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Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis

Overview of attention for article published in BMC Systems Biology, October 2014
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

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6 X users

Citations

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8 Dimensions

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38 Mendeley
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2 CiteULike
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Title
Computational modelling and analysis of the molecular network regulating sporulation initiation in Bacillus subtilis
Published in
BMC Systems Biology, October 2014
DOI 10.1186/s12918-014-0119-x
Pubmed ID
Authors

Adaoha EC Ihekwaba, Ivan Mura, Gary C Barker

Abstract

BackgroundBacterial spores are important contaminants in food, and the spore forming bacteria are often implicated in food safety and food quality considerations. Spore formation is a complex developmental process involving the expression of more than 500 genes over the course of 6 to 8 hrs. The process culminates in the formation of resting cells capable of resisting environmental extremes and remaining dormant for long periods of time, germinating when conditions promote further vegetative growth. Experimental observations of sporulation and germination are problematic and time consuming so that reliable models are an invaluable asset in terms of prediction and risk assessment. In this report we develop a model which assists in the interpretation of sporulation dynamics.ResultsThis paper defines and analyses a mathematical model for the network regulating Bacillus subtilis sporulation initiation, from sensing of sporulation signals down to the activation of the early genes under control of the master regulator Spo0A. Our model summarises and extends other published modelling studies, by allowing the user to execute sporulation initiation in a scenario where Isopropyl ß-D-1-thiogalactopyranoside (IPTG) is used as an artificial sporulation initiator as well as in modelling the induction of sporulation in wild-type cells. The analysis of the model results and the comparison with experimental data indicate that the model is good at predicting inducible responses to sporulation signals. However, the model is unable to reproduce experimentally observed accumulation of phosphorelay sporulation proteins in wild type B. subtilis. This model also highlights that the phosphorelay sub-component, which relays the signals detected by the sensor kinases to the master regulator Spo0A, is crucial in determining the response dynamics of the system.ConclusionWe show that there is a complex connectivity between the phosphorelay features and the master regulatory Spo0A. Additional we discovered that the experimentally observed regulation of the phosphotransferase Spo0B for wild-type B. subtilis may be playing an important role in the network which suggests that modelling of sporulation initiation may require additional experimental support.

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X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 8 21%
Student > Bachelor 7 18%
Student > Doctoral Student 3 8%
Student > Master 3 8%
Other 4 11%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 34%
Biochemistry, Genetics and Molecular Biology 9 24%
Computer Science 4 11%
Engineering 3 8%
Economics, Econometrics and Finance 1 3%
Other 3 8%
Unknown 5 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 November 2015.
All research outputs
#12,612,638
of 22,768,097 outputs
Outputs from BMC Systems Biology
#411
of 1,142 outputs
Outputs of similar age
#114,783
of 260,971 outputs
Outputs of similar age from BMC Systems Biology
#13
of 41 outputs
Altmetric has tracked 22,768,097 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 63% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 260,971 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.