Deutsch
 
Benutzerhandbuch Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Targeting cells with single vectors using multiple-feature Boolean logic

MPG-Autoren

Diester,  I.
Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Max Planck Society;

Externe Ressourcen
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Fenno, L. E., Mattis, J., Ramakrishnan, C., Hyun, M., Lee, S. Y., He, M., et al. (2014). Targeting cells with single vectors using multiple-feature Boolean logic. Nat Methods, 11(7), 763-72. doi:10.1038/nmeth.2996.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0024-E29C-3
Zusammenfassung
Precisely defining the roles of specific cell types is an intriguing frontier in the study of intact biological systems and has stimulated the rapid development of genetically encoded tools for observation and control. However, targeting these tools with adequate specificity remains challenging: most cell types are best defined by the intersection of two or more features such as active promoter elements, location and connectivity. Here we have combined engineered introns with specific recombinases to achieve expression of genetically encoded tools that is conditional upon multiple cell-type features, using Boolean logical operations all governed by a single versatile vector. We used this approach to target intersectionally specified populations of inhibitory interneurons in mammalian hippocampus and neurons of the ventral tegmental area defined by both genetic and wiring properties. This flexible and modular approach may expand the application of genetically encoded interventional and observational tools for intact-systems biology.