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Inducible, Dose-Adjustable and Time-Restricted Reconstitution of Stat1 Deficiency In Vivo

Overview of attention for article published in PLOS ONE, January 2014
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Title
Inducible, Dose-Adjustable and Time-Restricted Reconstitution of Stat1 Deficiency In Vivo
Published in
PLOS ONE, January 2014
DOI 10.1371/journal.pone.0086608
Pubmed ID
Authors

Nicole R. Leitner, Caroline Lassnig, Rita Rom, Susanne Heider, Zsuzsanna Bago-Horvath, Robert Eferl, Simone Müller, Thomas Kolbe, Lukas Kenner, Thomas Rülicke, Birgit Strobl, Mathias Müller

Abstract

Signal transducer and activator of transcription (STAT) 1 is a key player in interferon (IFN) signaling, essential in mediating host defense against viruses and other pathogens. STAT1 levels are tightly regulated and loss- or gain-of-function mutations in mice and men lead to severe diseases. We have generated a doxycycline (dox) -inducible, FLAG-tagged Stat1 expression system in mice lacking endogenous STAT1 (i.e. Stat1(ind) mice). We show that STAT1 expression depends on the time and dose of dox treatment in primary cells and a variety of organs isolated from Stat1(ind) mice. In bone marrow-derived macrophages, a fraction of the amount of STAT1 present in WT cells is sufficient for full expression of IFN-induced genes. Dox-induced STAT1 established protection against virus infections in primary cells and mice. The availability of the Stat1(ind) mouse model will enable an examination of the consequences of variable amounts of STAT1. The model will also permit the study of STAT1 dose-dependent and reversible functions as well as of STAT1's contributions to the development, progression and resolution of disease.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 1 3%
Unknown 30 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 29%
Student > Master 6 19%
Student > Doctoral Student 3 10%
Professor 2 6%
Other 2 6%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 35%
Medicine and Dentistry 6 19%
Biochemistry, Genetics and Molecular Biology 4 13%
Immunology and Microbiology 1 3%
Chemistry 1 3%
Other 0 0%
Unknown 8 26%