Human Proteome Database Research Articles

#4547 IDENTIFICATION OF GLYCOSYLATED IGF2 IN HUMAN URINARY PEPTIDOME AND ITS ASSOCIATION WITH CKD

Abstract Background and Aims Chronic kidney disease (CKD) is prevalent in 10% of world's adult population, with estimated glomerular filtration rate (eGFR) and albuminuria employed in its diagnosis. Role of protein glycosylation in causal mechanisms of CKD progression is largely unknown. Aim of this study was to identify urinary O-linked glycopeptides in association to CKD for better characterization of CKD molecular manifestations. Method Urine samples from eight CKD and two healthy subjects were analyzed by Capillary Electrophoresis-Tandem Mass Spectroscopy (CE-MS/MS) and glycopeptide analysis using Proteome Discoverer 1.4 was performed. Distribution of identified glycopeptides and correlation with Age, eGFR and Albuminuria were evaluated in 3810 datasets from the Human Urinary Proteome database using Spearman's rank correlation test and multiple linear regression analysis by statistical software R. The quantification of Insulin-like growth factor-II (IGF2) protein (7.5 kDa) was performed by enzyme-linked immunosorbent assay (ELISA) in two matched (for age, sex, no diabetes and no cardiovascular history) groups of 12 plasma samples each (eGFR < 30 ml/min/1.73m2 and eGFR > 90 ml/min/1.73m2). An open-source tool “Proteasix” was used to predict proteases involved in cleavage of the identified glycopeptides. The transcriptomics database and analysis tool “Nephroseq v4” were utilized to investigate the expression of predicted proteases in existing human transcriptomics CKD datasets. Results In total, 17 O-linked glycopeptides from 7 different proteins were identified, derived primarily from Insulin-like growth factor-II (IGF2) (n = 6). Glycosylation occurred at the surface exposed IGF2 Threonine 96 position. Further Investigation of the human proteome database containing 3810 datasets, showed that only three unglycosylated urinary peptides of IGF2 were identified, at significantly lower abundance and frequency (0-2.5% in the database) in comparison to the glycosylated forms (frequency of 23-90%). Interestingly, all identified IGF2 peptides belonged to E-domain of IGF2, i.e., 92 – 180 aa; which cleaves after undergoing O-linked glycosylation during the post-translational process yielding the “mature IGF2” (25-91 aa) protein. Results of multiple linear regression analysisa indicated that three IGF2 glycopeptides, DVStPPTVLPDNFPRYPVGKF [β(1024) = 0.08, p = 1.42*10−4], DVStPPTVLPDNFPRYPVG [β(560) = 0.01, p = 5.22*10−5] and DVStPPTVLPDNFPRYP [β(290) = 0.02, p = 1.07*10−4], exhibited positive correlation with Age and the glycopeptide tPPTVLPDNFPRYP showed strong negative association with eGFR [β(177) = -0.01, p = 4.21*10−9]. Along the same lines, the latter urinary IGF2 glycopeptide tPPTVLPDNFPRYP was found at increased [p < 2.2*10−16] abundance in CKD (n = 686) in comparison to healthy control (n = 229) datasets. In addition, IGF2 increased [p = 0.042] plasma levels were observed in CKD patients (eGFR < 30 ml/min/1.73m2 group) as supported by ELISA measurements. Protease predictions, considering also available transcriptomics data, suggest activation of cathepsin S with CKD potentially involved in the cleavage of the CKD-associated glycopeptide of IGF2. Conclusion Collectively, this study indicates that with aging and deteriorating kidney function, alterations in IGF2 proteoforms take place; which may be reflective of respective changes in the mature IGF2 protein abundance and function; as well as associated protease activity. Further, correlation analyses of the levels of the CKD-associated urinary IGF2 glycopeptide with the plasma IGF2 levels with CKD progression is planned. a Results of multiple linear regression where regression Co-efficient is β; degree of freedom is stated in (brackets); and p-value <0.05 was considered statistically significant

Effect of di‐ethylhexyl phthalate (DEHP) on androgen related proteins in JEG‐3 placental cells

