@article{70b7c0d68ffc4bcd9d4bd9a6e0db433d,
title = "Origin of wiring specificity in an olfactory map revealed by neuron type-specific, time-lapse imaging of dendrite targeting",
abstract = "How does wiring specificity of neural maps emerge during development? Formation of the adult Drosophila olfactory glomerular map begins with patterning of projection neuron (PN) dendrites at the early pupal stage. To better understand the origin of wiring specificity of this map, we created genetic tools to systematically characterize dendrite patterning across development at PN type–specific resolution. We find that PNs use lineage and birth order combinatorially to build the initial dendritic map. Specifically, birth order directs dendrite targeting in rotating and binary manners for PNs of the anterodorsal and lateral lineages, respectively. Two-photon– and adaptive optical lattice light-sheet microscope–based time-lapse imaging reveals that PN dendrites initiate active targeting with direction-dependent branch stabilization on the timescale of seconds. Moreover, PNs that are used in both the larval and adult olfactory circuits prune their larval-specific dendrites and re-extend new dendrites simultaneously to facilitate timely olfactory map organization. Our work highlights the power and necessity of type-specific neuronal access and time-lapse imaging in identifying wiring mechanisms that underlie complex patterns of functional neural maps.",
author = "Wong, {Kenneth Kin Lam} and Tongchao Li and Fu, {Tian Ming} and Gaoxiang Liu and Cheng Lyu and Sayeh Kohani and Qijing Xie and Luginbuhl, {David J.} and Srigokul Upadhyayula and Eric Betzig and Liqun Luo",
note = "Funding Information: F or AO-LLSM based imaging, the excitation and detection objectives along with the 25-mm c overslip were immersed in ~40 mL of culture medium at room temperature. Explant brains held o n Sylgard plate were excited simultaneously using 488 nm (for GFP) and 642 nm (for JF-646) l asers operating with ~2–10 mW input power to the microscope (corresponding to ~10–50 µW at t he back aperture of the excitation objective). An exposure time of 20–50 msec was used to b alance imaging speed and signal-to-noise ratio (SNR). Dithered lattice light-sheet patterns with a n inner/outer numerical aperture of 0.35/0.4 or 0.38/0.4 were used. The optical sections were c ollected by an axial step size of 250 nm in the detection objective coordinate, with a total of 81– 2 01 steps (corresponding to a total axial scan range of 20–50 µm). Emission light from GFP and J F-646 was separated by a dichromatic mirror (Di03-R561, Semrock, IDEX Health & Science, L LC, Rochester, NY) and captured by two Hamamatsu ORCA-Fusion sCMOS cameras s imultaneously (Hamamatsu Photonics, Hamamatsu City, Japan). Prior to the acquisition of the t ime series data, the imaged volume was corrected for optical aberrations using two-photon guide s tar based adaptive optics method (Chen et al., 2014; Wang et al., 2014; Liu et al., 2018). Each i maged volume was deconvolved using Richardson-Lucy algorithm on HHMI Janelia Research C ampus{\textquoteright} or Advanced Bioimaging Center{\textquoteright}s computing cluster ( https://github.com/scopetools/cudadecon, https://github.com/abcucberkeley/LLSM3DTools) w ith experimentally measured point spread functions obtained from 100 or 200 nm fluorescent b eads (Invitrogen FluoSpheresTMCarboxylate-Modified Microspheres, 505/515 nm, F8803, F F8811). The AO-LLSM was operated using a custom LabVIEW software (National I nstruments, Woburn, MA). S tatistics F or data analyses, t-test and one-way ANOVA were used to determine p values as indicated in t he figure legend for each graph, and graphs were generated using Excel. Exact p values were p rovided in Source Data files. M aterial and data availability A ll reagents generated in this study are available from the lead corresponding author upon r equest. Figure 3 - Source Data 1, Figure 5 - Source Data 1, Figure 6 - Source Data 1, and Figure 7 - Source Data 1 contain the numerical and statistical data used to generate the figures. A CKNOWLEDGEMENTS W e thank the Luo lab members for constructive feedback on the manuscript; Tzumin Lee for s haring equipment at Janelia Research Campus; Luke Lavis for sharing JF dyes. This work was s upport by a grant from NIH (R01 DC005982 to L.L.). T.L. was supported by NIH 1 K99DC01883001. G.L. and S.U. are funded by Philomathia Foundation. S.U. is funded by C han Zuckerberg Initiative Imaging Scientist program. S.U. is a Chan Zuckerberg Biohub I nvestigator. E.B. and L.L. are HHMI investigators. R EFERENCES A rshadi, C., G{\"u}nther, U., Eddison, M., Harrington, K. I. S., & Ferreira, T. A. (2021). SNT: a unifying toolbox for quantification of neuronal anatomy. Nature Methods, 18(4), 374–377. https://doi.org/10.1038/S41592-021-01105-7 Funding Information: We thank the Luo lab members for constructive feedback on the manuscript; Tzumin Lee for sharing equipment at Janelia Research Campus; Luke Lavis for sharing JF dyes. This work was support by a grant from NIH (R01 DC005982 to L.L.). T.L. was supported by NIH 1K99DC01883001. G.L. and S.U. are funded by Philomathia Foundation. S.U. is funded by Chan Zuckerberg Initiative Imaging Scientist program. S.U. is a Chan Zuckerberg Biohub Investigator. E.B. and L.L. are HHMI investigators. Publisher Copyright: {\textcopyright} 2023, eLife Sciences Publications Ltd. All rights reserved.",
year = "2023",
month = mar,
doi = "10.7554/elife.85521",
language = "English (US)",
volume = "12",
journal = "eLife",
issn = "2050-084X",
publisher = "eLife Sciences Publications",
}