@article {65618, title = {jYCaMP: an optimized calcium indicator for two-photon imaging at fiber laser wavelengths.}, journal = {Nature Methods}, volume = {17}, year = {2020}, month = {2020 May 25}, pages = {694-97}, abstract = {

Femtosecond lasers at fixed wavelengths above 1,000 nm are powerful, stable and inexpensive, making them promising sources for two-photon microscopy. Biosensors optimized for these wavelengths are needed for both next-generation microscopes and affordable turn-key systems. Here we report jYCaMP1, a yellow variant of the calcium indicator jGCaMP7 that outperforms its parent in mice and flies at excitation wavelengths above 1,000 nm and enables improved two-color calcium imaging with red fluorescent protein-based indicators.

}, issn = {1548-7105}, doi = {10.1038/s41592-020-0835-7}, author = {Mohr, Manuel Alexander and Bushey, Daniel and Abhi Aggarwal and Marvin, Jonathan S and Kim, Jeong Jun and Marquez, Emiliano Jimenez and Liang, Yajie and Patel, Ronak and Macklin, John J and Lee, Chi-Yu and Tsang, Arthur and Tsegaye, Getahun and Ahrens, Allison M and Chen, Jerry L and Kim, Douglas S and Wong, Allan M and Looger, Loren L and Schreiter, Eric R and Podgorski, Kaspar} } @article {49343, title = {Inverse-response Ca2+ indicators for optogenetic visualization of neuronal inhibition.}, journal = {Scientific Reports}, volume = {8}, year = {2018}, month = {2018 Aug 06}, pages = {11758}, abstract = {

We have developed a series of yellow genetically encoded Ca indicators for optical imaging (Y-GECOs) with inverted responses to Ca and apparent dissociation constants (K{\textquoteright}) ranging from 25 to 2400 nM. To demonstrate the utility of this affinity series of Ca indicators, we expressed the four highest affinity variants (K{\textquoteright}s = 25, 63, 121, and 190 nM) in the Drosophila medulla intrinsic neuron Mi1. Hyperpolarization of Mi1 by optogenetic stimulation of the laminar monopolar neuron L1 produced a decrease in intracellular Ca in layers 8-10, and a corresponding increase in Y-GECO fluorescence. These experiments revealed that lower K{\textquoteright} was associated with greater increases in fluorescence, but longer delays to reach the maximum signal change due to slower off-rate kinetics.

}, issn = {2045-2322}, doi = {10.1038/s41598-018-30080-x}, author = {Zhao, Yufeng and Bushey, Daniel and Zhao, Yongxin and Schreiter, Eric R and Harrison, D Jed and Wong, Allan M and Campbell, Robert E} } @article {49587, title = {Mapping Neurotransmitter Identity in the Whole-Mount Brain Using Multiplex High-Throughput Fluorescence Hybridization.}, journal = {Genetics}, volume = {211}, year = {2018}, month = {2018 Dec 18}, pages = {473-82}, abstract = {

Identifying the neurotransmitters used by specific neurons is a critical step in understanding the function of neural circuits. However, methods for the consistent and efficient detection of neurotransmitter markers remain limited. Fluorescence hybridization (FISH) enables direct labeling of type-specific mRNA in neurons. Recent advances in FISH allow this technique to be carried out in intact tissue samples such as whole-mount brains. Here, we present a FISH platform for high-throughput detection of eight common neurotransmitter phenotypes in brains. We greatly increase FISH throughput by processing samples mounted on coverslips and optimizing fluorophore choice for each probe to facilitate multiplexing. As application examples, we demonstrate cases of neurotransmitter co-expression, reveal neurotransmitter phenotypes of specific cell types and explore the onset of neurotransmitter expression in the developing optic lobe. Beyond neurotransmitter markers, our protocols can in principle be used for large scale FISH detection of any mRNA in whole-mount fly brains.

