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Time course decomposition of cell heterogeneity in TFEB signaling states reveals homeostatic mechanisms restricting the magnitude and duration of TFEB responses to mTOR activity modulation

Overview of attention for article published in BMC Cancer, June 2016
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  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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Title
Time course decomposition of cell heterogeneity in TFEB signaling states reveals homeostatic mechanisms restricting the magnitude and duration of TFEB responses to mTOR activity modulation
Published in
BMC Cancer, June 2016
DOI 10.1186/s12885-016-2388-9
Pubmed ID
Authors

Paula Andrea Marin Zapata, Carsten Jörn Beese, Anja Jünger, Giovanni Dalmasso, Nathan Ryan Brady, Anne Hamacher-Brady

Abstract

TFEB (transcription factor EB) regulates metabolic homeostasis through its activation of lysosomal biogenesis following its nuclear translocation. TFEB activity is inhibited by mTOR phosphorylation, which signals its cytoplasmic retention. To date, the temporal relationship between alterations to mTOR activity states and changes in TFEB subcellular localization and concentration has not been sufficiently addressed. mTOR was activated by renewed addition of fully-supplemented medium, or inhibited by Torin1 or nutrient deprivation. Single-cell TFEB protein levels and subcellular localization in HeLa and MCF7 cells were measured over a time course of 15 hours by multispectral imaging cytometry. To extract single-cell level information on heterogeneous TFEB activity phenotypes, we developed a framework for identification of TFEB activity subpopulations. Through unsupervised clustering, cells were classified according to their TFEB nuclear concentration, which corresponded with downstream lysosomal responses. Bulk population results revealed that mTOR negatively regulates TFEB protein levels, concomitantly to the regulation of TFEB localization. Subpopulation analysis revealed maximal sensitivity of HeLa cells to mTOR activity stimulation, leading to inactivation of 100 % of the cell population within 0.5 hours, which contrasted with a lower sensitivity in MCF7 cells. Conversely, mTOR inhibition increased the fully active subpopulation only fractionally, and full activation of 100 % of the population required co-inhibition of mTOR and the proteasome. Importantly, mTOR inhibition activated TFEB for a limited duration of 1.5 hours, and thereafter the cell population was progressively re-inactivated, with distinct kinetics for Torin1 and nutrient deprivation treatments. TFEB protein levels and subcellular localization are under control of a short-term rheostat, which is highly responsive to negative regulation by mTOR, but under conditions of mTOR inhibition, restricts TFEB activation in a manner dependent on the proteasome. We further identify a long-term, mTOR-independent homeostatic control negatively regulating TFEB upon prolonged mTOR inhibition. These findings are of relevance for developing strategies to target TFEB activity in disease treatment. Moreover, our quantitative approach to decipher phenotype heterogeneity in imaging datasets is of general interest, as shifts between subpopulations provide a quantitative description of single cell behaviour, indicating novel regulatory behaviors and revealing differences between cell types.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
India 1 2%
Unknown 43 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 20%
Researcher 6 13%
Professor > Associate Professor 5 11%
Student > Master 5 11%
Student > Bachelor 3 7%
Other 9 20%
Unknown 8 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 33%
Agricultural and Biological Sciences 8 18%
Nursing and Health Professions 3 7%
Medicine and Dentistry 3 7%
Immunology and Microbiology 2 4%
Other 5 11%
Unknown 9 20%
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 26 September 2017.
All research outputs
#7,878,286
of 23,881,329 outputs
Outputs from BMC Cancer
#2,162
of 8,483 outputs
Outputs of similar age
#124,097
of 344,548 outputs
Outputs of similar age from BMC Cancer
#36
of 172 outputs
Altmetric has tracked 23,881,329 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 8,483 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 68% 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 344,548 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 51% of its contemporaries.
We're also able to compare this research output to 172 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.