Metrics for the Human Proteome Project 2013-2014 and strategies for finding missing proteins

Expanding and Enriching the LncRNA Gene-Disease Landscape Using the GeneCaRNA Database

The GeneCaRNA human gene database is a member of the GeneCards Suite. It presents ~280,000 human non-coding RNA genes, identified algorithmically from ~690,000 RNAcentral transcripts. This expands by ~tenfold the ncRNA gene count relative to other sources. GeneCaRNA thus contains ~120,000 long non-coding RNAs (LncRNAs, >200 bases long), including ~100,000 novel genes. The latter have sparse functional information, a vast terra incognita for future research. LncRNA genes are uniformly represented on all nuclear chromosomes, with 10 genes on mitochondrial DNA. Data obtained from MalaCards, another GeneCards Suite member, finds 1547 genes associated with 1 to 50 diseases. About 15% of the associations portray experimental evidence, with cancers tending to be multigenic. Preliminary text mining within GeneCaRNA discovers interactions of lncRNA transcripts with target gene products, with 25% being ncRNAs and 75% proteins. GeneCaRNA has a biological pathways section, which at present shows 131 pathways for 38 lncRNA genes, a basis for future expansion. Finally, our GeneHancer database provides regulatory elements for ~110,000 lncRNA genes, offering pointers for co-regulated genes and genetic linkages from enhancers to diseases. We anticipate that the broad vista provided by GeneCaRNA will serve as an essential guide for further lncRNA research in disease decipherment.

The Differential Translation Capabilities of the Human DHFR2 Gene Indicates a Developmental and Tissue-Specific Endogenous Protein of Low Abundance

A functional role has been ascribed to the human dihydrofolate reductase 2 (DHFR2) gene based on the enzymatic activity of recombinant versions of the predicted translated protein. However, the in vivo function is still unclear. The high amino acid sequence identity (92%) between DHFR2 and its parental homolog, DHFR, makes analysis of the endogenous protein challenging. This paper describes a targeted mass spectrometry proteomics approach in several human cell lines and tissue types to identify DHFR2-specific peptides as evidence of its translation. We show definitive evidence that the DHFR2 activity in the mitochondria is in fact mediated by DHFR, and not DHFR2. Analysis of Ribo-seq data and an experimental assessment of ribosome association using a sucrose cushion showed that the two main Ensembl annotated mRNA isoforms of DHFR2, 201 and 202, are differentially associated with the ribosome. This indicates a functional role at both the RNA and protein level. However, we were unable to detect DHFR2 protein at a detectable level in most cell types examined despite various RNA isoforms of DHFR2 being relatively abundant. We did detect a DHFR2-specific peptide in embryonic heart, indicating that the protein may have a specific role during embryogenesis. We propose that the main functionality of the DHFR2 gene in adult cells is likely to arise at the RNA level.

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.

Protocol for Increasing the Sensitivity of MS-Based Protein Detection in Human Chorionic Villi

An important step in the proteomic analysis of missing proteins is the use of a wide range of tissues, optimal extraction, and the processing of protein material in order to ensure the highest sensitivity in downstream protein detection. This work describes a purification protocol for identifying low-abundance proteins in human chorionic villi using the proposed “1DE-gel concentration” method. This involves the removal of SDS in a short electrophoresis run in a stacking gel without protein separation. Following the in-gel digestion of the obtained holistic single protein band, we used the peptide mixture for further LC–MS/MS analysis. Statistically significant results were derived from six datasets, containing three treatments, each from two tissue sources (elective or missed abortions). The 1DE-gel concentration increased the coverage of the chorionic villus proteome. Our approach allowed the identification of 15 low-abundance proteins, of which some had not been previously detected via the mass spectrometry of trophoblasts. In the post hoc data analysis, we found a dubious or uncertain protein (PSG7) encoded on human chromosome 19 according to neXtProt. A proteomic sample preparation workflow with the 1DE-gel concentration can be used as a prospective tool for uncovering the low-abundance part of the human proteome.

Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins

The localization of proteins at a tissue- or cell-type-specific level is tightly linked to the protein function. To better understand each protein’s role in cellular systems, spatial information constitutes an important complement to quantitative data. The standard methods for determining the spatial distribution of proteins in single cells of complex tissue samples make use of antibodies. For a stringent analysis of the human proteome, we used orthogonal methods and independent antibodies to validate 5981 antibodies that show the expression of 3775 human proteins across all major human tissues. This enhanced validation uncovered 56 proteins corresponding to the group of “missing proteins” and 171 proteins of unknown function. The presented strategy will facilitate further discussions around criteria for evidence of protein existence based on immunohistochemistry and serves as a useful guide to identify candidate proteins for integrative studies with quantitative proteomics methods.

Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

A high-stringency blueprint of the human proteome

The Human Proteome Organization (HUPO) launched the Human Proteome Project (HPP) in 2010, creating an international framework for global collaboration, data sharing, quality assurance and enhancing accurate annotation of the genome-encoded proteome. During the subsequent decade, the HPP established collaborations, developed guidelines and metrics, and undertook reanalysis of previously deposited community data, continuously increasing the coverage of the human proteome. On the occasion of the HPP's tenth anniversary, we here report a 90.4% complete high-stringency human proteome blueprint. This knowledge is essential for discerning molecular processes in health and disease, as we demonstrate by highlighting potential roles the human proteome plays in our understanding, diagnosis and treatment of cancers, cardiovascular and infectious diseases.

A hidden human proteome encoded by 'non-coding' genes

It has been a long debate whether the 98% ‘non-coding’ fraction of human genome can encode functional proteins besides short peptides. With full-length translating mRNA sequencing and ribosome profiling, we found that up to 3330 long non-coding RNAs (lncRNAs) were bound to ribosomes with active translation elongation. With shotgun proteomics, 308 lncRNA-encoded new proteins were detected. A total of 207 unique peptides of these new proteins were verified by multiple reaction monitoring (MRM) and/or parallel reaction monitoring (PRM); and 10 new proteins were verified by immunoblotting. We found that these new proteins deviated from the canonical proteins with various physical and chemical properties, and emerged mostly in primates during evolution. We further deduced the protein functions by the assays of translation efficiency, RNA folding and intracellular localizations. As the new protein UBAP1-AST6 is localized in the nucleoli and is preferentially expressed by lung cancer cell lines, we biologically verified that it has a function associated with cell proliferation. In sum, we experimentally evidenced a hidden human functional proteome encoded by purported lncRNAs, suggesting a resource for annotating new human proteins.

Progress on Identifying and Characterizing the Human Proteome: 2019 Metrics from the HUPO Human Proteome Project

The Human Proteome Project (HPP) annually reports on progress made throughout the field in credibly identifying and characterizing the complete human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2019-01-11 contains 17 694 proteins with strong protein-level evidence (PE1), compliant with HPP Guidelines for Interpretation of MS Data v2.1; these represent 89% of all 19 823 neXtProt predicted coding genes (all PE1,2,3,4 proteins), up from 17 470 one year earlier. Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), has been reduced from 2949 to 2129 since 2016 through efforts throughout the community, including the chromosome-centric HPP. PeptideAtlas is the source of uniformly reanalyzed raw mass spectrometry data for neXtProt; PeptideAtlas added 495 canonical proteins between 2018 and 2019, especially from studies designed to detect hard-to-identify proteins. Meanwhile, the Human Protein Atlas has released version 18.1 with immunohistochemical evidence of expression of 17 000 proteins and survival plots as part of the Pathology Atlas. Many investigators apply multiplexed SRM-targeted proteomics for quantitation of organ-specific popular proteins in studies of various human diseases. The 19 teams of the Biology and Disease-driven B/D-HPP published a total of 160 publications in 2018, bringing proteomics to a broad array of biomedical research.

