Perspective on Proteomics for Virus Detection in Clinical Samples

MultiStageSearch: An Iterative Workflow for Unbiased Taxonomic Analysis of Pathogens Using Proteogenomics

The global SARS-CoV-2 pandemic emphasized the need for accurate pathogen diagnostics. While genomics is the gold standard, integrating mass spectrometry-based proteomics offers additional benefits. However, current proteomic and genomic reference databases are often biased toward specific taxa, such as pathogenic strains or model organisms, and proteomic databases are less comprehensive. These biases and gaps can lead to inaccurate identifications. To address these issues, we introduce MultiStageSearch, a multistep database search method that combines proteome and genome databases for taxonomic analysis. Initially, a generalist proteome database is used to infer potential species. Then, MultiStageSearch generates a specialized proteogenomic database for precise identification. This database is preprocessed to filter duplicates and cluster identical open reading frames to reduce genomic database biases. The workflow operates independently of strain-level NCBI taxonomy, enabling the identification of strains not represented in existing taxonomies. We benchmarked the workflow on viral and bacterial samples, demonstrating its superior performance in strain-level taxonomic inference compared to existing methods. MultiStageSearch offers a flexible and accurate approach for pathogen research and diagnostics, overcoming incomplete search spaces and biases inherent in reference databases.

Proteomics as a complementary approach to measure norovirus infection in clinical samples

Norovirus (NoV) is a leading cause of global acute gastroenteritis, particularly in young children, with no current licensed vaccine. Epidemiological studies have shown that asymptomatic cases are common, and infected patients may test positive for prolonged periods; however, the impact of these phenomena on transmission and public health measures remains unclear. A major limiting factor is our ability to measure infection, which is constrained to real-time reverse transcription polymerase chain reaction or antibody-based assays, both of which are susceptible to loss of detection by rapid NoV evolution. This review highlights the potential for proteomics to overcome current technical limitations and advance basic science discovery and clinical research. Importantly, proteomics-based protein detection can span NoV, host, and microbiome proteins and could help identify host or microbiome factors that correlate with disease outcome. Further developing proteomics tools to complement existing diagnostic technologies will improve our ability to assess NoV pathogenesis and transmission, as well as therapeutic efficacy.

Comprehensive phage display viral antibody profiling using VirScan: potential applications in chronic immune-mediated disease

Phage immunoprecipitation sequencing (PhIP-Seq) is a high-throughput platform that uses programmable phage display for serology. VirScan, a specific PhIP-Seq library encoding viral peptides from all known human viruses, enables comprehensive quantification of past viral exposures. We review its use in immune-mediated diseases (IMDs), highlighting its utility in identifying viral exposures in the context of IMD development. Finally, we evaluate its potential for precision medicine by integrating it with other large-scale omics data sets.

Universal Identification of Pathogenic Viruses by Liquid Chromatography Coupled with Tandem Mass Spectrometry Proteotyping

Accurate and rapid identification of viruses is crucial for an effective medical diagnosis when dealing with infections. Conventional methods, including DNA amplification techniques or lateral-flow assays, are constrained to a specific set of targets to search for. In this study, we introduce a novel tandem mass spectrometry proteotyping-based method that offers a universal approach for the identification of pathogenic viruses and other components, eliminating the need for a priori knowledge of the sample composition. Our protocol relies on a time and cost-efficient peptide sample preparation, followed by an analysis with liquid chromatography coupled to high-resolution tandem mass spectrometry. As a proof of concept, we first assessed our method on publicly available shotgun proteomics datasets obtained from virus preparations and fecal samples of infected individuals. Successful virus identification was achieved with 53 public datasets, spanning 23 distinct viral species. Furthermore, we illustrated the method's capability to discriminate closely related viruses within the same sample, using alphaviruses as an example. The clinical applicability of our method was demonstrated by the accurate detection of the vaccinia virus in spiked saliva, a matrix of paramount clinical significance due to its non-invasive and easily obtainable nature. This innovative approach represents a significant advancement in pathogen detection and paves the way for enhanced diagnostic capabilities.

