Mouse Genome Informatics (MGI) Resource: Genetic, Genomic, and Biological Knowledgebase for the Laboratory Mouse

Animal models to study bile acid metabolism

The use of animal models, particularly genetically modified mice, continues to play a critical role in studying the relationship between bile acid metabolism and human liver disease. Over the past 20 years, these studies have been instrumental in elucidating the major pathways responsible for bile acid biosynthesis and enterohepatic cycling, and the molecular mechanisms regulating those pathways. This work also revealed bile acid differences between species, particularly in the composition, physicochemical properties, and signaling potential of the bile acid pool. These species differences may limit the ability to translate findings regarding bile acid-related disease processes from mice to humans. In this review, we focus primarily on mouse models and also briefly discuss dietary or surgical models commonly used to study the basic mechanisms underlying bile acid metabolism. Important phenotypic species differences in bile acid metabolism between mice and humans are highlighted.

Bridging the Gap between Reproducibility and Translation: Data Resources and Approaches

Animal research has constituted a fundamental means to achieve groundbreaking therapies for human disease. However, for complex diseases, promising preclinical results have failed to translate to the clinic. Reasons for this disparity are multifactorial. These include the challenges inherent in modeling complex disease in animals, as well issues of study design, reproducibility and operational norms within the biomedical research enterprise. In this issue, we explore the range of information resources available for the comparative study of disease, as well as challenges to the ultimate translation of preclinical findings. Genomics resources in support of translational research are described for zebrafish, mice, rats and non-human primates. The utility of transcriptomics to explore the temporal basis of lesion development in toxicologic pathology is reviewed. Integration of the ever-increasing volume of text-based and bioinformatics data is a significant challenge, and in this issue, informatics resources and general text mining methodologies to explore and aggregate text data are described. Finally, factors contributing to both reproducibility and translatability are examined. Guidelines designed to address reproducibility are essential to improving individual studies. To this end, a viewpoint from the National Institutes of Health on measures needed to enhance rigor and reproducibility is given, as well as an overview of the role of the Institutional Animal Care and Use Committee in this regard. The challenge of improving generalizability of animal experiments so that their findings can be more frequently extended to the intended human population remains. Reasons why models that replicate key aspects of human disease fail to be predictive in humans are explored in two fields in which translation has been a challenge: sepsis and neurodegeneration.