Altered gut microbiota in female mice with persistent low body weights following removal of post-weaning chronic dietary restriction. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Chen, Jun; Toyomasu, Yoshitaka; Hayashi, Yujiro; Linden, David; Szurszewski, Joseph; Nelson, Heidi; Farrugia, Gianrico; Kashyap, Purna; Chia, Nicholas; Ordog, Tamas
• Is Part Of: Genome medicine. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: Anorexia nervosa -- Dietary restriction -- Protein-energy malnutrition -- Gut microbiota -- Insulin-like growth factor 1 (IGF1) -- Machine learning -- Animal model; Genomics -- Periodicals; Medical genetics -- Periodicals; 616.042
• DOI: 10.1186/s13073-016-0357-1
• Languages: English
• ISSNs: 1756-994X

Abstract

Abstract Background Nutritional interventions often fail to prevent growth failure in childhood and adolescent malnutrition and the mechanisms remain unclear. Recent studies revealed altered microbiota in malnourished children and anorexia nervosa. To facilitate mechanistic studies under physiologically relevant conditions, we established a mouse model of growth failure following chronic dietary restriction and examined microbiota in relation to age, diet, body weight, and anabolic treatment. Methods Four-week-old female BALB/c mice (n = 12/group) were fed ad libitum (AL) or offered limited food to abolish weight gain (LF). A subset of restricted mice was treated with an insulin-like growth factor 1 (IGF1) analog. Food access was restored in a subset of untreated LF (LF-RF) and IGF1-treated LF mice (TLF-RF) on day 97. Gut microbiota were determined on days 69, 96–99 and 120 by next generation sequencing of the V3–5 region of the 16S rRNA gene. Microbiota–host factor associations were analyzed by distance-based PERMANOVA and quantified by the coefficient of determination R2 for age, diet, and normalized body weight change (Δbwt). Microbial taxa on day 120 were compared following fitting with an overdispersed Poisson regression model. The machine learning algorithm Random Forests was used to predict age based on the microbiota. Results On day 120, Δbwt in AL, LF, LF-RF, and TLF-RF mice was 52 ± 3, –6 ± 1*, 40 ± 3*, and 46 ± 2 % (*, P < 0.05 versus AL). Age and diet, but not Δbwt, were associated with gut microbiota composition. Age explained a larger proportion of the microbiota variability than diet or Δbwt. Random Forests predicted chronological age based on the microbiota and indicated microbiota immaturity in the LF mice before, but not after, refeeding. However, on day 120, the microbiota community structure of LF-RF mice was significantly different from that of both AL and LF mice. IGF1 mitigated the difference from the AL group. Refed groups had a higher abundance ofBacteroidetes andProteobacteria and a lower abundance ofFirmicutes than AL mice. Conclusions Persistent growth failure can be induced by 97-day dietary restriction in young female mice and is associated with microbiota changes seen in lean mice and individuals and anorexia nervosa. IGF1 facilitates recovery of body weights and microbiota.