Microbiome Based Biomarkers of Wound Healing

基于微生物组的伤口愈合生物标志物

• 批准号: 10517803
• 负责人: Meghan Brennan
• 金额: $ 52.72万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-04 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10517803
• 关键词: 16S ribosomal RNA sequencing; Address; Agreement; American; Amputation; Anaerobic Bacteria; Antibiotic Resistance; Bacteria; Beds; Biological Assay; Biological Markers; Candidate Disease Gene; Cessation of life; Classification; Clinical; Clinical Data; Clinical Trials; Collection; Communities; Complex; Complications of Diabetes Mellitus; Cross-Sectional Studies; DNA; Data; Data Coordinating Center; Detection; Development; Diabetic Foot; Diabetic Foot Ulcer; Engineering; Exhibits; Genes; Genetic Transcription; Goals; Impaired healing; Infectious Agent; Limb Salvage; Limb structure; Longitudinal Studies; Lower Extremity; Machine Learning; Measurement; Measures; Metabolic; Metagenomics; Modeling; Molecular; Monitor; Operating Rooms; Outcome; Pathway interactions; Patients; Phase; Population; Problem Solving; Process; Public Health; Publishing; RNA; Resolution; Ribosomal RNA; Risk; Sampling; Sensitivity and Specificity; Shotguns; Site; Skin; Swab; Taxonomy; Techniques; Testing; Therapeutic; Time; Tissue Sample; Tissues; Ulcer; United States National Institutes of Health; Virulence; Virulence Factors; Visit; Work; base; biomarker panel; candidate marker; clinical implementation; cohort; design; detection method; diabetic patient; diagnostic assay; healing; machine learning algorithm; metatranscriptome; metatranscriptomics; microbial; microbial community; microbiome; microbiome analysis; microbiome research; molecular diagnostics; mortality; multi-site trial; multiplex assay; non-healing wounds; novel; novel therapeutics; pathogen; predictive marker; preservation; prognostic; prospective; sample collection; specific biomarkers; targeted biomarker; tool; transcriptome sequencing; treatment response; wound; wound environment; wound healing

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.

抽象的 糖尿病足溃疡（DFU）每年影响超过200万美国人，每年都有超过130,000次截肢 年，与高死亡率有关。迄今为止，还没有DFU的单一传染剂 被确定为康复结果的良好标志。这可能是因为DFU是一个主持人的 微生物（即伤口微生物组）。在社区级别分析的伤口微生物组很有希望 伤口愈合结果的预测因素。我们已经表明，超过12周的伤口持续很高 以及其微生物中混合群，厌氧细菌的持续比例。另外，我们 发现在持续和截肢伤口中的厌氧转录活性显着增加，即使是从 传统的16S基因基因测序鉴定为低丰度的物种。这暗示着 微生物转录，特别是来自厌氧菌的细菌，是伤口愈合的有希望的生物标志物 糖尿病患者。 拟议的项目将确定可用作预后和监视工具的微生物生物标志物 DFU伤口愈合。我们假设使用RNA代替DNA将提供更好的伤口快照 环境和更敏感的生物标志物：具体来说，厌氧菌的比例和转录活性 在伤口中，微生物组可以用作伤口愈合结果的预测指标。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成分的能力作为生物标志物 伤口愈合。我们已经大力评估了最佳样本收集技术和方法 检测，确定一个简单的溃疡床的拭子足以表征元转录组，并将 促进临床实施。我们将为候选人面板开发一个多路复用的RT-QPCR分析 生物标志物基因我们识别并验证测定敏感性，特异性，准确性和精度。我们将工作 与糖尿病足联盟指导委员会和数据协调中心密切相关，以测试和验证 我们的生物标志物在DFC的多站点试验中。我们的目标是开发多重生物标志物测定 复杂的相互作用发生在DFU微生物组和组织微环境中。它将使用一个简单的 拭子的溃疡床，依靠客观测量，旨在预测早期的愈合轨迹 临床过程中的时间。