Discovery Proteomics for COVID-19: Where We Are Now

Proteomic lung analysis revealed hyper-activation of neutrophil extracellular trap formation in cases of fatal COVID-19

The molecular pathology of lung injury in patients with Corona Virus Disease 2019 (COVID-19) remain unclear. In this study, we performed a proteomic study of lung tissues from seven patients with COVID-19, and eight without. Lung parenchymal tissues with COVID-19 were obtained from autopsy samples, while control samples were obtained from paracancerous tissues. Proteins were extracted using phenol extraction. A tandem mass tag-based quantitative proteomic approach combined with bioinformatic analysis was used to detect proteomic changes in the SARS-CoV-2-infected lung tissues. A total of 6,602, and 6,549 proteins were identified in replicates 1 and 2, respectively. Of these, 307, and 278, respectively, were identified as differentially expressed proteins (DEPs). In total, 216 DEPs were identified in this study. These proteins were enriched in 189 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The downregulated proteins are mainly involved in focal adhesion (n = 5), and the PI3K-Akt signaling pathway (n = 4). The upregulated proteins were related to neutrophil extracellular trap (NET) formation (n = 16), and the phagosome pathway (n = 11). The upregulated proteins in these two pathways interact with one another. Further immunohistochemistry verified NET enrichment in the tissues with COVID-19 compared to the controls. Our results systematically outlined the proteomic profiles of the lung's response to SARS-CoV-2 infection and indicated that NET formation was hyper-activated. These results will hopefully provide new evidence for understanding the mechanism behind fatal COVID-19.

Proteomic Analysis of Salivary Extracellular Vesicles from COVID-19 Patients Reveals a Specific Anti-COVID-19 Response Protein Signature

Despite the understanding of the coronavirus disease-19 (COVID-19), the role of salivary extracellular vesicles (sEVs) in COVID-19 remains unclear. Exploring the proteomic cargo of sEVs could prove valuable for diagnostic and prognostic purposes in assessing COVID-19. The proteomic cargo of sEVs from COVID-19(+) subjects and their healthy close contacts (HCC) was explored. sEVs were isolated by ultracentrifugation from unstimulated saliva samples, and subsequently characterized through nanoparticle tracking, transmission electron microscopy, and Western blot analyses. The proteomic cargo of sEVs was processed by LC-MS/MS. sEVs were morphologically compatible with EVs, with the presence of Syntenin-1 and CD81 EV markers. The sEV pellet showed 1417 proteins: 1288 in COVID-19(+) cases and 1382 in HCC. In total, 124 proteins were differentially expressed in sEVs from COVID-19(+) subjects. "Coronavirus-disease response", "complement and coagulation cascades", and "PMN extracellular trap formation" were the most enriched KEGG pathways in COVID-19(+) cases. The most represented biological processes were "Hemoglobin and haptoglobin binding" and "oxygen carrier activity", and the best-denoted molecular functions were "regulated exocytosis and secretion" and "leucocyte and PMN mediated immunity". sEV proteomic cargo in COVID-19(+) suggests activity related to immune response processes, oxygen transport, and antioxidant mechanisms. In contrast, in HCC, sEV signature profiles are mainly associated with epithelial homeostasis.

Proteomic profiling identifies biomarkers of COVID-19 severity

SARS-CoV-2 infection remains a major public health concern, particularly for the aged and those individuals with co-morbidities at risk for developing severe COVID-19. Understanding the pathogenesis and biomarkers associated with responses to SARS-CoV-2 infection remain critical components in developing effective therapeutic approaches, especially in cases of severe and long-COVID-19. In this study blood plasma protein expression was compared in subjects with mild, moderate, and severe COVID-19 disease. Evaluation of an inflammatory protein panel confirms upregulation of proteins including TNFβ, IL-6, IL-8, IL-12, already associated with severe cytokine storm and progression to severe COVID-19. Importantly, we identify several proteins not yet associated with COVID-19 disease, including mesothelin (MSLN), that are expressed at significantly higher levels in severe COVID-19 subjects. In addition, we find a subset of markers associated with T-cell and dendritic cell responses to viral infection that are significantly higher in mild cases and decrease in expression as severity of COVID-19 increases, suggesting that an immediate and effective activation of T-cells is critical in modulating disease progression. Together, our findings identify new targets for further investigation as therapeutic approaches for the treatment of SARS-CoV-2 infection and prevention of complications of severe COVID-19.

