A Neural Circuit for Gut-Induced Reward.

The gut is now recognized as a major regulator of motivational and emotional states. However, the relevant gut-brain neuronal circuitry remains unknown. We show that optical activation of gut-innervating vagal sensory neurons recapitulates the hallmark effects of stimulating brain reward neurons. Specifically, right, but not left, vagal sensory ganglion activation sustained self-stimulation behavior, conditioned both flavor and place preferences, and induced dopamine release from Substantia nigra. Cell-specific transneuronal tracing revealed asymmetric ascending pathways of vagal origin throughout the CNS. In particular, transneuronal labeling identified the glutamatergic neurons of the dorsolateral parabrachial region as the obligatory relay linking the right vagal sensory ganglion to dopamine cells in Substantia nigra. Consistently, optical activation of parabrachio-nigral projections replicated the rewarding effects of right vagus excitation. Our findings establish the vagal gut-to-brain axis as an integral component of the neuronal reward pathway. They also suggest novel vagal stimulation approaches to affective disorders.

Mutant hFGF23(A12D) stimulates osteoblast differentiation through FGFR3.

Fibroblast growth factor (FGF) 23 is a member of the FGF family involved in bone development by interacting with FGFRs. In a previous study, we discovered a mutant human FGF (hFGF) 23 (A12D) in the mandibular prognathism (MP) pedigree. However, the exact role of hFGF23(A12D) during bone formation remains unclear. The aim of this study was to identify the function of hFGF23(A12D) in bone formation. We infected isolated rat calvaria (RC) cells with the recombinant lentivirus containing mutant hFGF23(A12D) and WT hFGF23 respectively. Real-time PCR, western blot and enzyme-linked immunosorbent assay confirmed that hFGF23(A12D) failed to be secreted. We measured cell growth via the CCK-8 assay based on Zsgreen expression, detected cell differentiation ability via alkaline phosphatase staining, performed RT-PCR and found that hFGF23(A12D) inhibited proliferation of RC cells and stimulated the differentiation of RC cells to osteoblasts. Through RNA sequencing, RT-PCR and western blot, we found increased expression of FGFR3. Through co-immunoprecipitation assays and immunofluorescence staining, we revealed that hFGF23(A12D) activated the mitogen-activated protein kinase signalling pathway through interactions with the intracellular domain of FGFR3. In summary, we determined the mechanisms of hFGF23(A12D) involved in osteoblast generation and formation which is specifically due to its interaction with FGFR3.

On the roles of the Duodenum and the Vagus nerve in learned nutrient preferences.

BACKGROUND AND AIM: In most species, including humans, food preference is primarily controlled by nutrient value. However, the gut-brain pathways involved in preference learning remain elusive. The aim of the present study, performed in C57BL6/J mice, was to characterize the roles in nutrient preference of two critical elements of gut-brain pathways, i.e. the duodenum and vagal gut innervation. METHODS: Adult wild-type C57BL6/J mice from a normal-weight cohort sustained one of the following three procedures: duodenal-jejunal bypass intestinal rerouting (DJB), total subdiaphragmatic vagotomy (SDV), or sham surgery. Mice were assessed in short-term two-bottle preference tests before and after 24 h s exposures to solutions containing one of glutamate, lipids, sodium, or glucose. RESULTS: DJB and SDV interfered in preference formation in a nutrient-specific manner: whereas normal preference learning for lipids and glutamate was disrupted by both DJB and SDV, these interventions did not alter the formation of preferences for glucose. Interestingly, sodium preferences were abrogated by DJB but not by SDV. CONCLUSIONS: Different macronutrients make use of distinct gut-brain pathways to influence food preferences, thereby mirroring nutrient-specific processes of food digestion. Specifically, whereas both vagal innervation and duodenal sensing appear critical for generating responses to fats and protein, glucose preferences recruit post-duodenal, vagal-independent pathways in pair with the control of glucose homeostasis. Overall, our data suggest that the physiological processes involved in digesting and absorbing fats, amino acids, and glucose overlap with those mediating learned preferences for each of these nutrients.

Numerical and experimental investigation of multi-species bacterial co-aggregation.

This paper deals with the mathematical modeling of bacterial co-aggregation and its numerical implementation in a FEM framework. Since the concept of co-aggregation refers to the physical binding between cells of different microbial species, a system composed of two species is considered in the modeling framework. The extension of the model to an arbitrary number of species is straightforward. In addition to two-species (multi-species growth) dynamics, the transport of a nutritional substance and the extent of co-aggregation are introduced into the model as the third and fourth primary variables. A phase-field modeling approach is employed to describe the co-aggregation between the two species. The mathematical model is three-dimensional and fully based on the continuum description of the problem without any need for discrete agents which are the key elements of the individual-based modeling approach. It is shown that the use of a phase-field-based model is equivalent to a particular form of classical diffusion-reaction systems. Unlike the so-called mixture models, the evolution of each component of the multi-species system is captured thanks to the inherent capability of phase-field modeling in treating systems consisting of distinct multi-phases. The details of numerical implementation in a FEM framework are also presented. Indeed, a new multi-field user element is developed and implemented in ANSYS for this multiphysics problem. Predictions of the model are compared with the experimental observations. By that, the versatility and applicability of the model and the numerical tool are well established.