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Targeting cells with single vectors using multiple-feature Boolean logic

Abstract

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.

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Figure 1: Diversifying recombinase targeting strategies.
Figure 2: Intron engineering for INTRSECT.
Figure 3: INTRSECT: recombinases with engineered introns enable intersectional targeting in vitro.
Figure 4: INTRSECT specificity and functionality in vivo.
Figure 5: Exclusion logic using INTRSECT.
Figure 6: Combinatorial targeting with multiplexed recombinases.

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Acknowledgements

We thank M. Kay (Stanford) for providing the pRC-DJ plasmid used to produce AAV-DJ; M. Bigos at the Stanford Shared FACS Facility for assistance with experiment planning and data analysis; S. Roy for extensive discussions regarding intron function and structure; P. Wu for technical assistance in mouse engineering and characterization; and the entire Deisseroth lab for helpful discussions. The Neuroscience Gene Vector and Virus Core at Stanford is funded in part by US National Institutes of Health grant # NINDS P30 NS069375-01A1. This work is supported by the Stanford Medical Scientist Training Program (MSTP; L.E.F. and J.M.), a Stanford Bio-X Fellowship (J.M. and M. Hyun), the Samsung Scholarship (M. Hyun), the Robertson Neuroscience Fund of Cold Spring Harbor Laboratory (M. He, J.T. and Z.J.H.), the Stony Brook University MSTP (J.T.), a Howard Hughes Medical Institute International Student Fellowship (A.S.), National Science Foundation (NSF) grant 0801700 (L.G.), the NSF Graduate Research Fellowship Program (K.A.Z.), the New York University MSTP (H.B.), the Human Frontiers Science Project and German Academic Exchange Service (DAAD; I.D.), and US National Institute on Drug Abuse (NIDA) DA024763 (C.E.B.). K.D. is supported by the Wiegers Family Fund, US National Institute of Mental Health, NIDA, Defense Advanced Research Projects Agency REPAIR Program, Keck Foundation, McKnight Foundation, Gatsby Charitable Foundation, Snyder Foundation, Woo Foundation, Tarlton Foundation, and Albert Yu and Mary Bechman Foundation. All tools and methods are distributed and supported freely at http://www.optogenetics.org/ and Addgene.

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Contributions

L.E.F., J.M., C.R. and K.D. designed the study and interpreted results. L.E.F., J.M. and K.D. wrote the paper. L.E.F. and J.M. coordinated the experiments. L.E.F., J.M., S.Y.L., A.B. and A.S. performed in vitro electrophysiology experiments. J.M. and K.A.Z. performed in vivo electrophysiology experiments. L.E.F., J.M., M. Hyun, A.S., K.A.Z., H.B. and I.D. performed viral injections. L.E.F., J.M., M. Hyun, S.Y.L., J.T., K.A.Z., H.B., H.S., I.D. and C.P. performed immunohistochemistry. L.E.F., C.R., R.N., C.E.B. and F.M.B. provided viruses. L.G., J.M. and L.E.F. performed statistical analysis. L.E.F., J.M., C.R., M. Hyun, A.B. and C.P. performed molecular engineering and characterization. M. He, J.T. and Z.J.H. provided animals. All authors contributed to editing. K.D. supervised all aspects of the project.

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Correspondence to Karl Deisseroth.

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Fenno, L., Mattis, J., Ramakrishnan, C. et al. Targeting cells with single vectors using multiple-feature Boolean logic. Nat Methods 11, 763–772 (2014). https://doi.org/10.1038/nmeth.2996

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