Development of a Fully Automated Desktop Analyzer and Ultrahigh Sensitivity Digital Immunoassay for SARS-CoV-2 Nucleocapsid Antigen Detection.

SARS-CoV-2 desktop analyzer digital ELISA digital immunoassay nucleocapsid antigen

Journal

Biomedicines
ISSN: 2227-9059
Titre abrégé: Biomedicines
Pays: Switzerland
ID NLM: 101691304

Informations de publication

Date de publication:
15 Sep 2022
Historique:
received: 04 08 2022
revised: 09 09 2022
accepted: 11 09 2022
entrez: 23 9 2022
pubmed: 24 9 2022
medline: 24 9 2022
Statut: epublish

Résumé

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has had a significant impact on public health and the global economy. Several diagnostic tools are available for the detection of infectious diseases, with reverse transcription-polymerase chain reaction (RT-PCR) testing specifically recommended for viral RNA detection. However, this diagnostic method is costly, complex, and time-consuming. Although it does not have sufficient sensitivity, antigen detection by an immunoassay is an inexpensive and simpler alternative to RT-PCR. Here, we developed an ultrahigh sensitivity digital immunoassay (d-IA) for detecting SARS-CoV-2 nucleocapsid (N) protein as antigens using a fully automated desktop analyzer based on a digital enzyme-linked immunosorbent assay. We developed a fully automated d-IA desktop analyzer and measured the viral N protein as an antigen in nasopharyngeal (NP) swabs from patients with coronavirus disease. We studied nasopharyngeal swabs of 159 and 88 patients who were RT-PCR-negative and RT-PCR-positive, respectively. The limit of detection of SARS-CoV-2 d-IA was 0.0043 pg/mL of N protein. The cutoff value was 0.029 pg/mL, with a negative RT-PCR distribution. The sensitivity of RT-PCR-positive specimens was estimated to be 94.3% (83/88). The assay time was 28 min. Our d-IA system, which includes a novel fully automated desktop analyzer, enabled detection of the SARS-CoV-2 N-protein with a comparable sensitivity to RT-PCR within 30 min. Thus, d-IA shows potential for SARS-CoV-2 detection across multiple diagnostic centers including small clinics, hospitals, airport quarantines, and clinical laboratories.

Sections du résumé

BACKGROUND BACKGROUND
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has had a significant impact on public health and the global economy. Several diagnostic tools are available for the detection of infectious diseases, with reverse transcription-polymerase chain reaction (RT-PCR) testing specifically recommended for viral RNA detection. However, this diagnostic method is costly, complex, and time-consuming. Although it does not have sufficient sensitivity, antigen detection by an immunoassay is an inexpensive and simpler alternative to RT-PCR. Here, we developed an ultrahigh sensitivity digital immunoassay (d-IA) for detecting SARS-CoV-2 nucleocapsid (N) protein as antigens using a fully automated desktop analyzer based on a digital enzyme-linked immunosorbent assay.
METHODS METHODS
We developed a fully automated d-IA desktop analyzer and measured the viral N protein as an antigen in nasopharyngeal (NP) swabs from patients with coronavirus disease. We studied nasopharyngeal swabs of 159 and 88 patients who were RT-PCR-negative and RT-PCR-positive, respectively.
RESULTS RESULTS
The limit of detection of SARS-CoV-2 d-IA was 0.0043 pg/mL of N protein. The cutoff value was 0.029 pg/mL, with a negative RT-PCR distribution. The sensitivity of RT-PCR-positive specimens was estimated to be 94.3% (83/88). The assay time was 28 min.
CONCLUSIONS CONCLUSIONS
Our d-IA system, which includes a novel fully automated desktop analyzer, enabled detection of the SARS-CoV-2 N-protein with a comparable sensitivity to RT-PCR within 30 min. Thus, d-IA shows potential for SARS-CoV-2 detection across multiple diagnostic centers including small clinics, hospitals, airport quarantines, and clinical laboratories.

Identifiants

pubmed: 36140390
pii: biomedicines10092291
doi: 10.3390/biomedicines10092291
pmc: PMC9496537
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Japan Agency for Medical Research and Development
ID : JP20he0722003

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Auteurs

Ryotaro Chiba (R)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Kei Miyakawa (K)

Department of Microbiology, Yokohama City University School of Medicine, Yokohama 236-0004, Japan.

Kotaro Aoki (K)

Department of Microbiology and Infectious Diseases, Toho University School of Medicine, Tokyo 143-8540, Japan.

Takamitsu J Morikawa (TJ)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Yoshiki Moriizumi (Y)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Takuma Degawa (T)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Yoshiyuki Arai (Y)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Osamu Segawa (O)

Precision System Science Co., Ltd., Matsudo 271-0064, Japan.

Kengo Tanaka (K)

Precision System Science Co., Ltd., Matsudo 271-0064, Japan.

Hideji Tajima (H)

Precision System Science Co., Ltd., Matsudo 271-0064, Japan.

Susumu Arai (S)

Sumitomo Bakelite Co., Ltd., Tokyo 140-0002, Japan.

Hisatoshi Yoshinaga (H)

Sumitomo Bakelite Co., Ltd., Tokyo 140-0002, Japan.

Ryohei Tsukada (R)

Sumitomo Bakelite Co., Ltd., Tokyo 140-0002, Japan.

Akira Tani (A)

Olympus Corporation, Hachioji 192-8507, Japan.

Haruhito Fuji (H)

Olympus Corporation, Hachioji 192-8507, Japan.

Akinobu Sato (A)

Olympus Corporation, Hachioji 192-8507, Japan.

Yoshikazu Ishii (Y)

Department of Microbiology and Infectious Diseases, Toho University School of Medicine, Tokyo 143-8540, Japan.

Kazuhiro Tateda (K)

Department of Microbiology and Infectious Diseases, Toho University School of Medicine, Tokyo 143-8540, Japan.

Akihide Ryo (A)

Department of Microbiology, Yokohama City University School of Medicine, Yokohama 236-0004, Japan.

Toru Yoshimura (T)

Research and Development, Abbott Japan LLC, Matsudo 270-2214, Japan.

Classifications MeSH