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Functional properties of a Brazilian derived mouse embryonic stem cell line

Overview of attention for article published in Anais da Academia Brasileira de Ciências, March 2015
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Title
Functional properties of a Brazilian derived mouse embryonic stem cell line
Published in
Anais da Academia Brasileira de Ciências, March 2015
DOI 10.1590/0001-3765201520140474
Pubmed ID
Authors

Leandro Vairo, Emiliano Medei, Danúbia S Dos Santos, Deivid C Rodrigues, Regina C S Goldenberg, Antonio C Campos De Carvalho

Abstract

Pluripotent mouse embryonic stem cells (mESC) are cell lines derived from the inner cell mass of blastocyst-stage early mammalian embryos. Since ion channel modulation has been reported to interfere with both growth and differentiation process in mouse and human ESC it is important to characterize the electrophysiological properties of newly generated mESC and compare them to other lines. In this work, we studied the intercellular communication by way of gap junctions in a Brazilian derived mESC (USP-1, generated by Dr. Lygia Pereira's group) and characterized its electrophysiological properties. We used immunofluorescence and RT-PCR to reveal the presence of connexin 43 (Cx43), pluripotency markers and ion channels. Using a co-culture of neonatal mouse cardiomyocytes with mESC, where the heart cells expressed the enhanced Green Fluorescent Protein, we performed dye injections to assess functional coupling between the two cell types observing dye diffusion. The patch-clamp study showed outward currents identified as two types of potassium currents, transient outward potassium current (Ito) and delayed rectifier outward potassium current (Iks), by use of specific drug blockage. Calcium or sodium currents in undifferentiated mESC were not identified. We conclude that USP-1 mESC has functional Cx43 channels establishing intercellular communication among themselves and with cardiomyocytes and has a similar electrophysiological profile compared to other mESC cell lines.

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Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Researcher 3 25%
Professor 2 17%
Student > Bachelor 2 17%
Student > Master 1 8%
Other 0 0%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 42%
Agricultural and Biological Sciences 2 17%
Environmental Science 1 8%
Computer Science 1 8%
Medicine and Dentistry 1 8%
Other 2 17%