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Frontiers of Environmental Science & Engineering
Article . 2019 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Culturomics and metagenomics: In understanding of environmental resistome

Authors: Monika Harnisz; Grażyna Płaza; Łukasz Jałowiecki; Monika Nowrotek;

Culturomics and metagenomics: In understanding of environmental resistome

Abstract

AbstractPharmaceutical 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.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    54
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
54
Top 1%
Top 10%
Top 10%
hybrid