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Research Article | Open Access

Rapid Sensing of Biological and Environmental Analytes Using Microwave-Accelerated Bioassays and a MATLAB Application

Enock Bonyi1, Edward Constance1, Zeenat Kukoyi1, Sanjeeda Jafar2, Kadir Aslan1( )
Department of Civil Engineering, Morgan State University, 1700 East Cold Spring Lane, Baltimore, Maryland 21251, USA
Department of Biology, Morgan State University, 1700 East Cold Spring Lane, Baltimore, Maryland 21251, USA
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Abstract

We report a method for rapid detection and analysis of biological and environmental analytes by microwave-accelerated bioassays (MABs) and a novel MATLAB-based image processing of colorimetric signals. In this regard, colorimetric bioassays for histidine-rich protein 2 (HRP-2) and microcystin-leucine arginine (MC-LR) toxin were carried out using MABs and without microwave heating (i.e, gold standard bioassays). Our MATLAB-based detection method is based on the direct correlation of color intensity of a solution calculated from images captured with a smartphone with the concentration of the biomolecule of interest using a MATLAB code developed in-house. We demonstrated that our MATLAB-based detection method can yield bioassay sensitivity comparable to the colorimetric gold standard tool, i.e., UV-Visible spectroscopy. In addition, colorimetric bioassay time for the HRP-2 assay (used in malaria diagnosis) and colorimetric MC-LR bioassay (used in MC-LR toxin diagnosis) was reduced from up to 2 hours at room temperature without microwave heating to 15 minutes using the MABs technique.

Keywords

AnalyteColorimetric bioassaysMicrowave-accelerated bioassaysMicrowave heatingMATLAB

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Nano Biomedicine and Engineering
Volume 11 Issue 2,
June 2019
Pages 111-123
DOI: 10.5101/nbe.v11i2.p111-123

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Bonyi E, Constance E, Kukoyi Z, et al. Rapid Sensing of Biological and Environmental Analytes Using Microwave-Accelerated Bioassays and a MATLAB Application. Nano Biomedicine and Engineering, 2019, 11(2): 111-123. https://doi.org/10.5101/nbe.v11i2.p111-123

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Received: 20 September 2018
Accepted: 13 February 2019
Published: 15 April 2019
© Enock Bonyi, Edward Constance, Zeenat Kukoyi, Sanjeeda Jafar, and Kadir Aslan.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.