A combined approach of MALDI-TOF mass spectrometry and multivariate analysis as a potential tool for the detection of SARS-CoV-2 virus in nasopharyngeal swabs

Direct sub-atmospheric pressure ionization mass spectrometry: Evaporation/sublimation-driven ionization is amazing, fundamentally, and practically

This paper covers direct sub-atmospheric pressure ionization mass spectrometry (MS). The discovery, applications, and mechanistic aspects of novel ionization processes for use in MS that are not based on the high-energy input from voltage, laser, and/or high temperature but on sublimation/evaporation within a region linking a higher to lower pressure and modulated by heat and collisions, are discussed, including how this new reality has guided a series of discoveries, instrument developments, and commercialization. A research focus, inter alia, is on how best to understand, improve, and use these novel ionization processes, which convert volatile and nonvolatile compounds from solids (sublimation) or liquids (evaporation) into gas-phase ions for analysis by MS providing reproducible, accurate, sensitive, and prompt results. Our perception on how these unprecedented versus traditional ionization processes/methods relate to each other, how they can be made to coexist on the same mass spectrometer, and an outlook on new and expanded applications (e.g., clinical, portable, fast, safe, and autonomous) is presented, and is based on ST's Opening lecture presentation at the Nordic Mass spectrometry Conference, Geilo, Norway, January 2023. Focus will be on matrix-assisted ionization (MAI) and solvent-assisted ionization (SAI) MS covering the period from 2010 to 2023; a potential paradigm shift in the making.

The Impact of Artificial Intelligence on Microbial Diagnosis

Traditional microbial diagnostic methods face many obstacles such as sample handling, culture difficulties, misidentification, and delays in determining susceptibility. The advent of artificial intelligence (AI) has markedly transformed microbial diagnostics with rapid and precise analyses. Nonetheless, ethical considerations accompany AI adoption, necessitating measures to uphold patient privacy, mitigate biases, and ensure data integrity. This review examines conventional diagnostic hurdles, stressing the significance of standardized procedures in sample processing. It underscores AI's significant impact, particularly through machine learning (ML), in microbial diagnostics. Recent progressions in AI, particularly ML methodologies, are explored, showcasing their influence on microbial categorization, comprehension of microorganism interactions, and augmentation of microscopy capabilities. This review furnishes a comprehensive evaluation of AI's utility in microbial diagnostics, addressing both advantages and challenges. A few case studies including SARS-CoV-2, malaria, and mycobacteria serve to illustrate AI's potential for swift and precise diagnosis. Utilization of convolutional neural networks (CNNs) in digital pathology, automated bacterial classification, and colony counting further underscores AI's versatility. Additionally, AI improves antimicrobial susceptibility assessment and contributes to disease surveillance, outbreak forecasting, and real-time monitoring. Despite a few limitations, integration of AI in diagnostic microbiology presents robust solutions, user-friendly algorithms, and comprehensive training, promising paradigm-shifting advancements in healthcare.

Potential of MALDI-TOF MS biotyping to detect deltamethrin resistance in the dengue vector Aedes aegypti

Insecticide resistance in mosquitoes is spreading worldwide and represents a growing threat to vector control. Insecticide resistance is caused by different mechanisms including higher metabolic detoxication, target-site modification, reduced penetration and behavioral changes that are not easily detectable with simple diagnostic methods. Indeed, most molecular resistance diagnostic tools are costly and labor intensive and then difficult to use for routine monitoring of insecticide resistance. The present study aims to determine whether mosquito susceptibility status against the pyrethroid insecticides (mostly used for mosquito control) could be established by the protein signatures of legs and/or thoraxes submitted to MALDI-TOF Mass Spectrometry (MS). The quality of MS spectra for both body parts was controlled to avoid any bias due to unconformity protein profiling. The comparison of MS profiles from three inbreeds Ae. aegypti lines from French Guiana (IRF, IR03, IR13), with distinct deltamethrin resistance genotype / phenotype and the susceptible reference laboratory line BORA (French Polynesia), showed different protein signatures. On both body parts, the analysis of whole protein profiles revealed a singularity of BORA line compared to the three inbreeding lines from French Guiana origin, suggesting that the first criteria of differentiation is the geographical origin and/or the breeding history rather than the insecticide susceptibility profile. However, a deeper analysis of the protein profiles allowed to identify 10 and 11 discriminating peaks from leg and thorax spectra, respectively. Among them, a specific peak around 4870 Da was detected in legs and thoraxes of pyrethroid resistant lines compared to the susceptible counterparts hence suggesting that MS profiling may be promising to rapidly distinguish resistant and susceptible phenotypes. Further work is needed to confirm the nature of this peak as a deltamethrin resistant marker and to validate the routine use of MS profiling to track insecticide resistance in Ae. aegypti field populations.

Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review

Healthcare-associated infections (HAIs) are the most common adverse events in healthcare and constitute a major global public health concern. Surveillance represents the foundation for the effective prevention and control of HAIs, yet conventional surveillance is costly and labor intensive. Artificial intelligence (AI) and machine learning (ML) have the potential to support the development of HAI surveillance algorithms for the understanding of HAI risk factors, the improvement of patient risk stratification as well as the prediction and timely detection and prevention of infections. AI-supported systems have so far been explored for clinical laboratory testing and imaging diagnosis, antimicrobial resistance profiling, antibiotic discovery and prediction-based clinical decision support tools in terms of HAIs. This review aims to provide a comprehensive summary of the current literature on AI applications in the field of HAIs and discuss the future potentials of this emerging technology in infection practice. Following the PRISMA guidelines, this study examined the articles in databases including PubMed and Scopus until November 2023, which were screened based on the inclusion and exclusion criteria, resulting in 162 included articles. By elucidating the advancements in the field, we aim to highlight the potential applications of AI in the field, report related issues and shortcomings and discuss the future directions.

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.

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.

Instrumentation development, improvement, simplification, and miniaturization: The multifunctional plate source for use in mass spectrometry

In remembrance of Prof. Dr Przybylski, we are presenting a vision towards his beloved mass spectrometry (MS) and its far-reaching promises outside of the academic laboratory. Sub-atmospheric pressure (AP) ionization MS is well positioned to make a step-change in direct ionization, a concept that allows sublimation/evaporation ionization and mass analyses of volatile and nonvolatile molecules from clean or dirty samples, directly, accurately, sensitively, and in a straightforward manner that has the potential to expand the field of MS into unchartered application areas. Contrary to ambient ionization MS, ionization commences in the sub-AP region of the mass spectrometer, important for practical and safety reasons, and offers inter alia, simplicity, speed, sensitivity, and robustness directly from real-world samples without cleanup. The plate source concept, presented here, provides an easy to use, rapid, and direct sample introduction from AP into the sub-AP of a mass spectrometer. Utilizing sub-AP ionization MS based on the plate source concept, small to large molecules from various environments that would be deemed too dirty for some direct MS methods are demonstrated. The new source concept can be expanded to include multiple ionization methods using the same plate source "front end" without the need to vent the mass spectrometer between the different methods, thus allowing ionization of more compounds on the same mass spectrometer for which any one ionization method may be insufficient. Examples such as fentanyl, gamma-hydroxybutyric acid, clozapine, 1-propionyllysergic acid, hydrocodone angiotensin I and II, myoglobin, and carbonic anhydrase are included.

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.

Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models

Introduction. The different pathotypes of Escherichia coli can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 consists of stool culture of a diarrhoeal sample on enriched and/or selective media and identification of presumptive colonies and confirmation, which require a certain level of training and are time-consuming and expensive.Hypothesis. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a quick and easy way to obtain the protein spectrum of a microorganism, identify the genus and species, and detect potential biomarker peaks of certain characteristics.Aim. To verify the usefulness of MALDI-TOF MS to rapidly identify and differentiate STEC O157 : H7 from other E. coli pathotypes.Methodology. The direct method was employed, and the information obtained using Microflex LT platform-based analysis from 60 clinical isolates (training set) was used to detect differences between the peptide fingerprints of STEC O157 : H7 and other E. coli strains. The protein profiles detected laid the foundations for the development and evaluation of machine learning predictive models in this study.Results. The detection of potential biomarkers in combination with machine learning predictive models in a new set of 142 samples, called 'test set', achieved 99.3 % (141/142) correct classification, allowing us to distinguish between the isolates of STEC O157 : H7 and the other E. coli group. Great similarity was also observed with respect to this last group and the Shigella species when applying the potential biomarkers algorithm, allowing differentiation from STEC O157 : H7Conclusion. Given that STEC O157 : H7 is the main causal agent of haemolytic uremic syndrome, and based on the performance values obtained in the present study (sensitivity=98.5 % and specificity=100.0 %), the implementation of this technique provides a proof of principle for MALDI-TOF MS and machine learning to identify biomarkers to rapidly screen or confirm STEC O157 : H7 versus other diarrhoeagenic E. coli in the future.

Proteomic Analysis of Mucosal and Systemic Responses to SARS-CoV-2 Antigen

The mucosal environment of the upper respiratory tract is the first barrier of protection against SARS-CoV-2 transmission. However, the mucosal factors involved in viral transmission and potentially modulating the capacity to prevent such transmission have not fully been identified. In this pilot proteomics study, we compared mucosal and systemic compartments in a South African cohort of vaccinated and unvaccinated individuals undergoing maxillofacial surgery with previous history of COVID-19 or not. Inflammatory profiles were analyzed in plasma, nasopharyngeal swabs, and nasal and oral tissue explant cultures, using Olink and Luminex technologies. SARS-CoV-2-specific antibody levels were measured in serum and tissue explants. An increased pro-inflammatory proteomic profile was measured in the nasal compartment compared to plasma. However, IP-10 and MIG levels were higher in secretions than in nasal tissue, and the opposite was observed for TGF-β. Nasal anti-SARS-CoV-2 spike IgG correlated with mucosal MIG expression for all participants. A further positive correlation was found with IP-10 in BioNTech/Pfizer-vaccinated individuals. Systemic levels of anti-SARS-CoV-2 spike IgG elicited by this vaccine correlated with plasma IL-10, IL-6 and HBD4. Proteomic profiles measured in mucosal tissues and secretions using combined technologies could reveal correlates of protection at the mucosal portals of viral entry.

