Metabolism of SCCPs and MCCPs in Suspension Rice Cells Based on Paired Mass Distance (PMD) Analysis

Abstract

Short-chain and medium-chain chlorinated paraffins (SCCPs and MCCPs) are mixtures of complex chemical compounds with intensive usage. They are frequently detected in various environmental samples. However, the interaction between CPs and plants, especially the biotransformation behaviors of CPs within plants, is poorly understood. In this study, 1,2,5,6,9,10-hexachlorodecane (CP-4, a typical standard of individual SCCP congeners) and 52%-MCCP (a commercial mixture standard of MCCPs with 52% chlorine content by mass) were selected as representative chemicals to explore the metabolic behaviors of SCCPs and MCCPs using suspension rice cell culture exposure systems. Both 79.53% and 40.70% of CP-4 and 52%-MCCP were metabolized by suspension rice cells, respectively. A complementary suspected screening strategy based on the pair mass distances (PMD) analysis algorithm was used to study the metabolism of CPs mediated by the plant cells. Forty and 25 metabolic products for CP-4 and 52%-MCCP, respectively, were identified, including (multi-) hydroxylation, dechlorination, −HCl− elimination metabolites, (hydroxylation-) sulfation, and glycosylation conjugates. Here, we propose a comprehensive metabolic molecular network and provide insight on degradation pathways of SCCPs and MCCPs in plants for the first time, aiding in further understanding of the transformation behaviors of CPs.

Graphical Abstract

INTRODUCTION

Chlorinated paraffins (CPs) are divided into short- (SCCPs, C₁₀–C₁₃), medium- (MCCPs, C₁₄–C₁₇), and long-chain (LCCPs, C_>17) chlorinated paraffins based on carbon numbers of the molecules. SCCPs and MCCPs are dominant components of CP commercial products, such as commercial CP-42 and CP-52, widely used as flame retardants, cutting fluids, and plasticizers.^1,2 After SCCPs were added into Annex A of the Stockholm convention in 2017 because of their persistence, long distance transport, bioaccumulation and high toxicity to organisms,³ and production of MCCPs as substitutes increased steadily.⁴ Recent studies showed that the concentrations of MCCPs in environmental matrices were occasionally more dominant than SCCPs.^5,6

The wide occurrence of SCCPs and MCCPs in the environment and humans has drawn intense research interest.^7–11 However, knowledge of their biotic and abiotic degradation has remained quite limited. Though direct photolysis of CPs is small due to the lack of chromophores to absorb sunlight (>290 nm),¹² CPs can be transformed to chlorinated olefins, polyenes, or even toxic chlorinated aromatic hydrocarbons under various thermal processes.^13–16 Hydroxyl radical (^•OH) reaction with SCCPs has also been predicted for the atmosphere by quantum chemical calculations.^17,18 SCCPs were found to be biologically converted to chlorinated olefins by a bacterial dehydroxyhalogenase LinA2.¹⁹ Our previous work also showed that SCCPs could be metabolized to congeners with less chlorine and carbon atoms through dechlorination, chlorine rearrangement, and carbon-chain decomposition behaviors by pumpkin seedlings.^20,21 However, no information on the biotransformation of MCCPs has been reported to our knowledge.

Plants play an indispensable role in biotransformation of organic pollutants through activation, conjugation, and sequestration processes.²² Plant cells are efficient in vitro models to determine the biotransformation pathways of xenobiotics and to avoid false positives caused by bacterial activities. Metabolism of xenobiotics in plant cells was found to be similar to those in whole plants, suggesting a reliable surrogate for biotransformation pathways in whole plants in many cases.^23–26

In order to more comprehensively understand the myriad of potential metabolic pathways, new screening and dataprocessing methods are continuously developed. The paired mass distance (PMD) method is a powerful tool to sensitively and effectively identify metabolism pathways. PMD is the distance between specific mass-to-charge ratios (m/z) of two compounds obtained in mass spectrometry. Certain PMD values represent special metabolism reactions according to statistical analyses of reported metabolic pathways.²⁷ Coupled with a GlobalStd algorithm, using PMD analysis can track the possible reactions taking place between compounds and then infer the metabolism processes.

In this study, SCCP and MCCP congeners were separately exposed to suspension rice cells to research their biotransformation processes. According to previous results, chlorodecanes with six chlorine atoms are one group of the abundant monomers of SCCPs detected in the environment.^9,18,28–31 Thus, a single standard of 1,2,5,6,9,10-hexachlorodecane (CP-4) was selected from the limited commercially individual standards of SCCPs as the representative SCCP congener. Because MCCPs have no available commercial standards for a single congener, a standard mixture of 52%-MCCP (MCCPs with 52% chlorination by mass) was selected as the MCCP model. The PMD methodology was used to construct the possible metabolic pathways and to propose metabolite candidates. After further identification with high-resolution tandem mass spectrometry (HRMS/MS), a total of 65 new metabolites of CP-4 and 52%-MCCP were identified and their metabolic molecular networks elucidated. To our knowledge, this is the first report of (multi)-hydroxylation, sulfation, and glycosylation of CPs in any in vitro or in vivo model organisms, providing an indispensable message to evaluate environmental behaviors and risks of CPs.

