Microbial Ecology

, Volume 73, Issue 2, pp 479–491 | Cite as

Functional Metagenomics as a Tool for Identification of New Antibiotic Resistance Genes from Natural Environments

  • Débora Farage Knupp dos Santos
  • Paula Istvan
  • Betania Ferraz Quirino
  • Ricardo Henrique Kruger


Antibiotic resistance has become a major concern for human and animal health, as therapeutic alternatives to treat multidrug-resistant microorganisms are rapidly dwindling. The problem is compounded by low investment in antibiotic research and lack of new effective antimicrobial drugs on the market. Exploring environmental antibiotic resistance genes (ARGs) will help us to better understand bacterial resistance mechanisms, which may be the key to identifying new drug targets. Because most environment-associated microorganisms are not yet cultivable, culture-independent techniques are essential to determine which organisms are present in a given environmental sample and allow the assessment and utilization of the genetic wealth they represent. Metagenomics represents a powerful tool to achieve these goals using sequence-based and functional-based approaches. Functional metagenomic approaches are particularly well suited to the identification new ARGs from natural environments because, unlike sequence-based approaches, they do not require previous knowledge of these genes. This review discusses functional metagenomics-based ARG research and describes new possibilities for surveying the resistome in environmental samples.


Antibiotic resistance genes Environment Functional metagenomics Resistome 


  1. 1.
    Seiple IB, Zhang Z, Jakubec P, Langlois-Mercier A, Wright PM, Hog DT, Yabu K, Allu SR, Fukuzaki T, Carlsen PN, Kitamura Y, Zhou X, Condakes ML, Szczypinski FT, Green WD, Myers AG (2016) A platform for the discovery of new macrolide antibiotics. Nature 533:338–345. doi:10.1038/nature17967 CrossRefPubMedGoogle Scholar
  2. 2.
    Truman AW, Kwun MJ, Cheng J, Yang SH, Suh JW, Hong HJ (2014) Antibiotic resistance mechanisms inform discovery: identification and characterization of a novel amycolatopsis strain producing ristocetin. Antimicrob Agents Chemother 58:5687–5695. doi:10.1128/AAC.03349-14 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Ling LL, Schneider T, Peoples AJ, Spoering AL, Engels I, Conlon BP, Mueller A, Schaberle TF, Hughes DE, Epstein S, Jones M, Lazarides L, Steadman VA, Cohen DR, Felix CR, Fetterman KA, Millett WP, Nitti AG, Zullo AM, Chen C, Lewis K (2015) A new antibiotic kills pathogens without detectable resistance. Nature 517:455–459. doi:10.1038/nature14098 CrossRefPubMedGoogle Scholar
  4. 4.
    Martinez JL (2008) Antibiotics and antibiotic resistance genes in natural environments. Science 321:365–367. doi:10.1126/science.1159483 CrossRefPubMedGoogle Scholar
  5. 5.
    Hug LA, Baker BJ, Anantharaman K, Brown CT, Probst AJ, Castelle CJ, Butterfield CN, Hernsdorf AW, Amano Y, Ise K, Suzuki Y, Dudek N, Relman DA, Finstad KM, Amundson R, Thomas BC, Banfield JF (2016) A new view of the tree of life. Nature Microbiology 1. doi: 10.1038/nmicrobiol.2016.48
  6. 6.
    Sharon I, Kertesz M, Hug LA, Pushkarev D, Blauwkamp TA, Castelle CJ, Amirebrahimi M, Thomas BC, Burstein D, Tringe SG, Williams KH, Banfield JF (2015) Accurate, multi-kb reads resolve complex populations and detect rare microorganisms. Genome Res 25:534–543. doi:10.1101/gr.183012.114 CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Pereira MR, Mercaldi GF, Maester TC, Balan A, de Macedo Lemos EG (2015) Est16, a new esterase isolated from a metagenomic library of a microbial consortium specializing in diesel oil degradation. PLoS One 10:e0133723. doi:10.1371/journal.pone.0133723 CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Prive F, Newbold CJ, Kaderbhai NN, Girdwood SG, Golyshina OV, Golyshin PN, Scollan ND, Huws SA (2015) Isolation and characterization of novel lipases/esterases from a bovine rumen metagenome. Appl Microbiol Biotechnol 99:5475–5485. doi:10.1007/s00253-014-6355-6 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Kim HJ, Jeong YS, Jung WK, Kim SK, Lee HW, Kahng HY, Kim J, Kim H (2015) Characterization of novel family IV esterase and family I.3 lipase from an oil-polluted mud flat metagenome. Mol Biotechnol 57:781–792. doi:10.1007/s12033-015-9871-4 CrossRefPubMedGoogle Scholar
