Subcellular pharmacokinetic measurements have informed the study of central nervous system (CNS)-acting drug mechanisms. Recent investigations have been enhanced by the use of genetically encoded fluorescent biosensors for drugs of interest at the plasma membrane and in organelles. We describe screening and validation protocols for identifying hit pairs comprising a drug and biosensor, with each screen including 13-18 candidate biosensors and 44-84 candidate drugs. After a favorable hit pair is identified and validated via these protocols, the biosensor is then optimized, as described in other papers, for sensitivity and selectivity to the drug. We also show sample hit pair data that may lead to future intensity-based drug-sensing fluorescent reporters (iDrugSnFRs). These protocols will assist scientists to use fluorescence responses as criteria in identifying favorable fluorescent biosensor variants for CNS-acting drugs that presently have no corresponding biosensor partner. eLife (2022), DOI: 10.7554/eLife.74648 Graphical abstract.

Fluorescent indicators and actuators provide a means to optically observe and perturb dynamic events in living animals. Although chemistry and protein engineering have contributed many useful tools to observe and perturb cells, an emerging strategy is to use chemigenetics: systems in which a small molecule dye interacts with a genetically encoded protein domain. Here we review chemigenetic strategies that have been successfully employed in living animals as photosensitizers for photoablation experiments, fluorescent cell cycle indicators, and fluorescent indicators for studying dynamic biological signals. Although these strategies at times suffer from challenges, e.g. delivery of the small molecule and assembly of the chemigenetic unit in living animals, the advantages of using small molecules with high brightness, low photobleaching, no chromophore maturation time and expanded color palette, combined with the ability to genetically target them to specific cell types, make chemigenetic fluorescent actuators and indicators an attractive strategy for use in living animals.

For more than 100 years, the fruit fly has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula , that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type-related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the community and serves as a reference to study genetic perturbations and disease models at single-cell resolution.

Differentiable simulations of optical systems can be combined with deep learning-based reconstruction networks to enable high performance computational imaging via end-to-end (E2E) optimization of both the optical encoder and the deep decoder. This has enabled imaging applications such as 3D localization microscopy, depth estimation, and lensless photography via the optimization of local optical encoders. More challenging computational imaging applications, such as 3D snapshot microscopy which compresses 3D volumes into single 2D images, require a highly non-local optical encoder. We show that existing deep network decoders have a locality bias which prevents the optimization of such highly non-local optical encoders. We address this with a decoder based on a shallow neural network architecture using global kernel Fourier convolutional neural networks (FourierNets). We show that FourierNets surpass existing deep network based decoders at reconstructing photographs captured by the highly non-local DiffuserCam optical encoder. Further, we show that FourierNets enable E2E optimization of highly non-local optical encoders for 3D snapshot microscopy. By combining FourierNets with a large-scale multi-GPU differentiable optical simulation, we are able to optimize non-local optical encoders 170× to 7372× larger than prior state of the art, and demonstrate the potential for ROI-type specific optical encoding with a programmable microscope.

Circadian rhythms play an essential role in many biological processes and surprisingly only three prokaryotic proteins are required to constitute a true post-translational circadian oscillator. The evolutionary history of the three Kai proteins indicates that KaiC is the oldest member and central component of the clock, with subsequent additions of KaiB and KaiA to regulate its phosphorylation state for time synchronization. The canonical KaiABC system in cyanobacteria is well understood, but little is known about more ancient systems that possess just KaiBC, except for reports that they might exhibit a basic, hourglass-like timekeeping mechanism. Here, we investigate the primordial circadian clock in Rhodobacter sphaeroides (RS) that contains only KaiBC to elucidate its inner workings despite the missing KaiA. Using a combination X-ray crystallography and cryo-EM we find a novel dodecameric fold for KaiCRS where two hexamers are held together by a coiled-coil bundle of 12 helices. This interaction is formed by the C-terminal extension of KaiCRS and serves as an ancient regulatory moiety later superseded by KaiA. A coiled-coil register shift between daytime- and nighttime-conformations is connected to the phosphorylation sites through a long-range allosteric network that spans over 160 Å. Our kinetic data identify the difference in ATP-to-ADP ratio between day and night as the environmental cue that drives the clock and further unravels mechanistic details that shed light on the evolution of self-sustained oscillators.