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.

Serum peptidome profiles immune response of COVID-19 Vaccine administration

Background

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused significant loss of life and property. In response to the serious pandemic, recently developed vaccines against SARS-CoV-2 have been administrated to the public. Nevertheless, the research on human immunization response against COVID-19 vaccines is insufficient. Although much information associated with vaccine efficacy, safety and immunogenicity has been reported by pharmaceutical companies based on laboratory studies and clinical trials, vaccine evaluation needs to be extended further to better understand the effect of COVID-19 vaccines on human beings.

Methods

We performed a comparative peptidome analysis on serum samples from 95 participants collected at four time points before and after receiving CoronaVac. The collected serum samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to profile the serum peptides, and also subjected to humoral and cellular immune response analyses to obtain typical immunogenicity information.

Results

Significant difference in serum peptidome profiles by MALDI-TOF MS was observed after vaccination. By supervised statistical analysis, a total of 13 serum MALDI-TOF MS feature peaks were obtained on day 28 and day 42 of vaccination. The feature peaks were identified as component C1q receptor, CD59 glycoprotein, mannose-binding protein C, platelet basic protein, CD99 antigen, Leucine-rich alpha-2-glycoprotein, integral membrane protein 2B, platelet factor 4 and hemoglobin subunits. Combining with immunogenicity analysis, the study provided evidence for the humoral and cellular immune responses activated by CoronaVac. Furthermore, we found that it is possible to distinguish neutralizing antibody (NAbs)-positive from NAbs-negative individuals after complete vaccination using the serum peptidome profiles by MALDI-TOF MS together with machine learning methods, including random forest (RF), partial least squares-discriminant analysis (PLS-DA), linear support vector machine (SVM) and logistic regression (LR).

Conclusions

The study shows the promise of MALDI-TOF MS-based serum peptidome analysis for the assessment of immune responses activated by COVID-19 vaccination, and discovered a panel of serum peptides biomarkers for COVID-19 vaccination and for NAbs generation. The method developed in this study can help not only in the development of new vaccines, but also in the post-marketing evaluation of developed vaccines.

The application of mass spectrometry method for the study and identification of medically important viruses (review of literature)

It is difficult to overestimate the urgency of the problem of well-timed diagnosis of viral infections. According to the WHO, dozens of outbreaks of viral diseases are recorded annually, both in developing and developed countries. Moreover, the seasonal flu virus alone is capable of infecting up to 20% of the population, even in European countries with a high level of medicine. And the annual number of deaths due to viral infections, according to official statistics, exceeds 600 thousand people around the world. That's why the provision of a reliable and fairly rapid diagnosis of viruses, along with subsequent therapy, makes a significant contribution to reducing the incidence of mortality. Despite the fact that PCR-based methods currently remain the most common method for identifying viruses in clinical practice, as recent experience shows, in addition to the already known disadvantages, in the event of large outbreaks, such test systems may simply not be in the required amount. In this regard, it is necessary to supplement and improve the existing tools for identification and research of clinically significant viruses. The MALDI-TOF mass spectrometry method combines a degree of accuracy and versatility, sufficient both for the identification of clinical strains isolated from patients, and for the study of the phenotypic properties of viruses in research laboratories and centers. This article presents and summarizes the main data on the existing or potential application of the method of time-of-flight mass spectrometry with matrix-associated laser desorption / ionization for the identification or study of viruses.

Visual Detection of COVID-19 from Materials Aspect

Abstract

In the recent COVID-19 pandemic, World Health Organization emphasized that early detection is an effective strategy to reduce the spread of SARS-CoV-2 viruses. Several diagnostic methods, such as reverse transcription-polymerase chain reaction (RT-PCR) and lateral flow immunoassay (LFIA), have been applied based on the mechanism of specific recognition and binding of the probes to viruses or viral antigens. Although the remarkable progress, these methods still suffer from inadequate cellular materials or errors in the detection and sampling procedure of nasopharyngeal/oropharyngeal swab collection. Therefore, developing accurate, ultrafast, and visualized detection calls for more advanced materials and technology urgently to fight against the epidemic. In this review, we first summarize the current methodologies for SARS-CoV-2 diagnosis. Then, recent representative examples are introduced based on various output signals (e.g., colorimetric, fluorometric, electronic, acoustic). Finally, we discuss the limitations of the methods and provide our perspectives on priorities for future test development.

