Applied Microbiology and Biotechnology

, Volume 100, Issue 24, pp 10597–10608 | Cite as

Efficiency and sensitivity of the digital droplet PCR for the quantification of antibiotic resistance genes in soils and organic residues

  • Laura Cavé
  • Elisabeth Brothier
  • Danis Abrouk
  • Panignimyandé Salomon Bouda
  • Edmond Hien
  • Sylvie Nazaret
Methods and protocols

Abstract

Droplet digital PCR (ddPCR) allows absolute quantification and tolerance to inhibitors and has been proposed as the method of choice to overcome limitations of qPCR. The aim of this study was to evaluate ddPCR and qPCR performances to detect low copy number and copy number variation of antibiotic resistance genes (sul1 and qnrB genes encoding for resistance to sulfonamides and quinolones, respectively) using bacterial genomic DNA (gDNA) and metagenomic DNA extracted from soil and organic residue samples. With gDNA, qPCR showed a better range of quantification but the lower limit of quantification was at 15 copies of qnrB target vs. 1.6 in ddPCR. In the presence of background DNA or inhibitors, we observed a high loss of sensitivity in qPCR and an overestimation of target sequences. When using high amount of environmental DNA templates (70 ng per reaction), ddPCR was still allowing accurate quantification without adding PCR facilitator (i.e., T4 Gene 32 protein). Sensitivity to detect copy number variation was tenfold higher in ddPCR than in qPCR. Finally, the advantages of using ddPCR in environmental studies were confirmed with the quantification of sul1 and qnrB in soils, manures, or urban wastes.

Keywords

Digital droplet PCR Antibiotic resistance gene Soil Organic residue 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Laura Cavé
    • 1
  • Elisabeth Brothier
    • 1
  • Danis Abrouk
    • 2
  • Panignimyandé Salomon Bouda
    • 3
  • Edmond Hien
    • 3
  • Sylvie Nazaret
    • 1
  1. 1.Research Group on ‘Environmental multi-resistance and efflux pump ‘, CNRS, Ecole Nationale Vétérinaire de Lyon, and Université Lyon 1, UMR 5557 Ecologie MicrobienneUniversité de LyonVilleurbanne CedexFrance
  2. 2.Université de Lyon, France; ‘ibio platform’, CNRS, Ecole Nationale Vétérinaire de Lyon, and Université Lyon 1, UMR 5557 Ecologie MicrobienneUniversité de LyonVilleurbanne CedexFrance
  3. 3.LMI IESOL, UMR Eco&Sols, IRD-Université de OuagadougouOuagadougou 03Burkina Faso

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