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Molecular Methods for Detection of Antimicrobial Resistance

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  • Authors: Muna F. Anjum1, Ea Zankari2, Henrik Hasman3,4
  • Editors: Frank Møller Aarestrup5, Stefan Schwarz6, Jianzhong Shen7, Lina Cavaco8
    Affiliations: 1: Department of Bacteriology, Animal and Plant Health Agency, Surrey, United Kingdom; 2: National Food Institute, Technical University of Denmark, Lyngby, Denmark; 3: National Food Institute, Technical University of Denmark, Lyngby, Denmark; 4: Reference Laboratory for Antimicrobial Resistance and Staphylococci, Staten Serum Institut, Copenhagen, Denmark; 5: Technical University of Denmark, Lyngby, Denmark; 6: Friedrich-Loeffler-Institut, Neustadt, Germany; 7: China Agricultural University, Beijing, China; 8: Statens Serum Institut, Copenhagen, Denmark
  • Source: microbiolspec December 2017 vol. 5 no. 6 doi:10.1128/microbiolspec.ARBA-0011-2017
  • Received 04 February 2017 Accepted 07 June 2017 Published 07 December 2017
  • Muna F. Anjum, [email protected]
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  • Abstract:

    The increase in bacteria harboring antimicrobial resistance (AMR) is a global problem because there is a paucity of antibiotics available to treat multidrug-resistant bacterial infections in humans and animals. Detection of AMR present in bacteria that may pose a threat to veterinary and public health is routinely performed using standardized phenotypic methods. Molecular methods are often used in addition to phenotypic methods but are set to replace them in many laboratories due to the greater speed and accuracy they provide in detecting the underlying genetic mechanism(s) for AMR. In this article we describe some of the common molecular methods currently used for detection of AMR genes. These include PCR, DNA microarray, whole-genome sequencing and metagenomics, and matrix-assisted laser desorption ionization–time of flight mass spectrometry. The strengths and weaknesses of these methods are discussed, especially in the context of implementing them for routine surveillance activities on a global scale for mitigating the risk posed by AMR worldwide. Based on current popularity and ease of use, PCR and single-isolate whole-genome sequencing seem irreplaceable.

  • Citation: Anjum M, Zankari E, Hasman H. 2017. Molecular Methods for Detection of Antimicrobial Resistance. Microbiol Spectrum 5(6):ARBA-0011-2017. doi:10.1128/microbiolspec.ARBA-0011-2017.


1. Chan KG. 2016. Whole-genome sequencing in the prediction of antimicrobial resistance. Expert Rev Anti Infect Ther 14:617–619 http://dx.doi.org/10.1080/14787210.2016.1193005. [PubMed]
2. Hollenbeck BL, Rice LB. 2012. Intrinsic and acquired resistance mechanisms in Enterococcus. Virulence 3:421–433 http://dx.doi.org/10.4161/viru.21282. [PubMed]
3. Cox G, Wright GD. 2013. Intrinsic antibiotic resistance: mechanisms, origins, challenges and solutions. Int J Med Microbiol 303:287–292 http://dx.doi.org/10.1016/j.ijmm.2013.02.009. [PubMed]
4. Schlessinger D. 1988. Failure of aminoglycoside antibiotics to kill anaerobic, low-pH, and resistant cultures. Clin Microbiol Rev 1:54–59 http://dx.doi.org/10.1128/CMR.1.1.54. [PubMed]
5. Goodwin A, Kersulyte D, Sisson G, Veldhuyzen van Zanten SJ, Berg DE, Hoffman PS. 1998. Metronidazole resistance in Helicobacter pylori is due to null mutations in a gene ( rdxA) that encodes an oxygen-insensitive NADPH nitroreductase. Mol Microbiol 28:383–393 http://dx.doi.org/10.1046/j.1365-2958.1998.00806.x. [PubMed]
6. Huovinen P. 2001. Resistance to trimethoprim-sulfamethoxazole. Clin Infect Dis 32:1608–1614 http://dx.doi.org/10.1086/320532. [PubMed]
7. Poirel L, Potron A, Nordmann P. 2012. OXA-48-like carbapenemases: the phantom menace. J Antimicrob Chemother 67:1597–1606 http://dx.doi.org/10.1093/jac/dks121. [PubMed]
8. Boyce JM, Medeiros AA, Papa EF, O’Gara CJ. 1990. Induction of beta-lactamase and methicillin resistance in unusual strains of methicillin-resistant Staphylococcus aureus. J Antimicrob Chemother 25:73–81 http://dx.doi.org/10.1093/jac/25.1.73. [PubMed]
