UniProt and Mass Spectrometry-Based Proteomics-A 2-Way Working Relationship

Proteomics and metabolomics elucidate the biosynthetic pathway of acid stress-induced exopolysaccharides and its impact on growth phenotypes in Lactiplantibacillus plantarum HMX2

Lactiplantibacillus plantarum has been well acknowledged to produce exopolysaccharides (EPS) as a defense mechanism against acid stress. However, the complete biosynthetic pathway of EPS in L. plantarum and its impact on the cell growth and primary metabolism were still unclear. To fill these gaps, we carried out phenotypic, proteomic and metabolomics analysis of L. plantarum HMX2 cultured under different acidic conditions. Component and structure analysis showed that the repeating unit of EPS consisted of N-acetylmannosamine, N-acetylglucosamine, galactose, mannoses and glucoses. Multiomics analysis facilitated the curation and entablement of the complete EPS biosynthetic pathway ready for use in genome-scale metabolic models. Furthermore, proteomics and metabolomics data indicated that compared to the pH 6.5 condition, the acid stress at pH 4.5 significantly accelerated glycolysis and EPS biosynthesis processes while reduced the metabolic fluxes through the TCA cycle and the lactic acid fermentation, which suggested a trade-off between primary and secondary metabolism.

A modular, Galaxy-based immunopeptidogenomic (iPepGen) analysis pipeline for discovery, verification, and prioritization of candidate cancer neoantigen peptides

Background

Characterizing peptide antigens, processed from tumor-specific proteoforms, and bound to the major histocompatibility complex, is critical for immuno-oncology research. Next-generation sequencing predicts candidate neoantigen peptides derived from DNA mutations and/or RNA transcripts coding proteoform sequences that differ from the reference proteome. Mass spectrometry (MS)-based immunopeptidomics identifies predicted, MHC-bound neoantigen peptides and other tumor antigens. This "immunopeptidogenomic" approach requires multi-omic software integration, challenging researchers with limited bioinformatics expertise and resources. As a solution, we developed the immunopeptidogenomic (iPepGen) pipeline in the Galaxy ecosystem. iPepGen is composed of five core workflow modules, available via publicly accessible, scalable Galaxy instances, accompanied by training resources to empower community adoption.

Findings

Using representative multi-omic data from malignant peripheral nerve sheath tumors, we demonstrate the operation of iPepGen modules with these functions: 1) Predict neoantigen candidates from sequencing data and generate customized protein sequence databases, including reference and non-reference neoantigen candidate sequences; 2) Discover neoantigen peptide candidates by sequence database searching of tandem mass spectrometry (MS/MS) immunopeptidomics data; 3) Verify discovered peptide candidates through a secondary peptide-centric evaluation method against the MS/MS dataset; 4) Visualize and classify the nature of verified neoantigen peptides encoded by the genome and/or transcriptome; 5) Prioritize neoantigens for further exploration and empirical validation.

Conclusions

We demonstrate the effectiveness of the iPepGen pipeline for candidate neoantigen discovery and characterization. With tools, workflows, and training resources available in the open Galaxy ecosystem, iPepGen should provide cancer researchers with a flexible and accessible informatics resource tailored to accelerating immuno-oncology studies.

The Molecular Mechanisms of Bergapten Against Abdominal Aortic Aneurysm: Evidence From Network Pharmacology, Molecular Docking/Dynamics, and Experimental Validation

