Chromosome-Centric Human Proteome Project Research Articles

AlphaFun: Structural-Alignment-Based Proteome Annotation Reveals why the Functionally Unknown Proteins (uPE1) Are So Understudied.

With the rapid expansion of sequencing of genomes, the functional annotation of proteins becomes a bottleneck in understanding proteomes. The Chromosome-centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome and find functional annotations for them. However, until now there are still 1137 identified human proteins without functional annotation, called uPE1 proteins. Sequence alignment was insufficient to predict their functions, and the crystal structures of most proteins were unavailable. In this study, we demonstrated a new functional annotation strategy, AlphaFun, based on structural alignment using deep-learning-predicted protein structures. Using this strategy, we functionally annotated 99% of the human proteome, including the uPE1 proteins and missing proteins, which have not been identified yet. The accuracy of the functional annotations was validated using the known-function proteins. The uPE1 proteins shared similar functions to the known-function PE1 proteins and tend to express only in very limited tissues. They are evolutionally young genes and thus should conduct functions only in specific tissues and conditions, limiting their occurrence in commonly studied biological models. Such functional annotations provide hints for functional investigations on the uPE1 proteins. This proteome-wide-scale functional annotation strategy is also applicable to any other species.

Naive Pluripotent and Trophoblastic Stem Cell Lines as a Model for Detecting Missing Proteins in the Context of the Chromosome-Centric Human Proteome Project.

The Chromosome-centric Human Proteome Project (C-HPP) aims at identifying the proteins as gene products encoded by the human genome, characterizing their isoforms and functions. The existence of products has now been confirmed for 93.2% of the genes at the protein level. The remaining mostly correspond to proteins of low abundance or difficult to access. Over the past years, we have significantly contributed to the identification of missing proteins in the human spermatozoa. We pursue our search in the reproductive sphere with a focus on early human embryonic development. Pluripotent cells, developing into the fetus, and trophoblast cells, giving rise to the placenta, emerge during the first weeks. This emergence is a focus of scientists working in the field of reproduction, placentation and regenerative medicine. Most knowledge has been harnessed by transcriptomic analysis. Interestingly, some genes are uniquely expressed in those cells, giving the opportunity to uncover new proteins that might play a crucial role in setting up the molecular events underlying early embryonic development. Here, we analyzed naive pluripotent and trophoblastic stem cells and discovered 4 new missing proteins, thus contributing to the C-HPP. The mass spectrometry proteomics data was deposited on ProteomeXchange under the data set identifier PXD035768.

D283 Med, a Cell Line Derived from Peritoneal Metastatic Medulloblastoma: A Good Choice for Missing Protein Discovery.

Since the Chromosome-Centric Human Proteome Project (C-HPP) was launched in 2010, many techniques have been adopted for the discovery of missing proteins (MPs). Because of these efforts, only 1481 MPs remained as of July 2020; however, by relying only on technique optimization, researchers have reached a bottleneck in MP discovery. Protein expression is tissue- or cell-type-dependent. The tissues of the human testis and brain have been reported to harbor a large number of tissue-specific genes and proteins; however, few studies have been performed on human brain tissue or cells to identify MPs. Herein a metastatic cell line derived from brain cancer, D283 Med, was used to search for MPs. With a traditional and simple shotgun workflow to separate the peptides into 20 fractions, 12 MPs containing at least two unique non-nested peptides (amino acid length ≥9) were identified in this cell line with a protein false discovery rate of <1%. Following the same experimental protocol, only one MP was found in a nonmetastatic brain cancer cell line, U-118 MG. Furthermore, 12 MPs were verified as having two non-nested unique peptides by matching them with corresponding chemically synthesized peptides through parallel reaction monitoring. These results clearly demonstrate that the appropriate selection of experimental materials, either tissues or cell lines, is imperative for MP discovery. The data obtained in this study are available via ProteomeXchange (PXD021482) and PeptideAtlas (PASS01627).

Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation.

