Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 2.1

The Zea mays PeptideAtlas: A New Maize Community Resource

This study presents the Maize PeptideAtlas resource (www.peptideatlas.org/builds/maize) to help solve questions about the maize proteome. Publicly available raw tandem mass spectrometry (MS/MS) data for maize collected from ProteomeXchange were reanalyzed through a uniform processing and metadata annotation pipeline. These data are from a wide range of genetic backgrounds and many sample types and experimental conditions. The protein search space included different maize genome annotations for the B73 inbred line from MaizeGDB, UniProtKB, NCBI RefSeq, and for the W22 inbred line. 445 million MS/MS spectra were searched, of which 120 million were matched to 0.37 million distinct peptides. Peptides were matched to 66.2% of proteins in the most recent B73 nuclear genome annotation. Furthermore, most conserved plastid- and mitochondrial-encoded proteins (NCBI RefSeq annotations) were identified. Peptides and proteins identified in the other B73 genome annotations will improve maize genome annotation. We also illustrate the high-confidence detection of unique W22 proteins. N-terminal acetylation, phosphorylation, ubiquitination, and three lysine acylations (K-acetyl, K-malonyl, and K-hydroxyisobutyryl) were identified and can be inspected through a PTM viewer in PeptideAtlas. All matched MS/MS-derived peptide data are linked to spectral, technical, and biological metadata. This new PeptideAtlas is integrated in MaizeGDB with a peptide track in JBrowse.

Standardizing Protein Corona Characterization in Nanomedicine: A Multicenter Study to Enhance Reproducibility and Data Homogeneity

We recently revealed significant variability in protein corona characterization across various proteomics facilities, indicating that data sets are not comparable between independent studies. This heterogeneity mainly arises from differences in sample preparation protocols, mass spectrometry workflows, and raw data processing. To address this issue, we developed standardized protocols and unified sample preparation workflows, distributing uniform protein corona digests to several top-performing proteomics centers from our previous study. We also examined the influence of using similar mass spectrometry instruments on data homogeneity and standardized database search parameters and data processing workflows. Our findings reveal a remarkable stepwise improvement in protein corona data uniformity, increasing overlaps in protein identification from 11% to 40% across facilities using similar instruments and through a uniform database search. We identify the key parameters behind data heterogeneity and provide recommendations for designing experiments. Our findings should significantly advance the robustness of protein corona analysis for diagnostic and therapeutics applications.

Analysis of the GFP-labelled β-dystroglycan interactome in HEK-293 transfected cells reveals novel intracellular networks

Dystroglycan (DG) is a cell adhesion complex that is widely expressed in tissues. It is composed by two subunits, α-DG, a highly glycosylated protein that interacts with several extracellular matrix proteins, and transmembrane β-DG whose, cytodomain binds to the actin cytoskeleton. Glycosylation of α-DG is crucial for functioning as a receptor for its multiple extracellular binding partners. Perturbation of α-DG glycosylation is the central event in the pathogenesis of severe pathologies such as muscular dystrophy and cancer. β-DG acts as a scaffold for several cytoskeletal and nuclear proteins and very little is known about the fine regulation of some of these intracellular interactions and how they are perturbed in diseases. To start filling this gap by identifying uncharacterized intracellular networks preferentially associated with β-DG, HEK-293 cells were transiently transfected with a plasmid carrying the β-DG subunit with GFP fused at its C-terminus. With this strategy, we aimed at forcing β-DG to occupy multiple intracellular locations instead of sitting tightly at its canonical plasma membrane milieu, where it is commonly found in association with α-DG. Immunoprecipitation by anti-GFP antibodies followed by shotgun proteomic analysis led to the identification of an interactome formed by 313 exclusive protein matches for β-DG binding. A series of already known β-DG interactors have been found, including ezrin and emerin, whilst significant new matches, which include potential novel β-DG interactors and their related networks, were identified in diverse subcellular compartments, such as cytoskeleton, endoplasmic reticulum/Golgi, mitochondria, nuclear membrane and the nucleus itself. Of particular interest amongst the novel identified matches, Lamina-Associated Polypeptide-1B (LAP1B), an inner nuclear membrane protein, whose mutations are known to cause nuclear envelopathies characterized by muscular dystrophy, was found to interact with β-DG in HEK-293 cells. This evidence was confirmed by immunoprecipitation, Western blotting and immunofluorescence experiments. We also found by immunofluorescence experiments that LAP1B looses its nuclear envelope localization in C2C12 DG-knock-out cells, suggesting that LAP1B requires β-DG for a proper nuclear localization. These results expand the role of β-DG as a nuclear scaffolding protein and provide novel evidence of a possible link between dystroglycanopathies and nuclear envelopathies displaying with muscular dystrophy.

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

A uniform data processing pipeline enables harmonized nanoparticle protein corona analysis across proteomics core facilities

Protein corona, a layer of biomolecules primarily comprising proteins, forms dynamically on nanoparticles in biological fluids and is crucial for predicting nanomedicine safety and efficacy. The protein composition of the corona layer is typically analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Our recent study, involving identical samples analyzed by 17 proteomics facilities, highlighted significant data variability, with only 1.8% of proteins consistently identified across these centers. Here, we implement an aggregated database search unifying parameters such as variable modifications, enzyme specificity, number of allowed missed cleavages and a stringent 1% false discovery rate at the protein and peptide levels. Such uniform search dramatically harmonizes the proteomics data, increasing the reproducibility and the percentage of consistency-identified unique proteins across distinct cores. Specifically, out of the 717 quantified proteins, 253 (35.3%) are shared among the top 5 facilities (and 16.2% among top 11 facilities). Furthermore, we note that reduction and alkylation are important steps in protein corona sample processing and as expected, omitting these steps reduces the number of total quantified peptides by around 20%. These findings underscore the need for standardized procedures in protein corona analysis, which is vital for advancing clinical applications of nanoscale biotechnologies.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

Biological factors and statistical limitations prevent detection of most noncanonical proteins by mass spectrometry

