Next Article in Journal
Floating Wetlands for Sustainable Drainage Wastewater Treatment
Previous Article in Journal
Energy and Environmental Assessment of a Hybrid Dish-Stirling Concentrating Solar Power Plant
Previous Article in Special Issue
What Is the Impact of Dexamethasone and Prednisolone Glucocorticoids on the Structure of Meiobenthic Nematode Communities?
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Antidepressants Amitriptyline and Paroxetine Induce Changes in the Structure and Functional Traits of Marine Nematodes

1
LR01ES14 Laboratory of Environment Biomonitoring, Coastal Ecology and Ecotoxicology Unit, Faculty of Sciences of Bizerte, University of Carthage, Zarzouna 7021, Tunisia
2
Zoology Department, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
3
Faculty of Biology, Alexandru Ioan Cuza University of Iasi, 700506 Iasi, Romania
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sustainability 2022, 14(10), 6100; https://doi.org/10.3390/su14106100
Submission received: 21 March 2022 / Revised: 28 April 2022 / Accepted: 6 May 2022 / Published: 17 May 2022
(This article belongs to the Special Issue Marine Pollution and Ecological Environment)

Abstract

:
Increasing concentrations of the antidepressants amitriptyline and paroxetine were determined recently in marine habitats. However, their impact on marine biota is understudied, despite multiple undesirable effects they have on the environment. An important behavioral aspect that is increasingly measured following exposure to contaminants is the migration of fauna from contaminated areas. Hence, our aim was to better understand the migration pattern of marine meiobenthic fauna, but with a main focus on nematodes, following the exposure to both antidepressants, alone or in mixture. The experiment was carried out in microcosms, which comprised an uncontaminated upper and a lower contaminated compartment, where amitriptyline was added, alone or mixed with paroxetine, at concentrations of 0.4 and 40 µg L−1. The overall abundance of meiobenthic groups decreased significantly following exposure to amitriptyline in both compartments, a pattern augmented by the mixture with paroxetine. The migration of nematodes towards the upper compartments of microcosms was triggered by the level of contamination with antidepressants. As such, the species Terschellingia longicaudata showed no significant change in abundance, suggesting tolerance to both antidepressants. On the other hand, the abundances of nematode taxa Cyatholaimus prinzi, Calomicrolaimus sp., Calomicrolaimus honestus, Neochromadora sp., Chromadorina sp. and Chromadorina minor decreased significantly following the exposure to both antidepressants, even at low concentrations. At the end of the experiment, the dominant migratory nematodes belonged to deposit-feeders and omnivores-carnivores trophic guilds, with tail shapes of e/f types and body-sizes longer than 2 mm. Such functional traits increase their mobility in sediments and the chance to move away from contaminated habitats. Moreover, the sex ratio was imbalanced in the favor of males in contaminated lower compartments with mixtures of the lowest and highest concentrations of amitriptyline and paroxetine, suggesting that these drugs also affect the hormone system. In conclusion, the exposure to the antidepressants amitriptyline and paroxetine triggered important changes within nematode communities, as changes in taxonomic composition were a result of migration and survival of tolerant taxa, but equally acting on the hormone system and leading to unbalanced sex-ratio among the residents.

1. Introduction

The antidepressants comprise pharmaceuticals [1,2] used in the treatment of anxiety, as well as in obsessive and seizure disorders in humans [3]. A wide range of antidepressants were determined in urban wastewater, surface and groundwater, as well as in aquatic organisms (references). Antidepressants are released into the aquatic habitats through human metabolism in trash, lavatories, wastewater from hospitals or pharmaceutical companies (reference). It is increasingly recognized that wastewaters are the main sources for spreading these antidepressants in freshwater habitats and carried further into marine ecosystems [4,5]. Following their disposal in marine habitats, the antidepressants act on local fauna and habitats, even at low concentrations, ranging from ng L−1 to μg L−1 [6]. It was reported that the antidepressants could alter the regulation of neurotransmitters, to disrupt homeostasis, induce anomalies in the embryonic development, sterility and hermaphroditism in animals, as well as to decrease bacterial biodiversity in aquatic habitats [6,7,8]. Furthermore, the deleterious effects of these antidepressants are equally reflected on marine fauna behavior [9], by disturbing their locomotion and feeding habits [10].
Three classes of widely prescribed antidepressants are recognized nowadays: (i) tricyclic antidepressants, (ii) selective inhibitors of serotonin reuptake and (iii) serotonin/norepinephrine reuptake inhibitors [4,5]. Among the tricyclic antidepressants, the amitriptyline was detected in domestic wastewaters following treatment in sewage treatment plants [11,12]. In France, for example, the amitriptyline was measured in concentrations ranging up to 768 ng g−1 in wastewaters [13]. The amitriptyline was identified, along with other selective inhibitors of serotonin reuptake antidepressants, such as the paroxetine, in sediments, fish, and seafood [14]. Salgado et al. [15] reported paroxetine concentrations of 39.73 µg L−1 in untreated wastewaters, leading to their further transport in marine coast habitats. The interactions between these antidepressants and non-target organisms are still poorly understood, requiring more in-depth studies, particularly in coastal habitats [9]. Few results on the toxicity of mixed selective inhibitors of serotonin reuptake antidepressants and tricyclic ones are available. One such study which focused on the water flea Daphnia magna adults [1,2,3,4,5] concluded that the effects of mixtures are much higher than when these antidepressants were tested separately, suggesting synergistic interactions. Similar findings were also observed on hydra embryos, following exposure for 14 days to these antidepressants [1,2,3,4,5].
Currently, the toxic impact of these types of emergent pollutants on marine meiobenthos is not well documented, particularly on sediment-dwelling invertebrates such as free-living nematodes, polychaetes, copepods, and amphipods (Figure 1). The nematodes comprise the dominant meiobenthic group and have a long history of being reliably used as ecological indicators, due their small size (1–5 mm), high abundance and diversity, as well as easy laboratory maintenance [16,17,18,19].
The (eco)toxicological effects of pollutants on nematodes are generally tested within closed experimental microcosms, which are usually filled with sediment and topped with aerated water, in containers such as bottles [20,21,22,23,24,25,26,27,28,29,30], jars [31], Erlenmeyer flasks [32], tubes [33], boxes [25,26,27,28,29,30,31,32,33,34] and cores [35]. Such containers are widely used due their low price and easy maintenance costs, but debatable in mimicking reliably the natural conditions. The classical microcosm devices do not allow the test animals to actually avoid the pollution source by moving away from it. Moreover, the migratory hebaviour of test animals in the presence of pollutants is an expected natural reaction, especially for mobile taxa such as the nematodes [36]. The amount of evidence supporting the migratory behaviour of meiobenthos following exposure to pollutants has mounted recently, due to the necessity of more realistic experimental devices where the natural behaviour, besides the standard toxicological end points, is also to be assessed [37,38]. Recently, the response of marine nematodes following exposure to the antidepressant paroxetine was tested in laboratory microcosms by Ishak et al. [19]. The results obtained showed significant changes in nematofauna taxonomic composition, as well as the dominance of species with certain functional traits (i.e., type of feeding groups, tail and amphid shapes, body size) that are best adapted following the exposure to this antidepressant. However, besides paroxetine, another antidepressant frequently measured in aquatic habitats is the amitriptyline (see above). We suspect that both antidepressants could act in synergy, with yet unknown effects on marine fauna. Hence, the current study aimed to investigate the effects of amitriptyline, single or mixed with paroxetine, on the locomotion reaction of marine nematodes collected from the bay of Bizerte (northeast of Tunisia). An open experimental enclosure was used to study the locomotion reaction of nematodes and to assess their tolerance to these two antidepressants.

2. Material and Methods

2.1. Sampling Site and Acclimatization

The top 5 cm sediment was sampled from the Bizerte lagoon (37°13′437″ N, 9°51′457″ E) at 50 cm water depth, on the 9 January 2021 (7 AM). This biotope of this ecosystem consists mainly of silt—clayey sediments, which is suitable to observe the natural migratory movements of nematodes over a vertical profile as opposed to sandy sediments [30]. The sand is more porous, promoting mostly the type of passive movement of nematodes within interstitial habitats [39,40,41,42]. Several hand cores (10 cm2) were used to sample the sediment. The biotic and abiotic characteristics of the habitat were previously described by Béjaoui-Omri [43] in detail.

2.2. Experiment Set-Up

A laboratory experiment, comprising specially designed microcosms, was used (Figure 2). Each microcosm comprised 10 cm diameter polyvinyl chloride tubes, closed at both ends [19]. The main tube was separated in two equally sized compartments. The lower compartment was filled with contaminated defaunated sediments by repeated (three times) freezing (−20 °C) and thawing (12 h/48 h) [20]. The chosen antidepressants concentrations, of 0.4 and 40 µg L−1, respectively, were based on the EC50/48 h of the cladoceran Daphnia magna [44]. The upper compartment was filled with uncontaminated natural sediments. Both compartments were isolated from each other with a thin layer of impermeable agar (Figure 2). The microcosms were kept in a controlled room, with fixed lighting (8.5 h light/15.5 h dark) and temperature (18 °C/12 °C) for three days for acclimatization, equivalent to conditions during the month before sampling (from 8 December 2020 to 8 January 2021), according to http://www.infoclimat.fr (accessed on 9 January 2021). The experiment lasted 15 days.

2.3. Sediment Contamination

The amitriptyline and paroxetine (Sigma Aldrich, St. Louis, MO, USA, 98%) were dissolved in seawater and filtered through 0.7 µm pore-size Glass Microfibre GF/F, Whatman, without using any solvent in order to prepare the stock solutions [45,46]. Each stock solution was used separately or mixed to contaminate the defaunated sediments, and poured until the lower compartments were fully filled.
A total of 15 microcosms (i.e., three replicates per treatment) were designated. One comprised the control, with uncontaminated upper and lower compartments, noted UC and LC, respectively. Two other sets, comprising uncontaminated upper compartments, noted UA1 and UA2 and contaminated lower compartments, contaminated with the lowest and highest amitriptyline concentrations, noted LA1 and LA2, were used. Finally, two other sets, comprising uncontaminated upper compartments, noted UM1 and UM2 and contaminated lower compartments with mixture, of the lowest and highest concentrations of amitriptyline and paroxetine, noted LM1 and LM2, were also employed.