One of the main goals of the Chromosome-Centric Human Proteome Project (C-HPP) is detection of "missing proteins" (PE2-PE4). Using the UPS2 (Universal proteomics standard 2) set as a model to simulate the range of protein concentrations in the cell, we have previously shown that 2D fractionation enables the detection of more than 95% of UPS2 proteins in a complex biological mixture. In this study, we propose a novel experimental workflow for protein detection during the analysis of biological samples. This approach is extremely important in the context of the C-HPP and the neXt-MP50 Challenge, which can be solved by increasing the sensitivity and the coverage of the proteome encoded by a particular human chromosome. In this study, we used 2D fractionation for in-depth analysis of the proteins encoded by human chromosome 18 (Chr 18) in the HepG2 cell line. Use of 2D fractionation increased the sensitivity of the SRM SIS method by 1.3-fold (68 and 88 proteins were identified by 1D fractionation and 2D fractionation, respectively) and the shotgun MS/MS method by 2.5-fold (21 and 53 proteins encoded by Chr 18 were detected by 1D fractionation and 2D fractionation, respectively). The results of all experiments indicate that 111 proteins encoded by human Chr 18 have been identified; this list includes 42% of the Chr 18 protein-coding genes and 67% of the Chr 18 transcriptome species (Illumina RNaseq) in the HepG2 cell line obtained using a single sample. Corresponding mRNAs were not registered for 13 of the detected proteins. The combination of 2D fractionation technology with SRM SIS and shotgun mass spectrometric analysis did not achieve full coverage, i.e., identification of at least one protein product for each of the 265 protein-coding genes of the selected chromosome. To further increase the sensitivity of the method, we plan to use 5-10 crude synthetic peptides for each protein to identify the proteins and select one of the peptides based on the obtained mass spectra for the synthesis of an isotopically labeled standard for subsequent quantitative analysis. Data are available via ProteomeXchange with the identifier PXD019263.

Open-pFind Verified Four Missing Proteins from Multi-Tissues.

The Chromosome-Centric Human Proteome Project (C-HPP) was launched in 2012 to perfect the annotation of human protein existence by identifying stronger evidence of the expression of missing proteins (MPs) at the protein level. After an 8 year effort all over the world, the number of MPs in the neXtProt database significantly decreased from 5511 (2012-02-24) to 1899 (2020-01-17). It is now more difficult to provide confident evidence of the remaining MPs because of their specific characteristics, including low abundance, low molecular weight, unexpected modifications, transmembrane structure, tissue-expression specificity, and so on. A higher resolution mass spectrometry (MS) interpretation engine might provide an opportunity to identify these buried MPs in complex samples by the combination with multi-tissue large-scale proteomics. In this study, open-pFind was used to dig MPs from 20 pairs of healthy human tissues by Wang et al. ( Mol. Syst. Biol. 2019, 15 (2), e8503) combined with our large-scale testis data set digested by three enzymes (Glu-C, Lys-C, and trypsin) with specificity for different amino acid residues ( J. Proteme Res. 2019, 18 (12), 4189-4196). A total of 1 535 536 peptides with 17 283 477 peptide-spectrum matches (PSMs) were mapped to 14 279 protein entries at a false discovery rate of <1% at the PSM, peptide, and protein levels. A total of 103 MP candidates were identified, among which 86 candidates had more unique peptide numbers compared with our single testis tissue. After rigorous screening, manual checks, peptide synthesis, and matching with documented peptides from PeptideAtlas, we validated four MPs, P0C7T8 (duodenum and small intestine), Q8WWZ4 (stomach and rectum), Q8IV35 (fallopian tube), and O14921 (tonsil), at the protein level. All MS raw files have been deposited to the ProteomeXchange with identifier PXD021391.

Human Proteome Project and Human Pluripotent Stem Cells: Odd Bedfellows or a Perfect Match?

The Chromosome-Centric Human Proteome Project (C-HPP) aims at the identification of missing proteins (MPs) and the functional characterization of functionally unannotated PE1 (uPE1) proteins. A major challenge in addressing this goal is that many human proteins and MPs are silent in adult cells. A promising approach to overcome such challenge is to exploit the advantage of novel tools such as pluripotent stem cells (PSCs), which are capable of differentiation into three embryonic germ layers, namely, the endoderm, mesoderm, and ectoderm. Here we present several examples of how the Human Y Chromosome Proteome Project (Y-HPP) benefited from this approach to meet C-HPP goals. Furthermore, we discuss how integrating CRISPR engineering, human-induced pluripotent stem cell (hiPSC)-derived disease modeling systems, and organoid technologies provides a unique platform for Y-HPP and C-HPP for MP identification and the functional characterization of human proteins, especially uPE1s.

Comparative Proteomic Profiling of 3T3-L1 Adipocyte Differentiation Using SILAC Quantification.