The placenta is a critical fetal endocrine organ that plays an important role in fetal development, xenobiotic detoxification, and sex steroid homeostasis. Although the importance of the placenta in endocrine homeostasis is known, the effect of endocrine disruptors, like phthalates, on placental endocrine function needs further exploration. A common phthalate that expectant mothers can be exposed to is di‐ethylhexyl phthalate (DEHP) which is used to make flexible plastics. We aim to determine the effect of DEHP on the androgen related proteome in JEG‐3 placental cell model.JEG‐3 cells were seeded in 6‐well plates at 100,000 cells per well and treated with 0 (vehicle control), 1, 10, and 100 mM DEHP for 72 hours. The cells were harvested, homogenized, and protein sample was digested using an optimized protocol. Global proteomics data were acquired using a Q‐Exactive HF Quadrupole‐Orbitrap mass spectrometer (Thermo Fisher Scientific, Waltham, MA). The data were processed with MaxQuant (version 1.6.8.0) using the Andromeda search engine to search the high‐resolution MS/MS spectra against the human proteome database curated from Uniprot. Label‐free quantification (LFQ) intensities of androgen related proteins were compared across control and treatment groups.Out of the total 2368‐ 2530 proteins detected, 2085 proteins were common in control and all treatment groups. The control group had 49 unique proteins and DEHP treatment showed 63, 42, and 119 unique proteins to 1, 10 and 100 mM, respectively. ABCG2 was uniquely identified in the higher DEHP treatment group. DEHP treatment elevated the levels of aromatase (CYP19A1) and aldo‐keto reductase 1B1 (AKR1B1) in a dose‐dependent manner with a 291% and 59% increase in the 100 mM treatment, respectively. Steryl‐sulfatase (STS), estradiol 17‐beta‐dehydrogenase 11, and aldehyde dehydrogenase 3A2levels were unaltered by the DEHP treatments.Determining how environmental endocrine disruptors, like DEHP, affects the placental endocrine pathways is vital to mitigating the toxicity. The elevation of aromatase with DEHP treatment may lead to estrogenic effects as CYP19A1 converts androstenedione and testosterone to estrogens, resulting in hormone imbalance which can cause adverse fetal outcomes both physically and neurodevelopmentally.

Methylene tetrahydrofolate dehydrogenase 2 (MTHFD2) is overexpressed in head and neck squamous cell carcinoma (HNSCC) and correlated with patient’s poor prognosis

Abstract Objective To investigate methylene tetrahydrofolate dehydrogenase 2 (MTHFD2) expression, biological function, and correlation with head and neck squamous cell carcinoma (HNSCC) patient’s prognosis. Methods The relative expression levels of MTHFD2 gene mRNA in tumor tissues of HNSCC and adjacent normal tissues were analyzed in the Cancer Genome Atlas and oncomine database. MTHFD2 protein relative expression in tumor tissue of HNSCC patients was analyzed in human proteome database. Protein–protein interaction (PPI) network of MTHFD2 and correlated genes were constructed in STRING database. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway of MTHFD2 and relevant proteins involved in the PPI network was enriched. The Tumor Immune Estimation Resource database was used to analyze the relationship between MTHFD2 expression and immune infiltration. Overall survival (OS) and progression-free survival (PFS) for MTHFD2 high and low expression groups were investigated in the Kaplan–Meier Plotter database. Results In HNSCC, MTHFD2 mRNA relative expression level in tumor tissue was significantly higher than the corresponding normal tissue with statistical difference (p < 0.05). In the PPI network, 21 protein coding genes were involved in the network with 124 edges, which indicated that the enrichment was significant (p < 0.05). MTHFD2 and PPI network involved genes were mainly enriched in tetrahydrofolate metabolic process, one-carbon metabolic process biological process. In KEGG pathway, MTHFD2 and PPI network involved genes were mainly enriched in one-carbon pool by folate, metabolic pathways, glyoxylate, and dicarboxylate metabolism, and carbon metabolism. The relative expression level of MTHFD2 gene was correlated with immune infiltration of macrophage (r = 0.712, p < 0.05), neutrophil (r = 0.158, p < 0.05), dendritic cell (r = 0.1825, p < 0.05), and CD4+ T lymph cell (r = 0.1825, p < 0.05). HNSCC patients with high expression MTHFD2 had low OS compared to low expression cases (hazard ratio = 1.53, 95% CI: 1.16–2.02, p < 0.05). Conclusion MTHFD2 is overexpressed in HNSCC and correlated with patient’s prognosis. MTHFD2 maybe a potential target for HNSCC target treatment and provides a possible direction for the research and development of related targeted drugs.

