Establishment of sustainable technology for methanol-based production of acetoin by metabolically engineered Bacillus methanolicus.

Rising atmospheric carbon concentrations affect global health, the economy, and overall quality of life. We are fast approaching climate tipping points that must be addressed, not only by reducing emissions but also through new innovation and action toward carbon capture for sequestration and utilization (CCSU). In this perspective, we delineate next-generation biotechnologies for CCSU supported by engineering design principles derived from ecological processes inspired by three major biomes (plant-soil, deep biosphere, and marine). These are to interface with existing industrial infrastructure and, in some cases, tap into the carbon sink potential of nature. To develop ecosystem-inspired biotechnology, it is important to identify accessible control points of CO 2 and CH 4 within a given system as well as value-chain opportunities that drive innovation. In essence, we must supplement natural biogeochemical carbon sinks with new bioengineering solutions. ll

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to “model status,” synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the “chassis effect.” It remains a major challenge to uncover which genome-encoded and biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of genetic circuit performance. This was accomplished using a comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis effect and characterize the performance dynamics of a genetic inverter circuit operating within 6 Gammaproteobacteria. Our results solidify the notion that genetic devices are strongly impacted by the host context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar performance of the genetic inverter, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.

Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to model status, synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the chassis-effect. It remains a major challenge to uncover which genome encoded and physiological biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of toggle switch performance. This was accomplished using comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis-effect and characterize the performance dynamics of a genetic toggle switch operating within six Gammaproteobacteria. Our results solidify the notion that genetic devices are significantly impacted by host-context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar toggle switch performance, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.