Human SRMAtlas: A Resource of Targeted Assays to Quantify the Complete Human Proteome

Targeted mass spectrometry-based assays enable multiplex quantification of receptor tyrosine kinase, MAP Kinase, and AKT signaling

SUMMARY

A primary goal of the US National Cancer Institute's Ras initiative at the Frederick National Laboratory for Cancer Research is to develop methods to quantify RAS signaling to facilitate development of novel cancer therapeutics. We use targeted proteomics technologies to develop a community resource consisting of 256 validated multiple reaction monitoring (MRM)-based, multiplexed assays for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. As proof of concept, we quantify the response of melanoma (A375 and SK-MEL-2) and colorectal cancer (HCT-116 and HT-29) cell lines to BRAF inhibition by PLX-4720. These assays replace over 60 Western blots with quantitative mass spectrometry-based assays of high molecular specificity and quantitative precision, showing the value of these methods for pharmacodynamic measurements and mechanism of action studies. Methods, fit-for-purpose validation, and results are publicly available as a resource for the community at assays.cancer.gov.

MOTIVATION

A lack of quantitative, multiplexable assays for phosphosignaling limits comprehensive investigation of aberrant signaling in cancer and evaluation of novel treatments. To alleviate this limitation, we sought to develop assays using targeted mass spectrometry for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. The resulting assays provide a resource for replacing over 60 Western blots in examining cancer signaling and tumor biology with high molecular specificity and quantitative rigor.

Binding and detoxification ability of lactobacillus acidophilus towards di-n-butyl phthalate: Change of MAPK pathway in Caco-2 cell model

Di-n-butyl phthalate (DBP), a common compound of phthalates, can pose a risk to humans as a contaminant in the food industry. At present, the molecular mechanism of gene and protein toxicity caused by DBP in human cells is unclear. This in vitro study investigated the potential of inactivated Lactobacillus acidophilus NCFM in alleviating the damage caused by DBP in Caco-2 cells. According to the results from transcriptome and proteome analyses, the Caco-2 cells treated by DBP was resulted finally endoplasmic reticulum stress and mitochondrial oxidative damage. The most important differentially expressed genes and proteins involved in Caco-2 cells treated with NCFM to relieve DBP's cytotoxicity were TNF, NF-κB, CREB, P21, GADD45, FOS and CASP3. The molecular mechanism of DBP toxicity alleviated by strain NCFM was involved the MAPK pathway, via DBP bind to strain NCFM and avoid the activation of TNF receptor by DBP, so down-regulated the NF-κB, CREB, P21, GADD45, and CASP3, relieving the apoptosis of Caco-2 cells. Overall, our data provide new insights into detoxification of phthalate by using Lactobacillus. SIGNIFICANCE: Here we sequenced and assembled the transcriptome from Caco-2 cells which were treated with 4 groups: Control, DBP, strain NCFM, and strain NCFM+DBP groups, and combined it with proteome to characterize DBP detoxification genes/proteins through multiomics analysis. The cell viability in DBP treated groups were significantly increased by NCFM strain, indicating NCFM strain has the ability to alleviate the cytotoxicity of DBP via their binding ability with toxins. Furthermore, the results of transcriptome and proteome analysis showed that the signaling pathway of strain NCFM can alleviate DBP toxicity through MAPK pathway, and the potential biomarkers were identified too. This research may provided new information for developing new detoxification strategies for DBP.

Mesoglycan exerts its fibrinolytic effect through the activation of annexin A2

Mesoglycan is a drug based on a mixture of glycosaminoglycans mainly used for the treatment of blood vessel diseases acting as antithrombotic and profibrinolytic drugs. Besides the numerous clinical studies, there is no information about its function on the fibrinolytic cascade. Here, we have elucidated the mechanism of action by which mesoglycan induces the activation of plasmin from endothelial cells. Surprisingly, by a proteomic analysis, we found that, following mesoglycan treatment, these cells show a notable amount of annexin A2 (ANXA2) at the plasma membrane. This protein has been widely associated with fibrinolysis and appears able to move to the membrane when phosphorylated. In our model, this translocation has proven to enhance cell migration, invasion, and angiogenesis. Furthermore, the interaction of mesoglycan with syndecan 4 (SDC4), a coreceptor belonging to the class of heparan sulfate proteoglycans, represents the upstream event of the ANXA2 behavior. Indeed, the activation of SDC4 triggers the motility of endothelial cells culminating in angiogenesis. Interestingly, mesoglycan can induce the release of plasmin in endothelial cell supernatants only in the presence of ANXA2. This evaluation suggests that mesoglycan triggers the formation of a chain mechanism starting from the activation of SDC4, and the related cascade of events, including src complex and PKCα activation, promoting the phosphorylation of ANXA2 and its translocation to plasma membrane. This indicates a connection among mesoglycan, SDC4-(PKCα-src), and ANXA2 which, in turn, links the tissue plasminogen activator bringing it closer to plasminogen. This latter is so cleaved to release the plasmin and degrade fibrin sleeves.

Mass spectrometry-based chemical mapping and profiling toward molecular understanding of diseases in precision medicine

Precision medicine has been strongly promoted in recent years. It is used in clinical management for classifying diseases at the molecular level and for selecting the most appropriate drugs or treatments to maximize efficacy and minimize adverse effects. In precision medicine, an in-depth molecular understanding of diseases is of great importance. Therefore, in the last few years, much attention has been given to translating data generated at the molecular level into clinically relevant information. However, current developments in this field lack orderly implementation. For example, high-quality chemical research is not well integrated into clinical practice, especially in the early phase, leading to a lack of understanding in the clinic of the chemistry underlying diseases. In recent years, mass spectrometry (MS) has enabled significant innovations and advances in chemical research. As reported, this technique has shown promise in chemical mapping and profiling for answering "what", "where", "how many" and "whose" chemicals underlie the clinical phenotypes, which are assessed by biochemical profiling, MS imaging, molecular targeting and probing, biomarker grading disease classification, etc. These features can potentially enhance the precision of disease diagnosis, monitoring and treatment and thus further transform medicine. For instance, comprehensive MS-based biochemical profiling of ovarian tumors was performed, and the results revealed a number of molecular insights into the pathways and processes that drive ovarian cancer biology and the ways that these pathways are altered in correspondence with clinical phenotypes. Another study demonstrated that quantitative biomarker mapping can be predictive of responses to immunotherapy and of survival in the supposedly homogeneous group of breast cancer patients, allowing for stratification of patients. In this context, our article attempts to provide an overview of MS-based chemical mapping and profiling, and a perspective on their clinical utility to improve the molecular understanding of diseases for advancing precision medicine.