Optimization of proteomics sample preparation for forensic analysis of skin samples

We present an efficient protein extraction and in-solution enzymatic digestion protocol optimized for mass spectrometry-based proteomics studies of human skin samples. Human skin cells are a proteinaceous matrix that can enable forensic identification of individuals. We performed a systematic optimization of proteomic sample preparation for a protein-based human forensic identification application. Digestion parameters, including incubation duration, temperature, and the type and concentration of surfactant, were systematically varied to maximize digestion completeness. Through replicate digestions, parameter optimization was performed to maximize repeatability and increase the number of identified peptides and proteins. Final digestion conditions were selected based on the parameters that yielded the greatest percent of peptides with zero missed tryptic cleavages, which benefit the analysis of genetically variable peptides (GVPs). We evaluated the final digestion conditions for identification of GVPs by applying MS-based proteomics on a mixed-donor sample. The results were searched against a human proteome database appended with a database of GVPs constructed from known non-synonymous single nucleotide polymorphisms (SNPs) that occur at known population frequencies. The aim of this study was to demonstrate the potential of our proteomics sample preparation for future implementation of GVP analysis by forensic laboratories to facilitate human identification. SignificanceGenetically variable peptides (GVPs) can provide forensic evidence that is complementary to traditional DNA profiling and be potentially used for human identification. An efficient protein extraction and reproducible digestion method of skin proteins is a key contributor for downstream analysis of GVPs and further development of this technology in forensic application. In this study, we optimized the enzymatic digestion conditions, such as incubation time and temperature, for skin samples. Our study is among the first attempts towards optimization of proteomics sample preparation for protein-based skin identification in forensic applications such as touch samples. Our digestion method employs RapiGest (an acid-labile surfactant), trypsin enzymatic digestion, and an incubation time of 16 h at 37 °C.

A comprehensive analysis of RAS-effector interactions reveals interaction hotspots and new binding partners

RAS effectors specifically interact with GTP-bound RAS proteins to link extracellular signals to downstream signaling pathways. These interactions rely on two types of domains, called RAS-binding (RB) and RAS association (RA) domains, which share common structural characteristics. Although the molecular nature of RAS-effector interactions is well-studied for some proteins, most of the RA/RB-domain-containing proteins remain largely uncharacterized. Here, we searched through human proteome databases, extracting 41 RA domains in 39 proteins and 16 RB domains in 14 proteins, each of which can specifically select at least one of the 25 members in the RAS family. We next comprehensively investigated the sequence–structure–function relationship between different representatives of the RAS family, including HRAS, RRAS, RALA, RAP1B, RAP2A, RHEB1, and RIT1, with all members of RA domain family proteins (RASSFs) and the RB-domain-containing CRAF. The binding affinity for RAS-effector interactions, determined using fluorescence polarization, broadly ranged between high (0.3 μM) and very low (500 μM) affinities, raising interesting questions about the consequence of these variable binding affinities in the regulation of signaling events. Sequence and structural alignments pointed to two interaction hotspots in the RA/RB domains, consisting of an average of 19 RAS-binding residues. Moreover, we found novel interactions between RRAS1, RIT1, and RALA and RASSF7, RASSF9, and RASSF1, respectively, which were systematically explored in sequence–structure–property relationship analysis, and validated by mutational analysis. These data provide a set of distinct functional properties and putative biological roles that should now be investigated in the cellular context.

Bioluminescent Sensor Reveals that Carboxylesterase 1A is a Novel Endoplasmic Reticulum-Derived Serologic Indicator for Hepatocyte Injury.