2.4. Meiofauna Study

Following the end of the experiment (i.e., 15 days), the migratory patterns of nematodes found in the lower compartments, which were azoic at the beginning, were observed. The duration of the experiment, which was 15 days, was chosen as such as to be longer than the exploratory phase, characterized by the migration of nematodes back and forth over a vertical profile in sediments, which was estimated to be 9 days by previous investigations [16]. The nematodes were extracted using the levigation-sieving technique [47] with the aid of two sieves with 1 mm and 40 µm mesh size, respectively, and stained with rose Bengal solution (0.2 g·L−1) [48]. From each compartment, 100 individuals were randomly picked under a stereomicroscope and mounted on microscopic slides [49] for taxonomic identification at species level, using the keys of Platt and Warwick [50] for genus and the Nemys database at species level [51]. In addition, the collected nematodes were subdivided according to their gender and maturity status into juveniles (hereafter J), non-gravid females (hereafter f), gravid females (hereafter fg), and males (hereafter m). The non-gravid and gravid females were merged within a single group (hereafter F) to calculate the J/F and m/F ratios. Two supplementary indices were also calculated: the relative pharyngeal lumen volume (hereafter RVPL) and the d-index according to Boufahja et al. [26].
Five additional functional and morphological traits were calculated: the amphid shape, tail shape, trophic groups, adult length, and type of life history for each genus of nematode. The amphid classification, based on the amphideal fovea shapes, was further subdivided into four groups: circular (cr), spiral (sp), pocket (pk), and indistinct (id) [52]. The shape of tails was also subdivided into four components: conical (co), clavate/conical cylindrical (cla), short/round (s/r), and elongated/filiform (e/f) [53]. The feeding types, based on oral cavity shape, were also subdivided into four groups: epiphytic (2A), deposit-selective (1A), non-selective (1B), and omnivorous/predators (2B) [54]. The body-size of adults was also ranked into three further groups: 1–2 mm, 2–4 mm, and ˃4 mm [55]. The life history based on the colonization success level (hereafter c-p) was ranked from a value of 1 (i.e., successful colonizers, with shortened life cycle, high reproductive rate and tolerant to various types of stress) to 5 (resilient, long-life cycle, reduced brood and sensitive to pollution), analogous to K/r strategists [56,57].

2.5. Statistical Analyses

Community-based indices, such as abundance, species richness (hereafter S), Margalef’s species richness (hereafter d), Shannon-Weaner diversity index (hereafter H’), and evenness Pielou (hereafter J’) were calculated in PRIMER 5.0 [58,59]. Normality tests (i.e., Kolmogorov–Smirnov) and the homogeneity of variance (i.e., Bartlett tests), as well as log10(x + 1) transformations, were applied to raw data [60] in STATISTICA (v5.1). One-way ANOVA and subsequent Tukey’s HSD tests were used to check for overall and pairwise differences among treatments. Non-metric Multidimensional Scaling (hereafter nMDS) ordination was used, based on square root transformed species and relative functional traits abundances, based on Bray-Curtis similarity measures. The contribution of species and functional traits to the overall dissimilarity among treatments and compartments was done with SIMPER analysis (SiMilarity PERcentage analysis), see Clarke [58].

3. Results

3.1. Taxonomic Composition

At the end of the experiment, the nematofauna comprised 11 families, 17 genera, and 22 species. The most diverse families were Oncholaimidae and Xyalidae (Table 1).
Following the experiment completion, the most abundant species in UC compartment was Terschellingia longicaudata (19.6 ± 1.7%) and Oncholaimus campylocercoides (10.5 ± 2.4%). The remaining genera each comprised less than 10%.
In UC compartment, the genus Chromadorina sp. had the lowest abundance, 1.02 ± 0.02%. The other treatments registered an overall decrease in diversity and taxonomic composition compared to control. The species O. campylocercoides, T. longicaudata were detected in all compartments in high abundances. The species Cyatholaimus prinzi, Calomicrolaimus sp., C. honestus, Neochromadora sp., Chromadorina sp., and C. minor disappeared from most contaminated compartments following the experiment completion.

3.2. Univarites Indices

Besides the nematodes, other taxonomic meiobenthic groups were also considered in the current experiment. As such, in UC, the nematodes were the dominant group (1343 ± 109 ind.), followed by copepods (73 ± 4.58 ind.), polychaetes (13.66 ± 1.52 ind.) and amphipods (10.33 ± 0.57 ind.). The treatments recorded significant decreases in the abundance of nematodes in both upper and lower compartments, compared to control (Figure 3). Likewise, the abundance of copepods was significantly lower in both compartments in any type of treatment compared to control. The abundance of polychaetes was significantly lower in all upper compartments compared to UC, except for UA1, and in lower compartments only in LM2 compared to LC. The abundance of amphipods was significantly different in the upper compartments of UM1 and UM2 compared to UC, as well as in the lower compartments only in UM2 compared to LC.
The diversity (S) of the upper compartments showed significant decrease in most compartments, except for UA1 compared to UC (Table 1). The diversity of lower compartments also showed significant differences in all compartments compared to LC. The Margalef’s species richness showed a significant decrease in the upper sections of microcosms compared to UC (Figure 4) except for UA1, and differed in the lower compartments of all treatment combinations compared to LC. Pielou’s evenness which differed significantly between UC and LA2 and the Shannon-Wiener index showed a significant decrease in all upper compartments compared to UC, except for UA1 (Figure 4). The latter index in lower compartments differed significantly in all types of treatments compared to LC.

3.3. Multivariate Indices

The nMDS ordination (Figure 5) indicated that the taxonomic composition and abundance of nematodes differed among treatments and control (Stress = 0.11). The LA2 communities were situated the farthest from control, whereas the UA1 the closest. The dissimilarity values showed an increase in the average dissimilarity value between control and contaminated compartments. The lowest dissimilarity was observed between UC and UA1 (20.35%) and the highest between LC and LA2 (46.2%). SIMPER results reveal that the species which contributed most to the overall average dissimilarity were Paracomesoma dubium, O. campylocercoides, Oncholaimellus calvadocicus, Steineria sp. and T. longicaudata (Table 2).

3.4. Diversity of Functional Traits

The functional categories of the initial community and different compartments communities were composed as follows (Figure 6):
  • The UC community feeding groups were dominated by non-selective deposit feeders (1B) and omnivorous ones (2B), comprising 26.7 ± 0.7% and 27.4 ± 1.35% of the nematofauna, respectively. The experiment showed a significant increase in groups 1A in all compartments, except for UA1. The group 2A in LA2 and the group 1B in UA1, LA2, UM1 and UM2 decreased significantly compared to control. The nMDS results indicate that LA2 treatment was the furthest from LC, followed by LM2 and LM1, whereas UA1 and UA2 treatments were the closest to UC.
  • The amphid shapes of the control community (UC) were dominated by circular (cr) and pocket-shaped (pk) amphides, representing 46.4 ± 2.5% and 30.5 ± 2.7% of the nematofauna. A significant decrease was observed in the cr amphid shape in all compartments, except for UA1. In addition, the id amphid shape significantly decreased in LA1, LA2, LM1 and LM2 compared to control. The pk amphid shape percentage decreased in all compartments compared to control. The nMDS results indicate that LA2 was the furthest from LC, whereas UA1 and UA2 treatments were the closest to UC.
  • Tail shapes were dominated by elongated/filiform (e/f) and clavate (cla) tails, representing 36.6 ± 0.5% and 48.8 ± 1.9% of the control nematofauna (UC), respectively. The contamination induced a significant increase in the shape of the e/f tails in LA2 and LM2. The shape of the cla tail showed significant differences between UM2 vs. LM2 and the e/f shape between UA2 vs. LA2 and UM2 vs. LM2. The nMDS indicated that the LM2 community was the furthest from LC, whereas all types of treatments were close to UC.
  • The control nematofauna (UC) life history was dominated by cp3 and cp2 types, representing 45.1 ± 2.7%, and 43.3 ± 1.3. A significant decrease was observed in cp3 in the LA2 and LM2 compartments. Conversely, the results show a significant decrease in cp3 in the uncontaminated compartments UA2, UM1 and UM2. The cp2 showed significant differences between UC and LC; UA1 and LA1 and UA2 and LA2, the cp3 between UA2 and LA2 as well as UM1 and LM1, and UM2 and LM2, and the cp4 between LC and LA2. The nMDS ordination showed that LA2 and LM2 comprised a clear different cluster compared with UC, whereas UA1 treatment was the closest.
  • The body-length intervals were dominated by 1–2 mm and >4 mm size-classes, comprising 61.1 ± 2.4% and 23.8 ± 0.8% of the control nematofauna (UC), respectively. The contamination induced a significant increase in the body-size class 1–2 mm in all compartments compared to control and a significant decrease in the 2–4 mm size-class between UC vs. UM2 and LC vs. LM2, as well as of the >4 mm size-class in all compartments compared to control, except for LM1 and LM2. The body-size interval 1–2 mm significantly differed between the control (UC and LC) and all other analyzed compartments, as well as between UA2 vs. LA2 and UM1 vs. LM1. The 2–4 mm size-class showed significant differences between UC and UM2 and between LC and LM2 and the >4 mm class between UC and LC. The results of the nMDS indicated that LA2 and LM2 were the furthest from LC, whereas the UA1 community the closest to UC.
The functional traits dissimilarities were less than 30%, excepting the trophic group in LA2 (Table 2). SIMPER results show significant decreases in feeding group 2A and cp3 life history percentages, as well as in feeding group 2B and size-class 1–2 mm in most treatments compared to control. Second-stage nMDS ordination (Figure 7) indicated that the nematodes feedback to contaminants was mainly driven by their tail shape (84.7%), amphid shape (84.4%) and adult body-size (83.1%), followed by life history (71.4%).

