The use of next generation sequencing to measure the effects of antibiotics on resistance in the host microbiota

抗菌素耐药性在全球范围内不断增加，导致更严重和更难以治疗的感染，其严重程度足以使首席医疗官将其列入国家风险登记册。我们面临的未来是，感染变得无法治疗，以前的常规程序，如髋关节置换和化疗，变得风险太高，无法执行。在引起严重感染的细菌中，以及我们肠道中的“好”细菌中，耐药性都在增加，这些细菌构成了我们“微生物组”的一部分-微生物群落共享我们的身体，对日常功能至关重要。 肠道微生物组形成了一个耐药基因库，这些耐药基因可以在不同种类的细菌（包括致病菌株）之间传播，并使它们也产生耐药性。已经表明，肠道细菌的耐药性与发展耐药性感染的可能性增加有关。耐药细菌可以从食物来源（在养殖肉类和水产养殖中抗生素使用率高）、耐药流行率高的国家（主要是低资源国家）和医疗机构获得。通过使用抗生素治疗感染，我们正在选择耐药微生物并增加抗生素耐药性。已经表明，抗生素的使用与人口水平上的耐药性相关，基于此，人们认为通过减少抗生素的总体使用，我们可以减少耐药性。然而，减少抗生素的使用必须在安全的情况下实现，并且不会使患者因治疗不足而面临过度的感染风险，目前还没有强有力的证据表明以这种方式减少抗生素的使用可以降低耐药性。该项目的长期目标是开发能够减少耐药性发展的抗生素治疗策略。要做到这一点，我们需要能够测量和比较特定抗生素增加耐药性的程度。我们还需要能够了解导致耐药性的其他因素。肠道细菌大量存在于粪便样本中。由于DNA测序技术的快速发展，我们能够通过从粪便样本中提取细菌DNA并在几天内对其进行测序来测量这些细菌的耐药基因，而不是几个月。我建议开创和开发这种下一代测序（NGS）技术，以检测粪便样本中的抗生素耐药基因（测量肠道“耐药基因组”）。它已被用于检测来自人类微生物组项目的样本中的耐药性，并且耐药性模式显示出遵循全国范围的抗生素使用。我将用它来评估导致肠道细菌耐药性增加的因素，试图找出这种耐药性是从哪里获得的（食物，旅行，医疗机构）。我还将用它来研究先前抗生素使用与耐药性之间的关联，包括递送方式-在小鼠模型中有证据表明，与静脉注射相同剂量相比，口服抗生素可能会增加肠道的耐药性。然后，我将通过招募将接受抗生素治疗的患者并分析多个粪便样本来观察抗生素的动态效应，以确定耐药性是否恢复到以前的水平或保持不变。在这个项目中，我的目标是确定哪些抗生素策略导致肠道中抗生素耐药性的选择最少。临床医生将使用这些信息来选择抗生素策略，以进行临床试验，以显示耐药性的降低，而不会产生治疗不足的感染风险，并帮助决定使用哪种抗生素，以最大限度地降低患者未来耐药感染的风险。

Antimicrobial resistance is increasing worldwide, causing more serious and difficult to treat infections, and is of sufficient severity that the Chief Medical Officer has tabled it to be added to the national risk register. We face a future where infections become untreatable and previously routine procedures such as hip replacements and chemotherapy become too high risk to perform. Resistance is increasing both in the bacteria causing serious infection, but also in the 'good' bacteria in our gut which form part of our 'microbiome' - the community of microorganisms which share our body and are essential for daily function. The gut microbiome forms a reservoir of resistance genes which can be transmitted between different species of bacteria - including disease-causing strains, and cause them to become resistant too. It has been shown that resistance in the gut bacteria is associated with an increased likelihood of developing a resistant infection. Resistant bacteria can be acquired- from food sources (where there is high antibiotic use in farmed meat and aquaculture) from countries of high resistance prevalence (predominantly low-resource countries), and from healthcare institutions. By using antibiotics to treat infection, we are selecting for resistant organisms and increasing antimicrobial resistance.It has been shown that antibiotic use correlates with resistance on a population level, and based on this it is thought that by reducing overall antibiotic use we can reduce resistance. However reduction in antibiotic use has to be achieved safely and without putting patients at undue risk from undertreated infection, and there is not yet robust evidence that a reduction in antibiotic use in this way can provide a reduction in resistance.The long term aim of the project is to develop antibiotic treatment strategies able to reduce the development of resistance. To do this, we need to be able to measure and compare how much a particular antibiotic increases resistance. We also need to be able to understand what other factors lead to resistance. The bacteria colonising the gut are present in large numbers in faecal samples. Due to rapid advances in DNA sequencing technology we are able to measure resistance genes these bacteria by extracting bacterial DNA from faecal samples, and sequencing it in days, rather than months. I propose to pioneer and develop this Next-Generation Sequencing (NGS) technology to detect antibiotic resistance genes in faecal samples (measuring the gut ' resistome'). It has already been used to detect resistance in samples from the Human Microbiome Project, and the pattern of resistance was shown to follow country-wide antibiotic use. I will use it to assess the factors which lead to increased resistance in the gut bacteria, to try and find out where this resistance is being acquired from (food, travel, healthcare institutions). I will also use it to study the association between prior antibiotic use and resistance, including mode of delivery - there is evidence in mouse models that giving antibiotics orally may increase resistance in the gut compared to giving the same dose intravenously. I will then look at the dynamic effect of antibiotics by recruiting patients who will receive antibiotic therapy and analysing multiple faecal samples to see whether resistance returns to prior levels or is maintained. In this project I aim to identify which antibiotic strategies cause the least selection for antimicrobial resistance in the gut. This information will be used by clinicians to choose antibiotic strategies to take to clinical trials to show a reduction in resistance without risking undertreating infection, and to help decide which antibiotics to use to minimise the risk of future resistant infection to patients.