Discovery of novel liver injury indicators and development of practical assays to detect target indicator(s) would strongly facilitate the diagnosis of liver disorders. Herein, an alternative biomarker discovery strategy was applied to find suitable endoplasmic reticulum-resident protein(s) as serologic indicator(s) for hepatocyte injury via analysis of the human proteome database among plasma and various organs. Both database searching and preliminary experiments suggested that human carboxylesterase 1A (CES1A), one of the most abundant and hepatic-restricted proteins, could serve as a good serologic indicator for hepatocyte injury. Then, a highly selective and practical bioluminescent sensor was developed for real-time sensing of CES1A in various biological systems including plasma. With the help of this bioluminescent sensor, the release of hepatic CES1A into the extracellular medium or the circulation system could be directly monitored. Further investigations demonstrated that serum activity levels of CES1A were elevated dramatically in mice with liver injury or patients with liver diseases. Collectively, this study provided solid evidence to support that CES1A was a novel serological indicator for hepatocyte injury. Furthermore, the strategy used in this study paved a new way for the rational discovery of practical indicators to monitor the dynamic progression of injury in a given tissue or organ.

Neutrophil myeloperoxidase harbors distinct site-specific peculiarities in its glycosylation

Anti-neutrophil cytoplasmic autoantibodies (ANCAs) are directed against lysosomal components of neutrophils. ANCAs directed to proteinase 3 and myeloperoxidase (MPO) in particular are associated with distinct forms of small vessel vasculitides. MPO is an abundant neutrophil-derived heme protein that is part of the antimicrobial defense system. The protein is typically present in the azurophilic granules of neutrophils, but a large portion may also enter the extracellular space. It remains unclear why MPO is frequently the target of antibody-mediated autoimmune responses. MPO is a homodimeric glycoprotein, posttranslationally modified with complex sugars at specific sites. Glycosylation can strongly influence protein function, affecting its folding, receptor interaction, and backbone accessibility. MPO potentially can be heavily modified as it harbors 5 putative N-glycosylation sites (10 in the mature dimer). Although considered important for MPO structure and function, the full scope and relative abundance of the glycans attached to MPO is unknown. Here, combining bottom-up glycoproteomics and native MS approaches, we structurally characterized MPO from neutrophils of healthy human donors. We quantified the relative occupancy levels of the glycans at each of the five sites and observed complex heterogeneity and site-specific glycosylation. In particular, we detected glycosylation phenotypes uncommon for glycoproteins in the extracellular space, such as a high abundance of phosphorylated high-mannose species and severely truncated small glycans having the size of paucimannose or smaller. We hypothesize that the atypical glycosylation pattern found on MPO might contribute to its specific processing and presentation as a self-antigen by antigen-presenting cells.

Citrulline Effect Is a Characteristic Feature of Deiminated Peptides in Tandem Mass Spectrometry

Tandem mass spectrometry of peptides is of utmost importance in proteomics. Collision-induced dissociation usually generates y type fragment ion series from tryptic peptides, carrying information on their primary structure. Amino acid side chains or differences in their basicity could alter fragmentation processes considerably. The well-known proline effect is a cleavage preference at the N-terminus of proline residues in peptides, usually yielding a very abundant y ion while suppressing others. Previously, we reported a similar phenomenon occurring at the C-terminus of citrulline residues and coined the term Cit effect. To confirm the presence of Cit effect in large proteomic datasets, we analyzed 293 peptides containing Cit residues based on the human proteome database mining work of Lee et al. (2018). The occurrence of Cit effect was found to be 44%. Comparing bond scissions at the amide linkage between Cit-Zzz (citrulline followed by a specified residue) to Aaa1-Aaa2 (Aaa can be any residue except Cit), 5 Cit-Zzz cleavages were significantly (CL = 95.0%) more frequent in > 85% of the cases in terms of relative sequential base beak occurrence. We used Pro effect to compare with Cit effect and obtained very similar results. On the other hand, our study showed that Cit effect is slightly inferior in the overall incidence to Pro effect (50% vs. 33%, CL = 95%) among deiminated peptides when Pro residues were also present in the sequence. Our results suggest that Cit effect is a characteristic feature and a possible biasing factor of deiminated peptides which can confirm the position of citrullination sites.

Proteome-wide profiling of protein assemblies by cross-linking mass spectrometry.