Graphical Abstract

MALDI(+) FT-ICR Mass Spectrometry (MS) Combined with Machine Learning toward Saliva-Based Diagnostic Screening for COVID-19

Rapid identification of existing respiratory viruses in biological samples is of utmost importance in strategies to combat pandemics. Inputting MALDI FT-ICR MS (matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry) data output into machine learning algorithms could hold promise in classifying positive samples for SARS-CoV-2. This study aimed to develop a fast and effective methodology to perform saliva-based screening of patients with suspected COVID-19, using the MALDI FT-ICR MS technique with a support vector machine (SVM). In the method optimization, the best sample preparation was obtained with the digestion of saliva in 10 μL of trypsin for 2 h and the MALDI analysis, which presented a satisfactory resolution for the analysis with 1 M. SVM models were created with data from the analysis of 97 samples that were designated as SARS-CoV-2 positives versus 52 negatives, confirmed by RT-PCR tests. SVM1 and SVM2 models showed the best results. The calibration group obtained 100% accuracy, and the test group 95.6% (SVM1) and 86.7% (SVM2). SVM1 selected 780 variables and has a false negative rate (FNR) of 0%, while SVM2 selected only two variables with a FNR of 3%. The proposed methodology suggests a promising tool to aid screening for COVID-19.

MALDI-TOF Mass Spectrometric Detection of SARS-CoV-2 Using Cellulose Sulfate Ester Enrichment and Hot Acid Treatment

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. Here we report a novel strategy for the rapid detection of SARS-CoV-2 based on an enrichment approach exploiting the affinity between the virus and cellulose sulfate ester functional groups, hot acid hydrolysis, and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS). Virus samples were enriched using cellulose sulfate ester microcolumns. Virus peptides were prepared using the hot acid aspartate-selective hydrolysis and characterized by MALDI-TOF MS. Collected spectra were processed with a peptide fingerprint algorithm, and searching parameters were optimized for the detection of SARS-CoV-2. These peptides provide high sequence coverage for nucleocapsid (N protein) and allow confident identification of SARS-CoV-2. Peptide markers contributing to the detection were rigorously identified using bottom-up proteomics. The approach demonstrated in this study holds the potential for developing a rapid assay for COVID-19 diagnosis and detecting virus variants from a variety of sources, such as sewage and nasal swabs.

Identification of Endogenous Peptides in Nasal Swab Transport Media used in MALDI-TOF-MS Based COVID-19 Screening

Mass spectrometry (MS) based diagnostic detection of 2019 novel coronavirus infectious disease (COVID-19) has been postulated to be a useful alternative to classical PCR based diagnostics. These MS based approaches have the potential to be both rapid and sensitive and can be done on-site without requiring a dedicated laboratory or depending on constrained supply chains (i.e., reagents and consumables). Matrix-assisted laser desorption ionization (MALDI)-time-of-flight (TOF) MS has a long and established history of microorganism detection and systemic disease assessment. Previously, we have shown that automated machine learning (ML) enhanced MALDI-TOF-MS screening of nasal swabs can be both sensitive and specific for COVID-19 detection. The underlying molecules responsible for this detection are generally unknown nor are they required for this automated ML platform to detect COVID-19. However, the identification of these molecules is important for understanding both the mechanism of detection and potentially the biology of the underlying infection. Here, we used nanoscale liquid chromatography tandem MS to identify endogenous peptides found in nasal swab saline transport media to identify peptides in the same the mass over charge (m/z) values observed by the MALDI-TOF-MS method. With our peptidomics workflow, we demonstrate that we can identify endogenous peptides and endogenous protease cut sites. Further, we show that SARS-CoV-2 viral peptides were not readily detected and are highly unlikely to be responsible for the accuracy of MALDI based SARS-CoV-2 diagnostics. Further analysis with more samples will be needed to validate our findings, but the methodology proves to be promising.

Matrix-Assisted Laser Desorption and Ionization Time-of-Flight Mass Spectrometry Analysis for the Direct Detection of SARS-CoV-2 in Nasopharyngeal Swabs

The most common diagnostic method used for coronavirus disease-2019 (COVID-19) is real-time reverse transcription polymerase chain reaction (PCR). However, it requires complex and labor-intensive procedures and involves excessive positive results derived from viral debris. We developed a method for the direct detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in nasopharyngeal swabs, which uses matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-ToF MS) to identify specific peptides from the SARS-CoV-2 nucleocapsid phosphoprotein (NP). SARS-CoV-2 viral particles were separated from biological molecules in nasopharyngeal swabs by an ultrafiltration cartridge. Further purification was performed by an anion exchange resin, and purified NP was digested into peptides using trypsin. The peptides from SARS-CoV-2 that were inoculated into nasopharyngeal swabs were detected by MALDI-ToF MS, and the limit of detection was 10^6.7 viral copies. This value equates to 10^7.9 viral copies per swab and is approximately equivalent to the viral load of contagious patients. Seven NP-derived peptides were selected as the target molecules for the detection of SARS-CoV-2 in clinical specimens. The method detected between two and seven NP-derived peptides in 19 nasopharyngeal swab specimens from contagious COVID-19 patients. These peptides were not detected in four specimens in which SARS-CoV-2 RNA was not detected by PCR. Mutated NP-derived peptides were found in some specimens, and their patterns of amino acid replacement were estimated by accurate mass. Our results provide evidence that the developed MALDI-ToF MS-based method in a combination of straightforward purification steps and a rapid detection step directly detect SARS-CoV-2-specific peptides in nasopharyngeal swabs and can be a reliable high-throughput diagnostic method for COVID-19.

MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19

Background

Methods

Results

Conclusion

Consolidating the potency of Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) in viral diagnosis: extrapolating its applicability for COVID diagnosis?

