Do toxicokinetic and toxicodynamic processes hold the same for light and heavy rare earth elements in terrestrial organism Enchytraeus crypticus?

Journal Pre-proof Do toxicokinetic and toxicodynamic processes hold the same for light and heavy rare earth elements in terrestrial organism Enchytraeus crypticus?

Xueying Huang, Erkai He, Hao Qiu, Lulu Zhang, Yetao Tang, Chunmei Zhao, Min Li, Xue Xiao, Rongliang Qiu PII:

S0269-7491(19)37337-3

DOI:

https://doi.org/10.1016/j.envpol.2020.114234

Reference:

ENPO 114234

To appear in:

Environmental Pollution

Received Date:

11 December 2019

Accepted Date:

17 February 2020

Please cite this article as: Xueying Huang, Erkai He, Hao Qiu, Lulu Zhang, Yetao Tang, Chunmei Zhao, Min Li, Xue Xiao, Rongliang Qiu, Do toxicokinetic and toxicodynamic processes hold the same for light and heavy rare earth elements in terrestrial organism Enchytraeus crypticus?, Environmental Pollution (2020), https://doi.org/10.1016/j.envpol.2020.114234

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Journal Pre-proof Graphical abstract

Journal Pre-proof Do toxicokinetic and toxicodynamic processes hold the same for light and heavy rare earth elements in terrestrial organism Enchytraeus crypticus?

Xueying Huang1, Erkai He1,*, Hao Qiu2,3, Lulu Zhang4, Yetao Tang1,3, Chunmei Zhao1,3, Min Li1, Xue Xiao1, Rongliang Qiu1,3,5

1

School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou

510006, China 2

School of Environmental Science and Engineering, Shanghai Jiao Tong University,

Shanghai, 200240, China 3

Guangdong Provincial Key Lab for Environmental Pollution Control and Remediation

Technology, Sun Yat-sen University, Guangzhou 510006, China 4 South 5

China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China

Guangdong Laboratory for Lingnan Modern Agriculture, South China Agriculture

University, Guangzhou 510642, China

*Corresponding

author.

E-mail address: [email protected] (Erkai He)

1

Journal Pre-proof Abstract The widespread use of rare earth elements (REEs) in numerous sectors have resulted in their release into the environment. Existing knowledge about the effects of REEs were acquired mainly based on toxicity tests with aquatic organisms and a fixed exposure time, Here, the dynamic accumulation and toxicity of REEs (La, Ce, and Gd) in soil organism Enchytraeus crypticus were determined and modeled by a first-order one-compartment model and a time-toxicity logistic model, respectively. Generally, the accumulation and toxicity of REEs were both exposure level- and time-dependent. The overall uptake rate constants were 2.97, 2.48, and 2.38 L kg-1d-1 for La, Ce, and Gd, respectively. The corresponding elimination rate constants were 0.99, 0.78, and 0.56 d-1, respectively. The worms exhibited faster uptake and elimination ability for light REEs (La and Ce) than for heavy REEs (Gd). For all three REEs, the LC50 values based on exposure concentrations decreased with time and reached ultimate values after approximately 10 d exposure. The estimated ultimate LC50 values (LC50∞) were 279, 334, and 358 mg L-1 for Ce, Gd, and La, respectively. When expressed as body concentration, the LC50inter value was almost constant with time, demonstrating that internal body concentration could be a better indicator of dynamic toxicity of REEs than external dose. This study highlights that specific REE and exposure time should be taken into account in accurately assessing risk of REEs.

Key words: REEs, dynamic, accumulation, toxicity, TK-TD process Capsule: Toxicokinetics and toxicodynamics of REEs should be incorporated in assessing their risks to soil organism.

2

Journal Pre-proof 1.

Introduction Rare earth elements (REEs) include the family of lanthanides, scandium (Sc), and

yttrium (Y), possessing similar physical and chemical properties. According to their atomic number and electronic configuration, the REEs can be divided into two groups: the light rare earth elements (LREEs) La, Ce, Pr, Nd, Pm, Sm, and Eu, and the heavy rare earth elements (HREEs) Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, and Y (EPA 2012). Nowadays, REEs are widely used in high technology areas, e.g., information, biology, and energy (Du and Graedel, 2011; Sprecher et al., 2015). In addition, owing to their growth-promoting effects, the REEs have been extensively applied in agriculture, forestry, animal husbandry, and aquaculture for the past two decades in China (Yang et al., 1999; Hu et al., 2006). During the production, use, and disposal processes, REEs were unavoidably released into environment, causing elevated levels of REEs in natural water, sediments, and soils (Sneller et al., 2000; KulaksıZ and Bau, 2011). It has been reported that the measured mean REEs levels (4.67×103 mg kg-1) in the soil samples near the tailings were much higher than the background values of REEs (123.2 mg kg-1) in soil of Baotou region in China (Wang and Liang, 2015). The concentration of REEs in surface soil of southern REE mining areas can be five times higher than the average level of REEs in Chinese soils. Additionally, the total concentrations of dissolved REEs in river nearby REE mining areas are about three orders of magnitude higher than those in other natural rivers which not affected by mining activities (Liang et al., 2014). Thus, the ecotoxicology study of REEs is necessary for accurate assessment of its potential ecological risk. The REEs have shown a stimulatory or protective effect on organisms at low levels, while negative impacts on bacteria, plants, and animals could be induced when reaching critical concentrations (Pagano et al., 2015; Skovran and Martinez-Gomez, 2015; Herrmann et al., 2016). Previous studies of REE toxicity mainly focused on aquatic organisms, 3