9. Anjum MF. 2015. Screening methods for the detection of antimicrobial resistance genes present in bacterial isolates and the microbiota. Future Microbiol 10:317–320 http://dx.doi.org/10.2217/fmb.15.2. [PubMed]
10. Saiki RK, Gelfand DH, Stoffel S, Scharf SJ, Higuchi R, Horn GT, Mullis KB, Erlich HA. 1988. Primer-directed enzymatic amplification of DNA with a thermostable DNA polymerase. Science 239:487–491 http://dx.doi.org/10.1126/science.2448875. [PubMed]
11. Arya M, Shergill IS, Williamson M, Gommersall L, Arya N, Patel HR. 2005. Basic principles of real-time quantitative PCR. Expert Rev Mol Diagn 5:209–219 http://dx.doi.org/10.1586/14737159.5.2.209. [PubMed]
12. Anjum MF, Lemma F, Cork DJ, Meunier D, Murphy N, North SE, Woodford N, Haines J, Randall LP. 2013. Isolation and detection of extended spectrum β-lactamase (ESBL)-producing enterobacteriaceae from meat using chromogenic agars and isothermal loop-mediated amplification (LAMP) assays. J Food Sci 78:M1892–M1898 http://dx.doi.org/10.1111/1750-3841.12297. [PubMed]
13. Glais L, Jacquot E. 2015. Detection and characterization of viral species/subspecies using isothermal recombinase polymerase amplification (RPA) assays. Methods Mol Biol 1302:207–225 http://dx.doi.org/10.1007/978-1-4939-2620-6_16. [PubMed]
14. Abdullahi UF, Naim R, Taib WRW, Saleh A, Muazu A, Aliyu S, Baig AA. 2015. Loop-mediated isothermal amplification (LAMP), an innovation in gene amplification: bridging the gap in molecular diagnostics; a review. Indian J Sci Technol 8:1–12.
15. Dallenne C, Da Costa A, Decré D, Favier C, Arlet G. 2010. Development of a set of multiplex PCR assays for the detection of genes encoding important beta-lactamases in Enterobacteriaceae. J Antimicrob Chemother 65:490–495 http://dx.doi.org/10.1093/jac/dkp498. [PubMed]
16. Solanki R, Vanjari L, Subramanian S, B A, E N, Lakshmi V. 2014. Comparative evaluation of multiplex PCR and routine laboratory phenotypic methods for detection of carbapenemases among Gram negative bacilli. J Clin Diagn Res 8:DC23–DC26. [PubMed]
17. Poirel L, Walsh TR, Cuvillier V, Nordmann P. 2011. Multiplex PCR for detection of acquired carbapenemase genes. Diagn Microbiol Infect Dis 70:119–123 http://dx.doi.org/10.1016/j.diagmicrobio.2010.12.002. [PubMed]
18. Shen Z, Qu W, Wang W, Lu Y, Wu Y, Li Z, Hang X, Wang X, Zhao D, Zhang C. 2010. MPprimer: a program for reliable multiplex PCR primer design. BMC Bioinformatics 11:143 http://dx.doi.org/10.1186/1471-2105-11-143. [PubMed]
19. Schwartz T, Kohnen W, Jansen B, Obst U. 2003. Detection of antibiotic-resistant bacteria and their resistance genes in wastewater, surface water, and drinking water biofilms. FEMS Microbiol Ecol 43:325–335 http://dx.doi.org/10.1111/j.1574-6941.2003.tb01073.x. [PubMed]
20. Lévesque C, Piché L, Larose C, Roy PH. 1995. PCR mapping of integrons reveals several novel combinations of resistance genes. Antimicrob Agents Chemother 39:185–191 http://dx.doi.org/10.1128/AAC.39.1.185. [PubMed]
21. Chagas TP, Alves RM, Vallim DC, Seki LM, Campos LC, Asensi MD. 2011. Diversity of genotypes in CTX-M-producing Klebsiella pneumoniae isolated in different hospitals in Brazil. Braz J Infect Dis 15:420–425 http://dx.doi.org/10.1590/S1413-86702011000500002. [PubMed]
22. Hasman H, Mevius D, Veldman K, Olesen I, Aarestrup FM. 2005. beta-Lactamases among extended-spectrum beta-lactamase (ESBL)-resistant Salmonella from poultry, poultry products and human patients in The Netherlands. J Antimicrob Chemother 56:115–121 http://dx.doi.org/10.1093/jac/dki190. [PubMed]
23. Mulvey MR, Bryce E, Boyd DA, Ofner-Agostini M, Land AM, Simor AE, Paton S. 2005. Molecular characterization of cefoxitin-resistant Escherichia coli from Canadian hospitals. Antimicrob Agents Chemother 49:358–365 http://dx.doi.org/10.1128/AAC.49.1.358-365.2005. [PubMed]
24. Liu YY, Wang Y, Walsh TR, Yi LX, Zhang R, Spencer J, Doi Y, Tian G, Dong B, Huang X, Yu LF, Gu D, Ren H, Chen X, Lv L, He D, Zhou H, Liang Z, Liu JH, Shen J. 2016. Emergence of plasmid-mediated colistin resistance mechanism MCR-1 in animals and human beings in China: a microbiological and molecular biological study. Lancet Infect Dis 16:161–168 http://dx.doi.org/10.1016/S1473-3099(15)00424-7.