Ribosome profiling experiments indicate pervasive translation of short open reading frames (ORFs) outside of annotated protein-coding genes. However, shotgun mass spectrometry (MS) experiments typically detect only a small fraction of the predicted protein products of this noncanonical translation. The rarity of detection could indicate that most predicted noncanonical proteins are rapidly degraded and not present in the cell; alternatively, it could reflect technical limitations. Here, we leveraged recent advances in ribosome profiling and MS to investigate the factors limiting detection of noncanonical proteins in yeast. We show that the low detection rate of noncanonical ORF products can largely be explained by small size and low translation levels and does not indicate that they are unstable or biologically insignificant. In particular, proteins encoded by evolutionarily young genes, including those with well-characterized biological roles, are too short and too lowly expressed to be detected by shotgun MS at current detection sensitivities. Additionally, we find that decoy biases can give misleading estimates of noncanonical protein false discovery rates, potentially leading to false detections. After accounting for these issues, we found strong evidence for 4 noncanonical proteins in MS data, which were also supported by evolution and translation data. These results illustrate the power of MS to validate unannotated genes predicted by ribosome profiling, but also its substantial limitations in finding many biologically relevant lowly expressed proteins.

What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome?

Ribosome profiling (Ribo-Seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of noncanonical sites of ribosome translation outside the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7000 noncanonical ORFs are translated, which, at first glance, has the potential to expand the number of human protein CDSs by 30%, from ∼19,500 annotated CDSs to over 26,000 annotated CDSs. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of noncanonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome but searching for guidance on how to proceed. Here, we discuss the current state of noncanonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein coding."

Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the 'dark' proteome. This dark proteome is highly enriched for certain ( e.g. CLE, CEP, IDA, PSY) but not other ( e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life ( e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.

What can Ribo-seq and proteomics tell us about the non-canonical proteome?

Ribosome profiling (Ribo-seq) has proven transformative for our understanding of the human genome and proteome by illuminating thousands of non-canonical sites of ribosome translation outside of the currently annotated coding sequences (CDSs). A conservative estimate suggests that at least 7,000 non-canonical open reading frames (ORFs) are translated, which, at first glance, has the potential to expand the number of human protein-coding sequences by 30%, from ∼19,500 annotated CDSs to over 26,000. Yet, additional scrutiny of these ORFs has raised numerous questions about what fraction of them truly produce a protein product and what fraction of those can be understood as proteins according to conventional understanding of the term. Adding further complication is the fact that published estimates of non-canonical ORFs vary widely by around 30-fold, from several thousand to several hundred thousand. The summation of this research has left the genomics and proteomics communities both excited by the prospect of new coding regions in the human genome, but searching for guidance on how to proceed. Here, we discuss the current state of non-canonical ORF research, databases, and interpretation, focusing on how to assess whether a given ORF can be said to be "protein-coding".

In brief

The human genome encodes thousands of non-canonical open reading frames (ORFs) in addition to protein-coding genes. As a nascent field, many questions remain regarding non-canonical ORFs. How many exist? Do they encode proteins? What level of evidence is needed for their verification? Central to these debates has been the advent of ribosome profiling (Ribo-seq) as a method to discern genome-wide ribosome occupancy, and immunopeptidomics as a method to detect peptides that are processed and presented by MHC molecules and not observed in traditional proteomics experiments. This article provides a synthesis of the current state of non-canonical ORF research and proposes standards for their future investigation and reporting.

Highlights

Combined use of Ribo-seq and proteomics-based methods enables optimal confidence in detecting non-canonical ORFs and their protein products.Ribo-seq can provide more sensitive detection of non-canonical ORFs, but data quality and analytical pipelines will impact results.Non-canonical ORF catalogs are diverse and span both high-stringency and low-stringency ORF nominations.A framework for standardized non-canonical ORF evidence will advance the research field.

Exploiting bioactive natural products of marine origin: Evaluation of the meroterpenoid metachromin V as a novel potential therapeutic drug for colorectal cancer

Colorectal cancer (CRC) is the second most common cause of cancer death, leading to almost 1 million deaths per year. Despite constant progress in surgical and therapeutic protocols, the 5-year survival rate of advanced CRC patients remains extremely poor. Colorectal Cancer Stem Cells (CRC-CSCs) are endowed with unique stemness-related properties responsible for resistance, relapse and metastasis. The development of novel therapeutics able to tackle CSCs while avoiding undesired toxicity is a major need for cancer treatment. Natural products are a large reservoir of unexplored compounds with possible anticancer bioactivity, sustainability, and safety. The family of meroterpenoids derived from sponges share interesting bioactive properties. Bioassay-guided fractionation of a meroterpenoids extract led to the isolation of three compounds, all cytotoxic against several cancer cell lines: Metachromins U, V and W. In this study, we evaluated the anticancer potential of the most active one, Metachromins V (MV), on patient-derived CRC-CSCs. MV strongly impairs CSCs-viability regardless their mutational background and the cytotoxic effect is maintained on therapy-resistant metastatic CSCs. MV affects cell cycle progression, inducing a block in G2 phase in all the cell lines tested and more pronouncedly in CRC-CSCs. Moreover, MV triggers an important reorganization of the cytoskeleton and a strong reduction of Rho GTPases expression, impairing CRC-CSCs motility and invasion ability. By Proteomic analysis identified a potential molecular target of MV: CCAR1, that regulates apoptosis under chemotherapy treatments and affect β-catenin pathway. Further studies will be needed to confirm and validate these data in in vivo experimental models.

The 2022 Report on the Human Proteome from the HUPO Human Proteome Project

The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, "A Function for Each Protein".