Journal Pre-proof however, few ecotoxicity data are available for terrestrial organisms (González et al., 2014). Owing to the importance for soil ecosystem and the sensitivity to environmental stressors, Enchytraeids were often selected as model species in soil toxicity test (Didden and Rombke, 2001). Among Enchytraeids, Enchytraeus crypticus has a short life cycle, good control performance, and a large tolerance spectrum to soil properties (e.g. pH, clay content, organic matter content, temperature). It can be a good candidate for evaluating the soil toxicity of REEs (Castro-Ferreira et al., 2012; GonçAlves et al., 2016). Although REEs are a homogenous group with similar physiochemical properties, elements showed varied accumulation ability and toxic effect in organisms. Yang et al. (1999) reported that LREEs had higher bio-accumulative levels in aquatic organisms than that of HREEs. When exposing Hydra attenuate to eleven REEs, toxicity presented a decrease trend with the increasing atomic number, except for two heaviest elements (Er and Lu) (Blaise et al., 2018). Trifuoggi et al. (2017) utilized three varieties of sea urchins to identify the toxicity differences among seven REEs, showing that the pattern of embryotoxicity for individual REEs varied across test species. González et al. (2015) assessed the toxicity of LREE (Ce) and HREE (Gd, Lu) with six aquatic species, showing the toxicity of REEs to Aliivibrio fischeri and Pseudokirchneriella subcapitata increased with atomic number, while the other species were equally sensitive to tested elements. To date, there is still no consistent conclusion on how the accumulation and toxicity of REEs vary with their atomic number. Apart from exposure dose which has been widely recognized as a key factor in determining the ecotoxicity of chemicals, exposure time was also showed to be an important influencing factor especially under low-dose and long-term exposure conditions (Brock et al., 2010). Previously, toxicity tests were mainly conducted with a fixed exposure time to determine the dose-response relationship of chemicals, ignoring the factor of time. The 4

Journal Pre-proof toxicokinetics and toxicodynamics (TK-TD) concept was proposed, as it could help for better understanding of the dynamic accumulation and toxicity process of chemicals by considering both the exposure dose and exposure time as independent variables and by introducing the uptake, elimination and damage rates of chemical as constant parameters (Ashauer and Escher, 2010). Toxicokinetics links the external exposure dose of chemical to internal body concentration in a time course, including the processes of chemical uptake, distribution, transformation/sequestration and elimination. Toxicodynamics links the body concentration to toxic effects of organisms, describing the relationship between time and toxic response and including damage and recovery processes (Jager et al., 2011). The application of models using TK-TD concept have been well performed to incorporate the impact of exposure time on the accumulation and toxicity of chemicals (He and Van Gestel, 2013; Zhang and Van Gestel, 2017; Zhang et al., 2019). At present, the TK-TD concept is mainly developed for divalent metal ions (e.g. Ni, Pb and Zn), while they have not yet been validated for describing of accumulation and toxicity process of trivalent metal ions (e.g. REEs). Based on the assumption of critical body residual (CBR) theory, chemicals accumulated with time in the organism when uptake rate is higher than elimination rate (TK process), and toxic effect (e.g. mortality) may be induced when CBR is reached (TD process) (Broerse et al., 2012). Moreover, bioavailability of metals has been recognized as the fraction of total amount of metals that could be accumulated in organisms and finally cause toxic effect (Peijnenburg et al., 2002). In exposure medium, metal bioavailability can be influenced by environmental factors, such as pH, organic/inorganic ligands and coexisting cations (González et al., 2014; Herrmann et al., 2016; Khan et al., 2017). Above all, compared to external dose, the use of body concentration as exposure dose could incorporate the majority influence of exposure condition and exposure time. However, for the assessment of environmental risk of metals, total metal concentration is traditionally considered as the 5

Journal Pre-proof exposure dose and linked to toxic effect. Previous investigations have proved that body concentration was a better indicator than the total exposure concentration for predicting dynamic metal toxicity to organisms (He and Van Gestel. 2013; Topuz and Van Gestel. 2015; Zhang and Van Gestel. 2017). For REEs, the linkage between dynamic accumulation and toxicity deserves further investigation. Therefore, the present study aimed to investigate the dynamic accumulation and toxicity process of LREE (La, Ce) and HREE (Gd) in a terrestrial animal E. crypticus. Special attentions were paid 1) to determine whether the toxicokinetic and toxicodynamic processes of LREE and HREE differed with each other, and 2) to see whether body concentration could more accurately describe the dynamic toxicity of REEs. To achieve the above-mentioned aims, the uptake and elimination constants of REEs in organisms was quantified through fitting a first-order one-compartment model. Survival fraction at different exposure time was correlated to internal dose (body concentration) and external dose (free ion activity), separately.

2.