25. Haenni M, Poirel L, Kieffer N, Châtre P, Saras E, Métayer V, Dumoulin R, Nordmann P, Madec JY. 2016. Co-occurrence of extended spectrum β lactamase and MCR-1 encoding genes on plasmids. Lancet Infect Dis 16:281–282 http://dx.doi.org/10.1016/S1473-3099(16)00007-4.
26. Hasman H, Hammerum AM, Hansen F, Hendriksen RS, Olesen B, Agersø Y, Zankari E, Leekitcharoenphon P, Stegger M, Kaas RS, Cavaco LM, Hansen DS, Aarestrup FM, Skov RL. 2015. Detection of mcr-1 encoding plasmid-mediated colistin-resistant Escherichia coli isolates from human bloodstream infection and imported chicken meat, Denmark 2015. Euro Surveill 20:20 http://dx.doi.org/10.2807/1560-7917.ES.2015.20.49.30085. [PubMed]
27. Anjum MF, Duggett NA, AbuOun M, Randall L, Nunez-Garcia J, Ellis RJ, Rogers J, Horton R, Brena C, Williamson S, Martelli F, Davies R, Teale C. 2016. Colistin resistance in Salmonella and Escherichia coli isolates from a pig farm in Great Britain. J Antimicrob Chemother 71:2306–2313 http://dx.doi.org/10.1093/jac/dkw149. [PubMed]
28. Duggett NA, Sayers E, AbuOun M, Ellis RJ, Nunez-Garcia J, Randall L, Horton R, Rogers J, Martelli F, Smith RP, Brena C, Williamson S, Kirchner M, Davies R, Crook D, Evans S, Teale C, Anjum MF. 2017. Occurrence and characterization of mcr-1-harbouring Escherichia coli isolated from pigs in Great Britain from 2013 to 2015. J Antimicrob Chemother 72:691–695. [PubMed]
29. Nijhuis RH, Veldman KT, Schelfaut J, Van Essen-Zandbergen A, Wessels E, Claas EC, Gooskens J. 2016. Detection of the plasmid-mediated colistin-resistance gene mcr-1 in clinical isolates and stool specimens obtained from hospitalized patients using a newly developed real-time PCR assay. J Antimicrob Chemother 71:2344–2346 http://dx.doi.org/10.1093/jac/dkw192. [PubMed]
30. Veldman K, van Essen-Zandbergen A, Rapallini M, Wit B, Heymans R, van Pelt W, Mevius D. 2016. Location of colistin resistance gene mcr-1 in Enterobacteriaceae from livestock and meat. J Antimicrob Chemother 71:2340–2342 http://dx.doi.org/10.1093/jac/dkw181. [PubMed]
31. Figueiredo R, Card RM, Nunez J, Pomba C, Mendonça N, Anjum MF, Da Silva GJ. 2016. Detection of an mcr-1-encoding plasmid mediating colistin resistance in Salmonella enterica from retail meat in Portugal. J Antimicrob Chemother 71:2338–2340 http://dx.doi.org/10.1093/jac/dkw240. [PubMed]
32. Strommenger B, Kettlitz C, Werner G, Witte W. 2003. Multiplex PCR assay for simultaneous detection of nine clinically relevant antibiotic resistance genes in Staphylococcus aureus. J Clin Microbiol 41:4089–4094 http://dx.doi.org/10.1128/JCM.41.9.4089-4094.2003. [PubMed]
33. Chung Y, Kim TS, Min YG, Hong YJ, Park JS, Hwang SM, Song KH, Kim ES, Park KU. 2016. Usefulness of multiplex real-time PCR for simultaneous pathogen detection and resistance profiling of staphylococcal bacteremia. 2016:6913860.
