Running in the wheel: Defining individual severity levels in mice

The fine-scale grading of the severity experienced by animals used in research constitutes a key element of the 3Rs (replace, reduce, and refine) principles and a legal requirement in the European Union Directive 2010/63/EU. Particularly, the exact assessment of all signs of pain, suffering, and distress experienced by laboratory animals represents a prerequisite to develop refinement strategies. However, minimal and noninvasive methods for an evidence-based severity assessment are scarce. Therefore, we investigated whether voluntary wheel running (VWR) provides an observer-independent behaviour-centred approach to grade severity experienced by C57BL/6J mice undergoing various treatments. In a mouse model of chemically induced acute colitis, VWR behaviour was directly related to colitis severity, whereas clinical scoring did not sensitively reflect severity but rather indicated marginal signs of compromised welfare. Unsupervised k-means algorithm–based cluster analysis of body weight and VWR data enabled the discrimination of cluster borders and distinct levels of severity. The validity of the cluster analysis was affirmed in a mouse model of acute restraint stress. This method was also applicable to uncover and grade the impact of serial blood sampling on the animal’s welfare, underlined by increased histological scores in the colitis model. To reflect the entirety of severity in a multidimensional model, the presented approach may have to be calibrated and validated in other animal models requiring the integration of further parameters. In this experimental set up, however, the automated assessment of an emotional/motivational driven behaviour and subsequent integration of the data into a mathematical model enabled unbiased individual severity grading in laboratory mice, thereby providing an essential contribution to the 3Rs principles.实验用动物所遭受的损伤程度的精细分级，是3Rs（替代Replacement、减少Reduction、优化Refinement）原则的核心组成部分，同时也是欧盟《2010/63/EU指令》的法定要求。精准评估实验动物所表现出的所有疼痛、痛苦与窘迫迹象，是制定优化策略的前提条件。然而，目前基于证据的损伤程度评估所需的微创、低侵入性方法仍较为匮乏。为此，本研究探讨了自愿转轮运动（Voluntary Wheel Running，VWR）是否可提供一种无需观察者干预、以行为为核心的方法，用于对接受不同处理的C57BL/6J小鼠的损伤程度进行分级。在化学诱导性急性结肠炎小鼠模型中，自愿转轮运动行为与结肠炎损伤程度直接相关；而临床评分却无法灵敏地反映损伤程度，仅能体现出动物福利受损的轻微迹象。基于无监督k均值聚类算法对体重与VWR数据进行分析，可明确聚类边界与不同等级的损伤程度。该聚类分析的有效性在急性束缚应激小鼠模型中得到了验证。此方法同样可用于揭示并分级连续采血对动物福利的影响，这一点在结肠炎模型中通过升高的组织学评分得到了证实。若要在多维模型中全面反映损伤程度，本研究提出的方法或许需要在其他需整合更多参数的动物模型中进行校准与验证。然而，在本实验设置中，对情绪/动机驱动行为的自动化评估，并将数据整合至数学模型后，可实现实验小鼠无偏的个体损伤程度分级，从而为3Rs原则作出了重要贡献。