Search for: All records

Abstract The goal of engineering the microbiome of the built environment is to create places and spaces that are better for human health. Like other emerging technologies, engineering the microbiome of the built environment may bring considerable benefits but there has been a lack of exploration on its societal implication and how to engineer in an ethical way. To date, this topic area has also not been pulled together into a singular study for any systematic review or analysis. This study fills this gap by providing the first a systematic review of societal and ethical implications of engineering microbiomes and the application of this knowledge to engineering the microbiome of the built environment. To organize and guide our analysis, we invoked four major ethical principles (individual good/non-maleficence, collective good/beneficence, autonomy, and justice) as a framework for characterizing and categorizing 15 distinct themes that emerged from the literature. We argue that these different themes can be used to explain and predict the social and ethical implications of engineering the microbiome of the built environment that if addressed adequately can help to improve public health as this field further develops at global scales. 

Antibiotic resistance is a growing health concern. Efforts to control resistance would benefit from an improved ability to forecast when and how it will evolve. Epistatic interactions between mutations can promote divergent evolutionary trajectories, which complicates our ability to predict evolution. We recently showed that differences between genetic backgrounds can lead to idiosyncratic responses in the evolvability of phenotypic resistance, even among closely relatedEscherichia colistrains. In this study, we examined whether a strain's genetic background also influences the genotypic evolution of resistance. Do lineages founded by different genotypes take parallel or divergent mutational paths to achieve their evolved resistance states? We addressed this question by sequencing the complete genomes of antibiotic-resistant clones that evolved from several different genetic starting points during our earlier experiments. We first validated our statistical approach by quantifying the specificity of genomic evolution with respect to antibiotic treatment. As expected, mutations in particular genes were strongly associated with each drug. Then, we determined that replicate lines evolved from the same founding genotypes had more parallel mutations at the gene level than lines evolved from different founding genotypes, although these effects were more subtle than those showing antibiotic specificity. Taken together with our previous work, we conclude that historical contingency can alter both genotypic and phenotypic pathways to antibiotic resistance.