Microbiome Based Biomarkers of Wound Healing

摘要 糖尿病足溃疡（DFU）每年影响超过200万美国人，导致超过13万例截肢 年，并与高死亡率有关。到目前为止，还没有单一的DFU感染因子 被认为是愈合结果的良好标志。这可能是因为DFU是一个多样化的社区， 微生物（即，伤口微生物组）。在社区一级分析的伤口微生物组是有希望的 伤口愈合结果的预测因子。我们已经证明，伤口持续超过12周， 以及微生物群落中混合群体厌氧细菌的持久比例。另外我们 发现在持续性和截肢伤口中厌氧转录活性显著增加，即使是从 通过传统的基于16 S rRNA的基因测序鉴定为低丰度的物种。这表明 微生物转录，特别是来自厌氧菌的转录，是有希望的伤口愈合的生物标志物， 糖尿病患者 拟议的项目将确定微生物生物标志物，可用作预测和监测工具， DFU伤口愈合。我们假设使用RNA而不是DNA将提供更好的伤口快照 环境和更敏感的生物标志物：特别是厌氧菌的比例和转录活性 在伤口微生物组内的微生物可以用作伤口愈合结果的预测因子。使用RNAseq测量 DFU微生物组的元转录组，我们将利用机器学习方法的进步， 证明伤口微生物组的厌氧组分作为生物标志物的能力， 伤口愈合我们积极评估了最佳的样本收集技术和方法， 检测，确定溃疡床的简单拭子足以表征后转录组， 便于临床实施。我们将开发一种多重RT-qPCR检测方法，用于候选人组 我们鉴定和验证测定的灵敏度、特异性、准确性和精确度。我们将 与糖尿病足联盟指导委员会和数据协调中心密切合作， 我们的生物标志物在一个多中心试验与DFC。我们的目标是开发一种多重生物标志物检测， DFU微生物组和组织微环境中发生的复杂相互作用。它将使用一个简单的 拭子的溃疡床，依赖于客观的测量，并旨在预测愈合轨迹在早期 在临床过程中。

Abstract Diabetic foot ulcers (DFU) impact over 2 million Americans annually, result in over 130,000 amputations each year, and are associated with high mortality rates. To date, there has been no single infectious agent of DFU identified as a good marker of healing outcome. This is likely because DFUs are host to a diverse community of microbes (i.e., the wound microbiome). Wound microbiomes analyzed at the community-level are promising predictors of wound healing outcomes. We have shown that wounds persisting beyond 12 weeks exhibit high and persistent proportions of mixed-population, anaerobic bacteria within their microbiomes. Additionally, we found a significant increase of anaerobic transcriptional activity in persistent and amputated wounds, even from species identified as being in low abundance by traditional 16S rRNA based gene sequencing. This suggests microbial transcription, and specifically from anaerobic bacteria, are promising biomarkers of wound healing in diabetic patients. The proposed project will identify microbial biomarkers that can be used as prognostic and monitoring tools for DFU wound healing. We hypothesize using RNA instead of DNA will provide a better snapshot of the wound environment and more sensitive biomarkers: specifically, the proportion and transcriptional activity of anaerobes within the wound microbiome can be used as predictors of wound healing outcomes. Using RNAseq to measure the metatranscriptome of the DFU microbiome, we will leverage advances in machine learning approaches to demonstrate the capacity of the anaerobic component of the wound microbiome to serve as a biomarker for wound healing. We have vigorously evaluated the optimal sample collection techniques and methods of detection, determining a simple swab of the ulcer bed is sufficient to characterize the metatranscriptome and will facilitate clinical implementation. We will develop a multiplexed RT-qPCR assay for the panel of candidate biomarker genes we identify and validate the assay sensitivity, specificity, accuracy and precision. We will work closely with the Diabetic Foot Consortium Steering Committee and Data Coordinating Center to test and validate our biomarkers in a multi-site trial with the DFC. Our goal is to develop a multiplexed biomarker assay integrating the complex interactions occurring within the DFU microbiome and tissue microenvironment. It will use a simple swab of the ulcer bed, rely on objective measurements, and is designed to predict healing trajectories at an early time in the clinical course.