We describe an integrated workflow that robustly identifies cross-links from endogenous protein complexes in human cellular lysates. Our approach is based on the application of mass spectrometry (MS)-cleavable cross-linkers, sequential collision-induced dissociation (CID)-tandem MS (MS/MS) and electron-transfer dissociation (ETD)-MS/MS acquisitions, and a dedicated search engine, XlinkX, which allows rapid cross-link identification against a complete human proteome database. This approach allowed us to detect 2,179 unique cross-links (1,665 intraprotein cross-links at a 5% false discovery rate (FDR) and 514 interprotein cross-links at 1% FDR) in HeLa cell lysates. We validated the confidence of our cross-linking results by using a target-decoy strategy and mapping the observed cross-link distances onto existing high-resolution structures. Our data provided new structural information about many protein assemblies and captured dynamic interactions of the ribosome in contact with different elongation factors.

Abstracts from The Aerosol Society Drug Delivery to the Lungs 25Edinburgh International Conference Centre Edinburgh, Scotland, UK December 10–12, 2014

Abstracts from The Aerosol Society Drug Delivery to the Lungs 25Edinburgh International Conference Centre Edinburgh, Scotland, UK December 10–12, 2014

Identification of Membrane Drug Targets by Subtractive Genomic Approach in Mycoplasma Pneumonia

The Availability of genome sequences of pathogens has provided a tremendous amount of information that can be used in identification of drug targets and vaccine production. The application of in silico subtractive genomics technology significantly shortens the time required for such purposes. Subtractive genomics help enables the subtraction dataset between the host and pathogen. The aim of present work is to identify the Drug targets in Mycoplasma Pneumonia by subtractive genomic approach which helps to identify the homolog's and Non homolog's between the host and pathogen. The availability of complete Proteome sequence information of Mycoplasma Pneumonia from NCBI-FTP site helps to perform the BLAST against human proteome database. The screening of these proteins using different database like essential genes (DEG), metabolic pathways KEGG helps to identify essential proteins which may be used as drug targets against Mycoplasma Pneumonia. Prediction of these essential proteins of the outer membrane of the pathogen also could be potential vaccine targets

Abstract 4533: Mechanism of anti-proliferative effects of sanguinarine in pancreatic cancer cells: A label-free quantitative proteomics approach

Abstract Pancreatic cancer is one of the most lethal cancers, with a meager (∼3%) 5-year survival rate. The incidence of pancreatic cancer nearly equals its death rate as this neoplasm is associated with poor responsiveness to conventional chemotherapies. Therefore, it's crucial to identify newer mechanism-based agents and targets to effectively manage pancreatic cancer. Previous studies from our laboratory have demonstrated that the plant alkaloid sanguinarine (13-methyl[1,3]benzodioxolo [5,6-c]-1,3-dioxolo [4,5-i] phenanthridinium possesses strong antiproliferative effects against human pancreatic carcinoma cells (Cancer Letters 249; 198-208, 2007). In this study, employing a large-scale Nano-ESI ultra high resolution label-free quantitative proteomics, we attempted to determine the mechanism of sanguinarine's biological response in human pancreatic cancer cells. Based on pilot experiments, we selected BxPC-3 cells and a 1 microM sanguinarine treatment for 24 hours for our proteomics study. Proteins from control and sanguinarine-treated BxPC-3 cells were digested with trypsin followed by nano-liquid chromatography-tandem mass spectrometry (LC/MS/MS). Following LC/MS/MS acquisition, the data were searched against the Swiss-Prot human proteome database using Sequest HT search engine under the Proteome Discoverer 1.4 software (Thermo Fisher Scientific). Following protein identification, the LC/MS/MS data was aligned using Chromalign and quantitation of peptides was performed on the processed data using Sieve 2.1 (Thermo Fisher Scientific). A cumulative data of a total of 6 replicates (2 biological and 3 technical) were run and analyzed. Upon comparison with untreated control, 37 proteins (from a total of 3108) showed +1.8 fold significant differential expressions (p value <0.05). These proteins can be categorized under distinct biological functions: 1) cellular assembly and organization, 2) cellular function and maintenance, 3) inflammatory response, and 4) cell death and survival. On further data analysis and validation using real-time qPCR and Western blot analyses, we identified the dual specificity phosphatase-4 (DUSP4), as a novel target of sanguinarine in pancreatic cancer cells. In order to determine the clinical relevance of DUSP4 in pancreatic cancer cells, we determined the expression profile of DUSP4 in a tissue microarray (TMA) containing a wide range of pancreatic cancer tissue (different stages) and normal pancreas tissue from autopsy. We found that that DUSP4 is markedly downregulated in cancerous pancreatic tissues. Our data identified, for the first time, DUPS4 as a potential tumor suppressor in pancreatic cancer and a novel target of sanguinarine. However, further studies are needed to validate our findings in detailed in vitro and in vivo studies. Citation Format: Chandra K. Singh, Satwinderjeet Kaur, Jasmine George, Molly C. Pellitteri-Hahn, Cameron O. Scarlett, Nihal Ahmad. Mechanism of anti-proliferative effects of sanguinarine in pancreatic cancer cells: A label-free quantitative proteomics approach. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4533. doi:10.1158/1538-7445.AM2014-4533

