Yvonne K Urbach1, Kerstin A Raber1, Fabio Canneva1, Anne-C Plank1, Theresa Andreasson2, Henrik Ponten2, Johan Kullingsjö2, Huu Phuc Nguyen3, Olaf Riess3, Stephan von Hörsten4. 1. Experimental Therapy, Preclinical Experimental Center, Universitätsklinikum Erlangen, 91054 Erlangen, Germany. 2. NeuroSearch Sweden AB, Arvid Wallgrens Backe 20, 41346 Gothenburg, Sweden. 3. Department of Medical Genetics, University of Tübingen, 72076 Tübingen, Germany. 4. Experimental Therapy, Preclinical Experimental Center, Universitätsklinikum Erlangen, 91054 Erlangen, Germany. Electronic address: Stephan.v.Hoersten@uk-erlangen.dede.
Abstract
BACKGROUND: The need for improving throughput, validity, and reliability in the behavioral characterization of rodents may benefit from integrating automated intra-home-cage-screening systems allowing the simultaneous detection of multiple behavioral and physiological parameters in parallel. NEW METHOD: To test this hypothesis, transgenic Huntington's disease (tgHD) rats were repeatedly screened within phenotyping home-cages (PhenoMaster and IntelliCage for rats), where spontaneous activity, feeding, drinking, temperature, and metabolic performance were continuously measured. Cognition and emotionality were evaluated within the same environment by means of operant learning procedures and refined analysis of the behavioral display under conditions of novelty. This investigator-independent approach was further correlated with behavioral display of the animals in classical behavioral assays. Multivariate analysis (MVA) including Principle Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) was used to explore correlation patterns of variables within and across the two genotypes. RESULTS: The automated systems traced previously undetected aspects in the phenotype of tgHD rats (circadian activity, energy metabolism, rearing), and out of those spontaneous free rearing correlated with individual performance in the accelerod test. PCA revealed a segregation by genotype in juvenile tgHD rats that differed from adult animals, being further resolved by PLS-DA detecting "temperature" (juvenile) and "rearing" (adult) as phenotypic key variables in the tgHD model. CONCLUSIONS: Intra-home-cage phenotyping in combination with MVA, is capable of characterizing a complex phenotype by detecting novel physiological and behavioral markers with high sensitivity and standardization using fewer human resources. A broader application of automated systems for large-scale screening is encouraged.
BACKGROUND: The need for improving throughput, validity, and reliability in the behavioral characterization of rodents may benefit from integrating automated intra-home-cage-screening systems allowing the simultaneous detection of multiple behavioral and physiological parameters in parallel. NEW METHOD: To test this hypothesis, transgenic Huntington's disease (tgHD) rats were repeatedly screened within phenotyping home-cages (PhenoMaster and IntelliCage for rats), where spontaneous activity, feeding, drinking, temperature, and metabolic performance were continuously measured. Cognition and emotionality were evaluated within the same environment by means of operant learning procedures and refined analysis of the behavioral display under conditions of novelty. This investigator-independent approach was further correlated with behavioral display of the animals in classical behavioral assays. Multivariate analysis (MVA) including Principle Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) was used to explore correlation patterns of variables within and across the two genotypes. RESULTS: The automated systems traced previously undetected aspects in the phenotype of tgHD rats (circadian activity, energy metabolism, rearing), and out of those spontaneous free rearing correlated with individual performance in the accelerod test. PCA revealed a segregation by genotype in juvenile tgHD rats that differed from adult animals, being further resolved by PLS-DA detecting "temperature" (juvenile) and "rearing" (adult) as phenotypic key variables in the tgHD model. CONCLUSIONS: Intra-home-cage phenotyping in combination with MVA, is capable of characterizing a complex phenotype by detecting novel physiological and behavioral markers with high sensitivity and standardization using fewer human resources. A broader application of automated systems for large-scale screening is encouraged.
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