↓ Skip to main content

Autocrine FGF feedback can establish distinct states of Nanog expression in pluripotent stem cells: a computational analysis

Overview of attention for article published in BMC Systems Biology, September 2014
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
11 Dimensions

Readers on

mendeley
34 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
Autocrine FGF feedback can establish distinct states of Nanog expression in pluripotent stem cells: a computational analysis
Published in
BMC Systems Biology, September 2014
DOI 10.1186/s12918-014-0112-4
Pubmed ID
Authors

Dora Lakatos, Emily D Travis, Kelsey E Pierson, Jay L Vivian, Andras Czirok

Abstract

BackgroundThe maintenance of stem cell pluripotency is controlled by a core cluster of transcription factors, NANOG, OCT4 and SOX2 ¿ genes that jointly regulate each other¿s expression. The expression of some of these genes, especially of Nanog, is heterogeneous in a population of undifferentiated stem cells in culture. Transient changes in expression levels, as well as heterogeneity of the population is not restricted to this core regulator, but involve a large number of other genes that include growth factors, transcription factors or signal transduction proteins.ResultsAs the molecular mechanisms behind NANOG expression heterogeneity is not yet understood, we explore by computational modeling the core transcriptional regulatory circuit and its input from autocrine FGF signals that act through the MAP kinase cascade. We argue that instead of negative feedbacks within the core NANOG-OCT4-SOX2 transcriptional regulatory circuit, autocrine signaling loops such as the Esrrb - FGF - ERK feedback considered here are likely to generate distinct sub-states within the ¿ON¿ state of the core Nanog switch. Thus, the experimentally observed fluctuations in Nanog transcription levels are best explained as noise-induced transitions between negative feedback-generated sub-states. We also demonstrate that ERK phosphorilation is altered and being anti-correlated with fluctuating Nanog expression ¿ in accord with model simulations. Our modeling approach assigns an empirically testable function to the transcriptional regulators Klf4 and Esrrb, and predict differential regulation of FGF family members.ConclusionsWe argue that slow fluctuations in Nanog expression likely reflect individual cell-specific changes in parameters of an autocrine feedback loop, such as changes in ligand capture efficiency, receptor numbers or the presence of crosstalks within the MAPK signal transduction pathway. We proposed a model that operates with binding affinities of multiple transcriptional regulators of pluripotency, and the activity of an autocrine signaling pathway. The resulting model produces varied expression levels of several components of pluripotency regulation, largely consistent with empirical observations reported previously and in this present work.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
Unknown 33 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 35%
Student > Ph. D. Student 7 21%
Student > Master 3 9%
Other 2 6%
Professor > Associate Professor 2 6%
Other 5 15%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 44%
Biochemistry, Genetics and Molecular Biology 7 21%
Computer Science 3 9%
Mathematics 2 6%
Physics and Astronomy 1 3%
Other 3 9%
Unknown 3 9%

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 14 October 2014.
All research outputs
#12,032,816
of 21,321,525 outputs
Outputs from BMC Systems Biology
#417
of 1,139 outputs
Outputs of similar age
#96,908
of 225,257 outputs
Outputs of similar age from BMC Systems Biology
#1
of 1 outputs
Altmetric has tracked 21,321,525 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,139 research outputs from this source. They receive a mean Attention Score of 3.5. 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 225,257 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 56% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them