Protein Mobility Shifts Contribute to Gel Electrophoresis Liquid Chromatography Analysis

Profiling of cellular and subcellular proteomes by liquid chromatography with tandem mass spectrometry (MS) after fractionation by SDS-PAGE is referred to as GeLC (gel electrophoresis liquid chromatography)-MS. The GeLC approach decreases complexity within individual MS analyses by size fractionation with SDS-PAGE. SDS-PAGE is considered an excellent fractionation technique for intact proteins because of good resolution for proteins of all sizes, isoelectric points, and hydrophobicities. Additional information derived from the mobility of the intact proteins is available after an SDS-PAGE fractionation, but that information is usually not incorporated into the proteomic analysis. Any chemical or proteolytic modification of a protein that changes the mobility of that protein in the gel can be detected. The ability of SDS-PAGE to resolve proteins with chemical modifications has not been widely utilized within profiling experiments. In this work, we examined the ability of the GeLC-MS approach to help identify proteins that were modified after a small hairpin RNA-dependent knockdown in an experiment using stable isotope labeling by amino acids in cell culture-based quantitation.     

Characterization of human melanoma cell lines and melanocytes by proteome analysis

We have analyzed the proteomes of two human melanoma cell lines (A375 and 526), and of the human melanocytes, (FOM 78), by two-dimensional electrophoresis (2D-PAGE) and liquid chromatography – tandem mass spectrometry (LC-MS/MS). Our comparative proteomic analysis revealed that six proteins were over-expressed in both melanoma cell lines as compared to melanocytes: galectin-1, inosine-5'-monophosphate dehydrogenase 2, serine/threonine-protein phosphatase 2A 65 kDa regulatory subunit A alpha isoform, protein DJ-1, cyclophilin A and cofilin-1. We show, for the first time, that only specific isoforms of these molecules are over-expressed in melanoma. Different protein profiles were also found between each individual melanoma cell line and the melanocytes. s-Methyl-5-thioadenosine phosphorylase, ubiquitin and ribosomal protein S27 a precursor, the basic form of protein DJ-1, annexin a1, proliferation associated protein 2g4, isoform alfa-enolase of alfa-enolase, protein disulfide-isomerase precursor, and elongation factor 2 were more strongly expressed in A375 cells compared to melanocytes. In 526 cells, 60s acidic ribosomal protein p1 and calreticulin precursor were more highly expressed than in melanocytes. These molecular differences may help in better understanding melanoma development and its different responsiveness to therapies. The identified proteins could be exploited as biomarkers or therapeutic targets for melanoma.     

Protein expression pattern distinguishes different lymphoid neoplasms

To identify proteins associated with the histological subtypes of lymphoid neoplasms, we studied the proteomes of 42 cell lines from human lymphoid neoplasms including Hodgkin's lymphoma (HL; four cell lines), B cell malignancies (19 cell lines), T cell malignancies (16 cell lines), and natural killer (NK) cell lymphoma (three cell lines). The protein spots were sequentially selected by (i) Wilcoxon or Kruskal-Wallis tests to find the spots whose intensity was significantly (p <0.05) different among the cell line groups, (ii) by statistical-learning methods to prioritize the spots according to their contribution to the classification, and (iii) by unsupervised classification methods to validate the classification robustness by the selected spots. The selected spots discriminated (i) between HL cells and other cells, (ii) between the cells from B cell malignancies, T cell malignancies, and NK cell lymphoma cells, and (iii) between HL cells and anaplastic large cell lymphoma cells. Among the 31 informative protein spots, MS identified 24 proteins corresponding to 23 spots. Previous reports did not correlate these proteins to lymphocyte differentiation, suggesting that a proteomic study would identify the novel mechanisms responsible for the histogenesis of lymphoid neoplasms. These proteins may have potential as differential diagnostic markers for lymphoid neoplasms.     