[Analysis and identification of suspected snake venom samples using nano-ultra-high performance liquid chromatography-high resolution mass spectrometry]

Snake venom is a complex mixture secreted from the glands of poisonous snakes， which contains proteins， peptides， lipids， nucleosides， sugars， amino acids， amines， metal ions， and other components. According to the toxicological classification， snake venoms can be classified as neurotoxins， anticoagulants and procoagulant toxins， cardiac toxins， other toxin proteins， and enzymes. Proteins and peptides are the key components of snake venom. The establishment of rapid， accurate analysis and identification methods for proteins in snake venom is a prerequisite for snake venom-related forensic identification， intoxication events， and pharmaceutical development. Until now， the classical analysis and identification methods have mainly been biochemical or immunoassays for DNA or proteins， such as polymerase chain reaction， agglutination test， enzyme-linked immunosorbent assay， fluorescent immunoassay， and various biosensing approaches. These methods have some limitations such as a high false-positive ratio， low sensitivity， poor anti-interference ability， and limited species discrimination capability. In recent years， with the rapid development of mass spectrometry （MS） techniques， the proteomics of snake venom has also attracted much attention and has contributed to the identification of snake species， in which non-targeted and targeted proteomics represent two main divisions. However， species identification via proteomics is in its infancy in forensic science. First， the tandem MS spectra of peptide sequences are highly complex， which poses a great challenge for the strict and accurate matching of peptides based on the rational speculation of MS fragmentation rules and theoretical calculations in non-targeted proteomics. Second， for the confirmation and identification of unknown substances， reference substances are commonly needed， but those for snake venom are lacking. Proteomics in snake venom identification is still in progress to improve the identification confidence and clarify the identification rules. In this work， a method based on nano-ultra-high performance liquid chromatography-quadrupole-orbitrap high-resolution mass spectrometry （Nano LC-MS/HRMS） and size exclusion chromatography （SEC） was developed for identifying proteins and their source species， with strict rules for five suspected snake venom samples and their contamination in one case. Three SEC elution peaks were obtained from each of the five samples， which were lyophilized and treated with trypsin in solution， and then separated and analyzed by Nano LC-MS/HRMS. First， the Full MS/dd MS² mode was used for the non-targeted acquisition of peptide information in the samples， and after submission to the Swiss-Prot database， the protein databases of Serpentes， Colubroidea， Elapidae， Elapinae， and Naja were contracted stepwise and compared. A total of 32 proteins from Naja atra were identified under the conditions of both peptide spectrum match and false discovery rate less than 1%， and number of characteristic peptides greater than or equal to two. All of these were derived from ten families of Naja atra， mainly three-finger toxins， metalloproteinases， and phospholipase A2. Proteins D3TTC2， D5LMJ3， Q7T1K6， Q9DEQ3， and Q9YGI4 were the most common among the five samples. Finally， the parallel reaction monitoring mode was adopted to select two unique peptides for each protein for targeted verification. It was considered that a protein in the samples was truly identified when it met the strict standard "the Δm/z of at least 75% y⁺ and b⁺ ions of each unique peptide was less than 5 ppm". After these consequently procedures， we identified that all five samples contained the venom of the Naja atra. Our identification method is a systematic and strict example that can provide effective technical support for the forensic identification of snake venom poisoning， as well as for pharmaceutical development toward snake venoms.

Proteomics Standards Initiative at Twenty Years: Current Activities and Future Work

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies (CVs) for the proteomics community and other fields supported by mass spectrometry since its inception 20 years ago. Here we describe the general operation of the PSI, including its leadership, working groups, yearly workshops, and the document process by which proposals are thoroughly and publicly reviewed in order to be ratified as PSI standards. We briefly describe the current state of the many existing PSI standards, some of which remain the same as when originally developed, some of which have undergone subsequent revisions, and some of which have become obsolete. Then the set of proposals currently being developed are described, with an open call to the community for participation in the forging of the next generation of standards. Finally, we describe some synergies and collaborations with other organizations and look to the future in how the PSI will continue to promote the open sharing of data and thus accelerate the progress of the field of proteomics.

[The promise of omics in the precision medicine era]

The rise of omics technologies that simultaneously measure thousands of molecules in a complex biological sample represents the core of systems biology. These technologies have profoundly impacted biomarkers and therapeutic targets discovery in the precision medicine era. Systems biology aims to perform a systematic probing of complex interactions in biological systems. Powered by high-throughput omics technologies and high-performance computing, systems biology provides relevant, resolving, and multi-scale overviews from cells to populations. Precision medicine takes advantage of these conceptual and technological developments and is based on two main pillars: the generation of multimodal data and their subsequent modeling. High-throughput omics technologies enable the comprehensive and holistic extraction of biological information, while computational capabilities enable multidimensional modeling and, as a result, offer an intuitive and intelligible visualization. Despite their promise, translating these technologies into clinically actionable tools has been slow. In this contribution, we present the most recent multi-omics data generation and analysis strategies and their clinical deployment in the post-genomic era. Furthermore, medical application challenges of omics-based biomarkers are discussed.

Evolution of Protein Functional Annotation: Text Mining Study

Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through “handshakes” to biochemical processes.

Discovery of Missing Proteins from an Aneuploidy Cell Line Using a Proteogenomic Approach

With the steadfast development of proteomic technology, the number of missing proteins (MPs) has been continuously shrinking, with approximately 1470 MPs that have not been explored yet. Due to this phenomenon, the discovery of MPs has been increasingly more difficult and elusive. In order to face this challenge, we have hypothesized that a stable aneuploid cell line with increased chromosomes serves as a useful material for assisting MP exploration. Ker-CT cell line with trisomy at chromosome 5 and 20 was selected for this purpose. With a combination strategy of RNA-Seq and LC-MS/MS, a total of 22 178 transcripts and 8846 proteins were identified in Ker-CT. Although the transcripts corresponding to 15 and 15 MP genes located at chromosome 5 and 20 were detected, none of the MPs were found in Ker-CT. Surprisingly, 3 MPs containing at least two unique non-nest peptides of length ≥9 amino acids were identified in Ker-CT, whose genes are located on chromosome 3 and 10, respectively. Furthermore, the 3 MPs were verified using the method of parallel reaction monitoring (PRM). These results suggest that the abnormal status of chromosomes may not only impact the expression of the corresponding genes in trisomy chromosomes, but also influence that of other chromosomes, which benefits MP discovery. The data obtained in this study are available via ProteomeXchange (PXD028647) and PeptideAtlas (PASS01700), respectively.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource

We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data.

