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.