Hunger is a complex motivational state that drives multiple behaviors. The sensation of hunger is caused by an imbalance between energy intake and expenditure. One immediate response to hunger is increased food consumption. Hunger also modulates behaviors related to food seeking such as increased locomotion and enhanced sensory sensitivity in both insects [1-5] and vertebrates [6, 7]. In addition, hunger can promote the expression of food-associated memory [8, 9]. Although progress is being made [10], how hunger is represented in the brain and how it coordinates these behavioral responses is not fully understood in any system. Here, we use Drosophila melanogaster to identify neurons encoding hunger. We found a small group of neurons that, when activated, induced a fed fly to eat as though it were starved, suggesting that these neurons are downstream of the metabolic regulation of hunger. Artificially activating these neurons also promotes appetitive memory performance in sated flies, indicating that these neurons are not simply feeding command neurons but likely play a more general role in encoding hunger. We determined that the neurons relevant for the feeding effect are serotonergic and project broadly within the brain, suggesting a possible mechanism for how various responses to hunger are coordinated. These findings extend our understanding of the neural circuitry that drives feeding and enable future exploration of how state influences neural activity within this circuit.

Electron diffraction of extremely small three-dimensional crystals (MicroED) allows for structure determination from crystals orders of magnitude smaller than those used for X-ray crystallography. MicroED patterns, which are collected in a transmission electron microscope, were initially not amenable to indexing and intensity extraction by standard software, which necessitated the development of a suite of programs for data processing. The MicroED suite was developed to accomplish the tasks of unit-cell determination, indexing, background subtraction, intensity measurement and merging, resulting in data that can be carried forward to molecular replacement and structure determination. This ad hoc solution has been modified for more general use to provide a means for processing MicroED data until the technique can be fully implemented into existing crystallographic software packages. The suite is written in Python and the source code is available under a GNU General Public License.

Motor sequences are formed through the serial execution of different movements, but how nervous systems implement this process remains largely unknown. We determined the organizational principles governing how dirty fruit flies groom their bodies with sequential movements. Using genetically targeted activation of neural subsets, we drove distinct motor programs that clean individual body parts. This enabled competition experiments revealing that the motor programs are organized into a suppression hierarchy; motor programs that occur first suppress those that occur later. Cleaning one body part reduces the sensory drive to its motor program, which relieves suppression of the next movement, allowing the grooming sequence to progress down the hierarchy. A model featuring independently evoked cleaning movements activated in parallel, but selected serially through hierarchical suppression, was successful in reproducing the grooming sequence. This provides the first example of an innate motor sequence implemented by the prevailing model for generating human action sequences.

Over 6,000 fragments from the genome of Drosophila melanogaster were analyzed for their ability to drive expression of GAL4 reporter genes in the third-instar larval imaginal discs. About 1,200 reporter genes drove expression in the eye, antenna, leg, wing, haltere, or genital imaginal discs. The patterns ranged from large regions to individual cells. About 75% of the active fragments drove expression in multiple discs; 20% were expressed in ventral, but not dorsal, discs (legs, genital, and antenna), whereas \~{}23% were expressed in dorsal but not ventral discs (wing, haltere, and eye). Several patterns, for example, within the leg chordotonal organ, appeared a surprisingly large number of times. Unbiased searches for DNA sequence motifs suggest candidate transcription factors that may regulate enhancers with shared activities. Together, these expression patterns provide a valuable resource to the community and offer a broad overview of how transcriptional regulatory information is distributed in the Drosophila genome.

SmY RNAs are a family of approximately 70-90 nt small nuclear RNAs found in nematodes. In C. elegans, SmY RNAs copurify in a small ribonucleoprotein (snRNP) complex related to the SL1 and SL2 snRNPs that are involved in nematode mRNA trans-splicing. Here we describe a comprehensive computational analysis of SmY RNA homologs found in the currently available genome sequences. We identify homologs in all sequenced nematode genomes in class Chromadorea. We are unable to identify homologs in a more distantly related nematode species, Trichinella spiralis (class: Dorylaimia), and in representatives of non-nematode phyla that use trans-splicing. Using comparative RNA sequence analysis, we infer a conserved consensus SmY RNA secondary structure consisting of two stems flanking a consensus Sm protein binding site. A representative seed alignment of the SmY RNA family, annotated with the inferred consensus secondary structure, has been deposited with the Rfam RNA families database.

