The sense of taste provides animals with valuable information about the nature and quality of food. Mammals can recognize and respond to a diverse repertoire of chemical entities, including sugars, salts, acids and a wide range of toxic substances. Several amino acids taste sweet or delicious (umami) to humans, and are attractive to rodents and other animals. This is noteworthy because L-amino acids function as the building blocks of proteins, as biosynthetic precursors of many biologically relevant small molecules, and as metabolic fuel. Thus, having a taste pathway dedicated to their detection probably had significant evolutionary implications. Here we identify and characterize a mammalian amino-acid taste receptor. This receptor, T1R1+3, is a heteromer of the taste-specific T1R1 and T1R3 G-protein-coupled receptors. We demonstrate that T1R1 and T1R3 combine to function as a broadly tuned L-amino-acid sensor responding to most of the 20 standard amino acids, but not to their D-enantiomers or other compounds. We also show that sequence differences in T1R receptors within and between species (human and mouse) can significantly influence the selectivity and specificity of taste responses.

The sterol regulatory element binding protein (SREBP) family of transcription activators are critical regulators of cholesterol and fatty acid homeostasis. We previously demonstrated that human SREBPs bind the CREB-binding protein (CBP)/p300 acetyltransferase KIX domain and recruit activator-recruited co-factor (ARC)/Mediator co-activator complexes through unknown mechanisms. Here we show that SREBPs use the evolutionarily conserved ARC105 (also called MED15) subunit to activate target genes. Structural analysis of the SREBP-binding domain in ARC105 by NMR revealed a three-helix bundle with marked similarity to the CBP/p300 KIX domain. In contrast to SREBPs, the CREB and c-Myb activators do not bind the ARC105 KIX domain, although they interact with the CBP KIX domain, revealing a surprising specificity among structurally related activator-binding domains. The Caenorhabditis elegans SREBP homologue SBP-1 promotes fatty acid homeostasis by regulating the expression of lipogenic enzymes. We found that, like SBP-1, the C. elegans ARC105 homologue MDT-15 is required for fatty acid homeostasis, and show that both SBP-1 and MDT-15 control transcription of genes governing desaturation of stearic acid to oleic acid. Notably, dietary addition of oleic acid significantly rescued various defects of nematodes targeted with RNA interference against sbp-1 and mdt-15, including impaired intestinal fat storage, infertility, decreased size and slow locomotion, suggesting that regulation of oleic acid levels represents a physiologically critical function of SBP-1 and MDT-15. Taken together, our findings demonstrate that ARC105 is a key effector of SREBP-dependent gene regulation and control of lipid homeostasis in metazoans.

Long-lasting internal states, like hunger, aggression, and sexual arousal, pattern ongoing behavior by defining how the sensory world is translated to specific actions that subserve the needs of an animal. Yet how enduring internal states shape sensory processing or behavior has remained unclear. In Drosophila, male flies will perform a lengthy and elaborate courtship ritual, triggered by activation of sexually-dimorphic P1 neurons, in which they faithfully follow and sing to a female. Here, by recording from males as they actively court a fictive ‘female’ in a virtual environment, we gain insight into how the salience of female visual cues is transformed by a male’s internal arousal state to give rise to persistent courtship pursuit. We reveal that the gain of LCt0a visual projection neurons is strongly increased during courtship, enhancing their sensitivity to moving targets. A simple network model based on the LCt0a circuit accurately predicts a male’s tracking of a female over hundreds of seconds, underscoring that LCt0a visual signals, once released by P1-mediated arousal, become coupled to motor pathways to deterministically control his visual pursuit. Furthermore, we find that P1 neuron activity correlates with fluctuations in the intensity of a male’s pursuit, and that their acute activation is sufficient to boost the gain of the LCt0 pathways. Together, these results reveal how alterations in a male’s internal arousal state can dynamically modulate the propagation of visual signals through a high-fidelity visuomotor circuit to guide his moment-to-moment performance of courtship.Competing Interest StatementThe authors have declared no competing interest.

In this paper we propose a framework for fully automatic, robust and accurate segmentation of the human pelvis and proximal femur in CT data. We propose a composite statistical shape model of femur and pelvis with a flexible hip joint, for which we extend the common definition of statistical shape models as well as the common strategy for their adaptation. We do not analyze the joint flexibility statistically, but model it explicitly by rotational parameters describing the bent in a ball-and-socket joint. A leave-one-out evaluation on 50 CT volumes shows that image driven adaptation of our composite shape model robustly produces accurate segmentations of both proximal femur and pelvis. As a second contribution, we evaluate a fine grain multi-object segmentation method based on graph optimization. It relies on accurate initializations of femur and pelvis, which our composite shape model can generate. Simultaneous optimization of both femur and pelvis yields more accurate results than separate optimizations of each structure. Shape model adaptation and graph based optimization are embedded in a fully automatic framework.

Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain types of birdsong and, as in our experiments, flies grooming. High sequence variability necessitates rigorous quantification of large amounts of data to identify organizational principles and temporal structure of such behavior. To cope with large amounts of data, and minimize human effort and subjective bias, researchers often use automatic behavior recognition software. Our standard grooming assay involves coating flies in dust and videotaping them as they groom to remove it. The flies move freely and so perform the same movements in various orientations. As the dust is removed, their appearance changes. These conditions make it difficult to rely on precise body alignment and anatomical landmarks such as eyes or legs and thus present challenges to existing behavior classification software. Human observers use speed, location, and shape of the movements as the diagnostic features of particular grooming actions. We applied this intuition to design a new automatic behavior recognition system (ABRS) based on spatiotemporal features in the video data, heavily weighted for temporal dynamics and invariant to the animal’s position and orientation in the scene. We use these spatiotemporal features in two steps of supervised classification that reflect two time-scales at which the behavior is structured. As a proof of principle, we show results from quantification and analysis of a large data set of stimulus-induced fly grooming behaviors that would have been difficult to assess in a smaller dataset of human-annotated ethograms. While we developed and validated this approach to analyze fly grooming behavior, we propose that the strategy of combining alignment-invariant features and multi-timescale analysis may be generally useful for movement-based classification of behavior from video data.

Advances in neuro-technology for mapping, manipulating, and monitoring molecularly defined cell types are rapidly advancing insight into neural circuits that regulate appetite. Here, we review these important tools and their applications in circuits that control food seeking and consumption. Technical capabilities provided by these tools establish a rigorous experimental framework for research into the neurobiology of hunger.

The training of deep neural networks is a high-dimension optimization problem with respect to the loss function of a model. Unfortunately, these functions are of high dimension and non-convex and hence difficult to characterize. In this paper, we empirically investigate the geometry of the loss functions for state-of-the-art networks with multiple stochastic optimization methods. We do this through several experiments that are visualized on polygons to understand how and when these stochastic optimization methods find minima.

Intracellular levels of the amino acid aspartate are responsive to changes in metabolism in mammalian cells and can correspondingly alter cell function, highlighting the need for robust tools to measure aspartate abundance. However, comprehensive understanding of aspartate metabolism has been limited by the throughput, cost, and static nature of the mass spectrometry (MS)-based measurements that are typically employed to measure aspartate levels. To address these issues, we have developed a green fluorescent protein (GFP)-based sensor of aspartate (jAspSnFR3), where the fluorescence intensity corresponds to aspartate concentration. As a purified protein, the sensor has a 20-fold increase in fluorescence upon aspartate saturation, with dose-dependent fluorescence changes covering a physiologically relevant aspartate concentration range and no significant off target binding. Expressed in mammalian cell lines, sensor intensity correlated with aspartate levels measured by MS and could resolve temporal changes in intracellular aspartate from genetic, pharmacological, and nutritional manipulations. These data demonstrate the utility of jAspSnFR3 and highlight the opportunities it provides for temporally resolved and high-throughput applications of variables that affect aspartate levels.

The golden age of DNA: We describe a strategy for engineering bifunctional proteins that simultaneously associate with metals and DNA to create self-assembled nanostructures. A DNA binding protein engineered with a gold binding peptide arranges colloidal gold particles along a DNA guide by virtue of its introduced peptide motif. These self-assembled complexes represent a step toward constructing nanoarchitectures with potential in nanoelectronic and photonic devices.

Ends-out gene targeting allows seamless replacement of endogenous genes with engineered DNA fragments by homologous recombination, thus creating designer "genes" in the endogenous locus. Conventional gene targeting in Drosophila involves targeting with the preintegrated donor DNA in the larval primordial germ cells. Here we report G: ene targeting during O: ogenesis with L: ethality I: nhibitor and C: RISPR/Cas (Golic+), which improves on all major steps in such transgene-based gene targeting systems. First, donor DNA is integrated into precharacterized attP sites for efficient flip-out. Second, FLP, I-SceI, and Cas9 are specifically expressed in cystoblasts, which arise continuously from female germline stem cells, thereby providing a continual source of independent targeting events in each offspring. Third, a repressor-based lethality selection is implemented to facilitate screening for correct targeting events. Altogether, Golic+ realizes high-efficiency ends-out gene targeting in ovarian cystoblasts, which can be readily scaled up to achieve high-throughput genome editing.