Mass spectrometric identification of immunogenic SARS-CoV-2 epitopes and cognate TCRs

RankMHC: Learning to Rank Class-I Peptide-MHC Structural Models

The binding of peptides to class-I Major Histocompability Complex (MHC) receptors and their subsequent recognition downstream by T-cell receptors are crucial processes for most multicellular organisms to be able to fight various diseases. Thus, the identification of peptide antigens that can elicit an immune response is of immense importance for developing successful therapies for bacterial and viral infections, even cancer. Recently, studies have demonstrated the importance of peptide-MHC (pMHC) structural analysis, with pMHC structural modeling methods gradually becoming more popular in peptide antigen identification workflows. Most of the pMHC structural modeling tools provide an ensemble of candidate peptide poses in the MHC-I cleft, each associated with a score stemming from a scoring function, with the top scoring pose assumed to be the most representative of the ensemble. However, identifying the binding mode, that is, the peptide pose from the ensemble that is closer to an unavailable native structure, is not trivial. Oftentimes, the peptide poses characterized as best by a protein-ligand scoring function are not the ones that are the most representative of the actual structure. In this work, we frame the peptide binding pose identification problem as a Learning-to-Rank (LTR) problem. We present RankMHC, an LTR-based pMHC binding mode identification predictor, which is specifically trained to predict the most accurate ranking of an ensemble of pMHC conformations. RankMHC outperforms classical peptide-ligand scoring functions, as well as previous Machine Learning (ML)-based binding pose predictors. We further demonstrate that RankMHC can be used with many pMHC structural modeling tools that use different structural modeling protocols.

Machine learning-enhanced immunopeptidomics applied to T-cell epitope discovery for COVID-19 vaccines

Next-generation T-cell-directed vaccines for COVID-19 focus on establishing lasting T-cell immunity against current and emerging SARS-CoV-2 variants. Precise identification of conserved T-cell epitopes is critical for designing effective vaccines. Here we introduce a comprehensive computational framework incorporating a machine learning algorithm-MHCvalidator-to enhance mass spectrometry-based immunopeptidomics sensitivity. MHCvalidator identifies unique T-cell epitopes presented by the B7 supertype, including an epitope from a + 1-frameshift in a truncated Spike antigen, supported by ribosome profiling. Analysis of 100,512 COVID-19 patient proteomes shows Spike antigen truncation in 0.85% of cases, revealing frameshifted viral antigens at the population level. Our EpiTrack pipeline tracks global mutations of MHCvalidator-identified CD8 + T-cell epitopes from the BNT162b4 vaccine. While most vaccine epitopes remain globally conserved, an immunodominant A*01-associated epitope mutates in Delta and Omicron variants. This work highlights SARS-CoV-2 antigenic features and emphasizes the importance of continuous adaptation in T-cell vaccine development.

T Cell Peptide Prediction, Immune Response, and Host-Pathogen Relationship in Vaccinated and Recovered from Mild COVID-19 Subjects

COVID-19 remains a significant threat, particularly to vulnerable populations. The emergence of new variants necessitates the development of treatments and vaccines that induce both humoral and cellular immunity. This study aimed to identify potentially immunogenic SARS-CoV-2 peptides and to explore the intricate host-pathogen interactions involving peripheral immune responses, memory profiles, and various demographic, clinical, and lifestyle factors. Using in silico and experimental methods, we identified several CD8-restricted SARS-CoV-2 peptides that are either poorly studied or have previously unreported immunogenicity: fifteen from the Spike and three each from non-structural proteins Nsp1-2-3-16. A Spike peptide, LA-9, demonstrated a 57% response rate in ELISpot assays using PBMCs from 14 HLA-A*02:01 positive, vaccinated, and mild-COVID-19 recovered subjects, indicating its potential for diagnostics, research, and multi-epitope vaccine platforms. We also found that younger individuals, with fewer vaccine doses and longer intervals since infection, showed lower anti-Spike (ELISA) and anti-Wuhan neutralizing antibodies (pseudovirus assay), higher naïve T cells, and lower central memory, effector memory, and CD4hiCD8low T cells (flow cytometry) compared to older subjects. In our cohort, a higher prevalence of Vδ2-γδ and DN T cells, and fewer naïve CD8 T cells, seemed to correlate with strong cellular and lower anti-NP antibody responses and to associate with Omicron infection, absence of confusional state, and habitual sporting activity.

