High-Throughput Analysis of Rat Liver Plasma Membrane Proteome

(1) Despite their importance to cell function, these proteins seem to be .... defined by the pI table and the algorithm used in the Compute MW/pI prog...
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High-Throughput Analysis of Rat Liver Plasma Membrane Proteome by a Nonelectrophoretic In-Gel Tryptic Digestion Coupled with Mass Spectrometry Identification Rui Cao, QuanYuan He, Jian Zhou, QuanZe He, Zhen Liu, XianChun Wang, Ping Chen, Jingyun Xie, and SongPing Liang* College of Life Sciences, Hunan Normal University, Changsha, P.R. China Received July 4, 2007

In-gel digestion is commonly used after proteins are resolved by polyacrylamide gel electrophoresis (SDS-PAGE, 2-DE). It can also be used on its own in conjunction with tandem mass spectrometry (MS/ MS) for the direct analysis of complex proteins. Here, we describe a strategy combining isolation of purified plasma membrane, efficient digestion of plasma membrane proteins in polyacrylamide gel, and high-sensitivity analysis by advanced mass spectrometry to create a new rapid and high-throughput method. The plasma membrane protein mixture is directly incorporated into a polyacrylamide gel matrix, After formation of the gel, proteins in the gel section are digested with trypsin, and the resulting peptides are subjected to reversed-phase, high-performance liquid chromatography followed by electrospray ion-trap tandem mass analysis. Using this optimized strategy, we have identified 883 rat liver membrane proteins, of which 490 had a gene ontology (GO) annotation indicating a cellular component, and 294 (60%) of the latter were known integral membrane proteins or membrane proteins. In total, 333 proteins are predicted by the TMHMM 2.0 algorithm to have transmembrane domains (TMDs) and 52% (175 of 333) proteins to contain 2–16 TMDs. The identified membrane proteins provide a broad representation of the rat plasma membrane proteome with little bias evident due to protein pI and molecular weight (MW). Also, membrane proteins with a high GRAVY score (grand average hydrophobicity score) were identified, and basic and acidic membrane proteins were evenly represented. This study not only offered an efficient and powerful method in shotgun proteomics for the identification of proteins of complex plasma membrane samples but also allowed in-depth study of liver membrane proteomes, such as of rat models of liver-related disease. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of rat liver plasma membrane in general. Keywords: rat liver • plasma membrane • in-gel digestion • proteomics • Tandem mass spectrometry

Introduction The plasma membrane (PM) is a selectively permeable membrane that functions as a barrier and communication interface due to the presence of specific membrane proteins, which play important biological and pharmacological roles involving exchange of material and energy between the cell and its environment, These proteins have been used to effect about two-thirds of all drug targets.1 Despite their importance to cell function, these proteins seem to be disproportionately undercharacterized from biochemical, topographical, and structural perspectives due to their hydrophobic nature and generally low abundance. Because of their intrinsic hydrophobicity, PM integral membrane proteins are not readily soluble in polar solvents. As a result, the digestion of PM proteins usually results in low sequence coverage due to poor accessibility for proteolytic attack. This problem can be partially overcome by the use of surfactants or detergent to improve the solubility of the * To whom correspondence should be addressed. Fax: 86-731-886-1304. E-mail: [email protected]. 10.1021/pr070411f CCC: $40.75

 2008 American Chemical Society

PM proteins. But, high concentrations of these could suppress enzyme activity and interfere with subsequent MS measurement.2 Thus, high-throughput analysis of plasma integral membrane protein is more difficult with PM proteins than soluble proteins, due to the requirement for efficient protein solubilization and the incompatibility of MS with ionic and nonionic detergents.3,4 To address this need, various strategies for digestion of membrane proteins have been reported.5–10 In various shotgun methods, membrane proteins solubilized in either an organic acid, organic solvent, or an aqueous solution containing detergents such as SDS are subjected to proteolytic or chemical digestion. Alternatively, nonsolubilized membrane proteins are digested on the membrane or subjected to proteinase K digest in high pH aqueous buffer.9,10 The resulting peptides are separated in one- or two-dimensional HPLC. These methods are effective and optimize the identification of membrane proteins, but more generally applicable methods should be explored and improved. The combination of SDS-PAGE and LC-ESI MS/MS for analyzing a membrane proteome is a widely used technique;11–15 this is because the The Journal of Proteome Research 2008, 7, 535–545 535 Published on Web 01/01/2008

research articles in-gel approach for analyzing membrane proteins has some attractive features. For example, strong surfactants and detergents can be used to solubilize membrane proteins during insample preparation and gel separation. In addition, proteins embedded within the gel mix present a localized region for enzymatic cleavage and, thus, improve their chance of digestion and the protein coverage. More importantly, the detergents and other interfering substances can be removed with subsequent washing prior to protein digestion and will not interfere with it. Furthermore, the peptide mixtures obtained can be directly subjected to LC MS/MS analysis without further purification. However, problems such as protein insolubility is still remain.16 SDS-PAGE electrophoresis and the subsequent digestion and identification of each band of separated proteins is tedious and time-consuming. Methods involving the digestion of membrane protein mixtures in the polyacrylamide gel instead of in solution have been recently reported.17 The proteins are dissolved in solutions containing various detergents and directly incorporated into the gel matrix without electrophoresis. After in-gel digestion of the proteins, LC MS/MS is used to analyze the extracted peptides for protein identification. However, before this method can become universal in membrane proteome analysis, some evaluation and optimization seems necessary. Lu et al.,17 using this in-gel shotgun method followed by mass spectrometry, identified only 178 proteins from a membrane fraction isolated from PC3 cells. Of these, 96 proteins have a transmembrane domain. Hence, there still exists a substantial need for more comprehensive methods of analysis of plasma integral membrane proteins.

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Materials and Methods

The rat is a useful, widely used animal model for biological and toxicity studies. Rat liver is one of the most important organs involved in physiological, pathological, and toxicological work. Therefore, analysis of rat liver proteome would be a desirable contribution to understanding the molecular basis of liver function and structure. At present, although several proteomic profiling studies on the entire liver, its compartments, and organelles have been reported,18–23 the subcellular fractions of the rat liver PM proteome are seldom described. The major reason for this is that isolation of purified PM is not easy. PMs are easily contaminated by cytosolic proteins and secreted proteins. To separate PM from unexpected contaminants, we have recently reported a PM purification method that integrates sucrose density centrifugation and subsequent two-phase aqueous polymer partition to enrich and isolate rat liver PM, which can be coupled to an in-gel shotgun technique.

Materials. Unless stated otherwise, all reagents and chemicals were of the highest purity available. Water was purified using a Milli-Q system (Millipore, Bedford, MA). Dextran T500 was purchased from Amersham Pharmacia-Biotech (Uppsala, Sweden). HEPES, PEG 3350, sucrose, 1,4-dithiotreitol (DTT), trypsin (proteomics sequencing grade), CHAPS, n-octyl glucoside, phenylmethylsulfonyl fluoride (PMSF), and formic acid were obtained from Sigma (St. Louis, MO). Acryamide, ammonium bicarbonate, iodoacetamide, SDS, and Tris were from Bio-Rad (Hercules, CA). Acetonitrile and methanol (HPLCgrade) were purchased from Hunan Fine Chemistry Institute (Hunan, China). Rats were from Hunan Medical University. Purified Plasma Membrane Preparation. PMs were purified according to the procedure described in our previous paper.24 Briefly, the crude plasma membrane (CM) at the top of 42.3% sucrose was collected and washed. The CM pellets were transferred to the16 g two-phase systems (6.4% (w/w) PEG 3350, 6.4% (w/w) dextran T500, and 0.2 M potassium phosphate buffer; pH 7.2). The two-phase system was mixed by 20 inversions, vortexing, and another 20 inversions. Phase separation was accelerated by a 5 min centrifugation at 750g at 4 °C. The upper phase enriched in PM was separated and rewashed by addition to a fresh lower phase taken from the second tube, inverted 40 times, and centrifugated to separate the phases. At the same time, a fresh upper phase was repartitioned against the original lower phase. After mixing and phase separation, the two upper phases containing purified plasma membrane (PPM) were combined and diluted 5-fold with 1 mM sodium bicarbonate. The PPM were finally pelleted by centrifugation at 100 000g for 1.5 h in a SW28 rotor. The PPM was solubilized with 2% SDS, 8 M urea in 25 mM NH4HCO3 (pH 8.0), or 8 M urea, 1% NP-40 in 25 mM NH4HCO3. Electrophoresis and Western Blot Analysis. A 25 µg portion of the PPM proteins were separated by 10% SDS-PAGE and were transferred to a nitrocellulose membrane, which was blocked with 5% nonfat dry milk in TBST (150 mM NaCl, 0.1% Tween-20, 25 mM Tris, pH 7.5) for 1 h at room temperature and then incubated with the antiflotillin monoclonal antibody (1:250 dilution) for 1 h at the same condition. The membrane was incubated with secondary antibody following the manufacturer’s protocol. After it was washed with TBST, the membrane was incubated with horseradish peroxidase-conjugated antimouse for 1 h at room temperature. The membrane was washed with TBST again, and the bolt was developed using the Western lightning chemiluminescence reagent.

In this study, we have combined these two approaches for large-scale proteomic analysis of the PM proteome of rat liver. Excellent protein digestion in polyacrylamide gel and effective peptide extraction from polyacrylamide gel sections ensure sensitive and high-throughput analysis of rat liver membrane proteins. Using limited amounts of purified PM proteins (150 µg), we were able to identify 883 protein groups. Using gene ontology, 490 proteins were assigned to a subcellular compartment of those 294 (60%) were known or predicted to be membrane proteins. These comprised numerous transporters, channels, receptors, and other PM protein families. Evidently, the in-gel shotgun method is high-throughput and comprehensive enough to analyze membrane samples. We have provided a new powerful and convenient method for the isolation and identification of rat liver PM proteins or other membrane samples.

Incorporation of PM Proteins into Gel and In-Gel Digestion. The above protein solutions from the rat liver PM were incorporated into a polyacrylamide gel matrix (10% gel) without electrophoresis as described previously17 with some modifications. A 42 µL polyacrylamide gel was made as described below. The protein solution (16 µL, 150 ug protein), 14 µL 30% acrylamide stock (30%, 29:1) solution, 10 µL separating acrylamide gel buffer, 2 µL 1% ammonium persulfate (AP), and 0.4 µL 10% N,N,N′,N′-tetramethylethylenediamine (TEMED) were mixed in a small glass tube with an inner diameter of 1–2 mm (Waters/Micromass, Manchester, UK). The final gel concentration is 10%. After the gel was formed in the glass tube, it was fixed for 30 min with 50% v/v methanol and 7% v/v acetic acid, and the gel strip was removed, cut into small gel pieces, and washed twice with 25 mM NH4HCO3 and 50% acetonitrile. The gel digestion was done according to our

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Plasma Membrane Proteomics of Rat Liver 24

