A multi-index screening framework for selecting bacterial and fungal isolates for heavy-metal detoxification

Heavy-metal contamination of wastewater represents a major environmental challenge because of its persistence, toxicity, and bioaccumulation potential in aquatic ecosystems. Microbial bioremediation has emerged as a sustainable and cost-effective approach for detoxifying metal-contaminated water. However, most previous studies evaluate remediation performance using single indicators, such as removal efficiency or biosorption capacity, which provide limited insight into ecological risk reduction. In this study, a multi-index screening framework was developed to evaluate the detoxification potential of eight bacterial and fungal isolates: four bacteria (Bacillus subtilis, Pseudomonas aeruginosa, Acinetobacter baumannii, Rhodococcus erythropolis) and four fungi (Aspergillus niger, Penicillium spp., Trametes versicolor, Fusarium begoniae). Experiments were conducted using synthetic wastewater containing chromium (Cr), lead (Pb), copper (Cu), and zinc (Zn) under controlled laboratory conditions. Microbial remediation performance was assessed using removal efficiency together with multiple contamination and risk indices, including contamination factor (CF), pollution load index (PLI), potential ecological risk index (PERI), integrated pollution ratio (IPI), cumulative normalized metal load (TI), and relative improvement metric (EQI). Statistical analysis (p < 0.05) confirmed significant temporal changes in heavy-metal concentrations during the remediation period. The results showed that Pseudomonas aeruginosa and Penicillium spp. exhibited the strongest overall remediation performance among the tested bacterial and fungal treatments, respectively, achieving substantial reductions in heavy-metal concentrations and associated treatment-relative pollution and ecological-risk metrics during the 20-d treatment period. The integration of microbial removal efficiency with ecological risk assessment provides a more comprehensive evaluation of detoxification performance compared with conventional approaches. This multi-index framework therefore provides a systematic laboratory-scale approach for identifying microbial candidates with strong heavy-metal remediation potential and for comparing changes in metal removal and associated environmental risk during treatment.