A Targeted LC-MRM3 Proteomic Approach for the Diagnosis of SARS-CoV-2 Infection in Nasopharyngeal Swabs

Since its first appearance, severe acute respiratory syndrome coronavirus 2 quickly spread around the world and the lack of adequate PCR testing capacities, especially during the early pandemic, led the scientific community to explore new approaches such as mass spectrometry (MS). We developed a proteomics workflow to target several tryptic peptides of the nucleocapsid protein. A highly selective multiple reaction monitoring-cubed (MRM3) strategy provided a sensitivity increase in comparison to conventional MRM acquisition. Our MRM3 approach was first tested on an Amsterdam public health cohort (alpha-variant, 760 participants) detecting viral nucleocapsid protein peptides from nasopharyngeal swabs samples presenting a cycle threshold value down to 35 with sensitivity and specificity of 94.2% and 100.0%, without immunopurification. A second iteration of the MS-diagnostic test, able to analyze more than 400 samples per day, was clinically validated on a Leiden-Rijswijk public health cohort (delta-variant, 2536 participants) achieving 99.9% specificity and 93.1% sensitivity for patients with cycle threshold values up to 35. In this manuscript, we also developed and brought the first proof of the concept of viral variant monitoring in a complex matrix using targeted MS.

Integrated One Health strategies in Dengue

Zoonoses have rapidly spread globally, necessitating the implementation of vaccination strategies as a control measure. Emerging and re-emerging vector-borne diseases are among the major global public health concerns. Dengue, a zoonotic viral infection transmitted to humans by a vector, the Aedes mosquito, is a severe global health problem. Dengue is a serious tropical infectious disease, second only to malaria, causing around 25,000 deaths each year. The resurgence of Dengue is mainly due to climate change, demographic transitions and evolving social dynamics. The development of an effective vaccine against Dengue has proven to be a complex undertaking due to four different viral serotypes with distinct antigenic profiles. This review highlights the urgent need to address the dengue threat by exploring the application of biotechnological and -OMICS sciences.

Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.

Identification of SARS-CoV-2 biomarkers in saliva by transcriptomic and proteomics analysis

The detection of SARS-CoV-2 biomarkers by real time PCR (rRT-PCR) has shown that the sensitivity of the test is negatively affected by low viral loads and the severity of the disease. This limitation can be overcome by the use of more sensitive approaches such as mass spectrometry (MS), which has not been explored for the detection of SARS-CoV-2 proteins in saliva. Thus, this study aimed at assessing the translational applicability of mass spectrometry-based proteomics approaches to identify viral proteins in saliva from people diagnosed with COVID-19 within fourteen days after the initial diagnosis, and to compare its performance with rRT-PCR. After ethics approval, saliva samples were self-collected by 42 COVID-19 positive and 16 healthy individuals. Samples from people positive for COVID-19 were collected on average on the sixth day (± 4 days) after initial diagnosis. Viable viral particles in saliva were heat-inactivated followed by the extraction of total proteins and viral RNA. Proteins were digested and then subjected to tandem MS analysis (LC-QTOF-MS/MS) using a data-dependent MS/MS acquisition qualitative shotgun proteomics approach. The acquired spectra were queried against a combined SARS-CoV-2 and human database. The qualitative detection of SARS-CoV-2 specific RNA was done by rRT-PCR. SARS-CoV-2 proteins were identified in all COVID-19 samples (100%), while viral RNA was detected in only 24 out of 42 COVID-19 samples (57.1%). Seven out of 18 SARS-CoV-2 proteins were identified in saliva from COVID-19 positive individuals, from which the most frequent were replicase polyproteins 1ab (100%) and 1a (91.3%), and nucleocapsid (45.2%). Neither viral proteins nor RNA were detected in healthy individuals. Our mass spectrometry approach appears to be more sensitive than rRT-PCR for the detection of SARS-CoV-2 biomarkers in saliva collected from COVID-19 positive individuals up to 14 days after the initial diagnostic test. Based on the novel data presented here, our MS technology can be used as an effective diagnostic test of COVID-19 for initial diagnosis or follow-up of symptomatic cases, especially in patients with reduced viral load.

