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Development of standardized resources for characterization of the resident ocular surface microbiome.

Development of standardized resources for characterization of the resident ocular surface microbiome.
开发用于表征驻留眼表微生物组的标准化资源。
批准号:
10661354
负责人:
Laura Ensign
金额:
$63.58万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-07-01 至 2026-06-30

项目摘要

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中文摘要
翻译
项目摘要 身体暴露的上皮表面,包括皮肤、肠道、女性生殖道和气道, 由有助于体内平衡和疾病的微生物定殖。虽然当地的微生物 在这些部位中的许多部位被广泛表征,眼表面微生物组相对 替补演员宏基因组测序方法的使用有助于超越靶向 培养方法,以更充分地表征标本中存在的生物体的广度。但 眼表面的相对微生物生物量远低于其它粘膜表面如肠。 低微生物生物量标本的宏基因组学表征提出了许多挑战, 污染不仅发生在采样过程中和环境本身, 实验室处理方法。因此,缺乏协议标准化和遗漏关键控件 对于污染源的解释限制了跨研究比较的解释和可能性。解决 为了应对这些挑战,我们组建了一个大型多学科专家团队,主题包括:(i) 开发标准化方案和利用宏基因组的诊断测试的临床验证 低生物量生物样本的测序,(ii)开发开源宏基因组分析工具,(iii) 在大量不同患者人群中对眼表和外眼结果进行临床评估,以及 (iv)在严格的清洁准则下进行微生物的湿实验室表征。我们之前描述了使用 宏基因组测序,以检测石蜡包埋的脑活检中是否存在病原体 眼组织标本和脑脊液(CSF)。通过比较一系列的标本预处理和 处理方法和复杂的软件工具,我们能够优化方法, 微生物检测和最小化或去除污染。我们验证了我们的宏基因组测序, 分析方法的严格性所需的用作诊断测试。在这里,我们假设, 使用低微生物量眼标本的类似方法将有助于表征 健康眼表微生物组。在目标1中,我们将比较样本处理方法并验证 我们的分析方法在目标2中,我们将比较标本采集方法,包括采集 材料和程序。然后,我们将使用我们优化的标本采集和处理方法, 纵向采集眼部标本,用于表征微生物的持久性。在目标3中,我们将确定一个 具有持久性和/或独特微生物的参与者子集,以采集额外标本进行验证 活性的组成和表征。研究完成后,我们将为 健康眼表微生物组的表征和理解,以及开发的方案, 分析工具和数据集,将公开提供。
英文摘要
PROJECT SUMMARY The exposed epithelial surfaces of the body, including the skin, gut, female reproductive tract, and airways, are colonized by microorganisms that contribute to homeostasis and disease. While the resident microbiota has been extensively characterized in many of these sites, the ocular surface microbiome is relatively understudied. The use of metagenomic sequencing approaches has facilitated moving beyond targeted culturing approaches to more fully characterize the breadth of organisms present in a specimen. However, the relative microbial biomass at the ocular surface is much lower than other mucosal surfaces, such as the gut. Metagenomic characterization of low microbial biomass specimens presents numerous challenges, as sources of contamination not only arise during the sampling procedure and from the environment itself, but even from laboratory processing methods. As a result, the lack of protocol standardization and omission of key controls for sources of contamination limits the interpretation and potential for comparison across studies. To address these challenges, we have assembled a large multidisciplinary team of experts in topics including (i) development of standardized protocols and clinical validation of diagnostic tests utilizing metagenomic sequencing for low biomass biospecimens, (ii) development of open source metagenome analysis tools, (iii) clinical assessment of ocular surface and external eye findings among a large, diverse patient population, and (iv) wet lab characterization of microbes under strict cleanliness guidelines. We previously described the use of metagenomic sequencing to detect the presence of pathogens in biopsies from the brain, paraffin embedded ocular tissue specimens, and cerebral spinal fluid (CSF). By comparing a range of specimen pre-treatment and processing approaches and sophisticated software tools, we were able to optimize the methods to maximize organism detection and minimize or remove contamination. We validated our metagenomic sequencing and analytical approaches to the rigor required for use as a diagnostic test. Here, we hypothesize that following similar approaches with low microbial biomass ocular specimens will facilitate the characterization of the healthy ocular surface microbiome. In Aim 1, we will compare specimen processing approaches and validate our analytical methods. In Aim 2, we will compare specimen collection approaches, including collection materials and procedures. We will then use our optimized specimen collection and processing approaches to collect ocular specimens longitudinally for characterization of organism persistence. In Aim 3, we will identify a subset of participants with persistent and/or unique organisms to collect additional specimens for validation of composition and characterization of viability. Upon study completion, we will have contributed to the characterization and understanding of the healthy ocular surface microbiome, and developed protocols, analytical tools, and datasets that will be made publicly available.
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