Advances and Utility of the Human Plasma Proteome

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/

Equine Mesenchymal Stem/Stromal Cells Freeze-Dried Secretome (Lyosecretome) for the Treatment of Musculoskeletal Diseases: Production Process Validation and Batch Release Test for Clinical Use

In the last decades, it has been demonstrated that the regenerative therapeutic efficacy of mesenchymal stromal cells is primarily due to the secretion of soluble factors and extracellular vesicles, collectively known as secretome. In this context, our work described the preparation and characterization of a freeze-dried secretome (Lyosecretome) from adipose tissue-derived mesenchymal stromal cells for the therapy of equine musculoskeletal disorder. An intraarticular injectable pharmaceutical powder has been formulated, and the technological process has been validated in an authorized facility for veterinary clinical-use medicinal production. Critical parameters for quality control and batch release have been identified regarding (i) physicochemical properties; (ii) extracellular vesicle morphology, size distribution, and surface biomarker; (iii) protein and lipid content; (iv) requirements for injectable pharmaceutical dosage forms such as sterility, bacterial endotoxin, and Mycoplasma; and (v) in vitro potency tests, as anti-elastase activity and proliferative activity on musculoskeletal cell lines (tenocytes and chondrocytes) and mesenchymal stromal cells. Finally, proteins putatively responsible for the biological effects have been identified by Lyosecretome proteomic investigation: IL10RA, MXRA5, RARRES2, and ANXA1 modulate the inflammatory process RARRES2, NOD1, SERPINE1, and SERPINB9 with antibacterial activity. The work provides a proof-of-concept for the manufacturing of clinical-grade equine freeze-dried secretome, and prototypes are now available for safety and efficacy clinical trials in the treatment of equine musculoskeletal diseases

Integrative functional genomic analysis of intron retention in human and mouse brain with Alzheimer's disease

Intron retention (IR) has been implicated in the pathogenesis of complex diseases such as cancers; its association with Alzheimer's disease (AD) remains unexplored. We performed genome-wide analysis of IR through integrating genetic, transcriptomic, and proteomic data of AD subjects and mouse models from the Accelerating Medicines Partnership-Alzheimer's Disease project. We identified 4535 and 4086 IR events in 2173 human and 1736 mouse genes, respectively. Quantitation of IR enabled the identification of differentially expressed genes that conventional exon-level approaches did not reveal. There were significant correlations of intron expression within innate immune genes, like HMBOX1, with AD in humans. Peptides with a high probability of translation from intron-retained mRNAs were identified using mass spectrometry. Further, we established AD-specific intron expression Quantitative Trait Loci, and identified splicing-related genes that may regulate IR. Our analysis provides a novel resource for the search for new AD biomarkers and pathological mechanisms.

Proteomic Changes Associated With Sperm Fertilizing Ability in Meat-Type Roosters

The molecular basis of male fertility remains unclear, especially in chickens, where decades of genetic selection increased male fertility variability as a side effect. As transcription and translation are highly limited in sperm, proteins are key molecules defining their functionality, making proteomic approaches one of the most adequate methods to investigate sperm capacity. In this context, it is interesting to combine complementary proteomic approaches to maximize the identification of proteins related to sperm-fertilizing ability. In the present study, we aimed at identifying proteins related to fertility in meat-type roosters, showing fertility variability. Fertile roosters (fertility rates higher than 70% after artificial insemination) differed from subfertile roosters (fertility rates lower than 40%) in their sperm mass motility. Fertile and subfertile sperm protein contents were compared using two complementary label-free quantitative proteomic methods: Intact Cell MALDI-TOF-Mass Spectrometry and GeLC-MS/MS. Combining the two strategies, 57 proteins were identified as differentially abundant. Most of them were described for the first time as differentially abundant according to fertility in this species. These proteins were involved in various molecular pathways including flagellum integrity and movement, mitochondrial functions, sperm maturation, and storage in female tract as well as oocyte-sperm interaction. Collectively, our data improved our understanding of chicken sperm biology by revealing new actors involved in the complexity of male fertility that depends on multiple cell functions to reach optimal rates. This explains the inability of reductionist in vitro fertility testing in predicting male fertility and suggests that the use of a combination of markers is a promising approach.

Reflections on the HUPO Human Proteome Project, the Flagship Project of the Human Proteome Organization, at 10 Years

We celebrate the 10th anniversary of the launch of the HUPO Human Proteome Project (HPP) and its major milestone of confident detection of at least one protein from each of 90% of the predicted protein-coding genes, based on the output of the entire proteomics community. The Human Genome Project reached a similar decadal milestone 20 years ago. The HPP has engaged proteomics teams around the world, strongly influenced data-sharing, enhanced quality assurance, and issued stringent guidelines for claims of detecting previously "missing proteins." This invited perspective complements papers on "A High-Stringency Blueprint of the Human Proteome" and "The Human Proteome Reaches a Major Milestone" in special issues of Nature Communications and Journal of Proteome Research, respectively, released in conjunction with the October 2020 virtual HUPO Congress and its celebration of the 10th anniversary of the HUPO HPP.

Caloric Restriction Promotes Immunometabolic Reprogramming Leading to Protection from Tuberculosis

There is a strong relationship between metabolic state and susceptibility to Mycobacterium tuberculosis (MTB) infection, with energy metabolism setting the basis for an exaggerated immuno-inflammatory response, which concurs with MTB pathogenesis. Herein, we show that controlled caloric restriction (CR), not leading to malnutrition, protects susceptible DBA/2 mice against pulmonary MTB infection by reducing bacterial load, lung immunopathology, and generation of foam cells, an MTB reservoir in lung granulomas. Mechanistically, CR induced a metabolic shift toward glycolysis, and decreased both fatty acid oxidation and mTOR activity associated with induction of autophagy in immune cells. An integrated multi-omics approach revealed a specific CR-induced metabolomic, transcriptomic, and proteomic signature leading to reduced lung damage and protective remodeling of lung interstitial tightness able to limit MTB spreading. Our data propose CR as a feasible immunometabolic manipulation to control MTB infection, and this approach offers an unexpected strategy to boost immunity against MTB.