Material and methods

2.1 Test organism Enchytraeus crypticus (Enchytraeidae; Oligochaeta; Annelida) were cultured on agar media and kept in the climate room (20 ℃, 75% relative humidity). The agar media was prepared by mixing 1.875 g agar powder (Sigma-Aldrich) with 125 mL deionized water, the mixture solution was heated up just to boil for 1-2 minutes, cool down and then ready for use. The worms were fed regularly with yolk powder and oat meal. For the exposure experiment, adult worms, characterized by white spots in the clitellum region and length of approximately 1 cm, were used.

6

Journal Pre-proof 2.2 Exposure medium The quartz sand was used as test matrix in the present study. The specific procedures of preparing inert sand were to sift the sand by a 60-mesh sieve to obtain the finer sand, and then combust it at 600 ℃ for 3 h in the muffle furnace to remove the organic matter (Lock et al., 2006; Vijver et al., 2003). After that, the sand was immersed with diluted nitric acid for approximately 30 min to remove the organic residue, iron and manganese carbonate compounds, followed by repeatedly rinse with deionized water and dried at 60 ℃. In this way, the binding of REEs to test matrix could approximately be avoided. Simulated soil solution, which contained 0.2 mM Ca2+, 0.05 mM Mg2+, 2.0 mM Na+, and 0.078 mM K+, was used as dilution water to prepare test solution of La (LaCl3·6H2O), Ce (CeCl3·7H2O) and Gd (GdCl3·6H2O) of different concentrations. The pH of the test solutions was adjusted to 6.0 (± 0.05) with the 0.1 mM NaOH or HNO3, and 0.75 mg L-1 MES buffer. Before the exposure test, the test solution (5.5 mL) was added to test matrix (20.0 g inert sand) in a 100 mL glass jar for each replicate and equilibrated for 24 h. The solid to liquid ratio of test medium adopted in our study can keep the test matrix saturated. Therefore, worms were completely exposed to test solutions during the toxicity test. The sand-solution system was used to enable better control of exposure and speciation of REEs and avoid the influence solid phases of soil.

2.3 Toxicity test The dynamic uptake and toxicity tests of REEs were conducted with 6 different exposure time intervals: 1, 2, 4, 7, 10 and 14 d. Based on the results of a preliminary toxicity experiment (range-finding test), exposure concentrations of La and Gd were set as 0, 50, 100, 200, 300, 400, 500, 600, and 700 mg L-1, while the exposure concentrations of Ce were set as 0, 50, 100, 200, 250, 300, 350, 400, and 450 mg L-1 in order to obtain the entire 7

Journal Pre-proof dose-response relationship. Three replicates were utilized for each treatment of different exposure concentration and exposure time. For each replicate, 10 adult worms were introduced into a glass jar containing the prepared test medium. The jars were covered with perforated aluminum foils to reduce water volatilization and to prevent worms from escaping. The experiments were conducted in a climate room at 20 ℃, 75% relative humidity, and a cycle of 12 h light/12 h dark. Deionized water was added every 2d to offset water evaporation and to maintain the concentration of REEs in test medium unchanged during exposure. The exposure media after replenishing deionized were homogenized by slight shaking of the jars. During the test, the worms were not fed to avoid the influence of food on metal speciation. At the end of the toxicity test, surviving worms from three replicates of each treatment were counted, collected, rinsed with deionized water, and frozen at -20 ℃ for analysis of body REE concentration.

2.4 Chemical analysis The frozen worms were freeze-dried with freezer dryer (Labconco) for at least 48 h and weighed individually with the microbalance (Mettler-Toledo XPR2U), and then transferred to thoroughly cleaned Pyrex glass tubes (He and Van Gestel, 2013). The average fresh weight of the worms was approximately 1 mg. To measure concentration of REEs in worms, the samples were digested with HNO3 (65%-68%, GR) by a series of heating steps (85 ℃ for 3 h; 110 ℃ for 3 h; 130 ℃ for 30 mins; 150 ℃ until no acid left). Residues were dissolved into 5 mL 1% HNO3 and concentration of REEs was determined by Inductively Coupled Plasma Mass Spectrometry (ICP-MS; NexION 350D; Perkin Elmer) (He and Van Gestel, 2013; Zhang and Van Gestel, 2017). For every digestion cycle, 2 replicates of blank were performed simultaneously in order to ensure no pollution happened during the whole digestion process. Concentrations of La, Ce and Gd in test solutions were measured by 8

Journal Pre-proof Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES; 5300DV; Perkin Elmer) and used as external exposure dose for data analysis in the present study.

2.5 Modelling 2.5.1 Toxicokinetic process Assuming the exposure concentration of chemicals (La, Ce, Gd) remained steady during the exposure, a first-order one-compartment equation with uptake (Ku, L kg-1d-1) and elimination rate constant (Ke, d-1) was applied to describe the dynamic accumulation process of REE in organisms (Crommentuijn, 1994). Co(𝑡) =

𝐾𝑢 × 𝐶𝑤 𝐾𝑒

× (1 ― 𝑒 ― 𝐾𝑒 × 𝑡)

(1)

where Co (t) is the body concentration of REEs in the test organism at different sampling times (mg kg-1 REE dry body wt), Cw is the measured exposure concentration of REEs in test solutions, t represents exposure intervals (d). To find the overall Ku and Ke values, Equation (1) was fitted by minimizing the sum of squared residuals of predicted and observed body concentration for all data sets together. The background concentration was set as 0 in the present study because almost no REE was observed in the control organisms.

