Acta Scientific Microbiology (ISSN: 2581-3226)

Research Article Volume 4 Issue 11

In Silico Prediction and Comparison of Resistomes in Model Pseudomonas Strains by Resistance Gene Identifier (RGI)

Huayu Qin1, Ming Liu2 and Shiqi Xu1*

1Department of Biomedical Engineering, School of Biomedical Engineering, Chengde Medical University, China
2Department of School of Basic Medical Sciences, Chengde Medical University, China

*Corresponding Author: Shiqi Xu, School of Biomedical Engineering, Chengde Medical University, Shuangqiao District, Chengde Municipality, Hebei Province, China.

Received: October 04, 2021 ; Published: October 21, 2021

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Abstract

Pseudomonas is a genus of bacteria including strains of human and plant pathogens, plant-growth promoting and biological control agents. While most Pseudomonas strains are known resistant to several antibiotics, their genetic elements conferring antimicrobial resistance (AMR) are largely unexplored systematically. The current study exploits a robust AMR gene predicting tool Resistance Gene Identifier of most recently updated version 5.2.0 based on newly curated database (the Comprehensive Antibiotic Research Database version 3.1.3) to detect AMR genes from thirteen genomes of Pseudomonas strains affiliated with seven species, including twelve pseudomonads as popularly studied model strains plus a well-known Pseudomonas protegens CHA0. A list of 281 AMR genes have been detected in five genomes of Pseudomonas aeruginosa, while 32 in the rest Pseudomonas spp. strains. Among the species, P. aeruginosa, P. fluorescens, P. protegens and P. stutzeri have the resistome of multi-drug resistance, while the rest is resistant to narrower spectrum of drugs. All Pseudomonas spp. investigated here have resistance genes to antibiotics classes of fluoroquinolone and tetracycline, which is consistent with an antibiotic resistance gene hit of adeF (ARO No. 3000777, resistant to fluoroquinolone, tetracycline) has found in high redundancy in almost all Pseudomonas species except P. aeruginosa and P. stutzeri, implying the limit of these classes of drugs for treating pseudomonads. While inter-species data were focused here, further analysis will be conducted to reveal the features of inter-strain level features of pseudomonads. The in silico analysis will complement wet-lab research for designing treating strategies of these bacteria.

Keywords: Pseudomonas; Antimicrobial Resistance; Genome Analysis; Drug Resistance Mechanism; Antibiotic Resistance Gene Ontology

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Citation

Citation: Shiqi Xu., et al.In Silico Prediction and Comparison of Resistomes in Model Pseudomonas Strains by Resistance Gene Identifier (RGI)”. Acta Scientific Microbiology 4.11 (2021): 49-55.




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