Canada_IPAP Antimicrobial-resistant Enterococcus faecium in the One Health context in the UK and Canada

抗菌素耐药性是跨越一个健康连续体(人、动物和环境)的最大公共健康威胁之一。抗生素对公共卫生具有非常重要的价值，全世界每天都在使用抗生素，以挽救和减轻数百万人和动物的痛苦。然而，它们的广泛和往往不受控制的使用已导致具有医疗和兽医重要性的细菌的耐药性在全球范围内传播到前所未有的水平。这威胁着我们行医的方式和我们照顾病情最重的病人的能力，包括那些需要器官移植或癌症化疗等救命治疗的人，以及那些在重症监护病房的人。抗生素耐药性现已被世界卫生组织确认为对人类健康的最大威胁之一，并在国家和全球的医疗、兽医和非医学组织中日益流行。粪肠球菌是一种在人和动物的肠道中无害携带的细菌，已成为医院重症患者和免疫功能严重受损患者感染的主要原因。它有积累和传播多种抗生素耐药性决定因素的倾向。我们之前使用一种名为短读全基因组测序(WGS)的细菌DNA指纹技术确定了在医院引起感染的粪肠球菌属于不同于在牲畜中发现的菌株。此外，我们还发现在两个储存库中占主导地位的是不同类型的抗生素耐药性基因。然而，我们也发现了相同的耐药基因的例子，包括对人类医学中重要的抗生素类别的耐药性。短读的WGS在试图重建负责抗生素耐药性传播的传递单位的分层水平时存在局限性，这些传递单位的范围从整个细菌菌株到连续较小的可移动遗传元件层，即质粒和转座子，一直到基因水平。为了破译这种“俄罗斯娃娃”模型，需要一种不同的技术，称为长读WGS。在这里，我们建议仔细选择长时间阅读WGS的分离株，以使我们能够量化和了解人和动物菌株之间共享抗生素耐药性基因的架构背景。抗生素敏感性测试是世界各地实验室每天使用的一种技术，以确定抗生素是否仍然有效地治疗感兴趣的细菌菌株(即确保菌株没有产生耐药性)。抗生素的耐药性是由基因变化介导的，因此全基因组测序已成为一项有吸引力的技术，可以表征导致耐药性的所有已知基因变化，并根据细菌DNA预测抗生素是否仍然有效。然而，在采用WGS来指导抗生素处方之前，需要对控制抗生素耐药性的遗传学有一个完整的了解。我们之前的研究表明，WGS在预测大多数抗生素在粪肠球菌中的有效性方面非常好，除了对最具耐药性的菌株使用的3种最后手段：达托霉素、替格环素和利奈唑胺。在这里，我们的目标是通过产生更多的实验室测试和测序数据来纠正这一缺点，并应用最先进的种群基因组方法来改进预测。

Antimicrobial resistance is one of the greatest public health threats spanning the One Health continuum (humans, animals and the environment). Antibiotics are of invaluable public health importance and are used on a daily basis worldwide to save and ease the suffering of millions of human and animal lives. However, their extensive and often uncontrolled use has led to the global spread of resistance in bacteria of medical and veterinary importance to an unprecedented level. This is threatening the ways we practice medicine and our ability to care for the sickest patients including those in need of life-saving treatments such as organ transplantation or cancer chemotherapy, and those in intensive care units. Antibiotic resistance is now recognised by the WHO as one of the greatest threats to human health and is increasingly topical within medical, veterinary and lay organisations of national and global reach.Enterococcus faecium, a bacterium carried harmlessly in the gut of humans and animals, has emerged as a leading cause of infections in critically ill and severely immunocompromised patients in hospitals. It has a propensity to accumulate and disseminate multiple antibiotic resistance determinants. Our previous work using a bacterial DNA fingerprinting technique called short-read whole-genome sequencing (WGS) established that E. faecium causing infections in hospital belongs to distinct strains from those found in livestock. In addition, we found different types of antibiotic resistance genes predominating in the two reservoirs. However, we also found instances of identical resistance genes, including to classes of antibiotics that are important in human medicine. Short-read WGS has limitations when trying to reconstruct the hierarchical levels of transmission units responsible for the spread of antibiotic resistance, which range from the whole bacterial strains, to consecutively smaller layers of mobile genetic elements known as plasmids and transposons down to the gene level. In order to decipher this "Russian doll" model, a different technique known as long-read WGS is required. Here, we propose to carefully select isolates for long-read WGS to allow us to quantify and understand the architectural context of shared antibiotic resistance genes between human and animal strains of E. faecium. Antibiotic susceptibility testing is a technique used daily in laboratories around the world to establish if antibiotics are still effective at treating bacterial strains of interest (i.e. ensuring the strains have not developed resistance). Resistance to antibiotics is mediated by genetic changes, hence whole genome sequencing has emerged as an attractive technology to characterise the full repertoire of known genetic changes that cause resistance and predict from the bacterial DNA if antibiotics are still effective. However, a complete understanding of the genetics governing resistance to antibiotics is required before WGS can be adopted to inform antibiotic prescribing. Our previous research has shown that WGS is very good at predicting the effectiveness of most antibiotics in E.faecium, except for 3 last-resort antibiotics used against the most resistant strains: daptomycin, tigecycline and linezolid. Here, we aim to redress this shortcoming by generating additional laboratory tests and sequencing data and to apply state-of-the art population genomic methods to improve predictions.