Proteomics, Personalized Medicine and Cancer

As of 2020 the human genome and proteome are both at >90% completion based on high stringency analyses. This has been largely achieved by major technological advances over the last 20 years and has enlarged our understanding of human health and disease, including cancer, and is supporting the current trend towards personalized/precision medicine. This is due to improved screening, novel therapeutic approaches and an increased understanding of underlying cancer biology. However, cancer is a complex, heterogeneous disease modulated by genetic, molecular, cellular, tissue, population, environmental and socioeconomic factors, which evolve with time. In spite of recent advances in treatment that have resulted in improved patient outcomes, prognosis is still poor for many patients with certain cancers (e.g., mesothelioma, pancreatic and brain cancer) with a high death rate associated with late diagnosis. In this review we overview key hallmarks of cancer (e.g., autophagy, the role of redox signaling), current unmet clinical needs, the requirement for sensitive and specific biomarkers for early detection, surveillance, prognosis and drug monitoring, the role of the microbiome and the goals of personalized/precision medicine, discussing how emerging omics technologies can further inform on these areas. Exemplars from recent onco-proteogenomic-related publications will be given. Finally, we will address future perspectives, not only from the standpoint of perceived advances in treatment, but also from the hurdles that have to be overcome.

Multiple Reaction Monitoring-Based Targeted Assays for the Validation of Protein Biomarkers in Brain Tumors

The emergence of omics technologies over the last decade has helped in advancement of research and our understanding of complex diseases like brain cancers. However, barring genomics, no other omics technology has been able to find utility in clinical settings. The recent advancements in mass spectrometry instrumentation have resulted in proteomics technologies becoming more sensitive and reliable. Targeted proteomics, a relatively new branch of mass spectrometry-based proteomics has shown immense potential in addressing the shortcomings of the standard molecular biology-based techniques like Western blotting and Immunohistochemistry. In this study we demonstrate the utility of Multiple reaction monitoring (MRM), a targeted proteomics approach, in quantifying peptides from proteins like Apolipoprotein A1 (APOA1), Apolipoprotein E (APOE), Prostaglandin H2 D-Isomerase (PTGDS), Vitronectin (VTN) and Complement C3 (C3) in cerebrospinal fluid (CSF) collected from Glioma and Meningioma patients. Additionally, we also report transitions for peptides from proteins - Vimentin (VIM), Cystatin-C (CST3) and Clusterin (CLU) in surgically resected Meningioma tissues; Annexin A1 (ANXA1), Superoxide dismutase (SOD2) and VIM in surgically resected Glioma tissues; and Microtubule associated protein-2 (MAP-2), Splicing factor 3B subunit 2 (SF3B2) and VIM in surgically resected Medulloblastoma tissues. To our knowledge, this is the first study reporting the use of MRM to validate proteins from three types of brain malignancies and two different bio-specimens. Future studies involving a large cohort of samples aimed at accurately detecting and quantifying peptides of proteins with roles in brain malignancies could potentially result in a panel of proteins showing ability to classify and grade tumors. Successful application of these techniques could ultimately offer alternative strategies with increased accuracy, sensitivity and lower turnaround time making them translatable to the clinics.

Systems biology in cardiovascular disease: a multiomics approach

Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.

The clinical potential of prm-PASEF mass spectrometry

INTRODUCTION

The continuous technical improvement in sensitivity and specificity placed mass spectrometry as an alternative method for analyzing clinical samples. In parallel to the rapid development of discovery proteomics, targeted acquisition has been implemented as a complementary option for measuring a small set of proteins with high sensitivity and robustness in a large sample cohort. The combination of trapped ion mobility with a rapid time-of-flight (TOF) mass spectrometer improves the sensitivity even further and triggers the development of prm-PASEF.

AREAS COVERED

This article discusses the development of prm-PASEF and its advantages over the existing targeted and discovery methods for analyzing clinical samples. We are also highlighting the different requirements for the use of prm-PASEF on clinical samples.

EXPERT OPINION

prm-PASEF takes advantage of a dual ion-mobility trap enabling highly multiplexed targeted acquisition. It allows the implementation of a short chromatographic separation setup without sacrificing the number of targeted peptides. Analyzing clinical samples by prm-PASEF holds the promise to significantly improve throughput while maintaining sensitivity to detect the selected target proteins.

SUMOylation controls the binding of hexokinase 2 to mitochondria and protects against prostate cancer tumorigenesis

Human hexokinase 2 is an essential regulator of glycolysis that couples metabolic and proliferative activities in cancer cells. The binding of hexokinase 2 to the outer membrane of mitochondria is critical for its oncogenic activity. However, the regulation of hexokinase 2 binding to mitochondria remains unclear. Here, we report that SUMOylation regulates the binding of hexokinase 2 to mitochondria. We find that hexokinase 2 can be SUMOylated at K315 and K492. SUMO-specific protease SENP1 mediates the de-SUMOylation of hexokinase 2. SUMO-defective hexokinase 2 preferably binds to mitochondria and enhances both glucose consumption and lactate production and decreases mitochondrial respiration in parallel. This metabolic reprogramming supports prostate cancer cell proliferation and protects cells from chemotherapy-induced cell apoptosis. Moreover, we demonstrate an inverse relationship between SENP1-hexokinase 2 axis and chemotherapy response in prostate cancer samples. Our data provide evidence for a previously uncovered posttranslational modification of hexokinase 2 in cancer cells, suggesting a potentially actionable strategy for preventing chemotherapy resistance in prostate cancer.