This study endeavors to assess the potential protective role of bergapten (BP) in mitigating abdominal aortic aneurysm (AAA) and to decipher the underlying mechanisms and molecular targets. Network pharmacology was utilized to search for potential targets of BP against AAA. Molecular docking and molecular dynamics simulations were utilized to validate the interaction of BP with core targets, and then the therapeutic effect and mechanism of BP on AAA were verified by using an elastase-induced AAA model. Network pharmacology analysis identified five pharmacological targets for BP, including EGFR, SRC, PIK3CA, PIK3CB, and JAK2. Molecular docking and molecular dynamics simulations further prioritized JAK2 as the most promising candidate for the potential treatment of AAA. The results of animal experiments demonstrated that BP significantly reduced the expression of inflammatory cytokines IL-6, TNF-α, and IL-1β in the aortic tissue of AAA mouse model, and inhibited the phosphorylation of JAK2 and STAT3. BP plays an important role in the treatment of AAA, and it may become a promising drug to combat AAA progression. The inhibitory effect of BP on AAA vascular progression and the attenuation of inflammatory cell infiltration may be related to the regulation of JAK2/STAT3 signaling pathway.

Designing a multi-epitope vaccine against Pseudomonas aeruginosa via integrating reverse vaccinology with immunoinformatics approaches

Pseudomonas aeruginosa is a typically opportunistic pathogen responsible for a wide range of nosocomial infections. In this study, we designed two multi-epitope vaccines targeting P. aeruginosa proteins, incorporating cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and linear B lymphocyte (LBL) epitopes identified using reverse vaccinology and immunoinformatics approaches. The vaccines exhibited favorable physicochemical properties, including stability, solubility, and optimal molecular weight, suggesting their potential as viable candidates for vaccine development. Molecular docking studies revealed strong binding affinity to Toll-like receptors 1 (TLR1) and 2 (TLR2). Furthermore, molecular dynamics simulations confirmed the stability of the vaccine-TLR complexes over time. Immune simulation analyses indicated that the vaccines could induce robust humoral and cellular immune responses, providing a promising new approach for combating P. aeruginosa infections, particularly in the face of increasing antibiotic resistance.

Highly expressed GCN1 is associated with cancer progression and poor prognosis in hepatocellular carcinoma patients

BACKGROUND

General control non-derepressible protein 1 (GCN1), a ribosome-binding protein, has been implicated in the development and progression of multiple cancers. However, the potential role of GCN1 in hepatocellular carcinoma (HCC) has not yet been investigated.

METHODS

The expression of GCN1 in HCC was analyzed using multiple databases. Bioinformatics analysis was employed to investigate the correlation of GCN1 expression with clinical significance and immune infiltration in HCC. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, gene set enrichment analysis (GSEA), and in vitro experiments were conducted to study the function and potential mechanisms of GCN1 in HCC.

RESULTS

GCN1 was significantly upregulated in HCC, which was associated with worse clinicopathological features and poorer prognosis of the patients. GCN1 expression was closely associated with immune cell infiltration in HCC. GSEA analysis showed that GCN1 was involved in several tumor-related signaling pathways, including cell cycle, DNA replication, and Wnt signaling pathway. Knockdown of GCN1 inhibited the proliferation, invasion and migration of HCC cells, and also down-regulated the expression levels of cell cycle protein cyclin B1 (CCNB1), cyclin D1 (CCND1), and Wnt signaling pathway-related proteins Wnt3A and β-catenin.

CONCLUSION

GCN1 overexpression was associated with HCC progression and poor prognosis, and GCN1 knockdown could suppress the proliferation, migration and invasion ability of HCC cells by regulating Wnt signaling pathway, suggesting the potential of GCN1 as a prognostic and therapeutic target for HCC.

The hepatocellular model of fatty liver disease: from current imaging diagnostics to innovative proteomics technologies

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a prevalent chronic liver condition characterized by lipid accumulation and inflammation, often progressing to severe liver damage. We aim to review the pathophysiology, diagnostics, and clinical care of MASLD, and review highlights of advances in proteomic technologies. Recent advances in proteomics technologies have improved the identification of novel biomarkers and therapeutic targets, offering insight into the molecular mechanisms underlying MASLD progression. We focus on the application of mass spectrometry-based proteomics including single cell proteomics, proteogenomics, extracellular vesicle (EV-omics), and exposomics for biomarker discovery, emphasizing the potential of blood-based panels for noninvasive diagnosis and personalized medicine. Future research directions are presented to develop targeted therapies and improve clinical outcomes for MASLD patients.