34. Fang H, Ataker F, Hedin G, Dornbusch K. 2008. Molecular epidemiology of extended-spectrum beta-lactamases among Escherichia coli isolates collected in a Swedish hospital and its associated health care facilities from 2001 to 2006. J Clin Microbiol 46:707–712 http://dx.doi.org/10.1128/JCM.01943-07. [PubMed]
35. Randall LP, Lemma F, Rogers JP, Cheney TE, Powell LF, Teale CJ. 2014. Prevalence of extended-spectrum-β-lactamase-producing Escherichia coli from pigs at slaughter in the UK in 2013. J Antimicrob Chemother 69:2947–2950 http://dx.doi.org/10.1093/jac/dku258. [PubMed]
36. García-Fernández S, Morosini MI, Marco F, Gijón D, Vergara A, Vila J, Ruiz-Garbajosa P, Cantón R. 2015. Evaluation of the eazyplex® SuperBug CRE system for rapid detection of carbapenemases and ESBLs in clinical Enterobacteriaceae isolates recovered at two Spanish hospitals. J Antimicrob Chemother 70:1047–1050. [PubMed]
37. Kirchner M, Lemma F, Randall L, Anjum MF. 2017. Loop-mediated isothermal amplification (LAMP) for extended spectrum β-lactamase gene detection in poultry carcase. Vet Rec 181:119. [PubMed]
38. Carter B, Wu G, Woodward MJ, Anjum MF. 2008. A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes. BMC Genomics 9:53 http://dx.doi.org/10.1186/1471-2164-9-53. [PubMed]
39. Yu X, Susa M, Knabbe C, Schmid RD, Bachmann TT. 2004. Development and validation of a diagnostic DNA microarray to detect quinolone-resistant Escherichia coli among clinical isolates. J Clin Microbiol 42:4083–4091 http://dx.doi.org/10.1128/JCM.42.9.4083-4091.2004. [PubMed]
40. Barl T, Dobrindt U, Yu X, Katcoff DJ, Sompolinsky D, Bonacorsi S, Hacker J, Bachmann TT. 2008. Genotyping DNA chip for the simultaneous assessment of antibiotic resistance and pathogenic potential of extraintestinal pathogenic Escherichia coli. Int J Antimicrob Agents 32:272–277 http://dx.doi.org/10.1016/j.ijantimicag.2008.04.020. [PubMed]
41. Call DR, Bakko MK, Krug MJ, Roberts MC. 2003. Identifying antimicrobial resistance genes with DNA microarrays. Antimicrob Agents Chemother 47:3290–3295 http://dx.doi.org/10.1128/AAC.47.10.3290-3295.2003. [PubMed]
42. Aarts HJM, Guerra B, Malorny B. 2006. Molecular methods for detection of antimicrobial resistance, p 37–48. In Aarestrup FM (ed), Antimicrobial Resistance in Bacteria of Animal Origin. ASM Press, Washington, DC.
43. Anjum MF, Mafura M, Slickers P, Ballmer K, Kuhnert P, Woodward MJ, Ehricht R. 2007. Pathotyping Escherichia coli by using miniaturized DNA microarrays. Appl Environ Microbiol 73:5692–5697 http://dx.doi.org/10.1128/AEM.00419-07. [PubMed]
44. Card R, Zhang J, Das P, Cook C, Woodford N, Anjum MF. 2013. Evaluation of an expanded microarray for detecting antibiotic resistance genes in a broad range of Gram-negative bacterial pathogens. Antimicrob Agents Chemother 57:458–465 http://dx.doi.org/10.1128/AAC.01223-12. [PubMed]
45. Card RM, Mafura M, Hunt T, Kirchner M, Weile J, Rashid MU, Weintraub A, Nord CE, Anjum MF. 2015. Impact of ciprofloxacin and clindamycin administration on Gram-negative bacteria isolated from healthy volunteers and characterization of the resistance genes they harbor. Antimicrob Agents Chemother 59:4410–4416 http://dx.doi.org/10.1128/AAC.00068-15. [PubMed]
46. Mendonça N, Figueiredo R, Mendes C, Card RM, Anjum MF, da Silva GJ. 2016. Microarray evaluation of antimicrobial resistance and virulence of Escherichia coli isolates from Portuguese poultry. Antibiotics (Basel) 5:5 http://dx.doi.org/10.3390/antibiotics5010004. [PubMed]
47. Szmolka A, Fortini D, Villa L, Carattoli A, Anjum MF, Nagy B. 2011. First report on IncN plasmid-mediated quinolone resistance gene qnrS1 in porcine Escherichia coli in Europe. Microb Drug Resist 17:567–573 http://dx.doi.org/10.1089/mdr.2011.0068. [PubMed]