Ethical Principles, Constraints and Opportunities in Clinical Proteomics

Recent advances in mass spectrometry (MS)-based proteomics have vastly increased the quality and scope of biological information that can be derived from human samples. These advances have rendered current workflows increasingly applicable in biomedical and clinical contexts. As proteomics is poised to take an important role in the clinic, associated ethical responsibilities increase in tandem with impacts on the health, privacy, and wellbeing of individuals. We conducted and here report a systematic literature review of ethical issues in clinical proteomics. We add our perspectives from a background of bioethics, the results of our accompanying paper extracting individual-sensitive results from patient samples, and the literature addressing similar issues in genomics. The spectrum of potential issues ranges from patient re-identification to incidental findings of clinical significance. The latter can be divided into actionable and unactionable findings. Some of these have the potential to be employed in discriminatory or privacy-infringing ways. However, incidental findings may also have great positive potential. A plasma proteome profile, for instance, could inform on the general health or disease status of an individual regardless of the narrow diagnostic question that prompted it. We suggest that early discussion of ethical issues in clinical proteomics can ensure that eventual healthcare practices and regulations reflect the considered judgment of the community and anticipate opportunities and problems that may arise as the technology matures.

Glioblastoma CUSA Fluid Protein Profiling: A Comparative Investigation of the Core and Peripheral Tumor Zones

Simple Summary

The biological processes responsible for the high infiltration and recurrence rate of glioblastoma multiforme, the most frequent and aggressive primary brain tumor (GBM), are still under investigation. By the original analysis of cavitating ultrasound aspirator fluid as the biological specimen, the present study aimed to preliminarily explore and compare the protein profiles of the tumor core and tumor periphery, as defined by 5-aminolevulinic acid fluorescence, in newly diagnosed and recurrent glioblastoma sampled pools. The results showed distinguished protein elements in the different tumor and peritumoral zones, as well as in the two tumor states (newly diagnosed vs recurrent), and suggested the presence of pathological aspects in the fluorescent negative periphery, possibly contributing to the comprehension of the molecular mechanisms underlying this tumor’s onset and development, opening to potential clinical applications.

Abstract

The present investigation aimed to characterize the protein profile of cavitating ultrasound aspirator fluid of newly diagnosed and recurrent glioblastoma comparing diverse zones of collection, i.e., tumor core and tumor periphery, with the aid of 5-aminolevulinic acid fluorescence. The samples were pooled and analyzed in triplicate by LC-MS following the shotgun proteomic approach. The identified proteins were then grouped to disclose elements exclusive and common to the tumor state or tumor zones and submitted to gene ontology classification and pathway overrepresentation analysis. The proteins common to the distinct zones were further investigated by relative quantitation, following a label free approach, to disclose possible differences of expression. Nine proteins, i.e., tubulin 2B chain, CD59, far upstream element-binding, CD44, histone H1.4, caldesmon, osteopontin, tropomyosin chain and metallothionein-2, marked the core of newly diagnosed glioblastoma with respect to tumor periphery. Considering the tumor zone, including the core and the fluorescence positive periphery, the serine glycine biosynthesis, pentose phosphate, 5-hydroxytryptamine degredation, de novo purine biosynthesis and huntington disease pathways resulted statistically significantly overrepresented with respect to the human genome of reference. The fluorescence negative zone shared several protein elements with the tumor zone, possibly indicating the presence of pathological aspects of glioblastoma rather than of normal brain parenchyma. On the other hand, its exclusive protein elements were considered to represent the healthy zone and, accordingly, exhibiting no pathways overrepresentation. On the contrary to newly diagnosed glioblastoma, pathway overrepresentation was recognized only in the healthy zone of recurrent glioblastoma. The TGFβ signaling pathway, exclusively classified in the fluorescence negative periphery in newly diagnosed glioblastoma, was instead the exclusive pathway classified in the tumor core of recurrent glioblastoma. These results, preliminary obtained on sample pools, demonstrated the potential of cavitron ultrasonic surgical aspirate fluid for proteomic profiling of glioblastoma able to distinguish molecular features specific of the diverse tumor zones and tumor states, possibly contributing to the understanding of the highly infiltrative capability and recurrent rate of this aggressive brain tumor and opening to potential clinical applications to be further investigated.

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.

Potential Regulatory Role of Human-Carboxylesterase-1 Glycosylation in Liver Cancer Cell Growth

We previously reported that human carboxylesterase 1 (CES1), a serine esterase containing a unique N-linked glycosyl group at Asn79 (N79 CES1), is a candidate serological marker of hepatocellular carcinoma (HCC). CES1 is normally present at low-to-undetectable levels in normal human plasma, HCC tumors, and major liver cancer cell lines. To investigate the potential mechanism underlying the suppression of CES1 expression in liver cancer cells, we took advantage of the low detectability of this marker in tumors by overexpressing CES1 in multiple HCC cell lines, including stable Hep3B cells. We found that the population of CES1-overexpressing (OE) cells decreased and that their doubling time was longer compared with mock control liver cancer cells. Using interactive transcriptome, proteome, and subsequent Gene Ontology enrichment analysis of CES1-OE cells, we found substantial decreases in the expression levels of genes involved in cell cycle regulation and proliferation. This antiproliferative function of the N79 glycan of CES1 was further supported by quantitative real-time polymerase chain reaction, flow cytometry, and an apoptosis protein array assay. An analysis of the levels of key signaling target proteins via Western blotting suggested that CES1 overexpression exerted an antiproliferative effect via the PKD1/PKCμ signaling pathway. Similar results were also seen in another HCC cell line (PLC/RFP/5) after transient transfection with CES1 but not in similarly treated non-HCC cell lines (e.g., HeLa and Tera-1 cells), suggesting that CES1 likely exerts a liver cell-type-specific suppressive effect. Given that the N-linked glycosyl group at Asn79 (N79 glycan) of CES1 is known to influence CES1 enzyme activity, we hypothesized that the post-translational modification of CES1 at N79 may be linked to its antiproliferative activity. To investigate the regulatory effect of the N79 glycan on cellular growth, we mutated the single N-glycosylation site in CES1 from Asn to Gln (CES1-N79Q) via site-directed mutagenesis. Fluorescence 2-D difference gel electrophoresis protein expression analysis of cell lysates revealed an increase in cell growth and a decrease in doubling time in cells carrying the N79Q mutation. Thus our results suggest that CES1 exerts an antiproliferative effect in liver cancer cells and that the single N-linked glycosylation at Asn79 plays a potential regulatory role. These functions may underlie the undetectability of CES1 in human HCC tumors and liver cancer cell lines. Mass spectrometry data are available via ProteomeXchange under the identifier PXD021573.

