An innovative mixture sampling strategy with uniform design: Application to global sensitivity analysis of mixture...

Global sensitivity analysis combined with quantitative high-throughput screening (GSA-qHTS) uses random starting points of the trajectories in mixture design, which may lead to potential contingency and a lack of representativeness. Moreover, a scenario in which all factor levels were at stimulatory effects was not considered, thereby hindering a comprehensive understanding of GSA-qHTS. Accordingly, this study innovatively introduced an optimised experimental design, uniform design (UD), to generate non-random and representative sample points with smaller uniformity deviation as starting points of multiple trajectories. By combining UD with the previously optimised one-factor-at-a-time (OAT) method, a novel mixture design method was developed (UD-OAT). The single toxicity tests showed that three pyridinium and five imidazolium ionic liquids (ILs) exerted stimulatory effects on Vibrio qinghaiensis sp.-Q67; thus, four stimulatory effective concentrations of each IL were selected as factor levels. The UD-OAT generated 108 mixture samples with equal frequency and without repetition. High-throughput microplate toxicity analysis revealed that all 108 mixtures exhibited inhibitory effects. Among these, type B mixtures exhibited increasing toxicities that subsequently decreased, unlike type C mixtures, which consistently increased over time. GSA successfully identified three of the eight ILs as important factors influencing the toxicities of the mixtures. When individual ILs produced stimulatory effects, mixtures containing two to three ILs exhibited either stimulatory effects or none. In contrast, mixtures containing five to eight ILs exhibited inhibitory effects, while those containing four ILs showed a transition from stimulatory to inhibitory effects. This study provides a novel mixture design method for studying mixture toxicity and fills the application gap of GSA-qHTS. The phenomenon of individuals being beneficial while mixtures can be harmful challenges traditional mixture risk assessments.