Abstract

There is an increasing demand for convenient and accurate point-of-care tools that can detect and diagnose different stages of a disease in remote or impoverished settings. In recent years, lateral flow immunoassays (LFIA) have been indicated as a suitable medical diagnostic tool for these environments because they require little or no sample preparation, provide rapid and reliable results with no electronic components and thus can be manufactured at low costs and operated by unskilled personnel. However, even though they have been successfully applied to acute and chronic disease detection, LFIA based on gold nanoparticles, the standard marker, show serious limitations when high sensitivity is needed, such as early stage disease detection. Moreover, based on the lack of comparative information for label performance, significant optimization of the systems that are currently in use might be possible. To this end, in the presented work, we compare the detection limit between the four most used labels: colloidal-gold, silver enhanced gold, blue latex bead and carbon black nanoparticles. Preliminary results were obtained by using the biotin–streptavidin coupling as a model system and showed that carbon black had a remarkably low detection limit of 0.01μg/mL in comparison to 0.1μg/mL, 1μg/mL and 1mg/mL for silver-coated gold nanoparticles, gold nanoparticles and polystyrene beads, respectively. Therefore, as a proof of concept, carbon black was used in a detection system for Dengue fever. This was achieved by immobilizing monoclonal antibodies for the nonstructural glycoprotein (NS1) of the Dengue virus to carbon black. We found that the colorimetric detection limit of 57ng/mL for carbon black was ten times lower than the 575ng/mL observed for standard gold nanoparticles; which makes it sensitive enough to diagnose a patient on the first days of infection. We therefore conclude that, careful screening of detection labels should be performed as a necessary step during LFIA development in order to enhance the detection limit in a final test system.

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