1887

Microbiology Society logo

Volume 168, Issue 10

Exploration of the presence and abundance of multidrug resistance efflux genes in oil and gas environments Free

This article is part of the Antimicrobial Efflux collection.

Abstract

As sequencing technology improves and the cost of metagenome sequencing decreases, the number of sequenced environments increases. These metagenomes provide a wealth of data in the form of annotated and unannotated genes. The role of multidrug resistance efflux pumps (MDREPs) is the removal of antibiotics, biocides and toxic metabolites created during aromatic hydrocarbon metabolism. Due to their naturally occurring role in hydrocarbon metabolism and their role in biocide tolerance, MDREP genes are of particular importance for the protection of pipeline assets. However, the heterogeneity of MDREP genes creates a challenge during annotation and detection. Here we use a selection of primers designed to target MDREPs in six pure species and apply them to publicly available metagenomes associated with oil and gas environments. Using PCR with relaxed primer binding conditions we probed the metagenomes of a shale reservoir, a heavy oil tailings pond, a civil wastewater treatment, two marine sediments exposed to hydrocarbons following the Deepwater Horizon oil spill and a non-exposed marine sediment to assess the presence and abundance of MDREP genes. Through relaxed primer binding conditions during PCR, the prevalence of MDREPs was determined. The percentage of nucleotide sequences identified by the MDREP primers was partially augmented by exposure to hydrocarbons in marine sediment and in shale reservoir compared to hydrocarbon-free marine sediments while tailings ponds and wastewater had the highest percentages. We believe this approach lays the groundwork for a supervised method of identifying poorly conserved genes within metagenomes.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): MDR , MDREP , metagenomic , multidrug resistance efflux pumps and PCR
Funding
This study was supported by the:
  • NSERC
    • Principle Award Recipient: RaymondJ. Turner
© 2022 The Authors
Loading

Article metrics loading...

/content/journal/micro/10.1099/mic.0.001248
2022-10-03
2024-05-08
Loading full text...

Full text loading...

/deliver/fulltext/micro/168/10/mic001248.html?itemId=/content/journal/micro/10.1099/mic.0.001248&mimeType=html&fmt=ahah

