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

Role of gene therapy in treatment of cancer with craniofacial regeneration-current molecular strategies, future perspectives, and challenges: a narrative review

Gene therapy involves the introduction of foreign genetic material into host tissue to alter the expression of genetic products. Gene therapy represents an opportunity to alter the course of various diseases. Hence, genetic products utilizing safe and reliable vectors with improved biotechnology will play a critical role in the treatment of various diseases in the future. This review summarizes various important vectors for gene therapy along with modern techniques for potential craniofacial regeneration using gene therapy. This review also explains current molecular approaches for the management and treatment of cancer using gene therapy. The existing literature was searched to find studies related to gene therapy and its role in craniofacial regeneration and cancer treatment. Various databases such as PubMed, Science Direct, Scopus, Web of Science, and Google Scholar were searched for English language articles using the keywords "gene therapy," "gene therapy in present scenario," "gene therapy in cancer," "gene therapy and vector," "gene therapy in diseases," and "gene therapy and molecular strategies."

Understanding the impact of structural modifications at the NNAT gene's post-translational acetylation site: in silico approach for predicting its drug-interaction role in anorexia nervosa

PURPOSE

Anorexia nervosa (AN) is a neuropsychological public health concern with a socially disabling routine and affects a person's healthy relationship with food. The role of the NNAT (Neuronatin) gene in AN is well established. The impact of mutation at the protein's post-translational modification (PTM) site has been exclusively associated with the worsening of the protein's biochemical dynamics.

METHODS

To understand the relationship between genotype and phenotype, it is essential to investigate the appropriate molecular stability of protein required for proper biological functioning. In this regard, we investigated the PTM-acetylation site of the NNAT gene in terms of 19 other specific amino acid probabilities in place of wild type (WT) through various in silico algorithms. Based on the highest pathogenic impact computed through the consensus classifier tool, we generated 3 residue-specific (K59D, P, W) structurally modified 3D models of NNAT. These models were further tested through the AutoDock Vina tool to compute the molecular drug binding affinities and inhibition constant (Ki) of structural variants and WT 3D models.

RESULTS

With trained in silico machine learning algorithms and consensus classifier; the three structural modifications (K59D, P, W), which were also the most deleterious substitution at the acetylation site of the NNAT gene, showed the highest structural destabilization and decreased molecular flexibility. The validation and quality assessment of the 3D model of these structural modifications and WT were performed. They were further docked with drugs used to manage AN, it was found that the ΔGbind (kcal/mol) values and the inhibition constants (Ki) were relatively lower in structurally modified models as compared to WT.

CONCLUSION

We concluded that any future structural variation(s) at the PTM-acetylation site of the NNAT gene due to possible mutational consequences, will serve as a basis to explore its relationship with the propensity of developing AN.

LEVEL OF EVIDENCE

No level of evidence-open access bioinformatics research.

The complex biology of aryl hydrocarbon receptor activation in cancer and beyond

The aryl hydrocarbon receptor (AHR) signaling pathway is a complex regulatory network that plays a critical role in various biological processes, including cellular metabolism, development, and immune responses. The complexity of AHR signaling arises from multiple factors, including the diverse ligands that activate the receptor, the expression level of AHR itself, and its interaction with the AHR nuclear translocator (ARNT). Additionally, the AHR crosstalks with the AHR repressor (AHRR) or other transcription factors and signaling pathways and it can also mediate non-genomic effects. Finally, posttranslational modifications of the AHR and its interaction partners, epigenetic regulation of AHR and its target genes, as well as AHR-mediated induction of enzymes that degrade AHR-activating ligands may contribute to the context-specificity of AHR activation. Understanding the complexity of AHR signaling is crucial for deciphering its physiological and pathological roles and developing therapeutic strategies targeting this pathway. Ongoing research continues to unravel the intricacies of AHR signaling, shedding light on the regulatory mechanisms controlling its diverse functions.

Metabolic stress-induced reciprocal loop of long noncoding RNA ZFAS1 and ZEB1 promotes epithelial-mesenchymal transition and metastasis of pancreatic cancer cells