High-Sensitivity Detection toward SARS-CoV-2 S1 Glycoprotein by Parallel Reaction Monitoring Mass Spectrometry

The outbreak of coronavirus disease 2019 (COVID-19) has overwhelmed the global economy and human well-being. On account of the sharp increase in test demand, there is a need for an accurate and alternative diagnosis method for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, with the aim to specifically identify the trace SARS-CoV-2 S1 glycoprotein, we developed a high-sensitivity and high-selectivity diagnostic method based on the targeted parallel reaction monitoring (PRM) assay of eight selected peptides. This study emphasizes the outstanding detection sensitivity of 0.01 pg of the SARS-CoV-2 S1 glycoprotein even in the interference of other structural proteins, which to our knowledge is the current minimum limit of detection for the SARS-CoV-2 S1 glycoprotein. This technology could further identify 0.01 pg of the SARS-CoV-2 S1 glycoprotein in a spike pseudovirus, revealing its practical effectiveness. All our preliminary results throw light on the capability of the mass spectrometry-based targeted PRM assay to identify SARS-CoV-2 as a practicable orthogonal diagnostic tool. Furthermore, this technology could be extended to other pathogens (e.g., MERS-CoV S1 protein or SARS-CoV S1 protein) by quickly adjusting the targeted peptides of MS data acquisition. In summary, this strategy is universal and flexible and could be quickly adjusted to detect and discriminate different mutants and pathogens.

Temporal proteomic profiling reveals functional pathways in vaccinia virus-induced cell migration

Introduction

Viral diseases have always been intricate and persistent issues throughout the world and there is a lack of holistic discoveries regarding the molecular dysregulations of virus-host interactions. The temporal proteomics strategy can identify various differentially expressed proteins and offer collaborated interaction networks under pathological conditions.

Method

Herein, temporal proteomics at various hours post infection of Vero cells were launched to uncover molecular alternations during vaccinia virus (VACV)-induced cell migration. Different stages of infection were included to differentiate gene ontologies and critical pathways at specific time points of infection via bioinformatics.

Results

Bioinformatic results showed functional and distinct ontologies and pathways at different stages of virus infection. The enrichment of interaction networks and pathways verified the significances of the regulation of actin cytoskeleton and lamellipodia during VACV-induced fast cell motility.

Discussion

The current results offer a systematic proteomic profiling of molecular dysregulations at different stages of VACV infection and potential biomedical targets for treating viral diseases.

Advances in rapid detection of SARS-CoV-2 by mass spectrometry

COVID-19 has already been lasting for more than two years and it has been severely affecting the whole world. Still, detection of SARS-CoV-2 remains the frontline approach to combat the pandemic, and the reverse transcription polymerase chain reaction (RT-PCR)-based method is the well recognized detection method for the enormous analytical demands. However, the RT-PCR method typically takes a relatively long time, and can produce false positive and false negative results. Mass spectrometry (MS) is a very commonly used technique with extraordinary sensitivity, specificity and speed, and can produce qualitative and quantitative information of various analytes, which cannot be achieved by RT-PCR. Since the pandemic outbreak, various mass spectrometric approaches have been developed for rapid detection of SARS-CoV-2, including the LC-MS/MS approaches that could allow analysis of several hundred clinical samples per day with one MS system, MALDI-MS approaches that could directly analyze clinical samples for the detection, and efforts for the on-site detection with portable devices. In this review, these mass spectrometric approaches were summarized, and their pros and cons as well as further development were also discussed.