Protein Cargo of Extracellular Vesicles From Bovine Follicular Fluid and Analysis of Their Origin From Different Ovarian Cells

Follicular fluid (FF) fills the interior portion of the ovarian antral follicle and provides a suitable microenvironment for the growth of the enclosed oocyte through molecular factors that originate from plasma and the secretions of follicular cells. FF contains extracellular nanovesicles (ffEVs), including 30-100-nm membrane-coated exosomes, which carry different types of RNA, proteins, and lipids and directly influence oocyte competence to develop embryo. In the present study, we aimed to characterize the protein cargo of EVs from the FF of 3-6-mm follicles and uncover the origins of ffEVs by assessing expression levels of corresponding mRNAs in bovine follicular cells and oocyte and cell proteomes. Isolated exosome-like ffEVs were 53.6 + 23.3 nm in size and could be internalized by cumulus-oocyte complex. Proteomes of ffEVs and granulosa cells (GC) were assessed using nanoflow liquid chromatography coupled with high-resolution tandem mass spectrometry after the gel fractionation of total proteins. In total, 460 protein isoforms corresponding to 322 unique proteins were identified in ffEVs; among them, 190 were also identified via GC. Gene Ontology terms related to the ribosome, protein and RNA folding, molecular transport, endocytosis, signal transduction, complement and coagulation cascades, apoptosis, and developmental biology pathways, including PI3K-Akt signaling, were significantly enriched features of ffEV proteins. FfEVs contain numerous ribosome and RNA-binding proteins, which may serve to compact different RNAs to regulate gene expression and RNA degradation, and might transfer ribosomal constituents to the oocyte. Majority of genes encoding ffEV proteins expressed at different levels in follicular cells and oocyte, corroborating with numerous proteins, which were reported in bovine oocyte and cumulus cells in other studies thus indicating possible origin of ffEV proteins. The limited abundance of several mRNAs within follicular cells indicated that corresponding ffEV proteins likely originated from circulating exosomes released by other tissues. Analysis of bovine ffEV transcriptome revealed that mRNAs present in ffEV accounted for only 18.3% of detected ffEV proteins. In conclusion, our study revealed numerous proteins within ffEVs, which originated from follicular and other cells. These proteins are likely involved in the maintenance of follicular homeostasis and may affect oocyte competence.

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.

Splice-Junction-Based Mapping of Alternative Isoforms in the Human Proteome

The protein-level translational status and function of many alternative splicing events remain poorly understood. We use an RNA sequencing (RNA-seq)-guided proteomics method to identify protein alternative splicing isoforms in the human proteome by constructing tissue-specific protein databases that prioritize transcript splice junction pairs with high translational potential. Using the custom databases to reanalyze ~80 million mass spectra in public proteomics datasets, we identify more than 1,500 noncanonical protein isoforms across 12 human tissues, including ~400 sequences undocumented on TrEMBL and RefSeq databases. We apply the method to original quantitative mass spectrometry experiments and observe widespread isoform regulation during human induced pluripotent stem cell cardiomyocyte differentiation. On a proteome scale, alternative isoform regions overlap frequently with disordered sequences and post-translational modification sites, suggesting that alternative splicing may regulate protein function through modulating intrinsically disordered regions. The described approach may help elucidate functional consequences of alternative splicing and expand the scope of proteomics investigations in various systems.

The translation and function of many alternative splicing events await confirmation at the protein level. Lau et al. use an integrated proteotranscriptomics approach to identify non-canonical and undocumented isoforms from 12 organs in the human proteome. Alternative isoforms interfere with functional sequence features and are differentially regulated during iPSC cardiomyocyte differentiation.

GMP-compliant sponge-like dressing containing MSC lyo-secretome: Proteomic network of healing in a murine wound model

Chronic wounds account for 3% of total healthcare expenditure of developed countries; thus, innovative therapies, including Mesenchymal Stem Cells (MSCs) end their exosomes are increasingly considered, even if the activity depends on the whole secretome, made of both soluble proteins and extracellular vesicles. In this work, we prove for the first time the in vivo activity of the whole secretome formulated in a sponge-like alginate wound dressing to obtain the controlled release of bioactive substances. The product has been prepared in a public GMP-compliant facility by a scalable process; based on the murine model, treated wounds healed faster than controls without complications or infections. The treatment induced a higher acute inflammatory process in a short time and sustained the proliferative phase by accelerating fibroblast migration, granulation tissue formation, neovascularization and collagen deposition. The efficacy was substantially supported by the agreement between histological and proteomic findings. In addition to functional modules related to proteolysis, complement and coagulation cascades, protein folding and ECM remodeling, in treated skin, emerged the role of specific wound healing related proteins, including Tenascin (Tnc), Decorin (Dcn) and Epidermal growth factor receptor (EGFR). Of note, Decorin and Tenascin were also components of secretome, and network analysis suggests a potential role in regulating EGFR. Although further experiments will be necessary to characterize better the molecular keys induced by treatment, overall, our results confirm the whole secretome efficacy as novel "cell-free therapy". Also, sponge-like topical dressing containing the whole secretome, GMP- compliant and "ready-off-the-shelf", may represent a relevant point to facilitate its translation into the clinic.

