Longitudinal Large-Scale Semiquantitative Proteomic Data Stability Across Multiple Instrument Platforms.

With the rapid developments in mass spectrometry (MS)-based proteomics methods, label-free semiquantitative proteomics has become an increasingly popular tool for profiling global protein abundances in an unbiased manner. However, the reproducibility of these data across time and LC-MS platforms is not well characterized. Here, we evaluate the performance of three LC-MS platforms (Orbitrap Elite, Q Exactive HF, and Orbitrap Fusion) in label-free semiquantitative analysis of cell surface proteins over a six-year period. Sucrose gradient ultracentrifugation was used for surfaceome enrichment, following gel separation for in-depth protein identification. With our established workflow, we consistently detected and reproducibly quantified >2300 putative cell surface proteins in a human acute myeloid leukemia (AML) cell line on all three platforms. To our knowledge this is the first study reporting highly reproducible semiquantitative proteomic data collection of biological replicates across multiple years and LC-MS platforms. These data provide experimental justification for semiquantitative proteomic study designs that are executed over multiyear time intervals and on different platforms. Multiyear and multiplatform experimental designs will likely enable larger scale proteomic studies and facilitate longitudinal proteomic studies by investigators lacking access to high throughput MS facilities. Data are available via ProteomeXchange with identifier PXD022721.

Liver disease-associated keratin 8 and 18 mutations modulate keratin acetylation and methylation.

Keratin 8 (K8) and keratin 18 (K18) are the intermediate filament proteins whose phosphorylation/transamidation associate with their aggregation in Mallory-Denk bodies found in patients with various liver diseases. However, the functions of other post-translational modifications in keratins related to liver diseases have not been fully elucidated. Here, using a site-specific mutation assay combined with nano-liquid chromatography-tandem mass spectrometry, we identified K8-Lys108 and K18-Lys187/426 as acetylation sites, and K8-Arg47 and K18-Arg55 as methylation sites. Keratin mutation (Arg-to-Lys/Ala) at the methylation sites, but not the acetylation sites, led to decreased stability of the keratin protein. We compared keratin acetylation/methylation in liver disease-associated keratin variants. The acetylation of K8 variants increased or decreased to various extents, whereas the methylation of K18-del65-72 and K18-I150V variants increased. Notably, the highly acetylated/methylated K18-I150V variant was less soluble and exhibited unusually prolonged protein stability, which suggests that additional acetylation of highly methylated keratins has a synergistic effect on prolonged stability. Therefore, the different levels of acetylation/methylation of the liver disease-associated variants regulate keratin protein stability. These findings extend our understanding of how disease-associated mutations in keratins modulate keratin acetylation and methylation, which may contribute to disease pathogenesis.-Jang, K.-H., Yoon, H.-N., Lee, J., Yi, H., Park, S.-Y., Lee, S.-Y., Lim, Y., Lee, H.-J., Cho, J.-W., Paik, Y.-K., Hancock, W. S., Ku, N.-O. Liver disease-associated keratin 8 and 18 mutations modulate keratin acetylation and methylation.

Quantitative Mass Spectrometry Analysis of PD-L1 Protein Expression, N-glycosylation and Expression Stoichiometry with PD-1 and PD-L2 in Human Melanoma.

