# Commercial formulations of copper-based conventional and nano-formulated pesticides affect chironomid-associated microbiota and hosts traits

Thomas Moura, Florian Chapeau, Laurence Chevalier, Frédéric Caudaudap, Marion Vivant, Gaël Le Roux, van Xuan Nguyen, Eva Casale, Camille Larue, Laury Gauthier, et al.

► To cite this version:

Thomas Moura, Florian Chapeau, Laurence Chevalier, Frédéric Caudaudap, Marion Vivant, et al. Commercial formulations of copper-based conventional and nano-formulated pesticides affect chironomid-associated microbiota and hosts traits. Journal of Hazardous Materials, 2025, 499, pp.140294. 10.1016/j.jhazmat.2025.140294. hal-05515154

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# Commercial formulations of copper-based conventional and nano-formulated pesticides affect chironomid-associated microbiota and hosts traits

Thomas Moura<sup>a, ID</sup>, Florian Chapeau<sup>a, ID</sup>, Laurence Chevalier<sup>b, ID</sup>, Frédéric Candaudap<sup>a, ID</sup>, Marion Vivant<sup>a</sup>, Gaël Le Roux<sup>a</sup>, Van-Xuan Nguyen<sup>a</sup>, Eva Casale<sup>c</sup>, Camille Larue<sup>a, ID</sup>, Laury Gauthier<sup>a</sup>, Eric Pinelli<sup>a</sup>, Maïalen Barret<sup>a</sup>, Eric Houdeau<sup>c</sup>, Bruno Lamas<sup>c</sup>, Florence Mouchet<sup>a, ID</sup>, Lauris Evariste<sup>a,c,*</sup>

## HIGHLIGHTS

* Copper nano- and conventional pesticides show comparable toxicity in midges.

* Nano-Cu leads to greater bio-accumulation in adults, raising trophic transfer risks.

* Altered host life history traits are linked to impaired host-associated microbiota.

* These findings question the environmental safety of Cu nano-formulations.

## GRAPHICAL ABSTRACT

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

**Keywords:**

Holobiont

Aquatic ecotoxicology

Nano-toxicology

Bioassay

## ABSTRACT

Copper-based plant protection products (PPPs) are widely used in agriculture to control fungal and bacterial diseases. However, concerns regarding copper accumulation in the environment have led to restrictions on its use. Copper-based nano-formulations have been proposed as an alternative, offering improved efficiency and reduced application rates. However, their environmental risks remain poorly understood, particularly their effects on aquatic ecosystems. This study evaluates the ecotoxicity of conventional and nano-formulated copper pesticides using *Chironomus riparius* as a holobiont model, considering both host life history traits and microbiota responses. Larvae were exposed to environmentally relevant concentrations (5, 50, and 500 µg Cu/L) of conventional and nano-formulated products under controlled laboratory conditions. Exposure to the highest concentration resulted in 100 % mortality. Following exposure to 50 µg Cu/L, sublethal effects were observed,

<footnote><sup>a</sup> Centre de Recherche sur la Biodiversité et l'Environnement (CRBE), Université de Toulouse, Toulouse INP, CNRS, IRD, CRBE, Toulouse, France</footnote>

<footnote><sup>b</sup> Groupe de Physique des Matériaux UMR 6634, CNRS, Rouen, France</footnote>

<footnote><sup>c</sup> Toxalim, Université de Toulouse, INRAE, ENVT, EI-Purpan, Toulouse, France</footnote>

<footnote>* Correspondence to: TOXALIM Research Centre in food toxicology, 180 Chemin de Tournefeuille, 31027, Toulouse, cedex 3, France.
E-mail address: lauris.evariste@inrae.fr (L. Evariste).</footnote>
including alteration of the larval microbiota composition, apparently shifting towards a copper-tolerant profile following exposure to the conventional formulation. Despite the distinct shifts in bacterial taxa between conventional and nano-formulated treatments, similar decreased adult emergences are noticed following exposure to both formulations. Despite comparable toxicity profiles, nano-formulations resulted in higher copper bio-accumulation in emerging adults, raising concerns about trophic transfer and ecosystem impacts. Our findings highlight the need for a holistic approach integrating host-microbiota interactions in ecotoxicological assessments. The comparable toxicity of nano-formulated and conventional copper pesticides, coupled with increased bioaccumulation potential, questions the assumption that nano-formulations represent a safer alternative. These results emphasize the importance of comprehensive risk assessments to ensure sustainable agricultural practices while minimizing environmental harm.

