Please wait a minute...

Frontiers of Environmental Science & Engineering

Front. Environ. Sci. Eng.    2019, Vol. 13 Issue (3) : 40
Culturomics and metagenomics: In understanding of environmental resistome
Monika Nowrotek1, Łukasz Jałowiecki1, Monika Harnisz2, Grażyna Anna Płaza3()
1. Microbiology Unit, Institute for Ecology of Industrial Areas, Kossutha 6 Str., 40-844 Katowice, Poland
2. Department of Environmental Microbiology, Faculty of Environmental Sciences, University of Warmia and Mazury, Prawocheńskiego 1 Str., 10-720 Olsztyn, Poland
3. Silesian University of Technology, Faculty of Organization and Management, Institute of Engineering Production, Roosevelta 26 Str., 41-800 Zabrze, Poland
Download: PDF(838 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

State of the art of culturomics and metagenomics to study resistome was presented.

The combination of culturomics and metagenomics approaches was proposed.

The research directions of antibiotic resistance study has been suggested.

Pharmaceutical residues, mainly antibiotics, have been called “emerging contaminants” in the environment because of their increasing frequency of detection in aquatic and terrestrial systems and their sublethal ecological effects. Most of them are undiscovered. Both human and veterinary pharmaceuticals, including antibiotics, are introduced into the environment via many different routes, including discharges from municipal wastewater treatment plants and land application of animal manure and biosolids to fertilize croplands. To gain a comprehensive understanding of the widespread problem of antibiotic resistance, modern and scientific approaches have been developed to gain knowledge of the entire antibiotic-resistant microbiota of various ecosystems, which is called the resistome. In this review, two omics methods, i.e. culturomics, a new approach, and metagenomics, used to study antibiotic resistance in environmental samples, are described. Moreover, we discuss how both omics methods have become core scientific tools to characterize microbiomes or resistomes, study natural communities and discover new microbes and new antibiotic resistance genes from environments. The combination of the method for get better outcome of both culturomics and metagenomics will significantly advance our understanding of the role of microbes and their specific properties in the environment.

Keywords Culturomics      Metagenomics      Antibiotic resistance      Resistome     
This article is part of themed collection: Environmental Antibiotics and Antibiotic Resistance (Xin Yu, Hui Li & Virender K. Sharma)
Corresponding Authors: Grażyna Anna Płaza   
Issue Date: 11 June 2019
 Cite this article:   
Monika Nowrotek,Łukasz Jałowiecki,Monika Harnisz, et al. Culturomics and metagenomics: In understanding of environmental resistome[J]. Front. Environ. Sci. Eng., 2019, 13(3): 40.
E-mail this article
E-mail Alert
Articles by authors
Monika Nowrotek
Łukasz Jałowiecki
Monika Harnisz
Grażyna Anna Płaza
Fig.1  The  history of culturomics approach in clinical microbiology and possible its applications in environmental microbiology (adopted from Lagier et al. (2018)).
Features Metagenomics Culturomics
Definition Method allowing the description of microbial composition by high-throughput sequencing Method allowing the description of the microbial composition by high-throughput culture
Methodology Pyrosequencing of 16S rRNA amplicons Use of various selective and/or enrichment culture conditions coupled to MALDI-TOF MS identification
Limitations Does not provide a strain for further studies.
Not complete population (depth bias)a.
Only detects eubacteria.
Does not provide information on enzymatic abilities and specific metabolitesb.
Detects “non-cultivable” microbes
Misses so-called “non-cultivable” microbes.
Does not directly provide information on enzymatic abilities.
Major workload
Advantages Detects “non-cultivable” microbes Detect not complete populations.
Open approach.
Detects only viable bacteriac
Rate of success Approximately 200 bacterial species/sampled Approximately 100 bacterial species/sampled
Possible future development Increased deph of sequencing because of new technology. Coupling pyroseqencing with direct metagenomics Automated detection of microbial growthe.
Automated identificationf. Miniaturization.
Other innovative culture conditions
Tab.1  Comparison  between metagenomics and culturomics (according to Greub (2012))
Fig.2  The  methodology of culturomics approach.
Fig.3  Number  of articles published on culturomics in the past 4 years (Kambouris et al., 2017).
