Dynamic characterization of bacterial optogenetic sensors and their use in manipulating the gut microbiome to extend host longevity

The development and characterization of novel sensor elements are critical to synthetic biology, as they enable engineered organisms to respond intelligently and predictably to their environment. Bacterial two component systems (TCSs) are a particularly attractive family of sensors by virtue of their ubiquity and sensing diversity. We have previously engineered multiple TCSs that have the unique advantage of sensing specific wavelengths of light. The precision of light enables such optogenetic sensors to remotely manipulate biological systems with unprecedented spatiotemporal control. However, in order to leverage these advantages, we must accurately model optogenetic TCS dynamics. In this work, we demonstrate the application of a simple characterization method from control theory & electrical engineering to two optogenetic TCSs. We then compare its performance to previously published models and identify regimes in which it is reasonably accurate. In the second portion of this work, we leverage the spatiotemporal precision of one such optogenetic TCS, CcaSR, to to remotely control E. coli expression dynamics in the gastrointestinal tract of live C. elegans nematodes. Next, we engineer a synthetic genetic system that places biosynthesis of the exopolysaccharide colanic acid (CA), which has been recently demonstrated to enhance C. elegans longevity, under control of CcaSR. Finally, we demonstrate that light-mediated activation of CA production in gut bacteria elicits a protective effect on a host mitochondrial phenotype. Our method can be used to control the expression of virtually any gene in gut-resident E. coli and should enable a new of era of mechanistic studies of gut microbe-host interactions. Finally, we describe the development of a software package designed to facilitate the high-throughput identification of arbitrary protein clusters, including TCSs and other sensors, from bacterial genomes. We validate this package by correctly identifying 24/27 TCSs in E. coli, and then extract 45654 putative, nonredundant TCSs from 5550 RefSeq genomes, including 115 optogenetic TCSs, as well as over 500 novel TCSs from the human gut microbiome. Characterizing TCSs from these libraries could yield new optogenetic sensors with diverse input spectra, new models for studying alternative TCS signaling architectures, and novel sensors of disease in the gut microbiome.