Ghanam Abdelghani, Cecillon Sebastien, Mohammadi Hasna, Amine Aziz, Buret François, Haddour Naoufel
Univ Lyon, Ecole Centrale de Lyon, INSA Lyon, Université Claude Bernard Lyon 1, CNRS, Ampère, UMR5005, 69130 Ecully, France.
Chemical Analysis and Biosensors Group, Laboratory of Process Engineering and Environment, Faculty of Science and Techniques, Hassan II University of Casablanca, B.P 146, Mohammedia 20000, Morocco.
Micromachines (Basel). 2023 Oct 30;14(11):2027. doi: 10.3390/mi14112027.
This study introduces the utilization of self-powered microbial fuel cell (MFC)-based biosensors for the detection of biotoxicity in wastewater. Current MFC-based biosensors lack specificity in distinguishing between different pollutants. To address this limitation, a novel approach is introduced, capitalizing on the adaptive capabilities of anodic biofilms. By acclimating these biofilms to specific pollutants, an enhancement in the selectivity of MFC biosensors is achieved. Notably, electrochemically active bacteria (EAB) were cultivated on 3D porous carbon felt with and without a model toxicant (target analyte), resulting in the development of toxicant-resistant anodic biofilms. The model toxicants, Pb ions and the antibiotic neomycin sulfate (NS), were deployed at a concentration of 1 mg L during MFC operation. The influence of toxicity on biofilm growth and power production was investigated through polarization and power density curves. Concurrently, the electrochemical activity of both non-adapted and toxicity-adapted biofilms was investigated using cyclic voltammetry. Upon maturation and attainment of peak powers, the MFC reactors were evaluated individually as self-powered biosensors for pollutant detection in fresh wastewater, employing the external resistor (ER) mode. The selected ER, corresponding to the maximum power output, was positioned between the cathode and anode of each MFC, enabling output signal tracking through a data logging system. Subsequent exposure of mature biofilm-based MFC biosensors to various concentrations of the targeted toxicants revealed that non-adapted mature biofilms generated similar current-time profiles for both toxicity models, whereas toxicity-adapted biofilms produced distinctive current-time profiles. Accordingly, these results suggested that merely by adapting the anodic biofilm to the targeted toxicity, distinct and identifiable current-time profiles can be created. Furthermore, these toxicity-adapted and non-adapted biofilms can be employed to selectively detect the pollutant via the differential measurement of electrical signals. This differentiation offers a promising avenue for selective pollutant detection. To the best of our current knowledge, this approach, which harnesses the natural adaptability of biofilms for enhanced sensor selectivity, represents a pioneering effort in the realm of MFC-based biosensing.
本研究介绍了基于自供电微生物燃料电池(MFC)的生物传感器在检测废水中生物毒性方面的应用。目前基于MFC的生物传感器在区分不同污染物方面缺乏特异性。为了解决这一局限性,引入了一种新方法,利用阳极生物膜的适应能力。通过使这些生物膜适应特定污染物,实现了MFC生物传感器选择性的提高。值得注意的是,在有和没有模型毒物(目标分析物)的情况下,在三维多孔碳毡上培养电化学活性细菌(EAB),从而形成抗毒物阳极生物膜。在MFC运行期间,模型毒物铅离子和抗生素硫酸新霉素(NS)的浓度为1 mg/L。通过极化曲线和功率密度曲线研究了毒性对生物膜生长和产电的影响。同时,使用循环伏安法研究了未适应和适应毒性的生物膜的电化学活性。在成熟并达到峰值功率后,将MFC反应器作为自供电生物传感器单独评估,用于检测新鲜废水中的污染物,采用外部电阻(ER)模式。对应于最大功率输出的选定ER置于每个MFC的阴极和阳极之间,通过数据记录系统实现输出信号跟踪。随后,将基于成熟生物膜的MFC生物传感器暴露于各种浓度的目标毒物中,结果表明,未适应的成熟生物膜在两种毒性模型下产生相似的电流-时间曲线,而适应毒性的生物膜产生独特的电流-时间曲线。因此,这些结果表明,仅仅通过使阳极生物膜适应目标毒性,就可以创建独特且可识别的电流-时间曲线。此外,这些适应毒性和未适应毒性的生物膜可用于通过电信号的差异测量来选择性检测污染物。这种差异为选择性污染物检测提供了一条有前途的途径。就我们目前所知,这种利用生物膜的自然适应性来提高传感器选择性的方法,在基于MFC的生物传感领域代表了一项开创性的工作。