Running in the wheel: Defining individual severity levels in mice

Abstract

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.

One score to rule them all: severity assessment in laboratory mice

“…Missing variables did not contribute to the RELSA score, whereas values equal or above baseline level contributed with values of zero. Furthermore, levels of severity in the reference data were calculated using a k- means algorithm 13 . The number of clusters was determined heuristically with a scree plot (Fig.…”

“…This integration requires adequate compositional scoring systems. We have previously contributed evidence that the inclusion of data science and abstract mathematical methods to explain higher-order relationships in the data that go beyond the traditional scope of statistical post hoc analyses is highly informative in terms of determining severity conditions or levels 13–15 . Building on this experience, we aimed to develop an algorithm-based composite scoring system that enables objective monitoring of welfare states using a theoretically indefinite number of variables from various scientific fields, allowing comparisons between individual animals, treatment groups and animal models.…”

The search for translational pain outcomes to refine analgesic development: Where did we come from and where are we going?

“…Since the first description of wheel running depression associated with postsurgical pain induced by splenectomy (Clark et al, 2004), activity wheels have been tested successfully in several pain models. Known examples of these models to date include (among others) postsurgical pain after laparotomy (Kendall et al, 2016), CFA-induced hindlimb inflammation (Cobos et al, 2012;Kandasamy et al, 2016;Pitzer et al, 2016b;Kandasamy et al, 2017a;Sheahan et al, 2017), hindlimb osteoarthritis (Stevenson et al, 2011), chronic constriction injury of the sciatic nerve (Whitehead et al, 2017), paclitaxel-induced neuropathic pain (Griffiths et al, 2018), migraine induced by microinjection of allyl-isothiocyanate in the dura (Kandasamy et al, 2017b; and 2018a and 2018b), bone cancer pain in the femur (Tang et al, 2016), a model of osteogenesis imperfecta (Abdelaziz et al, 2015), and visceral pain induced by sodium dodecyl sulfate as a model of colitis (Häger et al, 2018) or by the intraperitoneal injection of acetic acid (Miller et al, 2011). These results indicate that wheel running is sensitive enough to detect several pain conditions.…”

Assessing Affective State in Laboratory Rodents to Promote Animal Welfare—What Is the Progress in Applied Refinement Research?

“…Nevertheless, no deviation is not an indication of whether an animal is experiencing a positive affective state or is in a neutral state. Even in rather negative states, for instance, in minor pain states (e.g., [23]) or some restraint stress models [24], body weight can remain stable while other behavioral parameters, for example, burrowing or wheel running, indicate a clear Figure 1. Graphical overview of the methods assessing positive or negative affective states as described in this article.…”

“…Manual scoring of home cage behavior is, however, laborious and very time consuming, therefore there is a high demand for automated systems. For example, activity measures can be derived from running wheels and can serve as an indicator of the severity of experimental procedures [24].…”