Effects of narcotic industrial pollutants on behaviour of midge larvae (Chironomus riparius (Meigen), Diptera): a quantitative structure-activity relationship

Effects of narcotic industrial pollutants on behaviour of midge larvae (Chironomus riparius (Meigen), Diptera): a quantitative structure-activity relationship

ELSEVIER Aquatic Toxicology 28 (1994) 209-221 AOgAHC lglgGHi,BGY Effects of narcotic industrial pollutants on behaviour of midge larvae (Chironomus...

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ELSEVIER

Aquatic Toxicology 28 (1994) 209-221

AOgAHC lglgGHi,BGY

Effects of narcotic industrial pollutants on behaviour of midge larvae (Chironomus rt'parius (Meigen), Diptera): a quantitative structure-activity relationship Peter T.J. van der Zandt *'a, Floor Heinis b, Arjen Kikkert b aDirectorate-Generalfor Environmental Protection, P.O. Box 30945, 2500 GX The Hague, The Netherlands bAquaSense, Amsterdam, The Netherlands

(Received 8 August 1992; revision received 30 August 1993; accepted 15 December 1993)

Abstract

Fourth-instar larvae of the midge Chironomus riparius were exposed for 96-98 h in a semistatic substrate-water system to nine industrial pollutants with a narcotic mode of action. Effects on the behaviour of the larvae were registered by means of the impedance conversion technique. Despite the common mode of action of the tested chemicals, different behavioural responses were observed. No-observed-effect concentrations (NOECs), based on aqueous concentrations, were derived. Correlation of these NOECs with octanol-water partition coefficients (Kow), ranging from -0.77 to 4.64, demonstrated a very accurate quantitative structureactivity relationship (QSAR). The results indicate that behaviour of chironomids is one of the most sensitive parameters in aquatic toxicity tests with narcotic chemicals. Key words." Chironomidae; Organic micropollutants; Toxicity; Narcosis; Behaviour; QSAR

1. Introduction For the major part of all existing chemicals - nowadays many hundreds of thousands of chemicals are known and more than 100000 are commercially available (CEC, 1987) - knowledge of (eco)toxicological effects, individually or in mixtures, is fragmentary or non-existent. If any assessment of the ecotoxicological potential of a chemical is performed, the tests are in most cases restricted to determination of the acute toxicity to pelagic species: fish, crustaceans (Daphniamagna), or algae. Consequently, little is known of the toxicity of chemicals to benthic organisms.

*Corresponding author. 0166-445X/94/$07.00 © 1994 Elsevier Science B.V. All fights reserved SSD I 0166-445X(93)E0058-J

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The larvae of Chironomidae (Diptera) often are the most widely distributed and frequently the most abundant group of insects in freshwater ecosystems (Pinder, 1986). They occupy an important position in aquatic food webs as they are major forage resources for fish and other vertebrate or invertebrate predators. Benthic organisms live in close contact with sediments that frequently adsorb and accumulate certain pollutants. Thus, chironomids and other benthic species may be exposed to xenobiotics via water and via sediment. Changes in behaviour of these organisms may give the first observable biological indication of perturbation of their environment (Rand, 1985). Quantitative structure-activity relationships (QSARs) can be useful tools for the estimation of environmental fate and effects of chemicals (Hermens, 1989). The effect concentrations of the large group of relatively unreactive organic chemicals that act by narcosis have been shown to be dependent on the octanoi-water partition coefficient (Kow) of these chemicals (K6nemann, 1981; Veith et al., 1983). In a recent study, Van Leeuwen et al. (1992) derived QSARs based on no-observed-effect concentrations (NOECs) for nineteen aquatic species with a variety of ecological functions at different trophic levels. 'No-effect levels' at an ecosystem level, i.e. hazardous concentrations for 5% of the species (HC5) in water, were extrapolated from these QSARs for about a hundred organic chemicals with a narcotic mode of action. Subsequently, the equilibrium partitioning theory, based on an equation as given by Van der Kooij et al. (1991), was applied to derive HC5 values for sediment. These levels could not be extrapolated directly from toxicity data, simply because data for these substances on sediment-dwelling organisms are lacking. In view of the lack of data on the effects of organic pollutants on sediment-dwelling organisms and because of the need for information on the relative sensitivity of these organisms to organic pollutants compared to organisms living in the water column, a study of larvae of the midge Chironomus riparius was undertaken. A QSAR for the effects of narcotic chemicals on the behaviour of midge larvae was calculated and compared with QSARs for other aquatic species.