Adipocyte differentiation is a general physiological process that is also critical for metabolic syndrome. In spite of extensive study in the past two decades, adipogenesis is a still complex cellular process that is accompanied by complicated molecular mechanisms. Here, we performed SILAC-based quantitative global proteomic profiling of 3T3-L1 adipocyte differentiation. We report protein changes to the proteome profiles, with 354 proteins exhibiting significant increase and 56 proteins showing decrease in our statistical analysis. Our results show that adipocyte differentiation is involved not only in metabolic processes by increasing TCA cycle, fatty acid synthesis, lipolysis, acetyl-CoA production, antioxidants, and electron transport, but also in nicotinamide metabolism, cristae formation, mitochondrial protein import, and Ca2+ transport into mitochondria and ER. A search for Chromosome-Centric Human Proteome Project (C-HPP) using neXtprot highlighted one protein with a protein existence uncertain (PE5) and 17 proteins as functionally uncharacterized protein existence 1 (uPE1). This study provides quantitative information on proteome changes in adipogenic differentiation, which is helpful in improving our understanding of the processes of adipogenesis.

Empowering Shotgun Mass Spectrometry with 2DE: A HepG2 Study.

One of the major goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to catalog and annotate a myriad of heterogeneous proteoforms, produced by ca. 20 thousand genes. To achieve a detailed and personalized understanding into proteomes, we suggest using a customized RNA-seq library of potential proteoforms, which includes aberrant variants specific to certain biological samples. Two-dimensional electrophoresis coupled with high-performance liquid chromatography allowed us to downgrade the difficulty of biological mixing following shotgun mass spectrometry. To benchmark the proposed pipeline, we examined heterogeneity of the HepG2 hepatoblastoma cell line proteome. Data are available via ProteomeXchange with identifier PXD018450.

Exploration of Missing Proteins by a Combination Approach to Enrich the Low-Abundance Hydrophobic Proteins from Four Cancer Cell Lines.

The mission of the Chromosome-Centric Human Proteome Project (C-HPP) to discover missing proteins (MPs) has become increasingly difficult due to the remaining low-abundance, high-hydrophobicity, or low-molecular-weight MPs. We have reported two approaches to resolve these identification problems for the low-abundance and high-hydrophobicity MPs, respectively. In this study, to improve the identification of low-abundance MPs with high hydrophobicity, we combined two approaches and obtained MPs from several different cancer cell lines. Their membrane fractions were isolated by ultracentrifugation, and the low-abundance proteins were enriched at the protein level with the ProteoMiner kit. After that, the peptides from the enriched proteins were separated by high concentrations of organic solvents according to their hydrophobicity as the first dimension of separation at the peptide level, and the second and third dimensions of separation involved a high pH reversed-phase and an acid reversed-phase column, respectively. In total, 16 MPs (at least two non-nested unique peptides with ≥9 amino acids) with 61 unique peptides were identified from four human cancer cell lines, including 2, 8, 2, and 7 MPs from HeLa, HCT116, SNU-1, and HepG2 cells, respectively. Furthermore, all MPs were verified with two non-nested unique peptides through parallel reaction monitoring (PRM) by matching the peptides with their chemically synthesized peptides. Interestingly, two additional MPs were verified from the same cell line by PRM assay, although the two non-nested unique peptides with ≥9 amino acids for each MP were identified from different MS injections or cell lines by data-dependent acquisition (DDA). Thus, a total of 18 MPs were dug out in this study. The data are available via ProteomeXchange (PXD014058) and PeptideAtlas (PASS01388).

The "Missing" Proteome: Undetected Proteins, Not-Translated Transcripts, and Untranscribed Genes.

The Chromosome-centric Human Proteome Project aims at characterizing the expression of proteins encoded in each chromosome at the tissue, cell, and subcellular levels. The proteomic profiling of a particular tissue or cell line commonly results in a substantial portion of proteins that are not observed (the "missing" proteome). The concurrent transcriptome profiling of the analyzed tissue/cells samples may help define the set of untranscribed genes in a given type of tissue or cell, thus narrowing the size of the "missing" proteome and allowing us to focus on defining the reasons behind undetected proteins, namely, whether they are technical (insufficient sensitivity of protein detection) or biological (correspond to not-translated transcripts). We believe that the quantitative polymerase chain reaction (qPCR) can provide an efficient approach to studying low-abundant transcripts related to undetected proteins due to its high sensitivity and the possibility of ensuring the specificity of detection via the simple Sanger sequencing of PCR products. Here we illustrated the feasibility of such an approach on a set of low-abundant transcripts. Although inapplicable to the analysis of whole transcriptome, qPCR can successfully be utilized to profile a limited cohort of transcripts encoded on a particular chromosome, as we previously demonstrated for human chromosome 18.