What have Data Standards ever done for us?

The Human Proteome Organization (HUPO) Proteomics Standards Initiative (PSI) has been successfully developing guidelines, data formats, and controlled vocabularies for both the field of molecular interaction and that of mass spectrometry for more than 20 years. This review explores some of the ways that the proteomics community has benefitted from the development of community standards and takes a look at some of the tools and resources that have been improved or developed as a result of the work of the HUPO-PSI.

Melatonin protects retinal pigment epithelium cells against ferroptosis in AMD via the PI3K/AKT/MDM2/P53 pathway

Introduction

Oxidative stress-prompted degeneration of the retinal pigment epithelium (RPE) notably contributes to the onset of age-related macular degeneration (AMD). However, the pathways leading to RPE deterioration and possible preventative strategies are not yet completely comprehended.

Methods

Ferroptosis was assayed through the evaluation of lipid peroxidation (C11-BODIPY and MDA), reactive oxygen species (ROS), transmission electron microscopy (TEM), iron content measurement, q-PCR, western blotting, and immunofluorescence. To assess the structure and retinal function of RPE in mice, ERG (electroretinography), OCT (optical coherence tomography), and H&E (hematoxylin and eosin) staining were employed. Network pharmacology methods were utilized to elucidate the potential mechanisms underlying melatonin's protective effects against ferroptosis in RPE cells in AMD. Genetic engineering techniques were applied to investigate the regulatory relationships among phosphatidylinositol 3-kinase (PI3K), protein kinase-B (AKT), murine double minute-2 (MDM2), protein 53 (P53), and solute carrier family 7 member 11 (SLC7A11). In vitro knockdown experiments of MDM2 were conducted to explore its regulatory role in ferroptosis within RPE cells.

Results

Aβ1-40 can trigger ferroptosis in RPE cells. Melatonin can inhibit the oxidative stress and ferroptosis induced by Aβ1-40 in RPE cells. Melatonin exhibits a protective effect on Aβ1-40-induced AMD, significantly improving the structure of the mouse retina and RPE layer, and facilitating the restoration of visual function. Network pharmacology methods revealed that the potential targets of melatonin in AMD are closely related to ferroptosis, and indicated that the predominant pathways are significantly associated with the PI3K/AKT/MDM2/P53 signaling pathway. Knocking down the specific expression of MDM2 can significantly weaken the inhibitory effect of melatonin on oxidative stress and ferroptosis.

Discussion

Melatonin can suppress cell death by ferroptosis in RPE via the PI3K/AKT/MDM2/P53 pathway, thereby preventing and decelerating the progression of AMD.

Construction of human pluripotent stem cell-derived testicular organoids and their use as humanized testis models for evaluating the effects of semaglutide

Background: The generation of human testicular organoids from human induced pluripotent stem cells (hiPSCs) presents exciting opportunities for gonadal developmental biology, and reproductive disease modeling. However, creating organoids that closely mimic the tissue structure of testes remains challenging. Methods: In this study, we established a method for generating testicular organoids (TOs) from hiPSCs using a stepwise differentiation approach and a combination of hanging drop and rotational culture systems. The capability of hiPSC-derived precursor testicular cells to self-assemble into organoids was confirmed by detection of morphology, single-cell RNA-sequencing, and protein profiles. The reliability of testicular organoids as a drug evaluation model was assessed by the measurements of transcriptome signatures and functional features, including hormone responsiveness and blood-testis barrier (BTB) formation, and drug sensitivity assessment by recording cell viability and BTB integrity in organoids exposed to reproductive toxicants. Finally, we applied testicular organoids to evaluate the effects of semaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1 RA), on testicular function, thereby underscoring their utility as a model for drug evaluation. Results: These organoids exhibited testicular cord-like structures and BTB function. RNA sequencing and functional assays confirmed that testicular organoids possess gene expression profiles and endocrine functions regulated by gonadotropins, closely resembling those of testicular tissue. Notably, these organoids displayed sensitivity to semaglutide. Treatment with semaglutide resulted in reduced testosterone levels and downregulation of INHBB expression, aligning with previous clinical observations. Conclusions: These findings introduced a method for generating testicular organoids from human pluripotent stem cells, highlighting their potential as valuable models for studying testicular function, drug toxicity, and the effects of compounds like semaglutide on testicular health.

