Gut Microbiota Composition Is Correlated to Grid Floor Induced Stress and Behavior in the BALB/c Mouse

Abstract

Stress has profound influence on the gastro-intestinal tract, the immune system and the behavior of the animal. In this study, the correlation between gut microbiota composition determined by Denaturing Grade Gel Electrophoresis (DGGE) and tag-encoded 16S rRNA gene amplicon pyrosequencing (454/FLX) and behavior in the Tripletest (Elevated Plus Maze, Light/Dark Box, and Open Field combined), the Tail Suspension Test, and Burrowing in 28 female BALB/c mice exposed to two weeks of grid floor induced stress was investigated. Cytokine and glucose levels were measured at baseline, during and after exposure to grid floor. Stressing the mice clearly changed the cecal microbiota as determined by both DGGE and pyrosequencing. Odoribacter, Alistipes and an unclassified genus from the Coriobacteriaceae family increased significantly in the grid floor housed mice. Compared to baseline, the mice exposed to grid floor housing changed the amount of time spent in the Elevated Plus Maze, in the Light/Dark Box, and burrowing behavior. The grid floor housed mice had significantly longer immobility duration in the Tail Suspension Test and increased their number of immobility episodes from baseline. Significant correlations were found between GM composition and IL-1α, IFN-γ, closed arm entries of Elevated Plus Maze, total time in Elevated Plus Maze, time spent in Light/Dark Box, and time spent in the inner zone of the Open Field as well as total time in the Open Field. Significant correlations were found to the levels of Firmicutes, e.g. various species of Ruminococccaceae and Lachnospiraceae. No significant difference was found for the evaluated cytokines, except an overall decrease in levels from baseline to end. A significant lower level of blood glucose was found in the grid floor housed mice, whereas the HbA1c level was significantly higher. It is concluded that grid floor housing changes the GM composition, which seems to influence certain anxiety-related parameters.

Changes in Cecal Microbiota and Mucosal Gene Expression Revealed New Aspects of Epizootic Rabbit Enteropathy

“…Pyrosequencing has been recently used to investigate the microbial composition of a variety of cecal filtrates and fractions that reproduced ERE in rabbits, but no statistical differences were found between samples in that work [22]. Our work showed that cecal microbiota in healthy rabbits is dominated by Firmicutes (78.25% of total OTUs), Bacteroidetes (15.75%), Verrucomirobia (2.40%) and Tenericutes (2.39%) and this quantitatively similar to that found in other monogastric herbivores (hindgut fermenters) [23] and in mouse, as the closest model, in which also Firmicutes dominate over Bacteroidetes [24], [25].…”

Bovine Colostrum Modulates Myeloablative Chemotherapy–Induced Gut Toxicity in Piglets

“…Raw data underwent denoising, chimera filtering, and operational taxonomic unit (OTU) picking, as previously described (33), and the remaining highquality sequences were clustered at 97% relatedness with the use of UCLAST (34). Representative sequences from each cluster were aligned with PyNAST (35), subjected to the Ribosomal Database Project-based 16S ribosomal RNA gene annotation.…”

Interoceptive dysfunction: Toward an integrated framework for understanding somatic and affective disturbance in depression.

“…Microbiome-HPA-axis interaction is characterized by bidirectional influence; stress can adversely impact the microbiome (e.g., Bailey et al, 2010; Bendtsen et al, 2012) and increase circulating inflammatory markers (e.g., Bailey et al, 2011), whereas probiotics (e.g., Lactobacillus rhamnosus ) appear to blunt HPA-axis responsivity to stress (e.g., Ait-Belgnaoui et al, 2012). A number of measures of anxiety- and depression-related behavior in rodent models, including behavior on the elevated plus maze, stress-induced hyperthermia, and forced-swim—a measure of proneness to adopt passive responding and “give up” attempts to escape an aversive situation—are thus affected by the makeup of the microbiome (e.g., Bravo et al, 2011; Neufeld et al, 2011).…”