Time Milestones
1676 Leeuwenhoek, his observations on oral microbiota
1888 Koch R., isolation of microbes on solid media
1931 Winogradsky, microbial ecology experiments
1953 J.D. Watson and F. Crick published “a radically different structure” for DNA
1977 Sanger et al. develop DNA sequencing; rRNA was proposed by Woese C. as marker for taxonomy
1980 Mullis K. develops PCR
1986 Pace et al. perform cloning DNA directly from the environmental samples
1990 Giovannoni et al. perform the first microbial community study by 16S rRNA libraries
1991 Schimdt et al. generate metagenomic library from marine plankton
1995 Healy et al. construct metagenomic libraries from a gene of interest-related environment to mining cellulases
1996 Stein et al. Describ genomic sequence bearing a 16S rRNA gene of an uncultured archaeon
1998 Handelsman et al. introduce the term “metagenomics”
2004 Sequencing of the sargasso sea by Venter et al.
2005 First next-generation sequencing machine released by Roche
2006 GA sequencer from Solexa is released
2008 Human microbiome project publication
2010 MetaHIT consortium releases the human gut microbial gene catalog
2011 PacBio RS sequencer is released
2016 MetaSUB consortium is created
Tab.2  Timeline  of the major stages in metagenomics research (modified from Escobar-Zepeda et al. (2015); Alves et al. (2018))
Fig.4  Overview  of metagenomic approaches used in antibiotic resistomes study (adopted from Monier et al. (2011); Schmieder and Edwards (2012)).
1 R A Abdallah, M Beye, A Diop, S Bakour, D Raoult, P E Fournier (2017). The impact of culturomics on taxonomy in clinical microbiology. Antonie van Leeuwenhoek, 110(10): 1327–1337 pmid: 28389704
2 T Akiyama, M C Savin (2010). Populations of antibiotic-resistant coliform bacteria change rapidly in a wastewater effluent dominated stream. The Science of the total environment, 408(24): 6192–6201 pmid: 20888028
3 E Allan (2014). Metagenomics: unrestricted access to microbial communities. Virulence, 5(3): 397–398 pmid: 24521706
4 L F Alves, C A Westmann, G L Lovate, G M V de Siqueira, T C Borelli, M E Guazzaroni (2018). Metagenomic approaches for understanding new concepts in microbial science. International Journal of Genomics, 2018: 1 pmid: 30211213
5 G C A Amos, L Zhang, P M Hawkey, W H Gaze, E M Wellington (2014). Functional metagenomic analysis reveals rivers are a reservoir for diverse antibiotic resistance genes. Veterinary Microbiology, 171(3-4): 441–447 pmid: 24636906
6 S Amrane, J C Lagier (2018). Metagenomic and clinical microbiology. Human Microbiome Journal, 9(1): 1–6
7 M F Anjum (2015). Screening methods for the detection of antimicrobial resistance genes present in bacterial isolates and the microbiota. Future Microbiology, 10(3): 317–320 pmid: 25812454
8 M Bilen, J C Dufour, J C Lagier, F Cadoret, Z Daoud, G Dubourg, D Raoult (2018). The contribution of culturomics to the repertoire of isolated human bacterial and archaeal species. Microbiome, 6(1): 94 pmid: 29793532
9 B Chen, Y Yang, X Liang, K Yu, T Zhang, X Li (2013). Metagenomic profiles of antibiotic resistance genes (ARGs) between human impacted estuary and deep ocean sediments. Environmental Science & Technology, 47(22): 12753–12760 pmid: 24125531
10 L Chistoserdova (2010). Functional metagenomics: recent advances and future challenges. Biotechnology & Genetic Engineering Reviews, 26(1): 335–352 pmid: 21415887
11 B Christgen, Y Yang, S Z Ahammad, B Li, D C Rodriquez, T Zhang, D W Graham (2015). Metagenomics shows that low-energy anaerobic-aerobic treatment reactors reduce antibiotic resistance gene levels from domestic wastewater. Environmental Science & Technology, 49(4): 2577–2584 pmid: 25603149
