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）过程从环境中的其他细菌获得新的DNA。这种转移的DNA通常会编码新的功能，以扩大生物体的生态位，改变其与宿主的关系，或在其环境中提供与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同时对单个样本中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。现有数千个公开可用的宏基因组序列数据集，涵盖来自非常多样化的生态系统的样本，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来检查这些数据集的移动基因内容，以识别那些可能影响微生物群落对压力的反应的基因。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以微生物群落研究为重点的计算科学社区的黑客马拉松来训练使用所得方法。招聘工作的目标是在整个大五指湖地区显著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霰弹枪数据进行，这些数据是通过对微生物样本进行整体测序获得的。然而，尽管它很重要，但在这种类型的短读序列数据中，很少有方法可以区分遗传基因与已被动员并在生物体之间转移的基因。通过提供在短读数据中重建可移动遗传元素的新计算方法，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。这项研究将改变微生物学的所有领域，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.