NEC05839 Chicken or the Egg: Is AMR in the Environment Driven by Dissemination of Antibiotics or Antibiotic Resistance Genes?

环境中的抗生素耐药性（AMR）是由人类和动物尿液中释放到污水中并最终进入接收河流的抗生素驱动的。AMR也从人类和动物粪便中脱落的肠道细菌中释放出来。在这两种情况下，抗生素和含有AMR的肠道细菌通过污水释放到环境中。尽管抗生素和抗药性细菌不断释放到我们的河流中，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数量方面所起的相对作用。这是一个至关重要的知识空白，因为它阻碍了行业和政策制定者决定在何处花费我们的时间和资源，以降低这种“环境中的抗菌素耐药性”。污水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来保护自己免受这些化学物质的侵害，所有这些策略都具有被广泛归类为“抗性基因”的基因。因此，污水是寻找富含抗性基因的细菌的绝佳场所。已知这些基因中的许多是移动的，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在环境中驱动AMR的关键-有点像“先有鸡还是先有蛋”。“污水中抗生素的浓度是否足够高，足以选择环境中的耐药基因，或者耐药基因只是从肠道来源的细菌传播到本地环境微生物中？”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会在不持续暴露于临界阈值浓度的抗生素的情况下进入并持续存在于自然微生物群落中？2）环境中的临界阈值浓度是否足够高，以维持天然微生物群落中肠道来源的AMR基因，或者它们自己选择。在拟议的研究中，我们的目标是回答这两个关键问题，使用四个创新的实验系统：1）一个小型的实验室微流体系统，用于精确控制和操纵微生物生物膜; 2）原位河流围隔生态系统和3）异位宏观生态系统，也可以控制和操纵微生物生物膜在受控条件下添加抗生素和/或抗生素抗性基因;以及最后4）使用淡水虾，钩虾（Gammaruspulex），作为抗生素抗性库升高的环境的指示物种。在Gammarus的情况下，我们将研究生活在这种虾中的微生物，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。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、行业和学术界，以更好地预测和理解AMR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.