Rational Design and Development of SARS-CoV-2 Serological Diagnostics by Immunoprecipitation-Targeted Proteomics

Current design of serological tests utilizes conservative immunoassay approaches and is focused on fast and convenient assay development, throughput, straightforward measurements, and affordability. Limitations of common serological assays include semiquantitative measurements, cross-reactivity, lack of reference standards, and no differentiation between human immunoglobulin subclasses. In this study, we suggested that a combination of immunoaffinity enrichments with targeted proteomics would enable rational design and development of serological assays of infectious diseases, such as COVID-19. Immunoprecipitation-targeted proteomic assays allowed for sensitive and specific measurements of NCAP_SARS2 protein with a limit of detection of 313 pg/mL in serum and enabled differential quantification of anti-SARS-CoV-2 antibody isotypes (IgG, IgA, IgM, IgD, and IgE) and individual subclasses (IgG1-4 and IgA1-2) in plasma and saliva. Simultaneous evaluation of the numerous antigen–antibody subclass combinations revealed a receptor-binding domain (RBD)-IgG1 as a combination with the highest diagnostic performance. Further validation revealed that anti-RBD IgG1, IgG3, IgM, and IgA1 levels were significantly elevated in convalescent plasma, while IgG2, IgG4, and IgA2 were not informative. Anti-RBD IgG1 levels in convalescent (2138 ng/mL) vs negative (95 ng/mL) plasma revealed 385 ng/mL as a cutoff to detect COVID-19 convalescent plasma. Immunoprecipitation-targeted proteomic assays will facilitate improvement and standardization of the existing serological tests, enable rational design of novel tests, and offer tools for the comprehensive investigation of immunoglobulin subclass cooperation in immune response.

Proteomics-based diagnostic peptide discovery for severe fever with thrombocytopenia syndrome virus in patients

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) virus is an emerging infectious virus which causes severe hemorrhage, thrombocytopenia, and leukopenia, with a high fatality rate. Since there is no approved therapeutics or vaccines for SFTS, early diagnosis is essential to manage this infectious disease.

METHODS

Here, we tried to detect SFTS virus in serum samples from SFTS patients by proteomic analysis. Firstly, in order to obtain the reference MS/MS spectral data of SFTS virus, medium from infected Vero cell culture was used for shotgun proteomic analysis. Then, tryptic peptides in sera from SFTS patients were confirmed by comparative analysis with the reference MS/MS spectral data of SFTS virus.

RESULTS

Proteomic analysis of culture medium successfully discovered tryptic peptides from all the five antigen proteins of SFTS virus. The comparative spectral analysis of sera of SFTS patients revealed that the N-terminal tryptic peptide of the nucleocapsid (N) protein is the major epitope of SFTS virus detected in the patient samples. The prevalence of the peptides was strongly correlated with the viral load in the clinical samples.

CONCLUSIONS

Proteomic analysis of SFTS patient samples revealed that nucleocapsid (N) protein is the major antigen proteins in sera of SFTS patients and N-terminal tryptic peptide of the N protein might be a useful proteomic target for direct detection of SFTS virus. These findings suggest that proteomic analysis could be an alternative tool for detection of pathogens in clinical samples and diagnosis of infectious diseases.

Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach

Fast and accurate identifications of pathogenic bacteria along with their associated antibiotic resistance proteins are of paramount importance for patient treatments and public health. To meet this goal from the mass spectrometry aspect, we have augmented the previously published Microorganism Classification and Identification (MiCId) workflow for this capability. To evaluate the performance of this augmented workflow, we have used MS/MS datafiles from samples of 10 antibiotic resistance bacterial strains belonging to three different species: Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa. The evaluation shows that MiCId's workflow has a sensitivity value around 85% (with a lower bound at about 72%) and a precision greater than 95% in identifying antibiotic resistance proteins. In addition to having high sensitivity and precision, MiCId's workflow is fast and portable, making it a valuable tool for rapid identifications of bacteria as well as detection of their antibiotic resistance proteins. It performs microorganismal identifications, protein identifications, sample biomass estimates, and antibiotic resistance protein identifications in 6-17 min per MS/MS sample using computing resources that are available in most desktop and laptop computers. We have also demonstrated other use of MiCId's workflow. Using MS/MS data sets from samples of two bacterial clonal isolates, one being antibiotic-sensitive while the other being multidrug-resistant, we applied MiCId's workflow to investigate possible mechanisms of antibiotic resistance in these pathogenic bacteria; the results showed that MiCId's conclusions agree with the published study. The new version of MiCId (v.07.01.2021) is freely available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Rise of the SARS-CoV-2 Variants: can proteomics be the silver bullet?

