title: A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.
abstract: Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems.
  
  
  
  Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks.
authors.affiliation: Center for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
authors.forename: Joseph S
authors.initials: JS
authors.lastname: Boyd
authors.affiliation: Center for Theoretical Biological Physics, Rice University, Houston, Texas, USA.
authors.forename: Ryan R
authors.initials: RR
authors.lastname: Cheng
authors.affiliation: Center for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
authors.forename: Mark L
authors.initials: ML
authors.lastname: Paddock
authors.affiliation: Center for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
authors.forename: Cigdem
authors.initials: C
authors.lastname: Sancar
authors.affiliation: Department of Biological Sciences, University of Texas at Dallas, Richardson, Texas, USA faruckm@utdallas.edu sgolden@ucsd.edu.
authors.forename: Faruck
authors.initials: F
authors.lastname: Morcos
authors.affiliation: Center for Circadian Biology, University of California, San Diego, La Jolla, California, USA faruckm@utdallas.edu sgolden@ucsd.edu.
authors.forename: Susan S
authors.initials: SS
authors.lastname: Golden
mesh_terms: D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism*; D057906:Circadian Clocks / Q000502:physiology*; D003198:Computer Simulation; D019143:Evolution, Molecular; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology*; D009154:Mutation; D015398:Signal Transduction / Q000502:physiology; D046940:Synechococcus / Q000235:genetics / Q000378:metabolism*
chemical_list: D001426:Bacterial Proteins