Proteomic and N-Terminomic TAILS Analyses of Human Alveolar Bone Proteins: Improved Protein Extraction Methodology and LysargiNase Digestion Strategies Increase Proteome Coverage and Missing Protein Identification

Mass Spectrometry-Based Proteomics of Poly(methylmethacrylate)-Embedded Bone

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely employed technique in proteomics research for studying the proteome biology of various clinical samples. Hard tissues, such as bone and teeth, are routinely preserved using synthetic poly(methyl methacrylate) (PMMA) embedding resins that enable histological, immunohistochemical, and morphological examination. However, the suitability of PMMA-embedded hard tissues for large-scale proteomic analysis remained unexplored. This study is the first to report on the feasibility of PMMA-embedded bone samples for LC-MS/MS analysis. Conventional workflows yielded merely limited coverage of the bone proteome. Using advanced strategies of prefractionation by high-pH reversed-phase liquid chromatography in combination with isobaric tandem mass tag labeling resulted in proteome coverage exceeding 1000 protein identifications. The quantitative comparison with cryopreserved samples revealed that each sample preparation workflow had a distinct impact on the proteomic profile. However, workflow replicates exhibited a high reproducibility for PMMA-embedded samples. Our findings further demonstrate that decalcification prior to protein extraction, along with the analysis of solubilization fractions, is not preferred for PMMA-embedded bone. The biological applicability of the proposed workflow was demonstrated using samples of human PMMA-embedded alveolar bone and the iliac crest, which revealed anatomical site-specific proteomic profiles. Overall, these results establish a crucial foundation for large-scale proteomics studies contributing to our knowledge of bone biology.

Mass spectrometry-based proteomic applications in dental implants research

Dental implants have been established as successful treatment options for missing teeth with steadily increasing demands. Today, the primary areas of research in dental implantology revolve around osseointegration, soft and hard tissue grafting as well as peri-implantitis diagnostics, prevention, and treatment. This review provides a comprehensive overview of the current literature on the application of MS-based proteomics in dental implant research, highlights how explorative proteomics provided insights into the biology of peri-implant soft and hard tissues and how proteomics facilitated the stratification between healthy and diseased implants, enabling the identification of potential new diagnostic markers. Additionally, this review illuminates technical aspects, and provides recommendations for future study designs based on the current evidence.

Digging deeper into ancient skeletal proteomes through consecutive digestion with multiple proteases

An increasing number of studies utilise the recovery of ancient skeletal proteomes for phylogenetic and evolutionary analysis. Although these studies manage to extract and analyse ancient peptides, the recovered proteomes are generally small in size and with low protein sequence coverage. We expand on previous observations which have shown that the parallel digestion and analysis of Pleistocene skeletal proteomes increases overall proteome size and protein sequence coverage. Furthermore, we demonstrate that the consecutive digestion of a skeletal proteome using two proteases, particularly the combination of Glu-C or chymotrypsin followed by trypsin digestion, enables the recovery of alternative proteome components not reachable through trypsin digestion alone. The proteomes preserved in Pleistocene skeletal specimens are larger than previously anticipated, but unlocking this protein sequence information requires adaptation of extraction and protein digestion protocols. The sequential utilisation of several proteases is, in this regard, a promising avenue for the study of highly degraded but unique hominin proteomes for phylogenetic purposes. SIGNIFICANCE: Palaeoproteomic analysis of archaeological materials, such as hominin skeletal elements, show great promise in studying past organisms and evolutionary relationships. However, as most proteomic methods are inherently destructive, it is essential to aim to recover as much information as possible from every sample. Currently, digestion with trypsin is the standard approach in most palaeoproteomic studies. We find that parallel or consecutive digestion with multiple proteases can improve proteome size and coverage for both Holocene and Pleistocene bone specimens. This allows for recovery of more proteomic data from a sample and maximises the chance of recovering phylogenetically relevant information.