48. Batchelor M, Hopkins KL, Liebana E, Slickers P, Ehricht R, Mafura M, Aarestrup F, Mevius D, Clifton-Hadley FA, Woodward MJ, Davies RH, Threlfall EJ, Anjum MF. 2008. Development of a miniaturised microarray-based assay for the rapid identification of antimicrobial resistance genes in Gram-negative bacteria. Int J Antimicrob Agents 31:440–451 http://dx.doi.org/10.1016/j.ijantimicag.2007.11.017. [PubMed]
49. Szmolka A, Anjum MF, La Ragione RM, Kaszanyitzky EJ, Nagy B. 2012. Microarray based comparative genotyping of gentamicin resistant Escherichia coli strains from food animals and humans. Vet Microbiol 156:110–118 http://dx.doi.org/10.1016/j.vetmic.2011.09.030. [PubMed]
50. Olowe OA, Choudhary S, Schierack P, Wieler LH, Makanjuola OB, Olayemi AB, Anjum M. 2013. Pathotyping bla CTX-M Escherichia coli from Nigeria. Eur J Microbiol Immunol (Bp) 3:120–125 http://dx.doi.org/10.1556/EuJMI.3.2013.2.5. [PubMed]
51. Anjum MF, Choudhary S, Morrison V, Snow LC, Mafura M, Slickers P, Ehricht R, Woodward MJ. 2011. Identifying antimicrobial resistance genes of human clinical relevance within Salmonella isolated from food animals in Great Britain. J Antimicrob Chemother 66:550–559 http://dx.doi.org/10.1093/jac/dkq498. [PubMed]
52. Kirchner M, Abuoun M, Mafura M, Bagnall M, Hunt T, Thomas C, Weile J, Anjum MF. 2013. Cefotaxime resistant Escherichia coli collected from a healthy volunteer; characterisation and the effect of plasmid loss. PLoS One 8:e84142 http://dx.doi.org/10.1371/journal.pone.0084142. [PubMed]
53. Kirchner M, Mafura M, Hunt T, Abu-Oun M, Nunez-Garcia J, Hu Y, Weile J, Coates A, Card R, Anjum MF. 2014. Antimicrobial resistance characteristics and fitness of Gram-negative fecal bacteria from volunteers treated with minocycline or amoxicillin. Front Microbiol 5:722 http://dx.doi.org/10.3389/fmicb.2014.00722. [PubMed]
54. Kirchner M, Mafura M, Hunt T, Card R, Anjum MF. 2013. Antibiotic resistance gene profiling of faecal and oral anaerobes collected during an antibiotic challenge trial. Anaerobe 23:20–22 http://dx.doi.org/10.1016/j.anaerobe.2013.07.011. [PubMed]
55. Card RM, Warburton PJ, MacLaren N, Mullany P, Allan E, Anjum MF. 2014. Application of microarray and functional-based screening methods for the detection of antimicrobial resistance genes in the microbiomes of healthy humans. PLoS One 9:e86428 http://dx.doi.org/10.1371/journal.pone.0086428. [PubMed]
56. Huehn S, La Ragione RM, Anjum M, Saunders M, Woodward MJ, Bunge C, Helmuth R, Hauser E, Guerra B, Beutlich J, Brisabois A, Peters T, Svensson L, Madajczak G, Litrup E, Imre A, Herrera-Leon S, Mevius D, Newell DG, Malorny B. 2010. Virulotyping and antimicrobial resistance typing of Salmonella enterica serovars relevant to human health in Europe. Foodborne Pathog Dis 7:523–535 http://dx.doi.org/10.1089/fpd.2009.0447. [PubMed]
57. Garneau P, Labrecque O, Maynard C, Messier S, Masson L, Archambault M, Harel J. 2010. Use of a bacterial antimicrobial resistance gene microarray for the identification of resistant Staphylococcus aureus. Zoonoses Public Health 57(Suppl 1) :94–99 http://dx.doi.org/10.1111/j.1863-2378.2010.01358.x. [PubMed]
58. Perreten V, Kadlec K, Schwarz S, Grönlund Andersson U, Finn M, Greko C, Moodley A, Kania SA, Frank LA, Bemis DA, Franco A, Iurescia M, Battisti A, Duim B, Wagenaar JA, van Duijkeren E, Weese JS, Fitzgerald JR, Rossano A, Guardabassi L. 2010. Clonal spread of methicillin-resistant Staphylococcus pseudintermedius in Europe and North America: an international multicentre study. J Antimicrob Chemother 65:1145–1154 http://dx.doi.org/10.1093/jac/dkq078. [PubMed]
59. El-Adawy H, Ahmed M, Hotzel H, Monecke S, Schulz J, Hartung J, Ehricht R, Neubauer H, Hafez HM. 2016. Characterization of methicillin-resistant Staphylococcus aureus isolated from healthy turkeys and broilers using DNA microarrays. Front Microbiol 7:2019 http://dx.doi.org/10.3389/fmicb.2016.02019. [PubMed]
