Composites, in which two or more material elements are combined to provide properties unattainable by single components, have a historical record dating to ancient times. Few include a living microbial community as a key design element. A logical basis for enabling bioelectronic composites stems from the phenomenon that certain microorganisms transfer electrons to external surfaces, such as an electrode. A bioelectronic composite that allows cells to be addressed beyond the confines of an electrode surface can impact bioelectrochemical technologies, including microbial fuel cells for power production and bioelectrosynthesis platforms where microbes produce desired chemicals. It is shown that the conjugated polyelectrolyte CPE‐K functions as a conductive matrix to electronically connect a three‐dimensional network of Shewanella oneidensis MR‐1 to a gold electrode, thereby increasing biocurrent ≈150‐fold over control biofilms. These biocomposites spontaneously assemble from solution into an intricate arrangement of cells within a conductive polymer matrix. While increased biocurrent is due to more cells in communication with the electrode, the current extracted per cell is also enhanced, indicating efficient long‐range electron transport. Further, the biocomposites show almost an order‐of‐magnitude lower charge transfer resistance than CPE‐K alone, supporting the idea that the electroactive bacteria and the conjugated polyelectrolyte work synergistically toward an effective bioelectronic composite.

Power generation and charge storage devices are commonly uncoupled when it comes to the design of materials relevant for their fabrication. Here, it is demonstrated that the biotic–abiotic composite comprising the self‐doped conjugated polyelectrolyte CPE‐K and electrogenic bacteria Shewanella oneidensis MR‐1 can reversibly switch its function between electrical current generation in chronoamperometry mode (≈150 mA m−2) and electrochemical energy storage as a pseudocapacitor with a specific capacitance of up to 80 F g−1. Interconversion of desirable properties for the different functions is achieved by the simple addition and removal of Mg2+ in the bulk electrolyte. Potentiostatic, galvanostatic, and electrochemical impedance spectroscopy characterization, accompanied by imaging and cell viability tests, indicate that the modulation of properties is a result of reversible changes in CPE‐K macrostructures and in the number of living bacteria within the composite. The results show the possibility to realize an “on‐demand” switch between current generation and charge storage by one integrated “living” material.

A novel conjugated oligoelectrolyte (COE) material, named S6, is designed to have a lipid‐bilayer stabilizing topology afforded by an extended oligophenylenevinylene backbone. S6 intercalates biological membranes acting as a hydrophobic support for glycerophospholipid acyl chains. Indeed, Escherichia coli treated with S6 exhibits a twofold improvement in butanol tolerance, a relevant feature to achieve within the general context of modifying microorganisms used in biofuel production. Filamentous growth, a morphological stress response to butanol toxicity in E. coli, is observed in untreated cells after incubation with 0.9% butanol (v/v), but is mitigated by S6 treatment. Real‐time fluorescence imaging using giant unilamellar vesicles reveals the extent to which S6 counters membrane instability. Moreover, S6 also reduces butanol‐induced lipopolysaccharide release from the outer membrane to further maintain cell integrity. These findings highlight a deliberate effort in the molecular design of a chain‐elongated COE to stabilize microbial membranes against environmental challenges.

A series of cationic conjugated oligoelectrolytes (COEs) was designed to understand how variations in molecular dimensions impact the relative activity against bacteria and mammalian cells.

New antibiotics are needed to battle growing antibiotic resistance, but the development process from hit, to lead, and ultimately to a useful drug takes decades. Although progress in molecular property prediction using machine-learning methods has opened up new pathways for aiding the antibiotics development process, many existing solutions rely on large data sets and finding structural similarities to existing antibiotics. Challenges remain in modeling unconventional antibiotic classes that are drawing increasing research attention. In response, we developed an antimicrobial activity prediction model for conjugated oligoelectrolyte molecules, a new class of antibiotics that lacks extensive prior structure−activity relationship studies. Our approach enables us to predict the minimum inhibitory concentration for E. coli K12, with 21 molecular descriptors selected by recursive elimination from a set of 5305 descriptors. This predictive model achieves an R 2 of 0.65 with no prior knowledge of the underlying mechanism. We find the molecular representation optimum for the domain is the key to good predictions of antimicrobial activity. In the case of conjugated oligoelectrolytes, a representation reflecting the three-dimensional shape of the molecules is most critical. Although it is demonstrated with a specific example of conjugated oligoelectrolytes, our proposed approach for creating the predictive model can be readily adapted to other novel antibiotic candidate domains.