INTRODUCTION

The challenges posed by emergent strains of SARS-CoV-2 need to be tackled by contemporary scientific approaches, with proteomics playing a significant role.

AREAS COVERED

In this review, we provide a brief synthesis of the impact of proteomics technologies in elucidating disease pathogenesis and classifiers for the prognosis of COVID-19 and propose proteomics methodologies that could play a crucial role in understanding emerging variants and their altered disease pathology. From aiding the design of novel drug candidates to facilitating the identification of T cell vaccine targets, we have discussed the impact of proteomics methods in COVID-19 research. Techniques varied as mass spectrometry, single-cell proteomics, multiplexed ELISA arrays, high-density proteome arrays, surface plasmon resonance, immunopeptidomics, and in silico docking studies that have helped augment the fight against existing diseases were useful in preparing us to tackle SARS-CoV-2 variants. We also propose an action plan for a pipeline to combat emerging pandemics using proteomics technology by adopting uniform standard operating procedures and unified data analysis paradigms.

EXPERT OPINION

The knowledge about the use of diverse proteomics approaches for COVID-19 investigation will provide a framework for future basic research, better infectious disease prevention strategies, improved diagnostics, and targeted therapeutics.

Coupling immuno-magnetic capture with LC-MS/MS(MRM) as a sensitive, reliable, and specific assay for SARS-CoV-2 identification from clinical samples

Recently, numerous diagnostic approaches from different disciplines have been developed for SARS-CoV-2 diagnosis to monitor and control the COVID-19 pandemic. These include MS-based assays, which provide analytical information on viral proteins. However, their sensitivity is limited, estimated to be 5 × 10⁴ PFU/ml in clinical samples. Here, we present a reliable, specific, and rapid method for the identification of SARS-CoV-2 from nasopharyngeal (NP) specimens, which combines virus capture followed by LC–MS/MS(MRM) analysis of unique peptide markers. The capture of SARS-CoV-2 from the challenging matrix, prior to its tryptic digestion, was accomplished by magnetic beads coated with polyclonal IgG-α-SARS-CoV-2 antibodies, enabling sample concentration while significantly reducing background noise interrupting with LC–MS analysis. A sensitive and specific LC–MS/MS(MRM) analysis method was developed for the identification of selected tryptic peptide markers. The combined assay, which resulted in S/N ratio enhancement, achieved an improved sensitivity of more than 10-fold compared with previously described MS methods. The assay was validated in 29 naive NP specimens, 19 samples were spiked with SARS-CoV-2 and 10 were used as negative controls. Finally, the assay was successfully applied to clinical NP samples (n = 26) pre-determined as either positive or negative by RT-qPCR. This work describes for the first time a combined approach for immuno-magnetic viral isolation coupled with MS analysis. This method is highly reliable, specific, and sensitive; thus, it may potentially serve as a complementary assay to RT-qPCR, the gold standard test. This methodology can be applied to other viruses as well.

Use of MALDI-TOF mass spectrometry for virus identification: a review

The possibilities of virus identification, including SARS-CoV-2, by MALDI-TOF mass spectrometry are discussed in this review.

Add mass spectrometry to the pandemic toolbox

A new protocol step improves robustness and ease-of-use for mass spectrometry in the clinic, opening the door to mass deployment to monitor infectious agents.

Discovery Proteomics for COVID-19: Where We Are Now

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus responsible for the pandemic coronavirus disease 2019 (COVID-19), which has had a devastating impact on society. Here, we summarize proteomic research that has helped elucidate hallmark proteins associated with the disease with respect to both short- and long-term diagnosis and prognosis. Additionally, we review the highly variable humoral response associated with COVID-19 and the increased risk of autoimmunity.