2. Materials and Methods Test organisms

In this study, fourth-instar larvae of the midge Chironomus riparius were used as test organisms. Midges were reared essentially as described by Anderson (1980) and modified by Heinis et al. (1990). They originated from a laboratory culture which was established five years ago. The larvae were kept at a temperature of 20 + I°C in a glass aquarium, filled with filtered water from Lake Maarsseveen and a substrate consisting of a layer of clean cellulose fibres. This substrate enables the tube-dwelling chironomids to exert their normal burrow-constructing behaviour. The larvae were fed twice a week with 5 ml of a suspension comprising of 10 g Trouvit and 0.5 g Tetraphyll in 300 ml distilled water. A 16-h light/8-h dark regime was maintained, using incandescent light. Under these conditions, a full cycle from the egg stage to the adult midge takes about three weeks.

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Test compounds The nine compounds tested are reported in the literature to have a narcotic mode of action (cf. Hermens, 1989) and included alcohols, several (substituted) aromatic hydrocarbons, and a ketone. Experimental octanol-water partition coefficients of these compounds were preferably obtained from De Bruijn et al. (1989), who determined Kow values using the slow-stirring method, or else from the THOR database in which so-called 'log P*'-values, classified as 'best measured values in literature', are available. The selected compounds covered a log Kow range from -0.77 to 4.64. A summary of the tested compounds and some of their characteristics is given in Table 1. Solutions of all tested compounds were made in particle-free water (mesh 0.45 gm) from Lake Maarsseveen I (Utrecht, The Netherlands; hardness 150 mg/1 as CaCO3; pH 8). Methanol was dissolved in water by firm shaking. 2-Methyl-l-propanol, 4-methyl-2-pentanone, 2,2,2-trichloroethanol, toluene, chlorobenzene and 1,3-dichlorobenzene were added to water in the required quantities and shaken for 24 h. Solutions of 1,2,3-trichlorobenzene and 1,2,3,4-tetrachlorobenzene were obtained by the generator column method (cf. Billington et al., 1988). The concentrations of all solutions were verified by GC analysis. Test concentrations were all below the aqueous solubility limit of the substances (Table 1).

Exposure Prior to exposure to the test compounds, the larvae were acclimatized to the test conditions for 24 h by placing ten larvae in a 500-ml test vessel filled with Lake Maarsseveen water and 3.0 g cellulose fibres as artificial substrate. Larvae that did not burrow within 15 minutes were removed. During the acclimatization and exposure period, the water temperature was held constant at 19 (_+ 0.5)°C and the light/ dark regime was identical to that used during cultivation. Groups of ten larvae were exposed to five toxicant concentrations and to a control exposure in a semi-static manner for a period of 96 h. The ratio between successive concentrations of the compounds was 3.2 or less. The test solutions were renewed every 24 h. The edges of the glass covers of the test vessels were treated with silicone grease to reduce evaporation of the test compounds. Oxygen levels in the test vessels were checked during the experiment. The actual concentrations of the test compounds were checked by GC analyses before and after renewal of the test solutions. Toluene, 4-methyl-2-pentanone and the chlorobenzenes were extracted with 1 ml CS2. Analyses were performed in duplicate using a Perkin Elmer Z-3B/8500 gas chromatograph, equipped with a CPsil 5-CB column (chromosorb 102 for methanol) and a FID detector. Injector and detector temperatures were 225°C and 250°C, respectively. The injection volume was 1 gl.

Effects monitoring After 96 h of exposure of the larvae to each test concentration, 1-h registrations of the behaviour of six larvae were started. The equipment allowed a simultaneous registration of the behaviour of two larvae, resulting in a minimum exposure time of 96 h and a maximum exposure time of 98 h. Activity patterns of individual organisms

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CAS-nr.

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Table 1 Test compounds

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were quantified by means of the impedance conversion technique described by Heinis and Swain (1986). Measurements were conducted in the test vessel. Micromanipulators were used to place two 200/~m diameter stainless steel needle electrodes closely adjacent to opposite sides of a larval tube. The larva, between electrodes with alternating current, together with the surrounding water then functions as the dielectricum of a capacitor. Any movement of the larva leads to a change in the dielectricum and consequently in a change of the impedance of the capacitor. These changes were transformed by an impedance convertor into signals that were permanently registered with a Graphtex Mark VII high-speed recorder and were stored on floppy disk at a rate of 16 samples per second. Three different types of behaviour of the filter-feeding larvae of Chironomus riparius were discerned (Fig. 1): (a) ventilation - the larva makes dorsoventral 'pumping' movements with the body, causing a water flow through the tube; registered as a regular, sinoidal signal with a frequency of 1-2 Hz; (b) other active behaviour - all other movements of the larva, mainly due to feeding and tube maintenance activities; registered as an irregular signal; and (c) inactive behaviour - the larva makes hardly any movement; registered as a signal with a very low amplitude. These registrations were analysed semi-automatically on a microcomputer (EXORset, equipped with a Motorola MC6809 microprocessor) and the percentage of the total time (i.e. 60 minutes) that was spent on each type of behaviour was calculated. Subsequently, the behavioural responses of six larvae for each test compound and exposure concentration were compared to those of the control group. For any type of behavioural effect the lowest effective concentration was determined with Student's t-test (p < 0.05; Sokal and Rohlf, 1981). This was used to establish NOEC-values for the chemicals involved.