Utilization of the Proteome Data Deposited in SRMAtlas for Validating the Existence of the Human Missing Proteins in GPM

The Human Proteome Project (HPP) has made great efforts to clarify the existing evidence of human proteins since 2012. However, according to the recent release of neXtProt (2019-1), approximately 10% of all human genes still have inadequate or no experimental evidence of their translation at the protein level. They were categorized as missing proteins (PE2-PE4). To further the goal of HPP, we developed a two-step bioinformatic strategy addressing the utilization of the SRMAtlas synthetic peptides corresponding to the missing proteins as an exclusive reference in order to explore their natural counterparts within GPM. In the first step, we searched the GPM for the non-nested SRMAtlas peptides corresponding to the missing proteins, taking under consideration only those detected via ≥2 non-nested unitypic/proteotypic peptides "Stranded peptides" with length ≥9 amino acids in the same proteomic study. As a result, 51 missing proteins were newly detected in 35 different proteomic studies. In the second step, we validated these newly detected missing proteins based on matching the spectra of their synthetic and natural peptides in SRMAtlas and GPM, respectively. The results showed that 23 of the missing proteins with ≥2 non-nested peptides were validated by careful spectral matching.

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0

The Human Proteome Organization's (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power.

The Human Eye Proteome Project: Updates on an Emerging Proteome

The human eye is a complex organ consisting of multiple compartments with unique and specialized properties that reflect their varied functions. Although there have been advancements in ocular imaging and therapeutics over the past decade, the pathogenesis of many common eye diseases remains poorly understood. Proteomics is an invaluable tool to gain insight into pathogenesis, diagnosis, and treatment of eye diseases. By 2013, when the Human Eye Proteome Project (also known as the EyeOme) was founded, there were 4842 nonredundant proteins identified in the human eye. Twenty-three recent papers on the human eye proteome were identified in PubMed searches. These papers were used to compile an updated resource of 9782 nonredundant proteins in the human eye. This updated catalogue sheds light on the molecular makeup of previously undescribed proteomes within the human eye, including optic nerve, sclera, iris, and ciliary body, while adding additional proteins to previously characterized proteomes such as aqueous humor, lens, vitreous, retina, and retinal pigment epithelium/choroid. Although considerable advances have been made to characterize the complete proteome of the human eye, additional high-quality data are needed to confirm and quantify previously discovered eye proteins in both health and disease.

In Vitro and In Vivo Proteomic Comparison of Human Neural Progenitor Cell-Induced Photoreceptor Survival

Retinal degenerative diseases lead to blindness with few treatments. Various cell-based therapies are aimed to slow the progression of vision loss by preserving light-sensing photoreceptor cells. A subretinal injection of human neural progenitor cells (hNPCs) into the Royal College of Surgeons (RCS) rat model of retinal degeneration has aided in photoreceptor survival, though the mechanisms are mainly unknown. Identifying the retinal proteomic changes that occur following hNPC treatment leads to better understanding of neuroprotection. To mimic the retinal environment following hNPC injection, a co-culture system of retinas and hNPCs is developed. Less cell death occurs in RCS retinal tissue co-cultured with hNPCs than in retinas cultured alone, suggesting that hNPCs provide retinal protection in vitro. Comparison of ex vivo and in vivo retinas identifies nuclear factor (erythroid-derived 2)-like 2 (NRF2) mediated oxidative response signaling as an hNPC-induced pathway. This is the first study to compare proteomic changes following treatment with hNPCs in both an ex vivo and in vivo environment, further allowing the use of ex vivo modeling for mechanisms of retinal preservation. Elucidation of the protein changes in the retina following hNPC treatment may lead to the discovery of mechanisms of photoreceptor survival and its therapeutic for clinical applications.

