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

Chivte, Prajkta; LaCasse, Zane; Seethi, Venkata Devesh Reddy; Bharti, Pratool; Bland, Joshua; Kadkol, Shrihari S.; Gaillard, Elizabeth R.

doi:10.1016/j.jmsacl.2021.09.001

Cited by 26 publications

(29 citation statements)

References 33 publications

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“…The main originality of our study was the use of saliva as the specimen. Although previous works reported the potential of MALDI-TOF MS to monitor SARS-CoV-2 proteins and host immune response against the virus using water gargle samples as saliva collection [53,54], these specimen collections would be unappropriated for young children or the elderly. Unlike NPSs, saliva collection is a non-invasive technique which can be performed by the patients themselves and prevents the risk of contamination for healthcare workers [55,56].…”

Section: Discussionmentioning

confidence: 99%

“…Unlike NPSs, saliva collection is a non-invasive technique which can be performed by the patients themselves and prevents the risk of contamination for healthcare workers [55,56]. Previous works reported the potential of MALDI-TOF MS to monitor SARS-CoV-2 proteins and host immune response against the virus using water gargle samples as saliva collection [53,54]. The introduction of the Salivette ® device has standardized the collection and improved the molecular detection of SARS-CoV-2 compared to NPSs [11].…”

Section: Discussionmentioning

confidence: 99%

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

Costa

Martin

Estellon

et al. 2022

JCM

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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).

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

Costa

Martin

Estellon

et al. 2022

JCM

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“…Additional peaks putatively corresponding to viral envelope glycoproteins ( m / z ∼26–47 kDa) were also observed in SARS-CoV-2-positive samples. Furthermore, Chivte et al 158 detected the peaks putatively assigned as immunoglobulin A (IgA) heavy chain ( m / z ∼56 kDa), Ig light chains ( m / z ∼23 kDa), IgM heavy chain ( m / z ∼70–71 kDa) and human α-amylase in unglycosylated (56 kDa) and glycosylated forms (62 kDa). The confidence in the identification of the peaks was supported through a comparison with observed m / z values for human serum immunoglobulins (IgA, IgG and IgM) and human α-amylase analysed after using the same protocol as for gargle/saliva samples.…”

Section: Maldi-tof Detection Of Specific Viral Proteins/peptidesmentioning

confidence: 99%

“…Hence, further validation studies must be performed with gargle/saliva samples whose positivity or negativity is simultaneously tested by RT-qPCR. A comparison to RT-qPCR tested samples was performed by Chivte et al ; 158 specifically the authors analysed 30 PCR positive and 30 PCR negative samples. Herein, the clinical state was determined based on the 5 selected peaks probably corresponding to spike protein fragments S1, S2/IgM heavy chain, IgA heavy chain/α-amylase, and an unknown potential biomarker near m / z 112 kDa.…”

Section: Maldi-tof Detection Of Specific Viral Proteins/peptidesmentioning

confidence: 99%

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

Guráň

Adam

et al. 2022

Analyst

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“…MALDI TOF analysis showed ≥90% agreement with RT-qPCR results, concluding that MALDI-TOF can be used to develop assays for COVID-19 in a relatively quick and inexpensive way. 11 …”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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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.

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

Cited by 26 publications

References 33 publications

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

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

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

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

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