Integrative multi-omics approach for identifying molecular signatures and pathways and deriving and validating molecular scores for COVID-19 severity and status

BACKGROUND

There is still more to learn about the pathobiology of COVID-19. A multi-omic approach offers a holistic view to better understand the mechanisms of COVID-19. We used state-of-the-art statistical learning methods to integrate genomics, metabolomics, proteomics, and lipidomics data obtained from 123 patients experiencing COVID-19 or COVID-19-like symptoms for the purpose of identifying molecular signatures and corresponding pathways associated with the disease.

RESULTS

We constructed and validated molecular scores and evaluated their utility beyond clinical factors known to impact disease status and severity. We identified inflammation- and immune response-related pathways, and other pathways, providing insights into possible consequences of the disease.

CONCLUSIONS

The molecular scores we derived were strongly associated with disease status and severity and can be used to identify individuals at a higher risk for developing severe disease. These findings have the potential to provide further, and needed, insights into why certain individuals develop worse outcomes.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes. We subsequently created highly accurate models that distinctively predict infection, ventilation, and death. These proteins were enriched in specific biological processes including cytokine signaling, Alzheimer's disease, and coronary artery disease. Mendelian randomization and gene network analyses identified eight causal proteins and 141 highly connected hub proteins including 35 with known drug targets. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes, reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

The 2022 Report on the Human Proteome from the HUPO Human Proteome Project

The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, "A Function for Each Protein".

Towards precision medicine: Omics approach for COVID-19

The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.

Plasma enzymatic activity, proteomics and peptidomics in COVID-19-induced sepsis: A novel approach for the analysis of hemostasis

Introduction: Infection by SARS-CoV-2 and subsequent COVID-19 can cause viral sepsis. We investigated plasma protease activity patterns in COVID-19-induced sepsis with bacterial superinfection, as well as plasma proteomics and peptidomics in order to assess the possible implications of enhanced proteolysis on major protein systems (e.g., coagulation). Methods: Patients (=4) admitted to the intensive care units (ICUs) at the University of California, San Diego (UCSD) Medical Center with confirmed positive test for COVID-19 by real-time reverse transcription polymerase chain reaction (RT-PCR) were enrolled in a study approved by the UCSD Institutional Review Board (IRB# 190699, Protocol #20-0006). Informed consent was obtained for the collection of blood samples and de-identified use of the data. Blood samples were collected at multiple time points and analyzed to quantify a) the circulating proteome and peptidome by mass spectrometry; b) the aminopeptidase activity in plasma; and c) the endopeptidase activity in plasma using fluorogenic substrates that are cleaved by trypsin-like endopeptidases, specific clotting factors and plasmin. The one patient who died was diagnosed with bacterial superinfection on day 7 after beginning of the study. Results: Spikes in protease activity (factor VII, trypsin-like activity), and corresponding increases in the intensity of peptides derived by hydrolysis of plasma proteins, especially of fibrinogen degradation products and downregulation of endogenous protease inhibitors were detected on day 7 for the patient who died. The activity of the analyzed proteases was stable in survivors. Discussion: The combination of multiomics and enzymatic activity quantification enabled to i) hypothesize that elevated proteolysis occurs in COVID-19-induced septic shock with bacterial superinfection, and ii) provide additional insight into malfunctioning protease-mediated systems, such as hemostasis.