12 B T T Chu, M L Petrovich, A Chaudhary, D Wright, B Murphy, G Wells, R Poretsky (2018). Metagenomics reveals the impact of wastewater treatment plants on the dispersal of microorganisms and genes in aquatic sediments. Applied and Environmental Microbiology, 84(5): e02168–e17
pmid: 29269503
13 T S Crofts, A J Gasparrini, G Dantas (2017). Next-generation approaches to understand and combat the antibiotic resistome. Nature Reviews. Microbiology, 15(7): 422–434 pmid: 28392565
14 J Davies, D Davies (2010). Origins and evolution of antibiotic resistance. Microbiology Molecular Reports, 74(3): 417–433 pmid: 20805405
15 J M Di Bella, Y Bao, G B Gloor, J P Burton, G Reid (2013). High throughput sequencing methods and analysis for microbiome research. Journal of Microbiological Methods, 95(3): 401–414 pmid: 24029734
16 A H A Elbehery, R K Aziz, R Siam (2016). Antibiotic resistome: Improving detection and quantification accuracy for comparative metagenomics. OMICS: A Journal of Integrative Biology, 20(4): 229–238 pmid: 27031878
17 A Escobar-Zepeda, A Vera-Ponce de Leon, A Sanchez-Flores (2015). The road to metagenomics: From microbiology to DNA sequencing technologies and bioinformatics. Froniers in Genetics, 6: 348 pmid: 26734060
18 D Fitzpatrick, F Walsh (2016). Antibiotic resistance genes across a wide variety of metagenomes. FEMS Microbiology Ecology, 92(2): 11–21 pmid: 26738556
19 J Gatica, V Tripathi, S Green, C M Manaia, T Berendonk, D Cacace, C Merlin, N Kreuzinger, T Schwartz, D Fatta-Kassinos, L Rizzo, C U Schwermer, H Garelick, E Jurkevitch, E Cytryn (2016). High throughput analysis of integrin gene cassettes in wastewater environments. Environmental Science & Technology, 50(21): 11825–11836 pmid: 27689892
20 G Greub (2012). Culturomics: A new approach to study the human microbiome. Clinical Microbiology and Infection, 18(12): 1157–1159 pmid: 23148445
21 J Guo, J Li, H Chen, P L Bond, Z Yuan (2017). Metagenomic analysis reveals wastewater treatment plants as hotspots of antibiotic resistance genes and mobile genetic elements. Water Research, 123(3): 468–478 pmid: 28689130
22 S K Gupta, H Shin, D Han, H G Hur, T Unno (2018). Metagenomic analysis reveals the prevalence and persistence of antibiotic- and heavy metal-resistance genes in wastewater treatment plant. Journal of Microbiology (Seoul, Korea), 56(6): 408–415 pmid: 29858829
23 I Hamad, S Ranque, E I Azhar, M Yasir, A A Jiman-Fatani, H Tissot-Dupont, D Raoult, F Bittar, F Bittar (2017). Culturomics and Amplicon-based Metagenomic Approaches for the Study of Fungal Population in Human Gut Microbiota. Scientific Reports, 7(1): 16788 pmid: 29196717
24 J Handelsman, M R Rondon, S F Brady, J Clardy, R M Goodman (1998). Molecular biological access to the chemistry of unknown soil microbes: A new frontier for natural products. Chemistry & Biology, 5(10): R245–R249 pmid: 9818143
25 Q Hu, X X Zhang, S Jia, K Huang, J Tang, P Shi, L Ye, H Ren (2016). Metagenomic insights into ultraviolet disinfection effects on antibiotic resistome in biologically treated wastewater. Water Research, 101(3): 309–317 pmid: 27267479
26 P Hugon, J C Dufour, P Colson, P E Fournier, K Sallah, D Raoult (2015). A comprehensive repertoire of prokaryotic species identified in human beings. The Lancet. Infectious Diseases, 15(10): 1211–1219 pmid: 26311042
27 R W Jackson, B Vinatzer, D L Arnold, S Dorus, J Murillo (2011). The influence of the accessory genome on bacterial pathogen evolution. Mobile Genetic Elements, 1(1): 55–65 pmid: 22016845