Inactivation of Coronaviruses during Sample Preparation for Proteomics Experiments

Mass spectrometry-based proteomics is applied in SARS-CoV-2 research and is, moreover, being discussed as a novel method for SARS-CoV-2 diagnostics. However, the safe inactivation of coronaviruses by proteomics lysis buffers has not been systematically analyzed yet. Hence, for safety reasons a heating step prior to sample preparation is often performed. This step could be omitted once the safe inactivation with the typical buffers is proven. Here we test five different proteomics lysis buffers-4% SDS, 1% SDC, TFA, 6 M GdmCl, and 8 M urea-for their inactivation capacity of coronaviruses. Two representative human coronaviruses, namely HCoV-229E and HCoV-OC43, were used as surrogate for SARS-CoV-2. Lysis was performed at room temperature and at 95 °C for 5 min. Inactivation was confirmed by the absence of a cytopathic effect in MRC-5 cells, and equivocal results were further confirmed by serial passaging and quantitative real-time PCR. While at room temperature SDS, SDC, and TFA inactivated both coronaviruses, and GdmCl and urea resulted in partially incomplete inactivation. This demonstrates that care should be taken when choosing lysis buffers for proteomics analysis of coronaviruses, because some buffers do not ensure inactivation and, hence, biosafety during the further sample preparation.

Application of omics technology to combat the COVID-19 pandemic

As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID-19 pandemic, multiomics-based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID-19. In order to help researchers and clinicians to keep up with the knowledge of COVID-19, we summarized the most recent progresses reported in omics-based research papers. This review discusses omics-based approaches for studying COVID-19, summarizing newly emerged SARS-CoV-2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID-19. This review can help researchers and clinicians gain insight into COVID-19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression.

A mass spectrometry-based targeted assay for detection of SARS-CoV-2 antigen from clinical specimens

Background

The COVID-19 pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has overwhelmed health systems worldwide and highlighted limitations of diagnostic testing. Several types of diagnostic tests including RT-PCR-based assays and antigen detection by lateral flow assays, each with their own strengths and weaknesses, have been developed and deployed in a short time.

Methods

Here, we describe an immunoaffinity purification approach followed a by high resolution mass spectrometry-based targeted qualitative assay capable of detecting SARS-CoV-2 viral antigen from nasopharyngeal swab samples. Based on our discovery experiments using purified virus, recombinant viral protein and nasopharyngeal swab samples from COVID-19 positive patients, nucleocapsid protein was selected as a target antigen. We then developed an automated antibody capture-based workflow coupled to targeted high-field asymmetric waveform ion mobility spectrometry (FAIMS) - parallel reaction monitoring (PRM) assay on an Orbitrap Exploris 480 mass spectrometer. An ensemble machine learning-based model for determining COVID-19 positive samples was developed using fragment ion intensities from the PRM data.

Findings

The optimized targeted assay, which was used to analyze 88 positive and 88 negative nasopharyngeal swab samples for validation, resulted in 98% (95% CI = 0.922–0.997) (86/88) sensitivity and 100% (95% CI = 0.958–1.000) (88/88) specificity using RT-PCR-based molecular testing as the reference method.

Interpretation

Our results demonstrate that direct detection of infectious agents from clinical samples by tandem mass spectrometry-based assays have potential to be deployed as diagnostic assays in clinical laboratories, which has hitherto been limited to analysis of pure microbial cultures.

Cov-MS: A Community-Based Template Assay for Mass-Spectrometry-Based Protein Detection in SARS-CoV-2 Patients

Rising population density and global mobility are among the reasons why pathogens such as SARS-CoV-2, the virus that causes COVID-19, spread so rapidly across the globe. The policy response to such pandemics will always have to include accurate monitoring of the spread, as this provides one of the few alternatives to total lockdown. However, COVID-19 diagnosis is currently performed almost exclusively by reverse transcription polymerase chain reaction (RT-PCR). Although this is efficient, automatable, and acceptably cheap, reliance on one type of technology comes with serious caveats, as illustrated by recurring reagent and test shortages. We therefore developed an alternative diagnostic test that detects proteolytically digested SARS-CoV-2 proteins using mass spectrometry (MS). We established the Cov-MS consortium, consisting of 15 academic laboratories and several industrial partners to increase applicability, accessibility, sensitivity, and robustness of this kind of SARS-CoV-2 detection. This, in turn, gave rise to the Cov-MS Digital Incubator that allows other laboratories to join the effort, navigate, and share their optimizations and translate the assay into their clinic. As this test relies on viral proteins instead of RNA, it provides an orthogonal and complementary approach to RT-PCR using other reagents that are relatively inexpensive and widely available, as well as orthogonally skilled personnel and different instruments. Data are available via ProteomeXchange with identifier PXD022550.