  10. 10.
    Su J, Zhang F, Sun W, Karuppiah V, Zhang G, Li Z, Jiang Q (2015) A new alkaline lipase obtained from the metagenome of marine sponge Ircinia sp. World J Microbiol Biotechnol 31:1093–1102. doi:10.1007/s11274-015-1859-5 CrossRefPubMedGoogle Scholar
  11. 11.
    Alnoch RC, Martini VP, Glogauer A, Costa AC, Piovan L, Muller-Santos M, de Souza EM, de Oliveira Pedrosa F, Mitchell DA, Krieger N (2015) Immobilization and characterization of a new regioselective and enantioselective lipase obtained from a metagenomic library. PLoS One 10:e0114945. doi:10.1371/journal.pone.0114945 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Vester JK, Glaring MA, Stougaard P (2015) An exceptionally cold-adapted alpha-amylase from a metagenomic library of a cold and alkaline environment. Appl Microbiol Biotechnol 99:717–727. doi:10.1007/s00253-014-5931-0 CrossRefPubMedGoogle Scholar
  13. 13.
    Xu B, Yang F, Xiong C, Li J, Tang X, Zhou J, Xie Z, Ding J, Yang Y, Huang Z (2014) Cloning and characterization of a novel alpha-amylase from a fecal microbial metagenome. J Microbiol Biotechnol 24:447–452CrossRefPubMedGoogle Scholar
  14. 14.
    Kanokratana P, Eurwilaichitr L, Pootanakit K, Champreda V (2015) Identification of glycosyl hydrolases from a metagenomic library of microflora in sugarcane bagasse collection site and their cooperative action on cellulose degradation. J Biosci Bioeng 119:384–391. doi:10.1016/j.jbiosc.2014.09.010 CrossRefPubMedGoogle Scholar
  15. 15.
    O’Mahony MM, Henneberger R, Selvin J, Kennedy J, Doohan F, Marchesi JR, Dobson AD (2015) Inhibition of the growth of Bacillus subtilis DSM10 by a newly discovered antibacterial protein from the soil metagenome. Bioengineered 6:89–98. doi:10.1080/21655979.2015.1018493 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Nagayama H, Sugawara T, Endo R, Ono A, Kato H, Ohtsubo Y, Nagata Y, Tsuda M (2015) Isolation of oxygenase genes for indigo-forming activity from an artificially polluted soil metagenome by functional screening using Pseudomonas putida strains as hosts. Appl Microbiol Biotechnol 99:4453–4470. doi:10.1007/s00253-014-6322-2 CrossRefPubMedGoogle Scholar
  17. 17.
    Lee CM, Yeo YS, Lee JH, Kim SJ, Kim JB, Han NS, Koo BS, Yoon SH (2008) Identification of a novel 4-hydroxyphenylpyruvate dioxygenase from the soil metagenome. Biochem Biophys Res Commun 370:322–326. doi:10.1016/j.bbrc.2008.03.102 CrossRefPubMedGoogle Scholar
  18. 18.
    D’Costa VM, Griffiths E, Wright GD (2007) Expanding the soil antibiotic resistome: exploring environmental diversity. Curr Opin Microbiol 10:481–489. doi:10.1016/j.mib.2007.08.009 CrossRefPubMedGoogle Scholar
  19. 19.
    Torres-Cortes G, Millan V, Ramirez-Saad HC, Nisa-Martinez R, Toro N, Martinez-Abarca F (2011) Characterization of novel antibiotic resistance genes identified by functional metagenomics on soil samples. Environ Microbiol 13:1101–1114. doi:10.1111/j.1462-2920.2010.02422.x CrossRefPubMedGoogle Scholar
  20. 20.
    Fang H, Wang H, Cai L, Yu Y (2015) Prevalence of antibiotic resistance genes and bacterial pathogens in long-term manured greenhouse soils as revealed by metagenomic survey. Environ Sci Technol 49:1095–1104. doi:10.1021/es504157v CrossRefPubMedGoogle Scholar
  21. 21.
    Wang Z, Zhang XX, Huang K, Miao Y, Shi P, Liu B, Long C, Li A (2013) Metagenomic profiling of antibiotic resistance genes and mobile genetic elements in a tannery wastewater treatment plant. PLoS One 8:e76079. doi:10.1371/journal.pone.0076079 CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Yang J, Wang C, Shu C, Liu L, Geng J, Hu S, Feng J (2013) Marine sediment bacteria harbor antibiotic resistance genes highly similar to those found in human pathogens. Microb Ecol 65:975–981. doi:10.1007/s00248-013-0187-2 CrossRefPubMedGoogle Scholar
