Enhanced detection of low abundance human plasma proteins using a tandem IgY12-SuperMix immunoaffinity separation strategy

The enormous dynamic range of human bodily fluid proteomes poses a significant challenge for current MS-based proteomics technologies as it makes it especially difficult to detect low abundance proteins in human biofluids such as blood plasma, which is an essential aspect for successful biomarker discovery efforts. Here we present a novel tandem IgY12-SuperMix immunoaffinity separation system for enhanced detection of low abundance proteins in human plasma. The tandem IgY12-SuperMix system separates approximately 60 abundant proteins from the low abundance proteins in plasma, allowing for significant enrichment of low abundance plasma proteins in the SuperMix flow-through fraction. High reproducibility of the tandem separations was observed in terms of both sample processing recovery and LC-MS/MS identification results based on spectral count data. The ability to quantitatively measure differential protein abundances following application of the tandem separations was demonstrated by spiking six non-human standard proteins at three different levels into plasma. A side-by-side comparison between the SuperMix flow-through and IgY12 flow-through samples analyzed by both one- and two-dimensional LC-MS/MS revealed a 60-80% increase in proteome coverage as a result of the SuperMix separations, suggesting significantly enhanced detection of low abundance proteins. A total of 695 plasma proteins were confidently identified in a single analysis (with a minimum of two peptides per protein) by coupling the tandem separation strategy with two-dimensional LC-MS/MS, including 42 proteins with reported normal concentrations of approximately 100 pg/ml to 100 ng/ml. The concentrations of two selected proteins, macrophage colony-stimulating factor 1 and matrix metalloproteinase-8, were independently validated by ELISA as 202 pg/ml and 12.4 ng/ml, respectively. Evaluation of binding efficiency revealed that 45 medium abundance proteins were efficiently captured by the SuperMix column with >90% retention. Taken together, these results illustrate the potential broad utilities of this tandem IgY12-SuperMix strategy for proteomics applications involving human biofluids where effectively addressing the dynamic range challenge of the specimen is imperative.     

Proteomic analysis of eccrine sweat: implications for the discovery of schizophrenia biomarker proteins

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately 2-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers.     

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.     

Proteomics-Driven Analysis of Ovine Whey Colostrum

The aim of this study was to shed light in to the complexity of the ovine colostrum proteome, with a specific focus on the low abundance proteins. The ovine colostrum is characterized by a few dominating proteins, as the immunoglobulins, but it also contains less represented protein species, equally important for the correct development of neonates. Ovine colostrum, collected immediately after lambing, was separated by 1D SDS-PAGE. Proteins bands were digested with trypsin and the resulting peptides were analyzed by LC-MS/MS. On the basis of the Swiss-Prot database, a total of 343 unique proteins were identified. To our knowledge, this study represents the most comprehensive analysis of ovine colostrum proteome.     

Characterization of the human gastric fluid proteome reveals distinct pH-dependent protein profiles: implications for biomarker studies

Gastric fluid is a source of gastric cancer biomarkers. However, very little is known about the normal gastric fluid proteome and its biological variations. In this study, we performed a comprehensive analysis of the human gastric fluid proteome using samples obtained from individuals with benign gastric conditions. Gastric fluid proteins were prefractionated using ultracentrifuge filters (3 kDa cutoff) and analyzed by two-dimensional gel electrophoresis (2-DE) and multidimensional LC-MS/MS. Our 2-DE analysis of 170 gastric fluid samples revealed distinct protein profiles for acidic and neutral samples, highlighting pH effects on protein composition. By 2D LC-MS/MS analysis of pooled samples, we identified 284 and 347 proteins in acidic and neutral samples respectively (FDR ≤1%), of which 265 proteins (72.4%) overlapped. However, unlike neutral samples, most proteins in acidic samples were identified from peptides in the filtrate (i.e., <3 kDa). Consistent with this finding, immunoblot analysis of six potential gastric cancer biomarkers rarely detected full-length proteins in acidic samples. These findings have important implications for biomarker studies because a majority of gastric cancer patients have neutral gastric fluid compared to noncancer controls. Consequently, sample stratification, choice of proteomic approaches, and validation strategy can profoundly affect the interpretation of biomarker findings. These observations should help to refine gastric fluid biomarker studies.     