2.5.2 Toxicodynamic process Log-logistic equation was applied for describing the survival fraction of organisms exposed to different concentration of REEs. 𝑆=

𝑆𝑚𝑎𝑥 Cw

(2)

𝑏

1 + (LC50)

Median lethal concentration (LC50) means 50% of mortality was induced for test organism at a certain concentration, S is the percentage of survival at certain exposure time, Smax is the maximum fraction of survival, and b represents the slope parameter. 9

Journal Pre-proof The ultimate LC50 value (LC50∞, mg L-1) is related to the damage rate constant of chemicals (Kd, d-1), the relationship between LC50 and exposure time could be described by a time-toxicity relationship equation (Crommentuijn, 1994). LC50(t) =

𝐿𝐶50∞ 1―𝑒

(3)

― 𝐾𝑑 × 𝑡

2.5.3 Relating toxicokinetics to toxicodynamics Log-logistic equation was used to relate survival fraction to body concentrations of REEs in organisms at certain time interval. 𝑆𝑚𝑎𝑥

𝑆=

𝐶0

1 + (LC50

(4)

𝑏

)

inter

where S is the survival fraction (%), C0 is the body concentration of REEs in E. crypticus (mg kg-1 dry body wt), LC50inter is the LC50 expressed as body concentration (mg kg-1 dry body wt), and b is the slope. The generalized-reduced-gradient-iterative solver function in the software JMP 16.0 (SAS Institute) was used for model fitting. All unknown parameters above were derived with the least square method, i.e., fitting uptake and toxicity data to the relevant equations with the solver function to minimize the sum of squared residuals of predicted and observed values.

3. Results 3.1 Dynamic bioaccumulation of REEs The relationship between body concentration of REEs in E. crypticus and exposure time under different exposure concentrations are shown in Figure 1. No surviving organisms was found under the exposure concentrations of La (518, 563, 687 mg L-1), Ce (348, 408, 466 mg L-1) and Gd (520, 711, 843 mg L-1) after 2 d, under the exposure concentrations of Ce (295 mg L-1) after 10 d, and under the exposure concentrations of Gd (457 mg L-1) after 7 d. Thus, 10

Journal Pre-proof body concentrations could not be measured under these treatments. Generally, body concentrations of REEs were positively related to exposure concentration and exposure time. The time required to reach equilibrium of body concentration was affected by the exposure levels and characteristics of REEs. With elevated exposure concentration of REEs, the equilibrium time was shortened. Under similar exposure level, time needed to reach the steady state of body residual of Ce is longer than that of La and Gd. The steady-state concentration of Gd in organisms was the highest and followed by Ce and La. For example, after 7 d exposure of La (201 mg L-1), Ce (229 mg L-1) and Gd (224 mg L-1), body concentration reached to 359 (±73), 721 (±100) and 823 (±103) mg kg-1 dry body wt, respectively. When all data from dynamic uptake at different exposure concentrations were fitted to one-compartment model (Equation 1), the estimated overall uptake rate constants (Ku) were 2.97 ± 0.66, 2.48 ± 0.21, and 2.38 ± 0.39 L kg-1d-1 and elimination rate constants (Ke) were 0.99 ± 0.097, 0.78 ± 0.060, and 0.56 ± 0.043 d-1 for La, Ce and Gd, respectively (Table 1). Generally, with increasing atomic number of REEs, the uptake and elimination rate constant reduced. When uptake data at different exposure concentration was fitted separately, Ku reached the highest value of 3.66 and 2.69 L kg-1d-1 when exposed to 280 mg L-1 of La and 329 mg L-1 of Gd, respectively, and then decreased with ascending exposure level. Ke values showed the similar trend with Ku for La and Gd. For Ce, the values of Ku and Ke showed a rough increasing trend with exposure level, ranging from 0.356 to 2.73 L kg-1d-1 and from 0.182 to 0.680 d-1, respectively (Table 1). The dynamic bioaccumulation of La, Ce and Gd was well described by the one compartment models, with R2 = 0.90, p < 0.01; R2 = 0.86, p < 0.01; and R2 = 0.87, p < 0.01, respectively.

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Journal Pre-proof 3.2 Dynamic toxicity of REEs Developments of survival fraction with exposure concentrations of REEs under different exposure time are shown in Figure 2. In the present study, no mortality of organisms was observed in the control groups during 14 d exposure. Overall, survival fraction of E. crypticus decreased with increasing exposure level and exposure time. The LC50s on the basis of external concentrations for the toxic effect of La, Ce and Gd as a function of time were calculated with Equation 2 and are shown in Figure 3. For La, Ce, and Gd exposure series, with increasing exposure time (1 d to 14 d), LC50 values decreased from 663 (±15.9) to 365 (±0.43) mg L-1, from 377 (±1.18) to 264 (±25.6) mg L-1, and from 455 (± 354) to 320 (± 0.355) mg L-1, respectively (Table 2). The LC50 showed a downtrend with time, and steady states were reached after around 10 d of exposure. Compared the LC50 values of La, Ce and Gd at a certain exposure time, it can be seen Ce was of strongest toxicity, followed by Gd and La. When fitting the dynamic LC50 values of La, Ce and Gd to Equation 3 separately, the estimated ultimate LC50 (LC50∞) values were 358 (±11.0), 297 (±0.383), and 334 (±12.7) mg L-1, the damage rate constants (Kd) were 0.805 (±0.058), 1.573 (±0.046) and 1.258 (±0.175) d-1, respectively (Table 2). The model well described the changes in LC50 values with time (R2 of 0.96 and p < 0.01) except for data point under 1 d La treatment, which might be caused by the delayed toxicity process compared with the accumulation process.

