Surgical site infections and the microbiome: Understanding the pathogenesis of surgical site infections

项目摘要 手术部位感染(SSI)是最常见的医院获得性感染，其发生率为2-11倍。 死亡率增加，住院天数增加9.7天，每年花费35-100亿美元。 有无数的技术被实施来降低SSI的比率，重点是减少皮肤病原体。 然而，如果病原菌来自胃肠道而不是皮肤菌群，这些预防措施 干预措施可能不足以减少或消除SSI。对细菌来源缺乏了解 病原体限制了我们个性化预防SSI方法的能力。 有越来越多的证据将宿主微生物组与SSI发育联系起来。现有证据 提示皮肤和胃肠道微生物区系多样性可能更能预测SSI的发展。 更传统的SSI预测指标。这些微生物群代表着针对皮肤和胃肠道的有意义的机会 将生态失调作为预防SSI的一种策略。 这项研究的总体目标是通过针对特定人群的干预措施来预防SSIS 病原菌来源和优化寄主微生物环境。中心假设是，生物多样性 皮肤和伤口微生物区系的变化可以预测SSI的发病机制。该假说将通过两个步骤进行检验 明确的目标。1)首先，这项研究旨在确定切口处微生物群落的多样性是否 通过测量微生物群落的多样性和组成与SSI的发展相关 手术中不同时间点的切面微生物群。样本将从300名患者中收集 正在接受开放式胃肠道手术。将进行病例对照研究，比较使用16S RNA的阿尔法多样性 30名SSI患者与30名年龄、性别、诊断和创伤类别的患者进行了测序比较。 未发生SSI的匹配对照组患者。2)下一步，本研究旨在确定致病菌株是否 引起SSI的细菌在手术时存在于皮肤或胃肠道微生物区系中。细菌的品系 从20名发生SSI的患者中分离出来的(从AIM 1收集的样本中)将使用以下方法进行鉴定 鸟枪式元基因组学。接下来，将使用鸟枪式元基因组学来确定该特定菌株是否 手术前皮肤和/或胃肠道内有细菌存在。 这是一项创新性和协作性研究，评估了SSI和微生物组之间的联系。 由于SSI是一个全球关注的问题，这些发现具有全球影响和影响。由此产生的结果是 研究将提供SSI发病机制的重要细节，以及病原体是否 在手术时出现在皮肤或胃肠道。这些结果将用于指导干预性研究 以影响SSI发展的可修改微生物区系特征为目标。这项研究是必要的第一步 在进行前瞻性、干预性临床试验之前，这些试验可以被设计成强调靶向SSI 以微生物群落为基础的预防。

Project Summary Surgical sites infections (SSIs) are the most common hospital-acquired infection and result in 2 to 11-fold increased mortality, an additional 9.7 days of hospital stay, and annual costs of 3.5 – 10 billion U.S. Dollars. There are myriad techniques implemented to reduce rates of SSIs focusing on reducing skin pathogens. However, if pathogenic bacteria arise from the gastrointestinal (GI) tract rather than skin flora, these preventive interventions may be inadequate to reduce or eliminate SSIs. A lack of knowledge of the source of bacterial pathogens limits our ability to personalize approaches to SSI prevention. There is a growing body of evidence linking the host microbiome to SSI development. Current evidence suggests that skin and GI microbiota diversity may be more predictive of SSI development compared with more traditional SSI predictors. These microbiomes represent a meaningful opportunity to target skin and GI tract dysbiosis as a strategy to prevent SSI. The overarching goal of this research aims to prevent SSIs through interventions targeting the specific source of pathogens and optimizing the host microbial environment. The central hypothesis is that the diversity of the skin and incisional microbiota is predictive of SSI pathogenesis. The hypothesis will be tested through 2 specific aims. 1) First, the study aims to determine if diversity in microbial communities at the incision site is associated with development of SSI by measuring the diversity and microbial community composition of the incisional microbiome at different time points during surgery. Samples will be collected from 300 patients undergoing open GI surgery. A case-control study will be performed comparing alpha diversity using 16S RNA sequencing in 30 patients who develop SSI compared with 30 age-, sex-, diagnosis-, and wound class- matched control patients who do not develop SSI. 2) Next, the study aims to determine if pathogenic strains of bacteria causing SSI are present in the skin or GI microbiota at the time of operation. The strain of bacteria isolated from a subset of 20 patients who develop SSI (from samples collected in Aim 1) will be identified using shotgun metagenomics. Next, shotgun metagenomics will be used to determine whether that specific strain of bacteria was present in the skin and/or GI tract immediately prior to operation. This is innovative and collaborative research assessing the association between SSIs and the microbiome. As SSIs are a global concern, these findings with have global implications and impact. The results from this study will provide important mechanistic details regarding SSI pathogenesis and whether pathogens are present at the skin or GI tract at the time of operation. These results will be used to guide interventional studies targeting modifiable microbiota features that influence SSI development. This study is the first necessary step before performing prospective, interventional clinical trials which can be designed to underscore targeted SSI prevention based on microbial communities.