Pancreatic cancer (PC) development faces significant metabolic stress due to metabolic reprogramming and a distinct hypovascular nature, often leading to glucose and glutamine depletion. However, the adaption mechanisms by which PC adapts to these metabolic challenges have not yet been completely explored. Here, we found that metabolic stress induced by glucose and glutamine deprivation led to an overexpression of ZNFX1 antisense RNA 1 (ZFAS1). This overexpression played a significant role in instigating PC cell epithelial-mesenchymal transition (EMT) and metastasis. Mechanistically, ZFAS1 enhanced the interaction between AMPK, a key kinase, and ZEB1, the primary regulator of EMT. This interaction resulted in the phosphorylation and subsequent stabilization of ZEB1. Interestingly, ZEB1 also reciprocally influenced the transcription of ZFAS1 by binding to its promoter. Furthermore, when ZFAS1 was depleted, the nutrient deprivation-induced EMT of PC cells and lung metastasis in nude mice were significantly inhibited. Our investigations also revealed that ZFAS1-rich exosomes released from cells suffering glucose and glutamine deprivation promoted the EMT and metastasis of recipient PC cells. Corroborating these findings, a correlated upregulation of ZFAS1 and ZEB1 expression was observed in PC tissues and was associated with a poor overall survival rate for patients. Our findings highlight the involvement of a long noncoding RNA-driven metabolic adaptation in promoting EMT and metastasis of PC, suggesting ZFAS1 as a promising novel therapeutic target for PC metabolic treatment.

A degradome-based prognostic signature that correlates with immune infiltration and tumor mutation burden in breast cancer

Introduction

Female breast cancer is the most common malignancy worldwide, with a high disease burden. The degradome is the most abundant class of cellular enzymes that play an essential role in regulating cellular activity. Dysregulation of the degradome may disrupt cellular homeostasis and trigger carcinogenesis. Thus we attempted to understand the prognostic role of degradome in breast cancer by means of establishing a prognostic signature based on degradome-related genes (DRGs) and assessed its clinical utility in multiple dimensions.

Methods

A total of 625 DRGs were obtained for analysis. Transcriptome data and clinical information of patients with breast cancer from TCGA-BRCA, METABRIC and GSE96058 were collected. NetworkAnalyst and cBioPortal were also utilized for analysis. LASSO regression analysis was employed to construct the degradome signature. Investigations of the degradome signature concerning clinical association, functional characterization, mutation landscape, immune infiltration, immune checkpoint expression and drug priority were orchestrated. Cell phenotype assays including colony formation, CCK8, transwell and wound healing were conducted in MCF-7 and MDA-MB-435S breast cancer cell lines, respectively.

Results

A 10-gene signature was developed and verified as an independent prognostic predictor combined with other clinicopathological parameters in breast cancer. The prognostic nomogram based on risk score (calculated based on the degradome signature) showed favourable capability in survival prediction and advantage in clinical benefit. High risk scores were associated with a higher degree of clinicopathological events (T4 stage and HER2-positive) and mutation frequency. Regulation of toll-like receptors and several cell cycle promoting activities were upregulated in the high-risk group. PIK3CA and TP53 mutations were dominant in the low- and high-risk groups, respectively. A significantly positive correlation was observed between the risk score and tumor mutation burden. The infiltration levels of immune cells and the expressions of immune checkpoints were significantly influenced by the risk score. Additionally, the degradome signature adequately predicted the survival of patients undergoing endocrinotherapy or radiotherapy. Patients in the low-risk group may achieve complete response after the first round of chemotherapy with cyclophosphamide and docetaxel, whereas patients in the high-risk group may benefit from 5-flfluorouracil. Several regulators of the PI3K/AKT/mTOR signaling pathway and the CDK family/PARP family were identified as potential molecular targets in the low- and high-risk groups, respectively. In vitro experiments further revealed that the knockdown of ABHD12 and USP41 significantly inhibit the proliferation, invasion and migration of breast cancer cells.

Conclusion

Multidimensional evaluation verified the clinical utility of the degradome signature in predicting prognosis, risk stratification and guiding treatment for patients with breast cancer.

Proteomic repository data submission, dissemination, and reuse: key messages

INTRODUCTION

The creation of ProteomeXchange data workflows in 2012 transformed the field of proteomics, consisting of the standardization of data submission and dissemination and enabling the widespread reanalysis of public MS proteomics data worldwide. ProteomeXchange has triggered a growing trend toward public dissemination of proteomics data, facilitating the assessment, reuse, comparative analyses, and extraction of new findings from public datasets. By 2022, the consortium is integrated by PRIDE, PeptideAtlas, MassIVE, jPOST, iProX, and Panorama Public.

AREAS COVERED

Here, we review and discuss the current ecosystem of resources, guidelines, and file formats for proteomics data dissemination and reanalysis. Special attention is drawn to new exciting quantitative and post-translational modification-oriented resources. The challenges and future directions on data depositions including the lack of metadata and cloud-based and high-performance software solutions for fast and reproducible reanalysis of the available data are discussed.

EXPERT OPINION

The success of ProteomeXchange and the amount of proteomics data available in the public domain have triggered the creation and/or growth of other protein knowledgebase resources. Data reuse is a leading, active, and evolving field; supporting the creation of new formats, tools, and workflows to rediscover and reshape the public proteomics data.

Dissecting Plasmodium yoelii Pathobiology: Proteomic Approaches for Decoding Novel Translational and Post-Translational Modifications

Malaria is a vector-borne disease. It is caused by Plasmodium parasites. Plasmodium yoelii is a rodent model parasite, primarily used for studying parasite development in liver cells and vectors. To better understand parasite biology, we carried out a high-throughput-based proteomic analysis of P. yoelii. From the same mass spectrometry (MS)/MS data set, we also captured several post-translational modified peptides by following a bioinformatics analysis without any prior enrichment. Further, we carried out a proteogenomic analysis, which resulted in improvements to some of the existing gene models along with the identification of several novel genes. Analysis of proteome and post-translational modifications (PTMs) together resulted in the identification of 3124 proteins. The identified PTMs were found to be enriched in mitochondrial metabolic pathways. Subsequent bioinformatics analysis provided an insight into proteins associated with metabolic regulatory mechanisms. Among these, the tricarboxylic acid (TCA) cycle and the isoprenoid synthesis pathway are found to be essential for parasite survival and drug resistance. The proteogenomic analysis discovered 43 novel protein-coding genes. The availability of an in-depth proteomic landscape of a malaria pathogen model will likely facilitate further molecular-level investigations on pre-erythrocytic stages of malaria.

How Far Are We from the Completion of the Human Protein Interactome Reconstruction?

After more than fifteen years from the first high-throughput experiments for human protein–protein interaction (PPI) detection, we are still wondering how close the completion of the genome-scale human PPI network reconstruction is, what needs to be further explored and whether the biological insights gained from the holistic investigation of the current network are valid and useful. The unique structure of PICKLE, a meta-database of the human experimentally determined direct PPI network developed by our group, presently covering ~80% of the UniProtKB/Swiss-Prot reviewed human complete proteome, enables the evaluation of the interactome expansion by comparing the successive PICKLE releases since 2013. We observe a gradual overall increase of 39%, 182%, and 67% in protein nodes, PPIs, and supporting references, respectively. Our results indicate that, in recent years, (a) the PPI addition rate has decreased, (b) the new PPIs are largely determined by high-throughput experiments and mainly concern existing protein nodes and (c), as we had predicted earlier, most of the newly added protein nodes have a low degree. These observations, combined with a largely overlapping k-core between PICKLE releases and a network density increase, imply that an almost complete picture of a structurally defined network has been reached. The comparative unsupervised application of two clustering algorithms indicated that exploring the full interactome topology can reveal the protein neighborhoods involved in closely related biological processes as transcriptional regulation, cell signaling and multiprotein complexes such as the connexon complex associated with cancers. A well-reconstructed human protein interactome is a powerful tool in network biology and medicine research forming the basis for multi-omic and dynamic analyses.

A Text Mining and Machine Learning Protocol for Extracting Posttranslational Modifications of Proteins from PubMed: A Special Focus on Glycosylation, Acetylation, Methylation, Hydroxylation, and Ubiquitination

Posttranslational modifications (PTMs) of proteins impart a significant role in human cellular functions ranging from localization to signal transduction. Hundreds of PTMs act in a human cell. Among them, only the selected PTMs are well established and documented. PubMed includes thousands of papers on the selected PTMs, and it is a challenge for the biomedical researchers to assimilate useful information manually. Alternatively, text mining approaches and machine learning algorithm automatically extract the relevant information from PubMed. Protein phosphorylation is a well-established PTM and several research works are under way. Many existing systems are there for protein phosphorylation information extraction. A recent approach uses a hybrid approach using text mining and machine learning to extract protein phosphorylation information from PubMed. Some of the other common PTMs that exhibit similar features in terms of entities that are involved in PTM process, that is, the substrate, the enzymes, and the amino acid residues, are glycosylation, acetylation, methylation, hydroxylation, and ubiquitination. This has motivated us to repurpose and extend the text mining protocol and machine learning information extraction methodology developed for protein phosphorylation to these PTMs. In this chapter, the chemistry behind each of the PTMs is briefly outlined and the text mining protocol and machine learning algorithm adaption is explained for the same.

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.

The World of Stable Ribonucleoproteins and Its Mapping With Grad-Seq and Related Approaches

Macromolecular complexes of proteins and RNAs are essential building blocks of cells. These stable supramolecular particles can be viewed as minimal biochemical units whose structural organization, i.e., the way the RNA and the protein interact with each other, is directly linked to their biological function. Whether those are dynamic regulatory ribonucleoproteins (RNPs) or integrated molecular machines involved in gene expression, the comprehensive knowledge of these units is critical to our understanding of key molecular mechanisms and cell physiology phenomena. Such is the goal of diverse complexomic approaches and in particular of the recently developed gradient profiling by sequencing (Grad-seq). By separating cellular protein and RNA complexes on a density gradient and quantifying their distributions genome-wide by mass spectrometry and deep sequencing, Grad-seq charts global landscapes of native macromolecular assemblies. In this review, we propose a function-based ontology of stable RNPs and discuss how Grad-seq and related approaches transformed our perspective of bacterial and eukaryotic ribonucleoproteins by guiding the discovery of new RNA-binding proteins and unusual classes of noncoding RNAs. We highlight some methodological aspects and developments that permit to further boost the power of this technique and to look for exciting new biology in understudied and challenging biological models.

