Optimization of protein solubilization for the analysis of the CD14 human monocyte membrane proteome using LC-MS/MS

Proteomic profiling of membrane proteins is of vital importance in the search for disease biomarkers and drug development. However, the slow pace in this field has resulted mainly from the difficulty to analyze membrane proteins by mass spectrometry (MS). The objective of this investigation was to explore and optimize solubilization of membrane proteins for shotgun membrane proteomics of the CD14 human monocytes by examining different systems that rely on: i) an organic solvent (methanol) ii) an acid-labile detergent 3-[3-(1,1-bisalkyloxyethyl)pyridin-1-yl]propane-1-sulfonate (PPS), iii) a combination of both agents (methanol + PPS). Solubilization efficiency of different buffers was first compared using bacteriorhodopsin as a model membrane protein. Selected approaches were then applied on a membrane subproteome isolated from a highly enriched human monocyte population that was ~ 98% positive for CD14 expression as determined by FACS analysis. A methanol-based buffer yielded 194 proteins of which 93 (48%) were mapped as integral membrane proteins. The combination of methanol and acid-cleavable detergent gave similar results; 203 identified proteins of which 93 (46%) were mapped integral membrane proteins. However, employing PPS 216 proteins were identified of which 75 (35%) were mapped as integral membrane proteins. These results indicate that methanol alone or in combination with PPS yielded significantly higher membrane protein identification/enrichment than the PPS alone.     

Comparison of SDS- and methanol-assisted protein solubilization and digestion methods for Escherichia coli membrane proteome analysis by 2-D LC-MS/MS

Both organic solvent and surfactant have been used for dissolving membrane proteins for shotgun proteomics. In this work, two methods of protein solubilization, namely using 60% methanol or 1% SDS, to dissolve and analyze the inner membrane fraction of an Escherichia coli K12 cell lysate were compared. A total of 358 proteins (1417 unique peptides) from the methanol-solubilized protein mixture and 299 proteins (892 peptides) from the SDS-solubilized sample-were identified by using trypsin digestion and 2-D LC-ESI MS/MS. It was found that the methanol method detected more hydrophobic peptides, resulting in a greater number of proteins identified, than the SDS method. We found that 159 out of 358 proteins (44%) and 120 out of 299 proteins (40%) detected from the methanol- and SDS-solubilized samples, respectively, are integral membrane proteins. Among the 190 integral membrane proteins 70 were identified exclusively in the methanol-solubilized sample, 89 were identified by both methods, and only 31 proteins were exclusively identified by the SDS method. It is shown that the integral membrane proteins reflected the theoretical proteome for number of transmembrane helices, length, functional class, and topology, indicating there was no bias in the proteins identified.     

Liquid chromatography MALDI MS/MS for membrane proteome analysis

Membrane proteins play critical roles in many biological functions and are often the molecular targets for drug discovery. However, their analysis presents a special challenge largely due to their highly hydrophobic nature. We present a surfactant-aided shotgun proteomics approach for membrane proteome analysis. In this approach, membrane proteins were solubilized and digested in the presence of SDS followed by newly developed auto-offline liquid chromatography/matrix-assisted laser desorption ionization (LC/MALDI) tandem MS analysis. Because of high tolerance of MALDI to SDS, one-dimensional (1D) LC separation can be combined with MALDI for direct analysis of protein digests containing SDS, without the need for extensive sample cleanup. In addition, the heated droplet interface used in LC/MALDI can work with high flow LC separations, allowing a relatively large amount of protein digest to be used for 1D LC/MALDI which facilitates the detection of low abundance proteins. The proteome identification results obtained by LC/MALDI are compared to the gel electrophoresis/MS method as well as the shotgun proteomics method using 2D LC/electrospray ionization MS. It is demonstrated that, while LC/MALDI provides more extensive proteome coverage compared to the other two methods, these three methods are complementary to each other and a combination of these methods should provide a more comprehensive membrane proteome analysis.     

Global proteome discovery using an online three-dimensional LC-MS/MS

We have developed a proteomics technology featuring on-line three-dimensional liquid chromatography coupled to tandem mass spectrometry (3D LC-MS/MS). Using 3D LC-MS/MS, the yeast-soluble, urea-solubilized peripheral membrane and SDS-solubilized membrane protein samples collectively yielded 3019 unique yeast protein identifications with an average of 5.5 peptides per protein from the 6300-gene Saccharomyces Genome Database searched with SEQUEST. A single run of the urea-solubilized sample yielded 2255 unique protein identifications, suggesting high peak capacity and resolving power of 3D LC-MS/MS. After precipitation of SDS from the digested membrane protein sample, 3D LC-MS/MS allowed the analysis of membrane proteins. Among 1221 proteins containing two or more predicted transmembrane domains, 495 such proteins were identified. The improved yeast proteome data allowed the mapping of many metabolic pathways and functional categories. The 3D LC-MS/MS technology provides a suitable tool for global proteome discovery.     

Investigation of solubilization and digestion methods for microsomal membrane proteome analysis using data-independent LC-MSE

To evaluate the implementation of various denaturants and their efficacy in bottom-up membrane proteomic methods using LC-MS analysis, microsomes isolated from tomato roots were treated with MS-compatible surfactants (RapiGest SF Surfactant from Waters and PPS Silent Surfactant from Protein Discovery), a chaotropic reagent (guanidine hydrochloride), and an organic solvent (methanol). Peptides were analyzed in triplicate sample and technical replicates by data-independent LC-MS(E) analysis. Overall, 2333 unique peptides matching to 662 unique proteins were detected with the order of denaturant method efficacy being RapiGest SF Surfactant, PPS Silent Surfactant, guanidine hydrochloride, and methanol. Using bioinformatic analysis, 103 proteins were determined to be integral membrane proteins. When normalizing the data as a percentage of the overall number of peptides and proteins identified for each method, the order for integral membrane protein identification efficacy was methanol, guanidine hydrochloride, RapiGest SF Surfactant, and PPS Silent Surfactant. Interestingly, only 8% of the proteins were identified in all four methods with the silent surfactants having the greatest overlap at 17%. GRAVY analysis at the protein and peptide level indicated that methanol and guanidine hydrochloride promoted detection of hydrophobic proteins and peptides, respectively; however, trypsin activity in the presence of each denaturant was determined as a major factor contributing to peptide identification by LC-MS(E) . These results reveal the complementary nature of each denaturant method, which can be used in an integrated approach to provide a more effective bottom-up analysis of membrane proteomes than can be achieved using only a single denaturant.     

Isoform analysis of LC-MS/MS data from multidimensional fractionation of the serum proteome

We developed a visualization approach for the identification of protein isoforms, precursor/mature protein combinations, and fragments from LC-MS/MS analysis of multidimensional fractionation of serum and plasma proteins. We also describe a pattern recognition algorithm to automatically detect and flag potentially heterogeneous species of proteins in proteomic experiments that involve extensive fractionation and result in a large number of identified serum or plasma proteins in an experiment. Examples are given of proteins with known isoforms that validate our approach and present a subset of precursor/mature protein pairs that were detected with this approach. Potential applications include identification of differentially expressed isoforms in disease states.     

Outer membrane proteome of Actinobacillus pleuropneumoniae: LC-MS/MS analyses validate in silico predictions

The Gram-negative bacterial pathogen Actinobacillus pleuropneumoniae causes porcine pneumonia, a highly infectious respiratory disease that contributes to major economic losses in the swine industry. Outer membrane (OM) proteins play key roles in infection and may be targets for drug and vaccine research. Exploiting the genome sequence of A. pleuropneumoniae serotype 5b, we scanned in silico for proteins predicted to be localized at the cell surface. Five genome scanning programs (Proteome Analyst, PSORT-b, BOMP, Lipo, and LipoP) were run to construct a consensus prediction list of 93 OM proteins in A. pleuropneumoniae. An inventory of predicted OM proteins was complemented by proteomic analyses utilizing gel- and solution-based methods, both coupled to LC-MS/MS. Different protocols were explored to enrich for OM proteins; the most rewarding required sucrose gradient centrifugation followed by membrane washes with sodium bromide and sodium carbonate. This protocol facilitated our identification of 47 OM proteins that represent 50% of the predicted OM proteome, most of which have not been characterized. Our study establishes the first OM proteome of A. pleuropneumoniae.     

Comparative proteome analysis of 3T3-L1 adipocyte differentiation using iTRAQ-coupled 2D LC-MS/MS

Adipose tissue is critical in obesity and type II diabetes. Blocking of adipocyte differentiation is one of the anti-obesity strategies targeting on strong rise in fat storage and secretion of adipokine(s). However, the molecular basis of adipocyte differentiation and its regulation remains obscure. Therefore, we exposed 3T3-L1 cell line to appropriate hormonal inducers as adipocyte differentiation model. Using iTRAQ-coupled 2D LC-MS/MS, a successfully exploited high-throughput proteomic technology, we nearly quantitated 1,000 protein species and found 106 significantly altered proteins during adipocyte differentiation. The great majority of differentially expressed proteins were related to metabolism enzymes, structural molecules, and proteins involved in signal transduction. In addition to previously reported differentially expressed molecules, more than 20 altered proteins previously unknown to be involved with adipogenic process were firstly revealed (e.g., HEXB, DPP7, PTTG1IP, PRDX5, EPDR1, SPNB2, STEAP3, TPP1, etc.). The partially differential proteins were verified by Western blot and/or real-time PCR analysis. Furthermore, the association of PCX and VDAC2, two altered proteins, with adipocyte conversion was analyzed using siRNA method, and the results showed that they could contribute considerably to adipogenesis. In conclusion, our data provide valuable information for further understanding of adipogenesis.     

Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome

Highly complex protein mixtures can be directly analyzed after proteolysis by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). In this paper, we have utilized the combination of strong cation exchange (SCX) and reversed-phase (RP) chromatography to achieve two-dimensional separation prior to MS/MS. One milligram of whole yeast protein was proteolyzed and separated by SCX chromatography (2.1 mm i.d.) with fraction collection every minute during an 80-min elution. Eighty fractions were reduced in volume and then re-injected via an autosampler in an automated fashion using a vented-column (100 microm i.d.) approach for RP-LC-MS/MS analysis. More than 162,000 MS/MS spectra were collected with 26,815 matched to yeast peptides (7,537 unique peptides). A total of 1,504 yeast proteins were unambiguously identified in this single analysis. We present a comparison of this experiment with a previously published yeast proteome analysis by Yates and colleagues (Washburn, M. P.; Wolters, D.; Yates, J. R., III. Nat. Biotechnol. 2001, 19, 242-7). In addition, we report an in-depth analysis of the false-positive rates associated with peptide identification using the Sequest algorithm and a reversed yeast protein database. New criteria are proposed to decrease false-positives to less than 1% and to greatly reduce the need for manual interpretation while permitting more proteins to be identified.     

Optimization of cell lysis and protein digestion protocols for the analysis of HeLa S3 cells by LC-MS/MS

In order to maximize the number of proteins identified from Hela S3 cell lysate we tested various cell lysis, protein precipitation and digestion protocols. First, we compared three different lysis buffers, two mechanical cell disruption methods and two precipitation methods. Then, we tested six different in-solution digestion protocols, three different in-gel digestion protocols and ten different peptide extraction protocols. The result is a proposal for an optimized protocol to prepare the whole cell lysate samples from HeLa S3 cells.     

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.     

Effect of 2MEGA labeling on membrane proteome analysis using LC-ESI QTOF MS

One of the challenges associated with large-scale proteome analysis using tandem mass spectrometry (MS/MS) and automated database searching is to reduce the number of false positive identifications without sacrificing the number of true positives found. In this work, a systematic investigation of the effect of 2MEGA labeling (N-terminal dimethylation after lysine guanidination) on the proteome analysis of a membrane fraction of an Escherichia coli cell extract by 2-dimensional liquid chromatography MS/MS is presented. By a large-scale comparison of MS/MS spectra of native peptides with those from the 2MEGA-labeled peptides, the labeled peptides were found to undergo facile fragmentation with enhanced a1 or a1-related (a(1)-17 and a(1)-45) ions derived from all N-terminal amino acids in the MS/MS spectra; these ions are usually difficult to detect in the MS/MS spectra of nonderivatized peptides. The 2MEGA labeling alleviated the biased detection of arginine-terminated peptides that is often observed in MALDI and ESI MS experiments. 2MEGA labeling was found not only to increase the number of peptides and proteins identified but also to generate enhanced a1 or a1-related ions as a constraint to reduce the number of false positive identifications. In total, 640 proteins were identified from the E. coli membrane fraction, with each protein identified based on peptide mass and sequence match of one or more peptides using MASCOT database search algorithm from the MS/MS spectra generated by a quadrupole time-of-flight mass spectrometer. Among them, the subcellular locations of 336 proteins are presently known, including 258 membrane and membrane-associated proteins (76.8%). Among the classified proteins, there was a dramatic increase in the total number of integral membrane proteins identified in the 2MEGA-labeled sample (153 proteins) versus the unlabeled sample (77 proteins).     

Analysis of anabolic steroids in human hair using LC-MS/MS

New highly sensitive, specific, reliable, reproducible and robust LC-MS/MS methods were developed to detect the anabolic steroids, nandrolone and stanozolol, in human hair for the first time. Hair samples from 180 participants (108 males, 72 females, 62% athletes) were screened using ELISA which revealed 16 athletes as positive for stanozolol and 3 for nandrolone. Positive samples were confirmed on LC-MS/MS in selective reaction monitoring (SRM) mode. The assays for stanozolol and nandrolone showed good linearity in the range 1-400 pg/mg and 5-400 pg/mg, respectively. The methods were validated for LLOD, interday precision, intraday precision, specificity, extraction recovery and accuracy. The assays were capable of detecting 0.5 pg stanozolol and 3.0 pg nandrolone per mg of hair, when approximately 20 mg of hair were processed. Analysis using LC-MS/MS confirmed 11 athletes’ positive for stanozolol (5.0 pg/mg to 86.3 pg/mg) and 1 for nandrolone (14.0 pg/mg) thus avoiding false results from ELISA screening. The results obtained demonstrate the application of these hair analysis methods to detect both steroids at low concentrations, hence reducing the amount of hair required significantly. The new methods complement urinalysis or blood testing and facilitate improved doping testing regimes. Hair analysis benefits from non-invasiveness, negligible risk of infection and facile sample storage and collection, whilst reducing risks of tampering and cross-contamination. Owing to the wide detection window, this approach may also offer an alternative approach for out-of-competition testing.     

