Organic Compounds In Fish Research Articles

Comprehensive characterization and prioritization of halogenated organic compounds in fish and their implications for exposure

Fish are an important pollution indicator for biomonitoring of halogenated organic compounds (HOCs) in aquatic environments, and HOCs in fish may pose health threats to consumers. This study performed nontarget and comprehensive analyses of HOCs in fish from an e-waste recycling zone by gas chromatography–high-resolution mass spectrometry, and further prioritized their human exposure risks. A total of 1652 formulas of HOCs were found in the fish, of which 1222, 117, and 313 were organochlorines, organobromines, and organochlorine-bromines, respectively. The total concentrations of HOCs were 15.4–18.7 μg/g (wet weight), and organobromines were the predominant (14.1–16.8 μg/g). Of the HOCs, 41 % were elucidated with tentative structures and divided into 13 groups. The estimated total daily exposures of HOCs via dietary consumption of the fish for local adult residents were 3082–3744 ng/kg bw/day. The total exposures were dominated by several groups of HOCs with the following contribution order: polyhalogenated biphenyls and their derivatives > polyhalogenated diphenyl ethers > halo- (H-)alkanes/olefines > H-benzenes > H-dioxins > H-polycyclic aromatic hydrocarbons > H-phenols. The comprehensive characterization and prioritization results provide an overview of the species and distributions of HOCs in edible fish, and propose an inventory of crucial HOCs associated with high exposure risks.

Investigating the bioaccumulation potential of anionic organic compounds using a permanent rainbow trout liver cell line

Permanent rainbow trout (Oncorhynchus mykiss) cell lines represent potential in vitro alternatives to experiments with fish. We here developed a method to assess the bioaccumulation potential of anionic organic compounds in fish, using the rainbow trout liver-derived RTL-W1 cell line. Based on the availability of high quality in vivo bioconcentration (BCF) and biomagnification (BMF) data and the substances’ charge state at physiological pH, four anionic compounds were selected: pentachlorophenol (PCP), diclofenac (DCF), tecloftalam (TT) and benzotriazol-tert-butyl-hydroxyl-phenyl propanoic acid (BHPP). The fish cell line acute toxicity assay (OECD TG249) was used to derive effective concentrations 50 % and non-toxic exposure concentrations to determine exposure concentrations for bioaccumulation experiments. Bioaccumulation experiments were performed over 48 h with a total of six time points, at which cell, medium and plastic fractions were sampled and measured using high resolution tandem mass spectrometry after online solid phase extraction. Observed cell internal concentrations were over-predicted by KOW-derived predictions while pH-dependent octanol–water partitioning (DOW) and membrane lipid-water partitioning (DMLW) gave better predictions of cell internal concentrations. Measured medium and cell internal concentrations at steady state were used to calculate RTL-W1-based BCF, which were compared to DOW- or DMLW-based model approaches and in vivo data. With the exception of PCP, the cell-derived BCF best compared to DOW-based model predictions, which were higher than predictions based on DMLW. All methods predicted the in vivo BCF for diclofenac well. For PCP, the cell-derived BCF was lowest although all BCF predictions underestimated the in vivo BCF by ≥ 1 order of magnitude. The RTL-W1 cells, and all other prediction methods, largely overestimated in vivo BMF, which were available for PCP, TT and BHPP. We conclude that the RTL-W1 cell line can supplement BCF predictions for anionic compounds. For BMF estimations, however, in vitro-in vivo extrapolations need adaptation or a multiple cell line approach.

