The vitamin-C-synthesizing enzyme senescent marker protein 30 (SMP30) is a cold resistance gene in Drosophila, and vitamin C concentration increases in brown adipose tissue post-cold exposure. However, the roles of SMP30 in thermogenesis are unknown. Here, we tested the molecular mechanism of thermogenesis using wild-type (WT) and vitamin C-deficient SMP30-knockout (KO) mice. SMP30-KO mice gained more weight than WT mice without a change in food intake in response to short-term high-fat diet feeding. Indirect calorimetry and cold-challenge experiments indicated that energy expenditure is lower in SMP30-KO mice, which is associated with decreased thermogenesis in adipose tissues. Therefore, SMP30-KO mice do not lose weight during cold exposure, whereas WT mice lose weight markedly. Mechanistically, the levels of serum FGF21 were notably lower in SMP30-KO mice, and vitamin C supplementation in SMP30-KO mice recovered FGF21 expression and thermogenesis, with a marked reduction in body weight during cold exposure. Further experiments revealed that vitamin C activates PPARα to upregulate FGF21. Our findings demonstrate that SMP30-mediated synthesis of vitamin C activates the PPARα/FGF21 axis, contributing to the maintenance of thermogenesis in mice.

SNT is an end-to-end framework for neuronal morphometry and whole-brain connectomics that supports tracing, proof-editing, visualization, quantification and modeling of neuroanatomy. With an open architecture, a large user base, community-based documentation, support for complex imagery and several model organisms, SNT is a flexible resource for the broad neuroscience community. SNT is both a desktop application and multi-language scripting library, and it is available through the Fiji distribution of ImageJ.

Environmental influences on immune phenotypes are well-documented, but our understanding of which elements of the environment affect immune systems, and how, remains vague. Behaviors, including socializing with others, are central to an individual’s interaction with its environment. We tracked behavior of rewilded laboratory mice of three inbred strains in outdoor enclosures and examined contributions of behavior, including social associations, to immune phenotypes. We found that the more associated two individuals were, the more similar their immune phenotypes were. Social association was particularly predictive of similar memory T and B cell profiles and was more influential than sibling relationships or worm infection status. These results highlight the importance of social networks for immune phenotype and reveal important immunological correlates of social life.

Social interactions pivot on an animal's experiences, internal states, and feedback from others. This complexity drives the need for precise descriptions of behavior to dissect the fine detail of its genetic and neural circuit bases. In laboratory assays, male reliably exhibit aggression, and its extent is generally measured by scoring lunges, a feature of aggression in which one male quickly thrusts onto his opponent. Here, we introduce an explicit approach to identify both the onset and reversals in hierarchical status between opponents and observe that distinct aggressive acts reproducibly precede, concur, or follow the establishment of dominance. We find that lunges are insufficient for establishing dominance. Rather, lunges appear to reflect the dominant state of a male and help in maintaining his social status. Lastly, we characterize the recurring and escalating structure of aggression that emerges through subsequent reversals in dominance. Collectively, this work provides a framework for studying the complexity of agonistic interactions in male flies enabling its neurogenetic basis to be understood with precision.

Epigenetic mechanisms play fundamental roles in brain function and behavior and stressors such as social isolation can alter animal behavior via epigenetic mechanisms. However, due to cellular heterogeneity, identifying cell-type-specific epigenetic changes in the brain is challenging. Here we report first use of a modified INTACT method in behavioral epigenetics of Drosophila: a method we call mini-INTACT. Using ChIP-seq on mini-INTACT purified dopaminergic nuclei, we identified epigenetic signatures in socially-isolated and socially-enriched Drosophila males. Social experience altered the epigenetic landscape in clusters of genes involved in transcription and neural function. Some of these alterations were predicted by expression changes of four transcription factors and the prevalence of their binding sites in several clusters. These transcription factors were previously identified as activity-regulated genes and their knockdown in dopaminergic neurons reduced the effects of social experience on sleep. Our work enables the use of Drosophila as a model for cell-type-specific behavioral epigenetics.

Animals are often bombarded with visual information and must prioritize specific visual features based on their current needs. The neuronal circuits that detect and relay visual features have been well studied. Much less is known about how an animal adjusts its visual attention as its goals or environmental conditions change. During social behaviours, flies need to focus on nearby flies. Here we study how the flow of visual information is altered when female Drosophila enter an aggressive state. From the connectome, we identify three state-dependent circuit motifs poised to modify the response of an aggressive female to fly-sized visual objects: convergence of excitatory inputs from neurons conveying select visual features and internal state; dendritic disinhibition of select visual feature detectors; and a switch that toggles between two visual feature detectors. Using cell-type-specific genetic tools, together with behavioural and neurophysiological analyses, we show that each of these circuit motifs is used during female aggression. We reveal that features of this same switch operate in male Drosophila during courtship pursuit, suggesting that disparate social behaviours may share circuit mechanisms. Our study provides a compelling example of using the connectome to infer circuit mechanisms that underlie dynamic processing of sensory signals.