  23. 23.
    Huang K, Tang J, Zhang XX, Xu K, Ren H (2014) A comprehensive insight into tetracycline resistant bacteria and antibiotic resistance genes in activated sludge using next-generation sequencing. Int J Mol Sci 15:10083–10100. doi:10.3390/ijms150610083 CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Yang Y, Li B, Ju F, Zhang T (2013) Exploring variation of antibiotic resistance genes in activated sludge over a four-year period through a metagenomic approach. Environ Sci Technol 47:10197–10205. doi:10.1021/es4017365 PubMedGoogle Scholar
  25. 25.
    Zhang T, Zhang XX, Ye L (2011) Plasmid metagenome reveals high levels of antibiotic resistance genes and mobile genetic elements in activated sludge. PLoS One 6:e26041. doi:10.1371/journal.pone.0026041 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Li B, Yang Y, Ma L, Ju F, Guo F, Tiedje JM, Zhang T (2015) Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes. ISME J 9:2490–2502. doi:10.1038/ismej.2015.59 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Yang Y, Li B, Zou S, Fang HH, Zhang T (2014) Fate of antibiotic resistance genes in sewage treatment plant revealed by metagenomic approach. Water Res 62:97–106. doi:10.1016/j.watres.2014.05.019 CrossRefPubMedGoogle Scholar
  28. 28.
    Nesme J, Cecillon S, Delmont TO, Monier JM, Vogel TM, Simonet P (2014) Large-scale metagenomic-based study of antibiotic resistance in the environment. Curr Biol 24:1096–1100. doi:10.1016/j.cub.2014.03.036 CrossRefPubMedGoogle Scholar
  29. 29.
    Ma L, Li B, Zhang T (2014) Abundant rifampin resistance genes and significant correlations of antibiotic resistance genes and plasmids in various environments revealed by metagenomic analysis. Appl Microbiol Biotechnol 98:5195–5204. doi:10.1007/s00253-014-5511-3 CrossRefPubMedGoogle Scholar
  30. 30.
    Cummings DE, Archer KF, Arriola DJ, Baker PA, Faucett KG, Laroya JB, Pfeil KL, Ryan CR, Ryan KR, Zuill DE (2011) Broad dissemination of plasmid-mediated quinolone resistance genes in sediments of two urban coastal wetlands. Environ Sci Technol 45:447–454. doi:10.1021/es1029206 CrossRefPubMedGoogle Scholar
  31. 31.
    Allen HK, An R, Handelsman J, Moe LA (2015) A response regulator from a soil metagenome enhances resistance to the beta-lactam antibiotic carbenicillin in Escherichia coli. PLoS One 10:e0120094. doi:10.1371/journal.pone.0120094 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Cheng G, Hu Y, Lu N, Li J, Wang Z, Chen Q, Zhu B (2013) Identification of a novel fosfomycin-resistant UDP-N-acetylglucosamine enolpyruvyl transferase (MurA) from a soil metagenome. Biotechnol Lett 35:273–278. doi:10.1007/s10529-012-1074-5 CrossRefPubMedGoogle Scholar
  33. 33.
    McGarvey KM, Queitsch K, Fields S (2012) Wide variation in antibiotic resistance proteins identified by functional metagenomic screening of a soil DNA library. Appl Environ Microbiol 78:1708–1714. doi:10.1128/AEM.06759-11 CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Donato JJ, Moe LA, Converse BJ, Smart KD, Berklein FC, McManus PS, Handelsman J (2010) Metagenomic analysis of apple orchard soil reveals antibiotic resistance genes encoding predicted bifunctional proteins. Appl Environ Microbiol 76:4396–4401. doi:10.1128/AEM.01763-09 CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Allen HK, Moe LA, Rodbumrer J, Gaarder A, Handelsman J (2009) Functional metagenomics reveals diverse beta-lactamases in a remote Alaskan soil. ISME J 3:243–251. doi:10.1038/ismej.2008.86 CrossRefPubMedGoogle Scholar
  36. 36.
    Forsberg KJ, Patel S, Gibson MK, Lauber CL, Knight R, Fierer N, Dantas G (2014) Bacterial phylogeny structures soil resistomes across habitats. Nature 509:612–616. doi:10.1038/nature13377 CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Su JQ, Wei B, Xu CY, Qiao M, Zhu YG (2014) Functional metagenomic characterization of antibiotic resistance genes in agricultural soils from China. Environ Int 65:9–15. doi:10.1016/j.envint.2013.12.010 CrossRefPubMedGoogle Scholar