MALDI-TOF-MS has essentially delivered more than expected with respect to clinical pathogens. Viruses are the most versatile entities of clinical pathogens that have challenged well-established microbiological methodologies. This review evaluates the existing scenario with respect to MALDI TOF-MS analytical technique in the successful analysis of viral pathogens. The milestones achieved with respect to detection and identification of COVID-19 has been presented. The fact that only a handful of scattered applications for COVID-19 exist has been pointed out in the review. Further, the lapses in the utilization of the available state-of-the art MALDI-TOF-MS variants/benchmark sophistications for COVID-19 analysis, are highlighted. When the world is seeking for rapid solutions for early, sensitive, rapid COVID-19 diagnosis, maybe MALDI-TOF-MS, may be the actual ‘gold standard’. Reverting to the title, this review emphasizes that there is a need for extrapolating MALDI-TOF-MS for COVID-19 analysis and this calls for urgent scientific attention.

Exploratory Study on Application of MALDI-TOF-MS to Detect SARS-CoV-2 Infection in Human Saliva

SARS-CoV-2 has caused a large outbreak since its emergence in December 2019. COVID-19 diagnosis became a priority so as to isolate and treat infected individuals in order to break the contamination chain. Currently, the reference test for COVID-19 diagnosis is the molecular detection (RT-qPCR) of the virus from nasopharyngeal swab (NPS) samples. Although this sensitive and specific test remains the gold standard, it has several limitations, such as the invasive collection method, the relative high cost and the duration of the test. Moreover, the material shortage to perform tests due to the discrepancy between the high demand for tests and the production capacities puts additional constraints on RT-qPCR. Here, we propose a PCR-free method for diagnosing SARS-CoV-2 based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) profiling and machine learning (ML) models from salivary samples. Kinetic saliva samples were collected at enrollment and ten and thirty days later (D0, D10 and D30), to assess the classification performance of the ML models compared to the molecular tests performed on NPS specimens. Spectra were generated using an optimized protocol of saliva collection and successive quality control steps were developed to ensure the reliability of spectra. A total of 360 averaged spectra were included in the study. At D0, the comparison of MS spectra from SARS-CoV-2 positive patients (n = 105) with healthy healthcare controls (n = 51) revealed nine peaks that significantly distinguished the two groups. Among the five ML models tested, support vector machine with linear kernel (SVM-LK) provided the best performance on the training dataset (accuracy = 85.2%, sensitivity = 85.1%, specificity = 85.3%, F1-Score = 85.1%). The application of the SVM-LK model on independent datasets confirmed its performances with 88.9% and 80.8% of correct classification for samples collected at D0 and D30, respectively. Conversely, at D10, the proportion of correct classification had fallen to 64.3%. The analysis of saliva samples by MALDI-TOF MS and ML appears as an interesting supplementary tool for COVID-19 diagnosis, despite the mitigated results obtained for convalescent patients (D10).

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.

Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry

BACKGROUND

The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date.

METHOD

23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity.

FINDINGS

Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application.

CONCLUSIONS

This systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.

Identification of Circulating Biomarkers of COVID-19 Using MALDI-TOF Mass Spectrometry

Matrix-assisted laser desorption/ionization source coupled with time-of-flight mass analyzer mass spectrometry (MALDI-TOF MS) is being widely used to obtain proteomic profiles for clinical purposes, as a fast, low-cost, robust, and efficient technique. Here we describe a method for biofluid analysis using MALDI-TOF MS for rapid acquisition of proteomic signatures of COVID-19 infected patients. By using solid-phase extraction, the method allows the analysis of biofluids in less than 15 min.

OUP accepted manuscript

Background

COVID-19 is a highly contagious respiratory disease that can be transmitted through human exhaled breath. It has caused immense loss and has challenged the healthcare sector. It has affected the economy of countries and thereby affected numerous sectors. Analysis of human breath samples is an attractive strategy for rapid diagnosis of COVID-19 by monitoring breath biomarkers.

Content

Breath collection is a noninvasive process. Various technologies are employed for detection of breath biomarkers like mass spectrometry, biosensors, artificial learning, and machine learning. These tools have low turnaround time, robustness, and provide onsite results. Also, MS-based approaches are promising tools with high speed, specificity, sensitivity, reproducibility, and broader coverage, as well as its coupling with various chromatographic separation techniques providing better clinical and biochemical understanding of COVID-19 using breath samples.

Summary

Herein, we have tried to review the MS-based approaches as well as other techniques used for the analysis of breath samples for COVID-19 diagnosis. We have also highlighted the different breath analyzers being developed for COVID-19 detection.