Mapping the immunopeptidome of seven SARS-CoV-2 antigens across common HLA haplotypes

Most COVID-19 vaccines elicit immunity against the SARS-CoV-2 Spike protein. However, Spike protein mutations in emerging strains and immune evasion by the SARS-CoV-2 virus demonstrates the need to develop more broadly targeting vaccines. To facilitate this, we use mass spectrometry to identify immunopeptides derived from seven relatively conserved structural and non-structural SARS-CoV-2 proteins (N, E, Nsp1/4/5/8/9). We use two different B-lymphoblastoid cell lines to map Human Leukocyte Antigen (HLA) class I and class II immunopeptidomes covering some of the prevalent HLA types across the global human population. We employ DNA plasmid transfection and direct antigen delivery approaches to sample different antigens and find 248 unique HLA class I and HLA class II bound peptides with 71 derived from N, 12 from E, 28 from Nsp1, 19 from Nsp4, 73 from Nsp8 and 45 peptides derived from Nsp9. Over half of the viral peptides are unpublished. T cell reactivity tested against 56 of the detected peptides shows CD8+ and CD4+ T cell responses against several peptides from the N, E, and Nsp9 proteins. Results from this study will aid the development of next-generation COVID vaccines targeting epitopes from across a number of SARS-CoV-2 proteins.

Thunder-DDA-PASEF enables high-coverage immunopeptidomics and is boosted by MS2Rescore with MS2PIP timsTOF fragmentation prediction model

Human leukocyte antigen (HLA) class I peptide ligands (HLAIps) are key targets for developing vaccines and immunotherapies against infectious pathogens or cancer cells. Identifying HLAIps is challenging due to their high diversity, low abundance, and patient individuality. Here, we develop a highly sensitive method for identifying HLAIps using liquid chromatography-ion mobility-tandem mass spectrometry (LC-IMS-MS/MS). In addition, we train a timsTOF-specific peak intensity MS2PIP model for tryptic and non-tryptic peptides and implement it in MS2Rescore (v3) together with the CCS predictor from ionmob. The optimized method, Thunder-DDA-PASEF, semi-selectively fragments singly and multiply charged HLAIps based on their IMS and m/z. Moreover, the method employs the high sensitivity mode and extended IMS resolution with fewer MS/MS frames (300 ms TIMS ramp, 3 MS/MS frames), doubling the coverage of immunopeptidomics analyses, compared to the proteomics-tailored DDA-PASEF (100 ms TIMS ramp, 10 MS/MS frames). Additionally, rescoring boosts the HLAIps identification by 41.7% to 33%, resulting in 5738 HLAIps from as little as one million JY cell equivalents, and 14,516 HLAIps from 20 million. This enables in-depth profiling of HLAIps from diverse human cell lines and human plasma. Finally, profiling JY and Raji cells transfected to express the SARS-CoV-2 spike protein results in 16 spike HLAIps, thirteen of which have been reported to elicit immune responses in human patients.

A multifaceted approach for identification, validation, and immunogenicity of naturally processed and in silico-predicted highly conserved SARS-CoV-2 peptides

SARS-CoV-2 remains a major global public health concern. Antibody waning and immune escape variant emergence necessitate the development of next generation vaccines that induce cross-reactive durable immune responses. T cell responses to SARS-CoV-2 demonstrate higher conservation, antigenic breadth, and longevity than antibody responses. Therefore, we sought to identify pathogen-derived T cell epitopes for a potential peptide-based vaccine. We pursued an approach leveraging: 1) liquid chromatography and tandem mass spectrometry (LC-MS/MS)-based identification of peptides from ancestral SARS-CoV-2-infected cell lines, 2) epitope prediction algorithms, and 3) overlapping peptide libraries. From this strategy, we identified 380 unique SARS-CoV-2-derived peptide sequences, including 53 antigenic HLA class I and class II peptides from multiple structural and non-structural/accessory viral proteins. These peptide sequences were highly conserved across variants of concern/interest (VoC/VoIs), and are estimated to achieve coverage of >96% of the world population. Our findings validate this discovery pipeline for peptide identification and immunogenicity testing, and are a crucial step toward the development of a next-generation multi-epitope SARS-CoV-2 peptide vaccine, and a novel vaccine platform methodology.

