Differential genetic regulation of motor activity and anxiety-related behaviors in mice using an automated home cage task.

Abstract

Traditional behavioral tests, such as the open field test, measure an animal's responsiveness to a novel environment. However, it is generally difficult to assess whether the behavioral response obtained from these tests relates to the expression level of motor activity and/or to avoidance of anxiogenic areas. Here, an automated home cage environment for mice was designed to obtain independent measures of motor activity levels and of sheltered feeding preference during three consecutive days. Chronic treatment with the anxiolytic drug chlordiazepoxide (5 and 10 mg/kg/day) in C57BL/6J mice reduced sheltered feeding preference without altering motor activity levels. Furthermore, two distinct chromosome substitution strains, derived from C57BL/6J (host strain) and A/J (donor strain) inbred strains, expressed either increased sheltering preference in females (chromosome 15) or reduced motor activity levels in females and males (chromosome 1) when compared to C57BL/6J. Longitudinal behavioral monitoring revealed that these phenotypic differences maintained after adaptation to the home cage. Thus, by using new automated behavioral phenotyping approaches, behavior can be dissociated into distinct behavioral domains (e.g., anxiety-related and motor activity domains) with different underlying genetic origin and pharmacological responsiveness.

A robust automated system elucidates mouse home cage behavioral structure

“…Similar patterns of intermittent locomotion have been observed in rodents exploring novel laboratory environments (42) and are also common in natural environments (43). Despite the prevalence of such movement patterns, procedures for capturing their basic features had not previously been developed for home cage behavioral assessment (1,(6)(7)(8)(9)(10)(11)(12)(13)(16)(17)(18).…”

“…The functions and interactions of these systems result in the coordinated organization of multiple behaviors (3-5). Although several sophisticated approaches for automated behavioral data collection and home cage monitoring exist, they do not employ algorithms that quantitatively capture the rich temporal and spatial structure of diverse behaviors that occur over multiple time scales (1,(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).As a first step in examining this structure, we made use of the observation that in natural environments animals typically alternate between two major discrete states, active and inactive (20)(21)(22). During active states (ASs), animals engage in behaviors such as foraging and patrolling within a regularly traversed home range.…”

“…The functions and interactions of these systems result in the coordinated organization of multiple behaviors (3)(4)(5). Although several sophisticated approaches for automated behavioral data collection and home cage monitoring exist, they do not employ algorithms that quantitatively capture the rich temporal and spatial structure of diverse behaviors that occur over multiple time scales (1,(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19).…”

Compulsivity in mouse strains homologous with chromosomes 7p and 15q linked to obsessive‐compulsive disorder

“…By partitioning the genome into a panel of new inbred strains with single CSs, (one strain for each chromosome), unique experimental designs and considerable statistical power are possible to accelerate the detection of quantitative trait loci (QTLs) with small effect sizes [Singer et al, 2004]. Several published studies demonstrate the considerable utility of these strains and new applications for CS strains continue to be discovered [Singer et al, 2004;Hill et al, 2006;Kas et al, 2008]. Compulsivity was assumed to be mimicked by continuous and repetitive wheel running during the 2 hr of food availability as it expresses the inability to stop wheel running despite the more appealing food availability.…”

Evidence for Epigenetic Interactions for Loci on Mouse Chromosome 1 Regulating Open Field Activity

“…By using gene expression analysis, Hitzemann et al (2003) were able to identify Kcnj9 as the most likely candidate gene in this region. In addition, several other likely positions for loci on chromosome 1 are found that affect motor activity levels (100 Mb, de Ledesma et al 2006190 Mb, Singer et al 2004 Mb, Kas et al 2008a, b).…”