Mass spectrometry applied to diagnosis, prognosis, and therapeutic targets identification for the novel coronavirus SARS-CoV-2: A review

Mass spectrometry (MS) has found numerous applications in medicine and has been widely used in the detection and characterization of biomolecules associated with viral infections such as COVID-19. COVID-19 is a multisystem disease and, therefore, the need arises to carry out a careful and conclusive assessment of the pathophysiological parameters involved in the infection, to develop an effective therapeutic approach, assess the prognosis of the disease, and especially the early diagnosis of the infected population. Thus, the urgent need for highly accurate methods of diagnosis and prognosis of this infection presents new challenges for the development of laboratory medicine, whose methods require sensitivity, speed, and accuracy of the techniques for analyzing the biological markers involved in the infection. In this context, MS stands out as a robust analytical tool, with high sensitivity and selectivity, accuracy, low turnaround time, and versatility for the analysis of biological samples. However, it has not yet been adopted as a frontline clinical laboratory technique. Therefore, this review explores the potential and trends of current MS methods and their contribution to the development of new strategies to COVID-19 diagnosis and prognosis and how this tool can assist in the discovery of new therapeutic targets, in addition, to comment what could be the future of MS in medicine.

Rapid Screening of COVID-19 Directly from Clinical Nasopharyngeal Swabs Using the MasSpec Pen

The outbreak of COVID-19 has created an unprecedent global crisis. While the polymerase chain reaction (PCR) is the gold standard method for detecting active SARS-CoV-2 infection, alternative high-throughput diagnostic tests are of a significant value to meet universal testing demands. Here, we describe a new design of the MasSpec Pen technology integrated to electrospray ionization (ESI) for direct analysis of clinical swabs and investigate its use for COVID-19 screening. The redesigned MasSpec Pen system incorporates a disposable sampling device refined for uniform and efficient analysis of swab tips via liquid extraction directly coupled to an ESI source. Using this system, we analyzed nasopharyngeal swabs from 244 individuals including symptomatic COVID-19 positive, symptomatic negative, and asymptomatic negative individuals, enabling rapid detection of rich lipid profiles. Two statistical classifiers were generated based on the lipid information acquired. Classifier 1 was built to distinguish symptomatic PCR-positive from asymptomatic PCR-negative individuals, yielding a cross-validation accuracy of 83.5%, sensitivity of 76.6%, and specificity of 86.6%, and validation set accuracy of 89.6%, sensitivity of 100%, and specificity of 85.3%. Classifier 2 was built to distinguish symptomatic PCR-positive patients from negative individuals including symptomatic PCR-negative patients with moderate to severe symptoms and asymptomatic individuals, yielding a cross-validation accuracy of 78.4%, specificity of 77.21%, and sensitivity of 81.8%. Collectively, this study suggests that the lipid profiles detected directly from nasopharyngeal swabs using MasSpec Pen-ESI mass spectrometry (MS) allow fast (under a minute) screening of the COVID-19 disease using minimal operating steps and no specialized reagents, thus representing a promising alternative high-throughput method for screening of COVID-19.

MALDI-ToF protein profiling as a potential rapid diagnostic platform for COVID-19

More than a year after the COVID-19 pandemic was declared, the need still exists for accurate, rapid, inexpensive and non-invasive diagnostic methods that yield high specificity and sensitivity towards the current and newly emerging SARS-CoV-2 strains. Compared to the nasopharyngeal swabs, several studies have established saliva as a more amenable specimen type for early detection of SARS-CoV-2. Considering the limitations and high demand for COVID-19 testing, we employed MALDI-ToF mass spectrometry in the analysis of 60 gargle samples from human donors and compared the resultant spectra against COVID-19 status. Several standards, including isolated human serum immunoglobulins, and controls, such as pre-COVID-19 saliva and heat inactivated SARS-CoV-2 virus, were simultaneously analyzed to provide a relative view of the saliva and viral proteome as they would appear in this workflow. Five potential biomarker peaks were established that demonstrated high concordance with COVID-19 positive individuals. Overall, the agreement of these results with RT-qPCR testing on nasopharyngeal swabs was ≥90% for the studied cohort, which consisted of young and largely asymptomatic student athletes. From a clinical standpoint, the results from this pilot study suggest that MALDI-ToF could be used to develop a relatively rapid and inexpensive COVID-19 assay.

Mass Spectrometry-Based Human Breath Analysis: Towards COVID-19 Diagnosis and Research

COVID-19 is a highly contagious respiratory disease that can be infected through human exhaled breath. Human breath analysis is an attractive strategy for rapid diagnosis of COVID-19 in a non-invasive way by monitoring breath biomarkers. Mass spectrometry (MS)-based approaches offer a promising analytical platform for human breath analysis due to their high speed, specificity, sensitivity, reproducibility, and broad coverage, as well as its versatile coupling methods with different chromatographic separation, and thus can lead to a better understanding of the clinical and biochemical processes of COVID-19. Herein, we try to review the developments and applications of MS-based approaches for multidimensional analysis of COVID-19 breath samples, including metabolites, proteins, microorganisms, and elements. New features of breath sampling and analysis are highlighted. Prospects and challenges on MS-based breath analysis related to COVID-19 diagnosis and study are discussed.

Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19

SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that predict high (hospitalized) and low-risk (outpatients) cases of COVID-19 identified by a platform that combines machine learning with matrix-assisted laser desorption ionization mass spectrometry analysis. Sample preparation, MS, and data analysis parameters were optimized to achieve an overall accuracy of 92%, sensitivity of 93%, and specificity of 92% in dataset without feature selection. We identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of SDS-PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins, both already described as biomarkers for viral infections in the acute phase. Unbiased discrimination of high- and low-risk COVID-19 patients using a technology that is currently in clinical use may have a prompt application in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.

