Identification of Biological Materials of Unknown Origin

来源不明的生物材料的鉴定

• 批准号: 7031388
• 负责人: Khalid Sayood
• 金额: $ 14.64万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-02-01 至 2011-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7031388
• 关键词: DNA; bacteria; bioterrorism /chemical warfare; motivation; nucleic acid sequence; sectioning; training

DESCRIPTION (provided by applicant): The applicant's long term goal is to understand and elucidate structure and organization within DNA sequences and uncover their relationship to biological functions. The objective of this application, which is a step toward the attainment of this long term goal, is to develop techniques for elucidating occult structural features in bacterial DNA which can be used for identification and differentiation of microbial organisms, including organisms whose genome has not been completely sequenced, using short fragments of DNA. A parallel goal is to achieve investigative independence as a computational biologist. The latter goal will be accomplished through coursework and training in the laboratories of Steven Hinrichs, M.D. The urgent need for rapid identification tests for biological materials has intensified because of the threat posed by bioterrorism. Rapid identification of both the fact and the mode of attack is essential for timely therapeutic intervention. The ability to identify bacteria based on short sequences of incomplete or possibly corrupt sequences allows for hazard detection, automation, and low cost distributed sensing capability. The identification techniques will be developed using three tools: the average mutual information (AMI) profile which reflects statistical relationships between bases along the DNA sequence, a cluster analysis technique developed by the applicant and co-workers which identifies genome specific trinucleotide clustering patterns, and a parsing technique for identification of polynucleotide sequences of interest. Components of the AMI profile which possess discriminatory capabilities will be identified by decomposing the profile and analyzing the coefficients using both supervised and unsupervised classification. The clustering strategy will be refined by correlating parameters in the technique with known biological behavior. Signature trinucleotide and polynucleotide clustering patterns will be identified for organisms of interest. The different classifications will be combined into a tree structured test for a model panel of bacteria of medical interest.

描述(由申请人提供)：申请人的长期目标是了解和阐明DNA序列中的结构和组织，并揭示它们与生物功能的关系。这项应用的目标是为了实现这一长期目标而迈出的一步，目的是开发技术来阐明细菌DNA中隐藏的结构特征，这种技术可用于鉴定和区分微生物，包括其基因组尚未完全测序的生物，使用DNA的短片段。一个平行的目标是作为一名计算生物学家实现调查独立性。后一项目标将通过在医学博士Steven Hinrichs的实验室进行课程学习和培训来实现。由于生物恐怖主义构成的威胁，对生物材料进行快速鉴定测试的迫切需要已经加强。迅速确定攻击的事实和方式对于及时的治疗干预至关重要。根据不完整或可能损坏的短序列识别细菌的能力允许危险检测、自动化和低成本的分布式传感能力。鉴定技术将使用三种工具开发：反映DNA序列上碱基之间统计关系的平均相互信息(AMI)图谱，由申请人和同事开发的鉴定基因组特定三核苷酸聚集型的聚类分析技术，以及用于鉴定感兴趣的多核苷酸序列的解析技术。将通过使用监督和非监督分类对轮廓进行分解并分析系数来识别具有区分能力的AMI轮廓的分量。通过将技术中的参数与已知的生物行为相关联，将改进聚类策略。将为感兴趣的生物确定标志性的三核苷酸和多核苷酸聚集型。不同的分类将被组合成一个树状结构的测试，用于医学上有价值的细菌的模型小组。