Volatile Metabolite-Based Detection of Clostridium difficile Infection

基于挥发性代谢物的艰难梭菌感染检测

• 批准号: 9088345
• 负责人: Sophia Koo
• 金额: $ 22.19万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9088345
• 关键词: Academic Medical Centers; Address; Air; Analytical Chemistry; Antibiotics; Antigens; Biological Assay; Canis familiaris; Cell Culture Techniques; Cessation of life; Characteristics; Clinical; Clostridium difficile; Complex; Coupled; Data; Data Set; Detection; Diagnosis; Diagnostic; Diagnostic Procedure; Diarrhea; Early treatment; Enrollment; Environment; Exotoxins; Exposure to; Feces; Gases; Health; Healthcare; Hospital Costs; Hospitals; Human; Incidence; Individual; Infection; Infection Control; Inflammatory Response; Injury; Inpatients; Institution; Intestines; Laboratories; Lead; Learning; Length of Stay; Life; Logistic Regressions; Machine Learning; Mass Fragmentography; Measures; Mediating; Metabolic; Methods; Microarray Analysis; Modeling; Nucleic Acid Amplification Tests; Odors; Patients; Performance; Pilot Projects; Proliferating; Provider; Pseudomembranous Colitis; Reference Standards; Research; Resistance; Sampling; Septic Shock; Severities; Smell Perception; Specimen; Symptoms; System; Techniques; Test Result; Testing; Toxic Megacolon; Toxin; Training; Tube; accurate diagnosis; air sampling; antimicrobial; base; cytotoxicity; design; forest; gut microbiome; innovation; learning strategy; metabolome; methicillin resistant Staphylococcus aureus; microbiome; mortality; novel; novel strategies; point of care; sample collection; sensor; tertiary care; transmission process; unnecessary treatment

 DESCRIPTION (provided by applicant): Clostridium difficile infection (CDI) is a major cause of nosocomial diarrhea and mortality worldwide, increasing dramatically in incidence and severity over the past decade and rivaling or exceeding methicillin-resistant Staphylococcus aureus as the most common healthcare-associated infection in the US. A critical barrier to reducing the nosocomial spread of CDI is the delay in timely identification of CDI cases, with subsequent delays in initiation of appropriate antimicrobial therapy and implementation of contact precautions and isolation measures to reduce horizontal CDI transmission. Despite advances in rapid laboratory-based CDI testing, there are still delays of 2-5 days between the onset of clinical symptoms and stool sampling and another 0.5-3.5 days between sample collection and actionable test results. Anticipating a delay in obtaining diagnostic results, many providers prescribe CDI antimicrobial therapy empirically, resulting in frequent and unnecessary treatment of patients who ultimately test negative for CDI. There is clearly an unmet need for diagnostic methods that can reduce this interval between onset of clinical symptoms and accurate identification of CDI. To address this unmet need, we propose a novel approach to CDI diagnosis based on detection of the volatile metabolome of the altered CDI microbiome. C. difficile flourishes in the antibiotic- disrupted intestinal microbiome and emits a distinctive odo detectable by human and canine olfaction. In a pilot study, we assessed the volatile metabolome of stool specimens from patients with suspected CDI using analytical chemistry techniques and discerned major differences in the stool volatome of patients with and without CDI. We propose two aims executed in parallel, to test the hypothesis that the altered CDI intestinal microbiome has a unique volatile metabolite profile, distinct from the profile of patiens with other causes of antibiotic-associated diarrhea, which can be used to identify patients with CDI in the hospital setting. Using thermal desorption GC-MS/MS to capture and identify these trace volatile metabolites and supervised learning methods - support vector machines, prediction analysis for microarray analysis, and random forests - to analyze this high-dimensional data matrix, we will deconvolute the complex volatome of CDI, (1) identifying the characteristic volatile metabolite profile of stool samples from hospitalized patients with CDI, compared to patients with other antibiotic-associated diarrhea, and (2) defining the CDI volatile metabolite profile in ambient air samples from the inpatient environment of patients with CDI, compared to patients with other antibiotic-associated diarrhea. The ultimate objective of this research is to derive and validate the volatile metabolic signature of CDI in stool samples and in the patient's environment, laying the groundwork for a novel CDI assay that can be coupled to a point-of-care gas sensor system for the bedside identification of CDI, reducing delays in diagnosis and decreasing nosocomial transmission of this common, highly morbid, and life- threatening infection.

 描述（由申请方提供）：艰难梭菌感染（CDI）是全球医院内腹泻和死亡的主要原因，在过去十年中发病率和严重程度急剧增加，与耐甲氧西林金黄色葡萄球菌相当或超过耐甲氧西林金黄色葡萄球菌，成为美国最常见的医疗保健相关感染。减少CDI医院传播的一个关键障碍是延迟及时识别CDI病例，随后延迟启动适当的抗菌治疗和实施接触预防措施和隔离措施，以减少CDI的水平传播。尽管基于实验室的快速CDI检测取得了进展，但在临床症状发作和粪便采样之间仍有2-5天的延迟，在样本采集和可操作的检测结果之间还有0.5-3.5天的延迟。由于预期会延迟获得诊断结果，许多提供者凭经验开具CDI抗菌治疗处方，导致对最终检测为CDI阴性的患者进行频繁和不必要的治疗。显然，对于可以缩短临床症状发作和准确识别CDI之间的间隔的诊断方法存在未满足的需求。为了解决这一未满足的需求，我们提出了一种基于检测改变的CDI微生物组的挥发性代谢组的CDI诊断新方法。C.艰难梭菌寄生在被抗生素破坏的肠道微生物组中，并发出人类和犬嗅觉可检测到的独特气味。在一项初步研究中，我们使用分析化学技术评估了疑似CDI患者粪便标本的挥发性代谢物组，并发现了有和无CDI患者粪便挥发性代谢物组的主要差异。我们提出了两个平行执行的目标，以检验以下假设：改变的CDI肠道微生物组具有独特的挥发性代谢产物谱，与其他原因的腹泻相关性腹泻患者的谱不同，这可用于在医院环境中识别CDI患者。使用热解吸GC-MS/MS来捕获和鉴定这些痕量挥发性代谢物，并使用监督学习方法-支持向量机、微阵列分析的预测分析和随机森林-来分析该高维数据矩阵，我们将对CDI的复杂挥发性组进行解卷积，（1）鉴定来自患有CDI的住院患者的粪便样品的特征性挥发性代谢物谱，与患有其他腹泻相关性腹泻的患者相比，以及（2）与患有其他腹泻相关性腹泻的患者相比，定义来自患有CDI的患者的住院环境的环境空气样品中的CDI挥发性代谢物谱。本研究的最终目的是推导和验证粪便样品和患者环境中CDI的挥发性代谢特征，为新型CDI测定奠定基础，该测定可与床旁识别CDI的即时气体传感器系统偶联，减少诊断延迟并减少这种常见、高度病态和危及生命的感染的医院传播。