Predictive analysis of transmissible quinolone resistance indicates Stenotrophomonas maltophilia as a potential source of a novel family of Qnr determinants

• Published in: BMC microbiology Vol. 8; no. 1; p. 148
• Main Authors: Sanchez, Maria B, Hernandez, Alvaro, Rodriguez-Martinez, Jose M, Martinez-Martinez, Luis, Martinez, Jose L
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 16.09.2008; BioMed Central; BMC
• Subjects: Amino Acid Sequence; Anti-Bacterial Agents - pharmacology; Bacterial infections; Bacterial Proteins - chemistry; Bacterial Proteins - genetics; Chromosomes, Bacterial - genetics; Cluster Analysis; Dosage and administration; Drug resistance in microorganisms; Drug Resistance, Bacterial - genetics; Drug therapy; Escherichia coli - drug effects; Escherichia coli - genetics; Gene Expression Regulation, Bacterial; Gene Order; Genetic aspects; Microbial Sensitivity Tests; Molecular Sequence Data; Physiological aspects; Quinolones; Quinolones - pharmacology; Sequence Alignment; Stenotrophomonas maltophilia; Stenotrophomonas maltophilia - genetics; Spain
• ISSN: 1471-2180; 1471-2180
• DOI: 10.1186/1471-2180-8-148

Predicting antibiotic resistance before it emerges at clinical settings constitutes a novel approach for preventing and fighting resistance of bacterial pathogens. To analyse the possibility that novel plasmid-encoded quinolone resistance determinants (Qnr) can emerge and disseminate among bacterial pathogens, we searched the presence of those elements in nearly 1000 bacterial genomes and metagenomes. We have found a number of novel potential qnr genes in the chromosomes of aquatic bacteria and in metagenomes from marine organisms. Functional studies of the Stenotrophomonas maltophilia Smqnr gene show that plasmid-encoded SmQnr confers quinolone resistance upon its expression in a heterologous host. Altogether, the data presented in our work support the notion that predictive studies on antibiotic resistance are feasible, using currently available information on bacterial genomes and with the aid of bioinformatic and functional tools. Our results confirm that aquatic bacteria can be the origin of plasmid-encoded Qnr, and highlight the potential role of S. maltophilia as a source of novel Qnr determinants.