Journal List > Hanyang Med Rev > v.38(2) > 1111606

Hanyang Med Rev. 2018 Jun;38(2):73-79. Korean.
Published online Jun 30, 2018.  https://doi.org/10.7599/hmr.2018.38.2.73
© 2018 Hanyang University College of Medicine · Institute of Medical Science
Human Resistome Study with Metagenomic Sequencing Data
Jae Hong Shin,1 and Mina Rho1,2
1Department of Computer Science and Engineering, College of Engineering, Hanyang University, Seoul, Korea.
2Department of Biomedical Informatics, Hanyang University, Seoul, Korea.

Corresponding Author: Mina Rho. Department of Computer Science and Engineering, College of Engineering, Hanyang University, Department of Biomedical Informatics, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea. Tel: +82-2-2220-2379 Fax: +82-2-2220-1886 Email: minarho@hanyang.ac.kr
Received Apr 03, 2018; Revised May 05, 2018; Accepted Jun 12, 2018.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Abstract

With the introduction of synthetic antibiotics, many lives including humans and animals have been saved against bacterial infection. An increasing level of antibiotics use, however, raises serious problems of multi-drug resistance and transferring of resistance genes across different environments and countries. Advances in high-throughput sequencing technology and efficient bioinformatics methods allow us to perform a large-scale screening and analysis of resistomes in the human and environmental microbiomes. Recent studies on human microbiomes have revealed a diverse distribution of resistance genes and their transferring activities in the communities. This review discusses recent progresses in metagenomic approaches to identify resistance genes in the human microbiome, including genomic sequence search and functional metagenomics methods. Using Rifampicin ADP-ribosyltransferase as an example, an integrative approach that analyzes the sequences and three-dimensional structures of the proteins derived from resistance genes is also introduced.

Keywords: Human microbiome; Metagenome; Antibiotics resistance

Figures


Fig. 1
Chemical structure of rifamycin families.
Click for larger image


Fig. 2
Mutiple sequence alignment of rifampicin ADP-ribosyltransferase se quencs and three-dimentional X-ray structure of Arr-ms and rifampicin (PDBID: 2HW2).
Click for larger image

Tables


Table 1
Summary of microbiome studies characterizing human and environmental resistomes
Click for larger image