Metabolomics in the Diagnosis and Prognosis of COVID-19

Coronavirus disease 2019 (COVID-19) pandemic triggered an unprecedented global effort in developing rapid and inexpensive diagnostic and prognostic tools. Since the genome of SARS-CoV-2 was uncovered, detection of viral RNA by RT-qPCR has played the most significant role in preventing the spread of the virus through early detection and tracing of suspected COVID-19 cases and through screening of at-risk population. However, a large number of alternative test methods based on SARS-CoV-2 RNA or proteins or host factors associated with SARS-CoV-2 infection have been developed and evaluated. The application of metabolomics in infectious disease diagnostics is an evolving area of science that was boosted by the urgency of COVID-19 pandemic. Metabolomics approaches that rely on the analysis of volatile organic compounds exhaled by COVID-19 patients hold promise for applications in a large-scale screening of population in point-of-care (POC) setting. On the other hand, successful application of mass-spectrometry to detect specific spectral signatures associated with COVID-19 in nasopharyngeal swab specimens may significantly save the cost and turnaround time of COVID-19 testing in the diagnostic microbiology and virology laboratories. Active research is also ongoing on the discovery of potential metabolomics-based prognostic markers for the disease that can be applied to serum or plasma specimens. Several metabolic pathways related to amino acid, lipid and energy metabolism were found to be affected by severe disease with COVID-19. In particular, tryptophan metabolism via the kynurenine pathway were persistently dysregulated in several independent studies, suggesting the roles of several metabolites of this pathway such as tryptophan, kynurenine and 3-hydroxykynurenine as potential prognostic markers of the disease. However, standardization of the test methods and large-scale clinical validation are necessary before these tests can be applied in a clinical setting. With rapidly expanding data on the metabolic profiles of COVID-19 patients with varying degrees of severity, it is likely that metabolomics will play an important role in near future in predicting the outcome of the disease with a greater degree of certainty.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.

Mass spectrometry analytical responses to the SARS-CoV2 coronavirus in review

This article reviews the many and varied mass spectrometry based responses to the SARS-CoV2 coronavirus amidst a continuing global healthcare crisis. Although RT-PCR is the most prevalent molecular based surveillance approach, improvements in the detection sensitivities with mass spectrometry coupled to the rapid nature of analysis, the high molecular precision of measurements, opportunities for high sample throughput, and the potential for in-field testing, offer advantages for characterising the virus and studying the molecular pathways by which it infects host cells. The detection of biomarkers by MALDI-TOF mass spectrometry, studies of viral peptides using proteotyping strategies, targeted LC-MS analyses to identify abundant peptides in clinical specimens, the analysis of viral protein glycoforms, proteomics approaches to understand impacts of infection on host cells, and examinations of point-of-care breath analysis have all been explored. This review organises and illustrates these applications with reference to the many studies that have appeared in the literature since the outbreak. In this respect, those studies in which mass spectrometry has a major role are the focus, and only those which have peer-reviewed have been cited.

Novel application of automated machine learning with MALDI-TOF-MS for rapid high-throughput screening of COVID-19: a proof of concept

The 2019 novel coronavirus infectious disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an unsustainable need for molecular diagnostic testing. Molecular approaches such as reverse transcription (RT) polymerase chain reaction (PCR) offers highly sensitive and specific means to detect SARS-CoV-2 RNA, however, despite it being the accepted "gold standard", molecular platforms often require a tradeoff between speed versus throughput. Matrix assisted laser desorption ionization (MALDI)-time of flight (TOF)-mass spectrometry (MS) has been proposed as a potential solution for COVID-19 testing and finding a balance between analytical performance, speed, and throughput, without relying on impacted supply chains. Combined with machine learning (ML), this MALDI-TOF-MS approach could overcome logistical barriers encountered by current testing paradigms. We evaluated the analytical performance of an ML-enhanced MALDI-TOF-MS method for screening COVID-19. Residual nasal swab samples from adult volunteers were used for testing and compared against RT-PCR. Two optimized ML models were identified, exhibiting accuracy of 98.3%, positive percent agreement (PPA) of 100%, negative percent agreement (NPA) of 96%, and accuracy of 96.6%, PPA of 98.5%, and NPA of 94% respectively. Machine learning enhanced MALDI-TOF-MS for COVID-19 testing exhibited performance comparable to existing commercial SARS-CoV-2 tests.

