Red-Light-Induced Genetic System for Control of Extracellular Electron Transfer.

Optogenetics is a powerful tool for spatiotemporal control of gene expression. Several light-inducible gene regulators have been developed to function in bacteria, and these regulatory circuits have been ported to new host strains. Here, we developed and adapted a red-light-inducible transcription factor for Shewanella oneidensis. This regulatory circuit is based on the iLight optogenetic system, which controls gene expression using red light. A thermodynamic model and promoter engineering were used to adapt this system to achieve differential gene expression in light and dark conditions within a S. oneidensis host strain. We further improved the iLight optogenetic system by adding a repressor to invert the genetic circuit and activate gene expression under red light illumination. The inverted iLight genetic circuit was used to control extracellular electron transfer within S. oneidensis. The ability to use both red- and blue-light-induced optogenetic circuits simultaneously was also demonstrated. Our work expands the synthetic biology capabilities in S. oneidensis, which could facilitate future advances in applications with electrogenic bacteria.

Computation in bacterial communities.

Bacteria across many scales are involved in a dynamic process of information exchange to coordinate activity and community structure within large and diverse populations. The molecular components bacteria use to communicate have been discovered and characterized, and recent efforts have begun to understand the potential for bacterial signal exchange to gather information from the environment and coordinate collective behaviors. Such computations made by bacteria to coordinate the action of a population of cells in response to information gathered by a multitude of inputs is a form of collective intelligence. These computations must be robust to fluctuations in both biological, chemical, and physical parameters as well as to operate with energetic efficiency. Given these constraints, what are the limits of computation by bacterial populations and what strategies have evolved to ensure bacterial communities efficiently work together? Here the current understanding of information exchange and collective decision making that occur in microbial populations will be reviewed. Looking toward the future, we consider how a deeper understanding of bacterial computation will inform future direction in microbiology, biotechnology, and biophysics.