3.5. Sex Ratio and Maturity Status

The UC nematodes community comprised 16.7 ± 4% males 65.9 ± 1.1% non-gravid females, 6.6 ± 0.5% gravid females and 7.5 ± 1.4% juveniles (Table 3). There were registered significant increases in the percentage of males in LA2, LM1 and LM2 and significant decreases in non-gravid females percentages in all compartments compared to upper and lower control. Significant differences in males’ percentages were also recorded between UA2 and LA2, UM1 and LM1, and UM2 and LM2, and for non-gravid females between UA1 and LA1. The percentage of juveniles increased significantly in UA2 compared to control, but decreased between UA2 and LA2. On the other hand, the ratio j/gf increased significantly at UM2 compared to UC (Table 4).

3.6. Taxon-Functional Traits

In the current study the nematodes O. campylocercoides and T. longicaudata were chosen for further demographic and morphometric indices investigations (Figure 8). Overall, the RVPL values increased significantly in compartments LA1, UA2, LM1, and LM2 for T. longicaudata and in all compartments, except UM1, for O. campylocercoides compared to control. The Boufahja’s index increased significantly in all compartments, except for T. longicaudata in UM1 and for O. campylocercoides in UA1 and UA2, respectively, compared to control.

4. Discussion

Tricyclic antidepressants are commonly used as sedatives, anxiolytics, antidepressants and antischizophrenics [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61]. The high demand for these antidepressants from pacients increased significantly over the past decade, which could be easily linked to their increasing concentrations in the aquatic habitats [62,63,64]. The chosen antidepressants for the current experiments, namely the amitriptyline and paroxetine, were selected because their presence in terrestrial and aquatic ecosystems alike has been detected at increasing concentrations recently [65,66]. Despite previous efforts which had a main focus on assessing the toxicity of these antidepressants on the biological processes and the behaviour of non-targeted animals [67,68,69,70,71] the number of studies on benthic invertebrates, including nematodes, is limited [16]. Therefore, the scope of the curent experiment was to assess the effect of both antidepressants on the migratory behaviour of coast-dwelling marine nemtodes.

4.1. What Is the Effect of Contamination with Amitriptyline on Nematodes?

According to experimental results, the exposure to amitriptyline led to a significant decrease in the abundance of the benthic community in both compartments compared to control microcosms (Figure 3).
The meiobenthic communities dwelling in the upper compartments UA1 and UA2 were significantly more abundant and diverse compared to the contaminated lower compartments LA1 and LA2 (Figure 4). Previous investigations demonstrated the capacity of nematodes to avoid pollution and their subsequent reactions [36,72,73]. Among the generic taxonomic groups evaluated in the current experiment, the diversity of marine free-living nematodes also decreased compared to controls. The dominant species from control microcosms was T. longicaudata, which is characterized by small body-size (i.e., 1–2 mm) and is an epistrate feeder (guild 2A). However, larger (>4 mm) and omnivore-carnivores (guild 2B) species such as O. campylocercoides was also widespread in microcosms at the end of the experiment.
Comparing the results obtained from the current study with those of Ishak et al., [19], the differences spotted by the SIMPER analysis are not straightforward. In this work, the SIMPER analysis indicated a clearer effect of amitriptyline on the community of nematodes. The variable responses of the average dissimilarity emphasize a higher contribution of functional traits between compartments compared to Ishak et al., [19] and showed that the distribution of species was mainly driven by the contamination with amitriptyline.
The migratory behavior of certain nematodes was also influenced by contamination with amitriptyline. The vertical distribution pattern of T. longicaudata was particularly affected following the exposure to this antidepressant by increasing its abundance in the lower compared with the upper compartments. This nematode has a rounded amphid (cr type), known to increase the detection and hence the avoidance rate of pollutants compared to other nematodes that posess different amphid shapes [30]. The slender body of this species, associated with a filiform tail (e/f type), facilitated its vertical migration in a previous experiment, despite contamination with pollutants [39]. The results of the current experiment partially confirm the potential migration response of nematodes from polluted areas [74]. Moreover, the nématode O. campylocercoides was able to tolerate high amitriptyline concentrations, but its abundance was higher in uncontaminated compartments. On the other hand, species such as Cyatholaimus prinzi, Calomicrolaimus sp., C. honestus, Neochromadora sp., Chromadorina sp., and C. minor showed high sensitivity to low concentrations of amitriptyline, reflected in their elimination from most treatments (Table 1). Most of these highly sensitive species belong to indistinct (Id), spiral (sp) amphids’ shape, which indicate lower efficiency of these types of amphid to detect the amitriptyline [73], leading to the conclusion that they could be considered negative bioindicators of contamination with amitriptyline.
The functional traits that contributed most to the dissimilarity between UA1 vs. LA1 and UA2 vs. LA2 were the increase in percentages of 1A feeding groups, e/f tail shapes and 2–4 mm size-class (Table 2). It can be concluded that these functional traits greatly favored the vertical migration. Previous studies reported that undulation, body wave lengths and frequencies [75], body-size and shape [20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76], the presence of caudal [77], as well as feeding strategies [78,79] favored the migration of nematodes within marine sediments, resulting in different distribution patterns over a vertical profile.
The nematodes T. longicaudata and O. campylocercoides, with higher RVPL values, remained in the contaminated and to a lesser extent in the uncontaminated compartments. Such individuals possess larger pharyngeal light and higher pumping potential, allowing them to successfully cope with the low availability of food within spiked sediments with amitriptyline or mixtures of antidepressants. The efficacy of RVPL in biomonitoring programs was validated by Boufahja et al. [26] from field and laboratory experiments. However, the usage of this index was paused until 2011, because of the inherent difficulties and time-consuming measurements of the pharyngeal light dimensions, given their small size and diversity in shapes that is approximated afterwards to a known geometric figure that allows the calculation of the volume. The data obtained from the current work are in accordance with those observed after exposure of the species Bathylaimus capacosus, Daptonema normandicum, Desmodora longiseta, Oncholaimus campilocercoides, Leptonemella aphanothecae, and Oncholaimellus mediterraneus to metals (i.e., copper and chromium) and diesel [26].
The sex ratios highlighted significant increase in the percentage of males in LA2 and subsequent decrease in females in LA1 and LA2 (Table 3). These results could suggest a hormonal effect potentially induced by amitriptyline on females. Moreover, the abundance of juveniles was significantly higher in UA2 than in LA2, leading to the speculative conclusion that the amitriptyline may have had an impact on juveniles, by increasing their mortality. This difference in the abundance of juveniles led to a significant increase in the J/gf ratio in UA2 and decrease in LA2. A previous study showed that the toxic effects of certain glucocorticoids, including paroxetine, were also reflected in changes in the sex ratios of Ceriodaphnia dubia [7].

4.2. How Does the Mixture of Amitriptyline and Paroxetine Affect Nematodes?

Grosse et al. [80] showed that pharmaceutical substances can be mixed with several types of drugs, with similar or different modus operandi in water. These mixtures can cause synergistic or, less likely, antagonist effects on aquatic biota [81,82]. More recently, Benchouala [45] assessed the toxic effect of paroxetine and a tricyclic antidepressant on Hydra attenuate biological cycle.
The paroxetine, a selective serotonin inhibitor and one of the most prescribed antidepressants in the world, is usually found together with amitriptyline in marine habitats [63]. The abundance of all meiobenthic generic groups decreased significantly in the mixture exposure compared to the control and also lower compared to just amitriptyline exposure, suggesting potential synergistic interactions between both pharmaceuticals. The uncontaminated upper compartments UM1 and UM2 comprised a nematofauna that was more abundant and with higher values for species richness compared to the lower contaminated compartments, LM1 and LM2. The contamination with the mixture confirmed the tolerance of T. longicaudata to amitriptyline and added on the list of negative bioindicators the genus Steineria sp. The SIMPER analysis showed a high increase in Steineria sp. abundance in mixtures compared to the microcosms’ contamination with amitriptyline alone. Besides, the high sensitivity of Chromadorina sp., and C. prinzi was also confirmed. Overall, the functional traits SIMPER analysis highlighted an overall response of nematofauna for mixtures as with amitriptyline alone, namely the dominance of adults with body-sizes between 1 and 2 mm, belonging to trophic groups 2A, with amphid cr, life history cp3, and tail shape e/f (Table 1). The sex ratios highlighted a significant increase in the percentage of males in LM1 and LM2, and subsequently, the decrease in that of females (Table 3). This similar output as registered for amitriptyline contamination alone supports that it could as well be neutral combination with paroxetine or less probably a slight synergic effect of both antidepressants.

5. Conclusions

The use of free-living marine nematodes as laboratory model organisms and ecological indicators for pollution has a long tradition. Until recently, ecotoxicological studies were based on rather close microcosms in the attempt to mimic natural conditions. However, the use of open microcosms design should be also considered because it allows the free movement of nematodes between compartments, facilitating their assessment as tolerant or sensitive species. The current study explored the multiple effects of two antidepressants and their interactions with meiobenthic communities, but with a main focus on marine nematodes.
The results of the current experimental reveal that the abundance of meiobenthic generic groups decreased significantly after exposure to amitriptyline alone, in both compartments, the pattern augmented by the addition of paroxetine. The migratory behavior of free nematodes was clearly influenced by contamination, mostly reflected in the behavior of the species T. longicaudata, which could be considered tolerant to contamination with both antidepressants. The nematodes Cyatholaimus prinzi, Calomicrolaimus sp., C. honestus, Neochromadora sp., Chromadorina sp. and C. minor could be considered susceptible to contamination, even at low concentrations. The contribution of functional traits to mean dissimilarity was mainly driven by the feeding groups 1A and 2B, e/f tail shape, and longer than 2 mm size-class adults. The sex ratios highlighted significant increases in the percentage of males, and subsequently, the decrease in females. Overall, the potential synergistic effect between the two considered antidepressants was visible for the overall decrease in traits of the meiobenthic communities.

Author Contributions

S.I. and M.A.: Formal analysis, Validation, Writing—original draft, Writing—review & editing. A.N.: Data curation, Investigation. A.H.H.: Funding acquisition, Writing—review & editing. H.B. and S.A.: Data curation, Investigation. G.P.: Writing—review & editing. F.B.: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Writing—review & editing. All authors have read and agreed to the published version of the manuscript.

Funding

The authors extend their appreciation to the Researchers Supporting Project number (RSP-2021/17), King Saud University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not be shared due to restrictions eg privacy and regulation.

Acknowledgments

The authors extend their appreciation to the Researchers Supporting Project number (RSP-2021/17), King Saud University, Riyadh, Saudi Arabia.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Schultz, M.M.; Furlong, E.T. Trace analysis of antidepressant pharmaceuticals and their select degradates in aquatic matrixes by LC/ESI/MS/MS. Anal. Chem. 2008, 80, 1756–1762. [Google Scholar] [CrossRef] [PubMed]
  2. Halling-Sørensen, B.; Nors Nielsen, S.; Lanzky, P.F.; Ingerslev, F.; Holten Lützhøft, H.C.; Jørgensen, S.E. Occurrence, fate and effects of pharmaceutical substances in the environment. A review. Chemosphere 1998, 36, 357–393. [Google Scholar] [CrossRef]
  3. Mills, D.S. Medical paradigms for the study of problem behavior: A critical review. Appl. Anim. Behav. Sci. 2003, 81, 265–277. [Google Scholar] [CrossRef]
  4. Hignite, C.; Azarnoff, D.L. Drugs and drug metabolites as environmental contaminants: Chlorophenoxyisobutyrate and salicylic acid in sewage water effluent. Life Sci. 1977, 20, 337–341. [Google Scholar] [CrossRef]
  5. Brooks, N.; Adger, W.N.; Kelly, P.M. The determinants of vulnerability and adaptive capacity at the national level and the implications for adaptation. Glob. Environ. Chang. 2005, 15, 151–163. [Google Scholar] [CrossRef]
  6. Giebułtowicz, J.; Nałęcz-Jawecki, G. Occurrence of antidepressant residues in the sewage-impacted Vistula and Utrata rivers and in tap water in Warsaw (Poland). Ecotoxicol. Environ. Saf. 2014, 104, 103–109. [Google Scholar] [CrossRef]
  7. Henry, T.B.; Kwon, J.W.; Armbrust, K.L.; Black, M.C. Acute and chronic toxicity of five selective serotonin reuptake inhibitors in Ceriodaphnia dubia. Environ. Toxicol. Chem. 2004, 23, 2229–2233. [Google Scholar] [CrossRef]
  8. Fong, P.P.; Molnar, N. Norfluoxetine induces spawning and parturition in estuarine and freshwater bivalves. Bull. Environ. Contam. Toxicol. 2008, 81, 535–538. [Google Scholar] [CrossRef]
  9. Schultz, M.M.; Bartell, S.E.; Schoenfuss, H.L. Effects of Triclosan and Triclocarban, Two Ubiquitous Environmental Contaminants, on Anatomy, Physiology, and Behavior of the Fathead Minnow (Pimephales promelas). Arch. Environ. Contam. Toxicol. 2012, 63, 114–124. [Google Scholar] [CrossRef]
  10. Nyman, A.M.; Hintermeister, A.; Schirmer, K.; Ashaueral, R. The Insecticide Imidacloprid Causes Mortality of the Freshwater Amphipod Gammarus pulex by Interfering with Feeding Behavior. PLoS ONE 2013, 8, e62472. [Google Scholar] [CrossRef] [Green Version]
  11. Joss, A.; Keller, E.; Alder, A.C. Removal of pharmaceuticals and fragrances in biological wastewater treatment. Water Res. 2005, 39, 3139–3152. [Google Scholar] [CrossRef] [PubMed]
  12. Zwiener, C.; Sweeger, S.; Glauner, T. Metabolites from the biodegradation of pharmaceutical residues of ibuprofen in biofilm reactor and batch experiment. Anal. Bioanal. Chem. 2002, 372, 569–575. [Google Scholar] [CrossRef] [PubMed]
  13. Lajeunesse, S.A.; Smyth, B.K.; Barclay, B.S.; Sauvé, C.C.; Gagnon, A. Distribution of antidepressant residues in wastewater and biosolids following different treatment processes by municipal wastewater treatment plants in Canada. Water Res. 2012, 46, 5600–5612. [Google Scholar] [CrossRef] [PubMed]
  14. Schultz, M.M.; Furlong, E.T.; Kolpin, D.W.; Werner, S.L.; Schoenfuss, H.L.; Barber, L.B.; Blazer, V.S.; Norris, D.O.; Vajda, A.M. Antidepressant Pharmaceuticals in Two U.S. Effluent-Impacted Streams: Occurrence and Fate in Water and Sediment, and Selective Uptake in Fish Neural Tissue. Environ. Sci. Technol. 2010, 44, 1918–1925. [Google Scholar] [CrossRef] [PubMed]
  15. Salgado, R.; Marques, R.; Noronha, J.P.; Mexia, J.T.; Carvalho, G.; Oehmen, A.; Reis, M.A.M. Assessing the diurnal variability of pharmaceutical and personal care products in a full-scale activated sludge plant. Environ. Pollut. 2011, 159, 2359–2367. [Google Scholar] [CrossRef]
  16. Boufahja, F.; Semprucci, F. Stress-induced selection of a single species from an entire meiobenthic nematode assemblage: Is it possible using iron enrichment and does pre-exposure affect the ease of the process? Environ. Sci. Pollut. Res. 2015, 22, 1979–1998. [Google Scholar] [CrossRef]
  17. Moreno, M.; Semprucci, F.; Vezzulli, L.; Balsamo, M.; Fabiano, M.; Albertelli, G. The use of nematodes in assessing ecological quality status in the Mediterranean coastal ecosystems. Ecol. Indic. 2011, 11, 328–336. [Google Scholar] [CrossRef]
  18. Semprucci, F.; Balsamo, M. Key role of free-living nematodes in the marine ecosystem. In Nematodes: Morphology, Functions and Management Strategies; Boeri, F., Jordan, A.C., Eds.; NOVA Science Publishers Inc.: Hauppauge, NY, USA, 2012; pp. 109–134. [Google Scholar]
  19. Ishak, S.; Allouche, M.; Harrath, A.H.; Alwasel, S.; Beyrem, H.; Pacioglu, O.; Badraoui, R.; Boufahja, F. Effects of the antidepressant paroxetine on migratory behaviour of meiobenthic nematodes: Computational and open experimental microcosm approach. Mar. Pollut. Bull. 2022, 177, 113558. [Google Scholar] [CrossRef]
  20. Austen, M.C.; McEvoy, A.J.; Warwick, R.M. The specificity of meiobenthiccommunity responses to different pollutants: Results from microcosm experiments. Mar. Pollut. Bull. 1994, 28, 557–563. [Google Scholar] [CrossRef]
  21. Hedfi, A.; Boufahja, F.; Ben Ali, M.; Aïssa, P.; Mahmoudi, E.; Beyrem, H. Do trace metals (chromium, copper and nickel) influence toxicity of diesel fuel for free-living marine nematodes? Environ. Sci. Pollut. Res. 2013, 20, 3760–3770. [Google Scholar] [CrossRef]
  22. Hedfi, A.; Mahmoudi, E.; Boufahja, F.; Beyrem, H.; Aїssa, P. Effects of Increasing Levels of Nickel Contamination on Structureof Offshore Nematode Communities in Experimental Microcosms. Bull. Environ. Contam. Toxicol. 2007, 79, 345–349. [Google Scholar] [CrossRef] [PubMed]
  23. Hedfi, A.; Mahmoudi, E.; Beyrem, H.; Boufahja, F.; Essid, N.; Aïssa, P. Réponse d’une communauté de nématodes libres marins à une contamination par le cuivre: Étude microcosmique. Bull. Soc. Zool. Fr. 2008, 133, 97–106. [Google Scholar]
  24. Boufahja, F.; Hedfi, A.; Amorri, J.; Aïssa, P.; Beyrem, H.; Mahmoudi, E. An Assessment of the Impact of Chromium-Amended Sediment on a Marine Nematode Assemblage Using Microcosm Bioassays. Biol. Trace Elem. Res. 2011, 142, 242–255. [Google Scholar] [CrossRef] [PubMed]
  25. Boufahja, F.; Sellami, B.; Dellali, M.; Aïssa, P.; Mahmoudi, E.; Beyrem, H. A microcosm experiment on the effects of permethrin on a free-living nematode assemblage. Nematology 2011, 13, 901–909. [Google Scholar] [CrossRef] [Green Version]
  26. Boufahja, F.; Hedfi, A.; Amorri, J.; Aïssa, P.; Mahmoudi, E.; Beyrem, H. Experimental validation of the “relative volume of the pharyngeal lumen (RVPL)” of free-living nematodes as a biomonitoring index using sediment-associated metals and/or Diesel Fuel in microcosms. Exp. Mar. Biol. Ecol. 2011, 399, 142–150. [Google Scholar] [CrossRef]
  27. Essid, N.; Boufahja, F.; Beyrem, H.; Aïssa, P.; Mahmoudi, E. Effects of 17-α-estradiol on a free-living marine nematode community: A microcosm experiment. Afr. J. Aquat. Sci. 2013, 38, 305–311. [Google Scholar] [CrossRef]
  28. Kang, T.; Kim, D.; Oh, J.H.; Yoo, S. Effect of oxytetracycline on the community structure of nematodes: Results from microcosm experiments. Plankton Benthos Res. 2019, 14, 105–113. [Google Scholar] [CrossRef] [Green Version]
  29. Nasri, A.; Hannachi, A.; Allouche, M.; Barhoumi, B.; Saidi, I.; Dallali, M.; Harrath, A.H.; Mansour, L.; Mahmoudi, E.; Beyrem, H. Chronic ecotoxicity of ciprofloxacin exposure on taxonomic diversity of a meiobenthic nematode community in microcosm experiments. J. King Saud Univ.-Sci. 2020, 32, 1470–1475. [Google Scholar] [CrossRef]
  30. Wakkaf, T.; Allouche, M.; Harrath, A.H.; Mansour, L.; Alwasel, S.; Mohamed, T.A.; Kapul, G.; Beyrem, H.; Sellami, B.; Boufahja, F. The individual and combined effects of cadmium, polyvinyl chloride (PVC) microplastics and their polyalkylamines modified forms on meiobenthic features in a microcosm. Environ. Pollut. 2020, 266, 115–263. [Google Scholar] [CrossRef]
  31. Ristau, K.; Steinfartz, S.; Traunspurger, W. First evidence of cryptic species diversity and significant population structure in a widespread freshwater nematode morphospecies (Tobrilus gracilis). Mol. Ecol. 2013, 22, 4562–4575. [Google Scholar] [CrossRef]
  32. Armenteros, M.; Pérez-García, A.J.; Ruiz-Abierno, A.; Díaz-Asencio, L.; Helguera, Y.; Vincx, M.; Decraemerde, W. Effects of organic enrichment on nematode assemblages in a microcosm experiment. Mar. Environ. Res. 2010, 70, 374–382. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Gingold, R.; Moens, T.; Rocha-Olivares, A. Assessing the Response of Nematode Communities to Climate Change-Driven Warming: A Microcosm Experiment. PLoS ONE 2013, 8, e66653. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Kang, T.; Oh, J.H.; Hong, J.S.; Kim, D. Response of Intertidal Meiofaunal Communities to Heavy Metal Contamination in Laboratory Microcosm Experiments. J. Coast. Res. 2018, 85, 361–365. [Google Scholar] [CrossRef]
  35. Ullberg, J.; Ólafsson, E. Free-living marine nematodes actively choose habitat when descending from the water column. Mar. Ecol. Prog. Ser. 2003, 260, 141–149. [Google Scholar] [CrossRef]
  36. Zhou, H. Effects of leaf litter addition on meiofaunal colonization of azoic sediments in a subtropical mangrove in Hong Kong. Exp. Mar. Biol. Ecol. 2001, 256, 99–121. [Google Scholar] [CrossRef]
  37. Ptatscheck, C.; Traunspurger, W. The ability to get everywhere: Dispersal modes of free-living, aquatic nematodes. Hydrobiologia 2020, 847, 3519–3547. [Google Scholar] [CrossRef]
  38. Pacioglu, O.; Duţu, F.; Pavel, A.B.; Duţu, L.T. The influence of hydrology and sediment grain-size on the spatial distribution of macroinvertebrate communities in two submerged dunes from the Danube Delta (Romania). Limnetica 2022, 41, 85–100. [Google Scholar] [CrossRef]
  39. Pacioglu, O.; Shaw, P.; Robertson, A. Patch scale response of hyporheic invertebrates to fine sediment removal in two chalk rivers. Fundam. Appl. Limnol.-Archiv. für Hydrobiol. 2012, 181, 283. [Google Scholar] [CrossRef]
  40. Pacioglu, O.; Moldovan, O.T. Response of invertebrates from the hyporheic zone of chalk rivers to eutrophication and land use. Environ. Sci. Pollut. Res. 2016, 23, 4729–4740. [Google Scholar] [CrossRef]
  41. Pacioglu, O.; Pârvulescu, L. The chalk hyporheic zone: A true ecotone? Hydrobiologia 2017, 790, 1–12. [Google Scholar] [CrossRef]
  42. Béjaoui-Omri, A.; Béjaoui, B.; Harzallah, A.; Aloui-Béjaoui, N.; El Bour, M.; Aleya, L. Dynamic energy budget model: A monitoring tool for growth and reproduction performance of Mytilus galloprovincialis in Bizerte Lagoon (Southwestern Mediterranean Sea). Environ. Sci. Pollut. Res. 2014, 21, 13081–13094. [Google Scholar] [CrossRef] [PubMed]
  43. Calleja, M.C.; Persoone, G.; Geladi, P. Human acute toxicity prediction of the first 50 MEIC chemicals by a banery of ecotoxicological tests and physicochernical properties. Food Chem. Toxicol. 1994, 32, 173–187. [Google Scholar] [CrossRef]
  44. Benchaouala, A. Ecotoxicity, Cytotoxicity and Androgenic Potential of Residues Pharmaceuticals on the Two Biological Models: Hydra Attenuata and MDA-kb2 Cells. Ecosystems; University of Lorraine: Metz, France, 2017; pp. 57–58. [Google Scholar]
  45. Yalkowsky, S.H.; Dannenfelser, R.M. The Aquasol Database of Aqueous Solubility; Ver 5; College of Pharmacy, University of Arizona: Tucson, AZ, USA, 1992. [Google Scholar]
  46. Troemel, E.R.; Chou, J.H.; Dwyer, N.D.; Colbert, H.A.; Bargmann, C.I. Divergent seven transmembrane receptors are candidate chemosensory receptors in Coenorhabditis elegans. Cell 1995, 83, 207–218. [Google Scholar] [CrossRef] [Green Version]
  47. Vitiello, P.; Dinet, A. Definition and sampling of meiobenthos. Rapp. Comm. Int. Mer. Medit. 1979, 25, 279–283. [Google Scholar]
  48. Elarbaoui, S.; Richard, M.; Boufahja, F.; Mahmoudi, E.; Thomas-Guyon, H. Effect of crude oil exposure and dispersant application on meiofauna: Anintertidal mesocosm experiment. Environ. Sci. Process. Impact. 2015, 17, 997–1004. [Google Scholar] [CrossRef] [PubMed]
  49. Seinhorst, J.W. A rapid method for the transfer of nematodes from fixative to an hydrous glycerin. Nematologica 1959, 4, 67–69. [Google Scholar] [CrossRef] [Green Version]
  50. Platt, H.M.; Warwick, R.M. Free-Living Marine Nematodes. Part II. British Chromadorids; Synopsis of the British fauna; Field Studies Council: Shrewsbury, UK, 1988; Volume 38. [Google Scholar]
  51. Bezerra, T.N.; Eisendle, U.; Hodda, M.; Holovachov, O.; Leduc, D.; Mokievsky, V.; Peña Santiago, R.; Sharma, J.; Smol, N.; Tchesunov, A.; et al. Nemys: World Database of Nematodes. 2021. Available online: http://nemys.ugent.be (accessed on 20 March 2022).
  52. Semprucci, F.; Balsamo, M.; Appolloni, L.; Sandulli, R. Assessment of ecological quality status along the Apulian coasts (eastern Mediterranean Sea) based on meiobenthic and nematode assemblages. Mar. Biodivers. 2018, 48, 105–115. [Google Scholar] [CrossRef]
  53. Thistle, D.; Lambshead, P.J.D.; Sherman, K.M. Nematode tail-shape groups respond to environmental differences in the deep-sea. Life Environ. 1995, 45, 107–115. [Google Scholar]
  54. Alves, A.S.; Veríssimo, H.; Costa, M.J.; Marques, J.C. Taxonomic resolution and Biological Traits Analysis (BTA) approaches in estuarine free-living nematodes. Estuar. Coast. Shelf Sci. 2014, 138, 69–78. [Google Scholar] [CrossRef] [Green Version]
  55. Schratzberger, M.; Warr, K.; Rogers, S.I. Functional diversity of nematodecommunities in the southwestern North Sea. Mar. Environ. Res. 2007, 63, 368–389. [Google Scholar] [CrossRef] [Green Version]
  56. Bongers, T. The Maturity Index, the evolution of nematode life history traits, adaptive radiation and cp-scaling. Plant Soil 1999, 212, 13–22. [Google Scholar] [CrossRef]
  57. Bradbury, I.R.; Laurel, B.; Snelgrove, P.V.R.; Bentzen, P.; Campana, S.E. Global patterns in marine dispersal estimates: The influence of geography, taxonomic category and life history. Proc. R. Soc. B Biol. Sci. 2008, 275, 1803–1809. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Clarke, K.R. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 1993, 18, 117–143. [Google Scholar] [CrossRef]
  59. Clarke, K.R.; Gorley, R.; Somerfield, P.; Warwick, R. Change in Marine Communities: An Approach to Statistical Analysis and Interpretation; PRIMER-E Ltd.: Plymouth, UK, 2014. [Google Scholar]
  60. Clarke, K.R.; Gorley, R.; Carman, K.R.; Fleeger, J.W.; Pomarico, S.M. Does historical exposure to hydrocarbon contamination alter the response of benthic communities to diesel contamination? Mar. Environ. Res. 2000, 49, 255–278. [Google Scholar]
  61. Pelissolo, A.; Boyer, P.; Lepine, J.P.; Bisserbe, J.C. Epidemiology of the consumption of anxiolytics and hypnotics in France and in the world. L’encephale 1996, 22, 187–196. [Google Scholar]
  62. Moore, M.; Yuen, H.M.; Dunn, N.; Mullee, M.A.; Maskell, J.; Kendrick, T. Explaining the rise in antidepressant prescribing: A descriptive study using the general practice research database. BMJ 2009, 339, b3999. [Google Scholar] [CrossRef] [Green Version]
  63. Noordam, R.; Aarts, N.; Verhamme, K.M.; Sturkenboom, M.C.M.; Stricker, B.H.; Visser, L.E. Prescription and indication trends of antidepressant drugs in the Netherlands between 1996 and 2012: A dynamic population-based study. Eur. J. Clin. Pharmacol. 2015, 71, 369–375. [Google Scholar] [CrossRef]
  64. National Centre for Health Statistics. 2014, Special Feature Onprescription Drugs. Available online: http://www.cdc.gov/nchs/hus.htm (accessed on 20 May 2020).