The era of gene therapy: From preclinical development to clinical application

Three decades of promise have culminated in the development of gene therapies that can be applied to a broad range of human diseases. After a brief history, we provide an overview of gene therapy types and delivery methods, gene editing technologies, regulatory affairs, clinical trials, approved products, ongoing challenges, and future goals. Information on clinical trials of candidates and on approved products for gene therapy developed between 1988 and 2020 is systematically collated. To obtain this global information, we scanned and reviewed more than 46,000 records of clinical trials from 17 clinical trial database providers. The medical benefits of transformative gene therapies are gradually being accepted by payors, and a significant increase in the number of gene therapy clinical trials and approved gene therapy products has resulted.

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.

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.

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.

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).

Aggregation and Cellular Toxicity of Pathogenic or Non-pathogenic Proteins

More than 20 unique diseases such as diabetes, Alzheimer’s disease, Parkinson’s disease are caused by the abnormal aggregations of pathogenic proteins such as amylin, β-amyloid (Aβ), and α-synuclein. All pathogenic proteins differ from each other in biological function, primary sequences, and morphologies; however, the proteins are toxic when aggregated. Here, we investigated the cellular toxicity of pathogenic or non-pathogenic protein aggregates. In this study, six proteins were selected and they were incubated at acid pH and high temperature. The aggregation kinetic and cellular toxicity of protein species with time were characterized. Three non-pathogenic proteins, bovine serum albumin (BSA), catalase, and pepsin at pH 2 and 65 °C were stable in protein structure and non-toxic at a lower concentration of 1 mg/mL. They formed aggregates at a higher concentration of 20 mg/mL with time and they induced the toxicity in short incubation time points, 10 min and 20 min only and they became non-toxic after 30 min. Other three pathogenic proteins, lysozyme, superoxide dismutase (SOD), and insulin, also produced the aggregates with time and they caused cytotoxicity at both 1 mg/mL and 20 mg/mL after 10 min. TEM images and DSC analysis demonstrated that fibrils or aggregates at 1 mg/mL induced cellular toxicity due to low thermal stability. In DSC data, fibrils or aggregates of pathogenic proteins had low thermal transition compared to fresh samples. The results provide useful information to understand the aggregation and cellular toxicity of pathogenic and non-pathogenic 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.

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).

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0

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

The UGTome: The expanding diversity of UDP glycosyltransferases and its impact on small molecule metabolism

The UDP glycosyltransferase (UGT) superfamily of enzymes is responsible for the metabolism and clearance of thousands of lipophilic chemicals including drugs, toxins and endogenous signaling molecules. They provide a protective interface between the organism and its chemical-rich environment, as well as controlling critical signaling pathways to maintain healthy tissue function. UGTs are associated with drug responses and interactions, as well as a wide range of diseases including cancer. The human genome contains 22 UGT genes; however as befitting their exceptionally diverse substrate ranges and biological activities, the output of these UGT genes is functionally diversified by multiple processes including alternative splicing, post-translational modification, homo- and hetero-oligomerization, and interactions with other proteins. All UGT genes are subject to extensive alternative splicing generating variant/truncated UGT proteins with altered functions including the capacity to dominantly modulate/inhibit cognate full-length forms. Heterotypic oligomerization of different UGTs can alter kinetic properties relative to monotypic complexes, and potentially produce novel substrate specificities. Moreover, the recently profiled interactions of UGTs with non-UGT proteins may facilitate coordination between different metabolic processes, as well as providing opportunities for UGTs to engage in novel 'moonlighting' functions. Herein we provide a detailed and comprehensive review of all known modes of UGT functional diversification and propose a UGTome model to describe the resulting expansion of metabolic capacity and its potential to modulate drug/xenobiotic responses and cell behaviours in normal and disease contexts.