Understanding the proteome encoded by "non-coding RNAs": new insights into human genome

A great number of non-coding RNAs (ncRNAs) account for the majority of the genome. The translation of these ncRNAs has been noted but seriously underestimated due to both technological and theoretical limitations. Based on the development of ribosome profiling (Ribo-seq), full length translating RNA analysis (RNC-seq) and mass spectrometry technology, more and more ncRNAs are being found to be translated in different organism, and some of them can produce functional peptides. While recently, not only individual new functional proteins, but also a new proteome have been experimentally discovered to be encoded by endogenous lncRNAs and circRNAs. These new proteins are of biological significance, suggesting the connection of the translation of ncRNAs to human physiology and diseases. Therefore, an in-depth and systematic understanding of the coding capabilities of ncRNAs is necessary for basic biology and medicine. In this review, we summarize the advances in the field of discovering this new proteome, i.e. "ncRNA-coded" proteins.

The neXtProt knowledgebase in 2020: data, tools and usability improvements

The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data on human protein and the tools to explore these. In order to provide comprehensive and up-to-date data, we evaluate and add new data sets. We describe the incorporation of three new data sets that provide expression, function, protein-protein binary interaction, post-translational modifications (PTM) and variant information. New SPARQL query examples illustrating uses of the new data were added. neXtProt has continued to develop tools for proteomics. We have improved the peptide uniqueness checker and have implemented a new protein digestion tool. Together, these tools make it possible to determine which proteases can be used to identify trypsin-resistant proteins by mass spectrometry. In terms of usability, we have finished revamping our web interface and completely rewritten our API. Our SPARQL endpoint now supports federated queries. All the neXtProt data are available via our user interface, API, SPARQL endpoint and FTP site, including the new PEFF 1.0 format files. Finally, the data on our FTP site is now CC BY 4.0 to promote its reuse.

The PRIDE database and related tools and resources in 2019: improving support for quantification data

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.

Evaluation of Aptamers as Affinity Reagents for an Enhancement of SRM-Based Detection of Low-Abundance Proteins in Blood Plasma

Selected reaction monitoring (SRM) is a mass spectrometric technique characterized by the exceptionally high selectivity and sensitivity of protein detection. However, even with this technique, the quantitative detection of low- and ultralow-abundance proteins in blood plasma, which is of great importance for the search and verification of novel protein disease markers, is a challenging task due to the immense dynamic range of protein abundance levels. One approach used to overcome this problem is the immunoaffinity enrichment of target proteins for SRM analysis, employing monoclonal antibodies. Aptamers appear as a promising alternative to antibodies for affinity enrichment. Here, using recombinant protein SMAD4 as a model target added at known concentrations to human blood plasma and SRM as a detection method, we investigated a relationship between the initial amount of the target protein and its amount in the fraction enriched with SMAD4 by an anti-SMAD4 DNA-aptamer immobilized on magnetic beads. It was found that the aptamer-based enrichment provided a 30-fold increase in the sensitivity of SRM detection of SMAD4. These results indicate that the aptamer-based affinity enrichment of target proteins can be successfully employed to improve quantitative detection of low-abundance proteins by SRM in undepleted human blood plasma.

Is It Possible to Find Needles in a Haystack? Meta-Analysis of 1000+ MS/MS Files Provided by the Russian Proteomic Consortium for Mining Missing Proteins

Despite direct or indirect efforts of the proteomic community, the fraction of blind spots on the protein map is still significant. Almost 11% of human genes encode missing proteins; the existence of which proteins is still in doubt. Apparently, proteomics has reached a stage when more attention and curiosity need to be exerted in the identification of every novel protein in order to expand the unusual types of biomaterials and/or conditions. It seems that we have exhausted the current conventional approaches to the discovery of missing proteins and may need to investigate alternatives. Here, we present an approach to deciphering missing proteins based on the use of non-standard methodological solutions and encompassing diverse MS/MS data, obtained for rare types of biological samples by members of the Russian Proteomic community in the last five years. These data were re-analyzed in a uniform manner by three search engines, which are part of the SearchGUI package. The study resulted in the identification of two missing and five uncertain proteins detected with two peptides. Moreover, 149 proteins were detected with a single proteotypic peptide. Finally, we analyzed the gene expression levels to suggest feasible targets for further validation of missing and uncertain protein observations, which will fully meet the requirements of the international consortium. The MS data are available on the ProteomeXchange platform (PXD014300).

Ependymoma Pediatric Brain Tumor Protein Fingerprinting by Integrated Mass Spectrometry Platforms: A Pilot Investigation

Ependymoma pediatric brain tumor occurs at approximate frequencies of 10-15% in supratentorial and 20-30% in posterior fossa regions. These tumors have an almost selective response to surgery and relative and confirmed resistance to radiotherapy and chemotherapic agents, respectively. Alongside histopathological grading, clinical and treatment evaluation of ependymomas currently consider the tumor localization and the genomic outlined associated molecular subgroups, with the supratentorial and the posterior fossa ependymomas nowadays considered diverse diseases. On these grounds and in trying to better understand the molecular features of these tumors, the present investigation aimed to originally investigate the proteomic profile of pediatric ependymoma tissues of different grade and localization by mass spectrometry platforms to disclose potential distinct protein phenotypes. To this purpose, acid-soluble and acid-insoluble fractions of ependymoma tumor tissues homogenates were analyzed by LC-MS following both the top-down and the shotgun proteomic approaches, respectively, to either investigate the intact proteome or its digested form. The two approaches were complementary in profiling the ependymoma tumor tissues and showed distinguished profiles for supratentorial and posterior fossa ependymomas and for WHO II and III tumor grades. Top-down proteomic analysis revealed statistically significant higher levels of thymosin beta 4, 10 kDa heat shock protein, non-histone chromosomal protein HMG-17, and mono-/uncitrullinated forms ratio of the glial fibrillary acidic protein (GFAP) fragment 388-432 in supratentorial ependymomas-the same GFAP fragment as well as the hemoglobin alpha- and the beta-chain marked grade II with respect to grade III posterior fossa ependymomas. Gene ontology classification of shotgun data of the identified cancer and the non-cancer related proteins disclosed protein elements exclusively marking tumor localization and pathways that were selectively overrepresented. These results, although preliminary, seem consistent with different protein profiles of ependymomas of diverse grade of aggressiveness and brain region development and contributed to enlarging the molecular knowledge of this still enigmatic tumor.

