Suchergebnisse

The growing appetite of behavioral neuroscience for automated data production is prompting the need for new computational standards allowing improved interoperability, reproducibility, and shareability. We show here how these issues can be solved by repurposing existing genomic formats whose structure perfectly supports the handling of time series. This allows existing genomic analysis and visualization tools to be deployed onto behavioral data. As a proof of principle, we implemented the conversion procedure in Pergola, an open source software, and used genomics tools to reproduce results obtained in mouse, fly, and worm. We also show how common genomics techniques such as principal component analysis, hidden Markov modeling, and volcano plots can be deployed on the reformatted behavioral data. These analyses are easy to share because they depend on the scripting of public software. They are also easy to reproduce thanks to their integration within Nextflow, a workflow manager using containerized software. ; We acknowledge the support of the "Secretaria d'Universitats i Recerca del Departament d'Economia i Coneixement de la Generalitat i del Fons Social Europeu," Spanish Ministry of Economy, Industry and Competitiveness (MEIC) under grant numbers BFU2014-55062-P and BFU2017-88264-P, the EMBL partnership, FEDER, the "Centro de Excelencia Severo Ochoa" Programme, and the CERCA Programme/Generalitat de Catalunya. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 635290-PanCanRisk and OpenRiskNet_731076. This reflects only the author's view and the funder is not responsible for any use that may be made of the information it contains. M.D. is supported by DIUE de la Generalitat de Catalunya (Grups consolidats SGR 2017/926), the Fondation Jérôme Lejeune (Paris, France), MINECO (SAF2013-49129-C2-1-R; SAF2016-79956-R), CDTI ("Smartfoods") and EU (EraNet Neuron PCIN-2013-060 and JPND AC17/00006), and the Catalan foundation "La Marató de TV3" (#2016/20-30). The CIBER of Rare Diseases is an initiative of the ISCIII.

A major problem in treating obesity is the high rate of relapse to abnormal food-taking habits after maintaining an energy balanced diet. Alterations of eating behavior such as compulsive-like behavior and lack of self-control over food intake play a critical role in relapse. In this study, we used an operant paradigm of food-seeking behavior on two different diet-induced obesity models, a free-choice chocolate-mixture diet and a high-fat diet with face validity for a rapid development of obesity or for unhealthy food regularly consumed in our societies. A reduced operant performance and motivation for the hedonic value of palatable chocolate pellets was revealed in both obesity mouse models. However, only mice exposed to high-fat diet showed an increased compulsive-like behavior in the absence of the reinforcer further characterized by impaired operant learning, enhanced impulsivity and intensified inflexibility. We used principal component analysis to globally identify the specific behaviors responsible for the differences among diet groups. Learning impairment and inflexible behaviors contributed to a first principal component, explaining the largest proportion of the variance in the high-fat diet mice phenotype. Reinforcement, impulsion and compulsion were the main contributors to the second principal component explaining the differences in the chocolate-mixture mice behavioral phenotype. These behaviors were not exclusive of chocolate group because some high-fat individuals showed similar values on this component. These data indicate that extended access to hypercaloric diets differentially modifies operant behavior learning, behavioral flexibility, impulsive-like and compulsive-like behavior, and these effects were dependent on the exposure to each specific diet. ; This work was supported by the DG Research of the European Commission FP7 (#HEALTH-F2 2013-602891 and PHECOMP #LHSM-CT-2007-037669), the Spanish 'RETICS-Instituto de Salud Carlos III' (#RD16/0017/0020), the Spanish 'Ministerio de Economia y Competitividad' (#SAF-2014-59648P), the 'Plan nacional sobre drogas' (#PNSD-2013-5068), the Catalan Government 'AGAUR-Generalitat de Catalunya' (#2014-SGR-1547) and the Catalan foundation 'La Marató de TV3' (#2016/20-30). The laboratory of M.D. is supported by DIUE de la Generalitat de Catalunya (Grups consolidats SGR 2014/1125). This work was supported by Fondation Jérôme Lejeune (Paris, France), MINECO (SAF2013-49129-C2-1-R), CDTI ('Smartfoods') and EU (Era Net Neuron PCIN-2013-060). The CRG is a Center of Excellence Severo Ochoa SEV-2012-0208. The CIBER of Rare Diseases is an initiative of the ISCIII. The laboratory of C.N. acknowledges the funding from the Spanish Ministry of Economy and Finance (MINECO), grant number BFU2011-28575. J.E. receivedthe FI grant from Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) de la Generalitat de Catalunya

Obesity represents an important risk factor contributing to the global burden of disease. The current obesogenic environment with easy access to calorie-dense foods is fueling this obesity epidemic. However, how these foods contribute to the progression of feeding behavior changes that lead to overeating is not well understood and needs systematic assessment. Using novel automated methods for the high-throughput screening of behavior, we here examine mice meal pattern upon long-term exposure to a free-choice chocolate-mixture diet and a high-fat diet with face validity for a rapid development of obesity induced by unhealthy food regularly consumed in our societies. We identified rapid diet-specific behavioral changes after exposure to those high-caloric diets. Mice fed with high-fat chow, showed long-lasting meal pattern disturbances, which initiate with a stable loss of circadian feeding rhythmicity. Mice receiving a chocolate-mixture showed qualitatively similar changes, though less marked, consisting in a transient disruption of the feeding behavior and the circadian feeding rhytmicity. Strikingly, compulsive-like eating behavior is triggered immediately after exposure to both high-fat food and chocolate-mixture diet, well before any changes in body weight could be observed. We propose these changes as behavioral biomarkers of prodromal states of obesity that could allow early intervention. ; The laboratory of M.D. is supported by DIUE de la Generalitat de Catalunya (Grups consolidats SGR 2014/1125). This work was supported by Fondation Jérôme Lejeune (Paris, France), MINECO (SAF2013‐49129‐C2‐1‐R; SAF2016‐79956‐R), CDTI ('Smartfoods') and EU (Era Net Neuron PCIN‐2013‐060) and the Catalan foundation 'La Marató de TV3' (#2016/20‐30). The CRG is a Center of Excellence Severo Ochoa SEV‐2012‐0208. The CIBER of Rare Diseases is an initiative of the ISCIII. The laboratory of C.N. acknowledge the funding from the Spanish Ministry of Economy and Finance (MINECO), grant number BFU2011‐28575. J.E. received the FI grant from Agència de Gestió d'Ajuts Universitaris i de Recerca (AGAUR) de la Generalitat de Catalunya. The laboratory of R.M. was supported by the DG Research of the European Commission FP7 (#HEALTH‐F2 2013‐602891 and PHECOMP #LHSM‐CT‐2007‐037669), the Spanish 'RETICS‐Instituto de Salud Carlos III' (#RD16/0017/0020), the Spanish 'Ministerio de Economia y Competitividad' (#SAF‐2014‐59648P), the 'Plan nacional sobre drogas' (#PNSD‐2013‐5068), the Catalan Government 'AGAUR‐Generalitat de Catalunya' (#2014‐SGR‐1547) and the Catalan foundation 'La Marató de TV3' (#2016/20‐30).