Quantitative assessment of key proteins that control the tumor-immune interface is one of the most formidable analytical challenges in immunotherapeutics. We developed a targeted MS platform to quantify programmed cell death-1 (PD-1), programmed cell death 1 ligand 1 (PD-L1), and programmed cell death 1 ligand 2 (PD-L2) at fmol/microgram protein levels in formalin fixed, paraffin-embedded sections from 22 human melanomas. PD-L1 abundance ranged 50-fold, from ∼0.03 to 1.5 fmol/microgram protein and the parallel reaction monitoring (PRM) data were largely concordant with total PD-L1-positive cell content, as analyzed by immunohistochemistry (IHC) with the E1L3N antibody. PD-1 was measured at levels up to 20-fold lower than PD-L1, but the abundances were not significantly correlated (r2 = 0.062, p = 0.264). PD-1 abundance was weakly correlated (r2 = 0.3057, p = 0.009) with the fraction of lymphocytes and histiocytes in sections. PD-L2 was measured from 0.03 to 1.90 fmol/microgram protein and the ratio of PD-L2 to PD-L1 abundance ranged from 0.03 to 2.58. In 10 samples, PD-L2 was present at more than half the level of PD-L1, which suggests that PD-L2, a higher affinity PD-1 ligand, is sufficiently abundant to contribute to T-cell downregulation. We also identified five branched mannose and N-acetylglucosamine glycans at PD-L1 position N192 in all 22 samples. Extent of PD-L1 glycan modification varied by ∼10-fold and the melanoma with the highest PD-L1 protein abundance and most abundant glycan modification yielded a very low PD-L1 IHC estimate, thus suggesting that N-glycosylation may affect IHC measurement and PD-L1 function. Additional PRM analyses quantified immune checkpoint/co-regulator proteins LAG3, IDO1, TIM-3, VISTA, and CD40, which all displayed distinct expression independent of PD-1, PD-L1, and PD-L2. Targeted MS can provide a next-generation analysis platform to advance cancer immuno-therapeutic research and diagnostics.

WITHDRAWN: Quantitative mass spectrometry analysis of PD-L1 protein expression, N-glycosylation and expression stoichiometry with PD-1 and PD-L2 in human melanoma.

This article has been withdrawn by the authors. We discovered an error after this manuscript was published as a Paper in Press. Specifically, we learned that the structures of glycans presented for the PD-L1 peptide were drawn and labeled incorrectly. We wish to withdraw this article and submit a corrected version for review.

Quantitative Profiling of Protein Tyrosine Kinases in Human Cancer Cell Lines by Multiplexed Parallel Reaction Monitoring Assays.

Protein tyrosine kinases (PTKs) play key roles in cellular signal transduction, cell cycle regulation, cell division, and cell differentiation. Dysregulation of PTK-activated pathways, often by receptor overexpression, gene amplification, or genetic mutation, is a causal factor underlying numerous cancers. In this study, we have developed a parallel reaction monitoring-based assay for quantitative profiling of 83 PTKs. The assay detects 308 proteotypic peptides from 54 receptor tyrosine kinases and 29 nonreceptor tyrosine kinases in a single run. Quantitative comparisons were based on the labeled reference peptide method. We implemented the assay in four cell models: 1) a comparison of proliferating versus epidermal growth factor-stimulated A431 cells, 2) a comparison of SW480Null (mutant APC) and SW480APC (APC restored) colon tumor cell lines, and 3) a comparison of 10 colorectal cancer cell lines with different genomic abnormalities, and 4) lung cancer cell lines with either susceptibility (11-18) or acquired resistance (11-18R) to the epidermal growth factor receptor tyrosine kinase inhibitor erlotinib. We observed distinct PTK expression changes that were induced by stimuli, genomic features or drug resistance, which were consistent with previous reports. However, most of the measured expression differences were novel observations. For example, acquired resistance to erlotinib in the 11-18 cell model was associated not only with previously reported up-regulation of MET, but also with up-regulation of FLK2 and down-regulation of LYN and PTK7. Immunoblot analyses and shotgun proteomics data were highly consistent with parallel reaction monitoring data. Multiplexed parallel reaction monitoring assays provide a targeted, systems-level profiling approach to evaluate cancer-related proteotypes and adaptations. Data are available through Proteome eXchange Accession PXD002706.

Epsilon-Q: An Automated Analyzer Interface for Mass Spectral Library Search and Label-Free Protein Quantification.

Mass spectrometry (MS) is a widely used proteome analysis tool for biomedical science. In an MS-based bottom-up proteomic approach to protein identification, sequence database (DB) searching has been routinely used because of its simplicity and convenience. However, searching a sequence DB with multiple variable modification options can increase processing time, false-positive errors in large and complicated MS data sets. Spectral library searching is an alternative solution, avoiding the limitations of sequence DB searching and allowing the detection of more peptides with high sensitivity. Unfortunately, this technique has less proteome coverage, resulting in limitations in the detection of novel and whole peptide sequences in biological samples. To solve these problems, we previously developed the "Combo-Spec Search" method, which uses manually multiple references and simulated spectral library searching to analyze whole proteomes in a biological sample. In this study, we have developed a new analytical interface tool called "Epsilon-Q" to enhance the functions of both the Combo-Spec Search method and label-free protein quantification. Epsilon-Q performs automatically multiple spectral library searching, class-specific false-discovery rate control, and result integration. It has a user-friendly graphical interface and demonstrates good performance in identifying and quantifying proteins by supporting standard MS data formats and spectrum-to-spectrum matching powered by SpectraST. Furthermore, when the Epsilon-Q interface is combined with the Combo-Spec search method, called the Epsilon-Q system, it shows a synergistic function by outperforming other sequence DB search engines for identifying and quantifying low-abundance proteins in biological samples. The Epsilon-Q system can be a versatile tool for comparative proteome analysis based on multiple spectral libraries and label-free quantification.