Deep coverage and quantification of the bone proteome provides enhanced opportunities for new discoveries in skeletal biology and disease

Dysregulation of cell signaling in chondrocytes and in bone cells, such as osteocytes, osteoblasts, osteoclasts, and an elevated burden of senescent cells in cartilage and bone, are implicated in osteoarthritis (OA). Mass spectrometric analyses provides a crucial molecular tool-kit to understand complex signaling relationships in age-related diseases, such as OA. Here we introduce a novel mass spectrometric workflow to promote proteomic studies of bone. This workflow uses highly specialized steps, including extensive overnight demineralization, pulverization, and incubation for 72 h in 6 M guanidine hydrochloride and EDTA, followed by proteolytic digestion. Analysis on a high-resolution Orbitrap Eclipse and Orbitrap Exploris 480 mass spectrometer using Data-Independent Acquisition (DIA) provides deep coverage of the bone proteome, and preserves post-translational modifications, such as hydroxyproline. A spectral library-free quantification strategy, directDIA, identified and quantified over 2,000 protein groups (with ≥ 2 unique peptides) from calcium-rich bone matrices. Key components identified were proteins of the extracellular matrix (ECM), bone-specific proteins (e.g., secreted protein acidic and cysteine rich, SPARC, and bone sialoprotein 2, IBSP), and signaling proteins (e.g., transforming growth factor beta-2, TGFB2), and lysyl oxidase homolog 2 (LOXL2), an important protein in collagen crosslinking. Post-translational modifications (PTMs) were identified without the need for specific enrichment. This includes collagen hydroxyproline modifications, chemical modifications for collagen self-assembly and network formation. Multiple senescence factors were identified, such as complement component 3 (C3) protein of the complement system and many matrix metalloproteinases, that might be monitored during age-related bone disease progression. Our innovative workflow yields in-depth protein coverage and quantification strategies to discover underlying biological mechanisms of bone aging and to provide tools to monitor therapeutic interventions. These novel tools to monitor the bone proteome open novel horizons to investigate bone-specific diseases, many of which are age-related.

In-Depth Characterization of Apoptosis N-terminome Reveals a Link Between Caspase-3 Cleavage and Post-Translational N-terminal Acetylation

The N-termini of proteins contain information about their biochemical properties and functions. These N-termini can be processed by proteases, and can undergo other co- or post-translational modifications. We have developed LATE (LysN Amino Terminal Enrichment), a method that uses selective chemical derivatization of α-amines to isolate the N-terminal peptides, in order to improve N-terminome identification in conjunction with other enrichment strategies. We applied LATE alongside another N-terminomic method to study caspase-3 mediated proteolysis both in vitro and during apoptosis in cells. This has enabled us to identify many unreported caspase-3 cleavages, some of which cannot be identified by other methods. Moreover, we have found direct evidence that neo-N-termini generated by caspase-3 cleavage can be further modified by Nt-acetylation. Some of these neo-Nt-acetylation events occur in the early phase of the apoptotic process and may have a role in translation inhibition. This has provided a comprehensive overview of the caspase-3 degradome and has uncovered previously unrecognized crosstalk between post-translational Nt-acetylation and caspase proteolytic pathways.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Molecular and Cellular Crosstalk between Bone and Brain: Accessing Bidirectional Neural and Musculoskeletal Signaling during Aging and Disease

Molecular omics technologies, including proteomics, have enabled the elucidation of key signaling pathways that mediate bidirectional communication between the brain and bone tissues. Here we provide a brief summary of the clinical and molecular evidence of the need to study the bone-brain axis of cross-tissue cellular communication. Clear clinical and molecular evidence suggests biological interactions and similarities between bone and brain cells. Here we review the current mass spectrometric techniques for studying brain and bone diseases with an emphasis on neurodegenerative diseases and osteoarthritis/osteoporosis, respectively. Further study of the bone-brain axis on a molecular level and evaluation of the role of proteins, neuropeptides, osteokines, and hormones in molecular pathways linked to bone and brain diseases is critically needed. The use of mass spectrometry and other omics technologies to analyze these cross-tissue signaling events and interactions will help us better understand disease progression and comorbidities and potentially identify new pathways and targets for therapeutic interventions. Proteomic measurements are particularly favorable for investigating the role of signaling and secreted and circulating analytes and identifying molecular and metabolic pathways implicated in age-related diseases.