The oncogenic activity of Hexokinase 2, the first rate-limiting enzyme of glycolysis, requires its mitochondrial localization. Here, the authors show that SUMOylation of hexokinase 2 disrupts its binding to mitochondria and protects cells from tumorigenesis in prostate cancer.

An Update on MRMAssayDB: A Comprehensive Resource for Targeted Proteomics Assays in the Community

Precise multiplexed quantification of proteins in biological samples can be achieved by targeted proteomics using multiple or parallel reaction monitoring (MRM/PRM). Combined with internal standards, the method achieves very good repeatability and reproducibility enabling excellent protein quantification and allowing longitudinal and cohort studies. A laborious part of performing such experiments lies in the preparation steps dedicated to the development and validation of individual protein assays. Several public repositories host information on targeted proteomics assays, including NCI’s Clinical Proteomic Tumor Analysis Consortium assay portals, PeptideAtlas SRM Experiment Library, SRMAtlas, PanoramaWeb, and PeptideTracker, with all offering varying levels of details. We introduced MRMAssayDB in 2018 as an integrated resource for targeted proteomics assays. The Web-based application maps and links the assays from the repositories, includes comprehensive up-to-date protein and sequence annotations, and provides multiple visualization options on the peptide and protein level. We have extended MRMAssayDB with more assays and extensive annotations. Currently it contains >828 000 assays covering >51 000 proteins from 94 organisms, of which >17 000 proteins are present in >2400 biological pathways, and >48 000 mapping to >21 000 Gene Ontology terms. This is an increase of about four times the number of assays since introduction. We have expanded annotations of interaction, biological pathways, and disease associations. A newly added visualization module for coupled molecular structural annotation browsing allows the user to interactively examine peptide sequence and any known PTMs and disease mutations, and map all to available protein 3D structures. Because of its integrative approach, MRMAssayDB enables a holistic view of suitable proteotypic peptides and commonly used transitions in empirical data. Availability: http://mrmassaydb.proteincentre.com.

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.

Analysis of ovarian cancer cell secretome during epithelial to mesenchymal transition reveals a protein signature associated with advanced stages of ovarian tumors

Ovarian cancer (OvCA) is the most lethal neoplasia among gynecologic malignancies and faces high rates of new cases particularly in South America. In special, the High Grade Serous Ovarian Carcinoma (HGSC) presents very poor prognosis with deaths caused mainly by metastasis. Among several mechanisms involved in metastasis, the Epithelial to Mesenchymal Transition (EMT) molecular reprogramming represents a model for latest stages of cancer progression. EMT promotes important cellular changes in cellular adhesion and cell-cell communication, which particularly depends on the paracrine signaling from neighbor cells. Considering the importance of cellular communication during EMT and metastasis, here we analyzed the changes in the secretome of the ovarian cancer cell line Caov-3 induced to EMT by Epidermal Growth Factor (EGF). Using a combination of GEL-LC-MS/MS and stable isotopic metabolic labelling (SILAC), we identified up-regulated candidates during EMT as a starting point to identify relevant proteins for HGSC. Based on public databases, our candidate proteins were validated and prioritized for further analysis. Importantly, several of the protein candidates were associated with cellular vesicles, which are important to the cell-cell communication and metastasis. Furthermore, the association of candidate proteins with gene expression data uncovered a subset of proteins correlated with the mesenchymal subtype of ovarian cancer. Based on this relevant molecular signature for aggressive ovarian cancer, supported by protein and gene expression data, we developed a targeted proteomic method to evaluate individual OvCA clinical samples. The quantitative information obtained for 33 peptides, representative of 18 proteins, was able to segregate HGSC from other tumor types. Our study highlighted the richness of the secretome and EMT to reveal relevant proteins for HGSC, which could be used in further studies and larger patient cohorts as a potential stratification signature for ovarian cancer tumor that could guide clinical conduct for patient treatment.

The genetic proteome: Using genetics to inform the proteome of mycobacterial pathogens

Mycobacterial pathogens pose a sustained threat to human health. There is a critical need for new diagnostics, therapeutics, and vaccines targeting both tuberculous and nontuberculous mycobacterial species. Understanding the basic mechanisms used by diverse mycobacterial species to cause disease will facilitate efforts to design new approaches toward detection, treatment, and prevention of mycobacterial disease. Molecular, genetic, and biochemical approaches have been widely employed to define fundamental aspects of mycobacterial physiology and virulence. The recent expansion of genetic tools in mycobacteria has further increased the accessibility of forward genetic approaches. Proteomics has also emerged as a powerful approach to further our understanding of diverse mycobacterial species. Detection of large numbers of proteins and their modifications from complex mixtures of mycobacterial proteins is now routine, with efforts of quantification of these datasets becoming more robust. In this review, we discuss the “genetic proteome,” how the power of genetics, molecular biology, and biochemistry informs and amplifies the quality of subsequent analytical approaches and maximizes the potential of hypothesis-driven mycobacterial research. Published proteomics datasets can be used for hypothesis generation and effective post hoc supplementation to experimental data. Overall, we highlight how the integration of proteomics, genetic, molecular, and biochemical approaches can be employed successfully to define fundamental aspects of mycobacterial pathobiology.

Biomarkers of neonatal skin barrier adaptation reveal substantial differences compared to adult skin

BACKGROUND

The objective of this study was to measure skin characteristics in premature (PT), late preterm (LPT), and full-term (FT) neonates compared with adults at two times (T1, T2).

METHODS

Skin samples of 61 neonates and 34 adults were analyzed for protein biomarkers, natural moisturizing factor (NMF), and biophysical parameters. Infant groups were: <34 weeks (PT), 34-<37 weeks (LPT), and ≥37 weeks (FT).