References
1. D'Costa VM, King CE, Kalan L, Morar M, Sung WW, Schwarz C, et al. Antibiotic resistance is ancient. Nature 2011;477:457–461.
2. Bhullar K, Waglechner N, Pawlowski A, Koteva K, Banks ED, Johnston MD, et al. Antibiotic Resistance Is Prevalent in an Isolated Cave Microbiome. PLOS ONE 2012;7:e34953
3. Ochman H, Lawrence JG, Groisman EA. Lateral gene transfer and the nature of bacterial innovation. Nature 2000;405:299–304.
4. Brown ED, Wright GD. Antibacterial drug discovery in the resistance era. Nature 2016;529:336.
5. Van Boeckel TP, Gandra S, Ashok A, Caudron Q, Grenfell BT, Levin SA, et al. Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data. The Lancet Infectious Diseases 2014;14:742–750.
6. Spellberg B, Gilbert DN. The future of antibiotics and resistance: a tribute to a career of leadership by John Bartlett. Clin Infect Dis 2014;59 Suppl 2:S71–S75.
7. Stogios PJ, Cox G, Spanogiannopoulos P, Pillon MC, Waglechner N, Skarina T, et al. Rifampin phosphotransferase is an unusual antibiotic resistance kinase. Nat Commun 2016;7:11343.
8. Qi X, Lin W, Ma M, Wang C, He Y, He N, et al. Structural basis of rifampin inactivation by rifampin phosphotransferase. Proc Natl Acad Sci U S A 2016;113:3803–3808.
9. Baysarowich J, Koteva K, Hughes DW, Ejim L, Griffiths E, Zhang K, et al. Rifamycin antibiotic resistance by ADP-ribosylation: Structure and diversity of Arr. Proc Natl Acad Sci U S A 2008;105:4886–4891.
10. Koch A, Mizrahi V, Warner DF. The impact of drug resistance on Mycobacterium tuberculosis physiology: what can we learn from rifampicin. Emerg Microbes Infect 2014;3:e17
11. Stapleton PD, Taylor PW. Methicillin resistance in Staphylococcus aureus: mechanisms and modulation. Science Progress 2002;85:57–72.
12. Blair JMA, Webber MA, Baylay AJ, Ogbolu DO, Piddock LJV. Molecular mechanisms of antibiotic resistance. Nature Reviews Microbiology 2014;13:42.
13. Knapp CW, Dolfing J, Ehlert PAI, Graham DW. Evidence of Increasing Antibiotic Resistance Gene Abundances in Archived Soils since 1940. Environmental Science & Technology 2010;44:580–587.
14. Andersson DI, Hughes D. Persistence of antibiotic resistance in bacterial populations. FEMS Microbiol Rev 2011;35:901–911.
15. Shoemaker NB, Vlamakis H, Hayes K, Salyers AA. Evidence for extensive resistance gene transfer among Bacteroides spp. and among Bacteroides and other genera in the human colon. Appl Environ Microbiol 2001;67:561–568.
16. von Wintersdorff CJH, Penders J, Stobberingh EE, Lashof AMLO, Hoebe CJPA, Savelkoul PHM, et al. High Rates of Antimicrobial Drug Resistance Gene Acquisition after International Travel, the Netherlands. Emerging Infectious Diseases 2014;20:649–657.
17. Walsh C. Molecular mechanisms that confer antibacterial drug resistance. Nature 2000;406:775–781.
18. Alekshun MN, Levy SB. Molecular Mechanisms of Antibacterial Multidrug Resistance. Cell 2007;128:1037–1050.
19. Ventola CL. The Antibiotic Resistance Crisis: Part 1: Causes and Threats. Pharmacy and Therapeutics 2015;40:277–283.
20. Ventola CL. The Antibiotic Resistance Crisis: Part 2: Management Strategies and New Agents. Pharmacy and Therapeutics 2015;40:344–352.
21. Zankari E, Hasman H, Kaas RS, Seyfarth AM, Agerso Y, Lund O, et al. Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing. J Antimicrob Chemother 2013;68:771–777.
22. Anjum MF. Screening methods for the detection of antimicrobial resistance genes present in bacterial isolates and the microbiota. Future Microbiology 2015;10:317–320.
23. Zhang XX, Zhang T, Fang HH. Antibiotic resistance genes in water environment. Appl Microbiol Biotechnol 2009;82:397–414.
24. Rappe MS, Giovannoni SJ. The uncultured microbial majority. Annu Rev Microbiol 2003;57:369–394.
25. Anantharaman K, Brown CT, Hug LA, Sharon I, Castelle CJ, Probst AJ, et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun 2016;7:13219.
26. Adu-Oppong B, Gasparrini AJ, Dantas G. Genomic and functional techniques to mine the microbiome for novel antimicrobials and antimicrobial resistance genes. Ann N Y Acad Sci 2017;1388:42–58.
27. Antonopoulos DA, Assaf R, Aziz RK, Brettin T, Bun C, Conrad N, et al. PATRIC as a unique resource for studying antimicrobial resistance. Briefings in Bioinformatics 2017:bbx083-bbx.
28. Lee D, Das S, Dawson NL, Dobrijevic D, Ward J, Orengo C. Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases. PLOS Computational Biology 2016;12:e1004926