Cleavage specificity analysis of six type II transmembrane serine proteases (TTSPs) using PICS with proteome-derived peptide libraries.

BackgroundType II transmembrane serine proteases (TTSPs) are a family of cell membrane tethered serine proteases with unclear roles as their cleavage site specificities and substrate degradomes have not been fully elucidated. Indeed just 52 cleavage sites are annotated in MEROPS, the database of proteases, their substrates and inhibitors.Methodology/Principal FindingTo profile the active site specificities of the TTSPs, we applied Proteomic Identification of protease Cleavage Sites (PICS). Human proteome-derived database searchable peptide libraries were assayed with six human TTSPs (matriptase, matriptase-2, matriptase-3, HAT, DESC and hepsin) to simultaneously determine sequence preferences on the N-terminal non-prime (P) and C-terminal prime (P’) sides of the scissile bond. Prime-side cleavage products were isolated following biotinylation and identified by tandem mass spectrometry. The corresponding non-prime side sequences were derived from human proteome databases using bioinformatics. Sequencing of 2,405 individual cleaved peptides allowed for the development of the family consensus protease cleavage site specificity revealing a strong specificity for arginine in the P1 position and surprisingly a lysine in P1′ position. TTSP cleavage between R↓K was confirmed using synthetic peptides. By parsing through known substrates and known structures of TTSP catalytic domains, and by modeling the remainder, structural explanations for this strong specificity were derived.ConclusionsDegradomics analysis of 2,405 cleavage sites revealed a similar and characteristic TTSP family specificity at the P1 and P1′ positions for arginine and lysine in unfolded peptides. The prime side is important for cleavage specificity, thus making these proteases unusual within the tryptic-enzyme class that generally has overriding non-prime side specificity.

Systematic Analyses of the Transcriptome, Translatome, and Proteome Provide a Global View and Potential Strategy for the C-HPP

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

First Proteomic Exploration of Protein-Encoding Genes on Chromosome 1 in Human Liver, Stomach, and Colon

The launch of the Chromosome-Centric Human Proteome Project provides an opportunity to gain insight into the human proteome. The Chinese Human Chromosome Proteome Consortium has initiated proteomic exploration of protein-encoding genes on human chromosomes 1, 8, and 20. Collaboration within the consortium has generated a comprehensive proteome data set using normal and carcinomatous tissues from human liver, stomach, and colon and 13 cell lines originating in these organs. We identified 12,101 proteins (59.8% coverage against Swiss-Prot human entries) with a protein false discovery rate of less than 1%. On chromosome 1, 1,252 proteins mapping to 1,227 genes, representing 60.9% of Swiss-Prot entries, were identified; however, 805 proteins remain unidentified, suggesting that analysis of more diverse samples using more advanced proteomic technologies is required. Genes encoding the unidentified proteins were concentrated in seven blocks, located at p36, q12-21, and q42-44, partly consistent with correlation of these blocks with cancers of the liver, stomach, and colon. Combined transcriptome, proteome, and cofunctionality analyses confirmed 23 coexpression clusters containing 165 genes. Biological information, including chromosome structure, GC content, and protein coexpression pattern was analyzed using multilayered, circular visualization and tabular visualization. Details of data analysis and updates are available in the Chinese Chromosome-Centric Human Proteome Database ( http://proteomeview.hupo.org.cn/chromosome/ ).

