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Concentration Addition, Independent Action, and Quantitative Structure–Activity Relationships for Chemical Mixture Toxicities of the Disinfection By products of Haloacetic Acids on the Green Alga Raphidocelis subcapitata

The potential toxicity of haloacetic acids (HAAs), common disinfection by products (DBPs), has been widely studied; but their combined effects on freshwater green algae remain poorly understood. The present study was conducted to investigate the toxicological interactions of HAA mixtures in the gree...

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Published in:Environmental toxicology and chemistry 2021-05, Vol.40 (5), p.1431-1442
Main Authors: Qin, Li‐Tang, Liu, Min, Zhang, Xin, Mo, Ling‐Yun, Zeng, Hong‐Hu, Liang, Yan‐Peng
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description The potential toxicity of haloacetic acids (HAAs), common disinfection by products (DBPs), has been widely studied; but their combined effects on freshwater green algae remain poorly understood. The present study was conducted to investigate the toxicological interactions of HAA mixtures in the green alga Raphidocelis subcapitata and predict the DBP mixture toxicities based on concentration addition, independent action, and quantitative structure–activity relationship (QSAR) models. The acute toxicities of 6 HAAs (iodoacetic acid [IAA], bromoacetic acid [BAA], chloroacetic acid [CAA], dichloroacetic acid [DCAA], trichloroacetic acid [TCAA], and tribromoacetic acid [TBAA]) and their 68 binary mixtures to the green algae were analyzed in 96‐well microplates. Results reveal that the rank order of the toxicity of individual HAAs is CAA > IAA ≈ BAA > TCAA > DCAA > TBAA. With concentration addition as the reference additive model, the mixture effects are synergetic in 47.1% and antagonistic in 25%, whereas the additive effects are only observed in 27.9% of the experiments. The main components that induce synergism are DCAA, IAA, and BAA; and CAA is the main component that causes antagonism. Prediction by concentration addition and independent action indicates that the 2 models fail to accurately predict 72% mixture toxicity at an effective concentration level of 50%. Modeling the mixtures by QSAR was established by statistically analyzing descriptors for the determination of the relationship between their chemical structures and the negative logarithm of the 50% effective concentration. The additive mixture toxicities are accurately predicted by the QSAR model based on 2 parameters, the octanol–water partition coefficient and the acid dissociation constant (pKa). The toxicities of synergetic mixtures can be interpreted with the total energy (ET) and pKa of the mixtures. Dipole moment and ET are the quantum descriptors that influence the antagonistic mixture toxicity. Therefore, in silico modeling may be a useful tool in predicting disinfection by‐product mixture toxicities. Environ Toxicol Chem 2021;40:1431–1442. © 2021 SETAC The toxicological interactions of disinfection by‐product mixtures on green algae. BAA = bromoacetic acid; CAA = chloroacetic acid; DBP = disinfection by‐product; DCAA = dichloroacetic acid; IAA = iodoacetic acid; pEC50 = predicted median effect concentration; QSAR = quantitative structure–activity relationship; TBAA = tribromoacetic acid;
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The main components that induce synergism are DCAA, IAA, and BAA; and CAA is the main component that causes antagonism. Prediction by concentration addition and independent action indicates that the 2 models fail to accurately predict 72% mixture toxicity at an effective concentration level of 50%. Modeling the mixtures by QSAR was established by statistically analyzing descriptors for the determination of the relationship between their chemical structures and the negative logarithm of the 50% effective concentration. The additive mixture toxicities are accurately predicted by the QSAR model based on 2 parameters, the octanol–water partition coefficient and the acid dissociation constant (pKa). The toxicities of synergetic mixtures can be interpreted with the total energy (ET) and pKa of the mixtures. Dipole moment and ET are the quantum descriptors that influence the antagonistic mixture toxicity. Therefore, in silico modeling may be a useful tool in predicting disinfection by‐product mixture toxicities. Environ Toxicol Chem 2021;40:1431–1442. © 2021 SETAC The toxicological interactions of disinfection by‐product mixtures on green algae. BAA = bromoacetic acid; CAA = chloroacetic acid; DBP = disinfection by‐product; DCAA = dichloroacetic acid; IAA = iodoacetic acid; pEC50 = predicted median effect concentration; QSAR = quantitative structure–activity relationship; TBAA = tribromoacetic acid; TCAA = trichloroacetic acid.