Water-dispersible nano-pollutions reshape microbial metabolism in type-specific manners: A metabolic and bacteriological investigation in <i>Escherichia coli</i>

doi:10.1007/s11783-022-1548-1

Front. Environ. Sci. Eng.

2022, Vol. 16

Issue (9) : 116 https://doi.org/10.1007/s11783-022-1548-1

RESEARCH ARTICLE

Water-dispersible nano-pollutions reshape microbial metabolism in type-specific manners: A metabolic and bacteriological investigation in Escherichia coli

Shuqin Liu¹, Rui Wu¹, Xi Yang¹, Shuting Fang¹, Zhangmin Xiang¹(

), Shenghong Yang²(

), Gangfeng Ouyang^1,³

¹. Guangdong Provincial Key Laboratory of Chemical Measurement and Emergency Test Technology, Guangdong Provincial Engineering Research Center for Ambient Mass Spectrometry, Institute of Analysis, Guangdong Academy of Sciences (China National Analytical Center Guangzhou), Guangzhou 510070, China
². Shandong Provincial Key Laboratory of Molecular Engineering, School of Chemistry and Chemical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
³. KLGHEI of Environment and Energy Chemistry, School of Chemistry, Sun Yat-sen University, Guangzhou 510275, China

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Abstract

• Water-dispersible nano-pollutions exhibit type-specific toxic effects on E. coli.

• Global metabolite profiling was used to characterize metabolic disruption patterns.

• Key dysregulated metabolites responsive to nano-pollution exposures were found.

• Amino acid metabolism and purine metabolism are perturbed at nano-pollutions.

Incomplete separation and recycling of nanoparticles are causing undesirable nanopollution and thus raising great concerns with regard to nanosafety. Since microorganisms are important regulator of physiological processes in many organisms, the interaction between nanopollution and microbial metabolomics and the resultant impact on the host’s health are important but unclear. To investigate how typical nanopollution perturbs microbial growth and metabolism, Escherichia coli (E. coli) in vitro was treated with six water-dispersible nanomaterials (nanoplastic, nanosilver, nano-TiO₂, nano-ZnO, semiconductor quantum dots (QDs), carbon dots (CDs)) at human-/environment-relevant concentration levels. The nanomaterials exhibited type-specific toxic effects on E. coli growth. Global metabolite profiling was used to characterize metabolic disruption patterns in the model microorganism exposed to different nanopollutants. The percentage of significant metabolites (p<0.05, VIP>1) accounted for 6%–38% of the total 293 identified metabolites in each of the nanomaterial-contaminated bacterial groups. Metabolic results also exhibited significant differences between different nanopollutants and dose levels, revealing type-specific and untypical concentration-dependent metabolic responses. Key metabolites responsive to nanopollution exposures were mainly involved in amino acid and purine metabolisms, where 5, 4, and 7 significant metabolic features were included in arginine and proline metabolism, phenylalanine metabolism, and purine metabolism, respectively. In conclusion, this study horizontally compared and demonstrated how typical nanopollution perturbs microbial growth and metabolomics in a type-specific manner, which broadens our understanding of the ecotoxicity of nanopollutants on microorganisms.

Keywords Nano-toxicity Nano-plastics Quantum dots Microbial metabolite Metabolic dysregulation

Corresponding Author(s): Zhangmin Xiang,Shenghong Yang

About author:

Tongcan Cui and Yizhe Hou contributed equally to this work.

Issue Date: 14 February 2022

Cite this article:

Shuqin Liu,Rui Wu,Xi Yang, et al. Water-dispersible nano-pollutions reshape microbial metabolism in type-specific manners: A metabolic and bacteriological investigation in Escherichia coli[J]. Front. Environ. Sci. Eng., 2022, 16(9): 116.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-022-1548-1
https://academic.hep.com.cn/fese/EN/Y2022/V16/I9/116

Fig.1 Growth curves of E. coli after exposure to six nanopollutants at different doses. All error bars represent the SD determined from eight independent assays. SD, standard deviation. Growth curves of E. coli after exposure to (a) PS nanoplastics; (b) nano-Ag; (c) nano-TiO₂; (d) nano-ZnO; (e) CDs; and (f) QDs.

Fig.2 TEM images of E. coli after exposure to six nanopollutants at different doses. PS-L, Ag-L, TiO₂-L, ZnO-L, CDs-L, and QDs-L represent microbial groups cultured with each nanomaterial at a low dose (1 mg/L), while PS-H, Ag-H, TiO₂-H, ZnO-H, CDs-H, and QDs-H represent microbial groups cultured with each nanomaterial at a high dose (20 mg/L).

Fig.3 Zeta potentials of six investigated nanomaterials in the TSB culture medium from 0 h to 30 h.

Fig.4 Up- and downregulated significant metabolic features (p<0.05, VIP>1,

| log 2 fold-change|

>1) detected by global metabolomic profiling of Escherichia coli after exposure to different nanopollutants (the percentage was calculated based on the total detected metabolic feature numbers for each condition). PS-L, Ag-L, TiO₂-L, ZnO-L, CDs-L, and QDs-L represent microbial groups cultured with each nanomaterial at a low dose (1 mg/L), while PS-H, Ag-H, TiO₂-H, ZnO-H, CDs-H, and QDs-H represent microbial groups cultured with each nanomaterial at a high dose (20 mg/L).

Fig.5 Classic Venn diagram summarizing the number of shared and distinct metabolic features of E. after exposure to six nanomaterials at a (a) low and a (b) high dose. PS-L, Ag-L, TiO₂-L, ZnO-L, CDs-L, and QDs-L represent microbial groups cultured with each nanomaterial at a low dose (1 mg/L), while PS-H, Ag-H, TiO₂-H, ZnO-H, CDs-H, and QDs-H represent microbial groups cultured with each nanomaterial at a high dose (20 mg/L).

Fig.6 Pathway impact analysis of significant metabolic pathways in E. coli after high-dose nanomaterial exposure. Data analysis was conducted using the open source platform MetaboAnalyst. Significant metabolites (p<0.05, VIP>1) of each exposure group were used for pathway analysis. The size of the bubble implies the pathway impact, and the color intensity indicates the significance of the impact. Pathway impact analysis of significant metabolic pathways in Escherichia coli after exposure to (a) PS nanoplastics; (b) nano-Ag; (c) nano-TiO₂; (d) nano-ZnO; (e) CDs; and (f) QDs.

Fig.7 Metabolites involved in arginine and proline metabolism in E. coli. The values in red are fold-changes of metabolites (*p<0.05). NS means the metabolite in the contaminated E. coli is not significant (p>0.05) compared with the control group. Metabolites in gray are undetected compounds.

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