The UniProt Consortium, Bateman A, Martin MJ, Orchard S, Magrane M, Adesina A, Ahmad S, Bowler-Barnett EH, Bye-A-Jee H, Carpentier D, Denny P, Fan J, Garmiri P, Gonzales LJDC, Hussein A, Ignatchenko A, Insana G, Ishtiaq R, Joshi V, Jyothi D, Kandasaamy S, Lock A, Luciani A, Luo J, Lussi Y, Marin JSM, Raposo P, Rice DL, Santos R, Speretta E, Stephenson J, Totoo P, Tyagi N, Urakova N, Vasudev P, Warner K, Wijerathne S, Yu CWH, Zaru R, Bridge AJ, Aimo L, Argoud-Puy G, Auchincloss AH, Axelsen KB, Bansal P, Baratin D, Batista Neto TM, Blatter MC, Bolleman JT, Boutet E, Breuza L, Gil BC, Casals-Casas C, Echioukh KC, Coudert E, Cuche B, de Castro E, Estreicher A, Famiglietti ML, Feuermann M, Gasteiger E, Gaudet P, Gehant S, Gerritsen V, Gos A, Gruaz N, Hulo C, Hyka-Nouspikel N, Jungo F, Kerhornou A, Mercier PL, Lieberherr D, Masson P, Morgat A, Paesano S, Pedruzzi I, Pilbout S, Pourcel L, Poux S, Pozzato M, Pruess M, Redaschi N, Rivoire C, Sigrist CJA, Sonesson K, Sundaram S, Sveshnikova A, Wu CH, Arighi CN, Chen C, Chen Y, Huang H, Laiho K, Lehvaslaiho M, McGarvey P, Natale DA, Ross K, Vinayaka CR, Wang Y, Zhang J. UniProt: the Universal Protein Knowledgebase in 2025

The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe ongoing changes to our production pipeline to limit the sequences available in UniProtKB to high-quality, non-redundant reference proteomes. We continue to manually curate the scientific literature to add the latest functional data and use machine learning techniques. We also encourage community curation to ensure key publications are not missed. We provide an update on the automatic annotation methods used by UniProtKB to predict information for unreviewed entries describing unstudied proteins. Finally, updates to the UniProt website are described, including a new tab linking protein to genomic information. In recognition of its value to the scientific community, the UniProt database has been awarded Global Core Biodata Resource status.

Insights on Wet and Dry Workflows for Human Gut Metaproteomics

The human gut microbiota (GM) is a community of microorganisms that resides in the gastrointestinal (GI) tract. Recognized as a critical element of human health, the functions of the GM extend beyond GI well-being to influence overall systemic health and susceptibility to disease. Among the other omic sciences, metaproteomics highlights additional facets that make it a highly valuable discipline in the study of GM. Indeed, it allows the protein inventory of complex microbial communities. Proteins with associated taxonomic membership and function are identified and quantified from their constituent peptides by liquid chromatography coupled to mass spectrometry analyses and by querying specific databases (DBs). The aim of this review was to compile comprehensive information on metaproteomic studies of the human GM, with a focus on the bacterial component, to assist newcomers in understanding the methods and types of research conducted in this field. The review outlines key steps in a metaproteomic-based study, such as protein extraction, DB selection, and bioinformatic workflow. The importance of standardization is emphasized. In addition, a list of previously published studies is provided as hints for researchers interested in investigating the role of GM in health and disease states.