# 1. Introduction

Plant protection products (PPPs) are extensively used in modern agriculture to enhance crop production. However, growing evidence highlights their global detrimental impacts on both biodiversity and human health [1]. Among available products, copper-based plant protection products are widely used in both conventional and organic agriculture to prevent plant diseases involving fungal or bacterial infections. However, excess copper levels in soils can have harmful effects on the growth and development in most plants, affect soil micro-organisms and fauna but also on the biodiversity at a larger scale [2,3]. As a consequence, copper use has been restricted in European countries (Regulation (EU) 1018/1981 2018) to protect both the environment and human health [4]. Protecting biodiversity and maintaining ecosystem services through the reduction of pesticide environmental footprint constitute an important goal for agricultural and environmental policies worldwide [5]. However, finding alternatives to reach this goal is remaining challenging given the increase of global food demand, climate change and pest resistances [6]. Among possible alternatives, copper-based nano-formulations are proposed as solutions allowing to reduce the copper use while maintaining or improving crop protection efficiency [7]. Indeed, it is argued that copper-based nano-formulations are more efficient compared to conventional products, allowing to reduce applications rates while providing increased plant growth yield [8]. Moreover, with an apparent better cost-efficiency and a lower environmental impact suggested by life cycle analysis data [9], these products are likely to attract interest from end users for disease control management in agriculture.

Increasing the use of copper-based nano-formulations would inevitably conduct to increased environmental releases of the compounds, raising concerns about their toxic and ecotoxic potentials, especially as these data are scarce. Indeed, on the one hand, repeated applications can lead to accumulation of nano-copper in soils, transfer into plants and seeds to reach the food chain, contributing to human exposure [10,11]. On the other hand, copper nanoparticles can leach to groundwater through runoff and reach aquatic ecosystems which constitute sinks for nanoparticles [12]. Indeed, while total Cu from anthropogenic sources is reaching in freshwater ecosystems concentrations ranging from a few µg/L to tens of µg/L [2,13], probabilistic models predicted that nano-copper could reach concentrations up to 0.06 mg/L, both forms constituting a significant risk for exposed organisms [14,15]. Thus, their release into aquatic environments can constitute a threat as non-target organisms from freshwater ecosystems were indicated to be more sensitive to copper nanoparticles compared to terrestrial organisms [16, 17].

While biological models such as zebrafish have been previously used to elucidate mechanistic toxicological pathways of nano-copper (e.g., oxidative stress, tissue-level histopathology) [18,19], these approaches do not capture ecosystem-level processes or population consequences. In contrast, the macroinvertebrate *Chironomus* sp. constitutes a model organism of interest in ecotoxicology that was previously used to evaluate water quality [20], and to determine the ecotoxic potential of contaminants of emerging concern such as pharmaceuticals and personal care products (PPCPs) [21], PFAS [22], nanomaterials [23,24] or micro-nano

plastics and plastic associated leachates [25,26]. From an ecological perspective, chironomids play key roles in aquatic ecosystems through organic matter and nutrient cycling [27], while constituting an important food source for aquatic organisms during its larval life and terrestrial organisms when reaching adult stages [28,29]. Thus, given their ecological significance, impairment of chironomids life cycle could have wider deleterious consequences on ecosystem functioning. However, traditional approaches often focus on the direct effects of pollutants on the host organism alone, neglecting the intricate interactions between the host and its associated microbiota. Over the last years, the holobiont concept is emerging in ecotoxicology, considering biological entity as a host organism and its associated microbiota [30,31]. Indeed, it is now recognized that the physiology and traits of host organisms highly depend on its associated microbial communities, and vice versa [32]. However, these microbial communities are also sensitive to environmental pollutants [33,34]. Thus, since the chironomid's microbiota serve as an interface between the host and environmental and was suggested to protect the host from toxic metals, supported by detoxification capacities [35,36], this reinforce the importance of considering host-microbiota interactions when evaluating potential adverse effects of a product.

This study aims to compare the ecotoxic potential of conventional and nano-formulated copper-based pesticides using *Chironomus* sp. as a holobiont model. Specifically, we evaluate the differential impacts of these formulations on both host organism life history traits and its associated microbiota, considering their potential toxicity at environmentally relevant concentrations. The findings will contribute to a better understanding of the ecological risks posed by copper-based nano-formulations in order to support the development of more sustainable agricultural practices.

# 2. Material and method

## 2.1. Chemicals, characterization and copper quantification

The Cu(OH)₂ nanopesticide Kocide® 3000 was selected as a representative commercially available nanocopper-based, water-dispersible product. It was obtained from Certis (Lot n°: JUN20HG030, Certis USA L.L.C). Kocide® 3000 contains 46.1 % Cu(OH)₂, 1–5 % of (undefined) clays, 5–10 % 2-propenoic acid, and 38.9–47.9 % of “other proprietary ingredients” (identity and/or exact percentage(s) are being withheld as a commercial secret). The pesticide Kocide® 2000 was selected as a conventional copper-based formulation available on the market with a long-standing, global usage, while sharing the same principal active ingredient (copper hydroxide, Cu(OH)₂ as Kocide® 3000. It was obtained from Certis Europe B.V.-France (Lot n°: T22202008). According to the safety data sheet, it consists of 53.8 % Cu(OH)₂, 5–10 % phosphate salt, 5–10 % clay minerals and other “proprietary” ingredients.

