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Flow-Based CL-SMIA for the Quantification of Protein Biomarkers from Nasal Secretions in Comparison with Sandwich ELISA.
- Source :
-
Biosensors [Biosensors (Basel)] 2023 Jun 22; Vol. 13 (7). Date of Electronic Publication: 2023 Jun 22. - Publication Year :
- 2023
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Abstract
- Protein biomarkers in nasal secretions can be used as a measure to differentiate between allergies, airway diseases and infections for non-invasive diagnostics. The point-of-care quantification of biomarker levels using flow-based microarray facilitates precise and rapid diagnosis and displays the potential for targeted and effective treatment. For the first time, we developed a flow-based chemiluminescence sandwich microarray immunoassay (CL-SMIA) for the quantification of nasal interferon-beta (IFN-β) on the Microarray Chip Reader-Research (MCR-R). Polycarbonate foils are used as a cost-effective surface for immobilizing capture antibodies. By using a commercially available set of anti-human IFN-β antibodies, the CL-SMIA can be compared directly to an enzyme-linked immunosorbent assay (ELISA) performed in microtiter plates concerning the bioanalytical performance and economic issues. Pre-incubation of the sample with detection antibodies facilitates the lower consumption of detection antibodies, as this allows for a longer interaction time between the antibody and the biomarker. The direct injection of pre-incubated samples into the microarray chips eliminates the adsorption of proteins in the tubing as well as the contamination of the tubing and valves of the MCR-R with clinical samples. The small flow cell allows for a low sample volume of 50 μL. The limit of detection of 4.53 pg mL <superscript>-1</superscript> was slightly increased compared to a sandwich ELISA performed on microtiter plates which were 1.60 pg mL <superscript>-1</superscript> . The possibility to perform the CL-SMIA in a multiplexed mode makes it a promising assay for the rapid and cost-effective non-invasive detection of biomarkers in nasal secretions.
Details
- Language :
- English
- ISSN :
- 2079-6374
- Volume :
- 13
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Biosensors
- Publication Type :
- Academic Journal
- Accession number :
- 37504069
- Full Text :
- https://doi.org/10.3390/bios13070670