Chicken or the Egg: Is AMR in the Environment Driven by Dissemination of Antibiotics or Antibiotic Resistance Genes?

环境中的抗菌素耐药性（AMR）是由人类和动物的尿液释放到污水中并最终进入河流的抗生素引起的。抗生素耐药性也会从人类和动物粪便中的肠道细菌中释放出来。在这两种情况下，抗生素和含有抗菌素耐药性的肠道细菌都通过污水释放到环境中。尽管抗生素和耐药细菌不断释放到我们的河流中，但我们仍然不知道它们在解释我们在环境中看到的抗生素耐药性方面所起的相对作用。这是一个极其重要的知识缺口，因为它阻碍了行业和政策制定者决定在何处花费时间和资源，从而降低这种“抗菌素耐药性的环境储存库”。污水中含有数千种化学物质，其中许多化学物质的浓度足以抑制或杀死细菌。微生物通过一系列策略保护自己免受这些化学物质的侵害，所有这些策略都含有被广泛归类为“抗性基因”的基因。因此，污水是发现富含抗性基因细菌的绝佳场所。已知这些基因中的许多是可移动的，这允许基因被共享，从而增加其在环境中的丰度。基因的这种流动性是为什么很难知道是什么导致了环境中的抗菌素耐药性的关键——有点像“先有鸡还是先有蛋”。污水中存在的抗生素浓度是否足以在环境中选择耐药基因，或者耐药基因是否只是从肠道细菌传播到天然环境微生物中？回答这个问题的关键在于以下两个问题：1)从污水中释放的基因是否在没有持续暴露于抗生素临界阈值浓度的情况下进入并持续存在于天然微生物群落中？2)环境中的临界阈值浓度是否足够高，足以在天然微生物群落中维持肠道来源的AMR基因或自行选择它们？在我们提出的研究中，我们的目标是通过四个创新的实验系统来回答这两个关键问题：1)用于精确控制和操纵微生物生物膜的小型实验室微流体系统；2)原位河流中生态系统和3)非原位宏观生态系统，它们也可以通过添加抗生素和/或抗生素抗性基因在受控条件下控制和操纵微生物生物膜；最后4)使用淡水虾Gammarus pulex作为抗生素耐药库升高环境的指示物种。以Gammarus为例，我们将研究生活在这种虾体内的微生物，并确定这些微生物是否获得与相同暴露的生物膜中发现的微生物相似的抗生素抗性特征。现代分子技术（即宏基因组、质粒宏基因组、qPCR、元转录组）将用于量化生物膜和Gammarus内的治疗效果。来自这些研究的数据将用于参数化一个数学/统计模型，该模型将被设计用于监管机构、工业界和学术界，以更好地预测和理解抗生素耐药性在环境中构成的风险。

Antimicrobial resistance (AMR) in the environment is driven by antibiotics released in the urine of humans and animals into sewage and ultimately the receiving rivers. AMR is also released from within the gut bacteria that are shed in faeces of both humans and animals. In both cases, antibiotics and AMR-containing gut bacteria are released into the environment through sewage. Despite the continued release of both antibiotics and antibiotic-resistant bacteria into our rivers, we still don't know the relative role that they play in explaining the amount of antibiotic resistance that we see in our environment. This is a critically important knowledge gap as it prevents industry and policy makers from determining where to spend our time and resources so as to lower this 'environmental reservoir of antimicrobial resistance'. Sewage contains thousands of chemicals, many of which are at concentrations sufficient to inhibit or kill bacteria. Microbes defend themselves from these chemicals with a range of strategies, all of which have genes that are broadly classified as 'resistance genes'. Hence, sewage is an excellent place to find bacteria rich in resistance genes. Many of these genes are known to be mobile, which allows for the genes to be shared, thereby increasing its abundance within the environment. This mobility of genes is key to why it is so difficult to know what is driving AMR in the environment-a bit like 'which came first, the chicken or the egg.' Are the concentrations of antibiotics present in sewage sufficiently high to select for resistance genes in the environment or are the genes for resistance simply spreading from the gut-derived bacteria into the native environmental microorganisms? The keys to answering this question lie in the following two questions: 1) Do genes released from sewage move into and persist in the natural microbial community without continued exposure to critical threshold concentrations of antibiotics; and 2) Are the critical threshold concentrations in the environment sufficiently high to maintain gut-derived AMR genes in the natural microbial community or select for them all on their own? In the proposed research we aim to answer these two key questions using four innovative experimental systems: 1) a small laboratory microfluidic system for the precise control and manipulation of microbial biofilms; 2) an in situ river mesocosm and 3) ex situ macrocosm which can also control and manipulate microbial biofilms under controlled conditions with the addition of antibiotics and/or antibiotic resistance genes; and finally 4) the use of the freshwater shrimp, Gammarus pulex, as an indicator species of environments where the reservoir of antibiotic resistance is elevated. In the case of the Gammarus, we will study the microorganisms that live within this shrimp and determine if these microbes acquire similar antibiotic resistance traits as those found in identically-exposed biofilms. Modern molecular techniques (i.e, metagenomes, plasmid metagenomes, qPCR, meta-transcriptomes), will be used to quantify treatment effects within biofilms and Gammarus. The data from these studies will be used to parameterise a mathematical/statistical model that will be designed for use by regulators, industry and academia to better predict and understand the risks posed by AMR in the environment.