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Fig. 1. Behavioural types of fourth-instar Chironomus riparius larvae: (a) ventilation; (lo) other activity; (c) inactivity.

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3. Results 3.1. Exposure concentrations

T h e m e a s u r e d c o n c e n t r a t i o n s o f the c o m p o u n d s at the highest a n d lowest test c o n c e n t r a t i o n s at the s t a r t o f the e x p e r i m e n t a n d b e f o r e r e n e w a l o f the test s o l u t i o n s a r e given in Table 2. F o r t o l u e n e a n d m o n o c h l o r o b e n z e n e , n o a d e q u a t e a n a l y s e s o f a c t u a l e x p o s u r e c o n c e n t r a t i o n s a t t = 0 a n d t = 24 h c o u l d be m a d e a n d t h e r e f o r e n o m i n a l e x p o s u r e c o n c e n t r a t i o n s are given. T h e analysis revealed t h a t 2-methyl-1p r o p a n o l a n d 2 , 2 , 2 - t r i c h l o r o e t h a n o l h a d a highest e x p o s u r e c o n c e n t r a t i o n t h a t rem a i n e d a l m o s t c o n s t a n t t h r o u g h o u t the test. O n the o t h e r h a n d , a s h a r p decrease o f the test c o n c e n t r a t i o n w a s o b s e r v e d f o r 1,2,3,4-tetrachlorobenzene: w i t h i n 24 h, 6 8 94% ( d e p e n d i n g on the initial c o n c e n t r a t i o n ) o f the c o m p o u n d h a d d i s a p p e a r e d . I n all o t h e r cases the test c o n c e n t r a t i o n s o f the substances s h o w e d a m o d e r a t e decrease d u r i n g 24 h, w i t h an a v e r a g e o f 35%. This decrease a p p e a r e d to be g r a d u a l ( d a t a n o t shown) a n d was a s s u m e d to be a c o n s e q u e n c e o f e v a p o r a t i o n o f the substances f r o m the test solutions. C o n s i d e r i n g the relatively low v o l a t i l i t y o f 1,2,3,4-tetrachlorobenzene (Table 1), the r e m a r k a b l y low c o n c e n t r a t i o n m e a s u r e d after 24 h c a n n o t be explained. I n general, however, the c o n c e n t r a t i o n s b e f o r e r e f r e s h m e n t o f the test s o l u t i o n s d e v i a t e d u p to a f a c t o r 2 f r o m the c o n c e n t r a t i o n s a t the s t a r t o f the test o r after r e f r e s h m e n t o f the test solutions. 3.2. Effects on behaviour

C o m p u t e r r e g i s t r a t i o n o f b e h a v i o u r a l p a t t e r n s e n a b l e d a s y s t e m a t i c analysis o f the Table 2 Exposure concentrations and effects on behaviour of Chironomus riparius Test compound

Methanol 2-Methyl-l-propanol 4-Methyl-2-pentanone 2,2,2-Trichloroethanol Toluene Monochlorobenzene 1,3-Dichlorobenzene 1,2,3-Trichlorobenzene 1,2,3,4-Tetrachlorobenzene

Highest concentration

Lowest concentration

t=0h (mmol/l)

t=24h (mmol/1)

t=0h (mmol/1)

t = 24h (mmol/l)

NOEC c (mmol/l)

1130 9.6 8.2 8.3 0.32a 0.10~ 0.0022 0.0022 0.0023

880 10.3 5.4 7.6 0.0014 0.0011 0.000014

87 0.61 0.44 0.26 0.010~ 0.0064a 0.00025 0.000099 0.000073

62 0.38 0.27 0.22 n.d. b 0.000044 0.000023

320 2.7 0.44 0.26 0.010 0.0064 0.00025 0.000099 0.000073

a NO accurate measurements could be made; nominal start concentrations are given. b Not determined. c NOEC values are based on measured exposure concentrations (except those of toluene and monochlorobenzene) and were determined with Student's t-test.