previous work. Briefly, the washed gel pieces were subjected to lyophilization in a SpeedVac, and the gel-bound proteins were reduced in 10 mM DTT and then alkylated in 55 mM iodoacetamide (IAA) containing 6 M guanidine hydrochloride. They were washed and then dehydrated in 100 µL acetonitrile and covered with 12.5 ng/µL trypsin in 25 mM MNH4HCO3 containing 0.1% n-octyl glucoside (W/V). Digestion was performed overnight at 37 °C in an Eppendorf tube. The supernatant was collected in a new Eppendorf tube. The gel pieces were then extracted in 100 µL of 60% ACN containing 0.1% formic acid for 10 min with ultrasonication. The supernatant was pooled and lyophilized in a SpeedVac to about 10 µL for mass spectrometric analysis. LC-MS/MS Analysis. The tryptic peptides were separated online with a Surveyor LC (Thermo Electron, San Jose, CA) using a 100 mm × 0.15 mm C18 column (Column Technology Inc.) at a flow rate of 1 µL/min using a 240-min 10–80% acetonitrile/water gradient. Both solvents contained 0.1% formic acid. Peptides were analyzed using a LTQ linear ion trap mass spectrometer (Thermo, San Jose, CA) equipped with an electrospray interface and operated in positive ion mode. The electrospray voltage was 3.1 kV versus the inlet of the mass spectrometer. The capillary temperature was set to 160 °C. Normalized collision energy was at 35.0%. An automated gain control function was used to manage the number of ions injected into the ion trap. The mass spectrometer was set so that one full MS scan (400–1800 m/z) was followed by 10 MS/ MS scans on the 10 most intense ions. Dynamic exclusion was set at repeat count 2, repeat duration 30 s, exclusion duration 90 s. System control and data collection were performed with Xcalibur software version 1.4 (Thermo). Database Searching. The acquired MS/MS spectra were searched against the RAT International Protein Index protein sequence database (version 3.07, 39 441 protein sequences, ftp://ftp.ebi.ac.uk/pub/databases/IPI/current/) using the TurboSEQUEST program in the BioWorks 3.1 software suite (Thermo). To calculate confidence levels and false positive rates, a decoy database containing the reverse sequences of the 39 441 proteins was appended to the rat database, and the SEQUEST algorithm was used to find the best matching sequences from the combined database.25 For the SEQUEST analysis, the peptide mass tolerance was set as 2.5 Da and the fragment ion tolerance was 0.5 Da. A tryptic enzyme restriction with a maximum of two internal missed cleavage sites was used. No residues (i.e., cysteine and methionine) were considered as modified in the database search. In order to obtain reliable protein identification, only peptides with a ∆Cn score above 0.13 were used (regardless of charge state). In addition, peptides with a +1 charge state were accepted if they were fully tryptic digested and had a cross correlation (Xcorr) of at least 1.55. Peptides with a +2 charge state were accepted if they had an Xcorr g 2.35. Peptides with a +3 charge state were accepted if they had an Xcorr g 2.75. These criteria were established based on probability-based evaluation using sequence-reversed database searching as previously described to provide a >99% overall confidence level for the entire set of unique peptide identifications (90% below 200 kDa (Figure 4A), which is the molecular weight distribution typically seen with in solution-based 2DLC methods.5,35 In this study,the smallest and largest MWs were 6 and 1833 kDa with pI values of 4.22 and 11.79, respectively. A groups of 670 proteins (76%), ranging from MW 10 to 100 kDa and pI 4.5 to 10, were compatible with general 1D or 2D PAGE. The other 213 proteins fell outside the typical limits of protein resolution seen using 2D-gel electrophoresis (Figure 4B). With these methods, proteins covering a wide pI range and even very basic proteins (up to a pI of 12) can be identified, which goes beyond the general 2DE separation limits.36 It is also obvious that basic and acidic integral membrane proteins were evenly represented (white spots). Figure 5 shows the histograms of the pI value distribution and molecular weight (MW) distribution patterns for the identified proteins, which were compared with the distribution patterns for the 39 441 proteins from the IPI rat protein database. Figure 5A shows the similarity between the distribution of the calculated pI values for the identified proteins(integral membrane proteins and total proteins) and the distribution of the estimated pI values for the entire proteome. These pI distributions are consistent with previous predictions for mouse brain proteome.37 Figure 5B indicated only a slight bias against lower MW proteins that can be attributed to the following: (1) the smaller numbers of possible/detectable peptides; (2) the lower MW proteins embedded in the gel matrix with lower efficiency. Bioinformatic analysis could also reveal a selective bias for integral membrane proteins possessing particular physiochemical characteristics, e.g., very hydrophobic proteins or multitransmembrane helices proteins. Therefore, we ana-

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Figure 2. Histogram illustrating the distributions of the identified proteins that have transmembrane domains (TMDs), as predicted by TMHMM.

Figure 3. (A) Comparison between proteins identified in the present study and previously studied proteomics data sets published recently.24 The bigger ellipse represents the present study. (B) Comparison of integral membrane protein in this data set with previously studied data.24

lyzed the identified PM proteins on the basis of the calculated average GRAVY (grand average of hydrophobicity) values and predicted transmembrane domains (TMDs) to assess the efficacy of the developed protocol for the identification of integral membrane proteins. The 2DE technique is unsuitable for the separation of integral membrane proteins, mainly because of protein aggregation during the IEF (isoelectric focusing) step.38 For this reason, only membrane proteins with a low GRAVY score and only one to two TM helices were detected. However, in our experiment, a broad range of hydrophobic integral membrane proteins (Figures 4 and 6) was identified by this gel-based shotgun method (white spots). The GRAVY values of rat liver PM proteins ranged from -1.837 to +1.104 (Figure 6). In total, 180 (20%) of these proteins have positive GRAVY values, indicating that a high number of very hydrophobic proteins were detectable by this approach. It is also evident (Figure 6) that the integral membrane proteins (white spots) have significantly more hydrophobic proteins than the other membrane proteins. The most hydrophobic protein identified was similar to CGI-141 (IPI00358470.2) having a GRAVY value of +1.104 which was identified by one unique peptide, R.VPVLGSLLNLPGIR.S (M + 2, Xcorr 2.84, ∆Cn 0.42) The least hydrophobic protein identified in the study was dimethylaniline monooxygenase (IPI00201564.3) with a positive hydropathy value of +0.001, which was identified by 2 unique peptides K.ALQSDYITYIDDLLTSINAKPDLR.A (M + 2, Xcorr 2.5195, ∆Cn 0.3527) and R.NLLPTPVVSWLISK.K (M + 2, Xcorr 2.5466, ∆Cn 0.3201). Figure 2 shows 337 proteins predicted