Dietary Uptake Patterns Affect Bioaccumulation and Biomagnification of Hydrophobic Organic Compounds in Fish

Biomagnification of hydrophobic organic compounds (HOCs) increases the eco-environmental risks they pose. Here, we gained mechanistic insights into biomagnification of deuterated polycyclic aromatic hydrocarbons (PAHs- d10) in zebrafish with carefully controlled water (ng L-1) by a passive dosing method and dietary exposures using pre-exposed Daphnia magna and fish food. A new bioaccumulation kinetic model for fish was established to take into account discrete dietary uptake, while the frequently used model regards dietary uptake as a continuous process. We found that when freely dissolved concentrations of the PAHs- d10 were constant in water, the intake amount of the PAHs- d10 played an important role in affecting their steady-state concentrations in zebrafish, and there was a peak concentration in zebrafish after each dietary uptake. Moreover, considering the randomness of predation, the Monte Carlo simulation results showed that the probabilities of biomagnification of the PAHs- d10 in zebrafish increased with their dietary uptake amount and frequency. This study indicates that in addition to the well-known lipid-water partitioning, the bioaccumulation of HOCs in fish is also a discontinuous kinetic process caused by the fluctuation of HOC concentration in the gastrointestinal tract as a result of the discrete food ingestion. The discontinuity and randomness of dietary uptake can partly explain the differences among aquatic ecosystems with respect to biomagnification for species at similar trophic levels and provides new insight for future analysis of experimental and field bioaccumulation data for fish.

A reductionist mechanistic model for bioconcentration of neutral and weakly polar organic compounds in fish

The bioconcentration factor (BCF) of neutral and weakly polar organic chemicals in fish is modeled using independently calibrated models of chemical partitioning (freely dissolved fraction of chemical in the aqueous phase [φsys ] and wet-weight fish-water partition coefficient [KFW ]), respiratory exchange (respiratory update rate constant [k1 ], and respiratory elimination rate constant [k2 = k1 /KFW ]), and biotransformation (whole-body biotransformation rate constant [kM ]) as BCF = φsys KFW /(1 + kM /k2 ). Existing k1 models tend to overestimate for chemicals with log KOW < 3.5, which constituted 30% to 50% of the examined chemicals. A revised k1 model covering a wider log KOW range (0-8.5) is presented k1 = (5.46 × 10(-6) MW + 0.261/KOW )(-1) , where MW is the molecular weight. The biotransformation rate constant kM is modeled using biota internal partitioning and Abraham parameters as reactivity descriptors. The reductionist model was tested using 3 different BCF data sets (US Environmental Protection Agency's Estimation Programs Interface [EPI], n = 548; Hertfordshire, n = 210; Arnot-Gobas, n = 1855) and compared with the following 3 state-of-the-art models: 1) the EPI Suite BCFBAF module, 2) the European Commision's Computer Assisted Evaluation of industrial chemical Substances According to Regulations (CAESAR), and 3) the EPI/Arnot mechanistic kinetic model. The reductionist model performed comparably with the alternative models (root mean square errors [RMSEs] = 0.72-0.77), with only 5 fitting parameters and no training against experimental BCFs. Respiratory elimination and biotransformation dominate the total depuration (i.e., [k2 + kM ]/kT ≥ 0.8) for approximately 98% of the data entries, thus validating the reductionist approximation. Mechanistic models provide greater insights into bioaccumulation and are more sensitive to biological variation. All three BCF data sets and relevant properties and checkpoint values necessary for reproducing predictions of the reductionist model have been documented. The present study shows that a streamlined mechanistic model of BCF is possible for assessment purposes.

Biotransformation model of neutral and weakly polar organic compounds in fish incorporating internal partitioning

