Hormetic effects of metal ions upon V. fischeri and the application of a new parameter for the quantitative assessment of hormesis

Zou, Xiaoming; Xiao, Xiaoyu; He, Yu; Hu, Lijun; Hu, Cui; Huang, Xiangfeng

doi:10.1016/j.jhazmat.2016.09.045

Cited by 22 publications

(9 citation statements)

References 32 publications

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“…One-way analysis of variance (ANOVA) at level p 50 and K F among SAs used, which was further verified by hierarchical cluster analysis. The possible relationship between overall dissipation behavior and dissipation factors and the relative importance of individual factors to overall dissipation were explored by PLS analysis aided with software SIMCA. ,, The abundance of taxonomic and functional profiles was visualized by a heatmap, and both principal component analysis (PCA) and nonmetric multidimensional scaling analysis (NMDS) were applied to group the samples. To compare the significant difference of taxonomic and functional profiles between different samples, STAMP software was employed. , Spearman correlation analysis was performed on the basis of abundance of taxonomic and functional profiles that were putatively involved in SA microbial degradation.…”

Section: Methodsmentioning

confidence: 99%

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

Rong

Zhou

et al. 2020

J. Agric. Food Chem.

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Sulfonamides (SAs) are widespread in soils, and their dissipation behavior is important for their fate, risk assessment, and pollution control. In this work, we investigated the dissipation behavior of different SAs in a soil under aerobic condition, focusing on revealing the relationship between overall dissipation (without sterilization and in dark) and individual abiotic (sorption, hydrolysis)/biotic (with sterilization and in dark) factors and taxonomy/function of microbiomes. The results showed that dissipation of all SAs in the soil followed the pseudo-first-order kinetic model with dissipation time at 50% removal (DT50) of 2.16–15.27 days. Based on, experimentally, abiotic/biotic processes and, theoretically, partial least-squares modeling, a relationship between overall dissipation and individual abiotic/biotic factors was developed with microbial degradation as the dominant contributor. Metagenomic analysis showed that taxonomic genera like Bradyrhizobium/Sphingomonas/Methyloferula and functions like CAZy family GT51/GH23/GT2, eggNOG category S, KEGG pathway ko02024/ko02010, and KEGG ortholog K01999/K03088 are putatively involved in SA microbial degradation in soil. Spearman correlation suggests abundant genera being multifunctional. This study provides some new insights into SA dissipation and can be applied to other antibiotics/soils in the future.

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Section: Methodsmentioning

confidence: 99%

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

Rong

Zhou

et al. 2020

J. Agric. Food Chem.

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“…For instance, the joint effects of the nZnO and pollutants were investigated in acute toxicity test, and the results showed antagonism [23]; the additive effect between (nZnO) with nano-copper oxide (nCuO) was identified in the mixture toxic effects upon Scenedesmus obliquus [24]; the antagonistic effect between nZnO with Pb was observed in the mixture toxic effects upon Leucaena leucocephala seedling [25]. However, the joint effects between nZnO and chemicals with different MOA have been rarely investigated, and the predictive powers of the concentration addition (CA) and independent action (IA) models have not been verified, although CA and IA models were extensively employed to predict the toxic effects of mixtures [26].…”

Section: Introductionmentioning

confidence: 99%

“…Vibrio fischeri, the marine bacterium, has been widely used as the test organism for investigating the toxicity of pollutants, including nZnO [27], antibiotics [26,28], and heavy metals [29]. In recent years, reactive compounds (i.e., antibiotics) and narcotic compounds (i.e., lignin phenols) were frequently detected in Yangtze River Basin and reported in many previous studies [30,31].…”

Section: Introductionmentioning

confidence: 99%

Mixture toxicity of zinc oxide nanoparticle and chemicals with different mode of action upon Vibrio fischeri

Fen

Xiao

et al. 2020

Environ Sci Eur

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Background: Zinc oxide nanoparticle (nZnO) and chemicals with different mode of action (MOA, i.e., narcotic and reactive) were frequently detected in the Yangtze River. Organisms are typically exposed to mixtures of nZnO and other chemicals rather than individual nZnO. Toxicity of nZnO is caused by the dissolution of Zn 2+ , which has been proved in the field of single toxicity. However, it is still unclear whether the released Zn 2+ plays a critical role in the nZnO toxicity of nZnO-chemicals mixtures. In the present study, the binary mixture toxicity of nZnO/Zn 2+ and chemicals with different MOA was investigated in acute (15 min) and chronic (12 h) toxicity test upon Vibrio fischeri (V. fischeri). The joint effects of nZnO and tested chemicals were explored. Moreover, two classic models, concentration addition (CA) and independent action (IA) were applied to predict the toxicity of mixtures. Results: The difference of toxicity unit (TU) values between the mixtures of Zn 2+-chemicals with those of nZnOchemicals was not significant (P > 0.05), not only in acute toxicity test but also in chronic toxicity test. The antagonistic or additive effects for nZnO-chemicals can be observed in most mixtures, with the TU values ranging from 0.75 to 1.77 and 0.47 to 2.45 in acute toxicity test and chronic test, respectively. We also observed that the prediction accuracy of CA and IA models was not very well in the mixtures where the difference between the toxicity ratios of the components was small (less than about 10), with the mean absolute percentage error (MAPE) values ranging from 0.14 to 0.67 for CA model and 0.17-0.51 for IA model, respectively. Conclusion: We found that the dissolved Zn 2+ mainly accounted for the nZnO toxicity in the mixtures of nZnOchemicals, and the joint effects of these mixtures were mostly antagonism and additivity. CA and IA models were unsuitable for predicting the mixture toxicity of nZnO-chemicals at their equitoxic ratios.

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“…tax rate affecting tax revenue 4 ). In recent years, significant research has shown that hormesis can be induced by many chemicals, especially some poisonous and harmful substances such as persistent organic pollutants, 5 pesticides, 6 metal ions, 7 antibiotic 8 and ionic liquids. 9,10 The quantitative description of the hormetic concentration–response relationship has become an important step for gaining a better understanding of hormesis and the influence and meaning of hormesis in environmental risk assessment.…”

Section: Introductionmentioning

confidence: 99%

JSFit: a method for the fitting and prediction of J- and S-shaped concentration–response curves

Wang

Liu

2018

RSC Adv.

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Hormetic effects of metal ions upon V. fischeri and the application of a new parameter for the quantitative assessment of hormesis

Cited by 22 publications

References 32 publications

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

Dissipation of Sulfonamides in Soil Emphasizing Taxonomy and Function of Microbiomes by Metagenomic Analysis

Mixture toxicity of zinc oxide nanoparticle and chemicals with different mode of action upon Vibrio fischeri

JSFit: a method for the fitting and prediction of J- and S-shaped concentration–response curves

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