RESULTS

Forty proteins were differentially expressed in FT infant skin, 38 in LPT infant skin, and 12 in PT infant skin compared with adult skin at T1. At T2, 40 proteins were differentially expressed in FT infants, 38 in LPT infants, and 54 in PT infants compared with adults. All proteins were increased at both times, except TMG3, S100A7, and PEBP1, and decreased in PTs at T1. The proteins are involved in filaggrin processing, protease inhibition/enzyme regulation, and antimicrobial function. Eight proteins were decreased in PT skin compared with FT skin at T1. LPT and FT proteins were generally comparable at both times. Total NMF was lower in infants than adults at T1, but higher in infants at T2.

CONCLUSIONS

Neonates respond to the physiological transitions at birth by upregulating processes that drive the production of lower pH of the skin and water-binding NMF components, prevent protease activity leading to desquamation, and increase the barrier antimicrobial properties.

IMPACT

Neonates respond to the transitions at birth by upregulating processes that drive the production of lower pH of the skin and NMF, prevent protease activity leading to desquamation, and increase the antimicrobial properties of the barrier. The neonatal epidermal barrier exhibits a markedly different array of protein biomarkers both shortly after birth and 2-3 months later, which are differentially expressed versus adults. The major biomarker-functional classes included filaggrin processing, protease inhibitor/enzyme regulators, antimicrobials, keratins, lipids, and cathepsins. The findings will guide improvement of infant skin care practices, particularly for the most premature infants with the ultimate goals mitigating nosocomial infection.

Absolute quantification of transcription factors in human erythropoiesis using selected reaction monitoring mass spectrometry

Quantitative changes in transcription factor (TF) abundance regulate dynamic cellular processes, including cell fate decisions. Protein copy number provides information about the relative stoichiometry of TFs that can be used to determine how quantitative changes in TF abundance influence gene regulatory networks. In this protocol, we describe a targeted selected reaction monitoring (SRM)-based mass-spectrometry method to systematically measure the absolute protein concentration of nuclear TFs as human hematopoietic stem and progenitor cells differentiate along the erythropoietic lineage.

For complete details on the use and execution of this protocol, please refer to Gillespie et al. (2020).

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Protocol for absolute quantification of TFs in human erythropoiesis

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Selected reaction monitoring mass-spectrometry parameters for each peptide

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Validated SRM assays corresponding to >100 TFs

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Copy number reveals the relative stoichiometries of TFs during erythropoiesis

Proteomic Analysis of Chr 18 Proteins Using 2D Fractionation

One of the main goals of the Chromosome-Centric Human Proteome Project (C-HPP) is detection of "missing proteins" (PE2-PE4). Using the UPS2 (Universal proteomics standard 2) set as a model to simulate the range of protein concentrations in the cell, we have previously shown that 2D fractionation enables the detection of more than 95% of UPS2 proteins in a complex biological mixture. In this study, we propose a novel experimental workflow for protein detection during the analysis of biological samples. This approach is extremely important in the context of the C-HPP and the neXt-MP50 Challenge, which can be solved by increasing the sensitivity and the coverage of the proteome encoded by a particular human chromosome. In this study, we used 2D fractionation for in-depth analysis of the proteins encoded by human chromosome 18 (Chr 18) in the HepG2 cell line. Use of 2D fractionation increased the sensitivity of the SRM SIS method by 1.3-fold (68 and 88 proteins were identified by 1D fractionation and 2D fractionation, respectively) and the shotgun MS/MS method by 2.5-fold (21 and 53 proteins encoded by Chr 18 were detected by 1D fractionation and 2D fractionation, respectively). The results of all experiments indicate that 111 proteins encoded by human Chr 18 have been identified; this list includes 42% of the Chr 18 protein-coding genes and 67% of the Chr 18 transcriptome species (Illumina RNaseq) in the HepG2 cell line obtained using a single sample. Corresponding mRNAs were not registered for 13 of the detected proteins. The combination of 2D fractionation technology with SRM SIS and shotgun mass spectrometric analysis did not achieve full coverage, i.e., identification of at least one protein product for each of the 265 protein-coding genes of the selected chromosome. To further increase the sensitivity of the method, we plan to use 5-10 crude synthetic peptides for each protein to identify the proteins and select one of the peptides based on the obtained mass spectra for the synthesis of an isotopically labeled standard for subsequent quantitative analysis. Data are available via ProteomeXchange with the identifier PXD019263.

A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS

Data-Independent Acquisition (DIA) is a method to improve consistent identification and precise quantitation of peptides and proteins by mass spectrometry (MS). The targeted data analysis strategy in DIA relies on spectral assay libraries that are generally derived from a priori measurements of peptides for each species. Although Escherichia coli (E. coli) is among the best studied model organisms, so far there is no spectral assay library for the bacterium publicly available. Here, we generated a spectral assay library for 4,014 of the 4,389 annotated E. coli proteins using one- and two-dimensional fractionated samples, and ion mobility separation enabling deep proteome coverage. We demonstrate the utility of this high-quality library with robustness in quantitation of the E. coli proteome and with rapid-chromatography to enhance throughput by targeted DIA-MS. The spectral assay library supports the detection and quantification of 91.5% of all E. coli proteins at high-confidence with 56,182 proteotypic peptides, making it a valuable resource for the scientific community. Data and spectral libraries are available via ProteomeXchange (PXD020761, PXD020785) and SWATHAtlas (SAL00222-28).