### 2.1.1. Electron microscopy

Raw powder of commercial formulations of copper-based phyto-pharmaceuticals including Kocide® 2000 (conv) or the nano-formulated Kocide® 3000 (nano) was first characterized by Scanning Electron Microscopy SEM (JEOL 7900 F) equipped with an EDS-Detector (Oxford,
Abington, England) for chemical composition and raw feature. Particles 'formulations were done in ultrapure water following supplier recommendations and were then analyzed by Transmission Electron Microscopy High Resolution with analytical configuration at 80 kV (ARM200- JEOL Japan): 1 mg eq.Cu/mL was mixed with water and stirred for 20 min in a ultrasonic bath at 100 W and 40 kHz in order to disperse the aggregates. The whole solution was deposited on a 0.45 µm acetate cellulose filter inserted in a conical centrifuge tube and spin 15 min at 10 000 rpm. Particles for TEM observations were collected on a holey carbon 400 mesh gold grid previously positioned at the bottom of the conic tube, below the filter. Grids are then air-dried before their TEM- observations. Preferentially, the images are acquired in a STEM- HAADF mode, based on Z-contrast that is particularly helpful in our case for metal- detection, due to the large difference in Z number be- tween Cu and materials that constitute particles. Elemental chemical and mapping composition was performed on STEM mode with a 8 C probe size, a camera length of 8 cm, and a 50 µm condenser aperture using a SDD detector XMax TLE (Resolution:127ev Mnk 0.7 sr; Oxford- Instruments, Abington, England).

### 2.1.2. X-Ray diffraction analysis

The chemical form of copper was identified by XRD Analysis. Data were collected on a Empyrean Xray diffractometer (Malvern-pan analytical Ltd) using a Co Kα 1 radiations (1.78886 °A, 40 kV, 40 mA) in Bragg- Brentano Θ/ Θ configuration. The pattern is collected between 5 and 90° with a step size of 0.03/0.017, a counting time of 1.0 s/step and an anti-scatter slit of 10.0 mm.

### 2.1.3. Particle size distribution after dispersion in ultrapure water and zeta potential

Size distribution of conventional and nano-formulated particles dispersed in ultrapure water was evaluated by both dynamic lights scattering (DLS) in addition to the TEM observations. Size distribution of particles in liquid media was measured using a nano ZetaSizer system (Malvern Instruments). Parameters of analysis were as follow: laser wave length of 633 nm, stabilization time 120 sec, temperature of 25°C, medium refractive index 1.7. To avoid underestimation of nanoparticles, the sample are eluted through a 0.45 µm acetate cellulose filter prior to the analysis in order to remove biggest aggregates and obtain a stable suspension. Five repeats were done for that the mean results were recorded. For zeta potential, the sample were previously centrifuged (10 000 rpm, 10 min) to remove biggest aggregates; measures were done on supernatant, in three replicates.

### 2.1.4. Inductively coupled plasma emission spectroscopy

Copper concentrations in the exposure media from independent experimental units (n = 3) were analyzed using Inductively Coupled Plasma Emission Spectroscopy (ICP-OES, quantification limit: 2–100000 µg/kg with 1–5 % precision measure; AMETEK Spectro ARCOS FHX22, Kleve, Germany). Sample solutions were diluted with a HNO₃ 2 % solution to avoid precipitation or adsorption in containers and reduce the spectral interference and viscosity effects. With this method, the amount of copper in a quality control sample was recovered at 96 % (nominal concentration: 50 µg/L).

### 2.1.5. Quantification of Cu load in emerged chironomids

Chironomid adults were digested using ultra-pure nitric acid (Optima grade, Fisher Scientific) in a clean room (class 100) at the CRBE Toulouse. The digestion was carried out overnight at 90°C on hot plates, using 0.5 mL of 65 % HNO₃ in 15 mL DigiTUBEs (SCP Science, France). After digestion, the samples were diluted to achieve a final concentration of 2 % nitric acid. Trace element analysis, including copper, was performed using a Thermo Scientific iCAP ICP-MS at Observatoire Midi-Pyrénées Toulouse. Blank values were negligible, and the analysis was successfully conducted across a range of matrices from blood and vegetation to fish muscle, covering concentrations from 5 to 100 mg/kg.

## 2.2. Chironomus rearing

Chironomus riparius used in the experiments originated from laboratory breeding facilities. The organisms were maintained in laboratory in accordance with the standard recommendations [37,38], in 20 L aerated aquaria placed in a thermostated room at 21 ± 1°C, under a 16–8 h light-dark cycle. The reconstituted water (RW) used for breeding and experiment is composed of deionized water and salts (66.2 mg/L CaCl₂·2H₂O; 61.4 mg/L MgSO₄·7H₂O; 96 mg/L NaHCO₃; 4 mg/L KCl; 63 mg/L CaSO₄·2H₂O; 1 mg/L NaBr). Sand of fine grain size (< 350 µm; Fontainebleau® VWR sand) is used as substrate for larvae. Chironomus are fed with grounded fish food dispersed in distilled water using an ultrasonic bath (400 mg of Tetramin® per tank per day). Prior exposure, egg masses are collected from the breeding tanks and placed in a crystallizing dish containing 1 L of RW and a fine layer of sand and 150 mg of food. Larvae of first instar (less than 48 h old) are collected and assigned to experiments.