Applications of Mass Spectrometry in the Characterization, Screening, Diagnosis, and Prognosis of COVID-19

Mass spectrometry (MS) is a powerful analytical technique that plays a central role in modern protein analysis and the study of proteostasis. In the field of advanced molecular technologies, MS-based proteomics has become a cornerstone that is making a significant impact in the post-genomic era and as precision medicine moves from the research laboratory to clinical practice. The global dissemination of COVID-19 has spurred collective efforts to develop effective diagnostics, vaccines, and therapeutic interventions. This chapter highlights how MS seamlessly integrates with established methods such as RT-PCR and ELISA to improve viral identification and disease progression assessment. In particular, matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) takes the center stage, unraveling intricate details of SARS-CoV-2 proteins, revealing modifications such as glycosylation, and providing insights critical to formulating therapies and assessing prognosis. However, high-throughput analysis of MALDI data presents challenges in manual interpretation, which has driven the development of programmatic pipelines and specialized packages such as MALDIquant. As we move forward, it becomes clear that integrating proteomic data with various omic findings is an effective strategy to gain a comprehensive understanding of the intricate biology of COVID-19 and ultimately develop targeted therapeutic paradigms.

Integrated Immunopeptidomics and Proteomics Study of SARS-CoV-2-Infected Calu-3 Cells Reveals Dynamic Changes in Allele-specific HLA Abundance and Antigen Presentation

We present an integrated immunopeptidomics and proteomics study of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection to comprehensively decipher the changes in host cells in response to viral infection. Immunopeptidomics analysis identified viral antigens presented by host cells through both class I and class II MHC system for recognition by the adaptive immune system. The host proteome changes were characterized by quantitative proteomics and glycoproteomics and from these data, the activation of toll-like receptor 3-interferon pathway was identified. Glycosylation analysis of human leukocyte antigen (HLA) proteins from the elution and flow-through of immunoprecipitation revealed that SARS-CoV-2 infection changed the glycosylation pattern of certain HLA alleles with different HLA alleles, showing distinct dynamic changes in relative abundance. The difference in the glycosylation and abundance of HLA alleles changed the number of strong binding antigens each allele presented, suggesting the impact of SARS-CoV-2 infection on antigen presentation is allele-specific. These results could be further exploited to explain the imbalanced response from innate and adaptive immune system in coronavirus disease 2019 cases, which would be helpful for the development of therapeutics and vaccine for coronavirus disease 2019 and preparation for future pandemic.

Immunopeptidome profiling of human coronavirus OC43-infected cells identifies CD4 T-cell epitopes specific to seasonal coronaviruses or cross-reactive with SARS-CoV-2

Seasonal "common-cold" human coronaviruses are widely spread throughout the world and are mainly associated with mild upper respiratory tract infections. The emergence of highly pathogenic coronaviruses MERS-CoV, SARS-CoV, and most recently SARS-CoV-2 has prompted increased attention to coronavirus biology and immunopathology, but the T-cell response to seasonal coronaviruses remains largely uncharacterized. Here we report the repertoire of viral peptides that are naturally processed and presented upon infection of a model cell line with seasonal coronavirus OC43. We identified MHC-bound peptides derived from each of the viral structural proteins (spike, nucleoprotein, hemagglutinin-esterase, membrane, and envelope) as well as non-structural proteins nsp3, nsp5, nsp6, and nsp12. Eighty MHC-II bound peptides corresponding to 14 distinct OC43-derived epitopes were identified, including many at very high abundance within the overall MHC-II peptidome. Fewer and less abundant MHC-I bound OC43-derived peptides were observed, possibly due to MHC-I downregulation induced by OC43 infection. The MHC-II peptides elicited low-abundance recall T-cell responses in most donors tested. In vitro assays confirmed that the peptides were recognized by CD4+ T cells and identified the presenting HLA alleles. T-cell responses cross-reactive between OC43, SARS-CoV-2, and the other seasonal coronaviruses were confirmed in samples of peripheral blood and peptide-expanded T-cell lines. Among the validated epitopes, spike protein S903-917 presented by DPA1*01:03/DPB1*04:01 and S1085-1099 presented by DRB1*15:01 shared substantial homology to other human coronaviruses, including SARS-CoV-2, and were targeted by cross-reactive CD4 T cells. Nucleoprotein N54-68 and hemagglutinin-esterase HE128-142 presented by DRB1*15:01 and HE259-273 presented by DPA1*01:03/DPB1*04:01 are immunodominant epitopes with low coronavirus homology that are not cross-reactive with SARS-CoV-2. Overall, the set of naturally processed and presented OC43 epitopes comprise both OC43-specific and human coronavirus cross-reactive epitopes, which can be used to follow CD4 T-cell cross-reactivity after infection or vaccination, and to guide selection of epitopes for inclusion in pan-coronavirus vaccines.