</description><identifier>ISSN: 0730-7268</identifier><identifier>EISSN: 1552-8618</identifier><identifier>DOI: 10.1002/etc.4995</identifier><identifier>PMID: 33507536</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Acids ; Algae ; Antagonism ; Aquatic plants ; Binary mixtures ; Byproducts ; Chemical activity ; Chloroacetic acid ; Chlorophyta ; Dichloroacetic acid ; Dipole moments ; Disinfection ; Disinfection by products ; Haloacetic acids ; Iodoacetic acid ; Mixture toxicity ; Modelling ; Octanol-water partition coefficients ; Quantum descriptors ; Raphidocelis subcapitata ; Structure-activity relationships ; Synergism ; Toxicity ; Trichloroacetic acid</subject><ispartof>Environmental toxicology and chemistry, 2021-05, Vol.40 (5), p.1431-1442</ispartof><rights>2021 SETAC</rights><rights>2021 SETAC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3865-8ad0aa68c46fb72bc0d60761eff241a87bf671942e90fdcd3b2b989aaff84543</citedby><cites>FETCH-LOGICAL-c3865-8ad0aa68c46fb72bc0d60761eff241a87bf671942e90fdcd3b2b989aaff84543</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33507536$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Qin, Li‐Tang</creatorcontrib><creatorcontrib>Liu, Min</creatorcontrib><creatorcontrib>Zhang, Xin</creatorcontrib><creatorcontrib>Mo, Ling‐Yun</creatorcontrib><creatorcontrib>Zeng, Hong‐Hu</creatorcontrib><creatorcontrib>Liang, Yan‐Peng</creatorcontrib><title>Concentration Addition, Independent Action, and Quantitative Structure–Activity Relationships for Chemical Mixture Toxicities of the Disinfection By products of Haloacetic Acids on the Green Alga Raphidocelis subcapitata</title><title>Environmental toxicology and chemistry</title><addtitle>Environ Toxicol Chem</addtitle><description>The potential toxicity of haloacetic acids (HAAs), common disinfection by products (DBPs), has been widely studied; but their combined effects on freshwater green algae remain poorly understood. The present study was conducted to investigate the toxicological interactions of HAA mixtures in the green alga Raphidocelis subcapitata and predict the DBP mixture toxicities based on concentration addition, independent action, and quantitative structure–activity relationship (QSAR) models. The acute toxicities of 6 HAAs (iodoacetic acid [IAA], bromoacetic acid [BAA], chloroacetic acid [CAA], dichloroacetic acid [DCAA], trichloroacetic acid [TCAA], and tribromoacetic acid [TBAA]) and their 68 binary mixtures to the green algae were analyzed in 96‐well microplates. Results reveal that the rank order of the toxicity of individual HAAs is CAA &gt; IAA ≈ BAA &gt; TCAA &gt; DCAA &gt; TBAA. With concentration addition as the reference additive model, the mixture effects are synergetic in 47.1% and antagonistic in 25%, whereas the additive effects are only observed in 27.9% of the experiments. The main components that induce synergism are DCAA, IAA, and BAA; and CAA is the main component that causes antagonism. Prediction by concentration addition and independent action indicates that the 2 models fail to accurately predict 72% mixture toxicity at an effective concentration level of 50%. Modeling the mixtures by QSAR was established by statistically analyzing descriptors for the determination of the relationship between their chemical structures and the negative logarithm of the 50% effective concentration. The additive mixture toxicities are accurately predicted by the QSAR model based on 2 parameters, the octanol–water partition coefficient and the acid dissociation constant (pKa). The toxicities of synergetic mixtures can be interpreted with the total energy (ET) and pKa of the mixtures. Dipole moment and ET are the quantum descriptors that influence the antagonistic mixture toxicity. Therefore, in silico modeling may be a useful tool in predicting disinfection by‐product mixture toxicities. Environ Toxicol Chem 2021;40:1431–1442. © 2021 SETAC The toxicological interactions of disinfection by‐product mixtures on green algae. 