The impacts of different macronutrients on body weight regulation remain unresolved, with different studies suggesting increased dietary fat, increased carbohydrates (particularly sugars), or reduced protein may all stimulate overconsumption and drive obesity. We exposed C57BL/6 mice to 29 different diets varying from 8.3% to 80% fat, 10% to 80% carbohydrate, 5% to 30% protein, and 5% to 30% sucrose. Only increased dietary fat content was associated with elevated energy intake and adiposity. This response was associated with increased gene expression in the 5-HT receptors, and the dopamine and opioid signaling pathways in the hypothalamus. We replicated the core findings in four other mouse strains (DBA/2, BALB/c, FVB, and C3H). Mice regulate their food consumption primarily to meet an energy rather than a protein target, but this system can be over-ridden by hedonic factors linked to fat, but not sucrose, consumption.

Graphical AbstractHighlights d Mice lacking gut microbiota have impaired UCP1-dependent thermogenesis in cold d These effects are replicated in germ-free mice treated with CL-316243 d IL-4 has no differential effect on energy metabolism in either control or ABX mice d Gavage of ABX mice with butyrate partially rescues the effects on BAT recruitment SUMMARYThe relation between gut microbiota and the host has been suggested to benefit metabolic homeostasis. Brown adipose tissue (BAT) and beige adipocytes facilitate thermogenesis to maintain host core body temperature during cold exposure. However, the potential impact of gut microbiota on the thermogenic process is confused. Here, we evaluated how BAT and white adipose tissue (WAT) responded to temperature challenges in mice lacking gut microbiota. We found that microbiota depletion via treatment with different cocktails of antibiotics (ABX) or in germfree (GF) mice impaired the thermogenic capacity of BAT by blunting the increase in the expression of uncoupling protein 1 (UCP1) and reducing the browning process of WAT. Gavage of the bacterial metabolite butyrate increased the thermogenic capacity of ABX-treated mice, reversing the deficit. Our results indicate that gut microbiota contributes to upregulated thermogenesis in the cold environment and that this may be partially mediated via butyrate.

Identifying drug-drug interactions (DDIs) is a major challenge in drug development. Previous attempts have established formal approaches for pharmacokinetic (PK) DDIs, but there is not a feasible solution for pharmacodynamic (PD) DDIs because the endpoint is often a serious adverse event rather than a measurable change in drug concentration. Here, we developed a metric “S-score” that measures the strength of network connection between drug targets to predict PD DDIs. Utilizing known PD DDIs as golden standard positives (GSPs), we observed a significant correlation between S-score and the likelihood a PD DDI occurs. Our prediction was robust and surpassed existing methods as validated by two independent GSPs. Analysis of clinical side effect data suggested that the drugs having predicted DDIs have similar side effects. We further incorporated this clinical side effects evidence with S-score to increase the prediction specificity and sensitivity through a Bayesian probabilistic model. We have predicted 9,626 potential PD DDIs at the accuracy of 82% and the recall of 62%. Importantly, our algorithm provided opportunities for better understanding the potential molecular mechanisms or physiological effects underlying DDIs, as illustrated by the case studies.