제목 : 미생물 세포 공장 개발을 위한 시스템 및 합성 생물학

내용 : A huge drop in next-generation sequencing cost and advances in data analytics can synergistically improve our understanding of microbial hosts to develop efficient bioprocesses. In this talk, I will introduce two genome and transcriptome analysis approaches for host engineering of Pseudomonas putida KT2440, which is a promising microbial platform. In the first part, a multifaceted adaptive laboratory evolution (ALE) strategy, utilized to enhance bioprocess-relevant phenotypes will be introduced. P. putida KT2440 was parallelly evolved in an automated platform in multiple replicates for efficient utilization of xylose and galactose and tolerance to toxic biomass-degrading ionic liquids. Subsequent genome resequencing of many evolved isolates successfully identified key causal mutation targets, strongly associated with the improved phenotypes. In the second part, I will introduce independent component analysis (ICA) of an RNA-seq data compendium, containing, 321 gene expression profiles collected under 118 unique experimental conditions. This analysis revealed 84 co-expressed gene groups which represent regulation targets of at least 38 transcription factors and simplify complicated transcriptome changes. These two approaches based on large-scale genomics and transcriptome data can effectively facilitate host engineering, which is critical for developing efficient bioprocesses.