A model for whole-body in vivo biotransformation of neutral and weakly polar organic chemicals in fish is presented. It considers internal chemical partitioning and uses Abraham solvation parameters as reactivity descriptors. It assumes that only chemicals freely dissolved in the body fluid may bind with enzymes and subsequently undergo biotransformation reactions. Consequently, the whole-body biotransformation rate of a chemical is retarded by the extent of its distribution in different biological compartments. Using a randomly generated training set (n = 64), the biotransformation model is found to be: log (HLφfish ) = 2.2 (±0.3)B - 2.1 (±0.2)V - 0.6 (±0.3) (root mean square error of prediction [RMSE] = 0.71), where HL is the whole-body biotransformation half-life in days, φfish is the freely dissolved fraction in body fluid, and B and V are the chemical's H-bond acceptance capacity and molecular volume. Abraham-type linear free energy equations were also developed for lipid-water (Klipidw ) and protein-water (Kprotw ) partition coefficients needed for the computation of φfish from independent determinations. These were found to be 1) log Klipidw = 0.77E - 1.10S - 0.47A - 3.52B + 3.37V + 0.84 (in Lwat /kglipid ; n = 248, RMSE = 0.57) and 2) log Kprotw = 0.74E - 0.37S - 0.13A - 1.37B + 1.06V - 0.88 (in Lwat /kgprot ; n = 69, RMSE = 0.38), where E, S, and A quantify dispersive/polarization, dipolar, and H-bond-donating interactions, respectively. The biotransformation model performs well in the validation of HL (n = 424, RMSE = 0.71). The predicted rate constants do not exceed the transport limit due to circulatory flow. Furthermore, the model adequately captures variation in biotransformation rate between chemicals with varying log octanol-water partitioning coefficient, B, and V and exhibits high degree of independence from the choice of training chemicals. The present study suggests a new framework for modeling chemical reactivity in biological systems.

Occurrence of priority and emerging organic compounds in fishes from the Rhone River (France)

The main objective of this study was to collect new data on the occurrence, levels of priority and emerging organic compounds in freshwater fish sampled in the Rhone River. The 34 studied contaminants included alkylphenols, bisphenol A, polybromodiphenylethers (PBDE), perfluorinated compounds, hexabromocyclododecanes (HBCD), hexachlorobenzene and hexachlorobutadiene (HCBD). About 50 fish samples (individual specimens or pooled fish) were collected from three sites located upstream and downstream of the Lyon metropolitan area in the Rhone River (France). Four species were caught at each site, namely: the barbel (Barbus barbus), the common bream (Abramis brama), the white bream (Blicca bjoerkna) and the chub (Squalius cephalus). Some contaminants were quantified in all the 32 fish samples analysed: 4-nonylphenol, α-HBCD, the six PBDE congeners (28, 47, 99, 100, 153, 154), perfluorooctanesulfonate (PFOS) and perfluorodecanoic acid. Twenty three of the 32 samples had a concentration of PFOS above the Environmental Quality Standards (EQS) (up to six times higher than the EQS), and all the 32 samples had concentrations of PBDE above the EQS (up to 4,000 times higher, with the sum of six PBDE varying from 4.5 to 182 ng/g dry weight). Clearly, the interest to consider PFOS and HBCD as new priority substances is confirmed. In contrast, the pertinence of a priority status for HCBD, which was never quantified in our study, might have to be reconsidered in the future.

Prediction of the Bioconcentration Factor of Organic Compounds in Fish

AbstractQuantitative structure‐activity relationship (QSAR) models for bioconcentration factor (BCF) prediction applicable to 131 organic compounds of different chemical structures were prepared. The study showed that the best QSAR model, pBCF = 0.00250227 MW – 0.0723952 ET – 0.21352 εHOMO – 0.892481 eLUMO – 2.58291, was made from four quantum chemical descriptors. The best model was selected on the basis of the value of the correlation coefficient (r2 = 0.871), cross validation coefficient (r2CV = 0.856), standard error (Std. Err. = 0.978), standard error of estimation (Std. Err. Est. = 0.556), F statistic (F = 213.22) and p value (p = 0.009), that were calculated by Statistica software. The molecular weight followed a direct relationship with the observed bioconcentration factor (oBCF) up to a MW of 361 Da, and thereafter it followed an inverse relationship. The total energy and HOMO‐LUMO gap, showed inverse relationships with oBCF. With the help of the QSAR model, bioconcentration factors of several hypothetical molecules can be predicted prior to their synthesis.

