Publication
Next Generation Sequencing as a tool to detect antibiotic resistance mechanisms
| dc.contributor.author | Manageiro, Vera | |
| dc.contributor.author | Caniça, Manuela | |
| dc.date.accessioned | 2018-03-07T19:19:16Z | |
| dc.date.available | 2018-03-07T19:19:16Z | |
| dc.date.issued | 2017-02 | |
| dc.description.abstract | Antibiotic resistance is an emerging problem, becoming a serious threat to global public health.The causes of its spread are complex, as are the strategies to combat this threat. Following recent improvements in sequencing technologies, whole-genome sequencing (WGS) provides a comprehensive alternative in the evaluation and detection of antibiotic resistance mechanisms. In the scope of the analysis of nonsusceptibility of Gram-negative isolates recovered from human, veterinary and environment samples, we identified the presence of a high diversity of resistance mechanisms, with emphasis in the recently described plasmid-mediated mcr gene, conferring resistance to colistin. Therefore, the objective of this study was to characterize the phenotype and genotype of those isolates using conventional microbiological methods and WGS. Whenever appropriate, genetic relatedness of isolates was also investigated by pulsed-field gel electrophoresis (PFGE). To understand the genetic background of those resistance mechanisms, which included oxyimino-β-lactam, fluoroquinolone and colistin resistance-encoding genes, we performed whole genome and plasmid sequencing using a 454 (Roche) and/or MiSeq (Illumina) sequencing strategy. A set of bioinformatic web tools were used to estimate the presence of pathogenicity determinants, antibiotic resistance (AR) genes, and clinically relevant mobile genetic elements. Indeed, the efficient gene capture and spread of resistance determinants by mobile genetic elements are factors to be taken into account, due to their contribution for the co-selection of multidrug resistant strains in the different settings and environment. Furthermore, WGS might be used with great benefit in combination with phenotypic methods for surveillance purposes. | pt_PT |
| dc.description.version | N/A | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.18/5363 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.subject | Next Generation Sequencing | pt_PT |
| dc.subject | Antibiotic Resistance | pt_PT |
| dc.subject | Gram-negative Bacteria | pt_PT |
| dc.subject | v | pt_PT |
| dc.title | Next Generation Sequencing as a tool to detect antibiotic resistance mechanisms | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Braga, Portugal | pt_PT |
| oaire.citation.title | 6th Bioinformatics Open Days 2017, Universidade do Minho, 23-24 February 2017 | pt_PT |
| rcaap.rights | restrictedAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |