↓ Skip to main content

Use of transcriptomic data for extending a model of the AppA/PpsR system in Rhodobacter sphaeroides

Overview of attention for article published in BMC Systems Biology, December 2017
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
14 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Use of transcriptomic data for extending a model of the AppA/PpsR system in Rhodobacter sphaeroides
Published in
BMC Systems Biology, December 2017
DOI 10.1186/s12918-017-0489-y
Pubmed ID
Authors

Rakesh Pandey, Judith P. Armitage, George H. Wadhams

Abstract

Photosynthetic (PS) gene expression in Rhodobacter sphaeroides is regulated in response to changes in light and redox conditions mainly by PrrB/A, FnrL and AppA/PpsR systems. The PrrB/A and FnrL systems activate the expression of them under anaerobic conditions while the AppA/PpsR system represses them under aerobic conditions. Recently, two mathematical models have been developed for the AppA/PpsR system and demonstrated how the interaction between AppA and PpsR could lead to a phenotype in which PS genes are repressed under semi-aerobic conditions. These models have also predicted that the transition from aerobic to anaerobic growth mode could occur via a bistable regime. However, they lack experimentally quantifiable inputs and outputs. Here, we extend one of them to include such quantities and combine all relevant micro-array data publically available for a PS gene of this bacterium and use that to parameterise the model. In addition, we hypothesise that the AppA/PpsR system alone might account for the observed trend of PS gene expression under semi-aerobic conditions. Our extended model of the AppA/PpsR system includes the biological input of atmospheric oxygen concentration and an output of photosynthetic gene expression. Following our hypothesis that the AppA/PpsR system alone is sufficient to describe the overall trend of PS gene expression we parameterise the model and suggest that the rate of AppA reduction in vivo should be faster than its oxidation. Also, we show that despite both the reduced and oxidised forms of PpsR binding to the PS gene promoters in vitro, binding of the oxidised form as a repressor alone is sufficient to reproduce the observed PS gene expression pattern. Finally, the combination of model parameters which fit the biological data well are broadly consistent with those which were previously determined to be required for the system to show (i) the repression of PS genes under semi-aerobic conditions, and (ii) bistability. We found that despite at least three pathways being involved in the regulation of photosynthetic genes, the AppA/PpsR system alone is capable of accounting for the observed trends in photosynthetic gene expression seen at different oxygen levels.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 29%
Professor 1 7%
Unspecified 1 7%
Student > Doctoral Student 1 7%
Student > Master 1 7%
Other 0 0%
Unknown 6 43%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 21%
Agricultural and Biological Sciences 2 14%
Unspecified 1 7%
Immunology and Microbiology 1 7%
Medicine and Dentistry 1 7%
Other 1 7%
Unknown 5 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 December 2017.
All research outputs
#20,458,307
of 23,015,156 outputs
Outputs from BMC Systems Biology
#1,011
of 1,144 outputs
Outputs of similar age
#377,608
of 441,975 outputs
Outputs of similar age from BMC Systems Biology
#33
of 41 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,144 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 441,975 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
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 is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.