MATERIALS AND METHODS

Chemicals and Reagents.

1,2,5,6,9,10-Hexachlorodecane (1,2,5,6,9,10-hexCD, CP-4, 10 μg/mL in cyclohexane, 99.9%) and ¹³C-1,5,5,6,6,10-hexachlorodecane (¹³C-1,5,5,6,6,10-hexCD in cyclohexane, 100 ng/μL, >98%) were purchased from Cambridge Isotope Laboratories (Andover, USA). Standard stock solutions of MCCPs mixtures (C_14–17 with chlorine contents of 42%, 52%, and 57%, 100 μg/mL in cyclohexane) and the injection standard of ε-hexachlorocyclohexane (ε-HCH in cyclohexane, 10 ng/μL, 99.9%) were obtained from Dr. Ehrenstorfer GmbH (Augsburg, Germany). HPLC-grade methanol and acetone were purchased from Fisher chemical (Waltham, MA). Ultra resi-analyzed ethyl acetate, pesticide-grade dichloromethane, n-hexane, and cyclohexane were obtained from J.T. Baker (Phillipsburg, NJ). Supelclean LC-Florisil SPE Tubes (1 g, volume 6 mL) were bought from Supelco (Sigma-Aldrich, St. Louis, MO). HLB 6 cm³ (200 mg) columns were purchased from Waters (Milford, MA). Ultrapure water (18.2 MΩ·cm) was prepared with a milli-Q purification system (Millipore, Billerica, MA).

Exposure Experiment.

The suspension rice cells (Oryza sativa Japonia cv. Nipponbare) were cultivated at 130 rpm and 28 °C in nutrient solution and inoculated into fresh solution every 4 days. All of the cultivation medium, glass vials, sealant, and tools for cell transferring were autoclaved, and the transferring procedure was performed carefully in a laminar flow hood to keep the cells away from contamination by exogenous microorganisms. Details regarding the medium solution composition are described in Text S1. To explore the metabolic behaviors of CPs in rice cells, exposure incubation experiments were carried out for individual CP-4 and 52%-MCCP, respectively. A schematic of the exposure experiments is illustrated in Figure 1. A volume of 10 μL of the parent compound working solution (CP-4 or 52%-MCCP, 500 μg/mL in acetone) was spiked into suspension cell cultures which were placed in a 25 mL conical flask at a constant volume of 10 mL, resulting in an initial concentration of 500 ng/mL as the exposure group. Three control groups were set up for quality control. Culture solutions added with CP-4 or 52%-MCCP but without rice cells were set up as cell-free medium controls to check for any potential abiotic transformations and volatilization. A volume of 10 mL of suspension rice cells was autoclaved at 120 °C for 20 min and spiked with the same amount of CP-4 or 52%-MCCP to serve as nonviable cell controls to quantitatively evaluate the adsorption of the parent compound to the surface of the cells and could be also used to access the losses of target compounds caused by volatilization and possible abiotic transformation in the exposure system at the same time. In addition, blank suspension cells with a 10 μL addition of acetone but without exposure chemicals (the blank control) was used to evaluate the effect of acetone and for potential cross contamination. All of the conical flasks of the exposure and control groups were replicated three times and fitted with the sterilized sealant films which allowed air exchange but prevented microorganisms from entering. These were cultivated at 130 rpm and 28 °C together in an exposure chamber away from light.

Figure 1.

Schematic of CP-4 and 52%-MCCP exposure experiment.

After 5 days incubation, rice cells and nutrient solution were separated by centrifugation at 4 °C and 3000 g for 10 min. The supernatant solution was transferred into a clean glass vial. Cells and conical flasks were rinsed with fresh medium three times, and the rinse medium was combined with the solution sample. The solution sample was extracted with ethyl acetate immediately. All of the rice cells samples were freeze dried after being stored at −80 °C overnight and then kept at −20 °C until further treatments.

Extraction and Clean up.

