a streptomycin resistance marker in h. parasuis based on site-directed mutations in rpsl gene to perform unmarked in-frame mutations and to verify natural transformation

a streptomycin resistance marker in h. parasuis based on site-directed mutations in rpsl gene to perform unmarked in-frame mutations and to verify natural transformation

;Ke Dai;Xintian Wen;Yung-Fu Chang;Sanjie Cao;Qin Zhao;Xiaobo Huang;Rui Wu;Yong Huang;Qigui Yan;Xinfeng Han;Xiaoping Ma;Yiping Wen
pediatrics 2018 Vol. 6 pp. e4253-
143
dai2018peerja

Abstract

Haemophilus parasuis is a member of the family Pasteurellaceae and a major causative agent of Glässer’s disease. This bacterium is normally a benign swine commensal but may become a deadly pathogen upon penetration into multiple tissues, contributing to severe lesions in swine. We have established a successive natural transformation-based markerless mutation system in this species. However, the two-step mutation system requires screening of natural competent cells, and cannot delete genes which regulate natural competence per se. In this study, we successfully obtained streptomycin-resistant derivatives from H. parasuis wild type strain SC1401 by using ethyl methane sulfonate (EMS, CH3SO2OC2H5). Upon sequencing and site-directed mutations, we uncovered that the EMS-induced point mutation in rpsL at codon 43rd (AAA → AGA; K43R) or at 88th (AAA → AGA; K88R) confers a much higher streptomycin resistance than clinical isolates. We have applied the streptomycin resistance marker as a positive selection marker to perform homologous recombination through conjugation and successfully generated a double unmarked in-frame targeted mutant 1401D88△tfox△arcA. Combined with a natural transformation-based knockout system and this genetic technique, multiple deletion mutants or attenuated strains of H. parasuis can be easily constructed. Moreover, the mutant genetic marker rpsL and streptomycin resistant phenotypes can serve as an effective tool to select naturally competent strains, and to verify natural transformation quantitatively.

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