Journal
NATURE
Volume 574, Issue 7780, Pages 702-+Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41586-019-1639-8
Keywords
-
Categories
Funding
- Office of Naval Research [N000141310074]
- NIH [T32GM007287]
Ask authors/readers for more resources
Gene duplication is a common and powerful mechanism by which cells create new signalling pathways(1,2), but recently duplicated proteins typically must become insulated from each other and from other paralogues to prevent unwanted crosstalk(3). A similar challenge arises when new sensors or synthetic signalling pathways are engineered within cells or transferred between genomes. How easily new pathways can be introduced into cells depends on the density and distribution of paralogous pathways in the sequence space that is defined by their specificity-determining residues(4,5). Here we directly investigate how crowded this sequence space is, by generating novel two-component signalling proteins in Escherichia coli using cell sorting coupled to deep sequencing to analyse large libraries designed on the basis of coevolutionary patterns. We produce 58 insulated pathways comprising functional kinase-substrate pairs that have different specificities than their parent proteins, and demonstrate that several of these new pairs are orthogonal to all 27 paralogous pathways in E. coli. Additionally, from the kinase-substrate pairs generated, we identify sets consisting of six pairs that are mutually orthogonal to each other, which considerably increases the two-component signalling capacity of E. coli. These results indicate that sequence space is not densely occupied. The relative sparsity of paralogues in sequence space suggests that new insulated pathways can arise easily during evolution, or be designed de novo. We demonstrate the latter by engineering a signalling pathway in E. coli that responds to a plant cytokinin, without crosstalk to extant pathways. Our work also demonstrates how coevolution-guided mutagenesis and the mapping of sequence space can be used to design large sets of orthogonal protein-protein interactions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available