Establishment of a near-standard two-dimensional human urine proteomic map

A proteomic map for human urine on two-dimensional (2-D) gels has been developed. Initial studies demonstrated that the urine proteins prepared by conventional methods showed interference and poor reproducibility in 2-D electrophoresis (2-DE). To address this issue, urine samples were dialyzed to remove any interfering molecules. The dialysis of urine proteins and the concentration by lyophilization without fractionation significantly improved the reproducibility and resolution and likely represents the total urine proteins on a 2-D gel. In addition, removing albumin from urine using Affi-Gel Blue helped to identify the low-abundant proteins. Using the developed method, we prepared proteins from urine collected from healthy females and males. The large inter- and intra-subject variation in protein profiles on 2-D gels made it difficult to establish a normal human urine proteomic 2-D map. To resolve this problem, urinary proteins were prepared from the pooled urine collected from 20 healthy females and males, respectively. The established male and female urine proteomes separated on 2-D gels were almost identical except for some potential sex-dependent protein spots. We have annotated 113 different proteins on the 2-D gel by peptide mass fingerprinting (PMF). We propose that the established total urine proteome can be used for 2-DE analysis, liquid chromatography-tandem mass spectrometry (LC-MS/MS), and identification of novel disease-specific biomarkers.     

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.     

Quantitative proteomic analysis of LPS-induced differential immune response associated with TLR4 Polymorphisms by multiplex amino acid coded mass tagging

Polymorphisms at toll-like receptor 4 (TLR4) gene have been found to be associated with immune disorders. A murine macrophage cell line GG2EE derived from C3H/HeJ mice with a polymorphism site at TLR4 is hyposensitive to lipopolysaccharide (LPS). To study the molecular base of diverse TLR4-mediated immune responses, the proteomic changes in both TLR4-deficient and wild-type cell lines in response to the same LPS challenge were quantitatively compared by using multiplex amino acid coded mass tagging (AACT)/SILAC-assisted MS. This strategy allows encoding of two distinct cell populations with different stable isotope-tagged lysine residues as the "in-spectra" quantitative markers. In MS analysis of tryptic peptides derived from the equally mixed three cell populations, the lysine-containing peptides originated from two LPS-stimulated cell populations can be clearly distinguished by their different mass shifts from the unstimulated and unlabeled counterpart. The LPS-induced differential protein expression in TLR4-deficient and wild-type proteomes were obtained by comparing the intensities of isotopically encoded peptides. Among the more than 900 proteins identified, 35 were found to be deregulated at different levels in these two cell lines stimulated by LPS. This multiplex mass-tagging methodology can be readily extended to other comparative proteomic quantitation of different cell populations.     

Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics

Mass spectrometry (MS)-based proteomics is increasingly applied in a quantitative format, often based on labeling of samples with stable isotopes that are introduced chemically or metabolically. In the stable isotope labeling by amino acids in cell culture (SILAC) method, two cell populations are cultured in the presence of heavy or light amino acids (typically lysine and/or arginine), one of them is subjected to a perturbation, and then both are combined and processed together. In this study, we describe a different approach--the use of SILAC as an internal or 'spike-in' standard--wherein SILAC is only used to produce heavy labeled reference proteins or proteomes. These are added to the proteomes under investigation after cell lysis and before protein digestion. The actual experiment is therefore completely decoupled from the labeling procedure. Spike-in SILAC is very economical, robust and in principle applicable to all cell- or tissue-based proteomic analyses. Applications range from absolute quantification of single proteins to the quantification of whole proteomes. Spike-in SILAC is especially advantageous when analyzing the proteomes of whole tissues or organisms. The protocol describes the quantitative analysis of a tissue sample relative to super-SILAC spike-in, a mixture of five SILAC-labeled cell lines that accurately represents the tissue. It includes the selection and preparation of the spike-in SILAC standard, the sample preparation procedure, and analysis and evaluation of the results.     