## 2.3. Exposure to phytopharmaceuticals during larval stages

Adapted from the normalized procedure [37–39], Chironomus larvae were exposed to 3 concentrations of commercial formulations of copper-based phytopharmaceuticals including conventional (conv) or the nano-formulated products (nano) under static conditions (total volume of 300 mL) during 7 days. The nominal copper concentration tested were 5–50 and 500 µg Cu/L, based on copper doses indicated by the manufacturer, corresponding to 14,3 – 143 and 1430 µg/L of raw conventional formulation and 16,7 – 167 and 1670 µg/L of raw nano-formulation.

Prior to exposure, 7 experimental units per tested condition were prepared, containing 75 mL of Fontainebleau sand and 300 mL of RW maintained under gentle aeration. 10 chironomid larvae (1.79 ± 0.1 mm) are placed into each experimental unit by pipetting. Aeration is interrupted during 24 h prior exposure in order to allow chironomids to settle and bury. Contamination was performed through the introduction of the appropriate volume of the test product stock solution prepared in deionized water. The negative control (Ctrl) containing sediment and RW alone. 1 mg of finely grinded Tetramin® was added every day to each experimental system. Aeration was restarted the day following Chironomus introduction until the end of the experiment. Water quality parameters, such as pH (8 ± 0.2), temperature (22.1 ± 0.7°C), nitrite, ammonia and dissolved oxygen content (9 ± 0.5 mg/L) were monitored throughout the experiment and did not vary between the tested conditions.

Following 7 days of exposure, the survival rate was determined based on the number of chironomids alive in each experimental unit. After rinsing in 70 % ethanol, larvae were photographed under binocular magnifier (Olympus SZX7) to measure larvae using ImageJ software and calculate the larval growth as previously described [40]. The development stage reached by the surviving larvae was determined through the measurement of cephalic capsule width. Larvae are classified as stage 1 when cephalic capsule width range from 0.07 to 0.12 mm; stage 2 from 0.13 to 0.24 mm, stage 3 from 0.26 to 0.40 mm and stage 4 from 0.43 to 0.60 mm. The potential induction of teratogenic effects was evaluated through observation and numeration of mentum deformities in larvae reaching the 4th developmental stage. For this purpose, cephalic capsules were discolored by incubation in potassium hydroxide (15 %) at 95 °C during 12 min and 12 h in 70 % ethanol. Then, cephalic capsules are mounted on a microscope slide for observation under light microscope. Mentum deformities were categorized based on previous work [41], considering only tooth deletions, additions, Khön gaps or first tooth split for anomaly scoring for analytical consistency [42,43].

The collected larvae were stored at –80°C for later bacterial DNA extraction intended to study the effects of the test products towards the larvae gut microbiota.
## 2.4. Effects of a whole life-cycle exposure to phytopharmaceuticals on life history traits

To evaluate the effects of the test products on the entire life cycle of the organisms, the exposures were carried out under similar conditions compared to the larvae exposure. However, the experimental units contained 100 mL of Fontainebleau sand and 400 mL of RW under gentle aeration. Each treatment was performed in 10 replicates, each containing groups of 5 first instar post-hatching larvae (1 ± 0.07 mm), and was water exposed until emergence. Adult escape was avoided using nets covering the test systems. During the exposure, 1 mg of finely grinded Tetramin® was added three times per week to each experimental unit.

Exposure lasted up to 24 days and adult emergence was monitored daily to determine the time to emergence and emergence rate. Adults were captured for sex identification, allowing to calculate the sex-ratio, and photographed for length measurement. Organisms were then stored at -80°C prior bacterial DNA extraction for gut microbiota survey.

## 2.5. Effects of the exposure towards host-associated gut microbiota

To evaluate the effects of the test products towards host-associated microbiota, Total DNA was extracted from the whole organisms (larvae or adult) using the QIAGEN DNeasy PowerSoil Pro Kits, following manufacturer's recommendations with little adjustment, including DNA elution using 30 µL of C6 solution. The DNA extracts quality and quantity were determined through the use of NanoDrop 2000 UV spectrophotometer (Thermo Scientific). The V4 region of 16S rRNA gene was targeted using the primers 515 F (5'-GTGY-CAGCMGCCGCGGTAA-3') and 806 R (5'- GGACTACNVGGGTWTCTAAT-3') primers set [44,45]. PCR samples were performed in a volume of 30 µL containing 22.9 µL of DNAse free PCR water, 3 µL of 10X PCR Buffer, 1 µL of DNA extract, 1.1 µL of 515 F primer, 1.1 µL of 806 R primer, 0.6 µL of dNTP (2.5 mM) and 0.3 µL of Taq DNA polymerase (5 U/mL - Sigma Aldrich). PCR run was performed as follows: 94°C - 120 s; (94°C - 30 s; 65°C - 40 s; 72°C - 30 s) x 30 cycles; 72°C for 10 min. Sequencing of the obtained 16S rRNA genes amplicons was operated by the Genotoul Get_PlaGe platform (Toulouse, France) through Illumina MiSeq technology (2 × 250 pb).