A two-gene marker for the two-tiered innate immune response in COVID-19 patients

For coronavirus disease 2019 (COVID-19), a pandemic disease characterized by strong immune dysregulation in severe patients, convenient and efficient monitoring of the host immune response is critical. Human hosts respond to viral and bacterial infections in different ways, the former is characterized by the activation of interferon stimulated genes (ISGs) such as IFI27, while the latter is characterized by the activation of anti-bacterial associated genes (ABGs) such as S100A12. This two-tiered innate immune response has not been examined in COVID-19. In this study, the activation patterns of this two-tiered innate immune response represented by IFI27 and S100A12 were explored based on 1421 samples from 17 transcriptome datasets derived from the blood of COVID-19 patients and relevant controls. It was found that IFI27 activation occurred in most of the symptomatic patients and displayed no correlation with disease severity, while S100A12 activation was more restricted to patients under severe and critical conditions with a stepwise activation pattern. In addition, most of the S100A12 activation was accompanied by IFI27 activation. Furthermore, the activation of IFI27 was most pronounced within the first week of symptom onset, but generally waned after 2-3 weeks. On the other hand, the activation of S100A12 displayed no apparent correlation with disease duration and could last for several months in certain patients. These features of the two-tiered innate immune response can further our understanding on the disease mechanism of COVID-19 and may have implications to the clinical triage. Development of a convenient two-gene protocol for the routine serial monitoring of this two-tiered immune response will be a valuable addition to the existing laboratory tests.

Clinical applications of plasma proteomics and peptidomics: Towards precision medicine

In the context of precision medicine, disease treatment requires individualized strategies based on the underlying molecular characteristics to overcome therapeutic challenges posed by heterogeneity. For this purpose, it is essential to develop new biomarkers to diagnose, stratify, or possibly prevent diseases. Plasma is an available source of biomarkers that greatly reflects the physiological and pathological conditions of the body. An increasing number of studies are focusing on proteins and peptides, including many involving the Human Proteome Project (HPP) of the Human Proteome Organization (HUPO), and proteomics and peptidomics techniques are emerging as critical tools for developing novel precision medicine preventative measures. Excitingly, the emerging plasma proteomics and peptidomics toolbox exhibits a huge potential for studying pathogenesis of diseases (e.g., COVID-19 and cancer), identifying valuable biomarkers and improving clinical management. However, the enormous complexity and wide dynamic range of plasma proteins makes plasma proteome profiling challenging. Herein, we summarize the recent advances in plasma proteomics and peptidomics with a focus on their emerging roles in COVID-19 and cancer research, aiming to emphasize the significance of plasma proteomics and peptidomics in clinical applications and precision medicine.

Multiplex protein profiling of bronchial aspirates reveals disease-, mortality- and respiratory sequelae-associated signatures in critically ill patients with ARDS secondary to SARS-CoV-2 infection

Introduction

Bronchial aspirates (BAS) obtained during invasive mechanical ventilation (IMV) constitutes a useful tool for molecular phenotyping and decision making.

Aim

To identify the proteomic determinants associated with disease pathogenesis, all-cause mortality and respiratory sequelae in BAS samples from critically ill patients with SARS-CoV-2-induced ARDS.

Methods

Multicenter study including 74 critically ill patients with COVID-19 and non-COVID-19 ARDS. BAS were obtained by bronchoaspiration after IMV initiation. Three hundred sixty-four proteins were quantified using proximity extension assay (PEA) technology. Random forest models were used to assess predictor importance.

Results

After adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-α were differentially detected in COVID-19 and non-COVID-19 patients. In random forest models for COVID-19, CST5, DPP7, NADK, KYAT1 and TYMP showed the highest variable importance. In COVID-19 patients, reduced levels of ENTPD2 and PTN were observed in nonsurvivors of ICU stay, even after adjustment. AGR2, NQO2, IL-1α, OSM and TRAIL showed the strongest associations with in-ICU mortality and were used to construct a protein-based prediction model. Kaplan-Meier curves revealed a clear separation in mortality risk between subgroups of PTN, ENTPD2 and the prediction model. Cox regression models supported these findings. In survivors, the levels of FCRL1, NTF4 and THOP1 in BAS samples obtained during the ICU stay correlated with lung function (i.e., D_LCO levels) 3 months after hospital discharge. Similarly, Flt3L and THOP1 levels were correlated with radiological features (i.e., TSS). These proteins are expressed in immune and nonimmune lung cells. Poor host response to viral infectivity and an inappropriate reparative mechanism seem to be linked with the pathogenesis of the disease and fatal outcomes, respectively.