200+ Protein Concentrations in Healthy Human Blood Plasma: Targeted Quantitative SRM SIS Screening of Chromosomes 18, 13, Y, and the Mitochondrial Chromosome Encoded Proteome

This work continues the series of the quantitative measurements of the proteins encoded by different chromosomes in the blood plasma of a healthy person. Selected Reaction Monitoring with Stable Isotope-labeled peptide Standards (SRM SIS) and a gene-centric approach, which is the basis for the implementation of the international Chromosome-centric Human Proteome Project (C-HPP), were applied for the quantitative measurement of proteins in human blood plasma. Analyses were carried out in the frame of C-HPP for each protein-coding gene of the four human chromosomes: 18, 13, Y, and mitochondrial. Concentrations of proteins encoded by 667 genes were measured in 54 blood plasma samples of the volunteers, whose health conditions were consistent with requirements for astronauts. The gene list included 276, 329, 47, and 15 genes of chromosomes 18, 13, Y, and the mitochondrial chromosome, respectively. This paper does not make claims about the detection of missing proteins. Only 205 proteins (30.7%) were detected in the samples. Of them, 84, 106, 10, and 5 belonged to chromosomes 18, 13, and Y and the mitochondrial chromosome, respectively. Each detected protein was found in at least one of the samples analyzed. The SRM SIS raw data are available in the ProteomeXchange repository (PXD004374, PASS01192).

ASV-ID, a Proteogenomic Workflow To Predict Candidate Protein Isoforms on the Basis of Transcript Evidence.

One of the goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to map and characterize the functions of protein isoforms produced by alternative splicing of genes. However, identifying alternative splice variants (ASVs) via mass spectrometry remains a major challenge, because ASVs usually contain highly homologous peptide sequences. A routine protein sequence analysis suggests that more than half of the investigated proteins do not generate two or more uniquely mapping peptides that would enable their isoforms to be distinguished. Here, we develop a new proteogenomics method, named "ASV-ID" (alternative splicing variants identification), which enables identification of ASVs by using a cell type-specific protein sequence database that is supported by RNA-Seq data. Using this workflow, we identify 1935 distinct proteins under highly stringent conditions. In fact, transcript evidence on these 841 proteins helps us distinguish them from other isoforms, despite the fact that these proteins are not predicted to make 2 or more uniquely mapping peptides. We also demonstrate that ASV-ID enables detection of 19 differently expressed isoforms present in several cell lines. Thus, a new workflow using ASV-ID has the potential to map yet-to-be-identified difficult protein isoforms in a simple and robust way.

Chromosome 17 Missing Proteins: Recent Progress and Future Directions as Part of the neXt-MP50 Challenge.

The Chromosome-centric Human Proteome Project (C-HPP), announced in September 2016, is an initiative to accelerate progress on the detection and characterization of neXtProt PE2,3,4 "missing proteins" (MPs) with a mandate to each chromosome team to find about 50 MPs over 2 years. Here we report major progress toward the neXt-MP50 challenge with 43 newly validated Chr 17 PE1 proteins, of which 25 were based on mass spectrometry, 12 on protein-protein interactions, 3 on a combination of MS and PPI, and 3 with other types of data. Notable among these new PE1 proteins were five keratin-associated proteins, a single olfactory receptor, and five additional membrane-embedded proteins. We evaluate the prospects of finding the remaining 105 MPs coded for on Chr 17, focusing on mass spectrometry and protein-protein interaction approaches. We present a list of 35 prioritized MPs with specific approaches that may be used in further MS and PPI experimental studies. Additionally, we demonstrate how in silico studies can be used to capture individual peptides from major data repositories, documenting one MP that appears to be a strong candidate for PE1. We are close to our goal of finding 50 MPs for Chr 17.

Multiproteases Combined with High-pH Reverse-Phase Separation Strategy Verified Fourteen Missing Proteins in Human Testis Tissue.