28 Ł Jałowiecki, J Chojniak, E Dorgeloh, B Hegedusova, H Ejhed, J Magnér, G Płaza (2017). Using phenotype microarrays in the assessment of the antibiotic susceptibility profile of bacteria isolated from wastewater in on-site treatment facilities. Folia Microbiologica, 62(6): 453–461 pmid: 28451946
29 M E Kambouris, C Pavlidis, E Skoufas, M Arabatzis, M Kantzanou, A Velegraki, G P Patrinos (2018). Culturomics: A new kid on the block of OMICS to enable personalized medicine. OMICS: A Journal of Integrative Biology, 22(2), 234–245 pmid: 28402209
30 S Khelaifia, J Ch Lagier, F Bibi, E I Azhar, O Croce, R Padmanabhan, A A Jiman-Fatani, M Yasir, C Robert, C Andrieu, P E Fournier, D Raoult (2016). Microbial culturomics to map halophilic bacterium in human gut: genome sequence and description of Oceanobacillus jeddahense sp. nov. Journal of Integrative Biolology, 20(4): 248–258 pmid: 27093109
31 J C Lagier, F Armougom, M Million, P Hugon, I Pagnier, C Robert, F Bittar, G Fournous, G Gimenez, M Maraninchi, J F Trape, E V Koonin, B La Scola, D Raoult (2012). Microbial culturomics: paradigm shift in the human gut microbiome study. Clinical Microbiology and Infection, 18(12): 1185–1193 pmid: 23033984
32 J C Lagier, G Dubourg, M Million, F Cadoret, M Bilen, F Fenollar, A Levasseur, J M Rolain, P E Fournier, D Raoult (2018). Culturing the human microbiota and culturomics. Nature Reviews. Microbiology, 16(9): 540–550 pmid: 29937540
33 J C Lagier, P Hugon, S Khelaifia, P E Fournier, B La Scola, D Raoult (2015). The rebirth of culture in microbiology through the example of culturomics to study human gut microbiota. Clinical Microbiology Reviews, 28(1): 237–264 pmid: 25567229
34 J C Lagier, S Khelaifia, M T Alou, S Ndongo, N Dione, P Hugon, A Caputo, F Cadoret, S I Traore, E H Seck, G Dubourg, G Durand, G Mourembou, E Guilhot, A Togo, S Bellali, D Bachar, N Cassir, F Bittar, J Delerce, M Mailhe, D Ricaboni, M Bilen, N P Dangui Nieko, N M Dia Badiane, C Valles, D Mouelhi, K Diop, M Million, D Musso, J Abrahão, E I Azhar, F Bibi, M Yasir, A Diallo, C Sokhna, F Djossou, V Vitton, C Robert, J M Rolain, B La Scola, P E Fournier, A Levasseur, D Raoult (2016). Culture of previously uncultured members of the human gut microbiota by culturomics. Nature Microbiology, 1(2): 16203 pmid: 27819657
35 K N Lam, J Cheng, K Engel, J D Neufeld, T C Charles (2015). Current and future resources for functional metagenomics. Frontiers in Microbiology, 6: article1196 pmid: 26579102
36 V F Lanza, F Baquero, J L Martínez, R Ramos-Ruíz, B González-Zorn, A Andremont, A Sánchez-Valenzuela, S D Ehrlich, S Kennedy, E Ruppé, W van Schaik, R J Willems, F de la Cruz, T M Coque (2018). In-depth resistome analysis by targeted metagenomics. Microbiome, 6(1): 11 pmid: 29335005
37 J Lee, J H Jeon, J Shin, H M Jang, S Kim, M S Song, Y M Kim (2017). Quantitative and qualitative changes in antibiotic resistance genes after passing through treatment processes in municipal wastewater treatment plants. Science of the Total Environment, 605-606: 906–914 pmid: 28686994
38 J R Lefkowitz, M Duran (2009). Changes in antibiotic resistance patterns of Escherichia coli during domestic wastewater treatment. Water Environment Research, 81(9): 878–885 pmid: 19860144
39 E Luby, A M Ibekwe, J Zilles, A Pruden (2016). Molecular methods for assessment of antibiotic resistance in agricultural ecosystems: prospects and challenges. Journal of Environmental Quality, 45(2): 441–453 pmid: 27065390