An immunoinformatics approach to study the epitopes of SARS-CoV-2 helicase, Nsp13

Introduction and objective.

Vaccines are administered worldwide to control on-going coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2. Vaccine efficacy is largely contributed by the epitopes present on the viral proteins and their alteration might help emerging variants to escape host immune surveillance. Therefore, this study was designed to study SARS-CoV-2 Nsp13 protein, its epitopes and evolution.

Methods

Clustal Omega was used to identify mutations in Nsp13 protein. Secondary structure and disorder score was predicted by CFSSP and PONDR-VSL2 webservers. Protein stability was predicted by DynaMut webserver. B cell epitopes were predicted by IEDB DiscoTope 2.0 tools and their 3D structures were represented by discovery studio. Antigenicity and allergenicity of epitopes were predicted by Vaxijen2.0 and AllergenFPv.1.0. Physiochemical properties of epitopes were predicted by Toxinpred, HLP webserver tool.

Results

Our data revealed 182 mutations in Nsp13 among Indian SARS-CoV-2 isolates, which were characterised by secondary structure and per-residue disorderness, stability and dynamicity predictions. To correlate the functional impact of these mutations, we characterised the most prominent B cell and T cell epitopes contributed by Nsp13. Our data revealed twenty-one epitopes, which exhibited antigenicity, stability and interactions with MHC class-I and class-II molecules. Subsequently, the physiochemical properties of these epitopes were analysed. Furthermore, eighteen mutations reside in these Nsp13 epitopes.

Conclusions

We report appearance of eighteen mutations in the predicted twenty-one epitopes of Nsp13. Among these, at least seven epitopes closely matches with the functionally validated epitopes. Altogether, our study shows the pattern of evolution of Nsp13 epitopes and their probable implications.

Viral T-cell epitopes - Identification, characterization and clinical application

T-cell immunity, mediated by CD4⁺ and CD8⁺ T cells, represents a cornerstone in the control of viral infections. Virus-derived T-cell epitopes are represented by human leukocyte antigen (HLA)-presented viral peptides on the surface of virus-infected cells. They are the prerequisite for the recognition of infected cells by T cells. Knowledge of viral T-cell epitopes provides on the one hand a diagnostic tool to decipher protective T-cell immune responses in the human population and on the other hand various prophylactic and therapeutic options including vaccination approaches and the transfer of virus-specific T cells. Such approaches have already been proven to be effective against various viral infections, particularly in immunocompromised patients lacking sufficient humoral, antibody-based immune response. This review provides an overview on the state of the art as well as current studies regarding the identification and characterization of viral T-cell epitopes and approaches of clinical application. In the first chapter in silico prediction tools and direct, mass spectrometry-based identification of viral T-cell epitopes is compared. The second chapter provides an overview of commonly used assays for further characterization of T-cell responses and phenotypes. The final chapter presents an overview of clinical application of viral T-cell epitopes with a focus on human immunodeficiency virus (HIV), human cytomegalovirus (HCMV) and severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), being representatives of relevant viruses.