T-cell-receptor cross-recognition and strategies to select safe T-cell receptors for clinical translation

Adoptive transfer of T-cell-receptor (TCR)-transduced T cells has shown promising results for cancer treatment, but has also produced severe immunotoxicities caused by on-target as well as off-target TCR recognition. Off-target toxicities are related to the ability of a single T cell to cross-recognize and respond to several different peptide–major histocompatibility complex (pMHC) antigens; a property that is essential for providing broad antigenic coverage despite a confined number of unique TCRs in the human body. However, this degeneracy makes it incredibly difficult to account for the range of targets that any TCR might recognize, which represents a major challenge for the clinical development of therapeutic TCRs. The prospect of using affinity-optimized TCRs has been impeded due to observations that affinity enhancement might alter the specificity of a TCR, thereby increasing the risk that it will cross-recognize endogenous tissue. Strategies for selecting safe TCRs for the clinic have included functional assessment after individual incubations with tissue-derived primary cells or with peptides substituted with single amino acids. However, these strategies have not been able to predict cross-recognition sufficiently, leading to fatal cross-reactivity in clinical trials. Novel technologies have emerged that enable extensive characterization of the exact interaction points of a TCR with pMHC, which provides a foundation from which to make predictions of the cross-recognition potential of individual TCRs. This review describes current advances in strategies for dissecting the molecular interaction points of TCRs, focusing on their potential as tools for predicting cross-recognition of TCRs in clinical development.

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T-cell-receptor (TCR) degeneracy plays a fundamental role in the capacity of our immune systems to recognize foreign antigens.

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TCR cross-reactivity provides an inherent risk in TCR–gene transfer cell therapies.

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Advances in description of TCR cross-recognition can guide the selection process for TCRs into clinical use.

Gene Therapy Leaves a Vicious Cycle

The human genetic code encrypted in thousands of genes holds the secret for synthesis of proteins that drive all biological processes necessary for normal life and death. Though the genetic ciphering remains unchanged through generations, some genes get disrupted, deleted and or mutated, manifesting diseases, and or disorders. Current treatment options—chemotherapy, protein therapy, radiotherapy, and surgery available for no more than 500 diseases—neither cure nor prevent genetic errors but often cause many side effects. However, gene therapy, colloquially called “living drug,” provides a one-time treatment option by rewriting or fixing errors in the natural genetic ciphering. Since gene therapy is predominantly a viral vector-based medicine, it has met with a fair bit of skepticism from both the science fraternity and patients. Now, thanks to advancements in gene editing and recombinant viral vector development, the interest of clinicians and pharmaceutical industries has been rekindled. With the advent of more than 12 different gene therapy drugs for curing cancer, blindness, immune, and neuronal disorders, this emerging experimental medicine has yet again come in the limelight. The present review article delves into the popular viral vectors used in gene therapy, advances, challenges, and perspectives.

Proteogenomics in the context of the Human Proteome Project (HPP)

INTRODUCTION

The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.

Middle-down approach: a choice to sequence and characterize proteins/proteomes by mass spectrometry

Owing to rapid growth in the elucidation of genome sequences of various organisms, deducing proteome sequences has become imperative, in order to have an improved understanding of biological processes. Since the traditional Edman method was unsuitable for high-throughput sequencing and also for N-terminus modified proteins, mass spectrometry (MS) based methods, mainly based on soft ionization modes: electrospray ionization and matrix-assisted laser desorption/ionization, began to gain significance. MS based methods were adaptable for high-throughput studies and applicable for sequencing N-terminus blocked proteins/peptides too. Consequently, over the last decade a new discipline called 'proteomics' has emerged, which encompasses the attributes necessary for high-throughput identification of proteins. 'Proteomics' may also be regarded as an offshoot of the classic field, 'biochemistry'. Many protein sequencing and proteomic investigations were successfully accomplished through MS dependent sequence elucidation of 'short proteolytic peptides (typically: 7-20 amino acid residues), which is called the 'shotgun' or 'bottom-up (BU)' approach. While the BU approach continues as a workhorse for proteomics/protein sequencing, attempts to sequence intact proteins without proteolysis, called the 'top-down (TD)' approach started, due to ambiguities in the BU approach, e.g., protein inference problem, identification of proteoforms and the discovery of posttranslational modifications (PTMs). The high-throughput TD approach (TD proteomics) is yet in its infancy. Nevertheless, TD characterization of purified intact proteins has been useful for detecting PTMs. With the hope to overcome the pitfalls of BU and TD strategies, another concept called the 'middle-down (MD)' approach was put forward. Similar to BU, the MD approach also involves proteolysis, but in a restricted manner, to produce 'longer' proteolytic peptides than the ones usually obtained in BU studies, thereby providing better sequence coverage. In this regard, special proteases (OmpT, Sap9, IdeS) have been used, which can cleave proteins to produce longer proteolytic peptides. By reviewing ample evidences currently existing in the literature that is predominantly on PTM characterization of histones and antibodies, herein we highlight salient features of the MD approach. Consequently, we are inclined to claim that the MD concept might have widespread applications in future for various research areas, such as clinical, biopharmaceuticals (including PTM analysis) and even for general/routine characterization of proteins including therapeutic proteins, but not just limited to analysis of histones or antibodies.