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

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

Proteomic analysis of cervical cancer cells treated with suberonylanilide hydroxamic acid

Suberonylanilide hydroxamic acid (SAHA) is an orally administered histone deacetylase inhibitor (HDACI) that has shown significant antitumour activity in a variety of tumour cells. To identify proteins involved in its antitumour activity, we utilized a proteomic approach to reveal protein expression changes in the human cervical cancer cell line HeLa following SAHA treatment. Protein expression profiles were analysed by 2-dimensional polyacrylamide gel electrophoresis (2-DE) and protein identification was performed on a MALDI-Q-TOF MS/MS instrument. As a result, a total of nine differentially expressed proteins were visualized by 2-DE and Coomassie brilliant blue (CBB) staining. Further, all the changed proteins were positively identified via mass spectrometry (MS)/MS analysis. Of these, PGAM1 was significantly downregulated in HeLa cells after treatment with SAHA. Moreover, PGAM1 has been proven to be downregulated in another cervical cancer cell line (CaSki) by western blot analysis. Together, using proteomic tools, we identified several differentially expressed proteins that underwent SAHA-induced apoptosis. These changed proteins may provide some clues to a better understanding of the molecular mechanisms underlying SAHA-induced apoptosis in cervical cancer.     

Comprehensive proteomics in yeast using chromatographic fractionation, gas phase fractionation, protein gel electrophoresis, and isoelectric focusing

We have investigated the use of a variety of different techniques to identify as many proteins as possible in a yeast lysate, with the aim of investigating the overlap and complementarity of data from different approaches. A standard lysate was prepared from log phase yeast (Saccharomyces cerevisiae). This was then subjected to analysis via five different approaches aimed at identifying as many proteins as possible using an ion trap mass spectrometer. The total number of non-redundant protein identifications from each experiment was: 524 proteins by 2-D (SCX/C18) nanoflow liquid chromatography-liquid chromatography tandem mass spectrometry (nanoLC-LC MS/MS (MudPIT)); 381 proteins by nanoLC-MS/MS with gas phase fractionation by mass range selection; 390 proteins by nanoLC-MS/MS with gas phase fractionation by ion abundance selection; 898 proteins by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) separation of proteins, in-gel digestion, and nanoLC-MS/MS of gel slices; and 422 proteins by isoelectric focusing of proteins, in-gel digestion and nanoLC-MS/MS of gel slices. The total number of non-redundant protein identifications in the five experiments was 1204. Combining only the two best experiments, the SDS-PAGE gel slices and the Mudpit, produces 1024 proteins identified, more than 85% of the total. Clearly, combining a Mudpit analysis with an SDS-PAGE gel slice experiment gives the greatest amount of protein identification information from a limited amount of sample.     

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

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

A proteomic approach to analysing spheroid formation of two human thyroid cell lines cultured on a random positioning machine

The human cell lines FTC-133 and CGTH W-1, both derived from patients with thyroid cancer, assemble to form different types of spheroids when cultured on a random positioning machine. In order to obtain a possible explanation for their distinguishable aggregation behaviour under equal culturing conditions, we evaluated a proteomic analysis emphasising cytoskeletal and membrane-associated proteins. For this analysis, we treated the cells by ultrasound, which freed up some of the proteins into the supernatant but left some attached to the cell fragments. Both types of proteins were further separated by free-flow IEF and SDS gel electrophoresis until their identity was determined by MS. The MS data revealed differences between the two cell lines with regard to various structural proteins such as vimentin, tubulins and actin. Interestingly, integrin α-5 chains, myosin-10 and filamin B were only found in FTC-133 cells, while collagen was only detected in CGTH W-1 cells. These analyses suggest that FTC-133 cells express surface proteins that bind fibronectin, strengthening the three-dimensional cell cohesion.     

