Comparative Evaluation and Quantitative Analysis of Loop-Mediated Isothermal Amplification Indicators.

Loop-mediated isothermal amplification (LAMP) as a diagnostic tool is rapidly gaining recognition and maturity. Among various advantages over traditional polymerase chain reaction, the ability to visually detect amplification by the incorporation of colorimetric indicators is one of its most unique features. There is an overwhelming variety of LAMP indicators in the literature, yet a comprehensive comparative study is lacking. This study evaluates the use of hydroxynaphthol blue, phenol red, calcein, leuco crystal violet, malachite green, and a fluorescent dye for visual detection. A method for objective quantitative analysis using ImageJ is described that is readily implemented in standard and microfluidic workflows. The work here also includes the largest inter-reader variability study involving 24 participants to evaluate these indicators. We found inaccuracies in visual assessment as bias and/or individual-based perception can exist, solidifying the need for objective analysis. There was not a "universal" indicator, although considerations in sample preparation, storage, and applicability are discussed in length.

Digital postprocessing and image segmentation for objective analysis of colorimetric reactions.

Recently, there has been an explosion of scientific literature describing the use of colorimetry for monitoring the progression or the endpoint result of colorimetric reactions. The availability of inexpensive imaging technology (e.g., scanners, Raspberry Pi, smartphones and other sub-$50 digital cameras) has lowered the barrier to accessing cost-efficient, objective detection methodologies. However, to exploit these imaging devices as low-cost colorimetric detectors, it is paramount that they interface with flexible software that is capable of image segmentation and probing a variety of color spaces (RGB, HSB, Y'UV, L*a*b*, etc.). Development of tailor-made software (e.g., smartphone applications) for advanced image analysis requires complex, custom-written processing algorithms, advanced computer programming knowledge and/or expertise in physics, mathematics, pattern recognition and computer vision and learning. Freeware programs, such as ImageJ, offer an alternative, affordable path to robust image analysis. Here we describe a protocol that uses the ImageJ program to process images of colorimetric experiments. In practice, this protocol consists of three distinct workflow options. This protocol is accessible to uninitiated users with little experience in image processing or color science and does not require fluorescence signals, expensive imaging equipment or custom-written algorithms. We anticipate that total analysis time per region of interest is ~6 min for new users and <3 min for experienced users, although initial color threshold determination might take longer.