are employed, yet such depletion results in removal of important low abundant proteins. A multi-dimensional peptide separation strategy utilizing conventional separation techniques combined with tandem mass spectrometry (MS/MS) was employed for a proteome analysis of human serum. Serum proteins were digested with trypsin and resolved into 20 fractions by ampholyte-free liquid phase isoelectric focusing. These 20 peptide fractions were further fractionated by strong cation-exchange chromatography, each of which was analyzed by microcapillary reversed-phase liquid chromatography coupled online with MS/MS analysis. This investigation resulted in the identification of 1444 unique proteins in serum. Proteins from all functional classes, cellular localization, and abundance levels were identified. This study illustrates that a majority of lower abundance proteins identified in serum are present as secreted or shed species by cells as a result of signalling, necrosis, apoptosis, and hemolysis. These findings show that the protein content of serum is quite reflective of the overall profile of the human organism and a conventional multidimensional fractionation strategy combined with MS/MS is entirely capable of characterizing a significant fraction of the serum proteome. We have constructed a publicly available human serum proteomic database (http://bpp.nci.nih.gov) to provide a reference resource to facilitate future investigations of the vast archive of pathophysiological content in serum. These authors contributed equally to this work.     

Extent of modifications in human proteome samples and their effect on dynamic range of analysis in shotgun proteomics

The complexity of the human proteome, already enormous at the organism level, increases further in the course of the proteome analysis due to in vitro sample evolution. Most of in vitro alterations can also occur in vivo as post-translational modifications. These two types of modifications can only be distinguished a posteriori but not in the process of analysis, thus rendering necessary the analysis of every molecule in the sample. With the new software tool ModifiComb applied to MS/MS data, the extent of modifications was measured in tryptic mixtures representing the full proteome of human cells. The estimated level of 8-12 modified peptides per each unmodified tryptic peptide present at >or=1% level is approaching one modification per amino acid on average. This is a higher modification rate than was previously thought, posing an additional challenge to analytical techniques. The solution to the problem is seen in improving sample preparation routines, introducing dynamic range-adjusted thresholds for database searches, using more specific MS/MS analysis using high mass accuracy and complementary fragmentation techniques, and revealing peptide families with identification of additional proteins only by unfamiliar peptides. Extensive protein separation prior to analysis reduces the requirements on speed and dynamic range of a tandem mass spectrometer and can be a viable alternative to the shotgun approach.     

Enhanced analysis of the mouse plasma proteome using cysteine-containing tryptic glycopeptides

A comprehensive understanding of the mouse plasma proteome is important for studies using mouse models to identify protein markers of human disease. To enhance our analysis of the mouse plasma proteome, we have developed a method for isolating low-abundance proteins using a cysteine-containing glycopeptide strategy. This method involves two orthogonal affinity capture steps. First, glycoproteins are coupled to an azlactone copolymer gel using hydrazide chemistry and cysteine residues are then biotinylated. After trypsinization and extensive washing, tethered N-glycosylated tryptic peptides are released from the gel using PNGase F. Biotinylated cysteinyl-containing glycopeptides are then affinity selected using a monomeric avidin gel and analyzed by LC-MS/MS. We have applied the method to a proteome analysis of mouse plasma. In two independent analyses using 200 muL each of C57BL mouse plasma, 51 proteins were detected. Only 42 proteins were seen when the same plasma sample was analyzed by glycopeptides only. A total of 104 N-glycosylation sites were identified. Of these, 17 sites have hitherto not been annotated in the Swiss-Prot database whereas 48 were considered probable, potential, or by similarity - i.e., based on little or no experimental evidence. We show that analysis by cysteine-containing glycopeptides allows detection of low-abundance proteins such as the epidermal growth factor receptor, the Vitamin K-dependent protein Z, the hepatocyte growth factor activator, and the lymphatic endothelium-specific hyaluronan receptor as these proteins were not detected in the glycopeptide control analysis.     

Online multidimensional separation with biphasic monolithic capillary column for shotgun proteome analysis

A biphasic monolithic capillary column with 10 cm segment of strong-cation exchange monolith and 65 cm segment of reversed-phase monolith was prepared within a single 100 microm i.d. capillary. Separation performance of this column was evaluated by a five-cycle online multidimensional separation of 10 microg tryptic digest of yeast proteins using nanoflow liquid chromatography coupled with tandem mass spectrometry, and it took 12 h for whole separation under the operating pressure only approximately 900 psi. Totally, 780 distinct proteins were positively identified through assignment of 2953 unique peptides at false-positive rate less than 1%. The good separation performance of this biphasic column was largely attributed to the good orthogonality of the strong-cation exchange monolith and reversed-phase monolith for multidimensional separation.     