Potential candidates from a functional food Zanthoxyli Pericarpium (Sichuan pepper) for the management of hyperuricemia: high-through virtual screening, network pharmacology and dynamics simulations

Introduction

Hyperuricemia (HUA) is a metabolic syndrome caused by purine metabolism disorders. Zanthoxyli Pericarpium (ZP) is a medicinal and food homologous plant, and its ripe peel is used to treat diseases and as a spice for cooking. Some studies have shown that ZP can inhibit the formation of xanthine oxidase and reduce the production of uric acid.

Methods

Through network pharmacology, ZP's potential targets and mechanisms for HUA treatment were identified. Databases like TCMSP, UniProt, and Swiss Target Prediction were utilized for ZP's active ingredients and targets. HUA-related targets were filtered using GeneCards, Drugbank, and Open Targets. Core targets for ZP's HUA treatment were mapped in a PPI network and analyzed with Cytoscape. GO and KEGG pathway enrichments were conducted on intersected targets via DAVID. Molecular docking and virtual screening were performed to find optimal binding pockets, and ADMET screening assessed compound safety. Molecular dynamics simulations confirmed compound stability in binding sites.

Results

We identified 81 ZP active ingredient targets, 140 HUA-related targets, and 6 drug targets, with xanthine dehydrogenase (XDH) as the top core target. Molecular docking revealed ZP's active ingredients had strong binding to XDH. Virtual screening via Protein plus identified 48 compounds near the optimal binding pocket, with 2'-methylacetophenone, ledol, beta-sitosterol, and ethyl geranate as the most promising. Molecular dynamics simulations confirmed binding stability, suggesting ZP's potential in HUA prevention and the need for further experimental validation.

Conclusion

Our study provides foundations for exploring the mechanism of the lowering of uric acid by ZP and developing new products of ZP. The role of ZP in the diet may provide a new dietary strategy for the prevention of HUA, and more experimental studies are needed to confirm our results in the future.

Construction of Protein Sequence Databases for Metaproteomics: A Review of the Current Tools and Databases

In metaproteomics studies, constructing a reference protein sequence database that is both comprehensive and not overly large is critical for the peptide identification step. Therefore, the availability of well-curated reference databases and tools for custom database construction is essential to enhance the performance of metaproteomics analyses. In this review, we first provide an overview of metaproteomics by presenting a concise historical background, outlining a typical experimental and bioinformatics workflow, emphasizing the crucial step of constructing a protein sequence database for metaproteomics. We then delve into the current tools available for building such databases, highlighting their individual approaches, utility, and advantages and limitations. Next, we examine existing protein sequence databases, detailing their scope and relevance in metaproteomics research. Then, we provide practical recommendations for constructing protein sequence databases for metaproteomics, along with an overview of the current challenges in this area. We conclude with a discussion of anticipated advancements, emerging trends, and future directions in the construction of protein sequence databases for metaproteomics.

Novel dual-pathogen multi-epitope mRNA vaccine development for Brucella melitensis and Mycobacterium tuberculosis in silico approach