Degradomics technologies in matrisome exploration

Consisting of a defined set of extracellular proteins secreted from resident cells and with minor contributions from serum proteins, the extracellular matrix (ECM) is an essential component of all tissues. Maintaining tissue homeostasis, structural support and cellular control through cell-ECM communication, the ECM has come to be viewed as not just a passive structural entity but rather as a dynamic signaling conduit between cells and the extracellular compartment. Proteins and their cleavage products mediate this communication, and aberrant signaling, either directly or indirectly distorting the ECM, results in pathological conditions including cancer, inflammation, fibrosis, and neurodegenerative diseases. Characterization of ECM components, the matrisome, the extracellular environment and their changes in disease is therefore of importance to understand and mitigate by developing novel therapeutics. Liquid chromatography-mass spectrometry (LC-MS) proteomics has been integral to protein and proteome research for decades and long superseded the obsolescent gel-based approaches. A continuous effort has ensured progress with increased sensitivity and throughput as more advanced equipment has been developed hand in hand with specialized enrichment, detection, and identification methods. Part of this effort lies in the field of degradomics, a branch of proteomics focused on discovering novel protease substrates by identification of protease-generated neo-N termini, the N-terminome, and characterizing the responsible protease networks. Various methods to do so have been developed, some specialized for specific tissue types, others for particular proteases, throughput, or ease of use. This review aims to provide an overview of the state-of-the-art proteomics techniques that have successfully been recently utilized to characterize proteolytic cleavages in the ECM and thereby guided new research and understanding of the ECM and matrisome biology.

Proteomic profiling of human bone from different anatomical sites - A pilot study

PURPOSE

The study aim is a comparative proteome-based analysis of different autologous bone entities (alveolar bone [AB], iliac cortical [IC] bone, and iliac spongiosa [IS]) used for alveolar onlay grafting.

EXPERIMENTAL DESIGN

Site-matched bone samples of AB, IC, and IS were harvested during alveolar onlay grafting. Proteins were extracted using a detergent-based (sodium dodecyl sulfate) strategy and trypsinized. Proteome analysis was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant was used for peptide-to-spectrum matching, peak detection, and quantitation. Linear models for microarray analysis (LIMMA) were used to detect differentially abundant peptides and proteins.

RESULTS

A total of 1730 different proteins were identified across the 15 samples at a false discovery rate of 1%. Partial least-squares discriminant analysis approved segregation of AB, IC, and IS protein profiles. LIMMA statistics highlighted 66 proteins that were more abundant in AB then in IC (vs. 92 proteins were enriched in IC over AB). Gene Ontology enrichment analysis revealed a matrisomal versus an immune-related proteome fingerprint in AB versus IC.

CONCLUSION AND CLINICAL RELEVANCE

This pilot study demonstrates an ECM protein-related proteome fingerprint in AB and an immune-related proteome fingerprint in IS and IC.

Paleoproteomics

Paleoproteomics, the study of ancient proteins, is a rapidly growing field at the intersection of molecular biology, paleontology, archaeology, paleoecology, and history. Paleoproteomics research leverages the longevity and diversity of proteins to explore fundamental questions about the past. While its origins predate the characterization of DNA, it was only with the advent of soft ionization mass spectrometry that the study of ancient proteins became truly feasible. Technological gains over the past 20 years have allowed increasing opportunities to better understand preservation, degradation, and recovery of the rich bioarchive of ancient proteins found in the archaeological and paleontological records. Growing from a handful of studies in the 1990s on individual highly abundant ancient proteins, paleoproteomics today is an expanding field with diverse applications ranging from the taxonomic identification of highly fragmented bones and shells and the phylogenetic resolution of extinct species to the exploration of past cuisines from dental calculus and pottery food crusts and the characterization of past diseases. More broadly, these studies have opened new doors in understanding past human-animal interactions, the reconstruction of past environments and environmental changes, the expansion of the hominin fossil record through large scale screening of nondiagnostic bone fragments, and the phylogenetic resolution of the vertebrate fossil record. Even with these advances, much of the ancient proteomic record still remains unexplored. Here we provide an overview of the history of the field, a summary of the major methods and applications currently in use, and a critical evaluation of current challenges. We conclude by looking to the future, for which innovative solutions and emerging technology will play an important role in enabling us to access the still unexplored "dark" proteome, allowing for a fuller understanding of the role ancient proteins can play in the interpretation of the past.

Effective protein extraction combined with data independent acquisition analysis reveals a comprehensive and quantifiable insight into the proteomes of articular cartilage and subchondral bone

OBJECTIVE

The objectives of this study was to establish a sensitive and reproducible method to map the cartilage and subchondral bone proteomes in quantitative terms, and mine the proteomes for proteins of particular interest in the pathogenesis of osteoarthritis (OA). The horse was used as a model animal.