A systemic review of T-cell epitopes defined from the proteome of SARS-CoV-2

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection remains in a global pandemic, and no eradicative therapy is currently available. Host T cells have been shown to play a crucial role in the antiviral immune protection and pathology in Coronavirus disease 2019 (COVID-19) patients; thus, identifying sufficient T-cell epitopes from the SARS-CoV-2 proteome can contribute greatly to the development of T-cell epitope vaccines and the precise evaluation of host SARS-CoV-2-specific cellular immunity. This review presents a comprehensive map of T-cell epitopes functionally validated from SARS-CoV-2 antigens, the human leukocyte antigen (HLA) supertypes to present these epitopes, and the strategies to screen and identify T-cell epitopes. To the best of our knowledge, a total of 1349 CD8+ T-cell epitopes and 790 CD4+ T-cell epitopes have been defined by functional experiments thus far, but most are presented by approximately twenty common HLA supertypes, such as HLA-A0201, A2402, B0702, DR15, DR7 and DR11 molecules, and 74-80% of the T-cell epitopes are derived from S protein and nonstructural protein. These data provide useful insight into the development of vaccines and specific T-cell detection systems. However, the currently defined T-cell epitope repertoire cannot cover the HLA polymorphism of major populations in an indicated geographic region. More research is needed to depict an overall landscape of T-cell epitopes, which covers the overall SARS-CoV-2 proteome and global patients.

Immunopeptidome profiling of human coronavirus OC43-infected cells identifies CD4 T cell epitopes specific to seasonal coronaviruses or cross-reactive with SARS-CoV-2

Seasonal "common-cold" human coronaviruses are widely spread throughout the world and are mainly associated with mild upper respiratory tract infections. The emergence of highly pathogenic coronaviruses MERS-CoV, SARS-CoV, and most recently SARS-CoV-2 has prompted increased attention to coronavirus biology and immunopathology, but identification and characterization of the T cell response to seasonal human coronaviruses remain largely uncharacterized. Here we report the repertoire of viral peptides that are naturally processed and presented upon infection of a model cell line with seasonal human coronavirus OC43. We identified MHC-I and MHC-II bound peptides derived from the viral spike, nucleocapsid, hemagglutinin-esterase, 3C-like proteinase, and envelope proteins. Only three MHC-I bound OC43-derived peptides were observed, possibly due to the potent MHC-I downregulation induced by OC43 infection. By contrast, 80 MHC-II bound peptides corresponding to 14 distinct OC43-derived epitopes were identified, including many at very high abundance within the overall MHC-II peptidome. These peptides elicited low-abundance recall T cell responses in most donors tested. In vitro assays confirmed that the peptides were recognized by CD4+ T cells and identified the presenting HLA alleles. T cell responses cross-reactive between OC43, SARS-CoV-2, and the other seasonal coronaviruses were confirmed in samples of peripheral blood and peptide-expanded T cell lines. Among the validated epitopes, S 903-917 presented by DPA1*01:03/DPB1*04:01 and S 1085-1099 presented by DRB1*15:01 shared substantial homology to other human coronaviruses, including SARS-CoV-2, and were targeted by cross-reactive CD4 T cells. N 54-68 and HE 128-142 presented by DRB1*15:01 and HE 259-273 presented by DPA1*01:03/DPB1*04:01 are immunodominant epitopes with low coronavirus homology that are not cross-reactive with SARS-CoV-2. Overall, the set of naturally processed and presented OC43 epitopes comprise both OC43-specific and human coronavirus cross-reactive epitopes, which can be used to follow T cell cross-reactivity after infection or vaccination and could aid in the selection of epitopes for inclusion in pan-coronavirus vaccines.

Author Summary

There is much current interest in cellular immune responses to seasonal common-cold coronaviruses because of their possible role in mediating protection against SARS-CoV-2 infection or pathology. However, identification of relevant T cell epitopes and systematic studies of the T cell responses responding to these viruses are scarce. We conducted a study to identify naturally processed and presented MHC-I and MHC-II epitopes from human cells infected with the seasonal coronavirus HCoV-OC43, and to characterize the T cell responses associated with these epitopes. We found epitopes specific to the seasonal coronaviruses, as well as epitopes cross-reactive between HCoV-OC43 and SARS-CoV-2. These epitopes should be useful in following immune responses to seasonal coronaviruses and identifying their roles in COVID-19 vaccination, infection, and pathogenesis.