Brucellosis and Tuberculosis, both of which are contagious diseases, have presented significant challenges to global public health security in recent years. Delayed treatment can exacerbate the conditions, jeopardizing patient lives. Currently, no vaccine has been approved to prevent these two diseases simultaneously. In contrast to traditional vaccines, mRNA vaccines offer advantages such as high efficacy, rapid development, and low cost, and their applications are gradually expanding. This study aims to develop multi-epitope mRNA vaccines argeting Brucella melitensis and Mycobacterium tuberculosis H37Rv (L4 strain) utilizing immunoinformatics approaches. The proteins Omp25, Omp31, MPT70, and MPT83 from the specified bacteria were selected to identify the predominant T- and B-cell epitopes for immunological analysis. Following a comprehensive evaluation, a vaccine was developed using helper T lymphocyte epitopes, cytotoxic T lymphocyte epitopes, linear B-cell epitopes, and conformational B-cell epitopes. It has been demonstrated that multi-epitope mRNA vaccines exhibit increased antigenicity, non-allergenicity, solubility, and high stability. The findings from molecular docking and molecular dynamics simulation revealed a robust and enduring binding affinity between multi-epitope peptides mRNA vaccines and TLR4. Ultimately, Subsequently, following the optimization of the nucleotide sequence, the codon adaptation index was calculated to be 1.0, along with an average GC content of 54.01%. This indicates that the multi-epitope mRNA vaccines exhibit potential for efficient expression within the Escherichia coli(E. coli) host. Analysis through immune modeling indicates that following administration of the vaccine, there may be variation in immunecell populations associated with both innate and adaptive immune reactions. These types encompass helper T lymphocytes (HTL), cytotoxic T lymphocytes (CTL), regulatory T lymphocytes, natural killer cells, dendritic cells and various immune cell subsets. In summary, the results suggest that the newly created multi-epitope mRNA vaccine exhibits favorable attributes, offering novel insights and a conceptual foundation for potential progress in vaccine development.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Design of Cryptococcus neoformans multi-epitope vaccine based on immunoinformatics method

Cryptococcus neoformans is a widely distributed opportunistic pathogenic fungus. While C. neoformans commonly infects immunocompromised individuals, it can also affect those who are immunocompetent. Transmission of C. neoformans primarily occurs through the respiratory tract, leading to the development of meningitis. The mortality rate of Cryptococcal meningitis is high, and treatment options are limited. Cryptococcus neoformans infections pose a significant public health threat and currently lack targeted and effective response strategies. This study aimed to screen T lymphocyte (cytotoxic T lymphocyte and helper T lymphocyte) and B lymphocyte epitopes derived from four C. neoformans antigens and develop two multi-epitope vaccines by combining them with various adjuvants. Molecular docking results demonstrated that the vaccines bind stably to Toll-like receptor 4 ( and induce innate immunity. The credibility of the molecular docking results was validated through subsequent molecular dynamics simulations. Furthermore, the results of immune simulation analyses underscored the multi-epitope vaccine's capability to effectively induce robust humoral and cellular immune responses within the host organism. These two vaccines have demonstrated theoretical efficacy against C. neoformans infection as indicated by computer analysis. Nevertheless, additional experimental validation is essential to substantiate the protective efficacy of the vaccines.

Exploring the multifaceted role of GCN1: Implications in cellular responses and disease pathogenesis

GCN1 is a highly conserved protein present widely across eukaryotes. As an upstream activator of protein kinase GCN2, GCN1 plays a pivotal role in integrated stress responses, such as amino acid starvation and oxidative stress. Through interaction with GCN2, GCN1 facilitates the activation of GCN2, thus initiating downstream signaling cascades in response to cellular stressors. In these contexts, the activation of GCN2 necessitates the presence and action of GCN1. Notably, GCN1 also operates as a ribosome collision sensor, contributing significantly to the translation quality control pathway. These discoveries offer valuable insights into cellular responses to internal stresses, vital for maintaining cellular homeostasis. Additionally, GCN1 exhibits the ability to regulate the cell cycle and suppress inflammation, among other processes, independently of GCN2. Our review outlines the structural characteristics and biological functions of GCN1, shedding light on its significant involvement in the onset and progression of various cancer and non-cancer diseases. Our work underscores the role of GCN1 in the context of drug therapeutic effects, hinting at its potential as a promising drug target. Furthermore, our work delves deep into the functional mechanisms of GCN1, promising innovative avenues for the diagnosis and treatment of diseases in the future. The exploration of GCN1's multifaceted roles not only enhances our understanding of its mechanisms but also paves the way for novel therapeutic interventions. The ongoing quest to unveil additional functions of GCN1 holds the promise of further enriching our comprehension of its mode of action.

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.