Memory and learning behavior in mice is temporally associated with diet-induced alterations in gut bacteria.
The ability of dietary manipulation to influence learning and behavior is well recognized and almost exclusively interpreted as direct effects of dietary constituents on the central nervous system. The role of dietary modification on gut bacterial populations and the possibility of such microbial population shifts related to learning and behavior is poorly understood. The purpose of this study was to examine whether shifts in bacterial diversity due to dietary manipulation could be correlated with changes in memory and learning. Five week old male CF1 mice were randomly assigned to receive standard rodent chow (PP diet) or chow containing 50% lean ground beef (BD diet) for 3 months. As a measure of memory and learning, both groups were trained and tested on a hole-board open field apparatus. Following behavioral testing, all mice were sacrificed and colonic stool samples collected and analyzed by automated rRNA intergenic spacer analysis (ARISA) and bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP) approach for microbial diversity. Results demonstrated significantly higher bacterial diversity in the beef supplemented diet group according to ARISA and bTEFAP. Compared to the PP diet, the BD diet fed mice displayed improved working (P=0.0008) and reference memory (P<0.0001). The BD diet fed animals also displayed slower speed (P<0.0001) in seeking food as well as reduced anxiety level in the first day of testing (P=0.0004). In conclusion, we observed a correlation between dietary induced shifts in bacteria diversity and animal behavior that may indicate a role for gut bacterial diversity in memory and learning.
Li
Wang
W
School of Pharmacy, Texas Tech University Health Sciences Center, Lubbock, TX 79430, United States.
Dowd
Scot E
SE
Scurlock
Bobbie
B
Acosta-Martinez
Veronica
V
Lyte
Mark
M
D000704:Analysis of Variance; D000821:Animal Feed; D000818:Animals; D001245:Association Learning / Q000502:physiology*; D001419:Bacteria / Q000145:classification* / Q000235:genetics; D044822:Biodiversity; D003106:Colon / Q000382:microbiology* / Q000502:physiology; D015169:Colony Count, Microbial; D021901:DNA, Intergenic / Q000235:genetics; D004044:Dietary Proteins / Q000378:metabolism; D004193:Discrimination Learning / Q000502:physiology*; D005106:Exploratory Behavior / Q000502:physiology; D008137:Longitudinal Studies; D008297:Male; D008568:Memory / Q000502:physiology*; D051379:Mice; D012329:RNA, Bacterial / Q000032:analysis; D012335:RNA, Ribosomal / Q000032:analysis; D011897:Random Allocation; D013037:Spatial Behavior / Q000502:physiology; D018709:Statistics, Nonparametric; D013997:Time Factors
D021901:DNA, Intergenic; D004044:Dietary Proteins; D012329:RNA, Bacterial; D012335:RNA, Ribosomal