29. Philippon A, Slama P, Dény P, Labia R. A Structure-Based Classification of Class A β-Lactamases, a Broadly Diverse Family of Enzymes. Clinical Microbiology Reviews 2016;29:29–57.
30. Lam KN, Cheng J, Engel K, Neufeld JD, Charles TC. Current and future resources for functional metagenomics. Front Microbiol 2015;6:1196.
31. Crofts TS, Gasparrini AJ, Dantas G. Next-generation approaches to understand and combat the antibiotic resistome. Nat Rev Microbiol 2017;15:422–434.
32. dos Santos DFK, Istvan P, Quirino BF, Kruger RH. Functional Metagenomics as a Tool for Identification of New Antibiotic Resistance Genes from Natural Environments. Microbial Ecology 2017;73:479–491.
33. Sommer MOA, Dantas G, Church GM. Functional characterization of the antibiotic resistance reservoir in the human microflora. Science 2009;325:1128–1131.
34. Riesenfeld CS, Goodman RM, Handelsman J. Uncultured soil bacteria are a reservoir of new antibiotic resistance genes. Environ Microbiol 2004;6:981–989.
35. Allen HK, Moe LA, Rodbumrer J, Gaarder A, Handelsman J. Functional metagenomics reveals diverse β-lactamases in a remote Alaskan soil. The ISME journal 2009;3:243–251.
36. Liu B, Pop M. ARDB--Antibiotic Resistance Genes Database. Nucleic Acids Res 2009;37:D443–D447.
37. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother 2013;57:3348–3357.
38. Gibson MK, Forsberg KJ, Dantas G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. Isme j 2015;9:207–216.
39. Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 2017;45:D566–Dd73.
40. Gibson MK, Forsberg KJ, Dantas G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. The ISME Journal 2015;9:207–216.
41. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, et al. Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 2012;67:2640–2644.
42. Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, et al. ARG-ANNOT, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother 2014;58:212–220.
43. Arango-Argoty G, Garner E, Pruden A, Heath LS, Vikesland P, Zhang L. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome 2018;6:23.
44. Hartmann G, Honikel KO, Knüsel F, Nüesch J. The specific inhibition of the DNA-directed RNA synthesis by rifamycin. Biochim Biophys Acta 1967;145:843–844.
45. Munita JM, Arias CA. Mechanisms of Antibiotic Resistance. Microbiol Spectr 2016;4 [doi: 10.1128/microbiolspec.VMBF-0016-2015]
46. Stogios PJ, Cox G, Spanogiannopoulos P, Pillon MC, Waglechner N, Skarina T, et al. Rifampin phosphotransferase is an unusual antibiotic resistance kinase. Nat Commun 2016;7:11343.
47. Baysarowich J, Koteva K, Hughes DW, Ejim L, Griffiths E, Zhang K, et al. Rifamycin antibiotic resistance by ADP-ribosylation: Structure and diversity of Arr. Proc Natl Acad Sci U S A 2008;105:4886–4891.
48. Dabbs ER, Yazawa K, Mikami Y, Miyaji M, Morisaki N, Iwasaki S, et al. Ribosylation by mycobacterial strains as a new mechanism of rifampin inactivation. Antimicrob Agents Chemother 1995;39:1007–1009.
49. Hu Y, Yang X, Qin J, Lu N, Cheng G, Wu N, et al. Metagenome-wide analysis of antibiotic resistance genes in a large cohort of human gut microbiota. Nat Commun 2013;4:2151.
50. Ghosh TS, Gupta SS, Nair GB, Mande SS. In Silico Analysis of Antibiotic Resistance Genes in the Gut Microflora of Individuals from Diverse Geographies and Age-Groups. PLOS ONE 2013;8:e83823
51. Yang Z, Guo Z, Qiu C, Li Y, Feng X, Liu Y, et al. Preliminary analysis showed country-specific gut resistome based on 1267 feces samples. Gene 2016;581:178–182.
52. Bengtsson-Palme J, Angelin M, Huss M, Kjellqvist S, Kristiansson E, Palmgren H, et al. The Human Gut Microbiome as a Transporter of Antibiotic Resistance Genes between Continents. Antimicrobial Agents and Chemotherapy 2015;59:6551.
53. Gibson MK, Wang B, Ahmadi S, Burnham C-AD, Tarr PI, Warner BB, et al. Developmental dynamics of the preterm infant gut microbiota and antibiotic resistome. Nat Microbiol 2016;1:16024.
54. Pérez-Cobas AE, Artacho A, Knecht H, Ferrús ML, Friedrichs A, Ott SJ, et al. Differential Effects of Antibiotic Therapy on the Structure and Function of Human Gut Microbiota. PLOS ONE 2013;8:e80201
55. Oh J, Byrd AL, Deming C, Conlan S, Program NCS, Barnabas B, et al. Biogeography and individuality shape function in the human skin metagenome. Nature 2014;514:59.