Improvements in proteomic metrics of low abundance proteins through proteome equalization using ProteoMiner prior to MudPIT

Ideally, shotgun proteomics would facilitate the identification of an entire proteome with 100% protein sequence coverage. In reality, the large dynamic range and complexity of cellular proteomes results in oversampling of abundant proteins, while peptides from low abundance proteins are undersampled or remain undetected. We tested the proteome equalization technology, ProteoMiner, in conjunction with Multidimensional Protein Identification Technology (MudPIT) to determine how the equalization of protein dynamic range could improve shotgun proteomics methods for the analysis of cellular proteomes. Our results suggest low abundance protein identifications were improved by two mechanisms: (1) depletion of high abundance proteins freed ion trap sampling space usually occupied by high abundance peptides and (2) enrichment of low abundance proteins increased the probability of sampling their corresponding more abundant peptides. Both mechanisms also contributed to dramatic increases in the quantity of peptides identified and the quality of MS/MS spectra acquired due to increases in precursor intensity of peptides from low abundance proteins. From our large data set of identified proteins, we categorized the dominant physicochemical factors that facilitate proteome equalization with a hexapeptide library. These results illustrate that equalization of the dynamic range of the cellular proteome is a promising methodology to improve low abundance protein identification confidence, reproducibility, and sequence coverage in shotgun proteomics experiments, opening a new avenue of research for improving proteome coverage.     

Rat plasma proteomics: effects of abundant protein depletion on proteomic analysis

The proteomic analysis of plasma and serum samples represents a formidable challenge due to the presence of a few highly abundant proteins such as albumin and immunoglobulins. Detection of low abundance protein biomarkers requires therefore either the specific depletion of high abundance proteins with immunoaffinity columns and/or optimized protein fractionation methods based on charge, size or hydrophobicity. Here we describe the depletion of seven abundant rat plasma proteins with an immunoaffinity column with coupled antibodies directed against albumin, IgG, transferrin, IgM, haptoglobin, fibrinogen and alpha1-anti-trypsin. The IgY-R7-LC2 (Beckman Coulter) column showed high specificity for the targeted proteins and was able to efficiently remove most of the albumin, IgG and transferrin from rat plasma samples as judged by Western blot analysis. Depleted rat plasma protein samples were analyzed by SELDI-TOF MS, 2D SDS-PAGE and 2D-LC and compared to non-depleted plasma samples as well as to the abundant protein fraction that was eluted from the immunoaffinity column. Analysis of the depleted plasma protein fraction revealed improved signal to noise ratios, regardless of which proteomic method was applied. However, only a small number of new proteins were observed in the depleted protein fraction. Immunoaffinity depletion of abundant plasma proteins results in the significant dilution of the original sample which complicates subsequent analysis. Most proteomic approaches require specialized sample preparation procedures during which significant losses of less abundant proteins and potential biomarkers can occur. Even though abundant protein depletion reduces the dynamic range of the plasma proteome by about 2-3 orders of magnitude, the difference between medium-abundant and low abundant plasma proteins is still in the range of 7-8 orders of magnitude and beyond the dynamic range of current proteomic technologies. Thus, exploring the plasma proteome in greater detail remains a daunting task.     

Proteomic analysis of cervical-vaginal fluid: identification of novel biomarkers for detection of intra-amniotic infection

Intra-amniotic infection (IAI) is associated with preterm birth and perinatal mortality. To identify potential biomarkers, we performed a comprehensive survey of the cervical-vaginal fluid (CVF) proteome from a primate IAI model utilizing multidimensional protein identification technology (LC/LC-MS/MS) and MALDI-TOF-MS analyses. Analyses of CVF proteome identified 205 unique proteins and differential expression of 27 proteins in controls and IAI samples. Protein expression signatures and immunodetection of specific biomarkers identified can be employed for noninvasive detection of IAI.     

Analysis of the human serum proteome

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

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.     

Improved proteome coverage by using high efficiency cysteinyl peptide enrichment: the human mammary epithelial cell proteome

Automated multidimensional capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been increasingly applied in various large scale proteome profiling efforts. However, comprehensive global proteome analysis remains technically challenging due to issues associated with sample complexity and dynamic range of protein abundances, which is particularly apparent in mammalian biological systems. We report here the application of a high efficiency cysteinyl peptide enrichment (CPE) approach to the global proteome analysis of human mammary epithelial cells (HMECs) which significantly improved both sequence coverage of protein identifications and the overall proteome coverage. The cysteinyl peptides were specifically enriched by using a thiol-specific covalent resin, fractionated by strong cation exchange chromatography, and subsequently analyzed by reversed-phase capillary LC-MS/MS. An HMEC tryptic digest without CPE was also fractionated and analyzed under the same conditions for comparison. The combined analyses of HMEC tryptic digests with and without CPE resulted in a total of 14 416 confidently identified peptides covering 4294 different proteins with an estimated 10% gene coverage of the human genome. By using the high efficiency CPE, an additional 1096 relatively low abundance proteins were identified, resulting in 34.3% increase in proteome coverage; 1390 proteins were observed with increased sequence coverage. Comparative protein distribution analyses revealed that the CPE method is not biased with regard to protein M(r) , pI, cellular location, or biological functions. These results demonstrate that the use of the CPE approach provides improved efficiency in comprehensive proteome-wide analyses of highly complex mammalian biological systems.     

Evaluation of multiprotein immunoaffinity subtraction for plasma proteomics and candidate biomarker discovery using mass spectrometry

Strategies for removal of high abundance proteins have been increasingly utilized in proteomic studies of serum/plasma and other body fluids to enhance the detection of low abundance proteins and achieve broader proteome coverage; however, both the reproducibility and specificity of the high abundance protein depletion process still represent common concerns. Here we report a detailed evaluation of immunoaffinity subtraction performed applying the ProteomeLab IgY-12 system that is commonly used in human serum/plasma proteome characterization in combination with high resolution LC-MS/MS. Plasma samples were repeatedly processed using this approach, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. The removal of target proteins by the immunoaffinity subtraction system and the overall process was highly reproducible. Non-target proteins, including one spiked protein standard (rabbit glyceraldehyde-3-phosphate dehydrogenase), were also observed to bind to the column at different levels but also in a reproducible manner. The results suggest that multiprotein immunoaffinity subtraction systems can be readily integrated into quantitative strategies to enhance detection of low abundance proteins in biomarker discovery studies.     

Low abundance protein enrichment for discovery of candidate plasma protein biomarkers for early detection of breast cancer

Molecular biomarkers of early stage breast cancer may improve the sensitivity and specificity of diagnosis. Plasma biomarkers have additional value in that they can be monitored with minimal invasiveness. Plasma biomarker discovery by genome-wide proteomic methods is impeded by the wide dynamic range of protein abundance and the heterogeneity of protein expression in healthy and disease populations which requires the analysis of a large number of samples. We addressed these issues through the development of a novel protocol that couples a combinatorial peptide ligand library protein enrichment strategy with isobaric label-based 2D LC-MS/MS for the identification of candidate biomarkers in high throughput. Plasma was collected from patients with stage I breast cancer or benign breast lesions. Low abundance proteins were enriched using a bead-based combinatorial library of hexapeptides. This resulted in the identification of 397 proteins, 22% of which are novel plasma proteins. Twenty-three differentially expressed plasma proteins were identified, demonstrating the effectiveness of the described protocol and defining a set of candidate biomarkers to be validated in independent samples. This work can be used as the basis for the design of properly powered investigations of plasma protein expression for biomarker discovery in larger cohorts of patients with complex disease.     

Quantitative proteomic profiling of pancreatic cancer juice

Pancreatic juice is an exceptionally rich source of cancer-specific proteins shed from cancerous ductal cells into the pancreatic juice. Quantitative proteomic analysis of the proteins specific to pancreatic cancer juice has not previously been reported. We used isotope-code affinity tag (ICAT) technology and MS/MS to perform quantitative protein profiling of pancreatic juice from pancreatic cancer patients and normal controls. ICAT technology coupled with MS/MS allows the systematic study of the proteome and measures the protein abundance in pancreatic juice with the potential for development of biomarkers. A total of 105 proteins were identified and quantified in the pancreatic juice from a pancreatic cancer patient, of which 30 proteins showed abundance changes of at least twofold in pancreatic cancer juice compared to normal controls. Many of these proteins have been externally validated. This is the first comprehensive study of the pancreatic juice proteome by quantitative global protein profiling, and the study reveals numerous proteins that are shown for the first time to be associated with pancreatic cancer, providing candidates for diagnostic biomarkers. One of the identified proteins, insulin-like growth factor binding protein-2 was further validated by Western blotting to be elevated in pancreatic cancer juice and overexpressed in pancreatic cancer tissue.     

Expanding the zebrafish embryo proteome using multiple fractionation approaches and tandem mass spectrometry

The proteome of zebrafish, Danio rerio, embryos has not been studied in great detail mainly due to the presence of high abundance yolk proteins in embryos. Here we report the highest number of the zebrafish embryo proteins identified so far to our knowledge, through a combination of a protein-level fractionation approach (1D SDS-PAGE) and two different peptide-level fractionation approaches (IEF and strong anion exchange (SAX)) of deyolked zebrafish embryos followed by LC-MS/MS. We detected 5267 proteins in total of which 3464 proteins were identified with at least two peptides (less than 1% peptide false discovery rate). The analysis of proteome coverage from each method showed that 56% of detected proteins were common to all approaches and 95% of the detected proteome was obtained from 1D SDS-PAGE approach alone. Bioinformatics analysis of the detected proteome demonstrated that nucleocytoplasmic transport (biological process) and ribosomal proteins (cellular component) were the most over-represented proteins, whereas cell-cell signaling (biological process) and extracellular space proteins (cellular component) were the most under-represented proteins in the identified proteome.     

Identification of differentially secreted biomarkers using LC-MS/MS in isogenic cell lines representing a progression of breast cancer

Proteins secreted (the secretome) from cancer cells are potentially useful as biomarkers of the disease. Using LC-MS/MS, the secreted proteomes from a series of isogenic breast cancer cell lines varying in aggressiveness were analyzed by mass spectrometry: nontumorigenic MCF10A, premalignant/tumorigenic MCF10AT, tumorigenic/locally invasive MCF10 DCIS.com, and tumorigenic/metastatic MCF 10CA cl. D. Proteomes were obtained from conditioned serum-free media, partially fractionated using a small reverse phase C2 column, and digested with trypsin for analysis by LC-MS/MS, using a method previously shown to give highly enriched secreted proteomes (Mbeunkui et al. J. Proteome Res. 2006, 5, 899-906). The search files produced from five analyses (three separate preparations) were combined for database searching (Mascot) which produced a list of over 250 proteins from each cell line. The aim was to discover highly secreted proteins which changed significantly in abundance corresponding with aggressiveness. The most apparent changes were observed for alpha-1-antichymotrypsin and galectin-3-binding protein which were highly secreted proteins from MCF10 DCIS.com and MCF10CA cl. D, yet undetected in the MCF10A and MCF10AT cell lines. Other proteins showing increasing abundance in the more aggressive cell lines included alpha-1-antitrypsin, cathepsin D, and lysyl oxidase. The S100 proteins, often associated with metastasis, showed variable changes in abundance. While the cytosolic proteins were low (e.g., actin and tubulin), there was significant secretion of proteins often associated with the cytoplasm. These proteins were all predicted as products of nonclassical secretion (SecretomeP, Center for Biological Sequence Analysis). The LC-MS/MS results were verified for five selected proteins by western blot analysis, and the relevance of other significant proteins is discussed. Comparisons with two other aggressive breast cancer cell lines are included. The protein with consistent association with aggressiveness in all lines, and in unrelated cancer cells, was the galectin-3-binding protein which has been associated with breast, prostate, and colon cancer earlier, supporting the approach and findings. This analysis of an isogenic series of cell lines suggests the potential usefulness of the secretome for identifying prospective markers for the early detection and aggressiveness/progression of cancer.     