Progress on Identifying and Characterizing the Human Proteome: 2018 Metrics from the HUPO Human Proteome Project

The Human Proteome Project (HPP) annually reports on progress throughout the field in credibly identifying and characterizing the human protein parts list and making proteomics an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2018-01-17, the baseline for this sixth annual HPP special issue of the Journal of Proteome Research, contains 17 470 PE1 proteins, 89% of all neXtProt predicted PE1-4 proteins, up from 17 008 in release 2017-01-23 and 13 975 in release 2012-02-24. Conversely, the number of neXtProt PE2,3,4 missing proteins has been reduced from 2949 to 2579 to 2186 over the past two years. Of the PE1 proteins, 16 092 are based on mass spectrometry results, and 1378 on other kinds of protein studies, notably protein-protein interaction findings. PeptideAtlas has 15 798 canonical proteins, up 625 over the past year, including 269 from SUMOylation studies. The largest reason for missing proteins is low abundance. Meanwhile, the Human Protein Atlas has released its Cell Atlas, Pathology Atlas, and updated Tissue Atlas, and is applying recommendations from the International Working Group on Antibody Validation. Finally, there is progress using the quantitative multiplex organ-specific popular proteins targeted proteomics approach in various disease categories.

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.

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.

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.

Update of the Functional Mitochondrial Human Proteome Network

Because of the pivotal role of mitochondrial alterations in several diseases, the Human Proteome Organization (HUPO) has promoted in recent years an initiative to characterize the mitochondrial human proteome, the mitochondrial human proteome project (mt-HPP). Here we generated an updated version of the functional mitochondrial human proteome network, made by nodes (mitochondrial proteins) and edges (gold binary interactions), using data retrieved from neXtProt, the reference database for HPP metrics. The principal new concept suggested was the consideration of mitochondria-associated proteins (first interactors), which may influence mitochondrial functions. All of the proteins described as mitochondrial in the sublocation or the GO Cellular Component sections of neXtProt were considered. Their other subcellular and submitochondrial localizations have been analyzed. The network represents the effort to collect all of the high-quality binary interactions described so far for mitochondrial proteins and the possibility for the community to reuse the information collected. As a proof of principle, we mapped proteins with no function, to speculate on their role by the background knowledge of their interactors, and proteins described to be involved in Parkinson's Disease, a neurodegenerative disorder, where it is known that mitochondria play a central role.

Quality control in mass spectrometry-based proteomics

Mass spectrometry is a highly complex analytical technique and mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining accurate and reproducible results. Therefore, a comprehensive and systematic approach to quality control is an essential requirement to inspire confidence in the generated results. A typical mass spectrometry experiment consists of multiple different phases including the sample preparation, liquid chromatography, mass spectrometry, and bioinformatics stages. We review potential sources of variability that can impact the results of a mass spectrometry experiment occurring in all of these steps, and we discuss how to monitor and remedy the negative influences on the experimental results. Furthermore, we describe how specialized quality control samples of varying sample complexity can be incorporated into the experimental workflow and how they can be used to rigorously assess detailed aspects of the instrument performance.

Large Scale Identification of Variant Proteins in Glioma Stem Cells

Glioblastoma (GBM), the most malignant of primary brain tumors, is a devastating and deadly disease, with a median survival of 14 months from diagnosis, despite standard regimens of radical brain tumor surgery, maximal safe radiation, and concomitant chemotherapy. GBM tumors nearly always re-emerge after initial treatment and frequently display resistance to current treatments. One theory that may explain GBM re-emergence is the existence of glioma stemlike cells (GSCs). We sought to identify variant protein features expressed in low passage GSCs derived from patient tumors. To this end, we developed a proteomic database that reflected variant and nonvariant sequences in the human proteome, and applied a novel retrograde proteomic workflow, to identify and validate the expression of 126 protein variants in 33 glioma stem cell strains. These newly identified proteins may harbor a subset of novel protein targets for future development of GBM therapy.

Utilizing glycine N-methyltransferasegene knockout mice as a model for identification of missing proteins in hepatocellular carcinoma

Glycine N-methyltransferase is a tumor suppressor gene for hepatocellular carcinoma, which can activate DNA methylation by inducing the S-adenosylmethionine to S-adenosylhomocystine. Previous studies have indicated that the expression of Glycine N-methyltransferase is inhibited in hepatocellular carcinoma. To confirm and identify missing proteins, the pathologic analysis of the tumor-bearing mice will provide critical histologic information. Such a mouse model is applied as a screening tool for hepatocellular carcinoma as well as a strategy for missing protein discovery. In this study we designed an analysis platform using the human proteome atlas to compare the possible missing proteins to human whole chromosomes. This will integrate the information from animal studies to establish an optimal technique in the missing protein biomarker discovery.