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

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

Increased Sensitivity of Mass Spectrometry by Alkaline Two-Dimensional Liquid Chromatography: Deep Cover of the Human Proteome in Gene-Centric Mode

Currently, great interest is paid to the identification of "missing" proteins that have not been detected in any biological material at the protein level (PE1). In this paper, using the Universal Proteomic Standard sets 1 and 2 (UPS1 and UPS2, respectively) as an example, we characterized mass spectrometric approaches from the point of view of sensitivity (Sn), specificity (Sp), and accuracy (Ac). The aim of the paper was to show the utility of a mass spectra approach for protein detection. This sets consists of 48 high-purity human proteins without single aminoacid polymorphism (SAP) or post translational modification (PTM). The UPS1 set consists of the same 48 proteins at 5 pmols each, and in UPS2, proteins were grouped into 5 groups in accordance with their molar concentration, ranging from 10^-11 to 10^-6 M. Single peptides from the 92% and 96% of all sets of proteins could be detected in a pure solution of UPS2 and UPS1, respectively, by selected reaction monitoring with stable isotope-labeled standards (SRM-SIS). We also found that, in the presence of a biological matrix such as Escherichia coli extract or human blood plasma (HBP), SRM-SIS makes it possible to detect from 63% to 79% of proteins in the UPS2 set (sensitivity) with the highest specificity (∼100%) and an accuracy of 80% by increasing the sensitivity of shotgun and selected reaction monitoring combined with a stable-isotope-labeled peptide standard (SRM-SIS technology) by fractionating samples using reverse-phase liquid chromatography under alkaline conditions (2D-LC_alk). It is shown that this technique of sample fractionation allows the SRM-SIS to detect 98% of the single peptides from the proteins present in the pure solution of UPS2 (47 out of 48 proteins). When the extracts of E. coli or Pichia pastoris are added as biological matrixes to the UPS2, 46, and 45 out of 48 proteins (∼95%) can be detected, respectively, using the SRM-SIS combined with 2D-LC_alk. The combination of the 2D-LC_alk SRM-SIS and shotgun technologies allows us to increase the sensitivity up to 100% in the case of the proteins of the UPS2 set. The usage of that technology can be a solution for identifying the so-called "missing" proteins and, eventually, creating the deep proteome of a particular chromosome of tissue or organs. Experimental data have been deposited in the PeptideAtlas SRM Experiment Library with the dataset identifier PASS01192 and the PRIDE repository with the dataset identifier PXD007643.

Global Profiling of Proteolysis from the Mitochondrial Amino Terminome during Early Intrinsic Apoptosis Prior to Caspase-3 Activation

The human genome encodes ∼20 mitochondrial proteases, yet we know little of how they sculpt the mitochondrial proteome, particularly during important mitochondrial events such as the initiation of apoptosis. To characterize global mitochondrial proteolysis we refined our technique, terminal amine isotopic labeling of substrates, for mitochondrial SILAC (MS-TAILS) to identify proteolysis across mitochondria and parent cells in parallel. Our MS-TAILS analyses identified 45% of the mitochondrial proteome and identified protein amino (N)-termini from 26% of mitochondrial proteins, the highest reported coverage of the human mitochondrial N-terminome. MS-TAILS revealed 97 previously unknown proteolytic sites. MS-TAILS also identified mitochondrial targeting sequence (MTS) removal by proteolysis during protein import, confirming 101 MTS sites and identifying 135 new MTS sites, revealing a wobbly requirement for the MTS cleavage motif. To examine the relatively unknown initial cleavage events occurring before the well-studied activation of caspase-3 in intrinsic apoptosis, we quantitatively compared N-terminomes of mitochondria and their parent cells before and after initiation of apoptosis at very early time points. By identifying altered levels of >400 N-termini, MS-TAILS analyses implicated specific mitochondrial pathways including protein import, fission, and iron homeostasis in apoptosis initiation. Notably, both staurosporine and Bax activator molecule-7 triggered in common 7 mitochondrial and 85 cellular cleavage events that are potentially part of an essential core of apoptosis-initiating events. All mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD009054.

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

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

Synaptic activity induces input-specific rearrangements in a targeted synaptic protein interaction network

Cells utilize dynamic, network-level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity-dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity-dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of pre-existing multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. Open Science: This manuscript was awarded with the Open Materials Badge. For more information see: https://cos.io/our-services/open-science-badges/.

Quality control in mass spectrometry-based proteomics

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

The neXtProt peptide uniqueness checker: a tool for the proteomics community

Summary

The neXtProt peptide uniqueness checker allows scientists to define which peptides can be used to validate the existence of human proteins, i.e. map uniquely versus multiply to human protein sequences taking into account isobaric substitutions, alternative splicing and single amino acid variants.