by the TMHMM 2.0 algorithm to have transmembrane domains (TMDs) and >174 proteins predicted to contain 2–16 TMDs. These results support the effectiveness of the method to solubilize and digest integral membrane proteins containing multiple TMDs, allowing large-scale detection and identification of this protein class with no bias against membrane proteins. This is because once the proteins are resolved on the gel matrix, the protein is unfolded, presenting a localized region for enzymatic cleavage, and thus improving the chance for protein digestion, regardless of whether it is hydrophobic or hydrophilic. Thus, the gelembedded digestion method could give a reasonable and uniform solubilization procedure for the identification of integral hydrophobic/hydrophilic membrane proteins. In summary, on the basis of the number of identified proteins and measurements of protein pI, MW, GRAVY, and TMDs, the analysis was comprehensive and enabling the detection of hydrophilic as well as highly hydrophobic proteins. Functional Categories of Identified Proteins. We categorized the identified proteins according to their function, based on universal GO annotation terms (Figure 7): 10.8% and 5.1% of the identified proteins were receptor signaling and structural proteins, respectively; 2.4% were involved in cell-cell adhesion, including junctional proteins; 22.9% were involved with metabolism; 4.1% had enzyme activity. In addition, 36.5% of the proteins were transport proteins which allow the passage of inorganic ions and other small, water-soluble molecules into the cells, and 18.2% of the proteins were not easily categorized and labeled “others”. For the proteins involved in cell adhesion, i.e., proteins acting as tight junctions, adherens junctions, desmosomes, and gap junctions, we identified 13 known plasma membrane proteins previously characterized using non-MS based methods (Table 2); claudin-1, claudin-3, epithelial-cadherin precursor, catenin alpha 1, beta-catenin, gap junction beta-1 protein, gap junction beta-2 protein, integrin-associated protein form 4, integrin beta-1 precursor, similar to desmoglein 2, desmoglein 2, and plakophilin 4. Within the category of primary transporters, secondary transporters, and nonreceptor type channels, a lot of types of transporters were found (Table 2 and Supporting Information Table S1): for the primary transporter, we identiThe Journal of Proteome Research • Vol. 7, No. 2, 2008 539

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Figure 4. (A) Molecular weight distribution of identified proteins. (B) Calculated pI of identified proteins plotted against their calculated molecular weight on a logarithmic scale. Colored in white are all integral membrane proteins which were found in this experiment. Colored in black are the all not integral membrane protein in this study.

fied calcium-transporting ATPase Atp2b1, potassium-transporting ATPase alpha chain Atp4a, and 4 subunits of the Na+/K+ ATPase complex (ATP1A1, ATP1A4, ATP1B1, and ATP1B3) .The secondary transporter proteins comprised the Na+/H+ exchanger (RGD1560736_predicted), Rho guanine nucleotide exchange factor Arhgef11, SO42- transporter Slc26a1, Na+/Cldependent GABA transporter Slc6a13, facilitated glucose transporter Slc2a2, the Na/Pi cotransporter Slc17a3, sodium/ nucleoside cotransporter Slc28a1, the solute carrier organic anion transporter Slco1a4, Slco1b2, Slco1a1, the monocarboxylate transporter Slc16a1, Slc16a2, system N amino acid transporter 1 Slc38a3, organic cation transporter Slc22a1, organic anion transporter Slc22a7, zinc transporter, canalicular multispecific organic anion transporter Abcc2, glycerol-6-phosphate transporter Slc37a4, equilibrative nucleoside transporter Slc29a1, and so on. Eight nonreceptor type channel proteins were identified, such as the potassium voltage-gated channel subfamily H member 1, transient receptor potential cation channel subfamily V member 2, and voltage-dependent anionselective channel proteins 1, 2, and 3. In addition to proteins constituting transporters and voltage-gated channels, our developed method revealed the presence of different receptors (Table 2 and Supporting Information Table S2). These comprised of epidermal growth factor receptor, scavenger receptor class B member Scarb1, macrophage mannose receptor precursor, transferrin receptor protein, asialoglycoprotein receptor 540

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Asgr1, polymeric-immunoglobulin receptor, G protein-coupled receptor 50, insulin receptor precursor, metabotropic glutamate receptor 5, and others. One of the receptors, asialoglycoprotein receptor Asgr1 (Table 2), which was identified by one unique peptide R.FVQQHMGPLNTWIGLTDQNGPWK.W (M +2, Xcorr 2.9152, ∆Cn 0.502) is expressed exclusively in hepatic parenchymal cells. Our analysis enabled identification of a significant number of transporters, channels, receptors, and some other proteins which carry out a broad range of different functions and belong to distinct families of the plasma membranes. Clearly, we were able to cover many of the membrane proteins of interest in rat liver proteome studies. In a previous study,24 we described an improved strategy for analysis of PM proteins that lead to identified proteins of high to moderate abundance in rat liver plasma membranes. Now, applying the new digestion technique and more sensitive mass spectrometric technology, it is possible to profile low abundance proteins from rat liver PM, such as these ion channels and receptors. This technology, combined with the new PM digestion method, has allowed us to probe the liver membrane proteome to great depth. In our study, we were also able to identify some disease-related proteins, such as translocon-associated protein alpha subunit precursor, annexin A1 Huntington disease gene homologue, programmed cell death protein 8, defender against cell death 1, and a predicted protein which is similar to novel cell deathregulatory protein GRIM19. Also, programmed cell death protein

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Figure 7. Functional characterization of the plasma membrane proteins.

Figure 5. Comparisons of protein distributions, based on their physiochemical characteristics. (A) pI and (B) molecular weight (MW), between the identified proteins (expressed as percents of the total number of identified proteins) in the data set and the entire rat proteome (expressed as percents of the total number of IPI rat database). Predicted pI values were obtained from the IPI rat protein database, and the pI distributions were plotted with a 0.2 pH unit increment. MW values were also obtained from the IPI rat protein database, and the MW distributions were plotted with 2 kDa increments: (ig) indentied protein in this study; (ig_TMDs) identified proteins in this study with TMDs; (ipi) proeins in IPI rat proteins database; (ipi_TMDs) proteins in IPI rat proteins dababase which have TMDs.

Figure 6. Relationship between molecular weight and GRAVY scores of the identified proteins. The white spots show the integral membrane proteins. A high number of hydrophobic proteins were detected in the experiment.