Advances in the Chromosome-Centric Human Proteome Project: looking to the future

INTRODUCTION

The mission of the Chromosome-Centric Human Proteome Project (C-HPP), is to map and annotate the entire predicted human protein set (~20,000 proteins) encoded by each chromosome. The initial steps of the project are focused on 'missing proteins (MPs)', which lacked documented evidence for existence at protein level. In addition to remaining 2,579 MPs, we also target those annotated proteins having unknown functions, uPE1 proteins, alternative splice isoforms and post-translational modifications. We also consider how to investigate various protein functions involved in cis-regulatory phenomena, amplicons lncRNAs and smORFs. Areas covered: We will cover the scope, historic background, progress, challenges and future prospects of C-HPP. This review also addresses the question of how we can best improve the methodological approaches, select the optimal biological samples, and recommend stringent protocols for the identification and characterization of MPs. A new strategy for functional analysis of some of those annotated proteins having unknown function will also be discussed. Expert commentary: If the project moves well by reshaping the original goals, the current working modules and team work in the proposed extended planning period, it is anticipated that a progressively more detailed draft of an accurate chromosome-based proteome map will become available with functional information.

Systematic Proteogenomic Approach To Exploring a Novel Function for NHERF1 in Human Reproductive Disorder: Lessons for Exploring Missing Proteins

One of the major goals of the Chromosome-Centric Human Proteome Project (C-HPP) is to fill the knowledge gaps between human genomic information and the corresponding proteomic information. These gaps are due to "missing" proteins (MPs)-predicted proteins with insufficient evidence from mass spectrometry (MS), biochemical, structural, or antibody analyses-that currently account for 2579 of the 19587 predicted human proteins (neXtProt, 2017-01). We address some of the lessons learned from the inconsistent annotations of missing proteins in databases (DB) and demonstrate a systematic proteogenomic approach designed to explore a potential new function of a known protein. To illustrate a cautious and strategic approach for characterization of novel function in vitro and in vivo, we present the case of Na(+)/H(+) exchange regulatory cofactor 1 (NHERF1/SLC9A3R1, located at chromosome 17q25.1; hereafter NHERF1), which was mistakenly labeled as an MP in one DB (Global Proteome Machine Database; GPMDB, 2011-09 release) but was well known in another public DB and in the literature. As a first step, NHERF1 was determined by MS and immunoblotting for its molecular identity. We next investigated the potential new function of NHERF1 by carrying out the quantitative MS profiling of placental trophoblasts (PXD004723) and functional study of cytotrophoblast JEG-3 cells. We found that NHERF1 was associated with trophoblast differentiation and motility. To validate this newly found cellular function of NHERF1, we used the Caenorhabditis elegans mutant of nrfl-1 (a nematode ortholog of NHERF1), which exhibits a protruding vulva (Pvl) and egg-laying-defective phenotype, and performed genetic complementation work. The nrfl-1 mutant was almost fully rescued by the transfection of the recombinant transgenic construct that contained human NHERF1. These results suggest that NHERF1 could have a previously unknown function in pregnancy and in the development of human embryos. Our study outlines a stepwise experimental platform to explore new functions of ambiguously denoted candidate proteins and scrutinizes the mandated DB search for the selection of MPs to study in the future.

Identification and Validation of Human Missing Proteins and Peptides in Public Proteome Databases: Data Mining Strategy

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10^-4)% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.

Why Are the Correlations between mRNA and Protein Levels so Low among the 275 Predicted Protein-Coding Genes on Human Chromosome 18?

In this work targeted (selected reaction monitoring, SRM, PASSEL: PASS00697) and panoramic (shotgun LC-MS/MS, PRIDE: PXD00244) mass-spectrometric methods as well as transcriptomic analysis of the same samples using RNA-Seq and PCR methods (SRA experiment IDs: SRX341198, SRX267708, SRX395473, SRX390071) were applied for quantification of chromosome 18 encoded transcripts and proteins in human liver and HepG2 cells. The obtained data was used for the estimation of quantitative mRNA-protein ratios for the 275 genes of the selected chromosome in the selected tissues. The impact of methodological limitations of existing analytical proteomic methods on gene-specific mRNA-protein ratios and possible ways of overcoming these limitations for detection of missing proteins are also discussed.