40 Y Ma, JW Metch, Y Yang, A Pruden, T Zhang (2016). Shift in antibiotic resistance gene profiles associated with nanosilver during wastewater treatment. FEMS Microbiology Ecology, 92(3): pii: fiw022 pmid: 26850160
41 G A March-Rosselló (2017). Rapid methods for detection of bacterial resistance to antibiotics. Enfermedades Infecciosas y Microbiologia Clinica, 35(3): 182–188 pmid: 28109552
42 J L Martínez, T M Coque, V F Lanza, F de la Cruz, F Baquero (2017). Genomic and metagenomic technologies to explore the antibiotic resistance mobilome. Annals of the New York Academy of Sciences, 1388(1): 26–41 pmid: 27861983
43 L Masucci, G Quaranta, D Nagel, S Primus, L Romano, R Graffeo, G Ianiro, A Gasbarrini, G Cammarota, M Sanguinetti (2017). Culturomics: Bacterial species isolated in 3 healthy donors for faecal microbiota transplantation in Clostridium difficileinfection. Microbiologia Medica, 32: 6510
44 J E McLain, E Cytryn, L M Durso, S Young (2016). Culture-based methods for detection of antibiotic resistance in agroecosystems: Advantages, challenges, and gaps in knowledge. Journal of Environmental Quality, 45(2): 432–440 pmid: 27065389
45 R R Miller, V Montoya, J L Gardy, D M Patrick, P Tang (2013). Metagenomics for pathogen detection in public health. Genome Medicine, 5(9): No article: 81
46 M Mohammadali, J Davies(2018). Antimicrobial resistance genes and wastewater treatment. In: Keen P L, Fugère R, eds. Antimicrobial Resistance in Wastewater Treatment Processes. 1st ed. Hoboken: John Wiley & Sons, Inc., 1–14
47 J M Monier, S Demanèche, T O Delmont, A Mathieu, T M Vogel, P Simonet (2011). Metagenomic exploration of antibiotic resistance in soil. Current Opinion in Microbiology, 14(3): 229–235 pmid: 21601510
48 P Mullany (2014). Functional metagenomics for the investigation of antibiotic resistance. Virulence, 5(3): 443–447 pmid: 24556726
49 M Nagarajan. (2018). Metagenomics. Perspectives, Methods, and Applications. 1st ed. London: Academic Press, Elsevier, , 1– 10
50 K Pärnänen, A Karkman, M Tamminen, C Lyra, J Hultman, L Paulin, M Virta (2016). Evaluating the mobility potential of antibiotic resistance genes in environmental resistomes without metagenomics. Scientific Reports, 6(1): 35790 pmid: 27767072
51 J A Perry, E L Westman, G D Wright (2014). The antibiotic resistome: What’s new? Current Opinion in Microbiology, 21: 45–50 pmid: 25280222
52 G Płaza, A Turek, R Szczygłowska (2013). Characterization of E. coli strains obtained from wastewater effluent. International Journal of Environmental of Research, 2(1): 67–74
53 L Rizzo, C Manaia, C Merlin, T Schwartz, C Dagot, M C Ploy, I Michael, D Fatta-Kassinos (2013). Urban wastewater treatment plants as hotspots for antibiotic resistant bacteria and genes spread into the environment: A review. The Science of the total environment, 447: 345–360 pmid: 23396083
54 G E Rosso, J A Muday, J F Curran (2018). Tools for Metagenomic Analysis at Wastewater Treatment Plants: Application to a Foaming Episode. Water environment research: A research publication of the Water Environment Federation, 90(3): 258–268 pmid: 28962671
55 T M Schmidt, E F DeLong, N R Pace (1991). Analysis of a marine picoplankton community by 16S rRNA gene cloning and sequencing. Journal of Bacteriology, 173(14): 4371–4378 pmid: 2066334
56 R Schmieder, R Edwards (2012). Insights into antibiotic resistance through metagenomic approaches. Future Microbiology, 7(1): 73–89 pmid: 22191448
57 E H Seck, A Diop, N Armstrong, J Delerce, P E Fournier, D Raoult, S Khelaifia (2018). Microbial culturomics to isolate halophilic bacteria from table salt: genome sequence and description of the moderately halophilic bacterium Bacillus salis sp. nov. New Microbes and New Infections, 23(1): 28–38 pmid: 29707210
