| Abstract | Microbial fuel cells (MFC) are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling-up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod-type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio-based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored |
| Text | 454825 2021 10.3390/pr9061038 bioelectrochemical systems microbial fuel cell depollution substrate biodegradation mathematical models microbial growth kinetic models gene regulatory network modelling MFC control MFC monitoring MFC applications Bio Electrochemical System Depollution Capabilities and Monitoring Applications Models, Applicability, Advanced Bio Based Concept for Predicting Pollutant Degradation and Microbial Growth Kinetics via Gene Regulation Modelling Tsipa A, Varnava CK, Grenni P, Ferrara V, Pietrelli A Tsipa A, Department of Civil and Environmental Engineering, University of Cyprus, Kallipoleos 75, Nicosia 1678, Cyprus; Nireas International Water Research Centre, University of Cyprus, P.O. Box 20537, Nicosia 1678, Cyprus Varnava CK, Department of Civil and Environmental Engineering, University of Cyprus, Kallipoleos 75, Nicosia 1678, Cyprus Grenni P, IRSA CNR Ferrara V, Department of Information Engineering, Electronics and Telecommunications, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy Pietrelli A Department of Information Engineering, Electronics and Telecommunications, University of Rome La Sapienza, Via Eudossiana 18, 00184 Rome, Italy; Ampere Lab., INSA LYON/ECL/UCBL 1, 36 Avenue Guy de Collongue, 69134 Ecully, France; ECP Lab., Universite Lumiere Lyon 2, 86 Rue Pasteur, 69007 Lyon, France Microbial fuel cells MFC are an emerging technology for waste, wastewater and polluted soil treatment. In this manuscript, pollutants that can be treated using MFC systems producing energy are presented. Furthermore, the applicability of MFC in environmental monitoring is described. Common microbial species used, release of genome sequences, and gene regulation mechanisms, are discussed. However, although scaling up is the key to improving MFC systems, it is still a difficult challenge. Mathematical models for MFCs are used for their design, control and optimization. Such models representing the system are presented here. In such comprehensive models, microbial growth kinetic approaches are essential to designing and predicting a biosystem. The empirical and unstructured Monod and Monod type models, which are traditionally used, are also described here. Understanding and modelling of the gene regulatory network could be a solution for enhancing knowledge and designing more efficient MFC processes, useful for scaling it up. An advanced bio based modelling concept connecting gene regulation modelling of specific metabolic pathways to microbial growth kinetic models is presented here; it enables a more accurate prediction and estimation of substrate biodegradation, microbial growth kinetics, and necessary gene and enzyme expression. The gene and enzyme expression prediction can also be used in synthetic and systems biology for process optimization. Moreover, various MFC applications as a bioreactor and bioremediator, and in soil pollutant removal and monitoring, are explored 9 Published version 10/06/2021 Pubblicazione Articolo pubblicato Processes_Tsipa2021.pdf Articolo in rivista MDPI 2227 9717 Processes Processes paola.grenni GRENNI PAOLA TA.P04.005.011 Vulnerabilita degli ecosistemi delle acque sotterranee e attenuazione naturale degli inquinanti nel suolo e nel sottosuolo |
