Evidence map›Paper›PMID 35089921›Full record

ArticlePLoS computational biology2022

Modeling the temporal dynamics of master regulators and CtrA proteolysis in Caulobacter crescentus cell cycle.

Chunrui Xu, Henry Hollis, Michelle Dai, Xiangyu Yao, Layne T Watson, Yang Cao, Minghan Chen

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

4 citing papers in PubMed, 5 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

7 authors at 2 institutions in 1 country.

Chunrui XuGenetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID 0000-0002-4755-1593
Henry HollisDepartment of Computer Science, Wake Forest University, Winston-Salem, North Carolina, United States of America.ORCID 0000-0002-6088-2792
Michelle DaiDepartment of Computer Science, Wake Forest University, Winston-Salem, North Carolina, United States of America.
Xiangyu YaoGenetics, Bioinformatics, and Computational Biology, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID 0000-0003-0804-1061
Layne T WatsonDepartment of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.
Yang CaoDepartment of Computer Science, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID 0000-0001-9336-3748
Minghan ChenDepartment of Computer Science, Wake Forest University, Winston-Salem, North Carolina, United States of America.ORCID 0000-0002-7321-8962
Virginia Tech · USWake Forest University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cell cycle of Caulobacter crescentus involves the polar morphogenesis and an asymmetric cell division driven by precise interactions and regulations of proteins, which makes Caulobacter an ideal model organism for investigating bacterial cell development and differentiation. The abundance of molecular data accumulated on Caulobacter motivates system biologists to analyze the complex regulatory network of cell cycle via quantitative modeling. In this paper, We propose a comprehensive model to accurately characterize the underlying mechanisms of cell cycle regulation based on the study of: a) chromosome replication and methylation; b) interactive pathways of five master regulatory proteins including DnaA, GcrA, CcrM, CtrA, and SciP, as well as novel consideration of their corresponding mRNAs; c) cell cycle-dependent proteolysis of CtrA through hierarchical protease complexes. The temporal dynamics of our simulation results are able to closely replicate an extensive set of experimental observations and capture the main phenotype of seven mutant strains of Caulobacter crescentus. Collectively, the proposed model can be used to predict phenotypes of other mutant cases, especially for nonviable strains which are hard to cultivate and observe. Moreover, the module of cyclic proteolysis is an efficient tool to study the metabolism of proteins with similar mechanisms.

Indexed as

Caulobacter crescentusBacterial ProteinsCell CycleDNA-Binding ProteinsGene Expression Regulation, BacterialProteolysisBacterial ProteinsDNA-Binding Proteins

Identifiers

PMID35089921
PMCPMC8865702
OpenAlexW4210730147

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.