Patients Recovering from Severe COVID-19 Develop a Polyfunctional Antigen-Specific CD4+ T Cell Response

Specific T cells are crucial to control SARS-CoV-2 infection, avoid reinfection and confer protection after vaccination. We have studied patients with severe or moderate COVID-19 pneumonia, compared to patients who recovered from a severe or moderate infection that had occurred about 4 months before the analyses. In all these subjects, we assessed the polyfunctionality of virus-specific CD4+ and CD8+ T cells by quantifying cytokine production after in vitro stimulation with different SARS-CoV-2 peptide pools covering different proteins (M, N and S). In particular, we quantified the percentage of CD4+ and CD8+ T cells simultaneously producing interferon-γ, tumor necrosis factor, interleukin (IL)-2, IL-17, granzyme B, and expressing CD107a. Recovered patients who experienced a severe disease display high proportions of antigen-specific CD4+ T cells producing Th1 and Th17 cytokines and are characterized by polyfunctional SARS-CoV-2-specific CD4+ T cells. A similar profile was found in patients experiencing a moderate form of COVID-19 pneumonia. No main differences in polyfunctionality were observed among the CD8+ T cell compartments, even if the proportion of responding cells was higher during the infection. The identification of those functional cell subsets that might influence protection can thus help in better understanding the complexity of immune response to SARS-CoV-2.

The interdependence of machine learning and LC-MS approaches for an unbiased understanding of the cellular immunopeptidome

INTRODUCTION

The comprehensive collection of peptides presented by Major Histocompatibility Complex (MHC) molecules on the cell surface is collectively known as the immunopeptidome. The analysis and interpretation of such data sets holds great promise for furthering our understanding of basic immunology and adaptive immune activation and regulation, and for direct rational discovery of T cell antigens and the design of T-cell based therapeutics and vaccines. These applications are however challenged by the complex nature of immunopeptidome data.

AREAS COVERED

Here, we describe the benefits and shortcomings of applying liquid chromatography-tandem mass spectrometry (MS) to obtain large scale immunopeptidome data sets and illustrate how the accurate analysis and optimal interpretation of such data is reliant on the availability of refined and highly optimized machine learning approaches.

EXPERT OPINION

Further we demonstrate how the accuracy of immunoinformatics prediction methods within the field of MHC antigen presentation has benefited greatly from the availability of MS-immunopeptidomics data, and exemplify how optimal antigen discovery is best performed in a synergistic combination of MS experiments and such in silico models trained on large scale immunopeptidomics data.

Development of a T cell-based immunodiagnostic system to effectively distinguish SARS-CoV-2 infection and COVID-19 vaccination status

Both SARS-CoV-2 infections and COVID-19 vaccines elicit memory T cell responses. Here, we report the development of 2 pools of experimentally defined SARS-CoV-2 T cell epitopes that, in combination with spike, were used to discriminate 4 groups of subjects with different SARS-CoV-2 infection and COVID-19 vaccine status. The overall T cell-based classification accuracy was 89.2% and 88.5% in the experimental and validation cohorts. This scheme was applicable to different mRNA vaccines and different lengths of time post infection/post vaccination and yielded increased accuracy when compared to serological readouts. T cell responses from breakthrough infections were also studied and effectively segregated from vaccine responses, with a combined performance of 86.6% across all 239 subjects from the 5 groups. We anticipate that a T cell-based immunodiagnostic scheme to classify subjects based on their vaccination and natural infection history will be an important tool for longitudinal monitoring of vaccinations and for establishing SARS-CoV-2 correlates of protection.

T cell responses to SARS-CoV-2 in humans and animals

SARS-CoV-2, the causative agent of COVID-19, first emerged in 2019. Antibody responses against SARS-CoV-2 have been given a lot of attention. However, the armamentarium of humoral and T cells may have differing roles in different viral infections. Though the exact role of T cells in COVID-19 remains to be elucidated, prior experience with human coronavirus has revealed an essential role of T cells in the outcomes of viral infections. Moreover, an increasing body of evidence suggests that T cells might be effective against SARS-CoV-2. This review summarizes the role of T cells in mouse CoV, human pathogenic respiratory CoV in general and SARS-CoV-2 in specific.

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.