Development of efficient protein extraction methods for shotgun proteome analysis of formalin-fixed tissues

There are vast archives of formalin-fixed tissues spanning many conceivable conditions such as different diseases, time courses, and different treatment and allowing acquisition of the necessary numbers of samples to carry out biomarker discovery study. However, the conventional protein analysis approach is not applicable for the analysis of proteins in the formalin-fixed tissue because the formalin fixation process resulted in the cross-linking of proteins, and thus, intact proteins cannot be efficiently extracted. In this study, several protocols were investigated to extract proteins from formalin-fixed mouse liver tissue for shotgun proteome analysis. It was found that incubation of tissue in a lysis buffer containing 6 M guanidine hydrochloride at high temperature led to the highest protein yield and the largest number of proteins identified. The peptides and proteins identified from formalin-fixed tissue were first comprehensively compared with those identified from frozen-fresh tissue. It was found that a majority of peptides identified from fixed tissue were unmodified and proteome coverage for the analysis of fixed tissue was not obviously compromised by the formalin fixation process. Valuable proteome information could be obtained by shotgun proteome analysis of formalin-fixed tissue, which presents a new approach for disease biomarker discovery.     

High confidence and sensitivity four-dimensional fractionation for human plasma proteome analysis

Reducing the complexity of plasma proteome through complex multidimensional fractionation protocols is critical for the detection of low abundance proteins that have the potential to be the most specific disease biomarkers. Therefore, we examined a four dimension profiling method, which includes low abundance protein enrichment, tryptic digestion and peptide fractionation by IEF, SCX and RP-LC. The application of peptide pI filtering as an additional criterion for the validation of the identifications allows to minimize the false discovery rate and to optimize the best settings of the protein identification database search engine. This sequential approach allows for the identification of low abundance proteins, such as angiogenin (10^?9 g/L), pigment epithelium growth factor (10^?8 g/L), hepatocyte growth factor activator (10^?7 g/L) and thrombospondin-1 (10^?6 g/L), having concentrations similar to those of many other growth factors and cytokines involved in disease pathophysiology.     

In-depth analysis of the human CSF proteome using protein prefractionation

The identification of disease markers in human body fluids requires an extensive and thorough analysis of its protein constituents. In the present study, we have extended our analysis of the human cerebrospinal fluid (CSF) proteome using protein prefractional followed by shotgun mass spectrometry. After the removal of abundant protein components from the mixture with the help of immunodepletion affinity chromatography, we used either anion exchange chromatography or sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to further subfractionate the proteins present in CSFs. Each protein subfraction was enzyme digested and analyzed by tandem mass spectrometry and the resulting data evaluated using the Spectrum Mill software. Different subfractionation methods resulted in the identification of a grant total of 259 proteins in CSF from a patient with normal pressure hydrocephalus. The greatest number of protein, 240 in total, were identified after prefractionating the CSF proteins by immunodepletion and SDS-PAGE. Immuno-depletion combined with anion exchange fractionation resulted in 112 proteins and 74 proteins were found when only immunodepletion of the CSF samples was carried out. All methods used showed a significant increase in the number of identified proteins as compared with nondepleted and unfractionated CSF sample analysis, which yielded only 38 protein identifications. The present work establishes a platform for future studies aimed at a detailed comparative proteome analysis of CSFs from different groups of patients suffering from various psychiatric and neurological disorders.     

Characterization of human tear proteome using multiple proteomic analysis techniques

Tear proteome profiling may generate useful information for the understanding of the interaction between an eye and its contacting objects, such as a contact lens or a lens implant. This is important for designing improved eye-care devices and maintaining the health of an eye. Proteome profiles of tear fluids may also be used for disease diagnosis and prognosis. However, only a small volume of tear fluid (<5 microL) can be collected in a clinical laboratory under normal operational conditions, which makes proteome profiling a challenge. In this work we apply several proteomic analysis techniques, including gel-based and solution-based approaches with LC-ESI and LC-MALDI MS and MS/MS to gauge the relative merits of producing proteome profiles and to generate as broad a coverage of the tear proteome as possible from this small amount of sample. It is shown that a total of 54 proteins can be confidently identified using less than 5 microL of tear fluid. Of these, 44 proteins can be detected by LC-MALDI MS alone with a consumption of 2 microL of tear fluid. Furthermore, LC-MALDI can be used to determine post-translational modifications (PTMs), such as glycosylation and phosphorylation, without any sample enrichment or treatment. This work represents one of the most extensive proteome profiles (i.e., proteins identified and PTMs characterized) generated from tear fluids using clinically relevant amounts of sample.     