Lattice light-sheet microscopy (LLSM) is valuable for its combination of reduced photobleaching and outstanding spatiotemporal resolution in 3D. Using LLSM to image biosensors in living cells could provide unprecedented visualization of rapid, localized changes in protein conformation or posttranslational modification. However, computational manipulations required for biosensor imaging with LLSM are challenging for many software packages. The calculations require processing large amounts of data even for simple changes such as reorientation of cell renderings or testing the effects of user-selectable settings, and lattice imaging poses unique challenges in thresholding and ratio imaging. We describe here a new software package, named ImageTank, that is specifically designed for practical imaging of biosensors using LLSM. To demonstrate its capabilities, we use a new biosensor to study the rapid 3D dynamics of the small GTPase Rap1 in vesicles and cell protrusions.

Locusts demonstrate remarkable phenotypic plasticity driven by changes in population density. This density dependent phase polyphenism is associated with many physiological, behavioral, and morphological changes, including observations that cryptic solitarious (solitary-reared) individuals start to fly at dusk, whereas gregarious (crowd-reared) individuals are day-active. We have recorded for 24-36 h, from an identified visual output neuron, the descending contralateral movement detector (DCMD) of Schistocerca gregaria in solitarious and gregarious animals. DCMD signals impending collision and participates in flight avoidance maneuvers. The strength of DCMD’s response to looming stimuli, characterized by the number of evoked spikes and peak firing rate, varies approximately sinusoidally with a period close to 24 h under constant light in solitarious locusts. In gregarious individuals the 24-h pattern is more complex, being modified by secondary ultradian rhythms. DCMD’s strongest responses occur around expected dusk in solitarious locusts but up to 6 h earlier in gregarious locusts, matching the times of day at which locusts of each type are most active. We thus demonstrate a neuronal correlate of a temporal shift in behavior that is observed in gregarious locusts. Our ability to alter the nature of a circadian rhythm by manipulating the rearing density of locusts under identical light-dark cycles may provide important tools to investigate further the mechanisms underlying diurnal rhythmicity.

Structure determination of conformationally variable proteins can prove challenging even when many possible molecular-replacement (MR) search models of high sequence similarity are available. Calmodulin (CaM) is perhaps the best-studied archetype of these flexible proteins: while there are currently ∼450 structures of significant sequence similarity available in the Protein Data Bank (PDB), novel conformations of CaM and complexes thereof continue to be reported. Here, the details of the solution of a novel peptide-CaM complex structure by MR are presented, in which only one MR solution of marginal quality was found despite the use of 120 different search models, an exclusivity enhanced by the presence of a high degree of hemihedral twinning (overall refined twin fraction = 0.43). Ambiguities in the initial MR electron-density maps were overcome by using MR-SAD: phases from the MR partial model were used to identify weak anomalous scatterers (calcium, sulfur and chloride), which were in turn used to improve the phases, automatically rebuild the structure and resolve sequence ambiguities. Retrospective analysis of consecutive wedges of the original data sets showed twin fractions ranging from 0.32 to 0.55, suggesting that the data sets were variably twinned. Despite these idiosyncrasies and obstacles, the data themselves and the final model were of high quality and indeed showed a novel, nearly right-angled conformation of the bound peptide.

Spike sorting is the computational process of extracting the firing times of single neurons from recordings of local electrical fields. This is an important but hard problem in neuroscience, complicated by the non-stationarity of the recordings and the dense overlap in electrical fields between nearby neurons. To solve the spike sorting problem, we have continuously developed over the past eight years a framework known as Kilosort. This paper describes the various algorithmic steps introduced in different versions of Kilosort. We also report the development of Kilosort4, a new version with substantially improved performance due to new clustering algorithms inspired by graph-based approaches. To test the performance of Kilosort, we developed a realistic simulation framework which uses densely sampled electrical fields from real experiments to generate non-stationary spike waveforms and realistic noise. We find that nearly all versions of Kilosort outperform other algorithms on a variety of simulated conditions, and Kilosort4 performs best in all cases, correctly identifying even neurons with low amplitudes and small spatial extents in high drift conditions.