The gain of signaling in primary sensory circuits is matched to the stimulus intensity by the process of adaptation. Retinal neural circuits adapt to visual scene statistics, including the mean (background adaptation) and the temporal variance (contrast adaptation) of the light stimulus. The intrinsic properties of retinal bipolar cells and synapses contribute to background and contrast adaptation, but it is unclear whether both forms of adaptation depend on the same cellular mechanisms. Studies of bipolar cell synapses identified synaptic mechanisms of gain control, but the relevance of these mechanisms to visual processing is uncertain because of the historical focus on fast, phasic transmission rather than the tonic transmission evoked by ambient light. Here, we studied use-dependent regulation of bipolar cell synaptic transmission evoked by small, ongoing modulations of membrane potential (V(M)) in the physiological range. We made paired whole-cell recordings from rod bipolar (RB) and AII amacrine cells in a mouse retinal slice preparation. Quasi-white noise voltage commands modulated RB V(M) and evoked EPSCs in the AII. We mimicked changes in background luminance or contrast, respectively, by depolarizing the V(M) or increasing its variance. A linear systems analysis of synaptic transmission showed that increasing either the mean or the variance of the presynaptic V(M) reduced gain. Further electrophysiological and computational analyses demonstrated that adaptation to mean potential resulted from both Ca channel inactivation and vesicle depletion, whereas adaptation to variance resulted from vesicle depletion alone. Thus, background and contrast adaptation apparently depend in part on a common synaptic mechanism.

An important aspect of understanding a biological pathway is to delineate the transcriptional regulatory mechanisms of the genes involved. Two important tasks are often encountered when studying transcription regulation, i.e., (1) the identification of common transcriptional regulators of a set of coexpressed genes; (2) the identification of genes that are regulated by one or several transcription factors. In this study, a systematic and statistical approach was taken to accomplish these tasks by establishing an integrated model considering all of the promoters and characterized transcription factors (TFs) in the genome. A promoter analysis pipeline (PAP) was developed to implement this approach. PAP was tested using coregulated gene clusters collected from the literature. In most test cases, PAP identified the transcription regulators of the input genes accurately. When compared with chromatin immunoprecipitation experiment data, PAP’s predictions are consistent with the experimental observations. When PAP was used to analyze one published expression-profiling data set and two novel coregulated gene sets, PAP was able to generate biologically meaningful hypotheses. Therefore, by taking a systematic approach of considering all promoters and characterized TFs in our model, we were able to make more reliable predictions about the regulation of gene expression in mammalian organisms.

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

Insect nervous systems are proven and powerful model systems for neuroscience research with wide relevance in biology and medicine. However, descriptions of insect brains have suffered from a lack of a complete and uniform nomenclature. Recognising this problem the Insect Brain Name Working Group produced the first agreed hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other insect taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Ito et al. (2014) purposely focused on the gnathal regions that account for approximately 50% of the adult CNS. We extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system to provide a nomenclature of the so-called ventral nervous system (VNS), which includes the thoracic and abdominal neuromeres that was not included in the original work and contains the neurons that play critical roles underpinning most fly behaviours.

Despite the importance of the insect nervous system for functional and developmental neuroscience, descriptions of insect brains have suffered from a lack of uniform nomenclature. Ambiguous definitions of brain regions and fiber bundles have contributed to the variation of names used to describe the same structure. The lack of clearly determined neuropil boundaries has made it difficult to document precise locations of neuronal projections for connectomics study. To address such issues, a consortium of neurobiologists studying arthropod brains, the Insect Brain Name Working Group, has established the present hierarchical nomenclature system, using the brain of Drosophila melanogaster as the reference framework, while taking the brains of other taxa into careful consideration for maximum consistency and expandability. The following summarizes the consortium’s nomenclature system and highlights examples of existing ambiguities and remedies for them. This nomenclature is intended to serve as a standard of reference for the study of the brain of Drosophila and other insects.