Microbial Genomics Laboratory

The Microbial Genomics Laboratory is led by Prof. Yunho Lee of the Department of Life Science, Graduate School, chair of the Department of Food Science and Biotechnology, and searches for safe and useful microbial resources on the basis of microbial genome information. The lab isolates previously unknown bacteria from natural environments such as rivers, soil, salt lakes and indoor air-conditioning systems, reports them as new species, and explains at the gene level how bacterial quorum sensing affects pathogenicity and competition. It verifies strains from traditional fermented foods such as doenjang and meju by whole-genome sequencing to find probiotic candidates, and also studies the biodegradation of oil-contaminated soil with indigenous microorganisms. As its current strategy the lab combines AI with genome mining that first screens public genome and patent data, narrowing down candidate strains in a data-first search, and collaborates with the AIForA Lab on AI methods.

• 01

  Isolation of previously unknown bacteria from rivers, soil, algae, salt lakes and indoor air-conditioning systems and description of new species by polyphasic taxonomy

• 02

  Gene-level study of how bacterial signaling (quorum sensing) affects pathogenicity, competition and spread, and of mechanisms against oxidative stress

• 03

  Bioremediation of oil-contaminated soil with consortia of indigenous microorganisms and aromatic hydrocarbon-degrading strains

• 04

  Discovery of food-grade probiotic candidates by whole-genome sequencing of strains from traditional fermented foods such as doenjang and meju

• 05

  A genome mining process that first screens public genome and patent data to secure safe microbial resources for age-specific health problems and an aging society

• 01

  AI-related research

  A data-first search strategy that combines genome mining of public genome data with AI to narrow down candidate strains, with collaboration on AI methods with the AIForA Lab stated on the lab website

• 02

  Joint AI research

  Joint papers, patents, and research projects with the AI Forecasting Analytics Lab, the department chair's lab, applying AI methods to this lab's data and research questions

  Joint research outputs to be added to the output lists on this page