}, issn = {1943-2631}, doi = {10.1534/genetics.118.301749}, author = {Meissner, Geoffrey W and Nern, Aljoscha and Singer, Robert H and Wong, Allan M and Malkesman, Oz and Long, Xi} } @article {48982, title = {Behavioral state modulates the ON visual motion pathway of Drosophila.}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, volume = {115}, year = {2017}, month = {2017 Dec 18}, pages = {E102-11}, abstract = {

The behavioral state of an animal can dynamically modulate visual processing. In flies, the behavioral state is known to alter the temporal tuning of neurons that carry visual motion information into the central brain. However, where this modulation occurs and how it tunes the properties of this neural circuit are not well understood. Here, we show that the behavioral state alters the baseline activity levels and the temporal tuning of the first directionally selective neuron in the ON motion pathway (T4) as well as its primary input neurons (Mi1, Tm3, Mi4, Mi9). These effects are especially prominent in the inhibitory neuron Mi4, and we show that central octopaminergic neurons provide input to Mi4 and increase its excitability. We further show that octopamine neurons are required for sustained behavioral responses to fast-moving, but not slow-moving, visual stimuli in walking flies. These results indicate that behavioral-state modulation acts directly on the inputs to the directionally selective neurons and supports efficient neural coding of motion stimuli.

}, issn = {1091-6490}, doi = {10.1073/pnas.1703090115}, author = {Strother, James A and Wu, Shiuan-Tze and Rogers, Edward M and Eliason, Jessica L M and Wong, Allan M and Nern, Aljoscha and Reiser, Michael B} } @article {48764, title = {A circuit node that integrates convergent input from neuromodulatory and social behavior-promoting neurons to control aggression in Drosophila.}, journal = {Neuron}, volume = {95}, year = {2017}, month = {2017 Aug 30}, pages = {1112-1128.e7}, abstract = {

Diffuse neuromodulatory systems such as norepinephrine (NE) control brain-wide states such as arousal, but whether they control complex social behaviors more specifically is not clear. Octopamine (OA), the insect homolog of NE, is known to promote both arousal and aggression. We have performed a\ systematic, unbiased screen to identify OA receptor-expressing neurons (OARNs) that control aggression in Drosophila. Our results uncover a tiny population of male-specific aSP2 neurons that mediate a specific influence of OA on aggression, independent of any effect on arousal. Unexpectedly, these neurons receive convergent input from OA neurons and P1 neurons, a population of FruM(+) neurons that promotes male courtship behavior. Behavioral epistasis experiments suggest that aSP2 neurons may constitute an integration node at which OAergic neuromodulation can bias the output of P1 neurons to favor aggression over inter-male courtship. These results have potential implications for thinking about\ the role of related neuromodulatory systems in mammals.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2017.08.017}, author = {Watanabe, Kiichi and Chiu, Hui and Pfeiffer, Barret D and Wong, Allan M and Hoopfer, Eric D and Rubin, Gerald M and Anderson, David J} } @article {48658, title = {A connectome of a learning and memory center in the adult Drosophila brain.}, journal = {eLife}, volume = {6}, year = {2017}, month = {2017 Jul 18}, pages = {e26975}, abstract = {

Understanding memory formation, storage and retrieval requires knowledge of the underlying neuronal circuits. In\ Drosophila, the mushroom body (MB) is the major site of associative learning. We reconstructed the morphologies and synaptic connections of all 983 neurons within the three functional units, or compartments, that compose the adult MB{\textquoteright}s α lobe, using a dataset of isotropic 8-nm voxels collected by focused ion-beam milling scanning electron microscopy. We found that Kenyon cells (KCs), whose sparse activity encodes sensory information, each make multiple\ en passant\ synapses to MB output neurons (MBONs) in each compartment. Some MBONs have inputs from all KCs, while others differentially sample sensory modalities. Only six percent of KC\>MBON synapses receive a direct synapse from a dopaminergic neuron (DAN). We identified two unanticipated classes of synapses, KC\>DAN and DAN\>MBON. DAN activation produces a slow depolarization of the MBON in these DAN\>MBON synapses and can weaken memory recall.