Solution samples which were put into brown glass vials were added with the surrogate standard (200 ng of ¹³C-1,5,5,6,6,10-hexCD), extracted with 3 mL of ethyl acetate on an oscillator at 270 r/min for 30 min, and then centrifuged at 8500 rpm for 15 min according to our former report.³² The extraction was carried out four times; then the pooled supernatant was divided into two fractions of equal volume. The two fractions of extracts were concentrated under nitrogen gas and then reconstituted with 200 μL of methanol and cyclohexane, respectively, for liquid chromatography (LC) and gas chromatography (GC) analysis. The rice cells sample was spiked with 200 ng of ¹³C-1,5,5,6,6,10-hexCD and extracted with 2 mL of methanol (twice) and 2 mL of methanol/dichloromethane (v/v = 1:1, twice) in sequence. The extracts were combined after each centrifugation at 8500 rpm for 10 min, divided into two fractions, and dried under N₂. One fraction was reconstituted with 500 μL of methanol, diluted with water to 10 mL, and loaded onto a HLB cartridge. The HLB cartridge (200 mg, Waters) was preconditioned with 5 mL of methanol and 5 mL of pure water in sequence. Analytes were eluted with 10 mL of methanol, evaporated to dryness with nitrogen gas, and reconstituted with 200 μL of methanol for LC analysis. The other fraction of cell extract was redissolved with 5 mL of hexane and loaded onto a LC-Florisi SPE tube which was preconditioned with 5 mL of hexane. The analytes were eluted with 10 mL of 15% acetone/hexane (v/v), solvent exchanged with 200 μL of cyclohexane, and added with 10 μL of 1 ng/μL ε-HCH for the parent compound and hydrophobic metabolites determination by GC.

Instrumental Analysis.

Parent compounds (CP-4, 52%-MCCP) and hydrophobic metabolites were analyzed with an Agilent 7890 B chromatograph coupled with a 7200-QTOF mass spectrometry system (GC-QTOF-HRMS, Agilent technologies, Santa Clara, CA, USA) based on the method of Gao et al., and details are shown in Text S2.³³ An ultimate 3000 ultrahigh performance liquid chromatography coupled with an orbitrap fusion mass spectrometer (UPLC-orbitrap-HRMS, Thermo Fisher Scientific Inc., Waltham, MA) was used to analyze the hydrophilic metabolites of CPs. The separation was achieved with a C18 reversed phase LC column (Acclaim RSLC 120 C18, 100 × 2.1 mm × 2.2 μm, Thermo Scientific) at 35 °C. Milli-Q water and methanol containing 1 mmol/L ammonium acetate were used as mobile phase A and B, respectively. The gradient elution (flow rate of 0.3 mL/min) was performed as follows (with respect to phase B): kept 30% for 1 min, increased to 50% within 1 min, continued to rise to 70% within 2 min, held for 2 min, and then increased to 90% within 4 min, held for 2 min, then increased to 100% within 4 min, and held for 4 min, and finally returned to the initial rate. The injection volume was 10 μL.

The orbitrap-HRMS was operated in the electrospray ionization (ESI) negative mode and with full scanning over a range of 60–900 m/z with a resolution of 120 000. To further confirm the structures of the proposed candidates, the MS fragment (MS²) was conducted in the mode of higher energy collisional dissociation (HCD) to obtain precursor/daughter ion pairs information. The MS¹ precursors were operated in quadrupole mode with a 3 m/z isolation window. MS² fragmentations were scanned with orbitrap at a resolution of 30 000 with a HCD energy of 10–30%.³⁴

Quality Assurance and Quality Control (QA/QC).

The mass precision of GC-QTOF-HRMS was calibrated within ±5 ppm mass error every 5–8 samples. An accurate mass of UPLC-orbitrap-HRMS (<2 ppm) was validated with the specific pierce ion calibration solution kit of Thermo Fisher Scientific once a week. Identification confidence levels of metabolites relied on the high-accuracy MS¹ and the characteristic fragments (MS²) information proposed by Schymanski et al. Five confidence levels were proposed for structure identification of unknown small molecules. The compound with a confirmed structure by a reference standard (MS, MS², retention time) was classified to confidence level 1. If the structure of a compound was matched with the spectral data from the literature or databases, including MS and MS², it was ranked to confidence level 2. The tentative candidate with defined molecular mass, formula, elemental composition, and substitution groups but with uncertain positions of substituents by MS and MS² information was classed as level 3. For confidence level 4, the molecular formulas and elemental compositions were unequivocal by MS information, but there was no sufficient evidence to propose characteristic functional groups. Chemicals which had a defined exact molecular mass but unequivocal formula that could not be identified were classed to confidence level 5.³⁵ The difference of the observed and the calculated isotopic abundance pattern was less than 250 m sigma.

A procedural and a solvent blank were detected every 5 samples to control potential contamination produced by the pretreatment and instrumental processes. The qualitative and quantitative ions of CP-4 were m/z 313.9563 (the second abundance congener of C₁₀H₁₅Cl₅⁻) and m/z 311.9592 (the first abundance congener of C₁₀H₁₅Cl₅⁻) on GC-QTOF-HRMS. CP-4 was quantified with the external standard curve method. However, the mixture of parent 52%-MCCPs was quantitatively analyzed with the internal standard curve method established by Gao et al., and the results of 52%-MCCPs were corrected by the recoveries of the surrogate standard.³³ Qualitative and quantitative ions for 52%-MCCP on GC-QTOF-HRMS are shown in Table S1. Recoveries of the surrogate standard (¹³C-1,5,5,6,6,10-hexCD) in rice cells and solutions were 91.6–94.8% (mean 93.2%) and 107.2–117.9% (mean 112.5%). The spiking recoveries of parent CP-4 and 52%-MCCP were 93.9–103.0% (mean 95.5%) and 94.2–116.1% (mean 103.0%) for rice cells and 82.3–105.1% (mean 92.6%) and 100.3–117.5% (mean 107.2%) for solutions. Method detection limits (MDLs) in the solutions and cells samples were 8.0–16.0 ng/L and 0.61–1.85 ng/g dry weight (d.w.) for CP-4 and 6.7–8.0 ng/mL and 0.10–0.14 μg/g d.w. for 52%-MCCP, respectively. The statistical differences between groups were evaluated by Tukey’s test with SPSS Statistic 25.0 software.

Suspect Screening Process.

The Suspect screening process for identifying metabolites of CPs was as follows. (1) Raw data convert. Full-scan raw data files obtained from GC-QTOF-HRMS and UPLC-orbitrap-HRMS were converted to mzXML form with MSConvert (ProteoWizard).³⁶ The mzXML files were then uploaded to xcms-online (version 3.7.1) to create a multigroup job which would be submitted to the database to extract peaks. The .csv format data with exact m/z, retention time, and peak intensity were obtained to fit with the following R script.³⁷ (2) Suspect PMDs of different metabolic reactions. Special PMD values of quasi-molecular ions of two compounds represent a typical metabolic reaction between them; for instance, a PMD value of 15.995 Da represents oxidation (R−H → R−OH), 33.961 Da means the reductive dechlorination (R−Cl → R−H), etc. The PMDs of possible metabolic reactions, such as the dechlorination, −HCl− elimination, hydroxylation, sulfation, and glycosylation, and so on, according to reported various biotransformation reactions of exogenous organic pollutants in plants, were all selected as suspected PMDs for screening the metabolites of CPs by the following pmdnet R script. All of the PMD values of those suspected metabolism pathways and metabolites are shown in Table S2.^{24,25,32,38–44} (3) Searching for metabolic pathways with PMD analysis. A pmdnet R script (details in Text S3) was developed to grab the compounds (peaks) between which showed the reaction relations fit with the suspected PMDs. Metabolic reactions which occurred (represented by PMDs) in the exposed cell systems could be identified. Then the molecular network was auto-output to describe the metabolic pathways of CPs in the cell culture. (4) Identifying the metabolites. According to the metabolic reactions which occurred in the cell culture, corresponding metabolites were further confirmed by their high-resolution mass spectrometry information. The natural isotopic pattern of chlorine atoms was a characteristic distinguishing the chlorine-containing metabolites from the endogenous metabolites, and it provided excellent evidence to elucidate the formula of metabolites. The natural abundance ratios of chlorine isotopes of molecules with different numbers of chlorine atoms (Cl₁–Cl₈) are shown in Figure S1, which were fit with binomial distributions and helped to illustrate the chlorine atom numbers of the metabolites. Accordingly, the suspected metabolites existing only in the treatment groups but not in any of the control groups were identified as target transformation products by quasi-molecular (MS¹) and fragment ions (MS²) via manual comparison of the chromatogram and MS information on the exposure group with those of the control groups (MassHunter Quantitative Analysis B.07 and Thermo Xcalibur Qual Browser 2.0). The mass tolerances of characteristic ions were ±10 and ±20 ppm for UPLC-orbitrap-HRMS and GC-QTOF-HRMS, respectively.

RESULTS AND DISCUSSION

Dissipation of Parent CP-4 and 52%-MCCP in the Rice Cell Exposure Systems.

After 5 days exposure, no CPs was detected in the blank controls, indicating that there was no cross contamination between reactors. The total amounts of parent CP-4 and 52%-MCCP detected in the solutions of cell-free medium controls at the end of exposure accounted for 99.62 ± 3.16% and 92.33 ± 3.49% of their initial amounts, respectively (shown in Figure 2), indicating good total recoveries and without volatilization and abiotic transformation losses of CPs in the exposure systems. In the nonviable cell controls, which were mainly used to evaluate the adsorption of parent compound to the cells, extremely low amounts of parent chemicals remained in the solutions, only accounting for 0.98 ± 0.36% and 2.89 ± 1.13% initial mass of CP-4 and 52%-MCCP, respectively, while the mass percentages associated with cells were large: 98.68 ± 8.68% for CP-4 and 99.69 ± 9.98% for 52%-MCCP. Also, the total recovered CP-4 and 52%-MCCP for the nonviable cell controls were 99.67 ± 9.04% and 102.58 ± 11.11%. These results indicated that the adsorption of CPs by cell fragments was quite strong, and no volatilization and abiotic transformation occurred in nonviable cells. For the exposure groups, similar distributions of parent chemicals were found with low mass remaining in solutions. The percentages of CP-4 and 52%-MCCP in solutions were 0.27 ± 0.07% and 7.62 ± 2.85% at 5 days. Compared with nonviable controls, the mass of CP-4 was slightly lower in exposure solutions (p < 0.05), which might be related to the simultaneously existing adsorption and absorption, but there were no significant differences for 52%-MCCP (p > 0.05). The results indicated that a large amount of CPs was adsorbed first and then partially or completely absorbed by cells. The absorption did not increase the transfer of CPs from solutions to cells. The percentages associated with cells of exposure groups were 19.87 ± 3.30% and 54.26 ± 6.00% of the initial mass of CP-4 and 52%-MCCP, respectively, significantly lower than those of nonviable cells (p < 0.001). In addition, the total recovered CP-4 and 52%-MCCP for the exposure systems were 20.14 ± 3.10% and 61.88 ± 8.85% at the end of exposure. The prominent discrepancies (p < 0.001) of mass balance between exposure groups and nonviable cell controls for both CP-4 and 52%-MCCP suggested that a large amount of CPs underwent biotransformation in the suspension rice cell systems. In comparison, the dissipation of CP-4 was greater than 52%-MCCP in the exposure systems, illustrating that the biotransformation of CP-4 (SCCP congener) was significantly greater than that of 52%-MCCP (p < 0.001).

