Organ and cell-specific biomarkers of Long-COVID identified with targeted proteomics and machine learning.

BACKGROUND: Survivors of acute COVID-19 often suffer prolonged, diffuse symptoms post-infection, referred to as "Long-COVID". A lack of Long-COVID biomarkers and pathophysiological mechanisms limits effective diagnosis, treatment and disease surveillance. We performed targeted proteomics and machine learning analyses to identify novel blood biomarkers of Long-COVID. METHODS: A case-control study comparing the expression of 2925 unique blood proteins in Long-COVID outpatients versus COVID-19 inpatients and healthy control subjects. Targeted proteomics was accomplished with proximity extension assays, and machine learning was used to identify the most important proteins for identifying Long-COVID patients. Organ system and cell type expression patterns were identified with Natural Language Processing (NLP) of the UniProt Knowledgebase. RESULTS: Machine learning analysis identified 119 relevant proteins for differentiating Long-COVID outpatients (Bonferonni corrected P < 0.01). Protein combinations were narrowed down to two optimal models, with nine and five proteins each, and with both having excellent sensitivity and specificity for Long-COVID status (AUC = 1.00, F1 = 1.00). NLP expression analysis highlighted the diffuse organ system involvement in Long-COVID, as well as the involved cell types, including leukocytes and platelets, as key components associated with Long-COVID. CONCLUSIONS: Proteomic analysis of plasma from Long-COVID patients identified 119 highly relevant proteins and two optimal models with nine and five proteins, respectively. The identified proteins reflected widespread organ and cell type expression. Optimal protein models, as well as individual proteins, hold the potential for accurate diagnosis of Long-COVID and targeted therapeutics.

Targeted proteomics identifies circulating biomarkers associated with active COVID-19 and post-COVID-19.

The ongoing Coronavirus Disease 2019 (COVID-19) pandemic is caused by the highly infectious Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). There is an urgent need for biomarkers that will help in better stratification of patients and contribute to personalized treatments. We performed targeted proteomics using the Olink platform and systematically investigated protein concentrations in 350 hospitalized COVID-19 patients, 186 post-COVID-19 individuals, and 61 healthy individuals from 3 independent cohorts. Results revealed a signature of acute SARS-CoV-2 infection, which is represented by inflammatory biomarkers, chemokines and complement-related factors. Furthermore, the circulating proteome is still significantly affected in post-COVID-19 samples several weeks after infection. Post-COVID-19 individuals are characterized by upregulation of mediators of the tumor necrosis (TNF)-α signaling pathways and proteins related to transforming growth factor (TGF)-ß. In addition, the circulating proteome is able to differentiate between patients with different COVID-19 disease severities, and is associated with the time after infection. These results provide important insights into changes induced by SARS-CoV-2 infection at the proteomic level by integrating several cohorts to obtain a large disease spectrum, including variation in disease severity and time after infection. These findings could guide the development of host-directed therapy in COVID-19.

Mass Spectrometry Multiplexed Detection of SARS-CoV-2.

Testing of large populations for virus infection is now a reality worldwide due to the coronavirus (SARS-CoV-2) pandemic. The demand for SARS-CoV-2 testing using alternatives other than PCR led to the development of mass spectrometry (MS)-based assays. However, MS for SARS-CoV-2 large-scale testing have some downsides, including complex sample preparation and slow data analysis. Here, we describe a high-throughput targeted proteomics method to detect SARS-CoV-2 directly from nasopharyngeal and oropharyngeal swabs. This strategy employs fully automated sample preparation mediated by magnetic particles, followed by detection of SARS-CoV-2 nucleoprotein peptides by turbulent flow chromatography coupled with tandem mass spectrometry.

A multiplex protein panel assay for severity prediction and outcome prognosis in patients with COVID-19: An observational multi-cohort study.