Next Generation Proteomic Pipeline for Chromosome-Based Proteomic Research Using NeXtProt and GENCODE Databases.

Human Proteome Project aims to map all human proteins including missing proteins as well as proteoforms with post translational modifications, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). neXtProt and Ensemble databases are usually used to provide curated information on human coding genes. However, to find these proteoforms, we (Chr #11 team) first introduce a streamlined pipeline using customized and concatenated neXtProt and GENCODE originated from Ensemble, with controlled false discovery rate (FDR). Because of large sized databases used in this pipeline, we found more stringent FDR filtering (0.1% at the peptide level and 1% at the protein level) to claim novel findings, such as GENCODE ASVs and missing proteins, from human hippocampus data set (MSV000081385) and ProteomeXchange (PXD007166). Using our next generation proteomic pipeline (nextPP) with neXtProt and GENCODE databases, two missing proteins such as activity-regulated cytoskeleton-associated protein (ARC, Chr 8) and glutamate receptor ionotropic, kainite 5 (GRIK5, Chr 19) were additionally identified with two or more unique peptides from human brain tissues. Additionally, by applying the pipeline to human brain related data sets such as cortex (PXD000067 and PXD000561), spinal cord, and fetal brain (PXD000561), seven GENCODE ASVs such as ACTN4-012 (Chr.19), DPYSL2-005 (Chr.8), MPRIP-003 (Chr.17), NCAM1-013 (Chr.11), EPB41L1-017 (Chr.20), AGAP1-004 (Chr.2), and CPNE5-005 (Chr.6) were identified from two or more data sets. The identified peptides of GENCODE ASVs were mapped onto novel exon insertions, alternative translations at 5'-untranslated region, or novel protein coding sequence. Applying the pipeline to male reproductive organ related data sets, 52 GENCODE ASVs were identified from two testis (PXD000561 and PXD002179) and a spermatozoa (PXD003947) data sets. Four out of 52 GENCODE ASVs such as RAB11FIP5-008 (Chr. 2), RP13-347D8.7-001 (Chr. X), PRDX4-002 (Chr. X), and RP11-666A8.13-001 (Chr. 17) were identified in all of the three samples.

Efficient Microscale Basic Reverse Phase Peptide Fractionation for Global and Targeted Proteomics.

Analysis of small biological samples would benefit from an efficient microscale fractionation strategy that minimizes sample handling, transfer steps, and accompanying losses. Here we describe a microscale basic reverse phase liquid chromatographic (bRPLC) fractionation method that offers high reproducibility and efficiency for peptide mixtures from small (5-20 µg) samples. We applied our platform to detect differentially expressed proteins from lung tumor cell lines that are sensitive (11-18) and resistant (11-18R) to the tyrosine kinase inhibitor erlotinib. Label-free analyses of 5-20 µg samples yielded identifications of approximately 3,200 to 4,000 proteins with coefficients of variation of 1.9-8.9% in replicate analyses. iTRAQ analyses produced similar protein inventories. Label-free and iTRAQ analyses displayed high concordance in identifications of proteins differentially expressed in 11-18 and 11-18R cells. Micro-bRPLC fractionation of cell proteomes increased sensitivity by an average of 4.5-fold in targeted quantitation using parallel reaction monitoring for three representative receptor tyrosine kinases (EGFR, PDGFRA, and BMX), which are present at low abundance in 11-18 and 11-18R cells. These data illustrate the broad utility of micro-bRPLC fractionation for global and targeted proteomic analyses. Data are available through Proteome eXchange Accession PXD003604.