Figure 2.

Mass percentages of CP-4 (a) and 52%-MCCP (b) distributed in solutions and rice cells which account for their initial mass after 5 days exposure. Parent compounds (CP-4 and 52%-MCCP) in blank cell controls were below the detection limit. Error bars represent one standard deviation of triplicates.

Metabolites Identification.

After running the pmdnet R script, possible metabolic types were quickly identified through the PMD analysis. Results showed that (multi-) hydroxylation, dechlorination, −HCl− elimination, sulfation, and glycosylation reactions occurred in the exposed rice cell systems. Then the metabolite candidates derived from those metabolic pathways were further verified by comparing with the information on compounds in the control groups, such as the retention times and chlorine isotopes, ensuring that identified metabolites only occurred in the exposure group which avoids the false positive disturbance of possible insource fragment ions of parent compounds, like [M + CH₃CO₂]⁻ and [M + HCl]⁻.

For parent CP-4 and 52%-MCCP, 20 and 21 phase I ((multi)hydroxylation, dechlorination, −HCl− elimination) metabolites and 20 and 4 phase II (sulfation and glycosylation) metabolites were finally identified with UPLC-orbitrap-HRMS. However, no hydrophobic metabolites (such as methylation) were found with GC-QTOF-HRMS. The active sites for substitution and conjugation were difficult to confirm for these metabolites just by LC-HRMS/MS detection, because of similar conformations with sp³-hybridized C–X bonds (X = H, Cl) in the molecular structures of CPs. However, the compositions and formulas of metabolites could be obtained through LC-HRMS/MS.^17,18 In the chromatograms and mass spectral information, corresponding metabolic reactions and characteristic fragment ions of these metabolites are summarized in Tables S3 and S4 and Figures S2 and S3. All of the metabolites were identified in ESI negative mode.

Hydroxylation Metabolites.

Ten phase I metabolites (M₃₇₉, M₃₆₃, M₃₆₁, M₃₄₅, M₃₂₉, M₃₂₇, M₃₁₁, M₂₉₅, M₂₉₁, M₂₇₅) were deduced to be (dechlorination)-(multi)-hydroxylation metabolites of CP-4 with 3–6 chlorine atoms according to their characteristic isotopic mass spectral information ([M – H]⁻) (Table S3 and Figure S2). The MS² spectra of M₃₆₃ (C₁₀H₁₅Cl₆O⁻) and M₃₂₉ (C₁₀H₁₆Cl₅O⁻) showed neutral losses of ClOH and OH between the precursor ion and the characteristic fragments, respectively, which were typical fragments of hydroxyl-containing compounds. However, the position of the hydroxyl group could not be identified. Thus, M₃₆₃ and M₃₂₉ were verified to be monohydroxylated metabolites with a confidence level of 3.³⁵ The other eight candidates were inferred to be monohydroxylated, dihydroxylated, or even trihydroxylated metabolites with unequivocal quasi-molecular ions and chlorine isotopes and classified into confidence level 4 (Table S3 and Figure S2).

Similarly, M₄₈₉ (C₁₄H₂₁Cl₈O⁻), M₄₆₇ (C₁₅H₂₄Cl₇O⁻), M₄₅₃ (C₁₄H₂₂Cl₇O⁻), M₄₃₃ (C₁₅H₂₅Cl₆O⁻), M₄₁₉ (C₁₄H₂₃Cl₆O⁻), and M₃₉₉ (C₁₅H₂₆Cl₅O⁻) were deduced to be monohydroxylated metabolites and M₄₃₅ (C₁₄H₂₃Cl₆O₂⁻) was inferred to be a dihydroxylated metabolite of 52%-MCCP congeners with the characteristic isotopic precursors ([M – H]⁻). Dechlorinated monohydroxylated (M₃₈₅, M₃₅₁), dechlorinated-dihydroxylated (M₄₀₁, M₃₆₇), dechlorinated-trihydroxylated (M₄₁₇, M₃₈₃, M₃₄₇), and dechlorinated-tetrahydroxylated (M₄₃₃, M₃₉₉, M₃₆₃) metabolites with five, four, or three chlorine atoms were also identified with unambiguous molecular formulas to confidence level 4.

