Although wastewater and sewage systems are known to be significant reservoirs of antibiotic resistant bacterial populations and periodic outbreaks of drug resistant infection, there is little quantitative understanding of the drivers behind resistant population growth in these settings. In order to fill this gap in quantitative understanding of the development of antibiotic resistant infections in wastewater, we have developed a mathematical model synthesizing many known drivers of antibiotic resistance in these settings to help predict the growth of resistant populations in different environmental scenarios. A number of these drivers of drug resistant infection outbreak including antibiotic residue concentration, antibiotic interaction, chromosomal mutation and horizontal gene transfer, have not previously been integrated into a single computational model. We validated the outputs of the model with quantitative studies conducted on the eVOLVER continuous culture platform. Our integrated model shows that low levels of antibiotic residues present in wastewater can lead to increased development of resistant populations, and the dominant mechanism of resistance acquisition in these populations is horizontal gene transfer rather than acquisition of chromosomal mutations. Additionally, we found that synergistic antibiotic interactions lead to increased resistant population growth. These findings, consistent with recent experimental and field studies, provide new quantitative knowledge on the evolution of antibiotic resistant bacterial reservoirs, and the model developed herein can be adapted for use as a prediction tool in public health policy making, particularly in low income settings where water sanitation issues remain widespread and disease outbreaks continue to undermine public health efforts.

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计算模型以量化废水中的抗生素抗性细菌的生长

尽管已知废水和污水处理系统是重要的抗生素耐药性细菌种群和耐药性感染的定期爆发地，但在这些情况下，人们对耐药菌种群增长背后的驱动因素缺乏定量的了解。为了填补对废水中抗生素抗药性感染发展的定量了解的空白，我们开发了一种数学模型，该模型综合了这些环境中许多已知的抗生素抗药性驱动因素，以帮助预测在不同环境情况下抗药性种群的增长。这些抗药性感染爆发的驱动因素包括抗生素残留浓度，抗生素相互作用，染色体突变和水平基因转移，以前尚未集成到单个计算模型中。我们通过在eVOLVER连续培养平台上进行的定量研究验证了模型的输出。我们的综合模型表明，废水中存在的抗生素残留水平低会导致抗性种群的发展，而这些种群中抗性获得的主要机制是水平基因转移而不是染色体突变的获得。此外，我们发现协同抗生素相互作用导致耐药菌种群增长。这些发现与近期的实验和现场研究相一致，为抗生素抗药性细菌库的演变提供了新的定量知识，