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response of the larvae to the toxicants and a quantification of the relative amount of time spent on the various types of activity. Within the groups of larvae that were exposed to Lake Maarsseveen water (control), similar behavioural responses were observed which can be characterised by the relative amount of time (mean + SEM) spent on the three types of behaviour: ventilation activity 22.1 + 3.0%, other active behaviour 55.8 + 3.3%, and inactivity 21.5 + 2.9%. The responses of the Ch. riparius groups to the test compounds were all more or less different. Moreover, no single dose-response relationships were found. For six out of the nine substances tested, exposure led to two subsequent, concentration-dependent responses. No such bi-phasic effect could be observed with exposure to methanol, toluene and 1,2,3-trichlorobenzene. For the six test compounds that induced a biphasic effect, the behavioural change that occurred during exposure to the lowest effective concentration appeared to depend on the nature of the tested compound and was followed by a another significant change in behaviour at a higher concentration (Fig. 2). With this respect basically two different types of bi-phasic effects could be observed. The first type was observed after exposure to 2-methyl-l-propanol, 4-methyl-2pentanone and 2,2,2-trichloroethanol (Fig. 2). The two concentration-dependent phases could generally be characterized by an increase in ventilation behaviour at low concentrations (not significant for 2-methyl-l-propanol), accompanied by a decrease of other active behaviour, inactivity or both, followed by an increase of inactivity at higher concentrations, accompanied by a decrease of active behaviour. An unexpected extreme of this effect was observed during exposure to the three highest test concentrations of 2,2,2-trichloroethanol, where none of the larvae survived. The second type of bi-phasic effect was observed after exposure of Ch. riparius larvae to monochlorobenzene (Fig. 2), 1,3-dichlorobenzene and 1,2,3,4-tetrachlorobenzene. Generally, at low concentrations an increase in the inactivity (not significant for 1,3-dichlorobenzene) along with a decrease in ventilation behaviour (not significant for 1,2,3,4-tetrachlorobenzene) could be observed. At higher exposure concentrations the percentage ventilation increased, and was accompanied by a decrease in inactivity (not observed for 1,2,3,4-tetrachlorobenzene). The effects of toluene and 1,2,3-trichlorobenzene at low exposure concentrations were similar to that of the first group, but no clear second effect was observed. Methanol also induced a significant increase in ventilation, but this effect was only significant at relatively high concentrations.

3.3. QSAR A graphical presentation of the NOECs of Table 2 plotted against the Kow is given in Fig. 3. By linear regression a QSAR, with a correlation coefficient (r) of 0.994 and a standard error of the y-estimate (s) of 0.27, was derived: log NOEC (mol/1) = -1.27 log Kow-l.62

(n = 9, r = 0.994, s = 0.27)

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P. TJ. van der Zandt et al./Aquatic Toxicology 28 (1994) 209-221

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The behaviour of the Chironomus riparius larvae could be described as three easily discernable activity types: (a) ventilation - 'pumping' movements of the larva, necessary for maintaining an optimal gas-exchange; (b) other active behaviour - all other movements of the larva, mainly due to feeding and tube maintenance activities; and (c) inactivity. Typical examples of registrations of these respective types of behaviour are shown in Fig. 1. The behaviour of the larvae in the cellulose substrate used in this study was comparable to behavioural responses observed in natural substrate. Because all test compounds belong to the group of non-polar narcotic chemicals (K6nemann, 1981; Hermens, 1989), behavioural responses to these chemicals were expected to be similar. The results demonstrated, however, that midge larvae may respond in a somewhat different way to these chemicals. Larvae exposed to six out of the nine tested compounds showed increased ventilation. For three of these compounds, 2-methyl-l-propanol, 4-methyl-2-pentanone and 2,2,2-trichloroethanol, a significant change of behaviour, resulting in an increase of inactivity, was observed at higher test concentrations (second effect). Methanol, toluene and 1,2,3-trichlorobenzene also gave enhanced ventilation. For methanol, however, this effect was observed at the highest tested concentrations, and further research is needed to discern whether a second behavioural effect is induced at even higher concentrations. For toluene and 1,2,3-trichlorobenzene, no clear (significant) second effect could be observed. The second effect of 2,2,2-trichloroethanol was quite radical, as all larvae died within a short concentration range. Using an experimental set-up similar to that of the current study, Heinis and Crommentuijn (1990) observed a bi-phasic effect of pentachlorophenol, parathion and cadmium on the behaviour of Ch. riparius larvae. Although these chemicals have quite different modes of action, they induced comparable effects that were characterized by a significant increase in ventilation (first effect), followed by an increase in