−HCl− Elimination Metabolites.

It was reported that the bacterial dehydrohalogenase LinA2 could catalyze SCCPs to form chlorinated olefins via the −HCl− elimination reaction.¹⁹ No elimination reactions of −HCl− in animals or plants have been reported previously. Here, 10 −HCl-eliminated hydroxylation metabolites were detected for the first time. M₃₄₃ (C₁₀H₁₄Cl₅O₂⁻) and M₂₇₃ (C₁₀H₁₆Cl₃O₂⁻) were verified to be mono-HCl-eliminated-dihydroxylated CP-4 with a quasi-molecular formula (including a double bound) and characteristic chlorine isotopic patterns. These two metabolites were classed to confidence level 3 with neutral losses of ClOH and ClOCH₂. M₃₅₉ (C₁₀H₁₄Cl₅O₃⁻), M₃₂₅ (C₁₀H₁₅Cl₄O₃⁻), and M₂₈₉ (C₁₀H₁₆Cl₃O₃⁻) were inferred to be mono-HCl-eliminated-trihydroxylated compounds of CP-4 with an isotopic mass spectrum [M – H]^– at 4.99, 5.14, and 4.6 min, respectively. M₂₉₁ (C₁₀H₁₃Cl₄O⁻), M₃₀₇ (C₁₀H₁₃Cl₄O₂⁻), and M₃₂₃ (C₁₀H₁₃Cl₄O₃⁻) were identified to be di-HCl-eliminated monohydroxylated, di-HCl-eliminated-dihydroxylated, and di-HCl-eliminated-trihydroxylated metabolites with 4 chlorines. M₂₈₇ (C₁₀H₁₄Cl₃O₃⁻) and M₃₀₃ (C₁₀H₁₄Cl₃O₄⁻) were di-HCl-eliminated-trihydroxylated and di-HCl-eliminated-tetrahydroxylated metabolites with 3 chlorine atoms. These eight metabolites were classified to be of confidence level 4.

Besides, though the fragmentation of M₃₈₁ (C₁₄H₂₃Cl₄O₃⁻), M₃₄₅ (C₁₄H₂₄Cl₃O₃⁻), M₃₉₇ (C₁₄H₂₃Cl₄O₄⁻), and M₃₆₁ (C₁₄H₂₄Cl₃O₄⁻) showed the same neutral loss (HCl) as the parent compound, they were deduced to be mono-HCl-eliminated-trihydroxylated and mono-HCl-eliminated-tetrahydroxylated metabolites of 52%-MCCP congeners with 4 or 3 chlorine atoms, being classified to confidence level 4.

Sulfation Metabolites.

For CP-4 sulfation metabolites, the characteristic fragment ion of 96.96010 (SO₄H⁻) was detected in all M₄₅₉, M₄₄₃, M₄₂₅, M₄₀₉, M₄₀₇, M₃₉₁, M₃₈₉, M₃₇₅, M₃₇₃, M₃₅₅, and M₃₃₉, which suggested that they were all sulfated conjugates, but the position of the sulfate group could not be verified uniquely. These sulfated metabolites were classified to level 3. Although no characteristic fragments of SO₄H⁻ were found in M₄₂₃ and M₃₅₃, these two sulfated metabolites were allotted to be of confidence level 4. Among these sulfated products, M₄₄₃ (C₁₀H₁₅Cl₆SO₄⁻), M₄₀₉ (C₁₀H₁₆Cl₅SO₄⁻), M₃₇₅ (C₁₀H₁₇Cl₄SO₄⁻), and M₃₃₉ (C₁₀H₁₈Cl₃SO₄⁻) were identified to be sulfated metabolites with 6, 5, 4, and 3 chlorine atoms, respectively. M₄₅₉ (C₁₀H₁₅Cl₆SO₅⁻), M₄₂₅ (C₁₀H₁₆Cl₅SO₄⁻), M₃₉₁ (C₁₀H₁₇Cl₄SO₄⁻), and M₃₅₅ (C₁₀H₁₈Cl₃SO₄⁻) were verified with their [M – H]⁻ as monohydroxylated sulfated metabolites with different numbers of chlorine atoms. M₄₀₇ (C₁₀H₁₄Cl₅SO₄⁻) and M₃₇₃ (C₁₀H₁₅Cl₄SO₄⁻) were two −HCl-eliminated sulfated compounds, and M₄₂₃ (C₁₀H₁₄Cl₅SO₅⁻), M₃₈₉ (C₁₀H₁₅Cl₄SO₅⁻), and M₃₅₃ (C₁₀H₁₆Cl₃SO₄⁻) were deduced as three −HCl-eliminated monohydroxylated sulfated metabolites.

