More than 250 million courses of antibiotics are prescribed annually in the ambulatory care setting in the United States alone, including more than 40 million in children under 18 years of age. The perception that antibiotic use has minimal attendant adverse side effects contributes to the over-utilization of antibiotics in clinical circumstances when they are not strictly indicated. We have learned much about the human microbiome. The emerging view is of profound life-long bi-directional interactions between our microbiota and our cells. Perturbations in the microbiota affect metabolic, immune, and cognitive physiology in experimental animal models. When a person takes an antibiotic, the antibiotic diffuses via the blood into all body compartments, selecting for resistance. We propose to examine the effects of two commonly used antibiotics (the beta-lactam, amoxicillin and the macrolide azithromycin) on human microbial populations and on metabolic and immune physiology, studying healthy human volunteers in a randomized controlled clinical trial at the NIH Clinical Center. Our hypothesis is that in addition to acutely perturbing the human microbiome, these agents will have measurable metabolic and immunologic effects, with residual effects in the weeks that follow. To test this hypothesis, we will assess the effects of a brief therapeutic course of antibiotics on microbiome and metagenome composition. After an initial evaluation period, antibiotics will be given for 7 days or 5 days (depending on the antibiotic), and there will be a post-treatment evaluation. A control group will receive no drug intervention. Specimens will be obtained from multiple sites at each of 10 time points occurring before, during, and after antibiotic administration, and used for estimating bacterial and fungal composition and gene content. We will also assess the effects of the antibiotic course on markers of innate and adaptive immunity as well as markers of metabolic and hormonal physiology. A subgroup of subjects will be studied in the clinical center metabolic chamber to assess 24-hour energy expenditure and its components (sleeping, diet-induced, and activity energy expenditure), as well as macronutrient oxidation rates (carbohydrate, fat, and protein), during 3 of the 10 study visits. In addition to the primary data analyses, we will build a model that integrates the temporal data to begin to understand the complex intertwined physiology between microbiome and host.