The human plasma proteome: history,character, and diagnostic prospects

The human plasma proteome holds the promise of a revolution in disease diagnosis and therapeutic monitoring provided that major challenges in proteomics and related disciplines can be addressed. Plasma is not only the primary clinical specimen but also represents the largest and deepest version of the human proteome present in any sample: in addition to the classical "plasma proteins," it contains all tissue proteins (as leakage markers) plus very numerous distinct immunoglobulin sequences, and it has an extraordinary dynamic range in that more than 10 orders of magnitude in concentration separate albumin and the rarest proteins now measured clinically. Although the restricted dynamic range of conventional proteomic technology (two-dimensional gels and mass spectrometry) has limited its contribution to the list of 289 proteins (tabulated here) that have been reported in plasma to date, very recent advances in multidimensional survey techniques promise at least double this number in the near future. Abundant scientific evidence, from proteomics and other disciplines, suggests that among these are proteins whose abundances and structures change in ways indicative of many, if not most, human diseases. Nevertheless, only a handful of proteins are currently used in routine clinical diagnosis, and the rate of introduction of new protein tests approved by the United States Food and Drug Administration (FDA) has paradoxically declined over the last decade to less than one new protein diagnostic marker per year. We speculate on the reasons behind this large discrepancy between the expectations arising from proteomics and the realities of clinical diagnostics and suggest approaches by which protein-disease associations may be more effectively translated into diagnostic tools in the future.     

Characterization of the human blood plasma proteome

We describe methods for broad characterization of the human plasma proteome. The combination of stepwise immunoglobulin G (IgG) and albumin protein depletion by affinity chromatography and ultrahigh-efficiency capillary liquid chromatography separations coupled to ion trap-tandem mass spectrometry enabled identification of 2392 proteins from a single plasma sample with an estimated confidence level of > 94%, and an additional 2198 proteins with an estimated confidence level of 80%. The relative abundances of the identified proteins span a range of over eight orders of magnitude in concentration (< 30 pg/mL to approximately 30 mg/mL), facilitated by the attomole-level sensitivity of the analysis methods. More than 80% of the observed proteins demonstrate interactions with IgG and/or albumin, and the human plasma protein loss in the affinity chromatography/strong cation exchange/reversed-phase liquid chromatography-tandem mass spectrometry methodology was investigated in detail. The results of this study provide a basis for a wide range of plasma proteomics studies, including broad quantitation of relative abundances in comparative studies of the identification of novel protein disease markers, as well as further studies of protein-protein interactions.     

Proteomic analysis of human gastric juice: a shotgun approach

Gastric juice is the most proximal fluid surrounding the stomach tissue. The analysis of gastric juice protein contents will thus be able to accurately reflect the pathophysiology of the stomach. This biological fluid is also a potential reservoir of secreted biomarkers in higher concentration as compared to the serum. Unlike the rest of the gastrointestinal fluids, there were very few studies reported on gastric juice proteome. To date, the proteins that routinely populate this biofluid are largely unknown. This is partly due to the technical difficulties in processing a sample that contains a collection of other gastrointestinal fluids, especially saliva. In this study, we attempt to profile the protein components of the gastric fluids from chronic gastritis patients using a direct shotgun proteomics approach. These data represent the first report of the proteome of human gastric juice with gastritis background.     

Evaluation of strategy for analyzing mouse liver plasma membrane proteome

Plasma membrane (PM) proteome is one of the major subproteomes present in the cell,and is very important in liver function. In the present work, C57 mouse liver PM was purified by density-gradient centrifugation. The purified PM was verified by electron microscope analysis and Western blotting. The results showed that the PM was enriched by more than 20-fold and the contamination of mitochondria was reduced by 2-fold compared with the homogenization fraction. Proteins were separated by 2DE and 1DE, trypsin-digested and submitted to ESI-Q-TOF and MALDI-TOF-TOF mass spectrometry or directly digested in solution and analyzed by LC-ESI ion trap mass spectrometry. In all, 547 non-redundant mouse liver PM proteins were identified, of which 34% contributed to plasma membrane or plasma membrane-related proteins. This study optimized and evaluated the HLPP plasma membrane proteome analysis method and made a systematic analysis on PM proteome.     

Evaluation of strategy for analyzing mouse liver plasma membrane proteome

Plasma membrane (PM) proteome is one of the major subproteomes present in the cell,and is very important in liver function. In the present work, C57 mouse liver PM was purified by density-gradient centrifugation. The purified PM was verified by electron microscope analysis and Western blotting. The results showed that the PM was enriched by more than 20-fold and the contamination of mitochondria was reduced by 2-fold compared with the homogenization fraction. Proteins were separated by 2DE and 1DE, trypsin-digested and submitted to ESI-Q-TOF and MALDI-TOF-TOF mass spectrometry or directly digested in solution and analyzed by LC-ESI ion trap mass spectrometry. In all, 547 non-redundant mouse liver PM proteins were identified, of which 34% contributed to plasma membrane or plasma membrane-related proteins. This study optimized and evaluated the HLPP plasma membrane proteome analysis method and made a systematic analysis on PM proteome.