Progress on the HUPO Draft Human Proteome: 2017 Metrics of the Human Proteome Project

The Human Proteome Organization (HUPO) Human Proteome Project (HPP) continues to make progress on its two overall goals: (1) completing the protein parts list, with an annual update of the HUPO draft human proteome, and (2) making proteomics an integrated complement to genomics and transcriptomics throughout biomedical and life sciences research. neXtProt version 2017-01-23 has 17 008 confident protein identifications (Protein Existence [PE] level 1) that are compliant with the HPP Guidelines v2.1 ( https://hupo.org/Guidelines ), up from 13 664 in 2012-12 and 16 518 in 2016-04. Remaining to be found by mass spectrometry and other methods are 2579 "missing proteins" (PE2+3+4), down from 2949 in 2016. PeptideAtlas 2017-01 has 15 173 canonical proteins, accounting for nearly all of the 15 290 PE1 proteins based on MS data. These resources have extensive data on PTMs, single amino acid variants, and splice isoforms. The Human Protein Atlas v16 has 10 492 highly curated protein entries with tissue and subcellular spatial localization of proteins and transcript expression. Organ-specific popular protein lists have been generated for broad use in quantitative targeted proteomics using SRM-MS or DIA-SWATH-MS studies of biology and disease.

Identification of Missing Proteins in the Phosphoproteome of Kidney Cancer

Identifying missing proteins (MPs) has been one of the critical missions of the Chromosome-Centric Human Proteome Project (C-HPP). Since 2012, over 30 research teams from 17 countries have been trying to search adequate and accurate evidence of MPs through various biochemical strategies. MPs mainly fall into the following classes: (1) low-molecular-weight (LMW) proteins, (2) membrane proteins, (3) proteins that contained various post-translational modifications (PTMs), (4) nucleic acid-associated proteins, (5) low abundance, and (6) unexpressed genes. In this study, kidney cancer and adjacent tissues were used for phosphoproteomics research, and 8962 proteins were identified, including 6415 phosphoproteins, and 44 728 phosphosites, of which 10 266 were unreported previously. In total, 75 candidate detections were found, including 45 phoshoproteins. GO analysis for these 75 candidate detections revealed that these proteins mainly clustered as membrane proteins and took part in nephron and kidney development. After rigorous screening and manual check, 9 of them were verified with the synthesized peptides. Finally, only one missing protein was confirmed. All mass spectrometry data from this study have been deposited in the PRIDE with identifier PXD006482.

[Use of de novo sequencing for proteins identification]

Three de novo sequencing programs (Novor, PEAKS and PepNovo+) have been used for identification of 48 individual human proteins constituting the Universal Proteomics Standard Set 2 (UPS2) ("Sigma-Aldrich", USA). Experimental data have been obtained by tandem mass spectrometry. The MS/MS was performed using pure UPS2 and UPS2 mixtures with E. coli extract and human plasma samples. Protein detection was based on identification of at least two peptides of 9 residues in length or one peptide containing at least 13 residues. Using these criteria 13 (Novor), 20 (PEAKS) and 11 (PepNovo+) proteins were detected in pure UPS2 sample. Protein identifications in mixed samples were comparable or worse. Better results (by ~20%) were obtained using prediction included high quality identified fragment (TAG) containing at least 7 residues and unidentified additional masses at N- and C-termini (PepNovo+). The latter approach confidently recognized mass-spectrometric artefacts (and probably PTM). Atypical mass changes missed in UNIMOD DB were found (PepNovo+) to be statistically significant at the C-terminus (+23.02, +26.04 and +27.03). Using peptides containing these modifications and milder detection threshold 41 of 48 UPS2 proteins were identified.