Conclusion

BAS proteomics identified novel factors associated with the pathology of SARS-CoV-2-induced ARDS and its adverse outcomes. BAS-based protein testing emerges as a novel tool for risk assessment in the ICU.

Proteomics research of SARS-CoV-2 and COVID-19 disease

Currently, coronavirus disease 2019 (COVID-19) is still spreading in a global scale, exerting a massive health and socioeconomic crisis. Deep insights into the molecular functions of the viral proteins and the pathogenesis of this infectious disease are urgently needed. In this review, we comprehensively describe the proteome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and summarize their protein interaction map with host cells. In the protein interaction network between the virus and the host, a total of 787 host prey proteins that appeared in at least two studies or were verified by co-immunoprecipitation experiments. Together with 29 viral proteins, a network of 1762 proximal interactions were observed. We also review the proteomics results of COVID-19 patients and proved that SARS-CoV-2 hijacked the host's translation system, post-translation modification system, and energy supply system via viral proteins, resulting in various immune disorders, multiple cardiomyopathies, and cholesterol metabolism diseases.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

HYGIEIA: HYpothesizing the Genesis of Infectious Diseases and Epidemics through an Integrated Systems Biology Approach

More than two years on, the COVID-19 pandemic continues to wreak havoc around the world and has battle-tested the pandemic-situation responses of all major global governments. Two key areas of investigation that are still unclear are: the molecular mechanisms that lead to heterogenic patient outcomes, and the causes of Post COVID condition (AKA Long-COVID). In this paper, we introduce the HYGIEIA project, designed to respond to the enormous challenges of the COVID-19 pandemic through a multi-omic approach supported by network medicine. It is hoped that in addition to investigating COVID-19, the logistics deployed within this project will be applicable to other infectious agents, pandemic-type situations, and also other complex, non-infectious diseases. Here, we first look at previous research into COVID-19 in the context of the proteome, metabolome, transcriptome, microbiome, host genome, and viral genome. We then discuss a proposed methodology for a large-scale multi-omic longitudinal study to investigate the aforementioned biological strata through high-throughput sequencing (HTS) and mass-spectrometry (MS) technologies. Lastly, we discuss how a network medicine approach can be used to analyze the data and make meaningful discoveries, with the final aim being the translation of these discoveries into the clinics to improve patient care.

The serum of COVID-19 asymptomatic patients up-regulates proteins related to endothelial dysfunction and viral response in circulating angiogenic cells ex-vivo

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already caused 6 million deaths worldwide. While asymptomatic individuals are responsible of many potential transmissions, the difficulty to identify and isolate them at the high peak of infection constitutes still a real challenge. Moreover, SARS-CoV-2 provokes severe vascular damage and thromboembolic events in critical COVID-19 patients, deriving in many related deaths and long-hauler symptoms. Understanding how these processes are triggered as well as the potential long-term sequelae, even in asymptomatic individuals, becomes essential.

Methods

We have evaluated, by application of a proteomics-based quantitative approach, the effect of serum from COVID-19 asymptomatic individuals over circulating angiogenic cells (CACs). Healthy CACs were incubated ex-vivo with the serum of either COVID-19 negative (PCR −/IgG −, n:8) or COVID-19 positive asymptomatic donors, at different infective stages: PCR +/IgG − (n:8) and PCR −/IgG + (n:8). Also, a label free quantitative approach was applied to identify and quantify protein differences between these serums. Finally, machine learning algorithms were applied to validate the differential protein patterns in CACs.

Results

Our results confirmed that SARS-CoV-2 promotes changes at the protein level in the serum of infected asymptomatic individuals, mainly correlated with altered coagulation and inflammatory processes (Fibrinogen, Von Willebrand Factor, Thrombospondin-1). At the cellular level, proteins like ICAM-1, TLR2 or Ezrin/Radixin were only up-regulated in CACs treated with the serum of asymptomatic patients at the highest peak of infection (PCR + /IgG −), but not with the serum of PCR −/IgG + individuals. Several proteins stood out as significantly discriminating markers in CACs in response to PCR or IgG + serums. Many of these proteins particiArticle title: Kindly check and confirm the edit made in the article title.pate in the initial endothelial response against the virus.

