生物
计算生物学
选择(遗传算法)
转座因子
恶臭假单胞菌
有机体
鉴定(生物学)
遗传学
基因
生物技术
计算机科学
突变体
机器学习
植物
作者
Andrew J. Borchert,Alissa Bleem,Gregg T. Beckham
标识
DOI:10.1021/acssynbio.2c00119
摘要
Randomly barcoded transposon insertion sequencing (RB-TnSeq) is an efficient, multiplexed method to determine microbial gene function during growth under a selection condition of interest. This technique applies to growth, tolerance, and persistence studies in a variety of hosts, but the wealth of data generated can complicate the identification of the most critical gene targets. Experimental and analytical methods for improving the resolution of RB-TnSeq are proposed, using Pseudomonas putida KT2440 as an example organism. Several key parameters, such as baseline media selection, substantially influence the determination of gene fitness. We also present options to increase statistical confidence in gene fitness, including increasing the number of biological replicates and passaging the baseline culture in parallel with selection conditions. These considerations provide practitioners with several options to identify genes of importance in TnSeq data sets, thereby streamlining metabolic characterization.
科研通智能强力驱动
Strongly Powered by AbleSci AI