Homology of highly divergent genes often cannot be determined from sequence similarity alone. For example, we recently identified in the aphid Hormaphis cornu a family of rapidly evolving bicycle genes, which encode novel proteins implicated as plant gall effectors, and sequence similarity search methods yielded few putative bicycle homologs in other species. Coding sequence-independent features of genes, such as intron-exon boundaries, often evolve more slowly than coding sequences, however, and can provide complementary evidence for homology. We found that a linear logistic regression classifier using only structural features of bicycle genes identified many putative bicycle homologs in other species. Independent evidence from sequence features and intron locations supported homology assignments. To test the potential roles of bicycle genes in other aphids, we sequenced the genome of a second gall-forming aphid, Tetraneura nigriabdominalis, and found that many bicycle genes are strongly expressed in the salivary glands of the gall forming foundress. In addition, bicycle genes are strongly overexpressed in the salivary glands of a non-gall forming aphid, Acyrthosiphon pisum, and in the non-gall forming generations of Hormaphis cornu. These observations suggest that Bicycle proteins may be used by multiple aphid species to manipulate plants in diverse ways. Incorporation of gene structural features into sequence search algorithms may aid identification of deeply divergent homologs, especially of rapidly evolving genes involved in host-parasite interactions.

Summary Energy homeostasis requires precise measurement of the quantity and quality of ingested food. The vagus nerve innervates the gut and can detect diverse interoceptive cues, but the identity of the key sensory neurons and corresponding signals that regulate food intake remains unknown. Here, we use an approach for target-specific, single-cell RNA sequencing to generate a map of the vagal cell types that innervate the gastrointestinal tract. We show that unique molecular markers identify vagal neurons with distinct innervation patterns, sensory endings, and function. Surprisingly, we find that food intake is most sensitive to stimulation of mechanoreceptors in the intestine, whereas nutrient-activated mucosal afferents have no effect. Peripheral manipulations combined with central recordings reveal that intestinal mechanoreceptors, but not other cell types, potently and durably inhibit hunger-promoting AgRP neurons in the hypothalamus. These findings identify a key role for intestinal mechanoreceptors in the regulation of feeding.

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i. e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i. e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

Animals learn trajectories to rewards in both spatial, navigational contexts and relational, non-navigational contexts. Synchronous reactivation of hippocampal activity is thought to be critical for recall and evaluation of trajectories for learning. Do hippocampal representations differentially contribute to experience-dependent learning of trajectories across spatial and relational contexts? In this study, we trained mice to navigate to a hidden target in a physical arena or manipulate a joystick to a virtual target to collect delayed rewards. In a navigational context, calcium imaging in freely moving mice revealed that synchronous CA1 reactivation was retrospective and important for evaluation of prior navigational trajectories. In a non-navigational context, reactivation was prospective and important for initiation of joystick trajectories, even in the same animals trained in both contexts. Adaptation of trajectories to a new target was well-explained by a common learning algorithm in which hippocampal activity makes dissociable contributions to reinforcement learning computations depending upon spatial context.

While we think of neurons as having a fixed identity, many show spectacular plasticity. Metamorphosis drives massive changes in the fly brain; neurons that persist into adulthood often change in response to the steroid hormone ecdysone. Besides driving remodeling, ecdysone signaling can also alter the differentiation status of neurons. The three sequentially born subtypes of mushroom body (MB) Kenyon cells (γ, followed by α'/β', and finally α/β) serve as a model of temporal fating. γ neurons are also used as a model of remodeling during metamorphosis. As γ neurons are the only functional Kenyon cells in the larval brain, they serve the function of all three adult subtypes. Correspondingly, larval γ neurons have a similar morphology to α'/β' and α/β neurons-their axons project dorsally and medially. During metamorphosis, γ neurons remodel to form a single medial projection. Both temporal fate changes and defects in remodeling therefore alter γ-neuron morphology in similar ways. Mamo, a broad-complex, tramtrack, and bric-à-brac/poxvirus and zinc finger (BTB/POZ) transcription factor critical for temporal specification of α'/β' neurons, was recently described as essential for γ remodeling. In a previous study, we noticed a change in the number of adult Kenyon cells expressing γ-specific markers when mamo was manipulated. These data implied a role for Mamo in γ-neuron fate specification, yet mamo is not expressed in γ neurons until pupariation, well past γ specification. This indicates that mamo has a later role in ensuring that γ neurons express the correct Kenyon cell subtype-specific genes in the adult brain.