报告题目：Analysis of 100s of metagenomes shows that microbial species exist and can be reliably tracked over space and perturbations
主讲人：Konstantinos (Kostas) T. Konstantinidis
主持人：张思宇 研究员
讲座时间：10月26日 9:00
讲座地点：闵行校区 资环楼354
主办单位：生态与环境科学学院
报告人简介：
Dr. Kostas Konstantinidis is the Richard C. Tucker Professor in the School of Civil and Environmental Engineering and the School of Biological Sciences (adjunct) at Georgia Tech and Program Faculty for the Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. The overarching goal of his research is to advance understanding of how microorganisms adapt to human-induced environmental perturbations and to cause disease. He is also interested in the biotechnological applications of microbial diversity in the bioremediation of environmental pollutants and the assessment of water quality. The great majority of microorganisms resists cultivation in the laboratory and thus, cannot be studied efficiently. Therefore, another major objective of his research program is to develop novel culture-independent (e.g., metagenomics and metatranscriptomics) approaches and associated bioinformatics tools to study microbial communities in-situ, in both natural (e.g., terrestrial or marine) as well as human-associated systems. He has published >220 papers in these areas, 13 in PNAS alone, and received several international distinctions and awards for his work, including the 2010 International Skerman Award from the World Federation for Culture Collections, and a 2014 Kavli Frontier Fellowship. He is an elected member of the honorary American Academy of Microbiology and in the top 1% of world's Highly Cited scientists and engineers by Clarivate/Web of Science 2020-present. His bioinformatics approaches are available for online analysis of microbial genome and metagenome data through the lab webserver, which receives >3,000 visitors each month.
报告内容简介：
Large scale surveys of natural prokaryotic communities (metagenomics) or isolate genomes have revealed species clusters around 95% Average Nucleotide Identity (ANI) of shared genes. That is, members of the same species tend to show >95% ANI among themselves and <85% to members of other species with a clear scarcity (gap) of genome pairs showing between 85-95% ANI. We have recently reported a similar ANI gap within species, around 99.5% ANI, revealing that discrete, intraspecies units may also exist. We suggested referring to these units as genomovars (Rodriguez-R, mBio 2024), and to employ a higher ANI value (99.9%) and level of shared genes (>99% of total genes) to define strains (Viver, Nat. Comms. 2024). In this talk, will present our improved bioinformatics methodologies to recover the genome of these species and intra-species units from metagenomic datasets. Subsequently, I will describe how tracking of pollution (or microbial source tracking) based on these methodologies and units of diversity can be performed more robustly than existing approaches (Lindner et al., Water Research 2021). These capabilities represent a novel problem-solving framework that may be especially useful to site-specific environmental monitoring of not only fecal pollution but also monitoring of the release of organisms of synthetic biology into the environment. Finally, I will show an example of how these metagenomic methodologies helped us to identify the keystone species degrading crude oil spills within complex coastal sediments, and how this work has led to the identification of novel biosurfactants for oil bioremediation.