Subsequent to conducting the Chromosome-Centric Human Proteome Project, we have focused on human testis-enriched missing proteins (MPs) since 2015. For protein coverage to be enhanced, a multiprotease strategy was used for separation of samples by 10% SDS-PAGE. For the separating efficiency to be improved, a high-pH reverse phase (RP) separation strategy was applied to fractionate complex samples in this study. A total of 11,558 proteins was identified, which is the largest proteome data set for single human tissue sample so far. On the basis of this large-scale data set, we verified 14 MPs (PE2) in neXtProt (2018-01) after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant filtering, and synthesized peptide matching. Tissue expression analysis showed that 3 of 14 MPs were testis-specific proteins. Functional analysis showed that 10 of 14 MPs were closely related to liver tumor, liver carcinoma, and hepatocellular carcinoma. Another 100 MPs were listed as candidates but required additional verification information. All MS data sets have been deposited into the ProteomeXchange with the identifier PXD009737.

Digging for Missing Proteins Using Low-Molecular-Weight Protein Enrichment and a "Mirror Protease" Strategy.

In 2012, the Chromosome-centric Human Proteome Project (C-HPP) launched an investigation for missing proteins (MPs) to complete the Human Proteome Project (HPP). The majority of the MPs were distributed in low-molecular-weight (LMW) ranges, especially from 0 to 40 kDa. LMW protein identification is challenging, owing to their short length, low abundance, and hydrophobicity. Furthermore, many sequences from trypsin digestion are unlikely to yield detectable peptides or a reasonable quality of MS2 spectrum. Therefore, we focused on small MPs by combining LMW protein enrichment and a pair of complementary proteases strategy with trypsin and LysargiNase for human testis samples. In-depth testis LMW protein profiling resulted in the identification of 4063 proteins, of which 2565 were LMW proteins and 1130 had pairs of peptides generated from both trypsin and LysargiNase. This provided additional mass spectral evidence of further verification of small MPs. Finally, two MPs were verified from the seven MP candidates. One of them, Q8N688 , was verified with two series of continuous and complementary b/y-product ions from the pairs of spectra for tryptic and LysargiNase digested peptides after the "mirror spectrum" matching. This make the confident identification of the representative peptides for the target MPs. On the contrary, the two verified peptides for Q86WR6 were identified with the same strategy from the gel-separation and gel-elution samples, respectively. Although the other five MP candidates showed high-quality spectra, they could not be sufficiently distinguished as PE1s and require further verification. All MS data sets have been deposited in the ProteomeXchange with identifier PXD010093.

Launching the C-HPP neXt-CP50 Pilot Project for Functional Characterization of Identified Proteins with No Known Function.

An important goal of the Human Proteome Organization (HUPO) Chromosome-centric Human Proteome Project (C-HPP) is to correctly define the number of canonical proteins encoded by their cognate open reading frames on each chromosome in the human genome. When identified with high confidence of protein evidence (PE), such proteins are termed PE1 proteins in the online database resource, neXtProt. However, proteins that have not been identified unequivocally at the protein level but that have other evidence suggestive of their existence (PE2-4) are termed missing proteins (MPs). The number of MPs has been reduced from 5511 in 2012 to 2186 in 2018 (neXtProt 2018-01-17 release). Although the annotation of the human proteome has made significant progress, the "parts list" alone does not inform function. Indeed, 1937 proteins representing ∼10% of the human proteome have no function either annotated from experimental characterization or predicted by homology to other proteins. Specifically, these 1937 "dark proteins" of the so-called dark proteome are composed of 1260 functionally uncharacterized but identified PE1 proteins, designated as uPE1, plus 677 MPs from categories PE2-PE4, which also have no known or predicted function and are termed uMPs. At the HUPO-2017 Annual Meeting, the C-HPP officially adopted the uPE1 pilot initiative, with 14 participating international teams later committing to demonstrate the feasibility of the functional characterization of large numbers of dark proteins (CP), starting first with 50 uPE1 proteins, in a stepwise chromosome-centric organizational manner. The second aim of the feasibility phase to characterize protein (CP) functions of 50 uPE1 proteins, termed the neXt-CP50 initiative, is to utilize a variety of approaches and workflows according to individual team expertise, interest, and resources so as to enable the C-HPP to recommend experimentally proven workflows to the proteome community within 3 years. The results from this pilot will not only be the cornerstone of a larger characterization initiative but also enhance understanding of the human proteome and integrated cellular networks for the discovery of new mechanisms of pathology, mechanistically informative biomarkers, and rational drug targets.

Next Steps on in Silico 2DE Analyses of Chromosome 18 Proteoforms.