Conclusions

The ex vivo incubation of CACs with the serum of asymptomatic COVID-19 donors at different stages of infection promoted protein changes representative of the endothelial dysfunction and inflammatory response after viral infection, together with activation of the coagulation process. The current approach constitutes an optimal model to study the response of vascular cells to SARS-CoV-2 infection, and an alternative platform to test potential inhibitors targeting either the virus entry pathway or the immune responses following SARS-CoV-2 infection.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-022-00465-w.

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.

Plasma markers of COVID-19 severity: a pilot study

BACKGROUND

SARS-CoV-2 infected patients show heterogeneous clinical presentations ranging from mild symptoms to severe respiratory failure and death. Consequently, various markers reflect this wide spectrum of disease presentations.

METHODS

Our pilot cohort included moderate (n = 10) and severe (n = 10) COVID-19 patients, and 10 healthy controls. We determined plasma levels of nine acute phase proteins (APPs) by nephelometry, and full-length (M65), caspase-cleaved (M30) cytokeratin 18, and ADAMTS13 (a disintegrin-like and metalloprotease with thrombospondin type-1 motif 13) by ELISA. In addition, we examined whole plasma N-glycosylation by capillary gel electrophoresis coupled to laser-induced fluorescence detection (CGE-LIF).

RESULTS

When compared to controls, COVID-19 patients had significantly lower concentrations of ADAMTS13 and albumin (ALB) but higher M30, M65, α1-acid glycoprotein (AGP), α1-antitrypsin (AAT), ceruloplasmin (CP), haptoglobin (HP), and high-sensitivity C-reactive protein (hs-CRP). The concentrations of α1-antichymotrypsin (ACT), α2-macroglobulin (A2MG) and serum amyloid A (SAA) proteins did not differ. We found significantly higher levels of AAT and M65 but lower ALB in severe compared to moderate COVID-19 patients. N-glycan analysis of the serum proteome revealed increased levels of oligomannose- and sialylated di-antennary glycans and decreased non-sialylated di-antennary glycan A2G2 in COVID-19 patients compared to controls.

CONCLUSIONS

COVID-19-associated changes in levels and N-glycosylation of specific plasma proteins highlight complexity of inflammatory process and grant further investigations.

Identification of SARS-CoV-2 Proteins from Nasopharyngeal Swabs Probed by Multiple Reaction Monitoring Tandem Mass Spectrometry

Numerous reverse transcription polymerase chain reaction (RT-PCR) tests have emerged over the past year as the gold standard for detecting millions of cases of SARS-CoV-2 reported daily worldwide. However, problems with critical shortages of key reagents such as PCR primers and RNA extraction kits and unpredictable test reliability related to high viral replication cycles have triggered the need for alternative methodologies to PCR to detect specific COVID-19 proteins. Several authors have developed methods based on liquid chromatography with tandem mass spectrometry (LC-MS/MS) to confirm the potential of the technique to detect two major proteins, the spike and the nucleoprotein, of COVID-19. In the present work, an S-Trap mini spin column digestion protocol was used for sample preparation prodromal to LC-MS/MS analysis in multiple reactions monitoring ion mode (MRM) to obtain a comprehensive method capable of detecting different viral proteins. The developed method was applied to n. 81 oro/nasopharyngeal swabs submitted in parallel to quantitative reverse transcription PCR (RT-qPCR) assays to detect RdRP, the S and N genes specific for COVID-19, and the E gene for all Sarbecoviruses, including SARS-CoV-2 (with cycle negativity threshold set to 40). A total of 23 peptides representative of the six specific viral proteins were detected in the monitoring of 128 transitions found to have good ionic currents extracted in clinical samples that reacted differently to the PCR assay. The best instrumental response came from the FLPFQFGR sequence of spike [558-566] peptide used to test the analytical performance of the method that has good sensitivity with a low false-negative rate. Transition monitoring using a targeted MS approach has the great potential to detect the fragmentation reactions of any peptide molecularly defined by a specific amino acid sequence, offering the extensibility of the approach to any viral sequence including derived variants and thus providing insights into the development of new types of clinical diagnostics.