Literature DB >> 27242778

Commentary: Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium.

Erica L Fonseca1, Ana Carolina P Vicente1.   

Abstract

Entities:  

Keywords:  BCR-1; Pseudomonas aeruginosa genomics; SPM-1; byciclomycin resistance; clone SP/ST277; integrative and conjugative elements (ICEs); metallo-beta-lactamase

Year:  2016        PMID: 27242778      PMCID: PMC4876116          DOI: 10.3389/fmicb.2016.00770

Source DB:  PubMed          Journal:  Front Microbiol        ISSN: 1664-302X            Impact factor:   5.640


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The robust study on Pseudomonas aeruginosa genome evolution, epidemiology, antimicrobial resistance mechanisms, and pathogenesis performed by Freschi et al. (2015) will offer a huge contribution to clinicians to improve the management of infections caused by this organism. Moreover, it is a big step toward the application of such genomic data to understand cystic fibrosis infections and to establish a powerful surveillance system in the clinical routine. This study also presented the first snapshot of the P. aeruginosa resistome by performing searches on 389 P. aeruginosa genomes using the Resistance Gene Identifier tool from the Comprehensive Antibiotic Resistance Database (CARD) (McArthur et al., 2013). The resistome comprises all genes that are direct or indirectly involved with antimicrobial resistance emergence, which includes intrinsic and acquired resistance genes, distinct resistance mechanisms as well as new determinants not yet identified in the clinical environment (Wright, 2007). Freschi and Colleagues have applied an interesting strategy to recover the resistome information, however, we would like to highlight here that some methodological limitations can compromise this type of screening due to the resistome complexity. For example, they included in the resistome screening three P. aeruginosa genomes (9BR, 19BR, and 213BR; Boyle et al., 2012) that belong to the pandemic high-risk clone SP/ST277 (Fonseca et al., 2015) however, some relevant resistance genes that characterize this clone were not identified. The blaSPM-1 gene codes for a metallo-β-lactamase that confers resistance to all β-lactams antibiotics, including carbapenems, which is the first line antibiotic class in the treatment of infections caused by Gram-negative bacteria. This gene characterizes the P. aeruginosa clone SP/ST277, being recognized as a genetic marker of this lineage. Recently, it was demonstrated that the blaSPM-1 is carried by the ICE6061, which also harbors the byciclomycin resistance bcr-1 gene (Fonseca et al., 2015). ICEs (Integrative and Conjugative Elements) are genetic mobile platforms that can have a major impact in the spread and resistance emergence (Carraro and Burrus, 2014). However, neither bla nor bcr-1 resistance genes were identified by Resistance Gene Identifier tool as part of the 19BR, 213BR, and 9BR resistome. Similarly, the IslandViewer, a specific tool to identify genomic islands, was not able to identify the ICE6061 in none of these three genomes. In order to verify whether this finding resulted from a bias imposed by any parameters used by Freschi et al. (2015) to perform the analyzes or if it was a methodological limitation of the approach used, we applied the Resistance Gene Identifier tool on one genome of clone SP/ST277, extensively studied by our group (PS106), as well as on 9BR, 19BR, and 213BR. A previous BLASTn search using ICE6061 as query revealed its presence in these genomes (Fonseca et al., 2015) however, they were not recognized in our analysis using Resistance Gene Identifier tool, showing some limitations of this approach in the resistome mining. Therefore, we provided here an evidence of an underestimated scenario of the antimicrobial resistance potential, which could also affect the efficient establishment of antimicrobial therapy strategies in the clinical routine. In conclusion, in spite of the valuable contribution of Freschi's study, we would like to stress here that, although the bioinformatics comprehend an important tool to study the overall biology of microorganisms and to assess specific genomic information, they all have limitations that are ameliorated when distinct in silico approaches are performed.

Author contributions

All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  6 in total

Review 1.  The antibiotic resistome: the nexus of chemical and genetic diversity.

Authors:  Gerard D Wright
Journal:  Nat Rev Microbiol       Date:  2007-03       Impact factor: 60.633

Review 2.  Biology of Three ICE Families: SXT/R391, ICEBs1, and ICESt1/ICESt3.

Authors:  Nicolas Carraro; Vincent Burrus
Journal:  Microbiol Spectr       Date:  2014-12

3.  The comprehensive antibiotic resistance database.

Authors:  Andrew G McArthur; Nicholas Waglechner; Fazmin Nizam; Austin Yan; Marisa A Azad; Alison J Baylay; Kirandeep Bhullar; Marc J Canova; Gianfranco De Pascale; Linda Ejim; Lindsay Kalan; Andrew M King; Kalinka Koteva; Mariya Morar; Michael R Mulvey; Jonathan S O'Brien; Andrew C Pawlowski; Laura J V Piddock; Peter Spanogiannopoulos; Arlene D Sutherland; Irene Tang; Patricia L Taylor; Maulik Thaker; Wenliang Wang; Marie Yan; Tennison Yu; Gerard D Wright
Journal:  Antimicrob Agents Chemother       Date:  2013-05-06       Impact factor: 5.191

4.  Complete genome sequences of three Pseudomonas aeruginosa isolates with phenotypes of polymyxin B adaptation and inducible resistance.

Authors:  Brian Boyle; Lucia Fernandez; Jerome Laroche; Irena Kukavica-Ibrulj; Caio M F Mendes; Robert W Hancock; Roger C Levesque
Journal:  J Bacteriol       Date:  2012-01       Impact factor: 3.490

5.  Full characterization of the integrative and conjugative element carrying the metallo-β-lactamase bla SPM-1 and bicyclomycin bcr1 resistance genes found in the pandemic Pseudomonas aeruginosa clone SP/ST277.

Authors:  Erica L Fonseca; Michel A Marin; Fernando Encinas; Ana Carolina P Vicente
Journal:  J Antimicrob Chemother       Date:  2015-06-20       Impact factor: 5.790

6.  Clinical utilization of genomics data produced by the international Pseudomonas aeruginosa consortium.

Authors:  Luca Freschi; Julie Jeukens; Irena Kukavica-Ibrulj; Brian Boyle; Marie-Josée Dupont; Jérôme Laroche; Stéphane Larose; Halim Maaroufi; Joanne L Fothergill; Matthew Moore; Geoffrey L Winsor; Shawn D Aaron; Jean Barbeau; Scott C Bell; Jane L Burns; Miguel Camara; André Cantin; Steve J Charette; Ken Dewar; Éric Déziel; Keith Grimwood; Robert E W Hancock; Joe J Harrison; Stephan Heeb; Lars Jelsbak; Baofeng Jia; Dervla T Kenna; Timothy J Kidd; Jens Klockgether; Joseph S Lam; Iain L Lamont; Shawn Lewenza; Nick Loman; François Malouin; Jim Manos; Andrew G McArthur; Josie McKeown; Julie Milot; Hardeep Naghra; Dao Nguyen; Sheldon K Pereira; Gabriel G Perron; Jean-Paul Pirnay; Paul B Rainey; Simon Rousseau; Pedro M Santos; Anne Stephenson; Véronique Taylor; Jane F Turton; Nicholas Waglechner; Paul Williams; Sandra W Thrane; Gerard D Wright; Fiona S L Brinkman; Nicholas P Tucker; Burkhard Tümmler; Craig Winstanley; Roger C Levesque
Journal:  Front Microbiol       Date:  2015-09-29       Impact factor: 5.640

  6 in total

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