8 and defender against cell death 1 protein are involved in apoptosis. This indicates the potential of the developed approach for global proteomic analysis of the proteins residing within these very important functional substructures of the plasma membrane (Table 2). In summary, the results from our study demonstrate that it is possible to achieve efficient enrichment and identification of hydrophobic integral membrane proteins using the two-phase system and gel-embedded digestion. Relative Abundances of Identified Proteins within the Rat Liver Plasma Membrane. One main objective of proteomic research is the systematic identification and quantification of

proteins expressed in a biological system. Biological experiments often require at least some information on protein abundance for correct interpretation. To get quantitative information, there are many label-free methods based on the number of peptides identified for each protein, spectral counts of identified peptides, ion intensity of peptides, and so on, which have been recently described.39–41 Here, we used a more recently exponentially modified protein abundance indices (emPAIs) method to determine protein relative abundance from nano-LC-MS/MS experiments in this study.42–44 The emPAI is 10PAI - 1, where PAI is the number of observed peptides divided by the number of theoretically observable peptides. In this study, proteins with an emPAI > 0.2 were classified as highly abundant (Supporting Information Table S2). Proteins with emPAI 0.19–0.05 were classified as of intermediate abundance, and proteins with an emPAI < 0.05 were classified as of low abundance (Supporting Information Table S2). It should be noted that emPAI information provides an estimation of the relative abundances of different proteins within the same sample. Figure 8 shows the distribution of emPAI for the identified proteins. Notably, the majority of proteins were identified with emPAI values fewer than 0.05, presumably due to their relatively low abundances in the identified proteins. A total of 69 proteins were identified with emPAIs > 0.2, and this list of proteins includes many expected high abundance structural proteins and metabolic enzymes, such as tubulin, actin, ATP synthase, voltage-dependent anionselective channel protein 1, etc. For the intermediate abundance proteins, some examples of proteins included on this list are Na+/K+ transporting ATPase, annexin 6, facilitated glucose transporter elongation factors, aminopeptidase N, canalicular multispecific organic anion transporter 1, claudin1, catenin, etc. On the other hand, all transcription factors, which are generally expressed in cells at relatively low levels, were identified with emPAI < 0.03. Moreover, these receptors are expected to be expressed with relatively low abundances and were mostly found with emPAI < 0.05. Our database provides proteomewide semiquantitative information on the relative abundances of rat liver PM and enabled a deeper insight into the organelle internal composition and the acquisition of novel information on the characteristics of the liver PM.

Conclusion A method that utilizes a combination of two-phase aqueous polymer partition-based isolation of PPM and gel-embedded digestion of PM was developed for large-scale analysis of the The Journal of Proteome Research • Vol. 7, No. 2, 2008 541

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Table 2. Selected Plasma Membrane Proteins from Rat Liver accession. no.

protein name

GRAVYa

TMDsb

identified peptides

transporter

IPI00390795.2 IPI00326305.3

IPI00208061.3

IPI00339124.2

IPI00194873.1

IPI00365705.4 IPI00366693.2 IPI00231450.5 IPI00205806.1 IPI00361512.2

IPI00214031.1

IPI00215390.1

IPI00207298.3 IPI00214674.1

IPI00196643.1

IPI00361514.2

IPI00325618.1 IPI00327166.2 IPI00214460.1

IPI00200122.1 IPI00325619.3 IPI00207160.1 IPI00205029.1 IPI00200393.1 IPI00203971.2 IPI00194857.1 IPI00361513.2

542

Na+/K+-ATPase alpha 4 subunit sodium/ potassium-transporting ATPase alpha-1 chain sodium/ potassium-transporting ATPase beta-3 chain sodium/ potassium-transporting ATPase beta-1 chain plasma membrane calcium-transporting ATPase 1 potassium-transporting ATPase alpha chain 1 PREDICTED: sodium/ hydrogen exchanger equilibrative nucleoside transporter 1 canalicular multispecific organic anion transporter 1 PREDICTED: similar to ATP-binding cassette transporter subfamily A member 8a solute carrier organic anion transporter family, member 1A4 solute carrier organic anion transporter family, member 1B2 sulfate anion transporter 1 solute carrier organic anion transporter family, member 1A1 solute carrier family 2, facilitated glucose transporter, member 2 PREDICTED: similar to ATP-binding cassette transporter subfamily A member 6 antigen peptide transporter 1 tap1 protein sodium- and chloride-dependent GABA transporter 2 system N amino acid transporter 1 antigen peptide transporter 2 sodium/nucleoside cotransporter 1 organic cation transporter monocarboxylate transporter 8 organic anion transporter 2 Na/Pi cotransporter 4 PREDICTED: similar to ATP-binding cassette transporter subfamily A member 9

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0.034

10

2

0.002

10

15

-0.261

1

3

-0.524

1

1

-0.169

7

2

0.061

8

2

-0.041

5

1

0.71

11

1

0.097

14

18

0.038

14

10

0.291

11

4

0.044

11

4

0.475 0.301

9 10

4 3

0.505

11

3

0.122

12

3

0.277

7

3

0.275 0.451

7 12

3 2

0.576

11

1

0.155

5

1

0.556

10

1

0.437 0.211

12 11

1 1

0.442 0.425 0.098

11 9 13

1 1 1

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Plasma Membrane Proteomics of Rat Liver Table 2. (Continued) accession no

IPI00367701.2

IPI00361311.2

IPI00214787.1

protein name

GRAVYa

PREDICTED: similar to solute carrier family 39 (zinc transporter), member 9 PREDICTED: similar to ATP-binding cassette transporter subfamily A member 8b monocarboxylate transporter 1

identified peptides

TMDsb

0.54

7

1

0.112

12

1

0.372

11

1

channel

IPI00421874.2 IPI00198327.2 IPI00231067.1 IPI00339126.2 IPI00198821.2

voltage-dependent anion-selective channel protein 1 voltage-dependent anion-selective channel protein 2 voltage-dependent anion-selective channel protein 3 potassium voltage-gated channel subfamily H member 1 transient receptor potential cation channel subfamily V member 2

