Unprecedented technological advances in single-cell RNA-sequencing (scRNA-seq) technology have now made it possible to profile genome-wide expression in single cells at low cost and high throughput. There is substantial ongoing effort to use scRNA-seq measurements to identify the "cell types" that form components of a complex tissue, akin to taxonomizing species in ecology. Cell type classification from scRNA-seq data involves the application of computational tools rooted in dimensionality reduction and clustering, and statistical analysis to identify molecular signatures that are unique to each type. As datasets continue to grow in size and complexity, computational challenges abound, requiring analytical methods to be scalable, flexible, and robust. Moreover, careful consideration needs to be paid to experimental biases and statistical challenges that are unique to these measurements to avoid artifacts. This chapter introduces these topics in the context of cell-type identification, and outlines an instructive step-by-step example bioinformatic pipeline for researchers entering this field.

Bacterial small non-coding RNAs (sRNAs) are being recognized as novel widespread regulators of gene expression in response to environmental signals. Here, we present the first search for sRNA-encoding genes in the nitrogen-fixing endosymbiont Sinorhizobium meliloti, performed by a genome-wide computational analysis of its intergenic regions. Comparative sequence data from eight related alpha-proteobacteria were obtained, and the interspecies pairwise alignments were scored with the programs eQRNA and RNAz as complementary predictive tools to identify conserved and stable secondary structures corresponding to putative non-coding RNAs. Northern experiments confirmed that eight of the predicted loci, selected among the original 32 candidates as most probable sRNA genes, expressed small transcripts. This result supports the combined use of eQRNA and RNAz as a robust strategy to identify novel sRNAs in bacteria. Furthermore, seven of the transcripts accumulated differentially in free-living and symbiotic conditions. Experimental mapping of the 5’-ends of the detected transcripts revealed that their encoding genes are organized in autonomous transcription units with recognizable promoter and, in most cases, termination signatures. These findings suggest novel regulatory functions for sRNAs related to the interactions of alpha-proteobacteria with their eukaryotic hosts.

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search is successful is important to all animals. Here we study the neuronal circuitry that allows larval of either sex to negotiate this exploration-exploitation transition. We do so by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM-data-based analyses of synaptic organization. We find that optogenetic activation of the dopaminergic neuron DAN-i1 can both establish memory during training, and acutely terminate learned search behavior in a subsequent recall test. Its activation leaves innate behavior unaffected, however. Specifically, DAN-i1 activation can establish associative memories of opposite valence upon paired and unpaired training with odor, and its activation during the recall test can terminate the search behavior resulting from either of these memories. Our results further suggest that in its behavioral significance DAN-i1 activation resembles but does not equal sugar reward. Dendrogram analyses of all the synaptic connections between DAN-i1 and its two main targets, the Kenyon cells and the mushroom body output neuron MBON-i1, further suggest that the DAN-i1 signals during training and during the recall test could be delivered to the Kenyon cells and to MBON-i1, respectively, within previously unrecognized, locally confined branching structures. This would provide an elegant circuit motif to terminate search upon its successful completion.In the struggle for survival animals have to explore their environment in search of food. Once food is found, however, it is adaptive to prioritize exploiting it over continuing a search that would now be as pointless as searching for the glasses you are wearing. This exploration-exploitation trade-off is important for animals and humans, as well as for technical search devices. We investigate which of the only 10,000 neurons of a fruit fly larva can tip the balance in this trade-off, and identify a single dopamine neuron called DAN-i1 that can do so. Given the similarities in dopamine neuron function across the animal kingdom, this may reflect a general principle of how search is terminated once it is successful.

We use Drosophila larval locomotion as a model to elucidate the working principles of motor circuits. Larval locomotion is generated by rhythmic and sequential contractions of body-wall muscles from the posterior to anterior segments, which in turn are regulated by motor neurons present in the corresponding neuromeres. Motor neurons are known to receive both excitatory and inhibitory inputs, combined action of which likely regulates patterned motor activity during locomotion. Although recent studies identified candidate inhibitory premotor interneurons, the identity of premotor interneurons that provide excitatory drive to motor neurons during locomotion remains unknown. In this study, we searched for and identified two putative excitatory premotor interneurons in this system, termed CLI1 and CLI2 (cholinergic lateral interneuron 1 and 2). These neurons were segmentally arrayed and activated sequentially from the posterior to anterior segments during peristalsis. Consistent with their being excitatory premotor interneurons, the CLIs formed GRASP- and ChAT-positive putative synapses with motoneurons and were active just prior to motoneuronal firing in each segment. Moreover, local activation of CLI1s induced contraction of muscles in the corresponding body segments. Taken together, our results suggest that the CLIs directly activate motoneurons sequentially along the segments during larval locomotion.

Genetic screens in Drosophila melanogaster and other organisms have been pursued to filter the genome for genetic functions important for memory formation. Such screens have employed primarily chemical or transposon-mediated mutagenesis and have identified numerous mutants including classical memory mutants, dunce and rutabaga. Here, we report the results of a large screen using panneuronal RNAi expression to identify additional genes critical for memory formation. We identified >500 genes that compromise memory when inhibited (low hits), either by disrupting the development and normal function of the adult animal or by participating in the neurophysiological mechanisms underlying memory formation. We also identified >40 genes that enhance memory when inhibited (high hits). The dunce gene was identified as one of the low hits and further experiments were performed to map the effects of the dunce RNAi to the α/β and γ mushroom body neurons. Additional behavioral experiments suggest that dunce knockdown in the mushroom body neurons impairs memory without significantly affecting acquisition. We also characterized one high hit, sickie, to show that RNAi knockdown of this gene enhances memory through effects in dopaminergic neurons without apparent effects on acquisition. These studies further our understanding of two genes involved in memory formation, provide a valuable list of genes that impair memory that may be important for understanding the neurophysiology of memory or neurodevelopmental disorders, and offer a new resource of memory suppressor genes that will aid in understanding restraint mechanisms employed by the brain to optimize resources.