Bioinformatics were conducted using QIIME 2 219.4 [46]. Demultiplexed paired-end reads were imported via a manifest in QIIME 2. After importing, quality filtering and denoising were performed with DADA2 on paired-end data using trim-left of 18 nt (forward) and 19 nt (reverse) and trunc-len of 220 nt (forward) and 210 nt (reverse) [47]. Default DADA2 behaviour for error learning and consensus chimera removal was used. A total of 2,028,570 reads were obtained for larvae (minimum = 8862; maximum = 37,748; mean = 24,738) and 533,840 reads (minimum = 1477; maximum = 40,611; mean = 8751) for adults. Amplicon sequences were aligned using Mafft and a phylogenetic tree was built using FastTree [48,49]. Taxonomy was assigned using naive Bayes taxonomy classifier with the Silva 138 reference database [50]. For diversity analysis of larvae, data were rarefied (qiime diversity core-metrics-phylogenetic) at a sampling depth of 10502 reads, discarding 3 samples while for adults, rarefaction was applied for at 2073 reads for females and 2361 for males, discarding 1 sample for each sex.

## 2.6. Statistical analysis

Graphs were generated and statistical analysis performed using the software GraphPad Prism software (version 9.3.1). Data related to chironomids physiological parameters were analyzed using one-way analysis of variance (ANOVA) followed by Tukey test after ensuring that the data were normally distributed and that the variance was homogeneous.

For the microbiota survey, differences in the alpha diversity indexes and phyla relative abundances were analyzed at each sampling time using one-way analysis of variance (ANOVA) followed by Tukey test.

Principal coordinates analysis (PCoA) plots were used to assess the variation between experimental conditions based on Bray-Curtis distances. Data were exported into R to compute ellipses with 95 % confidence intervals using Vegan package [51]. Differences in beta-diversity were assessed via pairwise Permanova tests with 999 permutations restricted to a single factor in line with the study design. We used a PERMDISP test in QIIME2 with 999 permutations to assess potential differences in group dispersion between treatments [52]. Differentially abundant taxa were analyzed by the linear discriminant analysis (LDA) effect size (LEfSe) method [53] and using the analysis of composition of microbiomes (ANCOM) framework implemented into QIIME2 [54]. Analyses were conducted using raw bacterial abundances at level 7 obtained from QIIME2 and exported to the Genotoul bioinformatics Galaxy platform (https://vm-galaxy-prod.toulouse.inra.fr) for LEfSe analysis. For stringency, differentially abundant taxa that were considered statistically significant for an alpha of 0.05, and LDA score (log10) exceeding 3.0.

# 3. Results

## 3.1. Particles characterization

The Fig. 1 gives a brief comparative overview of the both (Nano and conventional) Cu based pesticides. Under their marketed forms, they appear as regular round shape constituted of primary particles aggregates (Fig. 1A, B). Raw dry powders from the conventional product has a size centered near 250–300 µm while those of the nano-one is shifted towards 50 µm with an obvious polydisperse distribution. The nanometric properties of the raw powders were differentiated by impactor granulometry and TEM measurement after aerosolization (data not shown). The chemical form of copper was identified by XRD (Empyrean, Malvern Panalytical Ltd) (Fig. 1C, D). Minor and major peaks shared between the two products appeared in the XRD-diffractogram patterns of conv and nano-formulations. For the nano-formulation (Fig. 1D), the major crystalline phase (45 %w) found to be Cu(OH)₂ corresponding to the orthorhombic spertiniite. Additive components are identified as calcite/carbonate (C), quartz (Q), and copper sulfate respectively semi-quantified at 8, 7.8, 18.6 %wt. The datasheet for both products indicates the presence of bentonite/montmorillonite. Clays have peaks at low angles, with a characteristic line at 7.23. In the nano product pattern, we observe two peak (d=8.2 and 10) that are shifted from the Kaolinite/ Montmorillonite reference. As conventional product pattern is considered, copper hydroxide is identified but doesn't represent the major crystalline phase. Calcite/carbonate seems to be in high relative proportion (around 35 %W) whereas copper form as hydroxide and sulfate represents respectively 10 and 14.6 %w.

