Evidence map›Paper›PMID 27381914›Full record

ArticleJournal of bacteriology2016

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

Joseph S Boyd, Ryan R Cheng, Mark L Paddock, Cigdem Sancar, Faruck Morcos, Susan S Golden

Open access · bronzeAbstract read
In one paragraph

Article in Journal of bacteriology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 48 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Joseph S BoydCenter for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
Ryan R ChengCenter for Theoretical Biological Physics, Rice University, Houston, Texas, USA.
Mark L PaddockCenter for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
Cigdem SancarCenter for Circadian Biology, University of California, San Diego, La Jolla, California, USA.
Faruck MorcosDepartment of Biological Sciences, University of Texas at Dallas, Richardson, Texas, USA faruckm@utdallas.edu sgolden@ucsd.edu.
Susan S GoldenCenter for Circadian Biology, University of California, San Diego, La Jolla, California, USA faruckm@utdallas.edu sgolden@ucsd.edu.
University of California, San Diego · USCenter for Theoretical Biological Physics · USThe University of Texas at Dallas · US

Funding

Undergraduate Summer Research Experience: Molecular and cellular mechanisms of circadian timekeeping in a prokaryote modelR35GM118290 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GOLDEN, SUSAN S · 2016 to 2025
$6.7M
THE PATHWAY THAT SETS THE CYANOBACTERIAL CIRCADIAN CLOCKR01GM062419 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GOLDEN, SUSAN S · 2001 to 2015
$3.9M
NIGMS NIH HHS R01 GM062419NIGMS NIH HHS R35 GM118290
6 · The paper itself

Abstract

unlabelledTwo-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. IMPORTANCE: 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.

Indexed as

Computer SimulationBacterial ProteinsCircadian ClocksEvolution, MolecularGene Expression Regulation, BacterialMutationSignal TransductionSynechococcusBacterial Proteins

Identifiers

PMID27381914
PMCPMC4999937
OpenAlexW2461611684

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.