Characterization of human pineal gland proteome

The pineal gland is a neuroendocrine gland located at the center of the brain. It is known to regulate various physiological functions in the body through secretion of the neurohormone melatonin. Comprehensive characterization of the human pineal gland proteome has not been undertaken to date. We employed a high-resolution mass spectrometry-based approach to characterize the proteome of the human pineal gland. A total of 5874 proteins were identified from the human pineal gland in this study. Of these, 5820 proteins were identified from the human pineal gland for the first time. Interestingly, 1136 proteins from the human pineal gland were found to contain a signal peptide domain, which indicates the secretory nature of these proteins. An unbiased global proteomic profile of this biomedically important organ should benefit molecular research to unravel the role of the pineal gland in neuropsychiatric and neurodegenerative diseases.

Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification

INTRODUCTION

Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.

The Challenge of Human Spermatozoa Proteome: A Systematic Review

Currently, there are 20,197 human protein-coding genes in the most expertly curated database (UniProtKB/Swiss-Pro). Big efforts have been made by the international consortium, the Chromosome-Centric Human Proteome Project (C-HPP) and independent researchers, to map human proteome. In brief, anno 2017 the human proteome was outlined. The male factor contributes to 50% of infertility in couples. However, there are limited human spermatozoa proteomic studies. Firstly, the development of the mapping of the human spermatozoa was analyzed. The human spermatozoa have been used as a model for missing proteins. It has been shown that human spermatozoa are excellent sources for finding missing proteins. Y chromosome proteome mapping is led by Iran. However, it seems that it is extremely challenging to map the human spermatozoa Y chromosome proteins based on current mass spectrometry-based proteomics technology. Post-translation modifications (PTMs) of human spermatozoa proteome are the most unexplored area and currently the exact role of PTMs in male infertility is unknown. Additionally, the clinical human spermatozoa proteomic analysis, anno 2017 was done in this study.

Identifying the missing proteins in human proteome by biological language model

BACKGROUND

With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and pathway analysis. Toward that end, the Human Proteome Organization lunched the Human Protein Project in 2011. However many proteins are hard to be detected by experiment methods, which becomes one of the bottleneck in Human Proteome Project. In consideration of the complicatedness of detecting these missing proteins by using wet-experiment approach, here we use bioinformatics method to pre-filter the missing proteins.

RESULTS

Since there are analogy between the biological sequences and natural language, the n-gram models from Natural Language Processing field has been used to filter the missing proteins. The dataset used in this study contains 616 missing proteins from the "uncertain" category of the neXtProt database. There are 102 proteins deduced by the n-gram model, which have high probability to be native human proteins. We perform a detail analysis on the predicted structure and function of these missing proteins and also compare the high probability proteins with other mass spectrum datasets. The evaluation shows that the results reported here are in good agreement with those obtained by other well-established databases.

CONCLUSION

The analysis shows that 102 proteins may be native gene-coding proteins and some of the missing proteins are membrane or natively disordered proteins which are hard to be detected by experiment methods.

Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications

The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list-the draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications (PTMs), and splice isoforms of those proteins; and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data sets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.1 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [ www.thehpp.org/guidelines ]. The Human Proteome presented as neXtProt version 2016-02 has 16,518 confident protein identifications (Protein Existence [PE] Level 1), up from 13,664 at 2012-12, 15,646 at 2013-09, and 16,491 at 2014-10. There are 485 proteins that would have been PE1 under the Guidelines v1.0 from 2012 but now have insufficient evidence due to the agreed-upon more stringent Guidelines v2.0 to reduce false positives. neXtProt and PeptideAtlas now both require two non-nested, uniquely mapping (proteotypic) peptides of at least 9 aa in length. There are 2,949 missing proteins (PE2+3+4) as the baseline for submissions for this fourth annual C-HPP special issue of Journal of Proteome Research. PeptideAtlas has 14,629 canonical (plus 1187 uncertain and 1755 redundant) entries. GPMDB has 16,190 EC4 entries, and the Human Protein Atlas has 10,475 entries with supportive evidence. neXtProt, PeptideAtlas, and GPMDB are rich resources of information about post-translational modifications (PTMs), single amino acid variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven (B/D)-HPP has created comprehensive SRM resources, generated popular protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative.