References

  1. Segata N, Huttenhower C. Toward an efficient method of identifying core genes for evolutionary and functional microbial phylogenies. PLOS ONE 2011; 6:e24704 [View Article]
     [Google Scholar]
  2. Martincorena I, Seshasayee ASN, Luscombe NM. Evidence of non-random mutation rates suggests an evolutionary risk management strategy. Nature 2012; 485:95–98 [View Article] [PubMed]
     [Google Scholar]
  3. Maslov S, Krishna S, Pang TY, Sneppen K. Toolbox model of evolution of prokaryotic metabolic networks and their regulation. Proc Natl Acad Sci USA 2009; 106:9743–9748 [View Article]
     [Google Scholar]
  4. Denamur E, Matic I. Evolution of mutation rates in bacteria. Mol Microbiol 2006; 60:820–827 [View Article] [PubMed]
     [Google Scholar]
  5. Stokes HW, Gillings MR. Gene flow, mobile genetic elements and the recruitment of antibiotic resistance genes into Gram-negative pathogens. FEMS Microbiol Rev 2011; 35:790–819 [View Article]
     [Google Scholar]
  6. Darmon E, Leach DRF. Bacterial genome instability. Microbiol Mol Biol Rev 2014; 78:1–39 [View Article]
     [Google Scholar]
  7. Kim M, Park J, Kang M, Yang J, Park W. Gain and loss of antibiotic resistant genes in multidrug resistant bacteria: one health perspective. J Microbiol 2021; 59:535–545 [View Article]
     [Google Scholar]
  8. Brown DC, Turner RJ. Lessons and Considerations for the Creation of Universal Primers Targeting Non-Conserved, Horizontally Mobile Genes. Appl Environ Microbiol 2020; 87:1–18 [View Article]
     [Google Scholar]
  9. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 2012; 19:455–477 [View Article]
     [Google Scholar]
  10. Tringe SG, von Mering C, Kobayashi A, Salamov AA, Chen K et al. Comparative metagenomics of microbial communities. Science 2005; 308:554–557 [View Article]
     [Google Scholar]
  11. Chen K, Pachter L. Bioinformatics for whole-genome shotgun sequencing of microbial communities. PLOS Comput Biol 2005; 1:106–112 [View Article]
     [Google Scholar]
  12. Arndt D, Xia J, Liu Y, Zhou Y, Guo AC et al. METAGENassist: a comprehensive web server for comparative metagenomics. Nucleic Acids Res 2012; 40:W88–95 [View Article]
     [Google Scholar]
  13. Goll J, Rusch DB, Tanenbaum DM, Thiagarajan M, Li K et al. METAREP: JCVI metagenomics reports--an open source tool for high-performance comparative metagenomics. Bioinformatics 2010; 26:2631–2632 [View Article] [PubMed]
     [Google Scholar]
  14. Yao X, Tao F, Zhang K, Tang H, Xu P. Multiple roles for two efflux pumps in the polycyclic aromatic hydrocarbon-degrading Pseudomonas putida strain B6-2 (DSM 28064). Appl Environ Microbiol 2017; 83:e01882-17 [View Article]
     [Google Scholar]
  15. Hearn EM, Dennis JJ, Gray MR, Foght JM. Identification and characterization of the emhABC efflux system for polycyclic aromatic hydrocarbons in Pseudomonas fluorescens cLP6a. J Bacteriol 2003; 185:6233–6240 [View Article]
     [Google Scholar]
  16. Chen B, He R, Yuan K, Chen E, Lin L et al. Polycyclic aromatic hydrocarbons (PAHs) enriching antibiotic resistance genes (ARGs) in the soils. Environ Pollut 2017; 220:1005–1013 [View Article]
     [Google Scholar]
  17. García J, García-Galán MJ, Day JW, Boopathy R, White JR et al. A review of emerging organic contaminants (EOCs), antibiotic resistant bacteria (ARB), and antibiotic resistance genes (ARGs) in the environment: Increasing removal with wetlands and reducing environmental impacts. Bioresour Technol 2020; 307:123–228 [View Article]
     [Google Scholar]
  18. Kurenbach B, Hill AM, Godsoe W, van Hamelsveld S, Heinemann JA. Agrichemicals and antibiotics in combination increase antibiotic resistance evolution. PeerJ 2018; 6:e5801 [View Article]
     [Google Scholar]
  19. Wang F, Fu Y-H, Sheng H-J, Topp E, Jiang X et al. Antibiotic resistance in the soil ecosystem: A One Health perspective. Current Opinion in Environmental Science & Health 2021; 20:100230 [View Article]
