Studying pattern formation in Escherichia coli by engineering new modes of cell-cell communication
Zusammenfassung der Projektergebnisse
A major feature of living organisms is the ability to respond to environmental signals by triggering an internal response that leads to phenotypic alterations and changes in communal behavior. While bacteria are mostly studied as single cell systems, the construction of a diverse set of cell-cell communication systems will allow complex pattern formation in multicellular bacterial colonies as well. The aim of this project was to engineer Escherichia coli to sense a variety of extracellular signals with diverse diffusion and decay properties using two-component systems (TCSs) as a proof of concept. These signaling pathways typically consist of a membrane-bound sensor kinase that senses a specific environmental stimulus and a corresponding response regulator (RR) that mediates the cellular response, usually through differential expression of target genes. By creating artificial sensor circuits with desired behavior, I was not only able to address how these systems naturally work but also advance the development of new cellular tools for research, industry, and medicine. Light-switchable proteins enable unparalleled control of molecular biological processes in living organisms. Phytochrome-based light sensors from the marine cynaobacterium Synechocystis PCC 6803 have been successfully used to control gene expression in E. coli. However, both preexisting photoreversible TCSs, CcaS-CcaR (green/red) and Cph8-OmpR (red/far-red), possess very poor regulatory characteristics. Therefore, I systematically optimized both systems by genetic refactoring and engineering of the specific signaling proteins. The low leakiness and improved dynamic range make them a powerful optogenetic tool for a broad-range of scientific and engineering applications. The heme-nitric oxide/oxygen binding (H-NOX) domain is a recently discovered class of nitric oxide (NO) sensors in bacteria that function in a wide range of signaling pathways. Given the structural modularity of signaling proteins and variety of genetic arrangements in which this domain can be found, I hypothesized that H-NOX acts as an isolated NO sensing module in bacterial signaling processes. Thus, I incorporated H-NOX into an artificial TCS, resulting in a NO-dependent response. In addition to describing a NO sensor suitable for synthetic biological circuits, my results provided insights into the molecular mechanism of H-NOX- mediated signal transduction. A major challenge in our ability to characterize and engineer novel TCSs is that we often have limited knowledge of how these systems perform within the cell due poorly understood regulations. In addition, most bacteria that can be sequenced in environmental samples are not culturable in the laboratory. To overcome these limitations, I developed a breakthrough method for changing the input-output relationships of signaling pathways. Specifically, I have identified conserved amino acid residues at which the DNA-binding domains (DBDs) of RRs can be swapped for the DBD of a well-characterized RR, which can then activate reporter gene expression from a defined output promoter. My results demonstrated that this approach not only allows the design and test of signaling components in a rapid and generalizable way but also facilitates the study of cell-cell communication, or interactions between cells and non-living factors. In conclusion, my work provided new insights into the rational design of signaling pathways for the characterization and usage of sensor proteins with novel sensing specificities. By understanding the regulation of cell behavior, it will ultimately be possible to develop genetically modified organisms that respond differently to signals. This is even more important when engineering artificial signaling processes capable of giving rise to a wealth of complex cellular patterns.
Projektbezogene Publikationen (Auswahl)
- (2014) Refactoring and optimization of lightswitchable Escherichia coli two-component systems. ACS Synth Biol 3: 820-831
Schmidl SR, Sheth RU, Wu A, Tabor JJ
(Siehe online unter https://doi.org/10.1021/sb500273n)
