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Colorimetric Test for Fast Detection of SARS-CoV-2 in Nasal and Throat Swabs.

ABSTRACT: Mass testing is fundamental to face the pandemic caused by the coronavirus SARS-CoV-2 discovered at the end of 2019. To this aim, it is necessary to establish reliable, fast, and cheap tools to detect viral particles in biological material so to identify the people capable of spreading the infection. We demonstrate that a colorimetric biosensor based on gold nanoparticle (AuNP) interaction induced by SARS-CoV-2 lends itself as an outstanding tool for detecting viral particles in nasal and throat swabs. The extinction spectrum of a colloidal solution of multiple viral-target gold nanoparticles-AuNPs functionalized with antibodies targeting three surface proteins of SARS-CoV-2 (spike, envelope, and membrane)-is red-shifted in few minutes when mixed with a solution containing the viral particle. The optical density of the mixed solution measured at 560 nm was compared to the threshold cycle (C_t) of a real-time PCR (gold standard for detecting the presence of viruses) finding that the colorimetric method is able to detect very low viral load with a detection limit approaching that of the real-time PCR. Since the method is sensitive to the infecting viral particle rather than to its RNA, the achievements reported here open a new perspective not only in the context of the current and possible future pandemics, but also in microbiology, as the biosensor proves itself to be a powerful though simple tool for measuring the viral particle concentration.

SUBMITTER: Ventura BD

PROVIDER: S-EPMC7534800 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Detection of SARS-CoV-2 in nasal swabs using MALDI-MS

Project description:Detection of SARS-CoV-2 using RT–PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT–PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples.

2020-09-11 | PXD021388 | Pride

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Author Correction: Detection of SARS-CoV-2 in nasal swabs using MALDI-MS.

Project description:An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Project description:Nasopharyngeal (NP) swabs are considered the highest-yield sample for diagnostic testing for respiratory viruses, including SARS-CoV-2. The need to increase capacity for SARS-CoV-2 testing in a variety of settings, combined with shortages of sample collection supplies, have motivated a search for alternative sample types with high sensitivity. We systematically reviewed the literature to understand the performance of alternative sample types compared to NP swabs. We systematically searched PubMed, Google Scholar, medRxiv, and bioRxiv (last retrieval 1 October 2020) for comparative studies of alternative specimen types (saliva, oropharyngeal [OP], and nasal [NS] swabs) versus NP swabs for SARS-CoV-2 diagnosis using nucleic acid amplification testing (NAAT). A logistic-normal random-effects meta-analysis was performed to calculate % positive alternative-specimen, % positive NP, and % dual positives overall and in subgroups. The QUADAS 2 tool was used to assess bias. From 1,253 unique citations, we identified 25 saliva, 11 NS, 6 OP, and 4 OP/NS studies meeting inclusion criteria. Three specimen types captured lower % positives (NS [82%, 95% CI: 73 to 90%], OP [84%, 95% CI: 57 to 100%], and saliva [88%, 95% CI: 81 to 93%]) than NP swabs, while combined OP/NS matched NP performance (97%, 95% CI: 90 to 100%). Absence of RNA extraction (saliva) and utilization of a more sensitive NAAT (NS) substantially decreased alternative-specimen yield of positive samples. NP swabs remain the gold standard for diagnosis of SARS-CoV-2, although alternative specimens are promising. Much remains unknown about the impact of variations in specimen collection, processing protocols, and population (pediatric versus adult, late versus early in disease course), such that head-to head studies of sampling strategies are urgently needed.

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Detection of SARS-CoV-2 in nasal swabs using MALDI-MS

Project description:Detection of SARS-CoV-2 using RT-PCR and other advanced methods can achieve high accuracy. However, their application is limited in countries that lack sufficient resources to handle large-scale testing during the COVID-19 pandemic. Here, we describe a method to detect SARS-CoV-2 in nasal swabs using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and machine learning analysis. This approach uses equipment and expertise commonly found in clinical laboratories in developing countries. We obtained mass spectra from a total of 362 samples (211 SARS-CoV-2-positive and 151 negative by RT-PCR) without prior sample preparation from three different laboratories. We tested two feature selection methods and six machine learning approaches to identify the top performing analysis approaches and determine the accuracy of SARS-CoV-2 detection. The support vector machine model provided the highest accuracy (93.9%), with 7% false positives and 5% false negatives. Our results suggest that MALDI-MS and machine learning analysis can be used to reliably detect SARS-CoV-2 in nasal swab samples.

| MSV000086175 | MassIVE

Comparison of Nasal Swabs, Nasopharyngeal Swabs, and Saliva Samples for the Detection of SARS-CoV-2 and other Respiratory Virus Infections.

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