Rhythmic motor patterns underlying many types of locomotion are thought to be produced by central pattern generators (CPGs). Our knowledge of how CPG networks generate motor patterns in complex nervous systems remains incomplete, despite decades of work in a variety of model organisms. Substrate borne locomotion in Drosophila larvae is driven by waves of muscular contraction that propagate through multiple body segments. We use the motor circuitry underlying crawling in larval Drosophila as a model to try to understand how segmentally coordinated rhythmic motor patterns are generated. Whereas muscles, motoneurons and sensory neurons have been well investigated in this system, far less is known about the identities and function of interneurons. Our recent study identified a class of glutamatergic premotor interneurons, PMSIs (period-positive median segmental interneurons), that regulate the speed of locomotion. Here, we report on the identification of a distinct class of glutamatergic premotor interneurons called Glutamatergic Ventro-Lateral Interneurons (GVLIs). We used calcium imaging to search for interneurons that show rhythmic activity and identified GVLIs as interneurons showing wave-like activity during peristalsis. Paired GVLIs were present in each abdominal segment A1-A7 and locally extended an axon towards a dorsal neuropile region, where they formed GRASP-positive putative synaptic contacts with motoneurons. The interneurons expressed vesicular glutamate transporter (vGluT) and thus likely secrete glutamate, a neurotransmitter known to inhibit motoneurons. These anatomical results suggest that GVLIs are premotor interneurons that locally inhibit motoneurons in the same segment. Consistent with this, optogenetic activation of GVLIs with the red-shifted channelrhodopsin, CsChrimson ceased ongoing peristalsis in crawling larvae. Simultaneous calcium imaging of the activity of GVLIs and motoneurons showed that GVLIs' wave-like activity lagged behind that of motoneurons by several segments. Thus, GVLIs are activated when the front of a forward motor wave reaches the second or third anterior segment. We propose that GVLIs are part of the feedback inhibition system that terminates motor activity once the front of the motor wave proceeds to anterior segments.

The reciprocal hemizygosity test is a straightforward genetic test that can positively identify genes that have evolved to contribute to a phenotypic difference between strains or between species. The test involves a comparison between hybrids that are genetically identical throughout the genome except at the test locus, which is rendered hemizygous for alternative alleles from the two parental strains. If the two reciprocal hemizygotes display different phenotypes, then the two parental alleles must have evolved. New methods for targeted mutagenesis will allow application of the reciprocal hemizygosity test in many organisms. This review discusses the principles, advantages, and limitations of the test.

How do developing neurons select their synaptic partners? To identify molecules matching synaptic partners, we integrated the synapse-level connectome of neural circuits with the developmental expression patterns and binding specificities of cell adhesion molecules (CAMs) on pre- and postsynaptic neurons. We focused on parallel synaptic pathways in the Drosophila visual system, in which closely related neurons form synapses onto closely related target neurons. We show that the choice of synaptic partners correlates with the matching expression of receptor-ligand pairs of Beat and Side proteins of the immunoglobulin superfamily (IgSF) CAMs. Genetic analysis demonstrates that these proteins determine the choice between alternative synaptic targets. Combining transcriptomes, connectomes, and protein interactome maps provides a framework to uncover the molecular logic of synaptic connectivity.

Recurrent outbreaks of novel zoonotic coronavirus (CoV) diseases in recent years have highlighted the importance of developing therapeutics with broad-spectrum activity against CoVs. Because all CoVs use -1 programmed ribosomal frameshifting (-1 PRF) to control expression of key viral proteins, the frameshift signal in viral mRNA that stimulates -1 PRF provides a promising potential target for such therapeutics. To test the viability of this strategy, we explored whether small-molecule inhibitors of -1 PRF in SARS-CoV-2 also inhibited -1 PRF in a range of bat CoVs-the most likely source of future zoonoses. Six inhibitors identified in new and previous screens against SARS-CoV-2 were evaluated against the frameshift signals from a panel of representative bat CoVs as well as MERS-CoV. Some drugs had strong activity against subsets of these CoV-derived frameshift signals, while having limited to no effect on -1 PRF caused by frameshift signals from other viruses used as negative controls. Notably, the serine protease inhibitor nafamostat suppressed -1 PRF significantly for multiple CoV-derived frameshift signals. These results suggest it is possible to find small-molecule ligands that inhibit -1 PRF specifically in a broad spectrum of CoVs, establishing frameshift signals as a viable target for developing pan-coronaviral therapeutics.

Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, we combined a large-scale neuronal inactivation screen with automated action detection in response to a mechanosensory cue in Drosophila larva. We analyzed behaviors from 2.9x105 larvae and identified 66 candidate lines for mechanosensory responses out of which 25 for competitive interactions between actions. We further characterize in detail the neurons in these lines and analyzed their connectivity using electron microscopy. We found the neurons in the mechanosensory network are located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system.