Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring

Rajewicz, Wiktoria; Wu, Chao; Romano, Donato; Campo, Alexandre; Arvin, Farshad; Casson, Alexander J; Jansen van Vuuren, Godfried; Stefanini, Cesare; Varughese, Joshua Cherian; Lennox, Barry; Schönwetter-Fuchs, Sarah; Schmickl, Thomas; Thenius, Ronald

Abstract

Rapidly intensifying global warming and water pollution calls for more efficient and continuous environmental monitoring methods. Biohybrid systems connect mechatronic components to living organisms and this approach can be used to extract data from the organisms. Compared to conventional monitoring methods, they allow for a broader data collection over long periods, minimizing the need for sampling processes and human labour. We aim to develop a methodology for creating various bioinspired entities, here referred to as ‘biohybrids’, designed for long-term aquatic monitoring. Here, we test several aspects of the development of the biohybrid entity: autonomous power source, lifeform integration and partial biodegradability. An autonomous power source was supplied by microbial fuel cells which exploit electron flows from microbial metabolic processes in the sediments. Here, we show that by stacking multiple cells, sufficient power can be supplied. We integrated lifeforms into the developed bioinspired entity which includes organisms such as the zebra mussel Dreissena polymorpha and water flea Daphnia spp. The setups developed allowed for observing their stress behaviours. Through this, we can monitor changes in the environment in a continuous manner. The further development of this approach will allow for extensive, long-term aquatic data collection and create an early-warning monitoring system.

Citation

Rajewicz, W., Wu, C., Romano, D., Campo, A., Arvin, F., Casson, A. J., …Thenius, R. (2024). Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring. Bioinspiration & Biomimetics, 19(1), Article 015001. https://doi.org/10.1088/1748-3190/ad0c5d

• Journal Article Type: Article
• Acceptance Date: Nov 14, 2023
• Online Publication Date: Nov 22, 2023
• Publication Date: 2024-01
• Deposit Date: Nov 29, 2023
• Publicly Available Date: Nov 29, 2023
• Journal: Bioinspiration & Biomimetics
• Print ISSN: 1748-3182
• Publisher: IOP Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 19
• Issue: 1
• Article Number: 015001
• DOI: https://doi.org/10.1088/1748-3190/ad0c5d
• Keywords: bioinspiration, environmental monitoring, biohybrid
• Public URL: https://durham-repository.worktribe.com/output/1949668