Quantitative Profiling Identifies Potential Regulatory Proteins Involved in Development from Dauer Stage to L4 Stage in Caenorhabditis elegans.

When Caenorhabditis elegans encounters unfavorable growth conditions, it enters the dauer stage, an alternative L3 developmental period. A dauer larva resumes larval development to the normal L4 stage by uncharacterized postdauer reprogramming (PDR) when growth conditions become more favorable. During this transition period, certain heterochronic genes involved in controlling the proper sequence of developmental events are known to act, with their mutations suppressing the Muv (multivulva) phenotype in C. elegans. To identify the specific proteins in which the Muv phenotype is highly suppressed, quantitative proteomic analysis with iTRAQ labeling of samples obtained from worms at L1 + 30 h (for continuous development [CD]) and dauer recovery +3 h (for postdauer development [PD]) was carried out to detect changes in protein abundance in the CD and PD states of both N2 and lin-28(n719). Of the 1661 unique proteins identified with a < 1% false discovery rate at the peptide level, we selected 58 proteins exhibiting ≥2-fold up-regulation or ≥2-fold down-regulation in the PD state and analyzed the Gene Ontology terms. RNAi assays against 15 selected up-regulated genes showed that seven genes were predicted to be involved in higher Muv phenotype (p < 0.05) in lin-28(n791), which is not seen in N2. Specifically, two genes, K08H10.1 and W05H9.1, displayed not only the highest rate (%) of Muv phenotype in the RNAi assay but also the dauer-specific mRNA expression, indicating that these genes may be required for PDR, leading to the very early onset of dauer recovery. Thus, our proteomic approach identifies and quantitates the regulatory proteins potentially involved in PDR in C. elegans, which safeguards the overall lifecycle in response to environmental changes.

gFinder: A Web-Based Bioinformatics Tool for the Analysis of N-Glycopeptides.

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native N-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and N-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible N-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For N-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of N-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/ .

Integrated Proteomic Pipeline Using Multiple Search Engines for a Proteogenomic Study with a Controlled Protein False Discovery Rate.

In the Chromosome-Centric Human Proteome Project (C-HPP), false-positive identification by peptide spectrum matches (PSMs) after database searches is a major issue for proteogenomic studies using liquid-chromatography and mass-spectrometry-based large proteomic profiling. Here we developed a simple strategy for protein identification, with a controlled false discovery rate (FDR) at the protein level, using an integrated proteomic pipeline (IPP) that consists of four engrailed steps as follows. First, using three different search engines, SEQUEST, MASCOT, and MS-GF+, individual proteomic searches were performed against the neXtProt database. Second, the search results from the PSMs were combined using statistical evaluation tools including DTASelect and Percolator. Third, the peptide search scores were converted into E-scores normalized using an in-house program. Last, ProteinInferencer was used to filter the proteins containing two or more peptides with a controlled FDR of 1.0% at the protein level. Finally, we compared the performance of the IPP to a conventional proteomic pipeline (CPP) for protein identification using a controlled FDR of <1% at the protein level. Using the IPP, a total of 5756 proteins (vs 4453 using the CPP) including 477 alternative splicing variants (vs 182 using the CPP) were identified from human hippocampal tissue. In addition, a total of 10 missing proteins (vs 7 using the CPP) were identified with two or more unique peptides, and their tryptic peptides were validated using MS/MS spectral pattern from a repository database or their corresponding synthetic peptides. This study shows that the IPP effectively improved the identification of proteins, including alternative splicing variants and missing proteins, in human hippocampal tissues for the C-HPP. All RAW files used in this study were deposited in ProteomeXchange (PXD000395).

Distinct Protein Expression Profiles of Solid-Pseudopapillary Neoplasms of the Pancreas.

