Summary: A new study reports researchers have developed a new approach for genetically identifying and manipulating neurons in the mouse brain.
Source: Brandeis University.
The complexity of the human brain depends upon the many thousands of individual types of nerve cells it contains. Even the much simpler mouse brain probably contains 10,000 or more different neuronal cell types. Brandeis scientists Yasu Shima, Sacha Nelson and colleagues report in the journal eLife on a new approach for genetically identifying and manipulating these cell types.
Cells in the brain have different functions and therefore express different genes. Important instructions for which genes to express, in which cell types, lie not only in the genes themselves, but in small pieces of DNA called enhancers found in the large spaces between genes. The Brandeis group has found a way to highjack these instructions to express other artificial genes in particular cell types in the mouse brain. Some of these artificially expressed genes (also called transgenes) simply make the cells fluorescent so they can be seen under the microscope.
Other transgenes are master regulators that can be used to turn on or off any other gene of interest. This will allow scientists to activate or deactivate the cells to see how they alter behavior, or to study the function of specific genes by altering them only in some cell types without altering them everywhere in the body. In addition to developing the approach, the Brandeis group created a resource of over 150 strains of mice in which different brain cell types can be studied.
Funding: Funding provided by Human Frontier Science Program Long Term Fellowship, David and Lucile Packard Foundation, National Institutes of Health.
Source: Lawrence Goodman – Brandeis University
Image Source: This NeuroscienceNews.com image is credited to the researchers/Mayo Clinic.
Original Research: Full open access research for “A Mammalian enhancer trap resource for discovering and manipulating neuronal cell types” by Yasuyuki Shima, Ken Sugino, Chris Martin Hempel, Masami Shima, Praveen Taneja, James B Bullis, Sonam Mehta, Carlos Lois, and Sacha B Nelson in eLife. Published online March 21 2016 doi:10.7554/eLife.13503
[cbtabs][cbtab title=”MLA”]Brandeis University. “Trapping Individual Cell Types in the Mouse Brain.” NeuroscienceNews. NeuroscienceNews, 20 May 2016.
<https://neurosciencenews.com/genetic-identification-neurons-4261/>.[/cbtab][cbtab title=”APA”]Brandeis University. (2016, May 20).Trapping Individual Cell Types in the Mouse Brain. NeuroscienceNews. Retrieved May 20, 2016 from https://neurosciencenews.com/genetic-identification-neurons-4261/[/cbtab][cbtab title=”Chicago”]Brandeis University. “Trapping Individual Cell Types in the Mouse Brain.” NeuroscienceNews.
https://neurosciencenews.com/genetic-identification-neurons-4261/ (accessed May 20, 2016).[/cbtab][/cbtabs]
Abstract
A Mammalian enhancer trap resource for discovering and manipulating neuronal cell types
There is a continuing need for driver strains to enable cell-type-specific manipulation in the nervous system. Each cell type expresses a unique set of genes, and recapitulating expression of marker genes by BAC transgenesis or knock-in has generated useful transgenic mouse lines. However, since genes are often expressed in many cell types, many of these lines have relatively broad expression patterns. We report an alternative transgenic approach capturing distal enhancers for more focused expression. We identified an enhancer trap probe often producing restricted reporter expression and developed efficient enhancer trap screening with the PiggyBac transposon. We established more than 200 lines and found many lines that label small subsets of neurons in brain substructures, including known and novel cell types.
“A Mammalian enhancer trap resource for discovering and manipulating neuronal cell types” by Yasuyuki Shima, Ken Sugino, Chris Martin Hempel, Masami Shima, Praveen Taneja, James B Bullis, Sonam Mehta, Carlos Lois, and Sacha B Nelson in eLife. Published online March 21 2016 doi:10.7554/eLife.13503
