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From consortium design to bioaugmented filters: scalable yeast-based strategies for lead remediation in water systems

Summary

Lead contamination in water is a serious health problem worldwide. This research developed a solution using natural yeast strains from a river that can remove lead from water. Scientists optimized three different yeast types to work together and incorporated them into filters, achieving up to 99.97% lead removal. This sustainable, low-cost approach could make clean water more accessible globally, especially in resource-limited areas.

Background

Heavy metal contamination, particularly lead, poses significant threats to water systems and human health. Conventional remediation methods like chemical precipitation and membrane filtration are costly and generate secondary contaminants. Yeast-based biosorption offers a sustainable alternative due to yeast’s abundance, rapid growth, and cell wall rich in metal-binding functional groups.

Objective

This study aimed to design an optimized yeast consortium from River Cauvery isolates for lead bioremediation and demonstrate its integration into alginate-based bioaugmented filters. The research sought to optimize consortium performance through computational modeling and validate the biosorptive potential of immobilized yeast in filter systems.

Results

Individual strain optimization showed Candida tropicalis achieved 99% removal at pH 7 and 2g biomass, while Clavispora lusitaniae reached ~100% removal at pH 5.5-7.0. The 3-strain consortium achieved 97.49% lead removal at 100 ppm and 52.11% at 200 ppm. Bioaugmented filters demonstrated superior performance with 99.97% removal at 100 ppm and 95.19% at 500 ppm for the 3-mix consortium, significantly outperforming control filters.

Conclusion

The study demonstrates that computational modeling can optimize yeast consortium biosorptive capacity for lead remediation. Bioaugmented alginate filters containing optimized yeast consortia provide efficient, scalable lead removal from water systems. The findings support the potential for industrial wastewater treatment applications and provide a sustainable alternative to conventional chemical-based heavy metal removal methods.
  • Published in:Frontiers in Microbiology,
  • Study Type:Experimental Study,
  • Source: PMC12457418; PMID: 41001057
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