Background: Global healthcare systems continue to be challenged by the COVID-19 pandemic, and there is a need for clinical assays that can help optimise resource allocation, support treatment decisions, and accelerate the development and evaluation of new therapies. Methods: We developed a multiplexed proteomics assay for determining disease severity and prognosis in COVID-19. The assay quantifies up to 50 peptides, derived from 30 known and newly introduced COVID-19-related protein markers, in a single measurement using routine-lab compatible analytical flow rate liquid chromatography and multiple reaction monitoring (LC-MRM). We conducted two observational studies in patients with COVID-19 hospitalised at Charité - Universitätsmedizin Berlin, Germany before (from March 1 to 26, 2020, n=30) and after (from April 4 to November 19, 2020, n=164) dexamethasone became standard of care. The study is registered in the German and the WHO International Clinical Trials Registry (DRKS00021688). Findings: The assay produces reproducible (median inter-batch CV of 10.9%) absolute quantification of 47 peptides with high sensitivity (median LLOQ of 143 ng/ml) and accuracy (median 96.8%). In both studies, the assay reproducibly captured hallmarks of COVID-19 infection and severity, as it distinguished healthy individuals, mild, moderate, and severe COVID-19. In the post-dexamethasone cohort, the assay predicted survival with an accuracy of 0.83 (108/130), and death with an accuracy of 0.76 (26/34) in the median 2.5 weeks before the outcome, thereby outperforming compound clinical risk assessments such as SOFA, APACHE II, and ABCS scores. Interpretation: Disease severity and clinical outcomes of patients with COVID-19 can be stratified and predicted by the routine-applicable panel assay that combines known and novel COVID-19 biomarkers. The prognostic value of this assay should be prospectively assessed in larger patient cohorts for future support of clinical decisions, including evaluation of sample flow in routine setting. The possibility to objectively classify COVID-19 severity can be helpful for monitoring of novel therapies, especially in early clinical trials. Funding: This research was funded in part by the European Research Council (ERC) under grant agreement ERC-SyG-2020 951475 (to M.R) and by the Wellcome Trust (IA 200829/Z/16/Z to M.R.). The work was further supported by the Ministry of Education and Research (BMBF) as part of the National Research Node 'Mass Spectrometry in Systems Medicine (MSCoresys)', under grant agreements 031L0220 and 161L0221. J.H. was supported by a Swiss National Science Foundation (SNSF) Postdoc Mobility fellowship (project number 191052). This study was further supported by the BMBF grant NaFoUniMedCOVID-19 - NUM-NAPKON, FKZ: 01KX2021. The study was co-funded by the UK's innovation agency, Innovate UK, under project numbers 75594 and 56328.

Mass spectrometry-based proteomic platforms for better understanding of SARS-CoV-2 induced pathogenesis and potential diagnostic approaches.

While protein-protein interaction is the first step of the SARS-CoV-2 infection, recent comparative proteomic profiling enabled the identification of over 11,000 protein dynamics, thus providing a comprehensive reflection of the molecular mechanisms underlying the cellular system in response to viral infection. Here we summarize and rationalize the results obtained by various mass spectrometry (MS)-based proteomic approaches applied to the functional characterization of proteins and pathways associated with SARS-CoV-2-mediated infections in humans. Comparative analysis of cell-lines versus tissue samples indicates that our knowledge in proteome profile alternation in response to SARS-CoV-2 infection is still incomplete and the tissue-specific response to SARS-CoV-2 infection can probably not be recapitulated efficiently by in vitro experiments. However, regardless of the viral infection period, sample types, and experimental strategies, a thorough cross-comparison of the recently published proteome, phosphoproteome, and interactome datasets led to the identification of a common set of proteins and kinases associated with PI3K-Akt, EGFR, MAPK, Rap1, and AMPK signaling pathways. Ephrin receptor A2 (EPHA2) was identified by 11 studies including all proteomic platforms, suggesting it as a potential future target for SARS-CoV-2 infection mechanisms and the development of new therapeutic strategies. We further discuss the potentials of future proteomics strategies for identifying prognostic SARS-CoV-2 responsive age-, gender-dependent, tissue-specific protein targets.

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.

Mass spectrometry-based proteomics in basic and translational research of SARS-CoV-2 coronavirus and its emerging mutants.

Molecular diagnostics of the coronavirus disease of 2019 (COVID-19) now mainly relies on the measurements of viral RNA by RT-PCR, or detection of anti-viral antibodies by immunoassays. In this review, we discussed the perspectives of mass spectrometry-based proteomics as an analytical technique to identify and quantify proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and to enable basic research and clinical studies on COVID-19. While RT-PCR and RNA sequencing are indisputably powerful techniques for the detection of SARS-CoV-2 and identification of the emerging mutations, proteomics may provide confirmatory diagnostic information and complimentary biological knowledge on protein abundance, post-translational modifications, protein-protein interactions, and the functional impact of the emerging mutations. Pending advances in sensitivity and throughput of mass spectrometry and liquid chromatography, shotgun and targeted proteomic assays may find their niche for the differential quantification of viral proteins in clinical and environmental samples. Targeted proteomic assays in combination with immunoaffinity enrichments also provide orthogonal tools to evaluate cross-reactivity of serology tests and facilitate development of tests with the nearly perfect diagnostic specificity, this enabling reliable testing of broader populations for the acquired immunity. The coronavirus pandemic of 2019-2021 is another reminder that the future global pandemics may be inevitable, but their impact could be mitigated with the novel tools and assays, such as mass spectrometry-based proteomics, to enable continuous monitoring of emerging viruses, and to facilitate rapid response to novel infectious diseases.

Proteomics: A Tool to Study Platelet Function.

Platelets are components of the blood that are highly reactive, and they quickly respond to multiple physiological and pathophysiological processes. In the last decade, it became clear that platelets are the key components of circulation, linking hemostasis, innate, and acquired immunity. Protein composition, localization, and activity are crucial for platelet function and regulation. The current state of mass spectrometry-based proteomics has tremendous potential to identify and quantify thousands of proteins from a minimal amount of material, unravel multiple post-translational modifications, and monitor platelet activity during drug treatments. This review focuses on the role of proteomics in understanding the molecular basics of the classical and newly emerging functions of platelets. including the recently described role of platelets in immunology and the development of COVID-19.The state-of-the-art proteomic technologies and their application in studying platelet biogenesis, signaling, and storage are described, and the potential of newly appeared trapped ion mobility spectrometry (TIMS) is highlighted. Additionally, implementing proteomic methods in platelet transfusion medicine, and as a diagnostic and prognostic tool, is discussed.

Perspective on Proteomics for Virus Detection in Clinical Samples.

One of the most widely used methods to detect an acute viral infection in clinical specimens is diagnostic real-time polymerase chain reaction. However, because of the COVID-19 pandemic, mass-spectrometry-based proteomics is currently being discussed as a potential diagnostic method for viral infections. Because proteomics is not yet applied in routine virus diagnostics, here we discuss its potential to detect viral infections. Apart from theoretical considerations, the current status and technical limitations are considered. Finally, the challenges that have to be overcome to establish proteomics in routine virus diagnostics are highlighted.

Predicted peptide patterns from the SARS-CoV-2 proteome for MS-MS based diagnosis.

COVID-19 caused by 2019 novel coronavirus (2019-nCoV2) also known as SARS-CoV-2 has manifested globally since January 2020. COVID-19 was declared as a pandemic by the WHO and has become a serious global health concern. Real-time PCR based and antibody-based assays are being used for the clinical detection of the virus in body fluids and nasopharyngeal swabs. Antibody variability linked to viral mutations is a big concern. Hence, it is of interest to use data patterns from mass spectrometry-based platforms for the identification of SARS-CoV-2. This dataset can be used to perform targeted mass-spectrometric analysis of SARS-CoV-2 peptides. This work can be extrapolated for the detection of SARS-CoV-2 viral peptides in complex biological fluids for early diagnosis of COVID-19.