A DAMP-Based Assay for Rapid and Affordable Diagnosis of Bacterial Meningitis Agents:


Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
29 Jul 2024
Historique:
received: 08 07 2024
accepted: 25 07 2024
medline: 10 8 2024
pubmed: 10 8 2024
entrez: 10 8 2024
Statut: epublish

Résumé

The rapid and accurate diagnosis of meningitis is critical for preventing severe complications and fatalities. This study addresses the need for accessible diagnostics in the absence of specialized equipment by developing a novel diagnostic assay. The assay utilizes dual-priming isothermal amplification (DAMP) with unique internal primers to significantly reduce non-specificity. For fluorescence detection, the dye was selected among Brilliant Green, Thioflavin T, and dsGreen. Brilliant Green is preferred for this assay due to its availability, high fluorescence level, and optimal sample-to-background (S/B) ratio. The assay was developed for the detection of the primary causative agents of meningitis (

Identifiants

pubmed: 39125852
pii: ijms25158282
doi: 10.3390/ijms25158282
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Russian Science Foundation
ID : 22-75-10073

Auteurs

Liubov A Shkodenko (LA)

Laboratory of DNA-Nanosensor Diagnostics, ITMO University, Lomonosova Street, 9, 191002 St Petersburg, Russia.

Al-Abbass Mohamed (AA)

Laboratory of DNA-Nanosensor Diagnostics, ITMO University, Lomonosova Street, 9, 191002 St Petersburg, Russia.

Muhannad Ateiah (M)

Laboratory of DNA-Nanosensor Diagnostics, ITMO University, Lomonosova Street, 9, 191002 St Petersburg, Russia.

Maria S Rubel (MS)

Laboratory of DNA-Nanosensor Diagnostics, ITMO University, Lomonosova Street, 9, 191002 St Petersburg, Russia.

Elena I Koshel (EI)

Laboratory of DNA-Nanosensor Diagnostics, ITMO University, Lomonosova Street, 9, 191002 St Petersburg, Russia.

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Classifications MeSH