When the two products are dispersed in ultrapure water, TEM micrographs show significant differences in morphology between conv and nano-formulations (Fig. 1E, F). For the conventional product, particles appear as regular sheetlet shape frequently aggregated each other. Some of them contain copper distributed as cluster entrapped in the platelets or at their edges. In contrast for the nano formulation, micrographs reveal high number of nanorods (that are not visible in conv. sample) as well as low-contrast platelet particles. Nanorods are loaded with copper as shown by EDS-mapping (Fig. 1B). To highlight differences between the two products forms, we evaluated size distribution in liquid phase using two procedures (DLS and TEM measurement). DLS measures the equivalent spherical hydrodynamic diameter ($d_{hyd.}$) whereas TEM determines the projection size of the particle that can be expressed by several parameters such the equivalent circular diameter ($d_{ecd}$) or Feret's diameter where min-Feret is the minimum caliper diameter as chosen in this study. Briefly, the average hydrodynamic diameter is quite similar between conv. and nano with a mean value closed to 75–77 nm. However, the polydispersity index shows high value for nano and conv. (respectively 0.298 and 0.188) reflecting a broad dispersion probably due to the interaction between particles (Figure S1A). To
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Overview of the morphology, composition and size distribution of the conventional and nano-pesticides. A, B: Morphology of raw marketed dry powder imaged by Scanning Electron Microscopy (SEM) and element composition associated. C, D: Comparative X-ray Diffraction performed on conventional Cu-based formulation (C) and Cu-based nano-formulation (D). The cyan line indicates peak position for spertinitiite, orthorhombic crystalline structure of copper hydroxide. The numbers correspond to the crystallographic plane h, k, l. M/K: montmorillonite/kaolinite; Q: Quartz, C: calcite/carbonate. E, F: Transmission electron microscopy of particles dispersed in aqueous media showing the morphology and copper content defined by energy dispersive mapping (EDS-Cu map). Focus is done on the presence of copper trapped in large flat platelets for the conventional formulation (E-right panel), whereas in the nano-formulated product, nanometric needles are observed (F-right upper panel) where the smallest width is lower than 10 nm. The images are acquired in STEM-HAADF mode favoring a Z-contrast for the detection of element with high atomic number.</figcaption></figure>

overcome these limits, TEM-size measurement contributes to have a better overview of size distribution. The min-Feret diameter is significantly lower for nano with a given 107 nm compared with 160 nm for conv., while the median is set at 47 nm for nano versus 112 nm for conv (Figure S1B). TEM observations complete DLS analysis and demonstrate the nano-specific properties of nano products by the presence of nano-needles associated to a nano-size distribution.

The Zeta-potential measure the electrical potential of particles given by the charge present at their surface. The value recorded in ultrapure water (pH 6.5) are respectively -41.2 mV for the nano-formulation and -32.3 mV for the conventional product, indicating that particles are negatively charged. The magnitude of the nano-formulation potential is out of the range of + /-30mV, predicting a higher colloidal stability than the conventional one. When tested in a mineral water rich in cations as solvent media, we observe an increase of the potential (-25.6 mV for nano; -29.1 mV for conv) showing a high reactivity of particles with the molecules present in the water.

## 3.2. Effects induced through exposure during larval stages

Monitoring of the copper concentrations in the water column of the test systems using ICP analysis indicated that the target dose at the beginning of the exposure was reached in the different tested concentrations (Fig. 2A). Copper concentrations were comparable between the conventional product (conv) compared to the nano-formulated product (nano), except for the highest tested concentration of 500 µg Cu/L (T-test, *p* = 0.047), where Cu concentration was 7.9 ± 1.1 % lower for the conventional form (Fig. 2A). Over the exposure duration, Cu concentrations in the water column of test systems devoid of organisms decreased by 58-70 % depending on the considered condition, with a comparable kinetic between the two product formulations (Fig. 2B). Interestingly, the presence of larvae in the test systems led to maintain over 7 days a significantly higher Cu concentration in the water column (Fig. 2C), probably due to bioturbation activities.

Following 7 days of exposure to the test products, no larvae were recovered in the test systems contaminated with 500 µg of Cu/L (conv.

and nano) due to acute mortality. However, no significant decrease of survival was detected following exposure to 5 and 50 µg Cu/L compared to the control group (ANOVA, *p* = 0.086) (Fig. 3A). Under these conditions, the larval growth was not altered (ANOVA, *p* = 0.447) and all the collected organisms reached the fourth instar stage, indicating an absence of developmental delay (Fig. 3B). Analysis of mouth part deformities, as an indicator of teratogenicity, showed no effect on this endpoint of the tested products (ANOVA, *p* = 0.953) (Fig. 3C). Thus, considering larvae history traits, the concentration of 50 µg Cu/L constitute the no observed effect concentration (NOEC – 7 days) of both products.