In the boundaries of the chromosome-centric Human Proteome Project (c-HPP) to obtain information about proteoforms coded by chromosome 18, several cell lines (HepG2, glioblastoma, LEH), normal liver, and plasma were analyzed. In our study, we have been using proteoform separation by two-dimensional electrophoresis (2DE) (a sectional analysis) and a semivirtual 2DE with following shotgun mass spectrometry using LC-ESI-MS/MS. Previously, we published a first draft of this research, where only HepG2 cells were tested. Here, we present the next step using more detailed analysis and more samples. Altogether, confident (2 significant sequences minimum) information about proteoforms of 117 isoforms coded by 104 genes of chromosome 18 was obtained. The 3D-graphs showing distribution of different proteoforms from the same gene in the 2D map were generated. Additionally, a semivirtual 2DE approach has allowed for detecting more proteoforms and estimating their pI more precisely. Data are available via ProteomeXchange with identifier PXD010142.

Bridging the Chromosome-centric and Biology/Disease-driven Human Proteome Projects: Accessible and Automated Tools for Interpreting the Biological and Pathological Impact of Protein Sequence Variants Detected via Proteogenomics.

The Chromosome-centric Human Proteome Project (C-HPP) seeks to comprehensively characterize all protein products coded by the genome, including those expressed sequence variants confirmed via proteogenomics methods. The closely related Biology/Disease-driven Human Proteome Project (B/D-HPP) seeks to understand the biological and pathological associations of expressed protein products, especially those carrying sequence variants that may be drivers of disease. To achieve these objectives, informatics tools are required that interpret potential functional or disease implications of variant protein sequence detected via proteogenomics. Toward this end, we have developed an automated workflow within the Galaxy for Proteomics (Galaxy-P) platform, which leverages the Cancer-Related Analysis of Variants Toolkit (CRAVAT) and makes it interoperable with proteogenomic results. Protein sequence variants confirmed by proteogenomics are assessed for potential structure-function effects as well as associations with cancer using CRAVAT's rich suite of functionalities, including visualization of results directly within the Galaxy user interface. We demonstrate the effectiveness of this workflow on proteogenomic results generated from an MCF7 breast cancer cell line. Our free and open software should enable improved interpretation of the functional and pathological effects of protein sequence variants detected via proteogenomics, acting as a bridge between the C-HPP and B/D-HPP.

Deep Dive on the Proteome of Human Cerebrospinal Fluid: A Valuable Data Resource for Biomarker Discovery and Missing Protein Identification.

Cerebrospinal fluid (CSF) is a body fluid of choice for biomarker studies of brain disorders but remains relatively under-studied compared with other biological fluids such as plasma, partly due to the more invasive means of its sample collection. The present study establishes an in-depth CSF proteome through the analysis of a unique CSF sample from a pool of donors. After immunoaffinity depletion, the CSF sample was fractionated using off-gel electrophoresis and analyzed with liquid chromatography tandem mass spectrometry (MS) using the latest generation of hybrid Orbitrap mass spectrometers. The shotgun proteomic analysis allowed the identification of 20 689 peptides mapping on 3379 proteins. To the best of our knowledge, the obtained data set constitutes the largest CSF proteome published so far. Among the CSF proteins identified, 34% correspond to genes whose transcripts are highly expressed in brain according to the Human Protein Atlas. The principal Alzheimer's disease biomarkers (e.g., tau protein, amyloid-β, apolipoprotein E, and neurogranin) were detected. Importantly, our data set significantly contributes to the Chromosome-centric Human Proteome Project (C-HPP), and 12 proteins considered as missing are proposed for validation in accordance with the HPP guidelines. Of these 12 proteins, 8 proteins are based on 2 to 6 uniquely mapping peptides from this CSF analysis, and 4 match a new peptide with a "stranded" single peptide in PeptideAtlas from previous CSF studies. The MS proteomic data are available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD009646.

Identification of Missing Proteins in Normal Human Cerebrospinal Fluid.

The cerebrospinal fluid (CSF) proteome data set presented herein was obtained after immunodepletion of abundant proteins and off-gel electrophoresis fractionation of a commercial pool of normal human CSF; liquid chromatography tandem mass spectrometry analysis was performed with a linear ion trap-Orbitrap Elite. We report the identification of 12 344 peptides mapping on 2281 proteins. In the context of the Chromosome-centric Human Proteome Project (C-HPP), the existence of seven missing proteins is proposed to be validated. This data set is available to the ProteomeXchange Consortium ( http://www.proteomexchange.org/ ) with the data set identifier PXD008029.