Accurate qualitative and quantitative proteomic analysis of clinical hepatocellular carcinoma using laser capture microdissection coupled with isotope-coded affinity tag and two-dimensional liquid chromatography mass spectrometry

Laser capture microdissection (LCM) is a powerful tool that enables the isolation of specific cell types from tissue sections, overcoming the problem of tissue heterogeneity and contamination. This study combined the LCM with isotope-coded affinity tag (ICAT) technology and two-dimensional liquid chromatography to investigate the qualitative and quantitative proteomes of hepatocellular carcinoma (HCC). The effects of three different histochemical stains on tissue sections have been compared, and toluidine blue stain was proved as the most suitable stain for LCM followed by proteomic analysis. The solubilized proteins from microdissected HCC and non-HCC hepatocytes were qualitatively and quantitatively analyzed with two-dimensional liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) alone or coupled with cleavable ICAT labeling technology. A total of 644 proteins were qualitative identified, and 261 proteins were unambiguously quantitated. These results show that the clinical proteomic method using LCM coupled with ICAT and 2D-LC-MS/MS can carry out not only large-scale but also accurate qualitative and quantitative analysis.     

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

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

Low Cell Number Proteomic Analysis Using In-Cell Protease Digests Reveals a Robust Signature for Cell Cycle State Classification

Comprehensive proteome analysis of rare cell phenotypes remains a significant challenge. We report a method for low cell number MS-based proteomics using protease digestion of mildly formaldehyde-fixed cells in cellulo, which we call the “in-cell digest.” We combined this with averaged MS1 precursor library matching to quantitatively characterize proteomes from low cell numbers of human lymphoblasts. About 4500 proteins were detected from 2000 cells, and 2500 proteins were quantitated from 200 lymphoblasts. The ease of sample processing and high sensitivity makes this method exceptionally suited for the proteomic analysis of rare cell states, including immune cell subsets and cell cycle subphases. To demonstrate the method, we characterized the proteome changes across 16 cell cycle states (CCSs) isolated from an asynchronous TK6 cells, avoiding synchronization. States included late mitotic cells present at extremely low frequency. We identified 119 pseudoperiodic proteins that vary across the cell cycle. Clustering of the pseudoperiodic proteins showed abundance patterns consistent with “waves” of protein degradation in late S, at the G2&M border, midmitosis, and at mitotic exit. These clusters were distinguished by significant differences in predicted nuclear localization and interaction with the anaphase-promoting complex/cyclosome. The dataset also identifies putative anaphase-promoting complex/cyclosome substrates in mitosis and the temporal order in which they are targeted for degradation. We demonstrate that a protein signature made of these 119 high-confidence cell cycle–regulated proteins can be used to perform unbiased classification of proteomes into CCSs. We applied this signature to 296 proteomes that encompass a range of quantitation methods, cell types, and experimental conditions. The analysis confidently assigns a CCS for 49 proteomes, including correct classification for proteomes from synchronized cells. We anticipate that this robust cell cycle protein signature will be crucial for classifying cell states in single-cell proteomes.     

Proteomic profiling of lipid droplet proteins in hepatoma cell lines expressing hepatitis C virus core protein

Hepatitis C virus (HCV) core protein has been suggested to play crucial roles in the pathogeneses of liver steatosis and hepatocellular carcinomas due to HCV infection. Intracellular HCV core protein is localized mainly in lipid droplets, in which the core protein should exert its significant biological/pathological functions. In this study, we performed comparative proteomic analysis of lipid droplet proteins in core-expressing and non-expressing hepatoma cell lines. We identified 38 proteins in the lipid droplet fraction of core-expressing (Hep39) cells and 30 proteins in that of non-expressing (Hepswx) cells by 1-D-SDS-PAGE/MALDI-TOF mass spectrometry (MS) or direct nanoflow liquid chromatography-MS/MS. Interestingly, the lipid droplet fraction of Hep39 cells had an apparently lower content of adipose differentiation-related protein and a much higher content of TIP47 than that of Hepswx cells, suggesting the participation of the core protein in lipid droplet biogenesis in HCV-infected cells. Another distinct feature is that proteins involved in RNA metabolism, particularly DEAD box protein 1 and DEAD box protein 3, were detected in the lipid droplet fraction of Hep39 cells. These results suggest that lipid droplets containing HCV core protein may participate in the RNA metabolism of the host and/or HCV, affecting the pathopoiesis and/or virus replication/production in HCV-infected cells.     