60. McManus BA, Coleman DC, Deasy EC, Brennan GI, O’Connell B, Monecke S, Ehricht R, Leggett B, Leonard N, Shore AC. 2015. Comparative genotypes, staphylococcal cassette chromosome mec (SCCmec) genes and antimicrobial resistance amongst Staphylococcus epidermidis and Staphylococcus haemolyticus isolates from infections in humans and companion animals. PLoS One 10:e0138079 http://dx.doi.org/10.1371/journal.pone.0138079. [PubMed]
61. Nimmo GR, Steen JA, Monecke S, Ehricht R, Slickers P, Thomas JC, Appleton S, Goering RV, Robinson DA, Coombs GW. 2015. ST2249-MRSA-III: a second major recombinant methicillin-resistant Staphylococcus aureus clone causing healthcare infection in the 1970s. Clin Microbiol Infect 21:444–450 http://dx.doi.org/10.1016/j.cmi.2014.12.018. [PubMed]
62. Schlotter K, Huber-Schlenstedt R, Gangl A, Hotzel H, Monecke S, Müller E, Reißig A, Proft S, Ehricht R. 2014. Multiple cases of methicillin-resistant CC130 Staphylococcus aureus harboring mecC in milk and swab samples from a Bavarian dairy herd. J Dairy Sci 97:2782–2788 http://dx.doi.org/10.3168/jds.2013-7378. [PubMed]
63. Piccinini R, Tassi R, Daprà V, Pilla R, Fenner J, Carter B, Anjum MF. 2012. Study of Staphylococcus aureus collected at slaughter from dairy cows with chronic mastitis. J Dairy Res 79:249–255 http://dx.doi.org/10.1017/S002202991200009X. [PubMed]
64. Pilla R, Castiglioni V, Gelain ME, Scanziani E, Lorenzi V, Anjum M, Piccinini R. 2012. Long-term study of MRSA ST1, t127 mastitis in a dairy cow. Vet Rec 170:312 http://dx.doi.org/10.1136/vr.100510. [PubMed]
65. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup FM, Larsen MV. 2012. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 67:2640–2644 http://dx.doi.org/10.1093/jac/dks261. [PubMed]
66. Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, Rolain JM. 2014. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother 58:212–220 http://dx.doi.org/10.1128/AAC.01310-13. [PubMed]
67. Kwong JC, McCallum N, Sintchenko V, Howden BP. 2015. Whole genome sequencing in clinical and public health microbiology. Pathology 47:199–210 http://dx.doi.org/10.1097/PAT.0000000000000235. [PubMed]
68. Padmanabhan R, Mishra AK, Raoult D, Fournier PE. 2013. Genomics and metagenomics in medical microbiology. J Microbiol Methods 95:415–424 http://dx.doi.org/10.1016/j.mimet.2013.10.006. [PubMed]
69. Edwards DJ, Holt KE. 2013. Beginner’s guide to comparative bacterial genome analysis using next-generation sequence data. Microb Inform Exp 3:2 http://dx.doi.org/10.1186/2042-5783-3-2. [PubMed]
70. Gargis AS, Kalman L, Berry MW, Bick DP, Dimmock DP, Hambuch T, Lu F, Lyon E, Voelkerding KV, Zehnbauer BA, Agarwala R, Bennett SF, Chen B, Chin EL, Compton JG, Das S, Farkas DH, Ferber MJ, Funke BH, Furtado MR, Ganova-Raeva LM, Geigenmüller U, Gunselman SJ, Hegde MR, Johnson PL, Kasarskis A, Kulkarni S, Lenk T, Liu CS, Manion M, Manolio TA, Mardis ER, Merker JD, Rajeevan MS, Reese MG, Rehm HL, Simen BB, Yeakley JM, Zook JM, Lubin IM. 2012. Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotechnol 30:1033–1036 http://dx.doi.org/10.1038/nbt.2403. [PubMed]
71. Ellington MJ, Ekelund O, Aarestrup FM, Canton R, Doumith M, Giske C, Grundman H, Hasman H, Holden MT, Hopkins KL, Iredell J, Kahlmeter G, Köser CU, MacGowan A, Mevius D, Mulvey M, Naas T, Peto T, Rolain JM, Samuelsen Ø, Woodford N. 2017. The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee. Clin Microbiol Infect 23:2–22 http://dx.doi.org/10.1016/j.cmi.2016.11.012. [PubMed]
72. Thomsen MC, Ahrenfeldt J, Cisneros JL, Jurtz V, Larsen MV, Hasman H, Aarestrup FM, Lund O. 2016. A bacterial analysis platform: an integrated system for analysing bacterial whole genome sequencing data for clinical diagnostics and surveillance. PLoS One 11:e0157718 http://dx.doi.org/10.1371/journal.pone.0157718. [PubMed]
73. Clausen PT, Zankari E, Aarestrup FM, Lund O. 2016. Benchmarking of methods for identification of antimicrobial resistance genes in bacterial whole genome data. J Antimicrob Chemother 71:2484–2488 http://dx.doi.org/10.1093/jac/dkw184. [PubMed]