QSPR of the bioconcentration factors of non-ionic organic compounds in fish using extended topochemical atom (ETA) indices

Bioconcentration refers to the absorption or uptake of a chemical from the media to an organism's tissues leading to greater concentration in tissues than that in the surrounding environment. Considering the importance of bioconcentration from the viewpoint of ecological safety assessment, a QSPR study was conducted based upon log BCF of 122 non-ionic organic compounds in fish using the recently introduced extended topochemical atom (ETA) indices. In deriving the models, principal component factor analysis (FA) followed by multiple linear regression (MLR), stepwise regression, partial least squares (PLS) and principal component regression analysis (PCRA) were applied as statistical tools. This was repeated with non-ETA (topological and physicochemical) descriptors and a combination set including both the ETA and non-ETA descriptors. The ETA indices suggested negative contributions of functionalities of nitro, amino and hydroxy substructures and positive contributions of branching, volume and functionality of chloro substituents. Again, the predictive ability of the developed models was compared with the previously reported models. Finally the validation of all the QSAR models was discussed based on random division, sorted log BCF data and K-means clusters for the factor scores of the original variable (ETA) matrix without the response property values. The results suggest that ETA parameters are sufficiently rich in chemical information to encode the structural features contributing to the bioconcentration of the non-ionic organic compounds in fish and thus these merit further assessment to explore their potential in QSAR/QSPR/QSTR modelling.

Estimation of bioconcentration factors of nonionic organic compounds in fish by molecular connectivity indices and polarity correction factors

A bioconcentration factor (BCF) estimation model for a wide range of nonionic organic compounds was developed on the basis of molecular connectivity indices and polarity correction factors. The nonlinear topological modeling using polarity correction factors resulted in the best BCF estimation quality for all of the 239 compounds studied, with a mean absolute estimation error of 0.478 log units. Residual analysis indicated that the estimation errors came from many sources including BCF measurement, test species, and selection of descriptors. Statistical robustness of the developed model was validated by modified jackknifed tests where random deletion of a set of compounds and specific deletion of a class of compounds were both performed. Comparison between the MCI-based (molecular connectivity indices) model and a K ow-based (octanol/water partition coefficient) model revealed that the BCF estimation based on topological parameters was as good as that achieved by K ow.

Analysis of volatile halogenated organic compounds in fish

A method for the analysis of volatile halogenated hydrocarbons in biological samples has been developed. Extraction efficiencies for various C 1 and C 2 halocarbons were found to be in the range of 63–82%, and recoveries were faitly good. The detection limits lie in the sub-ppb range (0.1–1 ppb). The method has been used to analyse fish samples from both unpolluted and polluted areas in Norway. The compounds most frequently found were chloroform, trichloroethylene and tetrachloroethylene in concentrations ranging from 10–1000 ppb. From one area, corresponding water and fish samples were analysed which made it possible to estimate accumulation factors for chloroform and trichloroethylene, which were found to be 200–500 and 1400 respectively.

Gas Chromatographic – Mass Spectrometric Determination of Volatile Organic Compounds in Fish

A technique has been developed for the determination of volatile organic compounds in fish. The methodology is based on procedures used to determine purgeable organic compounds in water and wastewater. Fish tissue is added to reagent water, cooled in an ice bath, and homogenized with cell disruption using ultrasonic energy. The processed sample is then analyzed by a purge and trap procedure using an impinger-type device at 70 degrees C, with determination of the purged compounds by computerized gas chromatography-mass spectrometry. Both ground fish and cored fish specimens were successfully analyzed by this technique. The overall average recovery for 39 volatile compounds studied was 77% with an average standard deviation of 20%.

O-Methylation in Fish

DURING an investigation of the fate of some foreign organic compounds in fish, the metabolism of 3,4-dihydroxyphenylacetic acid (homoprotocatechuic acid) was investigated with the purpose of obtaining some information on methylation reactions in these animals. DeEds et al.1 have noted that this compound is methylated at the 3-hydroxyl group in rats and rabbits. A later report by Scheline et al.2 showed that homoprotocatechuic acid labelled with carbon-14 fed to rabbits at a dose-level of 100 mgm./kgm. resulted in about 85 per cent of the radioactivity being excreted in the urine within 44 hr. While the main excretory product was the original acid, nearly six per cent of the dose was found as 4-hydroxy-3-methoxyphenyl-acetic acid (homovanillic acid).