Identification of phosphorylated human peptides by accurate mass measurement alone

At sufficiently high mass accuracy, it is possible to distinguish phosphorylated from unmodified peptides by mass measurement alone. We examine the feasibility of that idea, tested against a library of all possible in silico tryptic digest peptides from the human proteome database. The overlaps between in silico tryptic digest phosphopeptides generated from known phosphorylated proteins (1–12 sites) and all possible unmodified human peptides are considered for assumed mass error ranges of ±10, ±50, ±100, ±1000, and ±10,000 ppb. We find that for mass error ±50 ppb, 95% of all phosphorylated human tryptic peptides can be distinguished from nonmodified peptides by accurate mass alone throughout the entire nominal mass range. We discuss the prospect of on-line LC MS/MS to identify phosphopeptide precursor ions in MS1 for selected dissociation in MS2 to identify the peptide and site(s) of phosphorylation.

Lung Cancer Serum Biomarker Discovery Using Label-Free Liquid Chromatography-Tandem Mass Spectrometry

Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer and the relatively favorable survival associated with early-stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit.We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry in a set of pooled non-small cell lung cancer case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by liquid chromatography-tandem mass spectrometry. The tandem mass spectrum data were searched against the human proteome database, and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting-derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring mass spectrometry assays.A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (p < 0.01). Functional analysis with Ingenuity Pathway Analysis tools showed significant enrichment of inflammatory response proteins, key molecules in cell-cell signaling and interaction network, and differential physiological responses for the two common non-small cell lung cancer subtypes.We identified a set of candidate serum biomarkers with statistically significant differential abundance across the lung cancer case/control pools, which, when validated, could improve lung cancer early detection.

Uncovering the Human Methyltransferasome

We present a comprehensive analysis of the human methyltransferasome. Primary sequences, predicted secondary structures, and solved crystal structures of known methyltransferases were analyzed by hidden Markov models, Fisher-based statistical matrices, and fold recognition prediction-based threading algorithms to create a model, or profile, of each methyltransferase superfamily. These profiles were used to scan the human proteome database and detect novel methyltransferases. 208 proteins in the human genome are now identified as known or putative methyltransferases, including 38 proteins that were not annotated previously. To date, 30% of these proteins have been linked to disease states. Possible substrates of methylation for all of the SET domain and SPOUT methyltransferases as well as 100 of the 131 seven-β-strand methyltransferases were surmised from sequence similarity clusters based on alignments of the substrate-specific domains.

Networks of Motifs from Sequences of Symbols

We introduce a method to convert an ensemble of sequences of symbols into a weighted directed network whose nodes are motifs, while the directed links and their weights are defined from statistically significant co-occurences of two motifs in the same sequence. The analysis of communities of networks of motifs is shown to be able to correlate sequences with functions in the human proteome database, to detect hot topics from online social dialogs, to characterize trajectories of dynamical systems, and it might find other useful applications to process large amounts of data in various fields.

Multiple, Non-conserved, Internal Viral Ligands Naturally Presented by HLA-B27 in Human Respiratory Syncytial Virus-infected Cells

Cytotoxic T lymphocyte (CTL)-mediated death of virus-infected cells requires prior recognition of short viral peptide antigens that are presented by human leukocyte antigen (HLA) class I molecules on the surface of infected cells. The CTL response is critical for the clearance of human respiratory syncytial virus (HRSV) infection. Using mass spectrometry analysis of complex HLA-bound peptide pools isolated from large amounts of HRSV-infected cells, we identified nine naturally processed HLA-B27 ligands. The isolated peptides are derived from six internal, not envelope, proteins of the infective virus. The sequences of most of these ligands are not conserved between different HRSV strains, suggesting a mechanism to explain recurrent infection with virus of different HRSV antigenic subgroups. In addition, these nine ligands represent a significant fraction of the proteome of this virus, which is monitored by the same HLA class I allele. These data have implications for vaccine development as well as for analysis of the CTL response.