Cov-MS: A Community-Based Template Assay for Mass-Spectrometry-Based Protein Detection in SARS-CoV-2 Patients

Rising population density and global mobility are among the reasons why pathogens such as SARS-CoV-2, the virus that causes COVID-19, spread so rapidly across the globe. The policy response to such pandemics will always have to include accurate monitoring of the spread, as this provides one of the few alternatives to total lockdown. However, COVID-19 diagnosis is currently performed almost exclusively by reverse transcription polymerase chain reaction (RT-PCR). Although this is efficient, automatable, and acceptably cheap, reliance on one type of technology comes with serious caveats, as illustrated by recurring reagent and test shortages. We therefore developed an alternative diagnostic test that detects proteolytically digested SARS-CoV-2 proteins using mass spectrometry (MS). We established the Cov-MS consortium, consisting of 15 academic laboratories and several industrial partners to increase applicability, accessibility, sensitivity, and robustness of this kind of SARS-CoV-2 detection. This, in turn, gave rise to the Cov-MS Digital Incubator that allows other laboratories to join the effort, navigate, and share their optimizations and translate the assay into their clinic. As this test relies on viral proteins instead of RNA, it provides an orthogonal and complementary approach to RT-PCR using other reagents that are relatively inexpensive and widely available, as well as orthogonally skilled personnel and different instruments. Data are available via ProteomeXchange with identifier PXD022550.

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.

Top-Down and Bottom-Up Proteomics Methods to Study RNA Virus Biology

RNA viruses cause a wide range of human diseases that are associated with high mortality and morbidity. In the past decades, the rise of genetic-based screening methods and high-throughput sequencing approaches allowed the uncovering of unique and elusive aspects of RNA virus replication and pathogenesis at an unprecedented scale. However, viruses often hijack critical host functions or trigger pathological dysfunctions, perturbing cellular proteostasis, macromolecular complex organization or stoichiometry, and post-translational modifications. Such effects require the monitoring of proteins and proteoforms both on a global scale and at the structural level. Mass spectrometry (MS) has recently emerged as an important component of the RNA virus biology toolbox, with its potential to shed light on critical aspects of virus-host perturbations and streamline the identification of antiviral targets. Moreover, multiple novel MS tools are available to study the structure of large protein complexes, providing detailed information on the exact stoichiometry of cellular and viral protein complexes and critical mechanistic insights into their functions. Here, we review top-down and bottom-up mass spectrometry-based approaches in RNA virus biology with a special focus on the most recent developments in characterizing host responses, and their translational implications to identify novel tractable antiviral targets.

Application of spectral library prediction for parallel reaction monitoring of viral peptides

A major part of the analysis of parallel reaction monitoring (PRM) data is the comparison of observed fragment ion intensities to a library spectrum. Classically, these libraries are generated by data‐dependent acquisition (DDA). Here, we test Prosit, a published deep neural network algorithm, for its applicability in predicting spectral libraries for PRM. For this purpose, we targeted 1529 precursors derived from synthetic viral peptides and analyzed the data with Prosit and DDA‐derived libraries. Viral peptides were chosen as an example, because virology is an area where in silico library generation could significantly improve PRM assay design. With both libraries a total of 1174 precursors were identified. Notably, compared to the DDA‐derived library, we could identify 101 more precursors by using the Prosit‐derived library. Additionally, we show that Prosit can be applied to predict tandem mass spectra of synthetic viral peptides with different collision energies. Finally, we used a spectral library predicted by Prosit and a DDA library to identify SARS‐CoV‐2 peptides from a simulated oropharyngeal swab demonstrating that both libraries are suited for peptide identification by PRM. Summarized, Prosit‐derived viral spectral libraries predicted in silico can be used for PRM data analysis, making DDA analysis for library generation partially redundant in the future.