3.3 Relationship between bioaccumulation and toxicity of REEs In Figure 4, survival fraction was related to the measured body concentration of REEs under different exposure concentration and exposure time. Generally, toxicity of REE showed an increasing trend with the increasing body concentration. LC50inter values based on body concentrations of REEs at different time points were obtained by fitting toxicity data to 12

Journal Pre-proof the log-logistic model (Equation 4) and are shown in Table 3. The overall LC50inter values for La, Ce and Gd were 1280 (1224-1335), 1119 (1056-1181) and 1193 (1177-1208) mg kg-1 dry body wt, respectively. When LC50inter were estimated at each exposure time for La, Ce and Gd, separately, similar values were found for each treatment, except for 1 d exposure of La.

4. Discussion 4.1 Toxicokinetic process of REEs in E. crypticus The one compartment model was applied in describing the uptake and elimination processes of light and heavy REEs in E. crypticus in our study. It is noted that the one compartment model agreed well with the dynamic accumulation data of La, Ce and Gd, indicating the applicability of using uptake and elimination rate constants to describe the toxicokinetic processes of REEs in organisms with varied exposure dose in the environment. In general, for La, Ce and Gd, the values of Ke were significantly higher than zero, suggesting the eliminating ability of E. crypticus for REEs. Moreover, the estimated value of overall Ku obviously exceeded that of overall Ke. In the concept of one-compartment model, the accumulation of metal in the organisms occurred when the uptake rate exceeds the loss rate by detoxification and elimination (Ashauer and Escher, 2010; Broerse et al., 2012). The estimated overall Ku value was highest for La (2.97 L kg-1 d-1) and slightly decreased with increasing atomic number, with Ce and Gd of 2.48 and 2.38 L kg-1 d-1, respectively. The Ke values showed the similar trend. The result implied that light REEs could be more easily taken up and excreted by E. crypticus. This phenomenon was similar to the findings for green alga Chlamydomonas reinhardtii, with the increase of atomic number, the maximum uptake rate of La, Ce, Sm and Eu decreased progressively from 2.0×10-14 to 1.4×10-14 mol cm-2 s-1 (Tan et al., 2017). Previously, the toxicokinetic processes of some monovalent and divalent metal ions in E. crypticus were also investigated and quantified. The uptake rate constants of 13

Journal Pre-proof Ni and Ag in E. crypticus exposed in solutions-sand medium were 11.9 and 49.5 L kg-1 d-1, separately (He and Van Gestel, 2013; Topuz and Van Gestel, 2015). The uptake rate constant of Pb in E. crypticus exposed to contaminated Lufa soil was 0.14 kgsoil kgworm-1 d-1 (Zhang and Van Gestel, 2017). In comparison, the uptake rate of REEs obtained in this study was lower than that of monovalent and divalent metal ions for E. crypticus under the same exposure condition, however, much higher than that of Pb in soil. The physiochemical properties such as pH, ionic strength, and inorganic and organic complexing agents were found being key influencing factors of metal distribution and availability in water and sediment (Herrmann et al., 2016). Binding of REEs to mineral particles, colloids and organic/ inorganic matters in soil led to the reduced availability and uptake rate (Romero-Freie et al., 2018). For different species exposed to same metal, the existence of species-specific differences in metal kinetics was also reported, e.g. the kinetic parameters of Cd in Lumbricus rubellus and Eisenia Andrei (Vijver et al., 2005; Smith et al., 2010). Overall, the uptake rate of a chemical was closely related to test species, chemical species, and exposure conditions (Ardestani et al., 2014). Apart from the estimation of overall value of Ku and Ke, the Ku and Ke under different exposure concentrations were estimated separately to determine the influence of exposure level on the uptake and eliminate rate constants. Generally, with the increasing exposure concentration of La and Gd, the Ku and Ke reached the highest value and then decreased with ascending exposure level. For Ce, the values of Ku and Ke showed a rough increasing trend with increasing exposure level. Crommentuijn et al. (1994) demonstrated that the uptake rate constant was determined by characteristics of the test species and toxic substances and the environmental factors influencing bioavailability of chemicals. While, the elimination rate constant was mainly determined by characteristics of the test organisms. It has been reported that with increasing exposure concentration the Ku of Ni in E. crypticus increased initially 14

Journal Pre-proof and then decreased after peaking, while the values of Ke remained almost constant (He and Van Gestel, 2013). Similarly, the Ku of Cd in E. albidus decreased with increasing exposure concentration (Lock and Janssen, 2001). Ameh et al. (2012) showed that the Ku of Ni in the earthworm Eudrilus eugenia had a negative relationship with exposure concentration, while the Ke showed a poor correlation with exposure level. So, a simple relationship between uptake and elimination rate constants and exposure concentrations of REEs could not be established. When comparing the body concentrations of REEs at the same exposure level, it was found that Gd had greater accumulation ability than that of Ce and La. The bioaccumulation of LREEs in bacteria also showed a rising trend from La to Eu with increasing atomic number, while this trend was not observed for HREEs (Tsuruta, 2006). For fungal biomass (Trichoderma strains), Ce possessed the most accumulation ability, followed by La, Gd, Pr, and Nd (d’Aquino et al., 2009). The accumulation ability of La, Ce, and Nd of hepatocytes varied in its nuclei and mitochondria (Huang et al., 2011).