-0.357 -0.221 -0.289 -0.183 -0.10524

0 0 0 4 6

9 6 4 1 1

receptor

IPI00369995.2 IPI00212694.1 IPI00373197.1 IPI00209707.1 IPI00366838.2 IPI00189766.4 IPI00370607.2 IPI00231738.4 IPI00365544.1 IPI00205255.1 IPI00515795.1 IPI00563042.1 IPI00208264.1 IPI00210027.3 IPI00231472.1 IPI00210290.1 IPI00214860.1

PREDICTED: similar to lipoprotein receptor-related protein epidermal growth factor receptor membrane associated progesterone receptor component 2 scavenger receptor class B member 1 PREDICTED: similar to macrophage mannose receptor precursor progesterone receptor membrane component 1 PREDICTED: similar to transferrin receptor protein 2 (TfR2) asialoglycoprotein receptor 1 B-cell receptor-associated protein BAP29 polymeric-immunoglobulin receptor precursor PREDICTED: G protein-coupled receptor 50 insulin receptor precursor calcium-independent alpha-latrotoxin receptor homologue 3 inositol 1,4,5-trisphosphate receptor type 1 metabotropic glutamate receptor 5 precursor neuromedin K receptor neuronal acetylcholine receptor protein, alpha-4 chain precursor

-0.507 -0.327 -0.459 0.054 -0.499

1 2 1 2 1

5 4 4 3 3

-0.291 -0.208 -0.634 -0.235 -0.501 0.258 -0.379 -0.277 -0.321 -0.078 0.221 0.091

2 1 1 3 1 7 2 7 6 6 7 4

2 1 1 1 1 1 1 1 1 1 1 1

cell adhesion

IPI00191681.1 IPI00195286.2 IPI00208940.1 IPI00358406.2 IPI00421429.2 IPI00369460.2 IPI00206662.1 IPI00325912.1 IPI00358406.2 IPI00208534.1 IPI00207191.1 IPI00358687.2 IPI00470238.2 IPI00199607.1 IPI00325146.6 IPI00206188.1

integrin beta-1 precursor claudin-1 claudin-3 catenin (Cadherin-associated protein), alpha 1, 102 kDa plakoglobin PREDICTED: similar to Tight junction protein 3 epithelial-cadherin precursor beta-catenin catenin (cadherin-associated protein), alpha 1, 102 kDa gap junction beta-2 protein gap junction beta-1 protein PREDICTED: similar to desmoglein 2 integrin-associated protein form 4 carcinoembryonic antigen-related cell adhesion molecule, secreted isoform CEACAM1a-4C2 precursor annexin A2 CD166 antigen precursor

-0.374 0.463 0.605 -0.374 -0.162 -0.592 -0.431 -0.178 -0.374 0.273 0.194 -0.243 0.641 -0.436

1 4 4 0 0 0 1 0 0 4 4 1 5 0

2 2 1 13 7 1 1 11 13 1 2 2 1 5

-0.526 -0.37

0 1

1 7

disease-related PM proteins

IPI00188509.2 IPI00231615.4 IPI00454221.2 IPI00204118.1

defender against cell death 1 annexin A1 PREDICTED: Huntington disease gene homologue programmed cell death protein 8

plasma membrane proteome of rat liver. There are several advantages over other methods optimized for membrane

0.815 -0.437 -0.061 -0.231

3 0 0 0

1 1 12

proteomics. In the plasma membrane preparation stage, efficient isolation of PPM was achieved using sucrose density The Journal of Proteome Research • Vol. 7, No. 2, 2008 543

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Table 2. (Continued) protein name

accession. no.

IPI00362610.1

PREDICTED: similar to novel cell death-regulatory protein GRIM19 splice isoform 2 of reticulon 4 PREDICTED: similar to p53 apoptosis-associated target translocon-associated protein alpha subunit precursor

IPI00230986.1 IPI00213817.1 IPI00364884.1

a

Grand average of hydrophobicity.

b

GRAVYa

TMDsb

identified peptides

-0.437

1

2

-0.079

2

1

0.666

4

1

-0.176

1

1

Predicted number of transmembrane a helices returned by TMHMM (http://www.cbs.dtu.dk/services/TMHMM).

Acknowledgment. We thank Jie Dai at the Shanghai Institutes for Biological Sciences for his contribution to the LTQ analysis. This work was supported by grants from the National Natural Science Foundation of China (contract No. 90408017 and No. 30770437), the “973 Program” (Grants 2007CB914203 and 2007CB516809), and the Doctoral Foundation from the Ministry of Education of China (No. 20050542003). Figure 8. Distribution of emPAI for identified proteins.

centrifugation and subsequent two-phase aqueous polymer partition. In the plasma membrane cleavage procedure, the gelembedded method allowed the use of a high detergent concentration to achieve efficient solubilization of very hydrophobic membrane proteins while avoiding interference with the subsequent LC-MS/MS analysis. The denatured membrane proteins fixed in the gel matrix after the gel is formed make more enzymatic cleavage sites accessible, thus increasing protein digestion efficiency and improving sequence coverage and sensitivity. The combination of a relatively simple sample preparation technique with highly efficient digestion and high scan speed mass spectrometry opens new possibilities in studying plasma membrane proteins. The analysis was demonstrated to be comprehensive with respect to the number of identified membrane proteins and the range of membrane protein pI and GRAVY values and the detection of hydrophilic as well as highly hydrophobic proteins. Furthermore, this strategy permits a comprehensive analysis of the protein complement within rat liver PM. Finally, these crucial methods can be used for analysis of proteomes of many other plasma membranes. The labeled MS/MS spectrum of the single peptide based identified proteins was given at the following web address: http://protchem.hunnu.edu.cn/Labweb/Publication/Material/ CaoRui_Photo_2007_1/index.html. Abbreviations. 2DE, two-dimensional gel electrophoresis; SDS-PAGE, sodium-dodecyl sulfate polyacrylamide gel electrophoresis; TMDs, transmembrane domains; PM, plasma membrane; MS/MS, tandem mass spectrometry; MW, molecular weight; PEG, polyethylene glycol; PMSF, phenylmethylsulfonyl fluoride; CM, crude plasma membrane; PPM, purified plasmamembrane;AP,ammoniumpersulfate;TEMED,N,N,N′,N′tetramethylethylenediamine; IAA, iodoacetamide; GO, gene ontology; TMHMM, transmembrane hidden Markov model; GRAVY, grand average of hydrophobicity. 544