}, doi = {10.7554/eLife.26975}, author = {Takemura, Shin-ya and Aso, Yoshinori and Hige, Toshihide and Wong, Allan M and Lu, Zhiyuan and Xu, C Shan and Rivlin, Patricia K and Hess, Harald F and Zhao, Ting and Parag, Toufiq and Berg, Stuart and Huang, Gary and Katz, William T and Olbris, Donald J and Plaza, Stephen M and Umayam, Lowell A and Aniceto, Roxanne and Chang, Lei-Ann and Lauchie, Shirley and et al} } @article {48414, title = {The emergence of directional selectivity in the visual motion pathway of Drosophila.}, journal = {Neuron}, volume = {94}, year = {2017}, month = {2017 Apr 05}, pages = {168-182.e10}, abstract = {

The perception of visual motion is critical for animal navigation, and flies are a prominent model system for exploring this neural computation. In Drosophila, the T4 cells of the medulla are directionally selective and necessary for ON motion behavioral responses. To examine the emergence of directional selectivity, we developed genetic driver lines for the neuron types with the most synapses onto T4 cells. Using calcium imaging, we found that these neuron types are not directionally selective and that selectivity arises in the T4 dendrites. By silencing each input neuron type, we identified which neurons are necessary for T4 directional selectivity and ON motion behavioral responses. We then determined the sign of the connections between these neurons and T4 cells using neuronal photoactivation. Our results indicate a computational architecture for motion detection that is a hybrid of classic theoretical models.

}, issn = {1097-4199}, doi = {10.1016/j.neuron.2017.03.010}, author = {Strother, James A and Wu, Shiuan-Tze and Wong, Allan M and Nern, Aljoscha and Rogers, Edward M and Le, Jasmine Q and Rubin, Gerald M and Reiser, Michael B} } @article {48975, title = {The functional organization of descending sensory-motor pathways in Drosophila.}, journal = {eLife}, year = {2017}, month = {2018 Jun 26}, pages = {e34272}, abstract = {

In most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck. DN activity activates, maintains or modulates locomotion and other behaviors. Individual DNs have been well-studied in species from insects to primates, but little is known about overall connectivity patterns across the DN population. We systematically investigated DN anatomy in\ Drosophila melanogaster\ and created over 100 transgenic lines targeting individual cell types. We identified roughly half of all\ Drosophila\ DNs and comprehensively map connectivity between sensory and motor neuropils in the brain and nerve cord, respectively. We find the nerve cord is a layered system of neuropils reflecting the fly{\textquoteright}s capability for two largely independent means of locomotion -- walking and flight -- using distinct sets of appendages. Our results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of neural circuits.

}, doi = {10.7554/eLife.34272}, author = {Namiki, Shigehiro and Dickinson, Michael H and Wong, Allan M and Korff, Wyatt and Card, Gwyneth M} } @article {48559, title = {Quantitative mRNA imaging throughout the entire Drosophila brain.}, journal = {Nature Methods}, volume = {14}, year = {2017}, month = {2017 Jun 05}, pages = {703-6}, abstract = {

We describe a fluorescence in situ hybridization method that permits detection of the localization and abundance of single mRNAs (smFISH) in cleared whole-mount adult Drosophila brains. The approach is rapid and multiplexable and does not require molecular amplification; it allows facile quantification of mRNA expression with subcellular resolution on a standard confocal microscope. We further demonstrate single-mRNA detection across the entire brain using a custom Bessel beam structured illumination microscope (BB-SIM).

}, issn = {1548-7105}, doi = {10.1038/nmeth.4309}, author = {Long, Xi and Colonell, Jennifer and Wong, Allan M and Singer, Robert H and Lionnet, Timoth{\'e}e} }