RESUMO
Water quality and water management are worldwide issues. The analysis of pollutants and in particular, heavy metals, is generally conducted by sensitive but expensive physicochemical methods. Other alternative methods of analysis, such as microbial biosensors, have been developed for their potential simplicity and expected moderate cost. Using a biosensor for a long time generates many changes in the growth of the immobilized bacteria and consequently alters the robustness of the detection. This work simulated the operation of a biosensor for the long-term detection of cadmium and improved our understanding of the bioluminescence reaction dynamics of bioreporter bacteria inside an agarose matrix. The choice of the numerical tools is justified by the difficulty to measure experimentally in every condition the biosensor functioning during a long time (several days). The numerical simulation of a biomass profile is made by coupling the diffusion equation and the consumption/reaction of the nutrients by the bacteria. The numerical results show very good agreement with the experimental profiles. The growth model verified that the bacterial growth is conditioned by both the diffusion and the consumption of the nutrients. Thus, there is a high bacterial density in the first millimeter of the immobilization matrix. The growth model has been very useful for the development of the bioluminescence model inside the gel and shows that a concentration of oxygen greater than or equal to 22 % of saturation is required to maintain a significant level of bioluminescence. A continuous feeding of nutrients during the process of detection of cadmium leads to a biofilm which reduces the diffusion of nutrients and restricts the presence of oxygen from the first layer of the agarose (1 mm) and affects the intensity of the bioluminescent reaction. The main advantage of this work is to link experimental works with numerical models of growth and bioluminescence in order to provide a general purpose model to understand, anticipate, or predict the dysfunction of a biosensor using immobilized bioluminescent bioreporter in a matrix.