Microplate luminescence automated digital analyzer for medicinal plants evaluation on quorum sensing inhibition

Quorum sensing is a mechanism used by most of pathogenic bacteria to coordinate their gene expression. Through this kind of mechanism the bacteria could detect the density of their local population until at a certain level they will act together to emerge virulence which cause disease in their host organism. Thus, the inhibition ability to quorum sensing mechanism is commonly used as an indicator to evaluate the potentiality of extracts from plants as antibacterial in drugs development. The quorum sensing activity could be detected using luminescence method. When the colony of bacteria reach the quorum and express certain activity, the luminescence will be produced. Microplate is a kind of experiment media which is used to conduct such experiment. The luminescence as the experiment result were captured as a digital image. The luminescence then examined to determine the plant performance to inhibit the bacteria virulence activity. Regarding most of the researcher's experience, it is believed that manual evaluation of those luminescence images is hard to interpret due to subjectivity factor and also inefficiency in time, especially when working with a large number of experiments. Therefore, in this research we developed a computer application to run quantification of the luminescence automatically. The automation process begin with gridding algorithm followed by object recognition and segmentation algorithm based on neural network learning. In order to improve the accuracy, image enhancement module were also attached to the system. In the output section, the quantification report presented using some statistical parameter to simplify interpretation and facilitate the researcher to run additional data analysis. With this application, the potentiality of extracts from plants as antibacterial agent could be inferred quickly, easily and accurately.