1-DE MS and 2-D LC-MS analysis of the mouse bronchoalveolar lavage proteome

Bronchoalveolar lavage fluid (BALF) is a complex mixture of proteins, which represents a unique clinically useful sampling of the lower respiratory tract. Many proteomic technologies can be used to characterize complex biological mixtures; however, it is not yet clear which technology(s) provide more information regarding the number of proteins identified and sequence coverage. In this study, we initially compared two common proteomic approaches, 2-D LC microESI MS/MS and 1-DE followed by gel slice digestion, peptide extraction and peptide identification by MS in characterization of the mouse BALF proteome; secondly, we identified 297 unique proteins from the mouse BALF proteome, greatly expanded the BALF proteome by about threefold regardless of species.     

Utility of electrophoretically derived protein mass estimates as additional constraints in proteome analysis of human serum based on MS/MS analysis

The proteome of a HUPO human serum reference sample was analyzed using multidimensional separation techniques at both the protein and the peptide levels. To eliminate false-positive identifications from the search results, we employed a data filtering method using molecular weight (MW) correlations derived from denaturing 1-DE. First, the six most abundant serum proteins were removed from the sample using immunoaffinity chromatography. 1-DE was then used to fractionate the remaining serum proteins according to the MW. Gel bands were isolated and in-gel digested with trypsin, and the resulting peptides were analyzed by 2-D LC/ESI-MS/MS. A SEQUEST search using the MS/MS results identified 494 proteins. Of these, 202 were excluded formally using protein data filtering as they were single-assignment proteins and their theoretical and electrophoretically-derived MWs did not correlate at high confidence. To evaluate this method, the results were compared with those of 1-D LC/MALDI-TOF/TOF and HUPO Plasma Proteome Project analyses. Our data filtering approach proved valuable in analysis of complex, large-scale proteomes such as human serum.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

iTRAQ-coupled 2-D LC-MS/MS analysis of membrane protein profile in Escherichia coli incubated with apidaecin IB

Apidaecins are a series of proline-rich, 18- to 20-residue antimicrobial peptides produced by insects. They are predominantly active against the gram-negative bacteria. Previous studies mainly focused on the identification of their internal macromolecular targets, few addressed on the action of apidaecins on the molecules, especially proteins, of bacterial cell membrane. In this study, iTRAQ-coupled 2-D LC-MS/MS technique was utilized to identify altered membrane proteins of Escherichia coli cells incubated with one isoform of apidaecins--apidaecin IB. Cell division protease ftsH, an essential regulator in maintenance of membrane lipid homeostasis, was found to be overproduced in cells incubated with apidaecin IB. Its over-expression intensified the degradation of cytoplasmic protein UDP-3-O-acyl-N- acetylglucosamine deacetylase, which catalyzes the first committed step in the biosynthesis of the lipid A moiety of LPS, and thus leaded to the further unbalanced biosynthesis of LPS and phospholipids. Our findings suggested a new antibacterial mechanism of apidaecins and perhaps, by extension, for other proline-rich antimicrobial peptides.     

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.     

An analysis of the Caenorhabditis elegans lipid raft proteome using geLC-MS/MS

Lipid rafts are microdomains of the phospholipid bilayer, proposed to form semi-stable "islands" that act as a platform for several important cellular processes; major classes of raft-resident proteins include signalling proteins and glycosylphosphatidylinositol (GPI)-anchored proteins. Proteomic studies into lipid rafts have been mainly carried out in mammalian cell lines and single cell organisms. The nematode Caenorhabditis elegans, the model organism with a well-defined developmental profile, is ideally suited for the study of this subcellular locale in a complex developmental context. A study of the lipid raft proteome of C. elegans is presented here. A total of 44 proteins were identified from the lipid raft fraction using geLC-MS/MS, of which 40 have been determined to be likely raft proteins after analysis of predicted functions. Prediction of GPI-anchoring of the proteins found 21 to be potentially modified in this way, two of which were experimentally confirmed to be GPI-anchored. This work is the first reported study of the lipid raft proteome in C. elegans. The results show that raft proteins, including numerous GPI-anchored proteins, may have a variety of potentially important roles within the nematode, and will hopefully lead to C. elegans becoming a useful model for the study of lipid rafts.