Considering host-associated microbiota survey performed through 16S sequencing, the applied treatments did not influence alpha diversity indexes calculated, including the observed diversity and Shannon index (ANOVA, *p* = 0.487 and 0.321 respectively) (Fig. 4A, B). However, based on Bray-Curtis distance, PCoA plot and calculated distances suggest changes in the structure of the gut microbial communities following exposure to both conventional and nano-formulations at 50 µg Cu/L and to a lesser extend to nano-formulation at 5 µg Cu/L (PERMANOVA, *p* = 0.001) (Fig. 4C, D). While dispersion did not differ following exposure to both product forms at 50 µg Cu/L compared to the control group, heterogeneity increased following exposure to the nano-formulation at 5 µg Cu/L (PERMDISP, *p* = 0.003). Thus, focusing on host-associated microbiota, the NOEC is 5 µg Cu/L for the conventional formulation and the lowest observed effect concentration (LOEC – 7 days) is 50 µg Cu/L while it is of 5 µg Cu/L for the nano-formulation.

The microbiota from organisms under the control conditions is composed of 5 main phyla, including Proteobacteria (61.63 ± 2.68 %), Bacteroidota (18.07 ± 1.16 %), Desulfobacterota (7.99 ± 0.64 %), Firmicutes (8.26 ± 0.65 %) and Bdellovibrionota (1.44 ± 0.37 %) (Fig. 4E-I). Analysis of differential taxa abundances using linear discriminant analysis (LDA) effect size (LEFSe) indicated that the exposure to conventional Cu at 50 µg Cu/L led to a decrease of minor taxa affiliated to the order Microtrichales (phylum Actinobacteria) while taxa identified from the genera *Shinella* and *Brevundimonas*, both from the phylum Proteobacteria, accounting respectively for 5.16 ± 1.05 % and 0.22 %.
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Copper (Cu) concentration and dynamic in experimental systems. (A) Concentration of Cu reached following contamination of the exposure media with conv. or nano products compared to the target concentration. (B) Evolution of Cu concentration over the first week of the experiment in test systems in absence of organisms. (C) Cu concentration in the water column after 7 days in presence or absence of *Chironomus riparius* larvae in the experimental systems. Data are presented as mean ± s.e.m with n = 3. Statistical differences in Cu concentrations between conventional (conv.) and nano conditions (nano) or in a condition with or without larvae in the experimental system was evaluated using Student's t test. \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Effects of a 7 days of exposure to conventional (conv) or nano-formulated (nano) copper-based pesticide on *C. riparius* larvae. (A) Larvae survival (B) Normalized growth rate (C) Frequency of mentum deformities occurrence in fourth instar larvae. Data are presented as mean ± s.e.m. Statistical analysis was conducted using ANOVA, followed by post hoc Tukey test when p < 0.05. "\*" indicates significant differences compared to the negative control (Ctrl) with \*: p ≤ 0.05; \*: p ≤ 0.01; \*: p ≤ 0.001; \*: p ≤ 0.0001.</figcaption></figure>
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**Fig. 4.** Host-associated microbiota response to 7 days of exposure to conventional (conv) or nano-formulated (nano) copper-based pesticide. (A-B) Observed microbial richness and Shannon alpha diversity indexes in *C. riparius* larval microbiota. (C) Principal Component Analysis (PCoA) based on Bray-Curtis dissimilarities calculated from 16S rDNA sequencing. (D) Bray-Curtis distances calculated. (E) Stacked bar plot representation of bacterial relative abundance at phylum level. (F-I) Relative abundances of the main phyla composing the larval microbiota. (J-K) Bacterial taxa differentially enriched in *C. riparius* associated microbiota using Linear Discriminant Analysis Effect Size (LEFSe) pipeline with Linear Discriminant Analysis (LDA) score > 3.0. Data are mean ± s.e.m. significance was determined using one-way ANOVA followed by post-hoc Tukey test for multiple comparisons. Bray-Curtis distances were compared using PERMANOVA; \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001.

± 0.08 % of the reads (Fig. 4J; Figure S2A). Different taxa were identified as differentially abundant in the *C. riparius* microbiota following exposure to the nano-formulated product (nano) at the same concentration compared to the control group, leading to a decrease of taxa from Proteobacteria phylum such as *Novispirillum* genus or Rhizobiales family, while taxa from the Firmicutes phylum, including the Bacilli and Clostridia classes increased (Fig. 4K; Figure S2B). The use of ANCOM emphasized the significant impact on the abundances of bacteria from the Rhizobiales family (W = 373) and taxa from the genera *Brevundimonas* (W = 351) and *Rubrivivax* (W= 383) from the Proteobacteria phylum.

### 3.3. Consequences of the exposure on adult traits and host-associated microbiota

Prolongation of the exposure to the test products until the adult stage led to a decreased survival of *C. riparius* following exposure to the nano-formulation at 50 µg Cu/L with a similar trend observed with the conventional product at the same concentration (ANOVA, *p* = 0.034) (Fig. 5A). Survival was determined based on the number of emerged adults and living larvae recovered at the end of the exposure (day 24).

