Open AccessExperimental and Analytical Approaches for Improving the Resolution of Randomly Barcoded Transposon Insertion Sequencing (RB-TnSeq) Studies
Author(s) -
Andrew J. Borchert,
Alissa Bleem,
Gregg T. Beckham
Publication year - 2022
Publication title -
acs synthetic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.156
H-Index - 66
ISSN - 2161-5063
DOI - 10.1021/acssynbio.2c00119
Subject(s) - biology , computational biology , selection (genetic algorithm) , transposable element , pseudomonas putida , organism , genetics , identification (biology) , gene , computer science , mutant , machine learning , botany
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.