Detection of Missing Proteins Using the PRIDE Database as a Source of Mass Spectrometry Evidence

The current catalogue of the human proteome is not yet complete, as experimental proteomics evidence is still elusive for a group of proteins known as the missing proteins. The Human Proteome Project (HPP) has been successfully using technology and bioinformatic resources to improve the characterization of such challenging proteins. In this manuscript, we propose a pipeline starting with the mining of the PRIDE database to select a group of data sets potentially enriched in missing proteins that are subsequently analyzed for protein identification with a method based on the statistical analysis of proteotypic peptides. Spermatozoa and the HEK293 cell line were found to be a promising source of missing proteins and clearly merit further attention in future studies. After the analysis of the selected samples, we found 342 PSMs, suggesting the presence of 97 missing proteins in human spermatozoa or the HEK293 cell line, while only 36 missing proteins were potentially detected in the retina, frontal cortex, aorta thoracica, or placenta. The functional analysis of the missing proteins detected confirmed their tissue specificity, and the validation of a selected set of peptides using targeted proteomics (SRM/MRM assays) further supports the utility of the proposed pipeline. As illustrative examples, DNAH3 and TEPP in spermatozoa, and UNCX and ATAD3C in HEK293 cells were some of the more robust and remarkable identifications in this study. We provide evidence indicating the relevance to carefully analyze the ever-increasing MS/MS data available from PRIDE and other repositories as sources for missing proteins detection in specific biological matrices as revealed for HEK293 cells.

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q-Exactive HF Mass Spectrometer

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092.

Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update

The Chromosome-Centric Human Proteome Project (C-HPP) aims to identify "missing" proteins in the neXtProt knowledgebase. We present an in-depth proteomics analysis of the human sperm proteome to identify testis-enriched missing proteins. Using protein extraction procedures and LC-MS/MS analysis, we detected 235 proteins (PE2-PE4) for which no previous evidence of protein expression was annotated. Through LC-MS/MS and LC-PRM analysis, data mining, and immunohistochemistry, we confirmed the expression of 206 missing proteins (PE2-PE4) in line with current HPP guidelines (version 2.0). Parallel reaction monitoring acquisition and sythetic heavy labeled peptides targeted 36 ≪one-hit wonder≫ candidates selected based on prior peptide spectrum match assessment. 24 were validated with additional predicted and specifically targeted peptides. Evidence was found for 16 more missing proteins using immunohistochemistry on human testis sections. The expression pattern for some of these proteins was specific to the testis, and they could possibly be valuable markers with fertility assessment applications. Strong evidence was also found of four "uncertain" proteins (PE5); their status should be re-examined. We show how using a range of sample preparation techniques combined with MS-based analysis, expert knowledge, and complementary antibody-based techniques can produce data of interest to the community. All MS/MS data are available via ProteomeXchange under identifier PXD003947. In addition to contributing to the C-HPP, we hope these data will stimulate continued exploration of the sperm proteome.

Missing Protein Landscape of Human Chromosomes 2 and 14: Progress and Current Status

Within the C-HPP, the Swiss and French teams are responsible for the annotation of proteins from chromosomes 2 and 14, respectively. neXtProt currently reports 1231 entries on chromosome 2 and 624 entries on chromosome 14; of these, 134 and 93 entries are still not experimentally validated and are thus considered as "missing proteins" (PE2-4), respectively. Among these entries, some may never be validated by conventional MS/MS approaches because of incompatible biochemical features. Others have already been validated but are still awaiting annotation. On the basis of information retrieved from the literature and from three of the main C-HPP resources (Human Protein Atlas, PeptideAtlas, and neXtProt), a subset of 40 theoretically detectable missing proteins (25 on chromosome 2 and 15 on chromosome 14) was defined for upcoming targeted studies in sperm samples. This list is proposed as a roadmap for the French and Swiss teams in the near future.