Targeting cells with single vectors using multiple-feature Boolean logic.

Targeting cells with single vectors using multiple-feature Boolean logic.
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DOI:
10.1038/nmeth.2996
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发表时间:
2014-07
期刊:
影响因子:
48
通讯作者:
Deisseroth, Karl
Deisseroth, Karl
中科院分区:
生物学1区
文献类型:
--
作者:
Fenno, Lief E.;Mattis, Joanna;Ramakrishnan, Charu;Hyun, Minsuk;Lee, Soo Yeun;He, Miao;Tucciarone, Jason;Selimbeyoglu, Aslihan;Berndt, Andre;Grosenick, Logan;Zalocusky, Kelly A.;Bernstein, Hannah;Swanson, Haley;Perry, Chelsey;Diester, Ilka;Boyce, Frederick M.;Bass, Caroline E.;Neve, Rachael;Huang, Z. Josh;Deisseroth, Karl

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Precisely defining the roles of specific cell types is an intriguing and challenging frontier in the study of intact biological systems, and has stimulated the rapid development of genetically-encoded observation and control tools. 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 recombinase tools with engineered introns to achieve expression of genetically-encoded payloads conditional upon multiple cell-type features, using Boolean logical operations all governed by a single versatile vector. We use 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.
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