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Data_Sheet_2_Bottom-up construction and screening of algae-bacteria consortia for pollutant biodegradation.xlsx

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/Data_Sheet_2_Bottom-up_construction_and_screening_of_algae-bacteria_consortia_for_pollutant_biodegradation_xlsx/25194206
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Microbial communities have been used as important biological tools for a variety of purposes associated with agriculture, the food industry and human health. Artificial engineering of microbial communities is an emerging field of research motivated by finding stable and efficient microbial systems. However, the successful design of microbial communities with desirable functions not only requires profound understanding of microbial activities, but also needs efficient approaches to piece together the known microbial traits to give rise to more complex systems. This study demonstrates the bottom-up integration of environmentally isolated phototrophic microalgae and chemotrophic bacteria as artificial consortia to bio-degrade selected volatile organic compounds (VOCs). A high throughput screening method based on 96-well plate format was developed for discovering consortia with bioremediation potential. Screened exemplar consortia were verified for VOCs degradation performance, among these, certain robust consortia were estimated to have achieved efficiencies of 95.72% and 92.70% and near 100% removal (7 days) of benzene, toluene, and phenol, respectively, with initial concentrations of 100 mg/L. VOCs degradation by consortia was mainly attributed to certain bacteria including Rhodococcus erythropolis, and Cupriavidus metallidurans, and directly contributed to the growth of microalgae Coelastrella terrestris (R = 0.82, p < 0.001). This work revealed the potential of converting VOCs waste into algal biomass by algae-bacteria consortia constructed through a bottom-up approach. The screening method enables rapid shortlisting of consortia combinatorial scenarios without prior knowledge about the individual strains or the need for interpreting complex microbial interactions.
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2024-02-09
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