Proteomics and Informatics for Understanding Phases and Identifying Biomarkers in COVID-19 Disease

The emergence of novel coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 coronavirus, has necessitated the urgent development of new diagnostic and therapeutic strategies. Rapid research and development, on an international scale, has already generated assays for detecting SARS-CoV-2 RNA and host immunoglobulins. However, the complexities of COVID-19 are such that fuller definitions of patient status, trajectory, sequelae, and responses to therapy are now required. There is accumulating evidence-from studies of both COVID-19 and the related disease SARS-that protein biomarkers could help to provide this definition. Proteins associated with blood coagulation (D-dimer), cell damage (lactate dehydrogenase), and the inflammatory response (e.g., C-reactive protein) have already been identified as possible predictors of COVID-19 severity or mortality. Proteomics technologies, with their ability to detect many proteins per analysis, have begun to extend these early findings. To be effective, proteomics strategies must include not only methods for comprehensive data acquisition (e.g., using mass spectrometry) but also informatics approaches via which to derive actionable information from large data sets. Here we review applications of proteomics to COVID-19 and SARS and outline how pipelines involving technologies such as artificial intelligence could be of value for research on these diseases.

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.

DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics

Data-independent acquisition (DIA) mass spectrometry, also known as Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH), is a popular label-free proteomics strategy to comprehensively quantify peptides/proteins utilizing mass spectral libraries to decipher inherently multiplexed spectra collected linearly across a mass range. Although there are many spectral libraries produced worldwide, the quality control of these libraries is lacking. We present the DIALib-QC (DIA library quality control) software tool for the systematic evaluation of a library’s characteristics, completeness and correctness across 62 parameters of compliance, and further provide the option to improve its quality. We demonstrate its utility in assessing and repairing spectral libraries for correctness, accuracy and sensitivity.

Most data-independent acquisition (DIA) methods depend on mass spectral libraries for peptide identification but tools to assess library quality are lacking. Here, the authors develop DIALib- QC for the systematic evaluation and correction of spectral libraries.

Verification of a Blood-Based Targeted Proteomics Signature for Malignant Pleural Mesothelioma

BACKGROUND

We have verified a mass spectrometry (MS)-based targeted proteomics signature for the detection of malignant pleural mesothelioma (MPM) from the blood.

METHODS

A seven-peptide biomarker MPM signature by targeted proteomics in serum was identified in a previous independent study. Here, we have verified the predictive accuracy of a reduced version of that signature, now composed of six-peptide biomarkers. We have applied liquid chromatography-selected reaction monitoring (LC-SRM), also known as multiple-reaction monitoring (MRM), for the investigation of 402 serum samples from 213 patients with MPM and 189 cancer-free asbestos-exposed donors from the United States, Australia, and Europe.

RESULTS

Each of the biomarkers composing the signature was independently informative, with no apparent functional or physical relation to each other. The multiplexing possibility offered by MS proteomics allowed their integration into a single signature with a higher discriminating capacity than that of the single biomarkers alone. The strategy allowed in this way to increase their potential utility for clinical decisions. The signature discriminated patients with MPM and asbestos-exposed donors with AUC of 0.738. For early-stage MPM, AUC was 0.765. This signature was also prognostic, and Kaplan-Meier analysis showed a significant difference between high- and low-risk groups with an HR of 1.659 (95% CI, 1.075-2.562; P = 0.021).

CONCLUSIONS

Targeted proteomics allowed the development of a multianalyte signature with diagnostic and prognostic potential for MPM from the blood.

IMPACT

The proteomic signature represents an additional diagnostic approach for informing clinical decisions for patients at risk for MPM.

A photocleavable peptide-tagged mass probe for chemical mapping of epidermal growth factor receptor 2 (HER2) in human cancer cells

Human epidermal growth factor receptor 2 (HER2) testing has great value for cancer diagnosis, prognosis and treatment selection. However, the clinical utility of HER2 is frequently tempered by the uncertainty regarding the accuracy of the methods currently available to assess HER2. The development of novel methods for accurate HER2 testing is in great demand. Considering the visualization features of in situ imaging and the quantitative capability of mass spectrometry, integration of the two components into a molecular mapping approach has attracted increasing interest. In this work, we reported an integrated chemical mapping approach using a photocleavable peptide-tagged mass probe for HER2 detection. The probe consists of four functional domains, including the recognition unit of an aptamer to catch HER2, a fluorescent dye moiety (FITC) for fluorescence imaging, a reporter peptide for mass spectrometric quantification, and a photocleavable linker for peptide release. After characterization of this novel probe (e.g., conjugation efficiency, binding affinity and specificity, and photolysis release efficiency), the probe binding and photolysis release conditions were optimized. Then, fluorescence images were collected, and the released reporter peptide after photolysis was quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A limit of quantification (LOQ) of 25 pM was obtained, which very well meets the requirements for clinical laboratory testing. Finally, the developed assay was applied for HER2 testing in four breast cancer cell lines and 42 pairs of human breast primary tumors and adjacent normal tissue samples. Overall, this integrated approach based on a photocleavable peptide-tagged mass probe can provide chemical mapping including both quantitative and visual information of HER2 reliably and consistently, and may pave the way for clinical applications in a more accurate manner.

NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses

Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between different charge-states of the same peptide, different peptides belonging to the same proteins, and individual proteins participating protein complexes and functional interactions. We applied NAguideR into three label-free proteomic datasets featuring peptide-level, protein-level, and phosphoproteomic variables respectively, all generated by data independent acquisition mass spectrometry (DIA-MS) with substantial biological replicates. The results indicate that NAguideR is able to discriminate the optimal imputation methods that are facilitating DIA-MS experiments over those sub-optimal and low-performance algorithms. NAguideR further provides downloadable tables and figures supporting flexible data analysis and interpretation. NAguideR is freely available at http://www.omicsolution.org/wukong/NAguideR/ and the source code: https://github.com/wangshisheng/NAguideR/.

