Resequencing microarray for rapid detection & antimicrobial resistance profiling

用于快速检测的重测序微阵列

• 批准号: 7324637
• 负责人: Susan Veronica Lynch
• 金额: $ 72.42万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7324637
• 关键词: Accounting; Acinetobacter baumannii; Adverse effects; Algorithms; Antibiotic Resistance; Antibiotics; Antimicrobial Resistance; Archaea; Automobile Driving; Bacteria; Bacterial Antibiotic Resistance; Bacterial DNA; Bacterial Infections; Bioinformatics; Biological Assay; Biological Markers; Blinded; Blood; Blood specimen; Cessation of life; Clinical; Clinical Research; Clinical Trials; Clostridium difficile; Collection; Communities; Compatible; Computer software; Condition; Critical Illness; Custom; Cytotoxin; DNA; DNA Resequencing; DNA amplification; Data; Databases; Detection; Development; Devices; Diagnostic; Diagnostic tests; Disease Outbreaks; Empiricism; Ensure; Enterobacter aerogenes bacterium; Enterobacter cloacae; Epidemiologic Studies; Evaluation; Expenditure; Face; Family; Feces; Future; Generations; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genotype; Goals; Gold; Harvest; Healthcare; Hospitalization; Hour; Human; Infection; Klebsiella; Klebsiella oxytoca; Klebsiella pneumonia bacterium; Label; Laboratories; Laboratory Research; Lead; Longevity; Masks; Mediating; Methods; Microarray Analysis; Microbial Drug Resistance; Microbiological Techniques; Mind; Molecular; Multicenter Studies; Names; Nucleic Acids; Nucleotides; Numbers; Oligonucleotides; Organism; Outcome; Patient Care; Patients; Pattern; Pharmaceutical Preparations; Pharmacists; Phase; Phenotype; Physicians; Polymerase Chain Reaction; Positioning Attribute; Preparation; Principal Investigator; Probability; Procedures; Process; Proteus mirabilis; Protocols documentation; Pseudomonas aeruginosa; Publishing; Purpose; RNA; Range; Regulator Genes; Reproducibility; Research; Research Design; Research Personnel; Resistance; Resistance profile; Ribosomal RNA; Robotics; Sampling; Scanning; Science; Scientist; Score; Screening procedure; Sensitivity and Specificity; Sequence Alignment; Serratia marcescens; Single Nucleotide Polymorphism; Specificity; Speed; Staging; Staining method; Stains; Standards of Weights and Measures; Stenotrophomonas; System; Technology; Testing; Time; Uncertainty; United States; Validation; Variant; Yang; antimicrobial; base; clinical application; cost; cytotoxicity; design; genome sequencing; microbial; multidisciplinary; novel; open source; pathogen; pathogenic bacteria; promoter; rRNA Genes; rapid detection; response; sample collection; tool

DESCRIPTION (provided by applicant): The long-term objective of this application is to create and validate a diagnostic tool (a resequencing microarray), that will permit rapid detection of nosocomial pathogens, Clostridium difficile, Pseudomonas aeruginosa, Acinetobacterspp., Enterobacterspp., Klebsiella spp., Serratia marcescens, Proteus mirabilis and Stenotrophomonas maltophila as well as their antibiotic resistance gene polymorphisms within 8 hours. The team of investigators involved in this application represents a multidisciplinary group of scientists involved in the molecular detection of bacteria in environmental and clinical samples. Drs. Andersen, Brodie and DeSantis of LBNL have created a number of microarrays e.g. the 16S rRNA PhyloChip that detects all known bacteria and archaea. Drs. Lynch and Flanagan of UCSF have previously used the PhyloChip to describe bacterial community dynamics associated with antimicrobial resistant pathogen proliferation in clinical samples from critically ill patients during antimicrobial administration. Drs. Wiener-Kronish and Miller of UCSF are physician-scientists. Drs. MacDougall and Yang of UCSF are antimicrobial pharmacists, who will obtain clinical samples for testing and validation. Dr. Foxall will bring the industrial expertise of Affymetrix, world leaders in microarray development, to make the proposed tool a clinical device based on the latest state-of-the-science technology. Dr. Segal of UCSF is a statistician and bioinformatics expert with particular expertise in microarray analysis. The proposed process involves selection of regions of genetic variation in biomarkers and antibiotic resistance determinants for pathogen identification and antibiotic resistance phenotype prediction; design and fabrication of an Affymetrix platform resequencing microarray, to be named the Bacterial Antibiotic Resistance GeneChip or BARChip which will interrogate each nucleotide position at the discriminatory loci selected; optimization of target preparation and hybridization processes to decrease time to result; clinical sample collection for final resequencing array validation in a CLIA certified laboratory followed by blinded validation of the BARChip with these prospectively collected clinical samples in the final year of the proposed project. This application would lead to the development of a diagnostic test that could rapidly determine whether a patient has a bacterial infection. The test would permit physicians to rapidly choose appropriate antibiotic(s) to treat the bacterial infection; this tool will also identify the strain of bacteria infecting patients, so outbreaks of infection could be rapidly identified and controlled.

描述(由申请人提供)： 这项应用的长期目标是创建和验证一种诊断工具(重新测序微阵列)，该工具将允许在8小时内快速检测院内病原体、艰难梭菌、铜绿假单胞菌、不动杆菌、肠杆菌、克雷伯氏菌、粘质沙雷氏菌、奇异变形杆菌和嗜麦芽窄食单胞菌及其抗生素耐药性基因多态性。参与这项应用的研究团队代表了一个多学科的科学家小组，他们参与了环境和临床样本中细菌的分子检测。LBNL的Andersen、Brodie和DeSantis博士已经创建了许多微阵列，例如16S rRNA基因芯片，它可以检测所有已知的细菌和古菌。加州大学旧金山分校的Lynch和Flanagan博士之前曾使用PhyloChip描述了在抗菌素治疗期间危重患者的临床样本中与抗菌素耐药病原体增殖相关的细菌群落动态。加州大学旧金山分校的维纳-克洛尼什博士和米勒博士是内科科学家。加州大学旧金山分校的麦克杜格尔博士和杨博士是抗菌药剂师，他们将获得临床样本进行测试和验证。福克索尔博士将带来世界领先的微阵列开发公司Affymetrix的行业专业知识，使拟议中的工具成为基于最新科学技术的临床设备。加州大学旧金山分校的西格尔博士是一位统计学家和生物信息学专家，在微阵列分析方面拥有特殊的专业知识。拟议的流程包括：选择生物标记物和抗生素耐药性决定因素的遗传变异区域，用于病原体鉴定和抗生素耐药性表型预测；设计和制造Affymetrix平台重测序微阵列，命名为细菌抗生素耐药性基因芯片或BAR芯片，它将询问所选识别基因座上的每个核苷酸位置；优化靶点制备和杂交过程，以缩短得出结果的时间；在CLIA认证的实验室收集用于最终重测序阵列验证的临床样本，然后使用这些预期在拟议项目的最后一年收集的临床样本对BAR芯片进行盲法验证。这一应用将导致一种诊断测试的开发，这种测试可以快速确定患者是否有细菌感染。该检测将使医生能够快速选择合适的抗生素(S)来治疗细菌感染；该工具还将识别感染患者的细菌菌株，因此可以快速识别和控制感染的爆发。