  65. Ma, L.D.; Li, J.; Li, J.J.; Liu, M.; Yan, D.Z.; Shi, W.Y.; Xu, G. Occurrence and source analysis of selected antidepressants and their metabolites in municipal wastewater and receiving surface water. Environ. Sci. Process. Impacts 2018, 7, 991–1082. [Google Scholar] [CrossRef]
  66. Muir, D.; Simmons, D.; Wang, X.; Peart, T.; Villella, M.; Miller, J.; Sherry, J. Bioaccumulation of pharmaceuticals and personal care product chemicals in fish exposed to wastewater effluent in an urban wetland. Sci. Rep. 2017, 7, 16999. [Google Scholar] [CrossRef]
  67. Konstantin, A.D.; Tatiana, O.K.; Sergey, L.K.; Darya, A.M.; Evgeniya, V.E.; Yuri, Y.M.; Allan, V.K. Acute effects of amitriptyline on adult zebrafish: Potential relevance to antidepressant drug screening and modeling human toxidromes. Neurotoxicol. Teratol. 2017, 62, 27–33. [Google Scholar]
  68. Sophie, L.G.; Matthew, J.W.; William, H.J.N.; Charles, R.T. The potential for adverse effects in fish exposed to antidepressants in the aquatic environment. Environ. Sci. Technol. 2021, 55, 16299–16312. [Google Scholar]
  69. Leire, M.; Martin, K.; Laura, D.M.; Haizea, Z.; Maitane, O.; Olatz, Z.; Urtzi, I.; Tobias, S.; Werner, B.; Ailette, P.; et al. Application of the Sea Urchin Embryo Test in Toxicity Evaluation and Effect-Directed Analysis of Wastewater Treatment Plant Effluents. Environ. Sci. Technol. 2020, 54, 8890–8899. [Google Scholar]
  70. Lilius, H.; Hästbacka, T.; Isomaa, B. Short Communication: A comparison of the toxicity of 30 reference chemicals to Daphnia Magna and Daphnia Pulex. Environ. Toxicol. Chem. 1995, 14, 2085–2088. [Google Scholar]
  71. Brodin, T.; Piovano, S.; Fick, J.; Klaminder, J.; Heynen, M.; Jonsson, M. Ecological effects of pharmaceuticals in aquatic systems—Impacts through behavioural alterations. Philos. Trans. R. Soc. B Biol. Sci. 2014, 369, 20130580. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  72. Allouche, M.; Ishak, S.; BenAli, M.; Hadfi, A.; Almalki, M.; Karachle, K.P.; Harrath, A.H.; Abu-zied, H.R.; Badraoui, R.; Boufahja, F. Molecular interactions of polyvinyl chloride microplastics and beta-blockers (Diltiazem and Bisoprolol) and their effects on marine meiofauna: Combined in vivo and modeling study. Hazard. Mater. 2022, 431, 128609. [Google Scholar] [CrossRef]
  73. Burr, A.H.; Burr, C. The amphid of the nematode Oncholaimus vesicarius: Ultrastructural evidence for a dual function as chemoreceptor and photoreceptor. J. Ultrastruct. Res. 1975, 51, 1–15. [Google Scholar] [CrossRef]
  74. Schratzberger, M.; Harrison, J.P.; Sapp, M.; Osborn, A.M. Rapid bacterial colonization of low-density polyethylene microplastics in coastal sediment microcosms. BMC Microbiol. 2014, 14, 232. [Google Scholar] [CrossRef] [Green Version]
  75. Gray, J.; Lissmann, H.W. The locomotion of nematodes. Exp. Biol. 1964, 41, 135–154. [Google Scholar] [CrossRef]
  76. Vanaverbeke, J.; Soetaert, K.; Vincx, M. Changes in morphometric characteristics of nematode communities during a spring phytoplankton bloom deposition. Mar. Ecol. Prog. Ser. 2004, 273, 139–146. [Google Scholar] [CrossRef] [Green Version]
  77. Gingold, R.; Ibarra-Obando, S.E.; Rocha-Olivares, A. Spatial aggregation patterns of free-living marine nematodes in contrasting sandy beach microhabitats. J. Mar. Biol. Assoc. UK 2011, 91, 615–622. [Google Scholar] [CrossRef]
  78. Saburova, M.A.; Polikarpov, I.G. Diatom activity within soft sediments: Behavioral and physiological processes. Mar. Ecol. Prog. Ser. 2003, 251, 115–126. [Google Scholar] [CrossRef]
  79. Mitbavkar, S.; Anil, A.C. Vertical migratory rhythms of benthic diatoms in a tropical intertidal sand flat: Influence of irradiance and tides. Mar. Biol. 2004, 145, 9–20. [Google Scholar] [CrossRef]
  80. Gros, M.; Petrović, M.; Barceló, D. Wastewater treatment plants as a pathway foraquatic contamination by pharmaceuticals in the Ebro river basin (Northeast Spain). Environ. Toxicol. Chem. 2007, 26, 1553–1562. [Google Scholar] [CrossRef]
  81. Cleuvers, M. Mixture toxicity of anti-inflammatory drugs diclofenac, ibuprofen, naproxen, and acetylsalicylic acid. Ecotoxicol. Environ. Saf. 2004, 59, 309–315. [Google Scholar] [CrossRef]
  82. Cleuvers, M. Aquatic ecotoxicity of pharmaceuticals including the assessment of combination effects. Toxicol. Lett. 2003, 142, 185–194. [Google Scholar] [CrossRef]
Figure 1. Photos showing the meiobenthic nematodes Paramonohystera pilosa (A,B) and Oncholaimus campylocercoides (C,D), the polychaetes (E,F), the copepods (G), and the amphipods (H).
Figure 1. Photos showing the meiobenthic nematodes Paramonohystera pilosa (A,B) and Oncholaimus campylocercoides (C,D), the polychaetes (E,F), the copepods (G), and the amphipods (H).
Sustainability 14 06100 g001
Figure 2. Experimental design (A) and organization (B) of microcosms with treatments codes: the upper compartments (U) were filled with untreated sediment, whereas the lower compartments (L) were filled with defaunated sediments contaminated with amitriptyline, alone or mixed with paroxetine. Control treatment (C); Amitriptyline (A: 0.4 and 40 µg L−1), mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2).
Figure 2. Experimental design (A) and organization (B) of microcosms with treatments codes: the upper compartments (U) were filled with untreated sediment, whereas the lower compartments (L) were filled with defaunated sediments contaminated with amitriptyline, alone or mixed with paroxetine. Control treatment (C); Amitriptyline (A: 0.4 and 40 µg L−1), mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2).
Sustainability 14 06100 g002
Figure 3. Abundances of meiobenthic taxa from uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2). * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001.
Figure 3. Abundances of meiobenthic taxa from uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2). * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001.
Sustainability 14 06100 g003
Figure 4. Distribution of univariate indices of nematofauna from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), H’ is the Shannon-Weaner index, d the Margalef’s species richness, J’ the Pielou’s evenness and S species richness. The stars indicate significant differences according to pairwise Tukey tests: p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).
Figure 4. Distribution of univariate indices of nematofauna from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), H’ is the Shannon-Weaner index, d the Margalef’s species richness, J’ the Pielou’s evenness and S species richness. The stars indicate significant differences according to pairwise Tukey tests: p < 0.01 (**), p < 0.001 (***), and p < 0.0001 (****).
Sustainability 14 06100 g004
Figure 5. nMDS plot based on √-transformed nematode abundances from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments from microcosms treated with amitriptyline and paroxetine. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2).
Figure 5. nMDS plot based on √-transformed nematode abundances from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments from microcosms treated with amitriptyline and paroxetine. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2).
Sustainability 14 06100 g005
Figure 6. nMDS plot based on √-transformed nematode functional groups from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments from microcosms treated with amitriptyline and paroxetine. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), 1A = Selective deposit feeders, 1B = non-selective deposit feeders, 2A = epigrowth feeders, 2B = omnivores-carnivores, s/r = short/round, e/f = elongated/filiform, co = conical, cla = clavate/conical-cylindrical, sp = spiral, pk = pocket-like, id = indistinct, cr = circular. Stars above bars indicate significant differences with corresponding controls after Chi-square test (√-transformed data): p < 0.05 (*), p < 0.01 (**), p < 0.01 (***) and p < 0.0001 (****).
