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ABI Innovation: Tools for reconstructing mobile genetic elements from shotgun metagenomic data

ABI Innovation：从鸟枪法宏基因组数据重建移动遗传元件的工具

基本信息

批准号：
1661338
负责人：
Ilana Brito
金额：
$ 102.96万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-07-01 至 2021-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1661338&HistoricalAwards=false
关键词：
ABI Innovation Tools reconstructing mobile

项目摘要

Bacteria may acquire novel DNA from other bacteria in their environment through the process of horizontal gene transfer (HGT). This transferred DNA often encodes new functions that expand an organism's niche, change its relationships with its host or provide a competitive edge against other organisms within its environment. For example, antibiotic resistance genes are frequently observed to be transferred between organisms. New high-throughput DNA sequencing technologies now allow researchers to simultaneously sequence data from millions of different bacterial species in a single sample, called metagenome sequencing. Thousands of publicly available metagenomic sequence datasets exist for samples from very diverse ecologies, including: gut microbiomes from humans, animals and insects, soil and root communities, surfaces in built environments, hydrothermal mats and vents, wastewater treatment plants, freshwater sources and marine ecosystems. Using these datasets, the research team will develop a suite of computational tools for examining the mobile gene content of these datasets, to identify those genes that may shape the response of microbial communities to stress. Graduate students will carry out the research under the direction of the PI, while undergraduates will be trained to use the resulting methods through a series of hackathons aimed at building the computational science community focused on microbial community research. Recruiting efforts will be aimed at measurably increasing the diversity in computational biology throughout the greater Finger Lakes region. Functional characterization of microbial communities is often performed using metagenomic shotgun data, obtained by sequencing microbial samples in their entirety. Yet, despite its importance, few methods exist to distinguish genes that are inherited versus those genes which have been mobilized and transferred between organisms in this type of short-read sequence data. By providing new computational methods for reconstructing mobile genetic elements in short-read data, researchers can tap into the huge resource of existing metagenomic data to examine the role of HGT in shaping the functions of natural microbial communities. This research will be transformative for all fields of microbiology, including clinical microbiology, microbiome research, environmental microbiology, and microbial engineering.

细菌可以通过水平基因转移（HGT）过程从其环境中的其他细菌获得新的DNA。这种转移的DNA通常编码新的功能，这些功能可以扩大生物体的生态位，改变其与宿主的关系，或提供与环境中其他生物体的竞争优势。例如，经常观察到抗生素抗性基因在生物体之间转移。新的高通量DNA测序技术现在允许研究人员在单个样本中同时对数百万种不同细菌物种的数据进行测序，称为宏基因组测序。数以千计的公开可用的宏基因组序列数据集存在于非常不同的生态系统中，包括：人类，动物和昆虫的肠道微生物组，土壤和根系群落，建筑环境中的表面，热液垫和喷口，废水处理厂，淡水资源和海洋生态系统。利用这些数据集，研究小组将开发一套计算工具，用于检查这些数据集的移动的基因内容，以确定那些可能影响微生物群落对压力反应的基因。研究生将在PI的指导下进行研究，而本科生将通过一系列旨在建立专注于微生物群落研究的计算科学社区的黑客松来培训使用所产生的方法。招聘工作的目的是在整个手指湖地区可衡量地增加计算生物学的多样性。微生物群落的功能表征通常使用宏基因组鸟枪数据进行，所述宏基因组鸟枪数据通过对微生物样品进行整体测序而获得。然而，尽管它的重要性，存在一些方法来区分遗传的基因与这些基因已经动员和转移生物体之间在这种类型的短读序列数据。通过提供新的计算方法来重建短读数据中的移动的遗传元件，研究人员可以利用现有宏基因组数据的巨大资源来研究HGT在塑造天然微生物群落功能中的作用。这项研究将为微生物学的所有领域带来变革，包括临床微生物学，微生物组研究，环境微生物学和微生物工程。