Availability and implementation

The pepx program is available at https://github.com/calipho-sib/pepx and can be launched from the command line or through a cgi web interface. Indexing requires a sequence file in FASTA format. The peptide uniqueness checker tool is freely available on the web at https://www.nextprot.org/tools/peptide-uniqueness-checker and from the neXtProt API at https://api.nextprot.org/.

Reprint of: Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

The Gene-Centric Content Management System and Its Application for Cognitive Proteomics

The Human Proteome Project is moving into the next phase of creating and/or reconsidering the functional annotations of proteins using the chromosome-centric paradigm. This challenge cannot be solved exclusively using automated means, but rather requires human intelligence for interpreting the combined data. To foster the integration between human cognition and post-genome array a number of specific tools were recently developed, among them CAPER, GenomewidePDB, and The Proteome Browser (TPB). For the purpose of tackling the task of protein functional annotating the Gene-Centric Content Management System (GenoCMS) was expanded with new features. The goal was to enable bioinformaticans to develop self-made applications and to position these applets within the generalized informational canvas supported by GenoCMS. We report the results of GenoCMS-enabled integration of the concordant informational flows in the chromosome-centric framework of the human chromosome 18 project. The workflow described in the article can be scaled to other human chromosomes, and also supplemented with new tracks created by the user. The GenoCMS is an example of a project-oriented informational system, which are important for public data sharing.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

Proteolytic Cleavage-Mechanisms, Function, and "Omic" Approaches for a Near-Ubiquitous Posttranslational Modification

Proteases enzymatically hydrolyze peptide bonds in substrate proteins, resulting in a widespread, irreversible posttranslational modification of the protein's structure and biological function. Often regarded as a mere degradative mechanism in destruction of proteins or turnover in maintaining physiological homeostasis, recent research in the field of degradomics has led to the recognition of two main yet unexpected concepts. First, that targeted, limited proteolytic cleavage events by a wide repertoire of proteases are pivotal regulators of most, if not all, physiological and pathological processes. Second, an unexpected in vivo abundance of stable cleaved proteins revealed pervasive, functionally relevant protein processing in normal and diseased tissue-from 40 to 70% of proteins also occur in vivo as distinct stable proteoforms with undocumented N- or C-termini, meaning these proteoforms are stable functional cleavage products, most with unknown functional implications. In this Review, we discuss the structural biology aspects and mechanisms of catalysis by different protease classes. We also provide an overview of biological pathways that utilize specific proteolytic cleavage as a precision control mechanism in protein quality control, stability, localization, and maturation, as well as proteolytic cleavage as a mediator in signaling pathways. Lastly, we provide a comprehensive overview of analytical methods and approaches to study activity and substrates of proteolytic enzymes in relevant biological models, both historical and focusing on state of the art proteomics techniques in the field of degradomics research.

Proteomics in cardiovascular diseases: Unveiling sex and gender differences in the era of precision medicine

Cardiovascular diseases (CVDs) represent the most important cause of mortality in women and in men. Contrary to the long-standing notion that the effects of the major risk factors on CVD outcomes are the same in both sexes, recent evidence recognizes new, potentially independent, sex/gender-related risk factors for CVDs, and sex/gender-differences in the clinical presentation of CVDs have been demonstrated. Furthermore, some therapeutic options may not be equally effective and safe in men and women. In this context, proteomics offers an extremely useful and versatile analytical platform for biomedical researches that expand from the screening of early diagnostic and prognostic biomarkers to the investigation of the molecular mechanisms underlying CDVs. In this review, we summarized the current applications of proteomics in the cardiovascular field, with emphasis on sex and gender-related differences in CVDs.

SIGNIFICANCE

Increasing evidence supports the profound effect of sex and gender on cardiovascular physio-pathology and the response to drugs. A clear understanding of the mechanisms underlying sexual dimorphisms in CVDs would not only improve our knowledge of the etiology of these diseases, but could also inform health policy makers and guideline committees in tailoring specific interventions for the prevention, treatment and management of CVDs in both men and women.

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

INTRODUCTION

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

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

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

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

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

Digging More Missing Proteins Using an Enrichment Approach with ProteoMiner

Human Proteome Project (HPP) aims at mapping entire human proteins with a systematic effort upon all the emerging techniques, which would enhance understanding of human biology and lay a foundation for development of medical applications. Until now, 2563 missing proteins (MPs, PE2-4) are still undetected even using the most sensitive approach of protein detection. Herein, we propose that enrichment of low-abundance proteins benefits MPs finding. ProteoMiner is an equalizing technique by reducing high-abundance proteins and enriching low-abundance proteins in biological liquids. With triton X-100/TBS buffer extraction, ProteoMiner enrichment, and peptide fractionation, 20 MPs (at least two non-nested unique peptides with more than eight a.a. length) with 60 unique peptides were identified from four human tissues including eight membrane/secreted proteins and five nucleus proteins. Then 15 of them were confirmed with two non-nested unique peptides (≥9 a.a.) identified by matching well with their chemically synthetic peptides in PRM assay. Hence, these results demonstrated ProteoMiner as a powerful means in discovery of MPs.