Combined Targeted Proteomics and Oxylipin Metabolomics for Monitoring of the COX-2 Pathway

The important role of inducible cyclooxygenase-2 (COX-2) in several diseases necessitates analytical tools enabling thorough understanding of its modulation. Analysis of a comprehensive oxylipin pattern provides detailed information about changes in enzyme activities. In order to simultaneously monitor gene expression levels, a targeted proteomics method for human COX-2 is developed. With limits of detection and quantification down to 0.25 and 0.5 fmol (on column) the method enables sensitive quantitative analysis via LC-MS/MS within a linear range up to 2.5 pmol. Three housekeeping proteins are included in the method for data normalization. A tiered approach for method development comprised of in silico and experimental steps is described for choosing unique peptides and selective and sensitive SRM transitions while avoiding isobaric interferences. This method combined with a well-established targeted oxylipin metabolomics method allows to investigate the role of COX-2 in the human colon carcinoma cell lines HCT-116, HT-29, and HCA-7. Moreover, the developed methodology is used to demonstrate the time-dependent prostanoid formation and COX-2 enzyme synthesis in lipopolysaccharide-stimulated human primary macrophages. The described approach is a helpful tool which will be further used as standard operation procedure, ultimately aiming at comprehensive targeted proteomics/oxylipin metabolomics strategies to examine the entire arachidonic acid cascade.

Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics

We introduce STAMPS, a pathway-centric web service for the development of targeted proteomics assays. STAMPS guides the user by providing several intuitive interfaces for a rapid and simplified method design. Applying our curated framework to signaling and metabolic pathways, we reduced the average assay development time by a factor of ∼150 and revealed that the insulin signaling is actively controlled by protein abundance changes in insulin-sensitive and -resistance states. Although at the current state STAMPS primarily contains mouse data, it was designed for easy extension with additional organisms.

The status of proteomics as we enter the 2020s: Towards personalised/precision medicine

The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.

Bioluminescent Sensor Reveals that Carboxylesterase 1A is a Novel Endoplasmic Reticulum-Derived Serologic Indicator for Hepatocyte Injury

Discovery of novel liver injury indicators and development of practical assays to detect target indicator(s) would strongly facilitate the diagnosis of liver disorders. Herein, an alternative biomarker discovery strategy was applied to find suitable endoplasmic reticulum-resident protein(s) as serologic indicator(s) for hepatocyte injury via analysis of the human proteome database among plasma and various organs. Both database searching and preliminary experiments suggested that human carboxylesterase 1A (CES1A), one of the most abundant and hepatic-restricted proteins, could serve as a good serologic indicator for hepatocyte injury. Then, a highly selective and practical bioluminescent sensor was developed for real-time sensing of CES1A in various biological systems including plasma. With the help of this bioluminescent sensor, the release of hepatic CES1A into the extracellular medium or the circulation system could be directly monitored. Further investigations demonstrated that serum activity levels of CES1A were elevated dramatically in mice with liver injury or patients with liver diseases. Collectively, this study provided solid evidence to support that CES1A was a novel serological indicator for hepatocyte injury. Furthermore, the strategy used in this study paved a new way for the rational discovery of practical indicators to monitor the dynamic progression of injury in a given tissue or organ.

Expanding beyond ICP-MS to better understand selenium biochemistry

Selenium is an essential trace element in human health and therefore its concentration in biological samples (biofluids and tissues) is used as an indicator of health and nutritional status. In humans, selenium's biological activity occurs through the 25 identified selenoproteins. As total selenium concentration encompasses both functional selenoproteins, small selenocompounds and other selenium-binding proteins, selenium speciation, rather than total concentration, is critical in order to assess functional selenium. Previously, quantitative analysis of selenoproteins required laborious techniques that were often slow and costly. However, more recent advancements in tandem mass spectrometry have facilitated the qualitative and quantitative identification of these proteins. In light of the current alternatives for understanding selenium biochemistry, we aim to provide a review of the modern applications of electrospray ionisation mass spectrometry (ESI-MS) as an alternative to inductively coupled plasma mass spectrometry (ICP-MS) for qualitative and quantitative selenium speciation.

Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies

Sequences of the genomes of all-important bacterial pathogens of man, plants, and animals have been completed. Still, it is not enough to achieve complete information of all the mechanisms controlling the biological processes of an organism. Along with all advances in different proteomics technologies, proteomics has completed our knowledge of biological processes all around the world. Proteomics is a valuable technique to explain the complement of proteins in any organism. One of the fields that has been notably benefited from other systems approaches is bacterial pathogenesis. An emerging field is to use proteomics to examine the infectious agents in terms of, among many, the response the host and pathogen to the infection process, which leads to a deeper knowledge of the mechanisms of bacterial virulence. This trend also enables us to identify quantitative measurements for proteins extracted from microorganisms. The present review study is an attempt to summarize a variety of different proteomic techniques and advances. The significant applications in bacterial pathogenesis studies are also covered. Moreover, the areas where proteomics may lead the future studies are introduced.

Mass Spectrometry of Human Transporters

Transporters are key to understanding how an individual will respond to a particular dose of a drug. Two patients with similar systemic concentrations may have quite different local concentrations of a drug at the required site. The transporter profile of any individual depends upon a variety of genetic and environmental factors, including genotype, age, and diet status. Robust models (virtual patients) are therefore required and these models are data hungry. Necessary data include quantitative transporter profiles at the relevant organ. Liquid chromatography with tandem mass spectrometry (LC-MS/MS) is currently the most powerful method available for obtaining this information. Challenges include sourcing the tissue, isolating the hydrophobic membrane-embedded transporter proteins, preparing the samples for MS (including proteolytic digestion), choosing appropriate quantification methodology, and optimizing the LC-MS/MS conditions. Great progress has been made with all of these, especially within the last few years, and is discussed here.

Absolute Quantification of Transcription Factors Reveals Principles of Gene Regulation in Erythropoiesis

Dynamic cellular processes such as differentiation are driven by changes in the abundances of transcription factors (TFs). However, despite years of studies, our knowledge about the protein copy number of TFs in the nucleus is limited. Here, by determining the absolute abundances of 103 TFs and co-factors during the course of human erythropoiesis, we provide a dynamic and quantitative scale for TFs in the nucleus. Furthermore, we establish the first gene regulatory network of cell fate commitment that integrates temporal protein stoichiometry data with mRNA measurements. The model revealed quantitative imbalances in TFs' cross-antagonistic relationships that underlie lineage determination. Finally, we made the surprising discovery that, in the nucleus, co-repressors are dramatically more abundant than co-activators at the protein level, but not at the RNA level, with profound implications for understanding transcriptional regulation. These analyses provide a unique quantitative framework to understand transcriptional regulation of cell differentiation in a dynamic context.

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

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

Salivary proteome signatures in the early and middle stages of human pregnancy with term birth outcome

The establishment and maintenance of pregnancy in humans proceed through a continuous change of biochemical and biophysical processes. It requires a constant interaction between the fetus and the maternal system. The present prospective study aims to elucidate changes in salivary proteome from the early to middle stages of term pregnancy, and establishing an expressional trajectory for modulated proteins. To date, a comprehensive characterization of the longitudinal salivary proteome in pregnancy has not been performed and it is our immediate interest. In the discovery phase, maternal saliva (N = 20) at 6–13, 18–21, and 26–29 weeks of gestation was analyzed using level-free proteomics (SWATH-MS) approach. The expression levels of 65 proteins were found to change significantly with gestational age and distributed into two distinct clusters with a unique expression trajectory. The results revealed that altered proteins are involved in maternal immune modulation, metabolism, and host defense mechanism. Further, verification of 12 proteins was employed using targeted mass spectrometry (MRM-MS) in a separate subset of saliva (N = 14). The MRM results of 12 selected proteins confirmed a similar expression pattern as in SWATH-MS analysis. Overall, the results not only demonstrate the longitudinal maternal saliva proteome for the first time but also set the groundwork for comparative analysis between term birth and adverse pregnancy outcomes.

Mapping the Human Kinome in Response to DNA Damage

We provide a catalog for the effects of the human kinome on cell survival in response to DNA-damaging agents, covering all major DNA repair pathways. By treating 313 kinase-deficient cell lines with ten diverse DNA-damaging agents, including seven commonly used chemotherapeutics, we identified examples of vulnerability and resistance that are kinase specific. To investigate synthetic lethal interactions, we tested the response to carmustine for 25 cell lines by establishing a phenotypic fluorescence-activated cell sorting (FACS) assay designed to validate gene-drug interactions. We show apoptosis, cell cycle changes, and DNA damage and proliferation after alkylation- or crosslink-induced damage. In addition, we reconstitute the cellular sensitivity of DYRK4, EPHB6, MARK3, and PNCK as a proof of principle for our study. Furthermore, using global phosphoproteomics on cells lacking MARK3, we provide evidence for its role in the DNA damage response. Our data suggest that cancers with inactivating mutations in kinases, including MARK3, are particularly vulnerable to alkylating chemotherapeutic agents.

Comparative lipidomics of 5-Fluorouracil-sensitive and -resistant colorectal cancer cells reveals altered sphingomyelin and ceramide controlled by acid sphingomyelinase (SMPD1)

5-Fluorouracil (5-FU) is a chemotherapeutic drug widely used to treat colorectal cancer. 5-FU is known to gradually lose its efficacy in treating colorectal cancer following the acquisition of resistance. We investigated the mechanism of 5-FU resistance using comprehensive lipidomic approaches. We performed lipidomic analysis on 5-FU–resistant (DLD-1/5-FU) and -sensitive (DLD-1) colorectal cancer cells using MALDI-MS and LC-MRM-MS. In particular, sphingomyelin (SM) species were significantly up-regulated in 5-FU–resistant cells in MALDI-TOF analysis. Further, we quantified sphingolipids including SM and Ceramide (Cer) using Multiple Reaction Monitoring (MRM), as they play a vital role in drug resistance. We found that 5-FU resistance in DLD-1/5-FU colorectal cancer cells was mainly associated with SM increase and Cer decrease, which are controlled by acid sphingomyelinase (SMPD1). In addition, reduction of SMPD1 expression was confirmed by LC-MRM-MS analysis and the effect of SMPD1 in drug resistance was assessed by treating DLD-1 cells with siRNA-SMPD1. Furthermore, clinical colorectal cancer data set analysis showed that down-regulation of SMPD1 was associated with resistance to chemotherapy regimens that include 5-FU. Thus, from our study, we propose that SM/Cer and SMPD1 are new potential target molecules for therapeutic strategies to overcome 5-FU resistance.

A proteomics outlook towards the elucidation of epithelial-mesenchymal transition molecular events

The main cause of death in cancer is the spread, or metastasis, of cancer cells to distant organs with consequent tumor formation. Additionally, metastasis is a process that demands special attention, as the cellular transformations make cancer at this stage very difficult or occasionally even impossible to be cured. The main process that converts epithelial tumor cells to mesenchymal-like metastatic cells is the Epithelial to Mesenchymal Transition (EMT). This process allows stationary and polarized epithelial cells, which are connected laterally to several types of junctions as well as the basement membrane, to undergo multiple biochemical changes that enable disruption of cell-cell adherence and apical-basal polarity. Moreover, the cells undergo important reprogramming to remodel the cytoskeleton and acquire mesenchymal characteristics such as enhanced migratory capacity, invasiveness, elevated resistance to apoptosis and a large increase in the production of ECM components. As expected, the alterations of the protein complement are extensive and complex, and thus exploring this by proteomic approaches is of particular interest. Here we review the overall findings of proteome modifications during EMT, mainly focusing on molecular signatures observed in multiple proteomic studies as well as coordinated pathways, cellular processes and their clinical relevance for altered proteins. As a result, an interesting set of proteins is highlighted as potential targets to be further investigated in the context of EMT, metastasis and cancer progression.

Hybrid Spectral Library Combining DIA-MS Data and a Targeted Virtual Library Substantially Deepens the Proteome Coverage

Data-independent acquisition mass spectrometry (DIA-MS) is a powerful technique that enables relatively deep proteomic profiling with superior quantification reproducibility. DIA data mining predominantly relies on a spectral library of sufficient proteome coverage that, in most cases, is built on data-dependent acquisition-based analysis of the same sample. To expand the proteome coverage for a pre-determined protein family, we report herein on the construction of a hybrid spectral library that supplements a DIA experiment-derived library with a protein family-targeted virtual library predicted by deep learning. Leveraging this DIA hybrid library substantially deepens the coverage of three transmembrane protein families (G protein-coupled receptors, ion channels, and transporters) in mouse brain tissues with increases in protein identification of 37%–87% and peptide identification of 58%–161%. Moreover, of the 412 novel GPCR peptides exclusively identified with the DIA hybrid library strategy, 53.6% were validated as present in mouse brain tissues based on orthogonal experimental measurement.

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A virtual library is built for a selected protein family using deep learning models

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The hybrid library strategy vastly deepens the coverage for the targeted protein family

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About 53.6% of novel GPCR peptides identified with the DIA hybrid library are validated

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Extend the strategy to deep mapping of multiple transmembrane protein families

Mass spectrometry-based protein identification in proteomics-a review

Statistically, accurate protein identification is a fundamental cornerstone of proteomics and underpins the understanding and application of this technology across all elements of medicine and biology. Proteomics, as a branch of biochemistry, has in recent years played a pivotal role in extending and developing the science of accurately identifying the biology and interactions of groups of proteins or proteomes. Proteomics has primarily used mass spectrometry (MS)-based techniques for identifying proteins, although other techniques including affinity-based identifications still play significant roles. Here, we outline the basics of MS to understand how data are generated and parameters used to inform computational tools used in protein identification. We then outline a comprehensive analysis of the bioinformatics and computational methodologies used in protein identification in proteomics including discussing the most current communally acceptable metrics to validate any identification.

PIKES Analysis Reveals Response to Degraders and Key Regulatory Mechanisms of the CRL4 Network

Co-opting Cullin4 RING ubiquitin ligases (CRL4s) to inducibly degrade pathogenic proteins is emerging as a promising therapeutic strategy. Despite intense efforts to rationally design degrader molecules that co-opt CRL4s, much about the organization and regulation of these ligases remains elusive. Here, we establish protein interaction kinetics and estimation of stoichiometries (PIKES) analysis, a systematic proteomic profiling platform that integrates cellular engineering, affinity purification, chemical stabilization, and quantitative mass spectrometry to investigate the dynamics of interchangeable multiprotein complexes. Using PIKES, we show that ligase assemblies of Cullin4 with individual substrate receptors differ in abundance by up to 200-fold and that Cand1/2 act as substrate receptor exchange factors. Furthermore, degrader molecules can induce the assembly of their cognate CRL4, and higher expression of the associated substrate receptor enhances degrader potency. Beyond the CRL4 network, we show how PIKES can reveal systems level biochemistry for cellular protein networks important to drug development.

The Wonderful World of Poo: The Turdome and Beyond

Defecate: it is something we all do, it is something we joke about, yet for many in real life it is a subject that is taboo. However, it is now being realised that faeces are a veritable scientific goldmine, have many potential uses, and may even save your life! In this article I will review the history behind the use of faecal material and look at some of its emerging playing fields, in particular its role in medical diagnosis. I will discuss faecal proteomics and other omics technologies (Proteogenomics: The Omics Pipeline), including studies on the microbiome, in order to understand, diagnose, and treat gastrointestinal tract pathologies and other diseases, and show how these technologies will play a role in the move towards personalized medicine.

Engineered ChymotrypsiN for Mass Spectrometry-Based Detection of Protein Glycosylation

We have engineered the substrate specificity of chymotrypsin to cleave after Asn by high-throughput screening of large libraries created by comprehensive remodeling of the substrate binding pocket. The engineered variant (chymotrypsiN, ChyB-Asn) demonstrated an altered substrate specificity with an expanded preference for Asn-containing substrates. We confirmed that protein engineering did not compromise the stability of the enzyme by biophysical characterization. Comparison of wild-type ChyB and ChyB-Asn in profiling lysates of HEK293 cells demonstrated both qualitative and quantitative differences in the nature of the peptides and proteins identified by liquid chromatography and tandem mass spectrometry. ChyB-Asn enabled the identification of partially glycosylated Asn sites within a model glycoprotein and in the extracellular proteome of Jurkat T cells. ChymotrypsiN is a valuable addition to the toolkit of proteases to aid the mapping of N-linked glycosylation sites within proteins and proteomes.

Measurement of Organ-Specific and Acute-Phase Blood Protein Levels in Early Lyme Disease

Lyme disease results from infection of humans with the spirochete Borrelia burgdorferi. The first and most common clinical manifestation is the circular, inflamed skin lesion referred to as erythema migrans; later manifestations result from infections of other body sites. Laboratory diagnosis of Lyme disease can be challenging in patients with erythema migrans because of the time delay in the development of specific diagnostic antibodies against Borrelia. Reliable blood biomarkers for the early diagnosis of Lyme disease in patients with erythema migrans are needed. Here, we performed selected reaction monitoring, a targeted mass spectrometry-based approach, to measure selected proteins that (1) are known to be predominantly expressed in one organ (i.e., organ-specific blood proteins) and whose blood concentrations may change as a result of Lyme disease, or (2) are involved in acute immune responses. In a longitudinal cohort of 40 Lyme disease patients and 20 healthy controls, we identified 10 proteins with significantly altered serum levels in patients at the time of diagnosis, and we also developed a 10-protein panel identified through multivariate analysis. In an independent cohort of patients with erythema migrans, six of these proteins, APOA4, C9, CRP, CST6, PGLYRP2, and S100A9, were confirmed to show significantly altered serum levels in patients at time of presentation. Nine of the 10 proteins from the multivariate panel were also verified in the second cohort. These proteins, primarily innate immune response proteins or proteins specific to liver, skin, or white blood cells, may serve as candidate blood biomarkers requiring further validation to aid in the laboratory diagnosis of early Lyme disease.

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

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

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0

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

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.