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Supporting Information Available: Tables S1 and S2 listing all identified proteins from rat liver plasma membrane in this study. This material is available free of charge via the Internet at http://pubs.acs.org. References (1) Hopkins, A. L.; Groom, C. R. The druggable genome. Nat. Rev. Drug Discov. 2002, 1 (9), 727–30. (2) Blonder, J.; Goshe, M. B.; Moore, R. J.; Pasa-Tolic, L.; Masselon, C. D.; Lipton, M. S.; Smith, R. D. Enrichment of integral membrane proteins for proteomic analysis using liquid chromatographytandem mass spectrometry. J. Proteome Res. 2002, 1 (4), 351–60. (3) Swiderek, K. A.; Alpert, A.; Heckendorf, A.; Nugent, K.; Patterson, S. D. Structural analysis of proteins and peptides in the presence of detergents: Tricks of the trade. J. Biomol. Tech. 1997, 8, 17–25. (4) Wu, C. C.; Yates, J. R., 3rd. The application of mass spectrometry to membrane proteomics. Nat. Biotechnol. 2003, 21 (3), 262–7. (5) Blonder, J.; Terunuma, A.; Conrads, T. P.; Chan, K. C.; Yee, C.; Lucas, D. A.; Schaefer, C. F.; Yu, L. R.; Issaq, H. J.; Veenstra, T. D.; Vogel, J. C. A proteomic characterization of the plasma membrane of human epidermis by high-throughput mass spectrometry. J. Invest. Dermatol. 2004, 123 (4), 691–9. (6) Brugiere, S.; Kowalski, S.; Ferro, M.; Seigneurin-Berny, D.; Miras, S.; Salvi, D.; Ravanel, S.; d’Herin, P.; Garin, J.; Bourguignon, J.; Joyard, J.; Rolland, N. The hydrophobic proteome of mitochondrial membranes from Arabidopsis cell suspensions. Phytochemistry 2004, 65 (12), 1693–707. (7) Fan, X.; She, Y. M.; Bagshaw, R. D.; Callahan, J. W.; Schachter, H.; Mahuran, D. J. A method for proteomic identification of membranebound proteins containing Asn-linked oligosaccharides. Anal. Biochem. 2004, 332 (1), 178–86. (8) Han, D. K.; Eng, J.; Zhou, H.; Aebersold, R. Quantitative profiling of differentiation-induced microsomal proteins using isotopecoded affinity tags and mass spectrometry. Nat. Biotechnol. 2001, 19 (10), 946–51. (9) Nielsen, P. A.; Olsen, J. V.; Podtelejnikov, A. V.; Andersen, J. R.; Mann, M.; Wisniewski, J. R. Proteomic mapping of brain plasma membrane proteins. Mol. Cell. Proteomics 2005, 4 (4), 402–8. (10) Wu, C. C.; MacCoss, M. J.; Howell, K. E.; Yates, J. R., 3rd. A method for the comprehensive proteomic analysis of membrane proteins. Nat. Biotechnol. 2003, 21 (5), 532–8. (11) Barbier-Brygoo, H.; Ephritikhine, G. Identification of new intrinsic proteins in Arabidopsis plasma membrane proteome. Mol. Cell. Proteomics 2006, 3, 675–691. (12) Rahbar, A. M.; Fenselau, C. Integration of Jacobson’s pellicle method into proteomic strategies for plasma membrane proteins. J. Proteome Res. 2004, 3 (6), 1267–77.

research articles

Plasma Membrane Proteomics of Rat Liver (13) Schindler, J.; Lewandrowski, U.; Sickmann, A.; Friauf, E.; Nothwang, H. G. Proteomic analysis of brain plasma membranes isolated by affinity two-phase partitioning. Mol. Cell. Proteomics 2006, 5 (2), 390–400. (14) Xiong, Y.; Chalmers, M. J.; Gao, F. P.; Cross, T. A.; Marshall, A. G. Identification of Mycobacterium tuberculosis H37Rv integral membrane proteins by one-dimensional gel electrophoresis and liquid chromatography electrospray ionization tandem mass spectrometry. J. Proteome Res. 2005, 4 (3), 855–61. (15) Zhao, Y.; Zhang, W.; Kho, Y.; Zhao, Y. Proteomic analysis of integral plasma membrane proteins. Anal. Chem. 2004, 76 (7), 1817–23. (16) Klein, C.; Garcia-Rizo, C.; Bisle, B.; Scheffer, B.; Zischka, H.; Pfeiffer, F.; Siedler, F.; Oesterhelt, D. The membrane proteome of Halobacterium salinarum. Proteomics 2005, 5 (1), 180–97. (17) Lu, X.; Zhu, H. Tube-gel digestion: a novel proteomic approach for high throughput analysis of membrane proteins. Mol. Cell. Proteomics 2005, 4 (12), 1948–58. (18) Fountoulakis, M.; Berndt, P.; Langen, H.; Suter, L. The rat liver mitochondrial proteins. Electrophoresis 2002, 23, 311–328. (19) Fountoulakis, M.; Suter, L. Proteomic analysis of the rat liver. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2002, 782, 197– 218. (20) Jiang, X. S.; Zhou, H.; Zhang, L.; Sheng, Q. H.; Zeng, R. A highthroughput approach for subcellular proteome. Mol. Cell. Proteomics 2004, 3, 441–455. (21) Kikuchi, M.; Hatano, N.; Yokota, S.; Shimozawa, N.; Imanaka, T.; Taniguchi, H. Proteomic analysis of rat liver peroxisome: presence of peroxisome-specific isozyme of Lon protease. J. Biol. Chem. 2004, 279 (1), 421–8. (22) Takatalo, M. S.; Kouvonen, P.; Corthals, G.; Nyman, T. A.; Ronnholm, R. H. Identification of new Golgi complex specific proteins by direct organelle proteomic analysis. Proteomics 2006, 6, 3502–3508. (23) Taylor, R. S.; Wu, C. C.; Hays, L. G.; Eng, J. K.; Yate, J. R.; Howell, K. E. Proteomics of rat liver Golgi complex: Minor proteins are identified through sequential fractionation. Electrophoresis 2000, 21, 3441–3459. (24) Cao, R.; Li, X.; Liu, Z.; Peng, X.; Hu, W.; Wang, X.; Chen, P.; Xie, J.; Liang, S. Integration of a two-phase partition method into proteomics research on rat liver plasma membrane proteins. J. Proteome Res. 2006, 5 (3), 634–42. (25) Elias, J. E.; Gygi, S. P. Target-decoy search strategy for increased confidence in. large-scale protein identifications by mass spectrometry. Nat. Methods 2007, 4 (3), 207–214. (26) Qian, W. J.; Liu, T.; Monroe, M. E.; Strittmatter, E. F.; Jacobs, J. M.; Kangas, L. J.; Petritis, K.; Camp, D. G., 2nd; Smith, R. D. Probabilitybased evaluation of peptide and protein identifications from tandem mass spectrometry and SEQUEST analysis: the human proteome. J. Proteome Res. 2005, 4, 53–62. (27) Kyte, J.; Doolittle, R. F. A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 1982, 157, 105– 132. (28) Krogh, A.; Larsson, B.; Heijne, G.; Sonnhammer, E. L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 2001, 305 (3), 567– 580.