Biological characteristics and biomarkers of novel SARS-CoV-2 facilitated rapid development and implementation of diagnostic tools and surveillance measures

Existing coronavirus named as a severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has speeded its spread across the globe immediately after emergence in China, Wuhan region, at the end of the year 2019. Different techniques, including genome sequencing, structural feature classification by electron microscopy, and chest imaging using computed tomography, are primarily used to diagnose and screen SARS-CoV-2 suspected individuals. Determination of the viral structure, surface proteins, and genome sequence has provided a design blueprint for the diagnostic investigations of novel SARS-CoV-2 virus and rapidly emerging diagnostic technologies, vaccine trials, and cell-entry-inhibiting drugs. Here, we describe recent understandings on the spike glycoprotein (S protein), receptor-binding domain (RBD), and angiotensin-converting enzyme 2 (ACE2) and their receptor complex. This report also aims to review recently established diagnostic technologies and developments in surveillance measures for SARS-CoV-2 as well as the characteristics and performance of emerging techniques. Smartphone apps for contact tracing can help nations to conduct surveillance measures before a vaccine and effective medicines become available. We also describe promising point-of-care (POC) diagnostic technologies that are under consideration by researchers for advancement beyond the proof-of-concept stage. Developing novel diagnostic techniques needs to be facilitated to establish automatic systems, without any personal involvement or arrangement to curb an existing SARS-CoV-2 epidemic crisis, and could also be appropriate for avoiding the emergence of a future epidemic crisis.

COVID-19 Pandemic: Review of Contemporary and Forthcoming Detection Tools

Recent severe acute respiratory syndrome 2 (SARS-CoV-2) known as COVID-19, presents a deadly challenge to the global healthcare system of developing and developed countries, exposing the limitations of health facilities preparedness for emerging infectious disease pandemic. Opportune detection, confinement, and early treatment of infected cases present the first step in combating COVID-19. In this review, we elaborate on various COVID-19 diagnostic tools that are available or under investigation. Consequently, cell culture, followed by an indirect fluorescent antibody, is one of the most accurate methods for detecting SARS-CoV-2 infection. However, restrictions imposed by the regulatory authorities prevented its general use and implementation. Diagnosis via radiologic imaging and reverse transcriptase PCR assay is frequently employed, considered as standard procedures, whereas isothermal amplification methods are currently on the verge of clinical introduction. Notably, techniques such as CRISPR-Cas and microfluidics have added new dimensions to the SARS-CoV-2 diagnosis. Furthermore, commonly used immunoassays such as enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay (LFIA), neutralization assay, and the chemiluminescent assay can also be used for early detection and surveillance of SARS-CoV-2 infection. Finally, advancement in the next generation sequencing (NGS) and metagenomic analysis are smoothing the viral detection further in this global challenge.

Point of Care Diagnostic Devices for Rapid Detection of Novel Coronavirus (SARS-nCoV19) Pandemic: A Review

Coronaviruses are recognized as causative agents of human diseases worldwide. In Wuhan, China, an outbreak of Severe acute respiratory syndrome novel Coronavirus (SARS-nCoV-2) was reported at the end of December 2019, causing 63 million COVID cases and 1.3 million deaths globally by 2 December, 2020. The transmission risk forecasts and the SARS-nCoV-2 epidemic pattern are progressive. Unfortunately, there is no specific FDA approved drugs or vaccines available currently to treat SARS-nCoV-2. In response to nCoV-2 spread, the rapid detection is crucial for estimating the severity of the disease and treatment of patients. Currently, there are several RT-PCR based diagnostic kits available for SARS-nCoV-2 detection, which are time-consuming, expensive, need advanced equipment facilities and trained personnel. The cost of diagnosis and the unavailability of sufficient test kits may prevent to check community transmission. Furthermore, expanding the testing facilities in asymptomatic cases in hotspots require more Point of Care (PoC) devices. Therefore, fast, inexpensive, and reliable methods of detection of SARS-nCoV-2 virus infection in humans is urgently required. The rapid and easy-to-use devices will facilitate onsite testing. In this review, nucleic acid assays, serological assays, multiplex assays, and PoC devices are discussed to understand various diagnostic approaches to reduce the spread and mortality rate in the future. Aptamer based detection is most specific, inexpensive and rapid detection of SARS-nCoV-2 without laboratory tools. To the best of our knowledge more than 900 SARS-nCoV-2 test kits are in pipeline, among 395 test kits are molecular bested test kits and only few test kits are developed using Aptamer technology https://www.finddx.org/covid-19/pipeline/.

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.

A concise discussion on the potential spectral tools for the rapid COVID-19 detection

Developing robust methods to detect the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a causative agent for the current global health pandemic, is an exciting area of research. Nevertheless, the currently used conventional reverse transcription-polymerase chain reaction (RT-PCR) technique in COVID-19 detection endures with some inevitable limitations. Consequently, the establishment of rapid diagnostic tools and quick isolation of infected patients is highly essential. Furthermore, the requirement of point-of-care testing is the need of the hour. Considering this, we have provided a brief review of the use of very recently reported robust spectral tools for rapid COVID-19 detection. The spectral tools include, colorimetric reverse transcription loop-mediated isothermal amplification (RT-LAMP) and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), with the admittance of principal component analysis (PCA) and machine learning (ML) for meeting the high-throughput and fool-proof platforms for the detection of SARS-CoV-2, are reviewed. Recently, these techniques have been readily applied to screen a large number of suspected patients within a short period and they demonstrated higher sensitivity for the detection of COVID-19 patients from unaffected human subjects.

Perspective on Proteomics for Virus Detection in Clinical Samples

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