Solid-pseudopapillary neoplasm (SPN) is an uncommon pancreatic tumor with mutation in CTNNB1 and distinct clinical and pathological features. We compared the proteomic profiles of SPN to mRNA expression. Pooled SPNs and pooled non-neoplastic pancreatic tissues were examined with high-resolution mass spectrometry. We identified 329 (150 up-regulated and 179 down-regulated) differentially expressed proteins in SPN. We identified 191 proteins (58.1% of the 329 dysregulated proteins) with the same expression tendencies in SPN based on mRNA data. Many overexpressed proteins were related to signaling pathways known to be activated in SPNs. We found that several proteins involved in Wnt signaling, including DKK4 and ß-catenin, and proteins that bind ß-catenin, such as FUS and NONO, were up-regulated in SPNs. Molecules involved in glycolysis, including PKM2, ENO2, and HK1, were overexpressed in accordance to their mRNA levels. In summary, SPN showed (1) distinct protein expression changes that correlated with mRNA expression, (2) overexpression of Wnt signaling proteins and proteins that bind directly to ß-catenin, and (3) overexpression of proteins involved in metabolism. These findings may help develop early diagnostic biomarkers and molecular targets.

Integrated Proteomic and Genomic Analysis of Gastric Cancer Patient Tissues.

V-erb-b2 erythroblastic leukemia viral oncogene homologue 2, known as ERBB2, is an important oncogene in the development of certain cancers. It can form a heterodimer with other epidermal growth factor receptor family members and activate kinase-mediated downstream signaling pathways. ERBB2 gene is located on chromosome 17 and is amplified in a subset of cancers, such as breast, gastric, and colon cancer. Of particular interest to the Chromosome-Centric Human Proteome Project (C-HPP) initiative is the amplification mechanism that typically results in overexpression of a set of genes adjacent to ERBB2, which provides evidence of a linkage between gene location and expression. In this report we studied patient samples from ERBB2-positive together with adjacent control nontumor tissues. In addition, non-ERBB2-expressing patient samples were selected as comparison to study the effect of expression of this oncogene. We detected 196 proteins in ERBB2-positive patient tumor samples that had minimal overlap (29 proteins) with the non-ERBB2 tumor samples. Interaction and pathway analysis identified extracellular signal regulated kinase (ERK) cascade and actin polymerization and actinmyosin assembly contraction as pathways of importance in ERBB2+ and ERBB2- gastric cancer samples, respectively. The raw data files are deposited at ProteomeXchange (identifier: PXD002674) as well as GPMDB.

Combination of Multiple Spectral Libraries Improves the Current Search Methods Used to Identify Missing Proteins in the Chromosome-Centric Human Proteome Project.

Approximately 2.9 billion long base-pair human reference genome sequences are known to encode some 20 000 representative proteins. However, 3000 proteins, that is, ~15% of all proteins, have no or very weak proteomic evidence and are still missing. Missing proteins may be present in rare samples in very low abundance or be only temporarily expressed, causing problems in their detection and protein profiling. In particular, some technical limitations cause missing proteins to remain unassigned. For example, current mass spectrometry techniques have high limits and error rates for the detection of complex biological samples. An insufficient proteome coverage in a reference sequence database and spectral library also raises major issues. Thus, the development of a better strategy that results in greater sensitivity and accuracy in the search for missing proteins is necessary. To this end, we used a new strategy, which combines a reference spectral library search and a simulated spectral library search, to identify missing proteins. We built the human iRefSPL, which contains the original human reference spectral library and additional peptide sequence-spectrum match entries from other species. We also constructed the human simSPL, which contains the simulated spectra of 173 907 human tryptic peptides determined by MassAnalyzer (version 2.3.1). To prove the enhanced analytical performance of the combination of the human iRefSPL and simSPL methods for the identification of missing proteins, we attempted to reanalyze the placental tissue data set (PXD000754). The data from each experiment were analyzed using PeptideProphet, and the results were combined using iProphet. For the quality control, we applied the class-specific false-discovery rate filtering method. All of the results were filtered at a false-discovery rate of <1% at the peptide and protein levels. The quality-controlled results were then cross-checked with the neXtProt DB (2014-09-19 release). The two spectral libraries, iRefSPL and simSPL, were designed to ensure no overlap of the proteome coverage. They were shown to be complementary to spectral library searching and significantly increased the number of matches. From this trial, 12 new missing proteins were identified that passed the following criterion: at least 2 peptides of 7 or more amino acids in length or one of 9 or more amino acids in length with one or more unique sequences. Thus, the iRefSPL and simSPL combination can be used to help identify peptides that have not been detected by conventional sequence database searches with improved sensitivity and a low error rate.

Chromosome-Based Proteomic Study for Identifying Novel Protein Variants from Human Hippocampal Tissue Using Customized neXtProt and GENCODE Databases.

