Optimised stress - intensification of pyocyanin production with zinc oxide nanoparticles

利用氧化锌纳米粒子优化绿脓素生产的应力强化

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作者:Joanna Honselmann Genannt Humme, Kamila Dubrowska, Bartłomiej Grygorcewicz, Marta Gliźniewicz, Oliwia Paszkiewicz, Anna Głowacka, Daniel Musik, Grzegorz Story, Rafał Rakoczy, Adrian Augustyniak

Background

Pyocyanin is a blue pigment produced by Pseudomonas aeruginosa. Due to its unique redox properties over the last decade, it has gained more and more interest as a utile chemical. Nevertheless, it remains a rather costly reagent. It was previously shown that the production of pyocyanin can be enhanced by employing various

Conclusions

Pyocyanin production can be steered using ZnO nanoparticles. Elevated production of pyocyanin due to exposure to nanoparticles is followed by the number of changes in physiology of bacteria and is a result of the cellular stress. We showed that the stress response of bacteria can be optimised using statistical methods and result in producing the desired metabolite more effectively.

Results

The Design of Experiment (DoE) methodology allowed for calculating the optimal process temperature and nanoparticle concentration to intensify pyocyanin production. Low concentrations of the nanoparticles (6.06 µg/mL) and a temperature of 32℃ enhanced pyocyanin production, whereas higher concentrations of nanoparticles (275.75 µg/mL) and higher temperature stimulated biomass production and caused the abolishment of pyocyanin production. Elevated pigment production in zinc oxide nanoparticles-supplemented media was sustained in the scaled-up culture. Conducted analyses confirmed that observed stimulation of pyocyanin production is followed by higher membrane potential, altered gene expression, generation of reactive oxygen species, and accumulation of zinc in the cell's biomass. Conclusions: Pyocyanin production can be steered using ZnO nanoparticles. Elevated production of pyocyanin due to exposure to nanoparticles is followed by the number of changes in physiology of bacteria and is a result of the cellular stress. We showed that the stress response of bacteria can be optimised using statistical methods and result in producing the desired metabolite more effectively.

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