Identification of ALDH6A1 as a Potential Molecular Signature in Hepatocellular Carcinoma via Quantitative Profiling of the Mitochondrial Proteome

Various liver diseases, including hepatocellular carcinoma (HCC), have been linked to mitochondrial dysfunction, reduction of reactive oxygen species (ROS), and elevation of nitric oxide (NO). In this study, we subjected the human liver mitochondrial proteome to extensive quantitative proteomic profiling analysis and molecular characterization to identify potential signatures indicative of cancer cell growth and progression. Sequential proteomic analysis identified 2452 mitochondrial proteins, of which 1464 and 2010 were classified as nontumor and tumor (HCC) mitochondrial proteins, respectively, with 1022 overlaps. Further metabolic mapping of the HCC mitochondrial proteins narrowed our biological characterization to four proteins, namely, ALDH4A1, LRPPRC, ATP5C1, and ALDH6A1. The latter protein, a mitochondrial methylmalonate semialdehyde dehydrogenase (ALDH6A1), was most strongly suppressed in HCC tumor regions (∼10-fold decrease) in contrast to LRPPRC (∼6-fold increase) and was predicted to be present in plasma. Accordingly, we selected ALDH6A1 for functional analysis and engineered Hep3B cells to overexpress this protein, called ALDH6A1-O/E cells. Since ALDH6A1 is predicted to be involved in mitochondrial respiration, we assessed changes in the levels of NO and ROS in the overexpressed cell lines. Surprisingly, in ALDH6A1-O/E cells, NO was decreased nearly 50% but ROS was increased at a similar level, while the former was restored by treatment with S-nitroso-N-acetyl-penicillamine. The lactate levels were also decreased relative to control cells. Propidium iodide and Rhodamine-123 staining suggested that the decrease in NO and increase in ROS in ALDH6A1-O/E cells could be caused by depolarization of the mitochondrial membrane potential (ΔΨ). Taken together, our results suggest that hepatic neoplastic transformation appears to suppress the expression of ALDH6A1, which is accompanied by a respective increase and decrease in NO and ROS in cancer cells. Given the close link between ALDH6A1 suppression and abnormal cancer cell growth, this protein may serve as a potential molecular signature or biomarker of hepatocarcinogenesis and treatment responses.

The ProteomeXchange consortium in 2020: enabling 'big data' approaches in proteomics

The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) has standardized data submission and dissemination of mass spectrometry proteomics data worldwide since 2012. In this paper, we describe the main developments since the previous update manuscript was published in Nucleic Acids Research in 2017. Since then, in addition to the four PX existing members at the time (PRIDE, PeptideAtlas including the PASSEL resource, MassIVE and jPOST), two new resources have joined PX: iProX (China) and Panorama Public (USA). We first describe the updated submission guidelines, now expanded to include six members. Next, with current data submission statistics, we demonstrate that the proteomics field is now actively embracing public open data policies. At the end of June 2019, more than 14 100 datasets had been submitted to PX resources since 2012, and from those, more than 9 500 in just the last three years. In parallel, an unprecedented increase of data re-use activities in the field, including 'big data' approaches, is enabling novel research and new data resources. At last, we also outline some of our future plans for the coming years.

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.

Proteomics: a powerful tool to study plant responses to biotic stress

In recent years, mass spectrometry-based proteomics has provided scientists with the tremendous capability to study plants more precisely than previously possible. Currently, proteomics has been transformed from an isolated field into a comprehensive tool for biological research that can be used to explain biological functions. Several studies have successfully used the power of proteomics as a discovery tool to uncover plant resistance mechanisms. There is growing evidence that indicates that the spatial proteome and post-translational modifications (PTMs) of proteins directly participate in the plant immune response. Therefore, understanding the subcellular localization and PTMs of proteins is crucial for a comprehensive understanding of plant responses to biotic stress. In this review, we discuss current approaches to plant proteomics that use mass spectrometry, with particular emphasis on the application of spatial proteomics and PTMs. The purpose of this paper is to investigate the current status of the field, discuss recent research challenges, and encourage the application of proteomics techniques to further research.

Alternative Strategy To Explore Missing Proteins with Low Molecular Weight

Identifying more missing proteins (MPs) is an important mission of C-HPP. With the number of identified MPs being attenuated year by year (2,949 to 2,129 MPs from 2016 to 2019), we have realized that the difficulty of exploring the remaining MPs is a challenge in technique. Herein, we propose a comprehensive strategy to effectively enrich, separate, and identify proteins with low molecular weights, aiming at the discovery of MPs. Basically, a protein extract from human placenta was passed through a C18 SPE column, and the bound proteins that were eluted were further separated with an SDS-PAGE gel or a 50 kDa cutoff filter. The separated proteins were subjected to trypsin digestion, and the MS/MS signals were searched against data sets with two different digestion modes (full-trypsin and semitrypsin). The strategy was adopted, resulting in the identification of 4 MPs with 8 unique peptides (≥2 non-nested unique peptides with ≥9 amino acids). Importantly, the identification of 6 out of 8 of the unique peptides derived from the MPs was further supported by parallel reaction monitoring, which confirmed the identification of 3 MPs from human placenta tissues (Q6NT89: TMF-regulated nuclear protein 1; A0A183: late cornified envelope protein 6A; and Q6UWQ7: insulin growth factor-like family member 2, mapped to chromosomes 1, 1, and 19, respectively). The three proteins ranged in length from 80 aa to 227 aa. The study not only establishes a feasible strategy for analyzing proteins with low molecular weights but also fills a small part of a large gap in the list of MPs. The data obtained in this study are available via ProteomeXchange (PXD014083) and PeptideAtlas (PASS01389).