4.2 Toxicodynamic process of REEs in E. crypticus In the present study, the toxicity of La, Ce and Gd for E. crypticus increased with time, showing exposure time played a significant role in toxicity of REEs before the equilibrium was reached. However, most ecotoxicity tests of REEs were performed with a fixed and short exposure time, leading to the possible underestimation of environmental risk of REEs. For the exposure of REEs to Lemna minor L., toxic effects were observed after prolonged exposure but not in acute toxicity test (Paola et al., 2007). Consistently, the toxicity of conventional monovalent and divalent metals also found increasing with exposure time and then reached steady state (Broerse and Van Gestel, 2010; Topuz and Van Gestel, 2015). Hence, the acute toxicity data of REEs was not reliable for the assessment of ecotoxicity of 15

Journal Pre-proof REEs and time effects should be well considered (Blinova et al., 2018). The estimated LC50∞ values for La, Ce and Gd were 358, 297, and 334 mg L-1, respectively. Obviously, even Gd accumulated mostly in organisms, Ce showed highest toxic effects and the damage rate constants (Kd) were of the same order. Similar result was found in the research of Gong et al. (2019), where the effects of La, Ce, and Y on root growth of wheat (Triticum aestivum L.) were investigated and Ce showed to be the most toxic element. For aquatic biota, the increased toxicity of REEs was observed with increasing atomic number for Aliivibrio fischeri and Pseudokirchneriella subcapitata, while these REEs were almost equally toxic for other species (González et al., 2015). In contrast, REEs presented a decreasing trend of toxicity with increasing atomic numbers for Hydra attenuata, except for the two heaviest elements (Er and Lu) (Blaise et al., 2018). Overall, toxicity of REEs did not show a coherent trend with their atomic number. Without considerations of interspecies differences, the distinctions of toxicity can be due to the variations in metal bioavailability in different uptake processes, or different basic physiological processes at the organism level (Rainbow et al., 2002). Wang et al. (2017) reported that Tb (HREE) had higher activity in forming the complex with the hERG K+ channel protein than La (LREE) and the function of K+ channel decreased to different degrees, resulting the cytotoxicity order of Tb > La. When investigating the potential sub-lethal effects of Sm and Y on Dreissena polymorpha, the major impacted biomarkers by Sm were found different from that of Y, suggesting that REEs displayed different modes of action (Hanana et al., 2018). The differences in toxicity of varying REEs could be related to their toxic mechanisms at the molecular level, therefore, further investigations are required.

4.3 Link between Toxicokinetic and Toxicodynamic process Based on our findings, LC50 values of La, Ce, and Gd, expressed as external 16

Journal Pre-proof concentrations, changed with time, while LC50 values of La (except for 1d), Ce, and Gd, expressed as body concentrations remained almost constant at different exposure time. The results were consistent with the previous findings for monovalent and divalent metal ions, showing that the LC50 values based on internal concentrations of Ni, Ag and Zn in the animals were almost stable over time (Topuz and Van Gestel, 2015; He and Van Gestel, 2013; He et al., 2019). In this study, LC50inter of La decreased with time from 1 to 2 d exposure, and then reached steady states. For the toxicity of Pb in E. crypticus, LC50inter was found varied with time because of the delayed toxicity of Pb compared to its accumulation (Zhang and Van Gestel., 2017). Since LC50inter was independent of exposure time, body concentration could be a better indicator to describe toxicity of REEs than external exposure concentration. Our results showed a well correlation between body REEs concentrations and their toxicity to E. crypticus. Exposure concentration, bioaccumulation factor, internal concentration etc. were used to represent the amount of toxicant at target sites within organisms (Mccarty and Mackay, 1993; Lock and Janssen, 2001). Compared to total metal concentration and free ion activity in exposure medium, internal dose is a more direct metrics for describing toxicity given the influence of environmental factors on the bioavailability of chemicals are incorporated (Gopalapillai and Hale, 2017). The toxicity increased with increasing bioaccumulation of REEs when all elements inside the organisms showing equally toxicity, hence, more accumulation resulted in more adverse effects (González et al., 2014). In this study, Gd was found of the greatest accumulating ability, while it was not the most toxic element among three tested elements. Hence, body concentration of REEs could not fully represent body residues that cause toxicity and this might be due to the different detoxification mechanisms of REEs in the Enchytraeids. For conventional divalent metals, it has been proved that organisms are able to control metal concentrations in certain tissues of their body to minimize damage of reactive 17

Journal Pre-proof forms of metals, e.g. bound to intracellular granules (Vijver et al., 2004). Metal toxicity is mainly explained by metal associated with enzymes and cell organelles contained the metal sensitive fraction. While, metal bound to heat stable proteins, including metallothionein-like proteins or metal rich granules, is considered as biologically detoxified (Jokob et al., 2017). In the research of Ding et al. (2006), obvious fractionation was found among light, middle and heavy REEs in hydroponic wheat (Triticum aestivum), showing small chemical properties difference of REEs could cause varied accumulation and distribution pattern. The fractionation of REE was mainly caused by chemical precipitation, cell wall absorption and complexation by organic ligands in xylem vessels. The obtained Ke values (related to body concentration) differed from Kd values (related to toxicity) also confirmed this conclusion. When expressing body residues with total measured body concentrations, the capacity of sequestration and compartmentalization to metals by organisms is neglected, causing the predictability of toxic effects decreased (Vijver et al., 2004).