The goal of the Chromosome-Centric Human Proteome Project (C-HPP) is to fully provide proteomic information from each human chromosome, including novel proteoforms, such as novel protein-coding variants expressed from noncoding genomic regions, alternative splicing variants (ASVs), and single amino acid variants (SAAVs). In the 144 LC/MS/MS raw files from human hippocampal tissues of control, epilepsy, and Alzheimer's disease, we identified the novel proteoforms with a workflow including integrated proteomic pipeline using three different search engines, MASCOT, SEQUEST, and MS-GF+. With a <1% false discovery rate (FDR) at the protein level, the 11 detected peptides mapped to four translated long noncoding RNA variants against the customized databases of GENCODE lncRNA, which also mapped to coding-proteins at different chromosomal sites. We also identified four novel ASVs against the customized databases of GENCODE transcript. The target peptides from the variants were validated by tandem MS fragmentation pattern from their corresponding synthetic peptides. Additionally, a total of 128 SAAVs paired with their wild-type peptides were identified with FDR <1% at the peptide level using a customized database from neXtProt including nonsynonymous single nucleotide polymorphism (nsSNP) information. Among these results, several novel variants related in neuro-degenerative disease were identified using the workflow that could be applicable to C-HPP studies. All raw files used in this study were deposited in ProteomeXchange (PXD000395).

Abundance-ratio-based semiquantitative analysis of site-specific N-linked glycopeptides present in the plasma of hepatocellular carcinoma patients.

Aberrant structures of site-specific N-linked glycans are closely associated with the tumorigenesis of hepatocellular carcinoma (HCC), one of the most common fatal cancers worldwide. Vitronectin (VTN) is considered a candidate glycobiomarker of HCC. In this study, we describe a reliable and simple quantification strategy based on abundance ratios of site-specific N-linked glycopeptides of VTN to screen for potential biomarkers. A total of 14 unique N-linked glycans corresponding to 27 unique N-linked glycopeptides were characterized at three N-linked sites (Asn-86, -169, and -242) present in VTN. These glycans could be good candidate markers for HCC. Among these glycans, the abundance ratio of two representative glycoforms (fucosyl vs non-fucosyl) was significantly increased in HCC plasma relative to normal plasma. This strategy was also successfully applied to another potential HCC biomarker, haptoglobin. Furthermore, we demonstrate that our approach employing tandem mass tag (TMT) and target N-linked glycopeptides of VTN is a useful tool for quantifying specific glycans in HCC plasma relative to normal plasma. Our strategy represents a simple and potentially useful screening platform for the discovery of cancer-specific glycobiomarkers.

Proteogenomic analysis of human chromosome 9-encoded genes from human samples and lung cancer tissues.

The Chromosome-centric Human Proteome Project (C-HPP) was recently initiated as an international collaborative effort. Our team adopted chromosome 9 (Chr 9) and performed a bioinformatics and proteogenomic analysis to catalog Chr 9-encoded proteins from normal tissues, lung cancer cell lines, and lung cancer tissues. Approximately 74.7% of the Chr 9 genes of the human genome were identified, which included approximately 28% of missing proteins (46 of 162) on Chr 9 compared with the list of missing proteins from the neXtProt Master Table (2013-09). In addition, we performed a comparative proteomics analysis between normal lung and lung cancer tissues. On the basis of the data analysis, 15 proteins from Chr 9 were detected only in lung cancer tissues. Finally, we conducted a proteogenomic analysis to discover Chr 9-residing single nucleotide polymorphisms (SNP) and mutations described in the COSMIC cancer mutation database. We identified 21 SNPs and four mutations containing peptides on Chr 9 from normal human cells/tissues and lung cancer cell lines, respectively. In summary, this study provides valuable information of the human proteome for the scientific community as part of C-HPP. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000603.

NSBP-1 mediates the effects of cholesterol on insulin/IGF-1 signaling in Caenorhabditis elegans.