(29) Ashburner, M.; Ball, C. A.; Blake, J. A.; Botstein, D.; Butler, H; Cherry, J. M.; Davis, A. P.; Dolinski, K.; Dwight, S. S.; Eppig, J. T. Gene Ontology: tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. (30) Blonder, J.; Hale, M. L.; Lucas, D. A.; Schaefer, C. F.; Yu, L. R.; Conrads, T. P.; Issaq, H. J.; Stiles, B. G.; Veenstra, T. D. Proteomic analysis of detergent-resistant membrane rafts. Electrophoresis 2004, 25 (9), 1307–18. (31) Speers, A. E.; Wu, C. C. Proteomics of Integral Membrane ProteinssTheory and Application. Chem. Rev. 2007, 107, 3687–3714. (32) Foster, L. J.; de Hoog, C. L.; Zhang, Y.; Zhang, Y.; Xie, X.; Mootha, V. K.; Mann, M. A mammalian organelle map by protein correlation profiling. Cell 2006, 125 (1), 187–99. (33) Bae, T. J.; Kim, M. S.; Kim, J. W.; Kim, B. W.; Choo, H. J.; Lee, J. W.; Kim, K. B.; Lee, C. S.; Kim, J. H.; Chang, S. Y.; Kang, C. Y.; Lee, S. W.; Ko, Y. G. Lipid raft proteome reveals ATP synthase complex in the cell surface. Proteomics 2004, 4 (11), 3536–48. (34) Kim, K. B.; Lee, J. W.; Lee, C. S.; Kim, B. W.; Choo, H. J.; Jung, S. Y.; Chi, S. G.; Yoon, Y. S.; Yoon, G.; Ko, Y. G. Oxidation-reduction respiratory chains and ATP synthase complex are localized in detergent-resistant lipid rafts. Proteomics 2006, 6 (8), 2444–53. (35) Durr, E.; Yu, J.; Krasinska, K. M.; Carver, L. A.; Yates, J. R.; Testa, J. E.; Oh, P.; Schnitzer, J. E. Direct proteomic mapping of the lung microvascular endothelial cell surface in vivo and in cell culture. Nat. Biotechnol. 2004, 22 (8), 985–92. (36) Josic, D.; Brown, M. K.; Huang, F.; Callanan, H.; Rucevic, M.; Nicoletti, A.; Clifton, J.; Hixson, D. C. Use of selective extraction and fast chromatographic separation combined with electrophoretic methods for mapping of membrane proteins. Electrophoresis 2005, 26 (14), 2809–22. (37) Wang, H.; Qian, W. J.; Chin, M. H.; Petyuk, V. A.; Barry, R. C.; Liu, T.; Gritsenko, M. A.; Mottaz, H. M.; Moore, R. J.; Camp Ii, D. G.; Khan, A. H.; Smith, D. J.; Smith, R. D. Characterization of the mouse brain proteome using global proteomic analysis complemented with cysteinyl-peptide enrichment. J. Proteome Res. 2006, 5 (2), 361–9. (38) Santoni, V.; Molloy, M.; Rabilloud, T. Membrane proteins and proteomics: un amour impossible. Electrophoresis 2000, 21, 1054– 1070. (39) Chelius, D.; Bondarenko, P. V. Quantitative profiling of proteins in complex mixtures using liquid chromatography and mass spectrometry. J. Proteome Res. 2002, (1), 317–323. (40) Liu, H.; Sadygov, R. G.; Yates, J. R., 3rd. A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 2004, (76), 4193–4201. (41) Forner, F.; Foster, L. J.; Campanaro, S.; Valle, G.; Mann, M. Quantitative proteomic comparison of rat mitochondria from muscle, heart, and liver. Mol. Cell. Proteomics 2006, 5 (4), 608–19. (42) Ishihama, Y.; Oda, Y.; Tabata, T.; Sato, T.; Nagasu, T.; Rappsilber, J.; Mann, M. Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol. Cell. Proteomics 2005, 4 (9), 1265–72. (43) Mann, K.; Macek, B.; Olsen, J. V. Proteomic analysis of the acidsoluble organic matrix of the chicken calcified eggshell layer. Proteomics 2006, 6 (13), 3801–3810. (44) Ong, S. E.; Mann, M. Mass spectrometry-based proteomics turns quantitative. Nat. Chem. Biol. 2005, 1 (5), 252–62.

PR070411F

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