5.

Conclusions In the present study, the dynamic bioaccumulation and toxicity of La, Ce, and Gd in E.

crypticus were assessed under the conceptual framework of “toxicokinetics and toxicodynamics”. It was proved that the bioaccumulation and toxicity of REEs in E. crypticus were dependent not only on exposure dose but also on exposure time. The estimated uptake and elimination rates of La were of highest value, followed by Ce and Gd, demonstrating LREE could be taken up and released faster than that of HREE. The toxicity of REEs showed a decreasing order for Ce, Gd and La. No general conclusion can be drawn on the relationship between REEs toxicity and their atomic number. The LC50 values (based on exposure concentration) of REEs decreased with time until equilibrium was reached, while the LC50inter values (based on body concentration) remained almost constant over time, 18

Journal Pre-proof showing body concentration was a better predictor than exposure concentration for the toxicity of REEs. For the purpose of conducting accurate risk assessment of REEs, further research on “bioaccumulation-ecotoxicity” pattern of REEs in terrestrial organisms under different environmental conditions is needed.

Acknowledgements This work was supported by the National Key R&D Program of China (No. 2018YFC1800500), the National Natural Science Foundation of China (No. 41701573, No. 41701571, No. 41877500, and No. 41977115), the 111 Project (B18060), the Science and Technology Program of Guangzhou, China (No. 201904010116), and the Fundamental Research Funds for the Central Universities (No. 19lgpy150), the Research Fund Program of Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology (No. 2018K01).

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22

Journal Pre-proof There is no competing interest to declare.

Journal Pre-proof Author contribution statement EH conceived the idea and designed the experiment; XH, ML, and XX performed the experiment; EH, XH, and HQ wrote the manuscript; all authors reviewed and revised the manuscript; EH, HQ, and RQ raised the funding.

Journal Pre-proof

Body La concentration (mg kg-1)

1800

La (mg L-1) 0.00 44.2 90.0 201 280 379

(A)

1500

1200

900

600

300

0 0

2

4

6

8

10

12

14

Time (day)

Body Ce concentration (mg kg-1)

1500

Ce (mg L-1) 0.00 56.8 113 174 229 295

(B)

1200

900

600

300

0 0

2

4

6

8

10

12

14

Time (day)

Body Gd concentration (mg kg-1)

1800

Gd (mg L-1) 0.00 49.9 101 224 329 457

(C)

1500

1200

900

600

300

0 0

2

4

6

8

10

12

14

Time (day)

Figure 1. Relationship between body REEs concentration (mg kg-1 dry body wt) in E. crypticus and exposure time under different concentrations of (A) La, (B) Ce and (C) Gd in sand-solution system. Data points show observed values with standard error, solid lines represent the fit of body REEs concentration data to the one compartment model (Equation 1) under different exposure level of REEs separately.

1

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Survival fraction (%)

100 80

La 1d 2d 4d 7d 10d 14d

60 40 20 0

(A) 0

100

200

300

400

500

600

700

Measured La concentration (mg L-1)

Survival fraction (%)

100 80

Ce 1d 2d 4d 7d 10d 14d

60 40 20 0

(B) 0

100

200

300

400

500

Measured Ce concentration (mg L-1)

Survival fraction (%)

100 80

Gd 1d 2d 4d 7d 10d 14d

60 40 20 0

(C) 0

100 200 300 400 500 600 700 800

Measured Gd concentrarion (mg L-1)

Figure 2. Correlated the survival fraction of E. crypticus with measured exposure concentrations of (A) La, (B) Ce, (C) Gd in sand-solution system after different exposure time. Data points show mean values of the survival fraction (with standard error) under different treatments, and solid lines show the fit of logistic survival model (Equation 2) to the toxicity data of different treatments separately.

2

Journal Pre-proof

700

La Ce Gd

LC50 (mg L-1)

600

500

400

300

200 0

2

4

6

8

10

12

14

Time (day)

Figure 3. LC50 value of E. crypticus at different time intervals exposed to La, Ce and Gd in sand-solution system. Data points (with standard error) represent LC50 values calculated by Equation 2 on the basis of the measured La, Ce and Gd concentrations in the test solutions. The solid lines show the exponential decrease of LC50 based on the data fitting to Equation 3.