Figure 6. nMDS plot based on √-transformed nematode functional groups from uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA1, LA2, LM1 and LM2) compartments from microcosms treated with amitriptyline and paroxetine. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), 1A = Selective deposit feeders, 1B = non-selective deposit feeders, 2A = epigrowth feeders, 2B = omnivores-carnivores, s/r = short/round, e/f = elongated/filiform, co = conical, cla = clavate/conical-cylindrical, sp = spiral, pk = pocket-like, id = indistinct, cr = circular. Stars above bars indicate significant differences with corresponding controls after Chi-square test (√-transformed data): p < 0.05 (*), p < 0.01 (**), p < 0.01 (***) and p < 0.0001 (****).
Sustainability 14 06100 g006
Figure 7. Second-stage nMDS ordination of the inter-matrix rank correlations. For species see Figure 4 and for functional traits Figure 5. The values comprise the mean similarity percentages between nMDS of species and functional traits.
Figure 7. Second-stage nMDS ordination of the inter-matrix rank correlations. For species see Figure 4 and for functional traits Figure 5. The values comprise the mean similarity percentages between nMDS of species and functional traits.
Sustainability 14 06100 g007
Figure 8. Mean distribution of morphometric (i.e., RVPL% and d) and population- (i.e., J/F and m/F) based indices of the nematodes Terschellingia longicaudata and Oncholaimus campylocercoides at uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments with paroxetine and amitriptyline. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), RVPL = Relative Volume of the Pharyngeal Light, J = Juveniles, F = non-gravid females + gravid females (F), m = Males, d = Boufahja’s d index (=Total body lenght/Intermediate Piece lenght). Different letters above bars represent significant differences (p < 0.05) values according to Chi-square test (√-transformed data in %) and Spjotvoll-Stoline test results.
Figure 8. Mean distribution of morphometric (i.e., RVPL% and d) and population- (i.e., J/F and m/F) based indices of the nematodes Terschellingia longicaudata and Oncholaimus campylocercoides at uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments with paroxetine and amitriptyline. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), RVPL = Relative Volume of the Pharyngeal Light, J = Juveniles, F = non-gravid females + gravid females (F), m = Males, d = Boufahja’s d index (=Total body lenght/Intermediate Piece lenght). Different letters above bars represent significant differences (p < 0.05) values according to Chi-square test (√-transformed data in %) and Spjotvoll-Stoline test results.
Sustainability 14 06100 g008
Table 1. Taxonomic list of nematode species and types of functional traits in uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA, LA2, LM1 and LM2) microcosms. Upper compartment (U); Lower compartment (L), Control treatment (C); amitriptyline (A: 0.4 and 40 µg L−1), mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2); Colonizers-Persisters scores (c-p); tail shape (Tl): conical (co), elongated/filiform (e/f), clavate (cla); amphid shape (Am): pocket-like (pk), indistinct (id), spiral (sp), circular (cr); feeding groups were classidied and ranked according to Wieser (1953) (FG) as folows: selective deposit-feeders (1A), non-selective deposit-feeders (1B), epistratum-feeders (2A), omnivores carnivores (2B); adult length (AL).
Table 1. Taxonomic list of nematode species and types of functional traits in uncontaminated (i.e., UC, LC, UA1, UA2, UM1 and UM2) and contaminated (i.e., LA, LA2, LM1 and LM2) microcosms. Upper compartment (U); Lower compartment (L), Control treatment (C); amitriptyline (A: 0.4 and 40 µg L−1), mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2); Colonizers-Persisters scores (c-p); tail shape (Tl): conical (co), elongated/filiform (e/f), clavate (cla); amphid shape (Am): pocket-like (pk), indistinct (id), spiral (sp), circular (cr); feeding groups were classidied and ranked according to Wieser (1953) (FG) as folows: selective deposit-feeders (1A), non-selective deposit-feeders (1B), epistratum-feeders (2A), omnivores carnivores (2B); adult length (AL).
Functional TraitsTreatments
Speciesc-pTIAmFGALUCLCUA1LA1UA2LA2UM1LM1UM2LM2
Terschellingia sp.2e/fpk1A2–4 mm2.37 ± 1.171.68 ± 0.561.67 ± 0.584.33 ± 0.581.67 ± 0.581 ± 0.581 ± 0.08 1.33 ± 0.58
Terschellingia longicaudata3e/fcr1A1–2 mm19.67 ± 1.7218.18 ± 0.7524 ± 122.67 ± 0.5831.33 ± 1.1550.33 ± 1.5327 ± 241.70 ± 5.5623.67 ± 0.5842.33 ± 2.52
Metalinhomoeus numidicus2e/fcr1B2–4 mm6.44 ± 0.616.74 ± 0.655.33 ± 0.5812.33 ± 0.585 ± 1.734.67 ± 0.585 ± 1.025 ± 0.704.67 ± 0.582.33 ± 0.58
Paracomesoma dubium2clasp2A1–2 mm7.44 ± 1.438.43 ± 0.7420.33 ± 1.5317.33 ± 0.5825.67 ± 1.1513 ± 118 ± 114.56 ± 1.1517.33 ± 0.5812.66 ± 1.53
Marylynnia puncticaudata3e/fsp2A2–4 mm1.36 ± 0.611.69 ± 0.600.67 ± 0.580.33 ± 0.58 5.33 ± 1.15
Daptonema trabeculosum2clacr1B1–2 mm2.37 ± 0.552.35 ± 0.563.67 ± 0.582 ± 0.24.33 ± 2.083.33 ± 1.153 ± 14.66 ± 0.853 ± 13.33 ± 0.58
Paramonohystera wieseri2clacr1B1–2 mm6.10 ± 1.006.05 ± 0.924.33 ± 0.585 ± 1.735 ± 17 ± 13.67 ± 0.588.62 ± 2.303.67 ± 0.587.33 ± 0.58
Paramonohystera pilosa2clacr1B1–2 mm3.05 ± 1.043.03 ± 1.002.33 ± 0.581.67 ± 0.58
Steineria sp.2clacr1B1–2 mm7.46 ± 0.625.06 ± 1.094.33 ± 0.583.67 ± 0.584 ± 12.67 ± 0.584.67 ± 0.5811.51 ± 1.053.33 ± 0.5811 ± 1
Metoncholaimus pristiurus3clapk2B>4 mm3.74 ± 1.233.36 ± 0.552 ± 0.22 ± 0.30.33 ± 0.580.33 ± 0.58 1.86 ± 0.391.67 ± 0.581.67 ± 0.58
Oncholaimelluscalvadocicus3clapk2B>4 mm8.15 ± 1.145.41 ± 1.655 ± 10.33 ± 0.581 ± 11.33 ± 1.152 ± 0.381.97 ± 0.881.33 ± 0.581.67 ± 0.58
Viscosia cobbi3e/fpk2B1–2 mm4.06 ± 0.953.37 ± 0.653.33 ± 0.580.67 ± 0.582.67 ± 1.53 2 ± 0.21.86 ± 0.3911.67 ± 0.58
Oncholaimus campylocercoides4clapk2B>4 mm10.48 ± 2.396.41 ± 2.1211.67 ± 0.585.33 ± 0.5811.67 ± 0.582.67 ± 0.5811.33 ± 0.5812.38 ± 1.5310.67 ± 0.5811.67 ± 1.53
Calomicrolaimus honestus3cosp2A1–2 mm2.04 ± 1.043.03 ± 1.002 ± 0.194.67 ± 0.58
Calomicrolaimus sp.3cosp2A1–2 mm4.06 ± 1.014.37 ± 0.553.67 ± 0.581.67 ± 0.58
Neochromadora sp.2coId2A1–2 mm2.38 ± 0.624.37 ± 1.521.67 ± 0.580.33 ± 0.58
Chromadorina sp.2coId2A1–2 mm1.02 ± 0.022.34 ± 1.511 ± 0.02
Chromadorina minor2coId2A1–2 mm1.70 ± 0.612.69 ± 0.54 0.33 ± 0.581.33 ± 1.15 1 ± 0.02 0.67 ± 0.58
Anticoma acuminata2e/fpk1A2–4 mm1.69 ± 0.582.69 ± 1.141.33 ± 0.581.33 ± 0.581.67 ± 0.581 ± 0.51 ± 0.04 0.67 ± 0.58
Ascolaimus sp.2cocr1B2–4 mm1.36 ± 0.613.03 ± 1.002 ± 0.21.67 ± 0.584.33 ± 0.583.33 ± 1.151.67 ± 0.582 ± 0.911 ± 11.67 ± 0.58
Cyatholaimus prinzi3cosp2A1–2 mm2.03 ± 1.022.69 ± 0.542 ± 0.01 0.33 ± 0.58 0.33 ± 0.58
Synonchiella edax4e/fsp2B2–4 mm1.02 ± 0.023.03 ± 1.001 ± 0.02 1.67 ± 0.581.99 ± 0.910.33 ± 0.580.67 ± 0.58
Table 2. Percentages of dissimilarity between treatment microcosms (in bold) and SIMPER output, based on square-root transformed data. Only the nematode species and their functional groups that accounted for more then 70% of overall dissimilarity were considered. More or less abundant are represented by + and −, and elimination as Φ.
Table 2. Percentages of dissimilarity between treatment microcosms (in bold) and SIMPER output, based on square-root transformed data. Only the nematode species and their functional groups that accounted for more then 70% of overall dissimilarity were considered. More or less abundant are represented by + and −, and elimination as Φ.
UC vs. UA1 (20.35%)UC vs. UA2 (37.83%)UC vs. UM1 (32.25%)UC vs. UM2 (32.84%)
SpeciesParacomesoma dubium (31.66%) + Paracomesoma dubium (24.45%) + Paracomesoma dubium (18.23%) + Paracomesoma dubium (17.61%) +
Terschellingia longicaudata (11.34%) + Terschellingia longicaudata (15.99%) + Terschellingia longicaudata (13.08%) + Oncholaimellus calvadocicus (11.75%) −
Oncholaimellus calvadocicus (7.34%) Oncholaimellus calvadocicus (9.34%) −Oncholaimellus calvadocicus (10.25%) −Terschellingia longicaudata (7.62%) +
Steineria sp. (7.33%) −Calomicrolaimus sp. (5.33%) Calomicrolaimus sp. (6.83%) −Steineria sp. (7.05%) −
Oncholaimus campylocercoides (5.43%) + Metoncholaimus pristiurus (4.45%) −Metoncholaimus pristiurus (6.27%) −Calomicrolaimus sp. (7.04%) −
Metoncholaimus pristiurus (4.07%) −Steineria sp. (4.44%) −Paramonohystera pilosa (5.13%) −Paramonohystera pilosa (5.29%) −
Chromadorina minor (4.07%) −Paramonohystera pilosa (4.00%) −Steineria sp. (4.55%) −Viscosia cobbi (5.27%) −
Paramonohystera wieseri (3.99%) −Paramonohystera wieseri (4.11%) −
Neochromadora sp. (4.11%) −
Feeding groups10.66%15.90%12.27%13.17%