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inactivity (second effect) at higher concentrations. These effects are similar to those of 2-methyl-l-propanol, 4-methyl-2-pentanone and 2,2,2-trichloroethanol, tested in the current study. This indicates that increased ventilation (pumping) may be a fairly common stress parameter of chironomid larvae exposed to relatively low concentrations of chemical pollutants. This effect is often followed, in a dose-dependent manner, by an increase of inactivity, which, however, may not be significant in all cases. The current study also shows that mono-, 1,3-di- and 1,2,3,4-tetrachlorobenzene form a different category of chemicals with respect to the observed behavioural effects induced in Ch. riparius larvae, even though they are known to have a 'normal' narcotic mode of action. At low concentrations, they reduced the time spent on active behaviour, while at higher concentrations increased ventilation was observed. The first effect could be due to the narcotic character of the chemicals, but the second effect clearly contradicts such an explanation. The reason for the observed differences within the group of narcotic chemicals tested in the current study is unknown. The regression parameters of the QSAR derived in this study indicate that in this experimental set-up, the NOEC of non-polar organic compounds (based on aqueous concentrations in the test vessel) is well described by their Kow values. This does not provide information on the actual route(s) of exposure of the organisms, except that it is related to the aqueous concentration and the Kow. The QSAR derived in this study has a rather steep slope (regression coefficient -1.27), considering the fact that the QSARs for narcotic chemicals that have been derived for a large number of other aquatic species in general have a regression coefficient of approximately -1.0 or lower, although coefficients of -1.1 are also found occasionally (cf. Van Leeuwen et al., 1992). The difference in regression coefficients is also illustrated in Fig. 4. The factor that led to this relatively high regression coefficient is difficult to identify. The set of nine narcotic chemicals used in this study is considered to be sufficient, and the derived regression parameters indicate a good

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correlation between Kow and NOEC, with no particular outliers. Two possible explanations for the observed steepness of the QSAR slope are discussed in the following paragraphs. Exposure of larvae via substrate in the gut, thus increasing the total dose, may be one possible explanation. The cellulose substrate was observed in the guts of the larvae in all exposures. Adsorption of non-polar organic compounds to soil and sediment is primarily determined by the organic carbon content of the adsorbent (Muir et al., 1983; Ziegenfuss et al., 1986; Adams, 1987; Knezovich and Harrison, 1988). The organic carbon adsorption coefficient (Koc) of several types of organic substances can be linearly correlated to the Kow (Briggs, 1981; Karickhoff, 1981; Jury et al., 1983). Therefore, while only aqueous concentrations were measured, exposure and uptake via substrate in the gut may have contributed significantly to the effect of the compounds with a relatively high Kow. Another possible source of bias may be biotransformation of chlorobenzenes by chironomids. Several authors have shown that chironomids are able to metabolize different organic contaminants rapidly, but, depending on the bioavailability, may also have high uptake rates for the same compounds (Kawatski and Bittner, 1975; Leversee et al., 1982; Muir et al., 1982, 1983). Biotransformation of chlorobenzenes may yield metabolites that are more toxic than the parent compounds, such as chlorophenols. Further research, involving determination of internal effect concentrations, is needed to establish the significance of biotransformation in this context. Chironomus riparius has been reported to be rather tolerant to organic and heavy metal pollution (Pinder, 1986). The current study, however, indicates that the behaviour of midge larvae in a substrate-water system is disturbed when non-polar narcotic chemicals are present at relatively low levels. The same was shown earlier for other chemicals (Heinis and Crommentuijn, 1990). In a recent evaluation of 35 QSARs for 24 aquatic species and a variety of measures of toxicity, Van Leeuwen et al. (1992) showed that the 21 days reproduction test on Daphnia magna and the 28 days early life stage test on Brachydanio rerioIPimephales promelas were the most sensitive aquatic ecotoxicological parameters. From Fig. 4, where these QSARs are compared with the QSAR for behaviour of Ch. riparius larvae, it can be concluded that the sensitivities of these parameters are in the same order of magnitude. In conclusion, Ch. riparius larvae may display different behaviour patterns when exposed to several industrial pollutants with a narcotic mode of action. The QSAR shows that the derived NOECs correlate very well with octanol-water partition coefficients, and that behaviour of chironomids is amongst the most sensitive indicators of narcotic organic micropollutants in a substrate-water system. This, together with a standardised breeding protocol and the automatic registration of the behaviour and data processing, may provide a potentially suitable tool in aquatic biomonitoring.

Acknowledgements The authors would like to thank Dr. Jack de Bruijn, Dr. Joop Hermens, Prof.Dr. Kees van Leeuwen and Catherine Ponsford for their helpful comments.

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