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Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Environmental toxicology and chemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Qin, Li‐Tang</au><au>Liu, Min</au><au>Zhang, Xin</au><au>Mo, Ling‐Yun</au><au>Zeng, Hong‐Hu</au><au>Liang, Yan‐Peng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Concentration Addition, Independent Action, and Quantitative Structure–Activity Relationships for Chemical Mixture Toxicities of the Disinfection By products of Haloacetic Acids on the Green Alga Raphidocelis subcapitata</atitle><jtitle>Environmental toxicology and chemistry</jtitle><addtitle>Environ Toxicol Chem</addtitle><date>2021-05</date><risdate>2021</risdate><volume>40</volume><issue>5</issue><spage>1431</spage><epage>1442</epage><pages>1431-1442</pages><issn>0730-7268</issn><eissn>1552-8618</eissn><abstract>The potential toxicity of haloacetic acids (HAAs), common disinfection by products (DBPs), has been widely studied; but their combined effects on freshwater green algae remain poorly understood. The present study was conducted to investigate the toxicological interactions of HAA mixtures in the green alga Raphidocelis subcapitata and predict the DBP mixture toxicities based on concentration addition, independent action, and quantitative structure–activity relationship (QSAR) models. The acute toxicities of 6 HAAs (iodoacetic acid [IAA], bromoacetic acid [BAA], chloroacetic acid [CAA], dichloroacetic acid [DCAA], trichloroacetic acid [TCAA], and tribromoacetic acid [TBAA]) and their 68 binary mixtures to the green algae were analyzed in 96‐well microplates. Results reveal that the rank order of the toxicity of individual HAAs is CAA &gt; IAA ≈ BAA &gt; TCAA &gt; DCAA &gt; TBAA. With concentration addition as the reference additive model, the mixture effects are synergetic in 47.1% and antagonistic in 25%, whereas the additive effects are only observed in 27.9% of the experiments. The main components that induce synergism are DCAA, IAA, and BAA; and CAA is the main component that causes antagonism. Prediction by concentration addition and independent action indicates that the 2 models fail to accurately predict 72% mixture toxicity at an effective concentration level of 50%. Modeling the mixtures by QSAR was established by statistically analyzing descriptors for the determination of the relationship between their chemical structures and the negative logarithm of the 50% effective concentration. The additive mixture toxicities are accurately predicted by the QSAR model based on 2 parameters, the octanol–water partition coefficient and the acid dissociation constant (pKa). The toxicities of synergetic mixtures can be interpreted with the total energy (ET) and pKa of the mixtures. Dipole moment and ET are the quantum descriptors that influence the antagonistic mixture toxicity. Therefore, in silico modeling may be a useful tool in predicting disinfection by‐product mixture toxicities. Environ Toxicol Chem 2021;40:1431–1442. © 2021 SETAC The toxicological interactions of disinfection by‐product mixtures on green algae. BAA = bromoacetic acid; CAA = chloroacetic acid; DBP = disinfection by‐product; DCAA = dichloroacetic acid; IAA = iodoacetic acid; pEC50 = predicted median effect concentration; QSAR = quantitative structure–activity relationship; TBAA = tribromoacetic acid; TCAA = trichloroacetic acid.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>33507536</pmid><doi>10.1002/etc.4995</doi><tpages>12</tpages></addata></record>
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source Wiley-Blackwell Read & Publish Collection
subjects Acids
Algae
Antagonism
Aquatic plants
Binary mixtures
Byproducts
Chemical activity
Chloroacetic acid
Chlorophyta
Dichloroacetic acid
Dipole moments
Disinfection
Disinfection by products
Haloacetic acids
Iodoacetic acid
Mixture toxicity
Modelling
Octanol-water partition coefficients
Quantum descriptors
Raphidocelis subcapitata
Structure-activity relationships
Synergism
Toxicity
Trichloroacetic acid
title Concentration Addition, Independent Action, and Quantitative Structure–Activity Relationships for Chemical Mixture Toxicities of the Disinfection By products of Haloacetic Acids on the Green Alga Raphidocelis subcapitata
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