For sulfation metabolites of 52%-MCCP, M₄₆₅ (C₁₄H₂₄Cl₅SO₄⁻), M₄₈₁ (C₁₄H₂₄Cl₅SO₅⁻), M₄₆₇ (C₁₄H₂₅Cl₄SO₄⁻), and M₄₆₇ (C₁₄H₂₅Cl₄SO₅⁻) were elucidated to be sulfated and monohydroxylated sulfated metabolites with confidence level 3 due to their characteristic fragment ion of 96.96010 m/z (SO₄H⁻).

Glycosylation Metabolites.

Fragmentation of M₅₂₃, M₅₀₇, M₄₈₉, M₄₈₇, M₄₇₃, M₄₅₇, and M₄₃₇ all revealed neutral loss of HCl moieties. The proposed chemical formula for M₄₅₇ was C₁₆H₂₇Cl₄O₆⁻, which was inferred to be the glycosylated metabolite of CP-4 with an error of 3.6 ppm. M₄₇₃ (C₁₆H₂₇Cl₄O₇⁻) has two isomers that were found at 5.61 and 6.24 min and inferred to be monohydroxylated glycosylation metabolites with quasi-molecular ion ([M – H]⁻) and distinct chlorine isotope ratios. Two monohydroxylated glycosylation metabolites with 3 chlorines (M₄₃₇, C₁₆H₂₈Cl₃O₇⁻) and 5 chlorines (M₅₀₇, C₁₆H₂₆Cl₅O₇⁻) were eluted at 5.48 and 6.25 min, respectively. Similarly, M₅₂₃ (C₁₆H₂₆Cl₅O₈⁻) and M₄₈₉ (C₁₆H₂₇Cl₄O₈⁻) were concluded to be dihydroxylated glycosylation metabolites with an error of 1.0 and 3.6 ppm, respectively. Besides, a −HCl-eliminated-dihydroxylated-glycosylated metabolite (M₄₈₇, C₁₆H₂₅Cl₄O₈⁻) was also identified with isotopic quasimolecular [M – H]⁻. No characteristic fragments of glycosyl were detected even in high collision energy mode, most probably due to the low abundance of precursor ions, so these seven metabolites with minor responses were confirmed to level 4. No glycosylated metabolites of 52%-MCCP congeners were found in this work.

The above results showed that a total of 40 metabolites of CP-4 were identified, more than 52%-MCCP that has only 25 metabolites. This was complementary to the result of more dissipation of parent CP-4 than 52%-MCCP in the exposure systems, further indicating that SCCPs were more readily metabolized than MCCPs by the rice cells. Our results showed that MCCPs were less transformed and more persistent than SCCPs. Gluge et al. studied the biodegradation of SCCPs and MCCPs with different chlorine contents by calculation using EPI Suite and found that MCCPs are more hardly biodegraded than SCCPs, which was consistent with our result in this work.⁴⁵ Thus, MCCPs are not suitable substitutes for SCCPs, and more research is needed on MCCPs’ environmental behavior and persistence.

Metabolic Molecular Network Maps of CPs in Rice Cell Systems.

Metabolic networks are widely used to interpret metabolism pathways and the mechanisms of endogenous compounds.^46–48 Due to uncertainty in the active sites for substitution and conjugation for CPs, the metabolic molecular networks were used to describe the complex biotransformation processes of CP-4 and 52%-MCCPs that gave the reaction relations between parent CPs and metabolites and also between phase I and II metabolites. As shown in Figure 3, the metabolites derived from (multi-) hydroxylation, dechlorination, −HCl− elimination, and sulfation reactions for CP-4 were found in both the exposed rice cells and the medium solutions, while glycosylation metabolites (M₅₂₃, M₅₀₇, M₄₈₉, M₄₈₇, M₄₇₃, M₄₅₇, and M₄₃₇) were only detected in the rice cells. For 52%-MCCP, monohydroxylated highly chlorinated (Cl₇, Cl₈) metabolites (M₄₆₇ (C₁₅H₂₄Cl₇O⁻), M₄₈₈ (C₁₄H₂₁Cl₈O⁻)) were exclusively detected in the rice cells, while another 11 mono-, di-, and trihydroxylated-dechlorinated metabolites with 6, 5, or 4 chlorines (M₄₅₃, M₄₃₅, M₄₃₃, M₄₁₉, M₄₁₇, M₄₀₁, M₃₉₉, M₃₈₃, M₃₈₁, M₃₆₅, M₃₅₁) were detected both in the rice cells and in solutions. The remaining 12 (−HCl-eliminated-) tri- and tetrahydroxylated (hydroxylated-) sulfated metabolites with 3, 4, or 5 chlorines (M₄₈₁, M₄₆₅, M₄₄₇, M₄₃₃, M₄₃₁, M₃₉₉, M₃₉₇, M₃₈₁, M₃₆₅, M₃₆₁, M₃₄₇, M₃₄₅) were only found in the solutions. Since all of the above identified metabolites existed only in the exposure groups but not in any control groups, they were all produced and mediated by rice cells. Metabolites found only in rice cells further confirmed this. For the metabolites found in both rice cells and solution samples, the following hypotheses are formulated. (I) The transformation occurred in the rice cells under the catalysis of enzymes existing in the cells, and then the metabolites were eliminated from the cells into the solution. (II) The transformation was carried out in the medium solution mediated by the enzymes excreted from rice cells. (III) Those two kinds of transformations existed at the same time, in parallel, in the exposure systems. For those hydroxylated and (hydroxylated-) sulfated metabolites only found in the solutions, hypothesis II is the preferred explanation, but we cannot rule out the possibility that these more polar metabolites were very easily eliminated from rice cells (hypothesis I).