     [Google Scholar]
  20. Frieri M, Kumar K, Boutin A. Antibiotic resistance. J Infect Public Health 2017; 10:369–378 [View Article]
     [Google Scholar]
  21. Rajamohan G, Srinivasan VB. Disinfectants amend the expression of membrane bound efflux transporters to augment antimicrobial resistance. Bacterial Adaptation to Co-Resistance 201919–38
     [Google Scholar]
  22. Schwaiger K, Harms KS, Bischoff M, Preikschat P, Mölle G et al. Insusceptibility to disinfectants in bacteria from animals, food and humans-is there a link to antimicrobial resistance?. Front Microbiol 2014; 5:88 [View Article] [PubMed]
     [Google Scholar]
  23. Little BJ, Lee JS. Microbiologically influenced corrosion: an update. International Materials Reviews 2014; 59:384–393 [View Article]
     [Google Scholar]
  24. Jia R, Yang D, Xu J, Xu D, Gu T. Microbiologically influenced corrosion of C1018 carbon steel by nitrate reducing Pseudomonas aeruginosa biofilm under organic carbon starvation. Corrosion Science 2019; 127:1–9 [View Article]
     [Google Scholar]
  25. Neria-González I, Wang ET, Ramírez F, Romero JM, Hernández-Rodríguez C. Characterization of bacterial community associated to biofilms of corroded oil pipelines from the southeast of Mexico. Anaerobe 2006; 12:122–133 [View Article] [PubMed]
     [Google Scholar]
  26. Bay DC, Rommens KL, Turner RJ. Small multidrug resistance proteins: a multidrug transporter family that continues to grow. Biochim Biophys Acta 2008; 1778:1814–1838 [View Article]
     [Google Scholar]
  27. He G-X, Zhang C, Crow RR, Thorpe C, Chen H et al. SugE, a new member of the SMR family of transporters, contributes to antimicrobial resistance in Enterobacter cloacae. Antimicrob Agents Chemother 2011; 55:3954–3957 [View Article] [PubMed]
     [Google Scholar]
  28. Heir E, Sundheim G, Holck AL. The Staphylococcus qacH gene product: a new member of the SMR family encoding multidrug resistance. FEMS Microbiol Lett 1998; 163:49–56 [View Article] [PubMed]
     [Google Scholar]
  29. van Veen HW, Margolles A, Müller M, Higgins CF, Konings WN. The homodimeric ATP-binding cassette transporter LmrA mediates multidrug transport by an alternating two-site (two-cylinder engine) mechanism. EMBO J 2000; 19:2503–2514 [View Article] [PubMed]
     [Google Scholar]
  30. Zgurskaya HI, Nikaido H. Multidrug resistance mechanisms: drug efflux across two membranes. Mol Microbiol 2000; 37:219–225 [View Article] [PubMed]
     [Google Scholar]
  31. Wassenaar TM, Ussery D, Nielsen LN, Ingmer H. Review and phylogenetic analysis of qac genes that reduce susceptibility to quaternary ammonium compounds in Staphylococcus species. Eur J Microbiol Immunol (Bp) 2015; 5:44–61 [View Article] [PubMed]
     [Google Scholar]
  32. Edgar R, Bibi E. MdfA, an Escherichia coli multidrug resistance protein with an extraordinarily broad spectrum of drug recognition. J Bacteriol 1997; 179:2274–2280 [View Article] [PubMed]
     [Google Scholar]
  33. Costa SS, Viveiros M, Amaral L, Couto I. Multidrug efflux pumps in Staphylococcus aureus: an update. Open Microbiol J 2013; 7:59–71 [View Article]
     [Google Scholar]
  34. Hassan KA, Liu Q, Elbourne LDH, Ahmad I, Sharples D et al. Pacing across the membrane: the novel PACE family of efflux pumps is widespread in Gram-negative pathogens. Res Microbiol 2018; 169:450–454 [View Article] [PubMed]
     [Google Scholar]
  35. Ogawa W, Minato Y, Dodan H, Onishi M, Tsuchiya T et al. Characterization of MATE-type multidrug efflux pumps from Klebsiella pneumoniae MGH78578. PLOS ONE 2015; 10:e0121619 [View Article]
     [Google Scholar]
  36. Hanczvikkel A, Víg A, Tóth A. Survival capability of healthcare-associated, multidrug resistant bacteria on untreated and on antimicrobial textiles; 2018 https://doi.org/10.1177/1528083718754901