Detergent-Insoluble Proteome Analysis Revealed Aberrantly Aggregated Proteins in Human Preeclampsia Placentas

Preeclampsia (PE) is a placenta disease, featured by hypertension, proteinuria, and other multiorgan dysfunctions, and its etiology is unclear. We and others have shown that intensive endoplasmic reticulum (ER) stress and unfolded protein response (UPR) occur in the PE placenta. In this study, we isolated detergent-insoluble proteins (DIPs) from human placenta tissues, which were enriched with protein aggregates, to characterize the placenta UPR in PE. With data-independent acquisition (DIA) mass spectrometry, we identified 2066 DIPs across all normal (n = 10) and PE (n = 10) placenta samples, among which 110 and 108 DIPs were significantly up- and down-regulated in PE, respectively. Per clustering analysis, differential DIPs could generally distinguish PE from normal placentas. We verified the MS quantitation of endoglin and vimentin by immunoblotting. In addition, we observed that PE placenta tissues have remarkably more endoglin in the cytoplasm. Furthermore, we found that DIPs were evenly distributed across different chromosomes and could be enriched in diversified gene ontology terms, while differential DIPs avoided to distribute on X-chromosome. Significantly up-regulated DIPs in PE were focused on the top functions of lipid metabolism, while 23 of these DIPs could form the top network regulating cellular movement, development, growth, and proliferation. Our results implicate that human PE placentas have disease-relevant differential DIPs, which reflect aberrantly aggregated proteins of placental tissues. The mass spectrometry proteomics data have been deposited to ProteomeXchange consortium with the data set identifier PXD006654, and iProX database (accession number: IPX0000948000).

The Human Odontoblast Cell Layer and Dental Pulp Proteomes and N-Terminomes

The proteome and N-terminome of the human odontoblast cell layer were identified for the first time by shotgun proteomic and terminal amine isotopic labeling of substrates (TAILS) N-terminomic analyses, respectively, and compared with that of human dental pulp stroma from 26 third molar teeth. After reverse-phase liquid chromatography-tandem mass spectrometry, >170,000 spectra from the shotgun and TAILS analyses were matched by 4 search engines to 4,888 and 12,063 peptides in the odontoblast cell layer and pulp stroma, respectively. Within these peptide groups, 1,543 and 5,841 protein N-termini, as well as 895 and 2,423 unique proteins, were identified with a false discovery rate of ≤1%. Thus, the human dental pulp proteome was expanded by 974 proteins not previously identified among the 4,123 proteins in our 2015 dental pulp study. Further, 222 proteins of the odontoblast cell layer were not found in the pulp stroma, suggesting many of these proteins are synthesized only by odontoblasts. When comparing the proteomes of older and younger donors, differences were more apparent in the odontoblast cell layer than in the dental pulp stroma. In the odontoblast cell layer proteome, we found proteomic evidence for dentin sialophosphoprotein, which is cleaved into dentin sialoprotein and dentin phosphoprotein. By exploring the proteome of the odontoblast cell layer and expanding the known dental pulp proteome, we found distinct proteome differences compared with each other and with dentin. Moreover, between 61% and 66% of proteins also occurred as proteoforms commencing with a neo-N-terminus not annotated in UniProt. Hence, TAILS increased proteome coverage and revealed considerable proteolytic processing, by identifying stable proteoforms in these dynamic dental tissues. All mass spectrometry raw data have been deposited to ProteomeXchange with the identifier <PXD006557>, with the accompanying metadata at Mendeley Data ( https://data.mendeley.com/datasets/b57zfh6wmy/1 ).

The human protein atlas: A spatial map of the human proteome

The correct spatial distribution of proteins is vital for their function and often mis-localization or ectopic expression leads to diseases. For more than a decade, the Human Protein Atlas (HPA) has constituted a valuable tool for researchers studying protein localization and expression in human tissues and cells. The centerpiece of the HPA is its unique antibody collection for mapping the entire human proteome by immunohistochemistry and immunocytochemistry. By these approaches, more than 10 million images showing protein expression patterns at a single-cell level were generated and are publicly available at www.proteinatlas.org. The antibody-based approach is combined with transcriptomics data for an overview of global expression profiles. The present article comprehensively describes the HPA database functions and how users can utilize it for their own research as well as discusses the future path of spatial proteomics.

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

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