Behavioural battery testing: Evaluation and behavioural outcomes in 8 inbred mouse strains
Introduction
A major difficulty in using mouse models to map QTLs for complex traits, such as behaviour, is the large number of animals required for the undertaking to be successful. This complication is further compounded by the paradox of dissecting complex traits into manageable components without losing sight of the multitude of underlying factors that may be interacting and attributable for the trait in question. Behavioural phenotyping assays performed in isolation may oversimplify and fail to account for the complex networks that are involved, so multi-scale phenotyping approaches are desirable as they provide much more information on many levels and enable us to generate a comprehensive profile of a phenotype [1], [2], [3]. Studies that aim to dissect and map behaviours using these approaches have become popular in the post-genomic era [4], [5], [6], [7], [8]. While comparisons between behavioural battery tested and naïve mice have been reported to demonstrate task-dependent differences, in the main behavioural profiles are found to be comparable [9]. In battery testing we can make use of a composite of measures across multiple tests and look for their correlation with overlapping behavioural phenotypes, which can in turn be complemented by association with biological markers to gain a broad appraisal of the underlying mechanisms [10], [11], [12]. A further advantage is that since screening can be performed using the same animals throughout a carefully devised phenotyping platform, these studies can actually serve to reduce the number of animals needed to effectively map QTLs for behaviours.
Mapping studies that make use of a battery of tests can only be fruitful if the experimental design is given careful consideration. Homogeneous test groups that account for age and weight across animals are an important starting point. However, standardising environmental variables in particular, which mouse behavioural batteries may be sensitive to, such as ambient conditions (noise, temperature, humidity), pH of drinking water, diet, single or group housing, and methods of animal husbandry, are critical since they can profoundly affect test outcome [13], [14], [15], [16], [17]. Behavioural differences have been shown to be vulnerable to housing parameters across certain inbred strains, which one group [18] demonstrated when they compared mice that were housed individually with group-housed mice in a behavioural test battery. In particular they found that in some strains, singly housed mice habituated to test conditions faster when the assay was measuring activity and exploratory behaviours, but showed more anxiety-like behaviours in the light–dark box and hyponeophagia tests, and less so in the elevated plus maze [18]. There is also a complex interplay of gene-environment with different forms of cage enrichment [19], [20] that is apparent even with subtle modification, which was found to significantly alter behaviours across inbred strains in specific tests [21]. Previous efforts of standardisation have proven challenging and identified several parameters that are uncontrollable. A key study [15] highlighted the limitations with cross-validation between laboratories, when they demonstrated that results were relatively reproducible but, some parameters could not be absolutely replicated between the three participating centres despite equating experimental design and test apparatus.
Standardising environmental variables is necessary, but equal consideration must be given to the criteria for experimental design especially when devising behavioural batteries since sequence of testing should take into account the sensitivity of specific tests that could significantly influence the outcome of subsequent tests. One group [9] showed that some tests were more susceptible to test order than others in their test battery. Measures in the light–dark box were particularly sensitive to test order in their investigation, and acoustic startle response in C57BL/6J was also affected. Circadian rhythms can further influence performance in some behavioural tests [22], [23], [24], such as those that measure activity and anxiety. These measures may be affected by the time of day as well as the cycle-phase in which the test is carried out, particularly since mice are nocturnal mammals and therefore testing during their alternate phase could affect the natural response observed across behavioural tests.
Even when taking into account all possible confounding factors, the inherent differences that are commonly reported within and between laboratories in mouse phenotyping studies are likely to be attributable to subtle and specific inter-laboratory practices, yet in order to obtain results from which we can make meaningful inferences, adopting common standards are a prerequisite for its success. The use of clearly defined objectives and employing a robust and reliable phenotyping battery at the outset will ultimately enable results to be obtained with a reasonable level of accuracy. A demonstrable behavioural battery [25] that was developed and validated across five test centres throughout Europe, showed the value of well defined Standard Operating Procedures (SOPs) within their behavioural battery, which allowed them to identify the potential sources of variation, and where necessary refine procedures to attain a good degree of reliable and reproducible strain ranking effects between participating centres.
We devised a high throughput behavioural battery that aimed to index a broad and comprehensive range of behaviours such as anxiety, locomotor activity, learning and memory, in order to map underlying QTLs and to further characterise the biological pathways involved within a recombinant inbred panel (BXD) and an outbred population (Heterogeneous Stock) of mice. Central to our success in this task was evaluation of the behavioural battery design, which was performed using the C57BL/6J strain, a progenitor of both BXD and HS. The specific aims of the evaluation exercise were to assess how robust our experimental design was by means of the potential confounds frequently associated with behavioural batteries. We investigated the effects of several aspects of our experimental design: individually versus sibling (pair) housed; testing at different times during the day (am/pm); the test run through the battery versus testing in isolation; and the initial placement within the light–dark box. In addition, we assessed how these behavioural profiles differ in this battery of tests across 8 well characterised inbred strains, some of which are also progenitors of the HS mice we used in our study.
Section snippets
Animals
Male mice [C57BL/6J (n = 111), 129S1/SvImJ (n = 11), A/J (n = 11), BALB/cByJ (n = 11), C3H/HeJ (n = 10), DBA/2J (n = 11), FVB/NJ (n = 11), SJL/J (n = 11)] were generated in the Comparative Biology Unit animal facilities at the Institute of Psychiatry using original stocks [respective stock numbers: 000664, 002448, 000646, 001026, 000659, 000671, 000671, and 000686] purchased from The Jackson Laboratory (Bar Harbor, ME, USA). We tested male mice only throughout our battery to avoid the possible confounds of
Behavioural battery evaluation
The mean (± standard deviation) age and weight across all groups, at the start of the evaluation battery, was 86.8 ± 4.6 days and 26.0±1.5 (g), respectively. Home cage measures across all comparison groups were comparable and showed no significant differences.
Discussion
The development of a number of high throughput mouse behavioural phenotyping batteries, which aim to better characterise their genetic underpinnings, has accelerated with a greater emphasis placed on studying the underlying complex networks [3], [4], [6], [7], [17], [25], [35], [50], [51]. Fundamental to fulfilling this challenge is the need for robust assays that account for a multitude of variables, including the subtle environmental stimuli which may be interacting with genetic factors [8],
Acknowledgements
Funding for this work was provided by the Medical Research Council (G0000170). The authors thank S. Whatley for supplying the C57BL/6J mice.
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