Evidence map›Paper›PMID 23555304›Full record

ArticlePLoS genetics2013

Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

Thomas Wallach, Katja Schellenberg, Bert Maier, Ravi Kiran Reddy Kalathur, Pablo Porras, Erich E Wanker, Matthias E Futschik, Achim Kramer

Abstract read
In one paragraph

Article in PLoS genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  15. Circadian Mechanisms in Alcohol Use Disorder and Tissue Injury.Alcoholism, clinical and experimental research · 2018
    Review
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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

8 authors.

Thomas WallachLaboratory of Chronobiology, Charité-Universitätsmedizin, Berlin, Germany.
Katja Schellenberg
Bert Maier
Ravi Kiran Reddy Kalathur
Pablo Porras
Erich E Wanker
Matthias E Futschik
Achim Kramer

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Essentially all biological processes depend on protein-protein interactions (PPIs). Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour) clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression) suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc.) contributing to temporal organization of cellular physiology in an unprecedented manner.

Indexed as

CLOCK ProteinsARNTL Transcription FactorsCell CycleCircadian ClocksCircadian RhythmErbB ReceptorsHEK293 CellsHumansProtein Interaction MapsProtein Phosphatase 1Signal TransductionARNTL Transcription FactorsBMAL1 protein, humanCLOCK ProteinsEGFR protein, humanErbB ReceptorsProtein Phosphatase 1

Identifiers

PMID23555304
PMCPMC3610820

What OpenQuestion holds

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Registered trials

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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.