Nematode sterol-binding protein 1 (NSBP-1) is a homolog of nucleosome assembly protein 1 in mammals that is expressed widely in Caenorhabditis elegans. NSBP-1 mutants are biologically lethal, demonstrating the significance of the gene in growth and development. We investigated how cholesterol influences the insulin signaling pathway through this novel sterol-binding protein in C. elegans. Here we report that NSBP-1 influences many biological processes mediated by insulin signaling, such as longevity, dauer formation, fat storage, and resistance to oxidative stress. We found that NSBP-1 is phosphorylated by AKT-1 downstream of insulin signaling. In the absence of insulin signaling, NSBP-1 is translocated to the nucleus and binds to DAF-16, a FOXO transcription factor, in a cholesterol-dependent manner. Moreover, NSBP-1 and DAF-16 regulate a common set of genes that can directly modulate fat storage, longevity, and resistance to stress. Together, our results present a new steroid-binding molecule that can connect sterol signaling to insulin signaling through direct interaction with FOXO.

Oocyte mitochondria link maternal environment to offspring phenotype.

During maturation oocytes undergo a recently discovered mitochondrial proteome remodeling event in flies1, frogs1, and humans2. This oocyte mitochondrial remodeling, which includes substantial changes in electron transport chain (ETC) subunit abundance1,2, is regulated by maternal insulin signaling1. Why oocytes undergo mitochondrial remodeling is unknown, with some speculating that it might be an evolutionarily conserved mechanism to protect oocytes from genotoxic damage by reactive oxygen species (ROS)2. In Caenorhabditis elegans, we previously found that maternal exposure to osmotic stress drives a 50-fold increase in offspring survival in response to future osmotic stress3. Like mitochondrial remodeling, we found that this intergenerational adaptation is also regulated by insulin signaling to oocytes3. Here, we used proteomics and genetic manipulations to show that insulin signaling to oocytes regulates offspring's ability to adapt to future stress via a mechanism that depends on ETC composition in maternal oocytes. Specifically, we found that maternally expressed mutant alleles of nduf-7 (complex I subunit) or isp-1 (complex III subunit) altered offspring's response to osmotic stress at hatching independently of offspring genotype. Furthermore, we found that expressing wild-type isp-1 in germ cells (oocytes) was sufficient to restore offspring's normal response to osmotic stress. Chemical mutagenesis screens revealed that maternal ETC composition regulates offspring's response to stress by altering AMP kinase function in offspring which in turn regulates both ATP and glycerol metabolism in response to continued osmotic stress. To our knowledge, these data are the first to show that proper oocyte ETC composition is required to link a mother's environment to adaptive changes in offspring metabolism. The data also raise the possibility that the reason diverse animals exhibit insulin regulated remodeling of oocyte mitochondria is to tailor offspring metabolism to best match the environment of their mother.

NRF2-dependent regulation of the prostacyclin receptor PTGIR drives CD8 T cell exhaustion.

The progressive decline of CD8 T cell effector function-also known as terminal exhaustion-is a major contributor to immune evasion in cancer. Yet, the molecular mechanisms that drive CD8 T cell dysfunction remain poorly understood. Here, we report that the Kelch-like ECH-associated protein 1 (KEAP1)-Nuclear factor erythroid 2-related factor 2 (NRF2) signaling axis, which mediates cellular adaptations to oxidative stress, directly regulates CD8 T cell exhaustion. Transcriptional profiling of dysfunctional CD8 T cells from chronic infection and cancer reveals enrichment of NRF2 activity in terminally exhausted (Texterm) CD8 T cells. Increasing NRF2 activity in CD8 T cells (via conditional deletion of KEAP1) promotes increased glutathione production and antioxidant defense yet accelerates the development of terminally exhausted (PD-1+TIM-3+) CD8 T cells in response to chronic infection or tumor challenge. Mechanistically, we identify PTGIR, a receptor for the circulating eicosanoid prostacyclin, as an NRF2-regulated protein that promotes CD8 T cell dysfunction. Silencing PTGIR expression restores the anti-tumor function of KEAP1-deficient T cells. Moreover, lowering PTGIR expression in CD8 T cells both reduces terminal exhaustion and enhances T cell effector responses (i.e. IFN-γ and granzyme production) to chronic infection and cancer. Together, these results establish the KEAP1-NRF2 axis as a metabolic sensor linking oxidative stress to CD8 T cell dysfunction and identify the prostacyclin receptor PTGIR as an NRF2-regulated immune checkpoint that regulates CD8 T cell fate decisions between effector and exhausted states.