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors

In-depth analyses of cancer cell proteomes are needed to elucidate oncogenic pathomechanisms, as well as to identify potential drug targets and diagnostic biomarkers. However, methods for quantitative proteomic characterization of patient-derived tumors and in particular their cellular subpopulations are largely lacking. Here we describe an experimental set-up that allows quantitative analysis of proteomes of cancer cell subpopulations derived from either liquid or solid tumors. This is achieved by combining cellular enrichment strategies with quantitative Super-SILAC-based mass spectrometry followed by bioinformatic data analysis. To enrich specific cellular subsets, liquid tumors are first immunophenotyped by flow cytometry followed by FACS-sorting; for solid tumors, laser-capture microdissection is used to purify specific cellular subpopulations. In a second step, proteins are extracted from the purified cells and subsequently combined with a tumor-specific, SILAC-labeled spike-in standard that enables protein quantification. The resulting protein mixture is subjected to either gel electrophoresis or Filter Aided Sample Preparation (FASP) followed by tryptic digestion. Finally, tryptic peptides are analyzed using a hybrid quadrupole-orbitrap mass spectrometer, and the data obtained are processed with bioinformatic software suites including MaxQuant. By means of the workflow presented here, up to 8,000 proteins can be identified and quantified in patient-derived samples, and the resulting protein expression profiles can be compared among patients to identify diagnostic proteomic signatures or potential drug targets.     

Profiling signatures of ovarian cancer tumour suppression using 2D-DIGE and 2D-LC-MS/MS with tandem mass tagging

Epithelial ovarian cancer (EOC) is the most common form of gynaecological malignancy in the developed world and has a poor prognosis due to its late detection. Identifying molecular markers of the disease may provide novel approaches to screening and could enable targeted treatment and the design of novel therapies. Although blood is recognized as a highly important source of disease-related biomarkers, the complexity and dynamic range of protein abundance in body fluids has hampered proteomic biomarker discovery and alternative approaches using cell models may be more successful. Herein, we have utilized two cellular models of EOC, where transfer of normal chromosome 18 material into the EOC cell lines TOV-112D and TOV-21G induced in vitro and in vivo suppression of their tumourigenic phenotype. A combination of quantitative two-dimensional difference gel electrophoresis (2D-DIGE) and two-dimensional-liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) with tandem mass tagging (TMT) was employed to examine the whole cell, secreted and crude membrane proteomes of the parental and hybrid cell models to identify differentially expressed proteins as potential markers of tumour suppression. Protein changes of interest were confirmed by immunoblotting in additional hybrid and revertant cell lines where incorporated chromosome 18 material was lost. One candidate marker was also tested in sera from a set of ovarian cancer cases and controls. We have identified a list of promising candidate biomarkers for further testing and functional characterization.     

Characterization of the Asia Oceania Human Proteome Organisation Membrane Proteomics Initiative Standard using SDS-PAGE shotgun proteomics

Although there are now multiple methods for the analysis of membrane proteomes, there is relatively little systematic characterization of proteomic workflows for membrane proteins. The Asia Oceania Human Proteome Organisation (AOHUPO) has therefore embarked on a Membrane Proteomics Initiative (MPI) using a large range of workflows. Here, we describe the characterization of the MPI mouse liver microsomal membrane Standard using SDS-PAGE prior to in-gel tryptic digestion and LC-ESI-MS/MS. The Na(2) CO(3) wash followed by SDS-PAGE prior to in-gel tryptic digestion and LC-MS/MS strategy was effective for the detection of membrane proteins with 47.1% of the identified proteins being transmembrane proteins. Gene Ontology term enrichment analysis showed that biological processes involving transport, lipid metabolism, cell communication, cell adhesion, and cellular component organization were significantly enriched. Comparison of the present data with the previously published reports on mouse liver proteomes confirmed that the MPI Standard provides an excellent resource for the analysis of membrane proteins in the AOHUPO MPI.