BBSRC-NSF/BIO:Collaborative Research: genomeRxiv: a microbial whole-genome database and diagnostic marker design resource for classification, identification, and data sharing

BBSRC-NSF/BIO：合作研究：genomeRxiv：用于分类、识别和数据共享的微生物全基因组数据库和诊断标记设计资源

• 批准号: 2018911
• 负责人: Charles Brown
• 金额: $ 29.73万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018911&HistoricalAwards=false
• 关键词: BBSRC; NSF; BIO; Collaborative; Research

Although invisible to the human eye, microorganisms have immense impact on society and the environment. They keep soil healthy, cause disease, and give us tools like antibiotics to fight the diseases other microbes cause. Accurate and precise identification of microbes is thus essential for understanding microbiology in general, for diagnosis and treatment of diseases, and for maintaining a healthy society and a healthy environment. The DNA sequencing revolution allows us to read the genetic code of individual microbes, and use this for fast and accurate identification. However, we cannot do this without reference databases that precisely define classes of microorganisms, and associate them with their unique characteristics. We also need fast computer programs that can handle the large amounts of data involved and, to be most useful to the world, we need to allow anyone, anywhere to upload the genetic data for the microbes they find, and quickly get an accurate identification of their likely impact. Therefore, scientists will build genomeRxiv, a Web site and a database of hundreds of thousands of accurately catalogued and classified public genome sequences of bacteria and archaea. Building on existing work, a combination of fast and accurate algorithms will be employed for users to query the database. A unique feature will keep submitted genomes private, which will enable and stimulate networking and facilitate sharing of genome sequencing results among scientists across academia, industry, and government, leading to a more efficient, and economically stimulating, use of research funds. Automated design of diagnostic tools will facilitate detection and regulation of pathogens for biosafety and biosecurity and directly impact clinical and veterinary medicine, plant pathology, and the use of beneficial microbes in agriculture. The scientific community will be trained in the use of genomeRxiv, and undergraduate and graduate students of diverse backgrounds will receive education at the interface of biology and computer science.The number of sequenced genomes is increasing exponentially, but automated assignment of taxonomic identity is constrained by transfer of existing taxonomy. Up to ≈20% of the existing classifications are expected to be incorrect, and determined by historically contingent polyphasic tests that do not correspond to meaningful phylogenomic groupings identifiable at genome level. The continued incorrect and inaccurate assignment of taxonomic identities undermines our understanding of prokaryote evolution and diversity, as well as legislative efforts to regulate and monitor pathogens, which are reliant on accurate identification. Tools already developed by the PIs of this project will be improved and integrated into a new computational service called genomeRxiv, which aims to solve these problems. The existing LINbase Web server will serve as the basis for the new genomeRxiv service. The highly resolved Life Identification NumberTM (LINTM) classification framework of PIs Vinatzer and Heath will be combined with the speed and computational efficiency of the sourmash software developed by PI Brown and the precision and filtering ability of the pyani software developed by PI Pritchard. A primer design software developed by PI Pritchard will be integrated into genomeRxiv to provide users with the ability to quickly design precise molecular detection tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

虽然肉眼看不见，但微生物对社会和环境有着巨大的影响。它们保持土壤健康，引起疾病，并给我们提供抗生素等工具来对抗其他微生物引起的疾病。因此，准确和精确地鉴定微生物对于理解微生物学、诊断和治疗疾病以及维持健康的社会和健康的环境至关重要。DNA测序革命使我们能够读取单个微生物的遗传密码，并利用它进行快速准确的识别。然而，如果没有精确定义微生物类别并将其与其独特特征相关联的参考数据库，我们就无法做到这一点。我们还需要快速的计算机程序来处理大量的相关数据，为了对世界最有用，我们需要允许任何人，任何地方上传他们发现的微生物的遗传数据，并快速准确地识别它们可能的影响。因此，科学家们将建立genomeRxiv，一个网站和一个数据库，其中包含数十万个准确编目和分类的细菌和古细菌的公共基因组序列。在现有工作的基础上，将采用一种快速和准确的算法，供用户查询数据库。一个独特的功能将使提交的基因组保持私密，这将使学术界、工业界和政府的科学家能够建立和促进网络，并促进基因组测序结果的共享，从而更有效、更经济地使用研究资金。诊断工具的自动化设计将促进病原体的检测和管理，以实现生物安全和生物安保，并直接影响临床和兽医学、植物病理学以及农业中有益微生物的使用。科学界将接受使用基因组的培训，不同背景的本科生和研究生将接受生物学和计算机科学的教育。测序的基因组数量呈指数级增长，但分类身份的自动分配受到现有分类的转移的限制。预计高达20%的现有分类是不正确的，并且由历史上偶然的多相测试确定，这些测试不对应于在基因组水平上可识别的有意义的非同源基因组分组。继续不正确和不准确的分类身份分配破坏了我们对原核生物进化和多样性的理解，以及监管和监测病原体的立法努力，而这些都依赖于准确的识别。该项目的PI已经开发的工具将得到改进，并集成到一个名为genomeRxiv的新计算服务中，该服务旨在解决这些问题。现有的LINbase Web服务器将作为新genomeRxiv服务的基础。PI Vinatzer和Heath的高分辨率Life Identification NumberTM（LINTM）分类框架将与PI Brown开发的sourmash软件的速度和计算效率以及PI Pritchard开发的pyani软件的精度和过滤能力相结合。由PI Pritchard开发的引物设计软件将被集成到genomeRxiv中，为用户提供快速设计精确分子检测工具的能力。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。