  37. Rajamohan G, Srinivasan VB, Gebreyes WA. Biocide-tolerant multidrug-resistant Acinetobacter baumannii clinical strains are associated with higher biofilm formation. J Hosp Infect 2009; 73:287–289 [View Article] [PubMed]
     [Google Scholar]
  38. Yu Z, Gunn L, Wall P, Fanning S. Antimicrobial resistance and its association with tolerance to heavy metals in agriculture production. Food Microbiol 2017; 64:23–32 [View Article] [PubMed]
     [Google Scholar]
  39. Condell O, Iversen C, Cooney S, Power KA, Walsh C et al. Efficacy of biocides used in the modern food industry to control Salmonella enterica, and links between biocide tolerance and resistance to clinically relevant antimicrobial compounds. Appl Environ Microbiol 2012; 78:3087–3097 [View Article] [PubMed]
     [Google Scholar]
  40. Amsalu A, Sapula SA, De Barros Lopes M, Hart BJ, Nguyen AH et al. Efflux pump-driven antibiotic and biocide cross-resistance in Pseudomonas aeruginosa isolated from different ecological niches: a case study in the development of multidrug resistance in environmental hotspots. Microorganisms 2020; 8:1647 [View Article]
     [Google Scholar]
  41. Sanderson H, Ortega-Polo R, Zaheer R, Goji N, Amoako KK et al. Comparative genomics of multidrug-resistant Enterococcus spp. isolated from wastewater treatment plants. BMC Microbiol 2019; 20:1–17 [View Article]
     [Google Scholar]
  42. da Costa WLO, Araújo CL de A, Dias LM, Pereira LC de S, Alves JTC et al. Functional annotation of hypothetical proteins from the Exiguobacterium antarcticum strain B7 reveals proteins involved in adaptation to extreme environments, including high arsenic resistance. PLoS ONE 2018; 13:e0198965 [View Article]
     [Google Scholar]
  43. de Laia ML, Moreira LM, Gonçalves JF, Ferro MIT, Rodrigues ACP et al. Gene expression analysis identifies hypothetical genes that may be critical during the infection process of Xanthomonas citri subsp. citri. Electron J Biotechnol 2019; 42:30–41 [View Article]
     [Google Scholar]
  44. Schmeisser C, Stöckigt C, Raasch C, Wingender J, Timmis KN et al. Metagenome survey of biofilms in drinking-water networks. Appl Environ Microbiol 2003; 69:7298–7309 [View Article] [PubMed]
     [Google Scholar]
  45. Pawłowski K. Uncharacterized/hypothetical proteins in biomedical “omics” experiments: is novelty being swept under the carpet?. Brief Funct Genomic Proteomic 2008; 7:283–290 [View Article] [PubMed]
     [Google Scholar]
  46. Pao SS, Paulsen IT, Saier MH Jr. Major facilitator superfamily. Microbiol Mol Biol Rev 1998; 62:1–34 [View Article]
     [Google Scholar]
  47. Bay DC, Turner RJ. Diversity and evolution of the small multidrug resistance protein family. BMC Evol Biol 1998; 9:140 [View Article] [PubMed]
     [Google Scholar]
  48. Klenotic PA, Moseng MA, Morgan CE, Yu EW. Structural and functional diversity of resistance–nodulation–cell division transporters. Chem Rev 2021; 121:5378–5416 [View Article] [PubMed]
     [Google Scholar]
  49. Vinella D, Brochier-Armanet C, Loiseau L, Talla E, Barras F et al. Iron-Sulfur (Fe/S) Protein Biogenesis: phylogenomic and genetic studies of A-type carriers. PLOS Genet 2021; 5:e1000497 [View Article] [PubMed]
     [Google Scholar]
  50. Chakravorty S, Helb D, Burday M, Connell N, Alland D. A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J Microbiol Methods 2007; 69:330–339 [View Article] [PubMed]
     [Google Scholar]
  51. Bukin YS, Galachyants YP, Morozov IV, Bukin SV, Zakharenko AS et al. The effect of 16S rRNA region choice on bacterial community metabarcoding results. Sci Data 2019; 6:190007 [View Article] [PubMed]
     [Google Scholar]
  52. Kerrigan Z, Kirkpatrick JB, D’Hondt S. Influence of 16S rRNA hypervariable region on estimates of bacterial diversity and community composition in seawater and marine sediment. Front Microbiol 2019; 10:1640 [View Article] [PubMed]