Figure 3.

Proposed metabolic molecular network maps of CP-4 (a) and 52%-MCCP (b) in the rice cell exposure systems. Metabolites were expressed using the abbreviations and details shown in Tables S3 and S4. (Red) Parent compounds. (Blue and gold) Metabolites of CPs in solution and rice cells, respectively. Red and black annotation represent the metabolites confident of level 3 and level 4.

Ample reports have shown that biotransformation plays a critical role on regulating the toxicity of xenobiotics to organisms via the “green liver model”.^22,49 Phase I reactions (hydroxylation, etc.) were usually considered as an activation step with phase I enzymes in organisms. The OH group was a widely reported active group easily forming phase II conjugation metabolites with endogenous molecules (glucose, etc.) of plants, e.g., 4-monochlorobiphenyl (CB-3) could be metabolized to form OH-CB-3s and sulfation CB-3s in sequence by poplar plants.^50–52 While phase II conjugation, especially the processes leading to polar biometabolites, could increase the excretion of the contaminants from the plant cells and improve the binding of the contaminants to the plant cell wall and is considered as an important detoxification process.^53,54 Taking Figure 3a as an example, monohydroxylated CP-4 linked to the parent compound uniquely, dihydroxylated, dechlorinated monohydroxylated, −HCl-eliminated monohydroxylated metabolites extended from the monohydroxylated CP-4 according to their reaction relations obtained through PMD analysis. Thus, from the metabolic network map, it could be concluded that the monohydroxylation reaction (phase I) was the activation metabolic step, generating dechlorinated or −HCl-eliminated (multi)-hydroxylation (di-, tri-, tetra-) metabolites. The OH group of hydroxylated metabolites was further triggered to form sulfation or glycosylation (phase II) metabolites.

More sulfation and glycosylation metabolites of CP-4 were identified than those of 52%-MCCP in number at the same exposure concentration. It might be related to the fact that 52%-MCCP was a mixture with thousands of congeners, and the concentration of each congener was far lower than that of CP-4; some metabolites of MCCP congeners might be yielded at nondetectable levels. For CP-4, fewer glycosylation metabolites were identified than sulfation metabolites in this report. For 52%-MCCP, several sulfation metabolites, but none of glycosylation metabolites, were found in the rice cell exposure systems. Though it was hard to estimate the contributions of sulfation and glycosylation to CP-4 metabolism without quantitative analysis on those metabolites, sulfation was considered more dominant than glycosylation for 52%-MCCPs in the rice cell exposure systems accordingly. For the halogenated organic pollutants, sulfation and glycosylation are the most commonly reported phase II metabolic reactions.^{32,42,50,55–57} Sulfation metabolites were found to be the major metabolic pathway of CB-3 in rats.^58,59 Erratico et al. reported that sulfation conjugates of hydroxylated bromodiphenyl ethers were formed more preferentially than the glucuronidated metabolites in an in vitro enzyme kinetic experiment.⁵¹ However, glycosylation was the predominant metabolism pathway for TBBPA in pumpkin that 86% of parent TBBPA was metabolized to form glycosyl TBBPA, and no sulfation metabolite was found.³⁸ Thus, sulfation and glycosylation behaviors depended greatly on the chemical and organism species.

To summarize, coupling the PMD analysis using HRMS/MS information with the characteristic chlorine isotopes, a total of 65 metabolites of CPs was successfully identified for the first time in exposed rice cell systems, including dechlorination (multi)-hydroxylation, −HCl− elimination (multi)-hydroxylation, sulfation, and glycosylation metabolites. Complex metabolism pathways were constructed correspondingly and complemented with metabolic molecular networks. The large extent of CPs transformation here illustrates the important role that plants play in the fate of CPs. Understanding the transformation behaviors of CPs provides indispensable information for the comprehensive assessment of their ecotoxicological risks. This work helps to fill the gap in the biotransformation of CPs by food plants to some extent. The metabolites in rice cells identified here may be further studied to improve our understanding of food safety and the potential adverse effects on biota (humans, herbivorous animals, and insects, etc.) related to CPs.