Metagenomic analysis on resistance genes in water and microplastics from a mariculture system

doi:10.1007/s11783-021-1438-y

Front. Environ. Sci. Eng.

2022, Vol. 16

Issue (1) : 4 https://doi.org/10.1007/s11783-021-1438-y

RESEARCH ARTICLE

Metagenomic analysis on resistance genes in water and microplastics from a mariculture system

Jian Lu^1,³, Jun Wu²(

), Jianhua Wang¹

¹. CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS); Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai 264003, China
². Yantai Research Institute, Harbin Engineering University, Yantai 264006, China
³. Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China

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Abstract

• Total 174 subtypes of ARGs were detected by metagenomic analysis.

• Chloramphenicol resistance genes were the dominant ARGs in water and microplastics.

• The abundances of MRGs were much higher than those of ARGs.

• Proteobacteria, Bacteroidetes, and Actinobacteria were the dominant phylum.

• Microplastics in mariculture system could enrich most of MRGs and some ARGs.

Microplastics existing widely in different matrices have been regarded as a reservoir for emerging contaminants. Mariculture systems have been observed to host microplastics and antibiotic resistance genes (ARGs). However, more information on proliferation of ARGs and metal resistance genes (MRGs) in mariculture system at the presence of microplastics is needed. This study used metagenomic analysis to investigate the distribution of ARGs and MRGs in water and microplastics of a typical mariculture pond. Total 18 types including 174 subtypes of ARGs were detected with the total relative abundances of 1.22/1.25 copies per 16S rRNA copy for microplastics/water. Chloramphenicol resistance genes were the dominant ARGs with the abundance of 0.35/0.42 copies per 16S rRNA copy for microplastics/water. Intergron intI1 was dominant gene among 6 detected mobile genetic elements (MGEs) with the abundance of 75.46/68.70 copies per 16S rRNA copy for water/microplastics. Total 9 types including 46 subtypes of MRGs were detected with total abundance of 5.02 × 10²/6.39 × 10² copies per 16S rRNA copy for water/ microplastics while genes resistant to copper and iron served as the dominant MRGs. Proteobacteria, Bacteroidetes, and Actinobacteria accounted for 84.2%/89.5% of total microbial community. ARGs with relatively high abundance were significantly positively related to major genera, MGEs, and MRGs. Microplastics in mariculture system could enrich most of MRGs and some ARGs to serve as potential reservoir for these pollutants. The findings of this study will provide important information on resistance gene pollution at presence of microplastics in the mariculture system for further proposing suitable strategy of environmental management.

Keywords Antibiotic resistance genes Metal resistance genes Metagenomic analysis Microplastics Mariculture

Corresponding Author(s): Jun Wu

Issue Date: 14 September 2021

Cite this article:

Jian Lu,Jun Wu,Jianhua Wang. Metagenomic analysis on resistance genes in water and microplastics from a mariculture system[J]. Front. Environ. Sci. Eng., 2022, 16(1): 4.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-021-1438-y
https://academic.hep.com.cn/fese/EN/Y2022/V16/I1/4

Fig.1 The relative abundances of different types (a) and subtypes (b) of detected ARGs in water and microplastic samples (Detailed subtypes corresponding to individual digit of x-axis in Fig. 1?(b) referred to Table S1).

Fig.2 The relative abundances of detected MGEs (a), MRG types (b), and MRG subtypes (c) in water and microplastic samples.

Fig.3 Bar plot on phylum level (a), Circos diagram on genus level (b), and Fisher’s exact test bar plot on phylum level (c) of water and microplastic samples.

Fig.4 Circos diagram (a) and Fisher’s exact test bar plot (b) of KEGG level 2 pathway in water and microplastic samples.

Fig.5 Contribution of major bacterial genera to proliferation of representative ARGs.

Fig.6 Co-occurrence network between typical ARGs and bacterial genera (a), ARGs-MGEs (b), and ARGs-MRGs (c). Red lines represent the positive correlation.

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