Over the last two decades, an association between microbiome composition and some diseases has been unambiguously established. The association between gut microbe composition and these diseases has prompted medical interest into bacteriotherapies, which seek to modify the gut microbiome composition in the hopes of treating the correlated disease. To inform these aims, in an experimental collaboration with Will Ludington at the Carnegie Institute for Science, we combinatorially dissect the natural gut microbiome of Drosophila melanogaster to reveal that interactions between bacteria shape host fitness through life history tradeoffs. Our results indicate that observed host phenotypes of a diverse microbiome may be approximately predicted by the phenotypes of its constitutive one- and two-species microbiomes, indicating a potential route for dimensionality reduction within the microbiome. Then, I use generalized Lotka-Volterra (gLV) models to probe the ecological mechanisms through which bacteriotherapies function. We describe direct bacteriotherapies, which drive a microbiome to a target state via an instantaneous influx of foreign microbes (e.g. probiotics or fecal microbiota transplantation), and then present a novel control framework for indirect bacteriotherapies, which drive a microbiome to a target state by deliberately modifying its environment (e.g. diet, acidity, or nutrients). These dual control methods for gLV systems, interpreted as bacteriotherapies, could eventually inform personalized medicine for the microbiome.