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1- Department of Environment, La.C. Islamic Azad University, Lahijan, Iran.
Abstract: (17 Views)
Background: Bacterial tolerance to heavy metals, commonly expressed as minimum inhibitory concentration (MIC), is often evaluated alongside biosorption capacity. However, the extent to which MIC can reliably predict metal absorption has rarely been quantified. This study investigated the quantitative relationship between MIC and biosorption capacity in native bacterial strains isolated from industrially contaminated soils.
Methods: Twenty morphologically and biochemically distinct strains were isolated. MIC values for lead, zinc, cadmium, and a mixture of the three metals were determined using the broth microdilution method. Biosorption capacity was assessed through triplicate batch experiments, and the amount of metal absorbed by biomass was quantified using ICP-OES. A cell-free abiotic control confirmed that metal recovery without biomass remained below 0.5 ppm. The most efficient strains were identified by 16S rRNA gene sequencing. We analyzed the relationship between MIC and biosorption using Pearson correlation, one-way ANOVA, and regression analysis of log-transformed MIC values.
Results: Biosorption capacity consistently increased with resistance level. All tested systems showed significant positive correlations: the multi-metal mixture (r = 0.895), lead (r = 0.879), cadmium (r = 0.780), and zinc (r = 0.748), all with p < 0.001. Strains with higher MIC values showed significantly greater biosorption. Pseudomonas aeruginosa and Bacillus sp. were the most efficient biosorbing strains.
Conclusion: MIC can serve as a simple and cost-effective criterion for the preliminary selection of promising bacterial biosorbents for heavy-metal bioremediation.
Methods: Twenty morphologically and biochemically distinct strains were isolated. MIC values for lead, zinc, cadmium, and a mixture of the three metals were determined using the broth microdilution method. Biosorption capacity was assessed through triplicate batch experiments, and the amount of metal absorbed by biomass was quantified using ICP-OES. A cell-free abiotic control confirmed that metal recovery without biomass remained below 0.5 ppm. The most efficient strains were identified by 16S rRNA gene sequencing. We analyzed the relationship between MIC and biosorption using Pearson correlation, one-way ANOVA, and regression analysis of log-transformed MIC values.
Results: Biosorption capacity consistently increased with resistance level. All tested systems showed significant positive correlations: the multi-metal mixture (r = 0.895), lead (r = 0.879), cadmium (r = 0.780), and zinc (r = 0.748), all with p < 0.001. Strains with higher MIC values showed significantly greater biosorption. Pseudomonas aeruginosa and Bacillus sp. were the most efficient biosorbing strains.
Conclusion: MIC can serve as a simple and cost-effective criterion for the preliminary selection of promising bacterial biosorbents for heavy-metal bioremediation.
Type of Study: Original Article |
Subject:
Environmental Health, Sciences, and Engineering
Received: 2026/07/12 | Accepted: 2026/08/9
Received: 2026/07/12 | Accepted: 2026/08/9
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