Wheat mitochondrial proteomes provide new links between antioxidant defense and plant salinity tolerance

The mitochondrial proteome and differences associated with salt tolerance have been investigated in Australian commercial varieties of wheat. Mitochondria isolated from shoots were used to generate a wheat mitochondrial reference map; 68 unique wheat mitochondrial proteins were identified from 192 gel spots using 2D PAGE and LC-MS/MS. This analysis also provided MS/MS spectra for 199 proteotypic peptides as a foundation for the development of targeted proteomics to study the respiratory apparatus in wheat. Using this reference map and 2D DIGE, we have found quantitative differences in the shoot mitochondrial proteomes of v. Wyalkatchem and v. Janz, two commercially important wheat varieties that are known from a range of experiments to differ in salinity tolerance. These proteins included Mn-superoxide dismutase (Mn-SOD), cysteine synthase, nucleotide diphosphate kinase, and the voltage dependent anion channel (VDAC). Antibodies to the mitochondrial alternative oxidase (AOX), previously linked to reduced ROS formation from the electron transport chain and salt tolerance in Arabidopsis, also showed a commensurate higher abundance in v. Wyakatchem in both control and salt-treated conditions. Together, the data presented here suggest that differences in mitochondrial ROS defense pathways in the mitochondrial proteomes of key Australian wheat varieties correlate with whole-plant salinity tolerance.     

Systematic discovery of ectopic pregnancy serum biomarkers using 3-D protein profiling coupled with label-free quantitation

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker discovery strategy consisting of abundant protein immunodepletion, SDS gels, LC-MS/MS, and label-free quantitation of MS signal intensities identified 70 candidate biomarkers with differences between groups greater than 2.5-fold. Further statistical analyses of peptide quantities were used to select the most promising 12 biomarkers for further study, which included known EP biomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specific isoforms of the pregnancy specific beta-1-glycoprotein family. Technical replicates showed good reproducibility and protein intensities from the label-free discovery analysis compared favorably with reported abundance levels of several known reference serum proteins over at least 3 orders of magnitude. Similarly, relative abundances of candidate biomarkers from the label-free discovery analysis were consistent with relative abundances from pilot validation assays performed for five of the 12 most promising biomarkers using label-free multiple reaction monitoring of both the patient serum pools used for discovery and the individual samples that constituted these pools. These results demonstrate robust, reproducible, in-depth 3-D serum proteome discovery, and subsequent pilot-scale validation studies can be achieved readily using label-free quantitation strategies.     

应用蛋白质组学筛选宫颈癌患者尿液中的肿瘤标志物

通过比较健康女性和宫颈癌患者的尿蛋白质组,发现并分析差异表达蛋白,从中筛选潜在的宫颈癌的标志物。研究对象由43名宫颈癌患者（CC）和47名健康女性（HW）组成。用超速离心法沉淀尿蛋白,再用一维凝胶电泳（SDS-PAGE）与液相色谱-质谱联用技术（LC-MS/MS）鉴定尿液中的蛋白质,蛋白质定量采用无标定量。比较患者尿蛋白质组、健康对照的尿蛋白质组和宫颈癌组织蛋白质组,有1910个蛋白质是患者和健康对照共有的尿蛋白,这其中有746个蛋白质也存在于宫颈癌组织蛋白质组。在这746个蛋白质中找到84个上调蛋白和82下调蛋白。通过生物信息学分析发现牛皮癣素（S100A7）和癌胚抗原相关细胞黏附分子8（CEACAM8）是宫颈癌尿液样本独有蛋白质。在验证组的70例样本中,双盲法测试S100A7、CEACAM8以及两者联合诊断宫颈癌的敏感性能达到73%、87%、93%。结果提示,宫颈癌患者的尿蛋白质组与健康女性的尿蛋白质组不同,并且S100A7和CEACAM8可以作为宫颈癌潜在的肿瘤标志物。     

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.