74. McArthur AG, Tsang KK. 2017. Antimicrobial resistance surveillance in the genomic age. Ann N Y Acad Sci 1388:78–91 http://dx.doi.org/10.1111/nyas.13289. [PubMed]
75. Sharma M, Nunez-Garcia J, Kearns AM, Doumith M, Butaye PR, Argudín MA, Lahuerta-Marin A, Pichon B, AbuOun M, Rogers J, Ellis RJ, Teale C, Anjum MF. 2016. Livestock-associated methicillin resistant Staphylococcus aureus (LA-MRSA) clonal complex (CC) 398 isolated from UK animals belong to European lineages. Front Microbiol 7:1741 http://dx.doi.org/10.3389/fmicb.2016.01741. [PubMed]
76. Doumith M, Godbole G, Ashton P, Larkin L, Dallman T, Day M, Day M, Muller-Pebody B, Ellington MJ, de Pinna E, Johnson AP, Hopkins KL, Woodford N. 2016. Detection of the plasmid-mediated mcr-1 gene conferring colistin resistance in human and food isolates of Salmonella enterica and Escherichia coli in England and Wales. J Antimicrob Chemother 71:2300–2305 http://dx.doi.org/10.1093/jac/dkw093. [PubMed]
77. Garvey MI, Pichon B, Bradley CW, Moiemen NS, Oppenheim B, Kearns AM. 2016. Improved understanding of an outbreak of meticillin-resistant Staphylococcus aureus in a regional burns centre via whole-genome sequencing. J Hosp Infect 94:401–404 http://dx.doi.org/10.1016/j.jhin.2016.09.013. [PubMed]
78. Stoesser N, Batty EM, Eyre DW, Morgan M, Wyllie DH, Del Ojo Elias C, Johnson JR, Walker AS, Peto TE, Crook DW. 2013. Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data. J Antimicrob Chemother 68:2234–2244 http://dx.doi.org/10.1093/jac/dkt180. [PubMed]
79. Bradley P, Gordon NC, Walker TM, Dunn L, Heys S, Huang B, Earle S, Pankhurst LJ, Anson L, de Cesare M, Piazza P, Votintseva AA, Golubchik T, Wilson DJ, Wyllie DH, Diel R, Niemann S, Feuerriegel S, Kohl TA, Ismail N, Omar SV, Smith EG, Buck D, McVean G, Walker AS, Peto TE, Crook DW, Iqbal Z. 2015. Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat Commun 6:10063 http://dx.doi.org/10.1038/ncomms10063. [PubMed]
80. 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 http://dx.doi.org/10.1128/AAC.00419-13. [PubMed]
81. McArthur AG, Wright GD. 2015. Bioinformatics of antimicrobial resistance in the age of molecular epidemiology. Curr Opin Microbiol 27:45–50 http://dx.doi.org/10.1016/j.mib.2015.07.004. [PubMed]
82. Inouye M, Dashnow H, Raven LA, Schultz MB, Pope BJ, Tomita T, Zobel J, Holt KE. 2014. SRST2: rapid genomic surveillance for public health and hospital microbiology labs. Genome Med 6:90 http://dx.doi.org/10.1186/s13073-014-0090-6. [PubMed]
83. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359 http://dx.doi.org/10.1038/nmeth.1923. [PubMed]
84. Hasman H, Saputra D, Sicheritz-Ponten T, Lund O, Svendsen CA, Frimodt-Møller N, Aarestrup FM. 2014. Rapid whole-genome sequencing for detection and characterization of microorganisms directly from clinical samples. J Clin Microbiol 52:139–146 http://dx.doi.org/10.1128/JCM.02452-13. [PubMed]
85. Schmieder R, Edwards R. 2012. Insights into antibiotic resistance through metagenomic approaches. Future Microbiol 7:73–89 http://dx.doi.org/10.2217/fmb.11.135. [PubMed]
86. 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 http://dx.doi.org/10.1371/journal.pone.0076079. [PubMed]
87. Li H, Durbin R. 2010. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26:589–595 http://dx.doi.org/10.1093/bioinformatics/btp698. [PubMed]
88. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079 http://dx.doi.org/10.1093/bioinformatics/btp352. [PubMed]
89. Nordahl Petersen T, Rasmussen S, Hasman H, Carøe C, Bælum J, Schultz AC, Bergmark L, Svendsen CA, Lund O, Sicheritz-Pontén T, Aarestrup FM. 2015. Meta-genomic analysis of toilet waste from long distance flights; a step towards global surveillance of infectious diseases and antimicrobial resistance. Sci Rep 5:11444 http://dx.doi.org/10.1038/srep11444. [PubMed]
90. Knudsen BE, Bergmark L. 2016. Impact of sample type and DNA isolation procedure on genomic inference of microbiome composition. mSystems 1:e00095-16. doi:10.1128/mSystems.00095-16.