  38. 38.
    dos Santos DF, Istvan P, Noronha EF, Quirino BF, Kruger RH (2015) New dioxygenase from metagenomic library from Brazilian soil: insights into antibiotic resistance and bioremediation. Biotechnol Lett 37:1809–1817. doi:10.1007/s10529-015-1861-x CrossRefPubMedGoogle Scholar
  39. 39.
    Amos GC, Zhang L, Hawkey PM, Gaze WH, Wellington EM (2014) Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes. Vet Microbiol 171:441–447. doi:10.1016/j.vetmic.2014.02.017 CrossRefPubMedGoogle Scholar
  40. 40.
    Lopez-Perez M, Mirete S, Jardon-Valadez E, Gonzalez-Pastor JE (2013) Identification and modeling of a novel chloramphenicol resistance protein detected by functional metagenomics in a wetland of Lerma, Mexico. Int Microbiol 16:103–111PubMedGoogle Scholar
  41. 41.
    Vercammen K, Garcia-Armisen T, Goeders N, Van Melderen L, Bodilis J, Cornelis P (2013) Identification of a metagenomic gene cluster containing a new class A beta-lactamase and toxin-antitoxin systems. Microbiologyopen 2:674–683. doi:10.1002/mbo3.104 CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Uyaguari MI, Fichot EB, Scott GI, Norman RS (2011) Characterization and quantitation of a novel beta-lactamase gene found in a wastewater treatment facility and the surrounding coastal ecosystem. Appl Environ Microbiol 77:8226–8233. doi:10.1128/AEM.02732-10 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Parsley LC, Consuegra EJ, Kakirde KS, Land AM, Harper WF Jr, Liles MR (2010) Identification of diverse antimicrobial resistance determinants carried on bacterial, plasmid, or viral metagenomes from an activated sludge microbial assemblage. Appl Environ Microbiol 76:3753–3757. doi:10.1128/AEM.03080-09 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Liu B, Pop M (2009) ARDB—Antibiotic Resistance Genes Database. Nucleic Acids Res 37:D443–447. doi:10.1093/nar/gkn656 CrossRefPubMedGoogle Scholar
  45. 45.
    McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, Bhullar K, Canova MJ, De Pascale G, Ejim L, Kalan L, King AM, Koteva K, Morar M, Mulvey MR, O’Brien JS, Pawlowski AC, Piddock LJ, Spanogiannopoulos P, Sutherland AD, Tang I, Taylor PL, Thaker M, Wang W, Yan M, Yu T, Wright GD (2013) The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 57:3348–3357. doi:10.1128/AAC.00419-13 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Craig JW, Chang FY, Kim JH, Obiajulu SC, Brady SF (2010) Expanding small-molecule functional metagenomics through parallel screening of broad-host-range cosmid environmental DNA libraries in diverse proteobacteria. Appl Environ Microbiol 76:1633–1641. doi:10.1128/AEM.02169-09 CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Kang HS, Charlop-Powers Z, Brady SF (2016) Multiplexed CRISPR/Cas9- and TAR-mediated promoter engineering of natural product biosynthetic gene clusters in yeast. ACS Synth Biol. doi:10.1021/acssynbio.6b00080 Google Scholar
  48. 48.
    Gillings MR (2014) Integrons: past, present, and future. Microbiol Mol Biol Rev 78:257–277. doi:10.1128/MMBR.00056-13 CrossRefPubMedPubMedCentralGoogle Scholar
  49. 49.
    Stokes HW, Hall RM (1989) A novel family of potentially mobile DNA elements encoding site-specific gene-integration functions: integrons. Mol Microbiol 3:1669–1683CrossRefPubMedGoogle Scholar
  50. 50.
    Deng Y, Bao X, Ji L, Chen L, Liu J, Miao J, Chen D, Bian H, Li Y, Yu G (2015) Resistance integrons: class 1, 2 and 3 integrons. Ann Clin Microbiol Antimicrob 14:45. doi:10.1186/s12941-015-0100-6 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Débora Farage Knupp dos Santos
    • 1
  • Paula Istvan
    • 1
  • Betania Ferraz Quirino
    • 2
    • 3
  • Ricardo Henrique Kruger
    • 1
  1. 1.Departamento de Biologia CelularUniversidade de BrasíliaBrasíliaBrazil
  2. 2.Embrapa-AgroenergiaBrasíliaBrazil
  3. 3.Universidade Católica de Brasília, Genomic Sciences and Biotechnology ProgramBrasíliaBrazil

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