3

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1d 2d 4d 7d 10 d 14 d

Survival fraction (%)

100 80 60

R2=0.74 p<0.01

40 20 0

(A) 0

500

1000 1500 2000 2500 3000

Body La concentration (mg kg-1)

1d 2d 4d 7d 10 d 14 d

Survival fraction (%)

100 80 60

R2=0.80 p<0.01

40 20 0

(B) 0

500

1000

1500

2000

2500

Body Ce concentration (mg kg-1)

1d 2d 4d 7d 10 d 14 d

Survival fraction (%)

100 80 60

R2=0.98 p<0.01

40 20 0

(C) 0

500

1000 1500 2000 2500 3000

Body Gd concentration (mg kg-1)

Figure 4. Relationship between the survival fraction of Enchytraeus crypticus and body concentrations of (A) La, (B) Ce and (C) Gd at different exposure time. Data points (with standard error) represent the average value of survival fraction and body concentration. The solid lines show the fit of logistic dose-response model (Equation 4) to all data together.

4

Journal Pre-proof Highlights (1) Toxicokinetics and toxicodynamics of REEs in E. crypticus were investigated (2) E. crypticus had higher uptake and elimination ability for La and Ce than for Gd (3) Ce showed to be most toxic element even Gd was mostly accumulated in E. crypticus (4) Internal dose of REE correlated better with dynamic toxic effect than external dose

Table 1. Estimated toxicokinetic parameters (standard error, ± SE) for describing the uptake and elimination process of La, Ce, and Gd in Enchytraeus crypticus obtained by the fit of one compartment model (Equation 1) to the body concentrations of REE at different exposure concentrations, separately. La

Ce

Gd

Treatment

Ku

Ke

Treatment

Ku

Ke

Treatment

Ku

Ke

(mg L-1)

(L kg-1d-1)

(d-1)

(mg L-1)

(L kg-1 d-1)

(d-1)

(mg L-1)

(L kg-1 d-1)

(d-1)

0.244

0.082

0.356

0.182

(±0.021)

(±0.019)

(±0.048)

(±0.039)

0.390

0.169

0.429

0.212

(±0.074)

(±0.053)

(±0.076)

(±0.055)

0.336

0.092

0.904

0.384

(±0.052)

(±0.034)

(±0.351)

(±0.191)

3.66

1.47

0.824

0.191

(±1.26)

(±0.53)

(±0.066)

(±0.024)

3.20

0.892

2.73

0.680

(±0.34)

(±0.105)

(±0.221)

(±0.065)

2.97

0.99

2.48

0.78

(±0.66)

(±0.097)

(±0.21)

(±0.060)

44.2 90.0 201 280 379 Overall

56.8 113 174 229 295 Overall

1

49.9 101 224 329 457 Overall

1.13

0.155

(±0.303)

(±0.021)

2.07

0.539

(±0.675)

(±0.021)

1.87

0.533

(±0.361)

(±0.021)

2.69

0.691

(±0.495)

(±0.021)

1.91

0.367

(±0.223)

(±0.051)

2.38

0.56

(±0.39)

(±0.043)

1

Table 2. LC50s with standard error (±SE) for the toxicity of La, Ce, and Gd on Enchytraeus crypticus at different exposure times based on

2

measured concentrations of REE in test solutions. LC50 values were estimated using a logistic survival model (Equation 2). The incipient LC50

3

value (LC50∞) and damage rate constant (Kd) were calculated by Equation 3, which described the relationship between LC50 and exposure time. LC50 (mg L-1) LC50∞ (mg L-1)

Kd (d-1)

1d

2d

4d

7d

10 d

14 d

La

663 (±15.9)

411 (±3.64)

377 (±0.04)

377 (±0.04)

368 (±0.35)

365 (±0.43)

358 (±11.0)

0.805 (±0.058)

Ce

377 (±1.18)

302 (±1.26)

298 (±0.095)

297 (±63.8)

268 (±11.2)

264 (±25.6)

297 (±0.383)

1.573 (±0.046)

Gd

455 (±354)

394 (±6.53)

363 (±8.36)

329 (±13.1)

311 (±7.44)

320 (±0.355)

334 (±12.7)

1.258 (±0.175)

4

2

Journal Pre-proof 5

Table 3. LC50s with 95% confidence intervals for the toxicity of La, Ce, and Gd to

6

Enchytraeus crypticus at different exposure times based on measured body concentration of

7

La, Ce and Gd (mg kg-1 dry body wt). LC50inter values were estimated using a logistic dose-

8

response model (Equation 4). R2 is the coefficient of determination of the regression analysis

9

between the observed and predicted survival fraction of E. crypticus.

Time

La

Ce

Gd

LC50inter

LC50inter

LC50inter

R2 (mg kg-1)

R2 (mg kg-1)

R2 (mg kg-1)

1d

2513 (±145)

0.97

974 (±23.5)

0.99

1276 (±0.638)

0.99

2d

1310 (±56.3)

0.99

936 (±5.55)

0.99

1095 (±0.176)

0.99

4d

1225 (±0.292)

0.99

1074 (±2.22)

0.99

1187 (±3.69)

0.99

7d

1348 (±0.205)

0.99

1311 (±0.826)

0.98

1218 (±51.2)

0.98

10d

1364 (±3.35)

0.99

1103 (±72.7)

0.96

1314 (± 17.3)

0.99

14d

1254 (±0.835)

0.99

1568 (±747)

0.79

1318 (±2.99)

0.98

All together

1280 (±55.1)

0.74

1119 (±62.5)

0.80

1193 (±15.3)

0.98

10

3