Environmental MicrobiologyMicrobiologyPeer-reviewed journal article
High-throughput Tn-seq screens identify both known and novel Pseudomonas putida KT2440 genes involved in metal resistance
Kévin RoyetiD, Laura Kergoat, Stefanie LutziD, Charlotte OrioliD, Nicolas ParisotiD, Christian Schori, Christian H. AhrensiD, Agnès RodrigueiD, Erwan GuegueniD
Abstract
Chemical waste with toxic effects is released into the environment by industrial and urban activities. Pseudomonas putida, a rhizosphere bacterium, harbors a wide variety of genes capable of degrading hydrocarbons and xenobiotic compounds in its natural environment. This bacterium harbors also a large set of metal resistance genes. Most studies that identify genes involved in metal resistance in P. putida focus on over/underexpressed genes and may miss other genes important for metal resistance whose expression does not change. In this study, we used a Tn-seq approach to determine the essential genome of P. putida required for growth in the presence of an excess of metals in a culture medium. Tn-seq enables the detection of mutants with reduced or increased fitness in the presence of metal excess. We validated our screen by identifying known metal resistance gene such as czcA-1 (PP_0043), cadA-3 (PP_5139), cadR (PP_5140) and pcoA2 (PP_5380). Their mutants were underrepresented in the presence of zinc, cadmium (for cadA-3 and cadR) or copper respectively. In this study, we demonstrate by targeted mutagenesis and complementation assay that PP_5337 and PP_0887 are putative transcriptional regulators involved in copper and cadmium resistance, respectively, in P. putida. The study revealed the role of two genes, PP_1663 and PP_5002, in cadmium and cobalt resistance respectively. This is the first evidence linking these genes to metal resistance and highlights the incomplete understanding of metal resistance mechanisms in P. putida.
- organism: bacteria (other)
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 7
- FWCI
- 2.82
- Field percentile
- top 10%
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