Key points• Proteins are more satiating than fats or lipids. Proteins are built by the 20 proteogenic amino acids.• Here, we identified L-arginine, L-lysine and L-glutamic acid as the most potent anorectic amino acids in rats.• L-Arginine and L-glutamic acid require intact neurons in the area postrema to inhibit food intake, whereas L-lysine requires intact afferent fibres of the vagus nerve. All three mediate their effect by the blood stream.• All three amino acids induce gastric distension by delaying gastric emptying and inducing secretion. However, the gastric phenotype does not mediate the anorectic response.• These results unravel amino acid-specific mechanisms regulating digestion and eating behaviour and thereby contribute to the understanding of nutrient sensing in vivo.Abstract To maintain nutrient homeostasis the central nervous system integrates signals that promote or inhibit eating. The supply of vital amino acids is tuned by adjusting food intake according to its dietary protein content. We hypothesized that this effect is based on the sensing of individual amino acids as a signal to control food intake. Here, we show that food intake was most potently reduced by oral L-arginine (Arg), L-lysine (Lys) and L-glutamic acid (Glu) compared to all other 17 proteogenic amino acids in rats. These three amino acids induced neuronal activity in the area postrema and the nucleus of the solitary tract. Surgical lesion of the area postrema abolished the anorectic response to Arg and Glu, whereas vagal afferent lesion prevented the response to Lys. These three amino acids also provoked gastric distension by differentially altering gastric secretion and/or emptying. Importantly, these peripheral mechanical vagal stimuli were dissociated from the amino acids' effect on food intake. Thus, Arg, Lys and Glu had a selective impact on food processing and intake suggesting them as direct sensory input to assess dietary protein content and quality in vivo. Overall, this study reveals novel amino acid-specific mechanisms for the control of food intake and of gastrointestinal function.

Jordi J, Guggiana-Nilo D, Soucy E, Song EY, Wee CL, Engert F. A high-throughput assay for quantifying appetite and digestive dynamics. Am J Physiol Regul Integr Comp Physiol 309: R345-R357, 2015. First published June 24, 2015 doi:10.1152/ajpregu.00225.2015.-Food intake and digestion are vital functions, and their dysregulation is fundamental for many human diseases. Current methods do not support their dynamic quantification on large scales in unrestrained vertebrates. Here, we combine an infrared macroscope with fluorescently labeled food to quantify feeding behavior and intestinal nutrient metabolism with high temporal resolution, sensitivity, and throughput in naturally behaving zebrafish larvae. Using this method and rate-based modeling, we demonstrate that zebrafish larvae match nutrient intake to their bodily demand and that larvae adjust their digestion rate, according to the ingested meal size. Such adaptive feedback mechanisms make this model system amenable to identify potential chemical modulators. As proof of concept, we demonstrate that nicotine, L-lysine, ghrelin, and insulin have analogous impact on food intake as in mammals. Consequently, the method presented here will promote large-scale translational research of food intake and digestive function in a naturally behaving vertebrate.appetite; hunger; satiation; satiety; DiR' dye FOOD INTAKE AND DIGESTION are key physiological processes that provide nutrients to drive all bodily functions. Nutrient intake is matched to nutritional needs by the brain-a process termed nutrient homeostasis-using an intertwined organism-wide array of extrinsic and intrinsic cues coding food availability and demand (2, 42). Dysfunction of feeding and digestive behavior is at the root of global health problems, such as obesity, malnutrition, and Type 2 diabetes, among many others, and, therefore, a deeper understanding of feeding and digestive behavior is of high importance (25).Drugs or genetic manipulations that alter food intake or digestion are highly desirable remedies for food-related disorders. To screen for genes or small molecules with clinically desirable impact, the technology of choice needs to support the analyses of hundreds to thousands of individual animals. Until now, large-scale studies of feeding behavior have solely been feasible in small invertebrates such as Drosophila, but were constrained to 20 -50 conditions in vertebrates, thereby making large-scale screens elusive (12,17,35). Technically, even more demanding than measuring food intake is the quantification of nutrient digestion, as there is no direct optical access to the gastrointestinal tract in most species. More specialized technologies, such as bioluminescence, MRI, or computed tomography, have been valuable to generate insights into in vivo dynamics of digestive function (10,18,19,31). However, all of these methods require immobilization of the experimental subject to reduce motion artifacts, thereby making concurrent behavioral observations impossible. Consequently, quantifying the dy...

The computational principles underlying predictive capabilities in animals are poorly understood. Here, we wondered whether predictive models mediating prey capture could be reduced to a simple set of sensorimotor rules performed by a primitive organism. For this task, we chose the larval zebrafish, a tractable vertebrate that pursues and captures swimming microbes. Using a novel naturalistic 3D setup, we show that the zebrafish combines position and velocity perception to construct a future positional estimate of its prey, indicating an ability to project trajectories forward in time. Importantly, the stochasticity in the fish’s sensorimotor transformations provides a considerable advantage over equivalent noise-free strategies. This surprising result coalesces with recent findings that illustrate the benefits of biological stochasticity to adaptive behavior. In sum, our study reveals that zebrafish are equipped with a recursive prey capture algorithm, built up from simple stochastic rules, that embodies an implicit predictive model of the world.