2A +2B −1A +1A +
1B − 2B −
Tail shape3.32%9.03%11.02%11.94%
cla +co −co −co −
Amphid shape11.03%8.16%18.56%12.36%
sp +sp +cr +cr +
pk −pk −pk −
Adult length7.81%12.63%9.80%9.40%
1–2 mm + 1–2 mm + 1–2 mm +1–2 mm +
c-p score4.43%10.58%7.49%7.69%
c-p3 −c-p3 −c-p3 −c-p3 −
LC vs. LA1 (32.26%)LC vs. LA2 (46.22%)LC vs. LM1 (39.08%)LC vs. LM2 (43.46%)
SpeciesParacomesoma dubium (14.93%) + Terschellingia longicaudata (35.88%) + Terschellingia longicaudata (24.32%) + Terschellingia longicaudata (28.40%) +
Metalinhomoeus numidicus (9.40%) + Paracomesoma dubium (5.19%) + Steineria sp. (6.62%) +Steineria sp. (6.99%) +
Oncholaimellus calvadocicus (8.31%) −Calomicrolaimus sp. (4.81%) −Calomicrolaimus sp. (5.75%) −Oncholaimus campylocercoides (6.19%) +
Terschellingia longicaudata (7.75%) + Neochromadora sp. (4.81%) −Neochromadora sp. (5.75%) −Neochromadora sp. (5.06%) −
Neochromadora sp. (6.63%) −Oncholaimellus calvadocicus (4.47%) −Oncholaimus campylocercoides (5.74%) + Calomicrolaimus sp. (5.06%) −
Synonchiella edax (4.98%) −Oncholaimus campylocercoides (4.07%) −Paracomesoma dubium (5.73%) + Metalinhomoeus numidicus (5.05%) −
Calomicrolaimus sp. (4.44%) −Marylynnia puncticaudata (4.05%) + Oncholaimellus calvadocicus (4.88%) −Paracomesoma dubium (5.02%) +
Cyatholaimus sp. (4.42%) −Viscosia cobbi (3.70%) −Calomicrolaimus honestus (3.99%) −Oncholaimellus calvadocicus (4.29%) −
Viscosia cobbi (4.42%) − Paramonohystera pilosa (3.99%) −Calomicrolaimus honestus (3.51%) −
Terschellingia sp. (4.42%) +
Feeding groups13.81%32.04%19.36%21.78%
2B −1A +1A +1A +
Tail shape13.38%27.58%20.73%11.94%
co −e/f −co −co −
Amphid shape15.55%29.83%23.55%16.93%
cr +cr +cr +cr +
id − id Φsp −
Adult length7.56%15.85%13.65%17.10%
>4 mm −1–2 mm + 1–2 mm + 1–2 mm +
c-p score8.50%8.50%5.88% 9.30%
c-p2 +c-p3 +c-p2 −c-p2 −
UC vs. LC (15.19%)UA1 vs. LA1 (22.95%)UA2 vs. LA2 (30.71%)UM1 vs. LM1 (18.41%)UM2 vs. LM2 (26.24%)
SpeciesOncholaimus campylocercoides (13.29%) −Metalinhomoeus numidicus (15.96%) + Terschellingia longicaudata (31.54%) + Terschellingia longicaudata (28.57%) +Terschellingia longicaudata (41.13%) +
Oncholaimellus calvadocicus (8.89%) −Oncholaimus campylocercoides (14.45%) −Paracomesoma dubium (21.03%) −Paracomesoma dubium (16.44%) −Steineria sp. (16.90%) +
Steineria sp. (7.77%) −Oncholaimellus calvadocicus (10.63%) −Oncholaimus campylocercoides (14.95%) −Steineria sp. (16.32%) + Paracomesoma dubium (10.38%) −
Synonchiella edax (6.67%) + Paracomesoma dubium (6.82%) −
Neochromadora sp. (6.66%) + Calomicrolaimus honestus (6.08%) +
Ascolaimus sp. (5.55%) + Terschellingia sp. (6.07%) +
Terschellingia longicaudata (5.21%) − Viscosia cobbi (6.06%) −
Paracomesoma dubium (4.84%) +
Chromadorina sp. (4.43%) +
Calomicrolaimus honestus (4.07%) +
Feeding groups7.97%14.87%20.99%11.60%14.29%
2A +2B −1A +2A −2A −
Tail shape8.90%11.42%22.63%2.11%21.93%
cla −e/f +e/f +e/f +e/f +
Amphid shape9.85%11.35%20.28%14.01%16.85%
pk −cr +cr +cr +cr +
sp +
Adult length7.93%11.31%8.84%5.36%9.17%
>4 mm −2–4 mm +>4 mm −1–2 mm +1–2 mm +
c-p score5.53%10.50%24.40%6.48%10.86%
c-p2 +c-p2 +c-p3 +c-p3 +c-p3 +
Table 3. Relative abundances (±SD) of males (m), non-gravid females (f), gravid females (gf) and juveniles (J) in uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), f = non-gravid females; gf = gravid females, J = juveniles (J), males (m). The uncontaminated compartments were filled with sediment collected at the beginning of the experiment (i.e., Upper: U), whereas the compartments where azoic sediment was used were either contaminated or not with amitriptyline and amitriptyline and paroxetine mixture (i.e., Lower: L). Bold values indicate significant differences compared to “UC” (p < 0.05, Tukey-HSD test). Stars ** and **** indicate significant differences between underlined treatments at p < 0.01 and p < 0.0001 (Tukey-HSD test), respectively.
Table 3. Relative abundances (±SD) of males (m), non-gravid females (f), gravid females (gf) and juveniles (J) in uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) compartments. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2), f = non-gravid females; gf = gravid females, J = juveniles (J), males (m). The uncontaminated compartments were filled with sediment collected at the beginning of the experiment (i.e., Upper: U), whereas the compartments where azoic sediment was used were either contaminated or not with amitriptyline and amitriptyline and paroxetine mixture (i.e., Lower: L). Bold values indicate significant differences compared to “UC” (p < 0.05, Tukey-HSD test). Stars ** and **** indicate significant differences between underlined treatments at p < 0.01 and p < 0.0001 (Tukey-HSD test), respectively.
%UCLCUA1LA1UA2LA2UM1LM1UM2LM2
m16.76 ± 421.41 ± 3.6320.71 ± 2.7726.34 ± 2.7723 ± 532.37 ± 3.13 **18.09 ± 2.3531.59 ± 3.44 ****15.45 ± 1.3337.61 ± 3.63 ****
f65.88 ± 1.1662.09 ± 5.4375.13 ± 4.7037.48 ± 4.32 ****51.33 ± 4.7352.32 ± 7.1140.56 ± 1.9444.13 ± 5.4331.88 ± 2.2049.51 ± 7.42
gf6.55 ± 0.484.95 ± 0.095.51 ± 0.615.26 ± 0.9145.43 ± 0.495.28 ± 0.551.87 ± 0.092.24 ± 0.072.94 ± 0.18
J7.52 ± 1.399.59 ± 1.665.5 ± 0.447.86 ± 0.5821.66 ± 1.532.22 ± 0.42 ****5.56 ± 0.6710.27 ± 0.446.22 ± 0.496.21 ± 0.80
Table 4. Demographic ratios (±SD) in uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) microcosms. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2). Non-gravid females (f); gravid females (gf); juveniles (J); non-gravid females + gravid females (F); males (m). Bold values indicate significant differences compared to “UC” (p < 0.05, Tukey-HSD test). Stars ** and **** indicate significant differences between underlined treatments at p < 0.01 and p < 0.0001 (Tukey-HSD test), respectively.
Table 4. Demographic ratios (±SD) in uncontaminated (UC, LC, UA1, UA2, UM1 and UM2) and contaminated (LA1, LA2, LM1 and LM2) microcosms. U = Upper compartment, L = Lower compartment, C = Control treatment, A = amitriptyline (0.4 and 40 µg L−1), M = mixture of amitriptyline and paroxetine both at 0.4 µg L−1 (M1) and 40 µg L−1 (M2). Non-gravid females (f); gravid females (gf); juveniles (J); non-gravid females + gravid females (F); males (m). Bold values indicate significant differences compared to “UC” (p < 0.05, Tukey-HSD test). Stars ** and **** indicate significant differences between underlined treatments at p < 0.01 and p < 0.0001 (Tukey-HSD test), respectively.
%UCLCUA1LA1UA2LA2UM1LM1UM2LM2
gf/F0.1 ± 0.010.1 ± 0.010.07 ± 0.010.14 ± 0.020.08 ± 0.010.11 ± 0.020.13 ± 0.010.04 ± 0.010.07 ± 0.010.05 ± 0.01
J/gf1.14 ± 0.141.57 ± 0.36 **** 1.01 ± 0.181.54 ± 0.39 **5.42 ± 0.380.41 ± 0.08 ****1.1 ± 0.095.5 ± 0.5 ****2.79 ± 0.322.11 ± 0.2 ****
m/F0.23 ± 0.060.22 ± 0.050.26 ± 0.020.62 ± 0.050.42 ± 0.130.56 ± 0.020.39 ± 0.030.69 ± 0.030.46 ± 0.070.72 ± 0.05
J/F0.1 ± 0.020.13 ± 0.020.07 ± 0.010.19 ± 0.030.39 ± 0.020.04 ± 0.010.12 ± 0.010.23 ± 0.040.18 ± 0.030.12 ± 0.01
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ishak, S.; Allouche, M.; Nasri, A.; Harrath, A.H.; Alwasel, S.; Plăvan, G.; Beyrem, H.; Boufahja, F. The Antidepressants Amitriptyline and Paroxetine Induce Changes in the Structure and Functional Traits of Marine Nematodes. Sustainability 2022, 14, 6100. https://doi.org/10.3390/su14106100

AMA Style

Ishak S, Allouche M, Nasri A, Harrath AH, Alwasel S, Plăvan G, Beyrem H, Boufahja F. The Antidepressants Amitriptyline and Paroxetine Induce Changes in the Structure and Functional Traits of Marine Nematodes. Sustainability. 2022; 14(10):6100. https://doi.org/10.3390/su14106100

Chicago/Turabian Style

Ishak, Sahar, Mohamed Allouche, Ahmed Nasri, Abdel Halim Harrath, Saleh Alwasel, Gabriel Plăvan, Hamouda Beyrem, and Fehmi Boufahja. 2022. "The Antidepressants Amitriptyline and Paroxetine Induce Changes in the Structure and Functional Traits of Marine Nematodes" Sustainability 14, no. 10: 6100. https://doi.org/10.3390/su14106100

APA Style

Ishak, S., Allouche, M., Nasri, A., Harrath, A. H., Alwasel, S., Plăvan, G., Beyrem, H., & Boufahja, F. (2022). The Antidepressants Amitriptyline and Paroxetine Induce Changes in the Structure and Functional Traits of Marine Nematodes. Sustainability, 14(10), 6100. https://doi.org/10.3390/su14106100

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop