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

细菌可以通过水平基因转移(HGT)从环境中的其他细菌那里获得新的DNA。这种转移的DNA通常编码新的功能，扩大有机体的生态位，改变其与宿主的关系，或在其环境中提供相对于其他生物的竞争优势。例如，抗生素耐药性基因经常被观察到在生物体之间转移。新的高通量DNA测序技术现在允许研究人员在一个样本中同时对来自数百万种不同细菌的数据进行测序，称为元基因组测序。现有数千个公开可用的元基因组序列数据集，样本来自非常不同的生态系统，包括：来自人类、动物和昆虫的肠道微生物群、土壤和根群落、已建成环境的表面、热液垫子和通风口、废水处理厂、淡水水源和海洋生态系统。利用这些数据集，研究团队将开发一套计算工具，用于检查这些数据集的移动基因含量，以识别那些可能塑造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黑客松培训使用所产生的方法，旨在建立专注于微生物群落研究的计算科学社区。招聘工作的目的将是在整个大指湖地区显着增加计算生物学的多样性。微生物群落的功能特征通常是使用通过对微生物样本进行整体测序获得的超基因组鸟枪数据来进行的。然而，尽管它很重要，但在这种短读序列数据中，几乎没有方法来区分遗传基因和已经动员并在生物体之间转移的基因。通过为在短读数据中重建可移动的遗传元件提供新的计算方法，研究人员可以利用现有元基因组数据的巨大资源来研究HGT在塑造自然微生物群落功能中的作用。这项研究将对微生物学的所有领域产生革命性的影响，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。

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.