58 J Tang, Y Bu, X X Zhang, K Huang, X He, L Ye, Z Shan, H Ren (2016). Metagenomic analysis of bacterial community composition and antibiotic resistance genes in a wastewater treatment plant and its receiving surface water. Ecotoxicology and Environmental Safety, 132(2): 260–269 pmid: 27340885
59 J C Venter, K Remington, J F Heidelberg, A L Halpern, D Rusch, J A Eisen, D Wu, I Paulsen, K E Nelson, W Nelson, D E Fouts, S Levy, A H Knap, M W Lomas, K Nealson, O White, J Peterson, J Hoffman, R Parsons, H Baden-Tillson, C Pfannkoch, Y H Rogers, H O Smith (2004). Environmental genome shotgun sequencing of the Sargasso Sea. Science, 304(5667): 66–74 pmid: 15001713
60 Z Wang, X X Zhang, K Huang, Y Miao, P Shi, B Liu, C Long, A Li (2013). Metagenomic profiling of antibiotic resistance genes and mobile genetic elements in a tannery wastewater treatment plant. PLoS One, 8(10): e76079 pmid: 24098424
61 K Q Xiao, B Li, L Ma, P Bao, X Xue Zhou, T Zhang, Y G Zhu (2016). Metagenomic profiles of antibiotic resistance genes in paddy soils from South China. FEMS Microbiology Ecology, 92: fiw023 pmid: 26850156
62 Y Yang, B Li, F Ju, T Zhang (2013). Exploring variation of antibiotic resistance genes in activated sludge over a four-year period through a metagenomic approach. Environmental Science & Technology, 47(18): 10197–10205 pmid: 23919449
Related articles from Frontiers Journals
[1] Lian Yang, Qinxue Wen, Zhiqiang Chen, Ran Duan, Pan Yang. Impacts of advanced treatment processes on elimination of antibiotic resistance genes in a municipal wastewater treatment plant[J]. Front. Environ. Sci. Eng., 2019, 13(3): 32-.
[2] Qiaowen Tan, Weiying Li, Junpeng Zhang, Wei Zhou, Jiping Chen, Yue Li, Jie Ma. Presence, dissemination and removal of antibiotic resistant bacteria and antibiotic resistance genes in urban drinking water system: A review[J]. Front. Environ. Sci. Eng., 2019, 13(3): 36-.
[3] Virender K. Sharma, Xin Yu, Thomas J. McDonald, Chetan Jinadatha, Dionysios D. Dionysiou, Mingbao Feng. Elimination of antibiotic resistance genes and control of horizontal transfer risk by UV-based treatment of drinking water: A mini review[J]. Front. Environ. Sci. Eng., 2019, 13(3): 37-.
[4] Menglu Zhang, Sheng Chen, Xin Yu, Peter Vikesland, Amy Pruden. Degradation of extracellular genomic, plasmid DNA and specific antibiotic resistance genes by chlorination[J]. Front. Environ. Sci. Eng., 2019, 13(3): 38-.
[5] Yangyang Yu, Xiaolin Zhu, Guanlan Wu, Chengzhi Wang, Xing Yuan. Analysis of antibiotic resistance of Escherichia coli isolated from the Yitong River in North-east China[J]. Front. Environ. Sci. Eng., 2019, 13(3): 39-.
[6] Gastón Azziz, Matías Giménez, Héctor Romero, Patricia M. Valdespino-Castillo, Luisa I. Falcón, Lucas A. M. Ruberto, Walter P. Mac Cormack, Silvia Batista. Detection of presumed genes encoding beta-lactamases by sequence based screening of metagenomes derived from Antarctic microbial mats[J]. Front. Environ. Sci. Eng., 2019, 13(3): 44-.
[7] Xuan Zhu, Chengsong Ye, Yuxin Wang, Lihua Chen, Lin Feng. Assessment of antibiotic resistance genes in dialysis water treatment processes[J]. Front. Environ. Sci. Eng., 2019, 13(3): 45-.
[8] Yuchen PANG,Jingjing HUANG,Jinying XI,Hongying HU,Yun ZHU. Effect of ultraviolet irradiation and chlorination on ampicillin-resistant Escherichia coli and its ampicillin resistance gene[J]. Front. Environ. Sci. Eng., 2016, 10(3): 522-530.
Full text