Microbial toxicity of test substances in tetrazolium assay is often quantified while referring to IC50 values. However, the implication of such estimates is very limited and can differ across studies depending on prevailing test conditions. In this work, a factorial design-based end-point microbial assay was adopted, which suggests significant interaction (P= 0.041) between inoculum and tetrazolium dose on formazan production. A dynamic model framework was proposed to be incorporated in toxicity assay, that not only captures the nonlinear interdependency between biomass, substrate, formazan content but also measure the toxicity in terms of inhibition parameter. Microbial growth, glucose uptake, formazan production in presence and absence of heavy metal toxicant (Cu 2+ ) in designed batch studies were utilized for sequential estimation of model parameters and their bootstrap confidence intervals. A logistic growth model (R 2 >0.96) with multiplicative inhibition terms fit the experimental data reasonably well. Dynamic relative sensitivity analysis revealed that both microbial growth and formazan production profiles were sensitive to toxicant inhibition parameter. The adoption of a dynamic model framework as a stable index for the toxic potential of test substances can be extended to design a versatile, robust in-vitro assay system.
Microbial toxicity of test substances in tetrazolium assay is often quantified while referring to IC50 values. However, the implication of such estimates is very limited and can differ across studies depending on prevailing test conditions. In this work, a factorial design-based end-point microbial assay was adopted, which suggests significant interaction (P = 0.041) between inoculum and tetrazolium dose on formazan production. A dynamic model framework was proposed to be incorporated in toxicity assay, that not only captures the nonlinear interdependency between biomass, substrate, formazan content but also measure the toxicity in terms of inhibition parameter. Microbial growth, glucose uptake, formazan production in presence and absence of heavy metal toxicant (Cu2+) in designed batch studies were utilized for sequential estimation of model parameters and their bootstrap confidence intervals. A logistic growth model (R2 > 0.96) with multiplicative inhibition terms fit the experimental data reasonably well. Dynamic relative sensitivity analysis revealed that both microbial growth and formazan production profiles were sensitive to toxicant inhibition parameter. The adoption of a dynamic model framework as a stable index for the toxic potential of test substances can be extended to design a versatile, robust in-vitro assay system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.