91. Murray PR. 2012. What is new in clinical microbiology-microbial identification by MALDI-TOF mass spectrometry: a paper from the 2011 William Beaumont Hospital Symposium on molecular pathology. J Mol Diagn 14:419–423 http://dx.doi.org/10.1016/j.jmoldx.2012.03.007. [PubMed]
92. Hrabák J, Chudáčková E, Papagiannitsis CC. 2014. Detection of carbapenemases in Enterobacteriaceae: a challenge for diagnostic microbiological laboratories. Clin Microbiol Infect 20:839–853 http://dx.doi.org/10.1111/1469-0691.12678. [PubMed]
93. Panda A, Kurapati S, Samantaray JC, Srinivasan A, Khalil S. 2014. MALDI-TOF mass spectrometry proteomic based identification of clinical bacterial isolates. Indian J Med Res 140:770–777. [PubMed]
94. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, Suppes R, Feinstein D, Zanotti S, Taiberg L, Gurka D, Kumar A, Cheang M. 2006. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 34:1589–1596 http://dx.doi.org/10.1097/01.CCM.0000217961.75225.E9. [PubMed]
95. Frickmann H, Masanta WO, Zautner AE. 2014. Emerging rapid resistance testing methods for clinical microbiology laboratories and their potential impact on patient management. BioMed Res Int 2014:375681 http://dx.doi.org/10.1155/2014/375681. [PubMed]
96. Bauer KA, Perez KK, Forrest GN, Goff DA. 2014. Review of rapid diagnostic tests used by antimicrobial stewardship programs. Clin Infect Dis 59(Suppl 3) :S134–S145 http://dx.doi.org/10.1093/cid/ciu547. [PubMed]
97. Kostrzewa M, Sparbier K, Maier T, Schubert S. 2013. MALDI-TOF MS: an upcoming tool for rapid detection of antibiotic resistance in microorganisms. Proteomics Clin Appl 7:767–778 http://dx.doi.org/10.1002/prca.201300042. [PubMed]
98. Schaumann R, Knoop N, Genzel GH, Losensky K, Rosenkranz C, Stîngu CS, Schellenberger W, Rodloff AC, Eschrich K. 2012. A step towards the discrimination of beta-lactamase-producing clinical isolates of Enterobacteriaceae and Pseudomonas aeruginosa by MALDI-TOF mass spectrometry. Med Sci Monit 18:MT71–MT77 http://dx.doi.org/10.12659/MSM.883339. [PubMed]
99. dos Santos KV, Diniz CG, Veloso LC, de Andrade HM, Giusta MS, Pires SF, Santos AV, Apolônio AC, de Carvalho MA, Farias LM. 2010. Proteomic analysis of Escherichia coli with experimentally induced resistance to piperacillin/tazobactam. Res Microbiol 161:268–275 http://dx.doi.org/10.1016/j.resmic.2010.03.006. [PubMed]
100. Hrabák J, Chudácková E, Walková R. 2013. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry for detection of antibiotic resistance mechanisms: from research to routine diagnosis. Clin Microbiol Rev 26:103–114 http://dx.doi.org/10.1128/CMR.00058-12. [PubMed]
101. Burckhardt I, Zimmermann S. 2011. Using matrix-assisted laser desorption ionization-time of flight mass spectrometry to detect carbapenem resistance within 1 to 2.5 hours. J Clin Microbiol 49:3321–3324 http://dx.doi.org/10.1128/JCM.00287-11. [PubMed]
102. Studentova V, Papagiannitsis CC, Izdebski R, Pfeifer Y, Chudackova E, Bergerova T, Gniadkowski M, Hrabak J. 2015. Detection of OXA-48-type carbapenemase-producing Enterobacteriaceae in diagnostic laboratories can be enhanced by addition of bicarbonates to cultivation media or reaction buffers. Folia Microbiol (Praha) 60:119–129 http://dx.doi.org/10.1007/s12223-014-0349-8. [PubMed]
103. Chong PM, McCorrister SJ, Unger MS, Boyd DA, Mulvey MR, Westmacott GR. 2015. MALDI-TOF MS detection of carbapenemase activity in clinical isolates of Enterobacteriaceae spp., Pseudomonas aeruginosa, and Acinetobacter baumannii compared against the Carba-NP assay. J Microbiol Methods 111:21–23 http://dx.doi.org/10.1016/j.mimet.2015.01.024. [PubMed]
104. Wang Y, Tian GB, Zhang R, Shen Y, Tyrrell JM, Huang X, Zhou H, Lei L, Li HY, Doi Y, Fang Y, Ren H, Zhong LL, Shen Z, Zeng KJ, Wang S, Liu JH, Wu C, Walsh TR, Shen J. 2017. Prevalence, risk factors, outcomes, and molecular epidemiology of mcr-1-positive Enterobacteriaceae in patients and healthy adults from China: an epidemiological and clinical study. Lancet Infect Dis 17:390–399 http://dx.doi.org/10.1016/S1473-3099(16)30527-8. [PubMed]

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The increase in bacteria harboring antimicrobial resistance (AMR) is a global problem because there is a paucity of antibiotics available to treat multidrug-resistant bacterial infections in humans and animals. Detection of AMR present in bacteria that may pose a threat to veterinary and public health is routinely performed using standardized phenotypic methods. Molecular methods are often used in addition to phenotypic methods but are set to replace them in many laboratories due to the greater speed and accuracy they provide in detecting the underlying genetic mechanism(s) for AMR. In this article we describe some of the common molecular methods currently used for detection of AMR genes. These include PCR, DNA microarray, whole-genome sequencing and metagenomics, and matrix-assisted laser desorption ionization–time of flight mass spectrometry. The strengths and weaknesses of these methods are discussed, especially in the context of implementing them for routine surveillance activities on a global scale for mitigating the risk posed by AMR worldwide. Based on current popularity and ease of use, PCR and single-isolate whole-genome sequencing seem irreplaceable.

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Overview of different open-access bioinformatic tools for identification of antimicrobial resistance

Source: microbiolspec December 2017 vol. 5 no. 6 doi:10.1128/microbiolspec.ARBA-0011-2017

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