Limits...
Functional verification of computationally predicted qnr genes.

Flach CF, Boulund F, Kristiansson E, Larsson DJ - Ann. Clin. Microbiol. Antimicrob. (2013)

Bottom Line: Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations.Co-expression of two qnr genes suggested non-synergistic action.The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden. joakim.larsson@fysiologi.gu.se.

ABSTRACT

Background: The quinolone resistance (qnr) genes are widely distributed among bacteria. We recently developed and applied probabilistic models to identify tentative novel qnr genes in large public collections of DNA sequence data including fragmented metagenomes.

Findings: By using inducible recombinant expressions systems the functionality of four identified qnr candidates were evaluated in Escherichia coli. Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations. The two novel, functionally verified qnr genes are termed Vfuqnr and assembled qnr 1. Co-expression of two qnr genes suggested non-synergistic action.

Conclusion: The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.

Show MeSH

Related in: MedlinePlus

Phylogenetic tree showing the relationships between Qnr variants. The six plasmid-borne classes are shown in bold. The two candidates functionally verified in this work are marked with an asterisk (NC2 and NC4). The tree was constructed using MrBayes [23].
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4222258&req=5

Figure 2: Phylogenetic tree showing the relationships between Qnr variants. The six plasmid-borne classes are shown in bold. The two candidates functionally verified in this work are marked with an asterisk (NC2 and NC4). The tree was constructed using MrBayes [23].

Mentions: Although recombinant expression in E. coli could not verify nc1 and nc3 as functional qnr genes, it does not rule out functionality in another host. The nc1 is relatively dissimilar to all known qnr genes (33% amino acid identity to QnrC and QnrS1) and originates from a coastal sea water metagenome, suggesting that the natural bacterial host might be distantly related to E. coli. The nc2 gene was identified in the sequenced genome of Vibrio furnissii[18] and its deduced protein product shows 72% identity to QnrC and QnrVC1 (Figure 2). When the nc4 gene was identified in baby stool metagenomes, its gene product showed the highest similarity to QnrB determinants identified in Citrobacter freundii (up to 80% identity) [9]. Later, sequences from Serratia marcescens encoding a protein, not verified to confer resistance, showing 98% identity with NC4 have been submitted to GenBank [19]. Only three amino acids between position 142 and 146 differ between NC3 and NC4. Our results indicate that this region is of importance for the protein’s functionality, at least in E.coli. The two candidates show 78-79% identity to QnrB1 (Figure 2), for which two loop structures are important for the quinolone inhibiting action [20]. In addition, mutational analyses of QnrB1 have identified several individual amino acids critical for its protective activity [21,22]. However, amino acids 142–146 are not located within the loop structures and were not included or identified as critical in the mutational analyses.


Functional verification of computationally predicted qnr genes.

Flach CF, Boulund F, Kristiansson E, Larsson DJ - Ann. Clin. Microbiol. Antimicrob. (2013)

Phylogenetic tree showing the relationships between Qnr variants. The six plasmid-borne classes are shown in bold. The two candidates functionally verified in this work are marked with an asterisk (NC2 and NC4). The tree was constructed using MrBayes [23].
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4222258&req=5

Figure 2: Phylogenetic tree showing the relationships between Qnr variants. The six plasmid-borne classes are shown in bold. The two candidates functionally verified in this work are marked with an asterisk (NC2 and NC4). The tree was constructed using MrBayes [23].
Mentions: Although recombinant expression in E. coli could not verify nc1 and nc3 as functional qnr genes, it does not rule out functionality in another host. The nc1 is relatively dissimilar to all known qnr genes (33% amino acid identity to QnrC and QnrS1) and originates from a coastal sea water metagenome, suggesting that the natural bacterial host might be distantly related to E. coli. The nc2 gene was identified in the sequenced genome of Vibrio furnissii[18] and its deduced protein product shows 72% identity to QnrC and QnrVC1 (Figure 2). When the nc4 gene was identified in baby stool metagenomes, its gene product showed the highest similarity to QnrB determinants identified in Citrobacter freundii (up to 80% identity) [9]. Later, sequences from Serratia marcescens encoding a protein, not verified to confer resistance, showing 98% identity with NC4 have been submitted to GenBank [19]. Only three amino acids between position 142 and 146 differ between NC3 and NC4. Our results indicate that this region is of importance for the protein’s functionality, at least in E.coli. The two candidates show 78-79% identity to QnrB1 (Figure 2), for which two loop structures are important for the quinolone inhibiting action [20]. In addition, mutational analyses of QnrB1 have identified several individual amino acids critical for its protective activity [21,22]. However, amino acids 142–146 are not located within the loop structures and were not included or identified as critical in the mutational analyses.

Bottom Line: Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations.Co-expression of two qnr genes suggested non-synergistic action.The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Infectious Diseases, University of Gothenburg, Gothenburg, Sweden. joakim.larsson@fysiologi.gu.se.

ABSTRACT

Background: The quinolone resistance (qnr) genes are widely distributed among bacteria. We recently developed and applied probabilistic models to identify tentative novel qnr genes in large public collections of DNA sequence data including fragmented metagenomes.

Findings: By using inducible recombinant expressions systems the functionality of four identified qnr candidates were evaluated in Escherichia coli. Expression of several known qnr genes as well as two novel candidates provided fluoroquinolone resistance that increased with elevated inducer concentrations. The two novel, functionally verified qnr genes are termed Vfuqnr and assembled qnr 1. Co-expression of two qnr genes suggested non-synergistic action.

Conclusion: The combination of a computational model and recombinant expression systems provides opportunities to explore and identify novel antibiotic resistance genes in both genomic and metagenomic datasets.

Show MeSH
Related in: MedlinePlus