DESIGN

Protein was extracted from articular cartilage and subchondral bone samples from three horses in triplicate by pressure cycling technology or ultrasonication. Digested proteins were analysed by data independent acquisition based mass spectrometry. Data was processed using a pre-established spectral library as reference database (FDR 1%).

RESULTS

We identified to our knowledge the hitherto most comprehensive quantitative cartilage (1758 proteins) and subchondral bone (1482 proteins) proteomes in all species presented to date. Both extraction methods were sensitive and reproducible and the high consistency of the identified proteomes (>97% overlap) indicated that both methods preserved the diversity among the extracted proteins. Proteome mining revealed a substantial number of quantifiable cartilage and bone matrix proteins and proteins involved in osteogenesis and bone remodeling, including ACAN, BGN, PRELP, FMOD, COMP, ACP5, BMP3, BMP6, BGLAP, TGFB1, IGF1, ALP, MMP3, and collagens. A number of proteins, including COMP and TNN, were identified in different protein isoforms with potential unique biological roles.

CONCLUSION

We have successfully developed two sensitive and reproducible non-species specific workflows enabling a comprehensive quantitative insight into the proteomes of cartilage and subchondral bone. This facilitates the prospect of investigating the molecular events at the osteochondral unit in the pathogenesis of OA in future projects.

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.

Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits ("endophenotypes"), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

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.

Leveraging proteomics in orphan disease research: pitfalls and potential

Introduction: The term 'orphan diseases' includes conditions meeting prevalence-based or commercial viability criteria: they affect a small number of individuals and are considered an unviable market for drug development. Proteomics is an important technology to study them, providing information on mechanisms and evolution, biomarkers, and effects of therapeutic interventions.Areas covered: Herein, we review how proteomics and bioinformatic tools could be applied to the study of rare diseases and discuss pitfalls and potential.Expert opinion: Research in the field of rare diseases has to face many challenges, and implementation plans should foresee highly specialized collaborative consortia to create multidisciplinary frameworks for data sharing, advancing research, supporting clinical studies, and accelerating drug development. The integration of different technologies will allow better knowledge of disease pathophysiology, and the inclusion of proteomics and other omics technologies in this context will be pivotal to this aim.Several aspects of rare diseases, often perceived as limiting factors, might actually be advantages for a precision medicine approach: the limited number of patients, the collaboration with patient societies, and the availability of curated clinical registries could allow the development of homogeneous clinical databases and ultimately a better control over the data to be analyzed.

UPEFinder: A Bioinformatic Tool for the Study of Uncharacterized Proteins Based on Gene Expression Correlation and the PageRank Algorithm

The Human Proteome Project (HPP) is leading the international effort to characterize the human proteome. Although the main goal of this project was first focused on the detection of missing proteins, a new challenge arose from the need to assign biological functions to the uncharacterized human proteins and describe their implications in human diseases. Not only the proteins with experimental evidence (uPE1 proteins) but also the uncharacterized missing proteins (uMPs) were the objects of study in this challenge, neXt-CP50. In this work, we developed a new bioinformatic approach to infer biological annotations for the uPE1 proteins and uMPs based on a "guilt-by-association" analysis using public RNA-Seq data sets. We used the correlation of these proteins with the well-characterized PE1 proteins to construct a network. In this way, we applied the PageRank algorithm to this network to identify the most relevant nodes, which were the biological annotations of the uncharacterized proteins. All of the generated information was stored in a database. In addition, we implemented the web application UPEFinder (https://upefinder.proteored.org) to facilitate the access to this new resource. This information is especially relevant for the researchers of the HPP who are interested in the generation and validation of new hypotheses about the functions of these proteins. Both the database and the web application are publicly available (https://github.com/ubioinformat/UPEfinder).

New strategies to identify protease substrates

Proteome dynamics is governed by transcription, translation, and post-translational modifications. Limited proteolysis is an irreversible post-translational modification that generates multiple but unique proteoforms from almost every native protein. Elucidating these proteoforms and understanding their dynamics at a system-wide level is of utmost importance because uncontrolled proteolytic cleavages correlate with many pathologies. Mass spectrometry-based degradomics has revolutionized protease research and invented workflows for global identification of protease substrates with resolution down to precise cleavage sites. In this review, we provide an overview of current strategies in protease substrate degradomics and introduce the concept of workflow, mass spectrometry-based and in silico enrichment of protein termini with the perspective of full deconvolution of digital proteome maps for precision medicine, and degradomics biomarker diagnostics.

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.

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.