Open Science Resources for the Mass Spectrometry-Based Analysis of SARS-CoV-2

The SARS-CoV-2 virus is the causative agent of the 2020 pandemic leading to the COVID-19 respiratory disease. With many scientific and humanitarian efforts ongoing to develop diagnostic tests, vaccines, and treatments for COVID-19, and to prevent the spread of SARS-CoV-2, mass spectrometry research, including proteomics, is playing a role in determining the biology of this viral infection. Proteomics studies are starting to lead to an understanding of the roles of viral and host proteins during SARS-CoV-2 infection, their protein-protein interactions, and post-translational modifications. This is beginning to provide insights into potential therapeutic targets or diagnostic strategies that can be used to reduce the long-term burden of the pandemic. However, the extraordinary situation caused by the global pandemic is also highlighting the need to improve mass spectrometry data and workflow sharing. We therefore describe freely available data and computational resources that can facilitate and assist the mass spectrometry-based analysis of SARS-CoV-2. We exemplify this by reanalyzing a virus-host interactome data set to detect protein-protein interactions and identify host proteins that could potentially be used as targets for drug repurposing.

Proteomics in the COVID-19 Battlefield: First Semester Check-Up

Proteomics offers a wide collection of methodologies to study biological systems at the finest granularity. Faced with COVID-19, the most worrying pandemic in a century, proteomics researchers have made significant progress in understanding how the causative virus hijacks the host's cellular machinery and multiplies exponentially, how the disease can be diagnosed, and how it develops, as well as its severity predicted. Numerous cellular targets of potential interest for the development of new antiviral drugs have been documented. Here, the most striking results obtained in the proteomics field over this first semester of the pandemic are presented. The molecular machinery of SARS-CoV-2 is much more complex than initially believed, as many post-translational modifications can occur, leading to a myriad of proteoforms and a broad heterogeneity of viral particles. The interplay of protein-protein interactions, protein abundances, and post-translational modifications has yet to be fully documented to provide a full picture of this intriguing but lethal biological threat. Proteomics has the potential to provide rapid detection of the SARS-CoV-2 virus by mass spectrometry proteotyping, and to further increase the knowledge of severe respiratory syndrome COVID-19 and its long-term health consequences.

Protein Sensing Device with Multi-Recognition Ability Composed of Self-Organized Glycopeptide Bundle

We designed and synthesized amphiphilic glycopeptides with glucose or galactose at the C-terminals. We observed the protein-induced structural changes of the amphiphilic glycopeptide assembly in the lipid bilayer membrane using transmission electron microscopy (TEM) and Fourier transform infrared reflection-absorption spectra (FTIR-RAS) measurements. The glycopeptides re-arranged to form a bundle that acted as an ion channel due to the interaction among the target protein and the terminal sugar groups of the glycopeptides. The bundle in the lipid bilayer membrane was fixed on a gold-deposited quartz crystal microbalance (QCM) electrode by the membrane fusion method. The protein-induced re-arrangement of the terminal sugar groups formed a binding site that acted as a receptor, and the re-binding of the target protein to the binding site induced the closing of the channel. We monitored the detection of target proteins by the changes of the electrochemical properties of the membrane. The response current of the membrane induced by the target protein recognition was expressed by an equivalent circuit consisting of resistors and capacitors when a triangular voltage was applied. We used peanut lectin (PNA) and concanavalin A (ConA) as target proteins. The sensing membrane induced by PNA shows the specific response to PNA, and the ConA-induced membrane responded selectively to ConA. Furthermore, PNA-induced sensing membranes showed relatively low recognition ability for lectin from Ricinus Agglutinin (RCA120) and mushroom lectin (ABA), which have galactose binding sites. The protein-induced self-organization formed the spatial arrangement of the sugar chains specific to the binding site of the target protein. These findings demonstrate the possibility of fabricating a sensing device with multi-recognition ability that can recognize proteins even if the structure is unknown, by the protein-induced self-organization process.