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Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation

Overview of attention for article published in Genome Biology (Online Edition), May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)

Mentioned by

blogs
2 blogs
twitter
32 tweeters

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
197 Mendeley
citeulike
3 CiteULike
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Title
Single-cell analysis of CD4+ T-cell differentiation reveals three major cell states and progressive acceleration of proliferation
Published in
Genome Biology (Online Edition), May 2016
DOI 10.1186/s13059-016-0957-5
Pubmed ID
Authors

Valentina Proserpio, Andrea Piccolo, Liora Haim-Vilmovsky, Gozde Kar, Tapio Lönnberg, Valentine Svensson, Jhuma Pramanik, Kedar Nath Natarajan, Weichao Zhai, Xiuwei Zhang, Giacomo Donati, Melis Kayikci, Jurij Kotar, Andrew N. J. McKenzie, Ruddy Montandon, Oliver Billker, Steven Woodhouse, Pietro Cicuta, Mario Nicodemi, Sarah A. Teichmann

Abstract

Differentiation of lymphocytes is frequently accompanied by cell cycle changes, interplay that is of central importance for immunity but is still incompletely understood. Here, we interrogate and quantitatively model how proliferation is linked to differentiation in CD4+ T cells. We perform ex vivo single-cell RNA-sequencing of CD4+ T cells during a mouse model of infection that elicits a type 2 immune response and infer that the differentiated, cytokine-producing cells cycle faster than early activated precursor cells. To dissect this phenomenon quantitatively, we determine expression profiles across consecutive generations of differentiated and undifferentiated cells during Th2 polarization in vitro. We predict three discrete cell states, which we verify by single-cell quantitative PCR. Based on these three states, we extract rates of death, division and differentiation with a branching state Markov model to describe the cell population dynamics. From this multi-scale modelling, we infer a significant acceleration in proliferation from the intermediate activated cell state to the mature cytokine-secreting effector state. We confirm this acceleration both by live imaging of single Th2 cells and in an ex vivo Th1 malaria model by single-cell RNA-sequencing. The link between cytokine secretion and proliferation rate holds both in Th1 and Th2 cells in vivo and in vitro, indicating that this is likely a general phenomenon in adaptive immunity.

Twitter Demographics

The data shown below were collected from the profiles of 32 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 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
United Kingdom 2 1%
Germany 2 1%
Sweden 1 <1%
Unknown 189 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 47 24%
Student > Ph. D. Student 46 23%
Student > Master 23 12%
Student > Bachelor 15 8%
Student > Postgraduate 9 5%
Other 31 16%
Unknown 26 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 26%
Biochemistry, Genetics and Molecular Biology 40 20%
Immunology and Microbiology 23 12%
Medicine and Dentistry 16 8%
Computer Science 9 5%
Other 23 12%
Unknown 35 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 02 June 2016.
All research outputs
#871,950
of 17,499,602 outputs
Outputs from Genome Biology (Online Edition)
#803
of 3,612 outputs
Outputs of similar age
#19,561
of 271,024 outputs
Outputs of similar age from Genome Biology (Online Edition)
#1
of 1 outputs
Altmetric has tracked 17,499,602 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,612 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.6. This one has done well, scoring higher than 77% 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 271,024 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% 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