     [Google Scholar]
  53. Fadeev E, Cardozo-Mino MG, Rapp JZ, Bienhold C, Salter I et al. Comparison of Two 16S rRNA primers (V3-V4 and V4-V5) for studies of Arctic microbial communities. Front Microbiol 2021; 12:637526 [View Article] [PubMed]
     [Google Scholar]
  54. Nakatsu CH, Byappanahalli MN, Nevers MB. Bacterial community 16S rRNA gene sequencing characterizes riverine microbial impact on Lake Michigan. Front Microbiol 2019; 10:996 [View Article] [PubMed]
     [Google Scholar]
  55. An D, Brown D, Chatterjee I, Dong X, Ramos-Padron E et al. Microbial community and potential functional gene diversity involved in anaerobic hydrocarbon degradation and methanogenesis in an oil sands tailings pond. Genome 2013; 56:612–618 [View Article] [PubMed]
     [Google Scholar]
  56. Turnbaugh PJ, Gordon JI. The core gut microbiome, energy balance and obesity. J Physiol 2009; 587:4153–4158 [View Article] [PubMed]
     [Google Scholar]
  57. Bernhard AE, Colbert D, McManus J, Field KG. Microbial community dynamics based on 16S rRNA gene profiles in a Pacific Northwest estuary and its tributaries. FEMS Microbiol Ecol 2005; 52:115–128 [View Article] [PubMed]
     [Google Scholar]
  58. Dethlefsen L, Huse S, Sogin ML, Relman DA. The pervasive effects of an antibiotic on the human gut microbiota, as revealed by deep 16S rRNA sequencing. PLOS Biol 2008; 6:e280 [View Article]
     [Google Scholar]
  59. Castro HF, Classen AT, Austin EE, Norby RJ, Schadt CW. Soil microbial community responses to multiple experimental climate change drivers. Appl Environ Microbiol 2010; 76:999–1007 [View Article] [PubMed]
     [Google Scholar]
  60. Hanson AD, Pribat A, Waller JC, de Crécy-Lagard V. “Unknown” proteins and “orphan” enzymes: the missing half of the engineering parts list--and how to find it. Biochem J 2009; 425:1–11 [View Article] [PubMed]
     [Google Scholar]
  61. Kolker E, Makarova KS, Shabalina S, Picone AF, Purvine S et al. Identification and functional analysis of “hypothetical” genes expressed in Haemophilus influenzae. Nucleic Acids Res 2004; 32:2353–2361 [View Article] [PubMed]
     [Google Scholar]
  62. Koonin EV, Mushegian AR, Rudd KE. Sequencing and analysis of bacterial genomes. Curr Biol 1996; 6:404–416 [View Article] [PubMed]
     [Google Scholar]
  63. Kosloff M, Kolodny R. Sequence-similar, structure-dissimilar protein pairs in the PDB. Proteins 2008; 71:891–902 [View Article]
     [Google Scholar]
  64. Snipen L, Angell IL, Rognes T, Rudi K. Reduced metagenome sequencing for strain-resolution taxonomic profiles. Microbiome 2021; 9:79 [View Article] [PubMed]
     [Google Scholar]
  65. Venter JC, Remington K, Heidelberg JF, Halpern AL, Rusch D et al. Environmental genome shotgun sequencing of the Sargasso Sea. Science 2004; 304:66–74 [View Article]
     [Google Scholar]
  66. Delmont TO, Malandain C, Prestat E, Larose C, Monier J-M et al. Metagenomic mining for microbiologists. ISME J 2011; 5:1837–1843 [View Article] [PubMed]
     [Google Scholar]
  67. Mao D, Yu S, Rysz M, Luo Y, Yang F et al. Prevalence and proliferation of antibiotic resistance genes in two municipal wastewater treatment plants. Water Res 2015; 85:458–466 [View Article] [PubMed]
     [Google Scholar]
  68. Mukherjee M, Laird E, Gentry TJ, Brooks JP, Karthikeyan R. Increased antimicrobial and multidrug resistance downstream of wastewater treatment plants in an Urban Watershed. Front Microbiol 2021; 12:657353 [View Article] [PubMed]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/micro/10.1099/mic.0.001248
Loading
Exploration of the presence and abundance of multidrug resistance efflux genes in oil and gas environments
Microbiology 168, 001248 (2022); https://doi.org/10.1099/mic.0.001248
/content/journal/micro/10.1099/mic.0.001248
/content/journal/micro/10.1099/mic.0.001248
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error