Huize Chen, Cheng Chen, Ao Xia, Vinod Kumar, Jingmiao Zhang, Yun Huang, Xianqing Zhu, Xun Zhu, Qiang Liao
This study provides a predictive framework for substrate selection, in which tailoring surface functional-group density to match specific microbial biochemical motifs enables the development of high-performance systems, shifting the field from empirical trial and error to rational design.
The application of conductive substrates in anaerobic digestion has garnered growing interest due to their potential to enhance wastewater treatment performance. However, the initial attachment mechanisms governing distinct colonization across substrates remain unclear. In this study, the most commonly used conductive materials from previous research (biochar, activated carbon, magnetite, and graphite) were employed to investigate the adhesion and biofilm formation characteristics of a typical electron acceptor, Methanosarcina barkeri. Results indicate that adsorption is governed primarily by Lewis acid-base interactions between acidic functional groups on the activated carbon surface and methanochondroitin in the cellular outer layer. During early colonization, cell attachment to activated carbon was 2.3, 3.3 and 6.3 times higher than biochar, magnetite and graphite, respectively. This mechanism was corroborated by substrate modification experiments demonstrating that removing surface acidic functional groups reduced attachment capacity by 57.6%, whereas enriching carboxyl groups increased it by 116.8%. Theoretical calculations revealed that this enhancement arises from an attractive interaction energy of approximately -15 kcal/mol between methanochondroitin and carboxyl groups. Consequently, this advantage in early colonization promoted the preferential formation of a structurally mature, extracellular polymeric substances-rich biofilm on the activated carbon surface, ensuring mechanical stability under fluid shear stress and providing substantial material support for efficient electron transfer and storage. This study provides a predictive framework for substrate selection, in which tailoring surface functional-group density to match specific microbial biochemical motifs enables the development of high-performance systems, shifting the field from empirical trial and error to rational design.