Monitoring of the emergence dynamic within the test systems indicated a significant decrease of adult emergence following exposure to both conventional and nano-formulated products at 50 µg Cu/L (ANOVA, *p* = 0.006) (Fig. 5B, C). Sex identification of emerged organisms allowed to determine that the sex-ratio and the proportion of female emerged were not significantly affected after exposure to the different test conditions (ANOVA, *p* = 0.586 and ANOVA, *p* = 0.898) (Fig. 5D,E). Following exposure to both conv. and nano products at 50 µg Cu/L, the overall decrease of adult emergence is not associated to significant differential effects between sex (ANOVA, *p* = 0.704 and *p* = 0.156 for male and female respectively). However, exposure to this dose is associated to a 48 % (conv) and 35 % (nano) lower mean emergence rate for female, while it was only 29 % for male (Figure S3 A, B). The size of adults emerged from Cu-contaminated conditions was comparable to the size of organisms from the control group (ANOVA, *p* = 0.935 for male and *p* = 0.163 for female) (Figure S3C, D). Interestingly, Cu quantification in the emerged adults indicated that the Cu load was significantly higher following exposure to the highest dose of the nano-formulated product compared to the conventional pesticide reaching respectively 23.25 ± 7.27 and 9.99 ± 1.62 µg Cu/g, compared to the control group where 6.33 ± 2.06 µg Cu/g were recovered (KW, *p* = 0.046) (Fig. 5F).

The microbiota of males and females emerged from the control groups exhibited closely related microbiota as suggested by the similarities in alpha and beta diversity indexes calculated using Bray-Curtis distances (Figure S4A-D). Only few minor taxa from the genera *Akkermansia*, *Neisseria*, *Paenibacillus* with a relative abundance lower than 1 %, except for *Methylophilus* accounting for 4.9 ± 1.5 % of the reads in females, were significantly differentially abundant between sexes according to the LEFSe analysis (Figure S4E, F).

In both sexes, the 3 main phyla composing the host-associated microbiota were Proteobacteria (males: 39.3 ± 9.22%; females: 52.8 ± 6.8 %), Bacteroidota (males: 24.1 ± 3.1%; females: 26.8 ± 4.4 %) and Firmicutes (males: 17.7 ± 4.7%; females: 8.7 ± 1.6 %) with an important interindividual variability (Figure S5). Interestingly, emerged adults of both sexes exposed to conventional or nano-formulated test

products harbored a microbiota closely related to that of the control group. While few males emerged following prolonged exposure to the highest concentration of the conventional product, the collected organisms harbored an associated microbiota with a significantly lower Shannon index (ANOVA, *p* = 0.007). However, its structure and dispersion were not altered as suggested by the absence of effect on the beta diversity index calculated based on Bray-Curtis distances (PERMANOVA, *p* = 0.285; PERMDISP, *p* = 0.915) (Fig. 6A-D). The significantly lower Shannon index calculated under this experimental condition is associated to organisms harboring a microbiota with a trend in an increased relative abundance of bacteria from the phylum Proteobacteria compared to the other groups (ANOVA, *p* = 0.013). In addition, while no taxa were detected differentially affected using ANCOM, based on LEFSe analysis, taxa from the genera *Akkermansia*, *Pseudomonas* or *Clostridia* were shown to significantly decrease following exposure, benefiting to microorganisms from the genus *Nevskia* whose relative abundance increased (Fig. 6E-G & Figure S6).

In females, while alpha diversity indexes were similar across the tested conditions (Observed diversity: ANOVA, *p* = 0.071; Shannon index, ANOVA, *p* = 0.247), the host-associated microbiota structure was affected only following exposure to the lowest dose of the conventional Cu-based pesticide (conv_5) as indicated by the increased Bray-Curtis distance compared to the control group (PERMANOVA, *p* = 0.006) without influencing the dispersion (PERMDISP, *p* = 0.935) (Fig. 7A-D). Under this condition, the organism's associated microbiota exhibited a higher relative abundance of bacteria from the genus *Nevskia* as in males and decreased relative abundances of taxa from the genera *Methylophilus*, *Linnobacter*, *Taibaiella*, *Chitinimonas* and *Aeromonas* as suggested by LEFSe analysis while no effects were detected with the ANCOM framework (Fig. 7E, F; Figure S7). In addition, a significant negative correlation suggests that a lower host-microbiota diversity is associated to a later emergence of adult females (Fig. 7G). Considering the whole dataset from male and female emerged adults, the time to emergence is negatively correlated to the abundance of Firmicutes, indicating that adults emerging earlier harbor higher abundances of this phyla while the opposite is observed for Proteobacteria or minor phyla such as Myxococcota and Armatimonadota (Figure S8).

## 4. Discussion

The findings of this study provide new insights into the ecotoxic potential of commercial formulations of copper-based pesticides, particularly the impacts of conventional compared to nano-formulated products towards the midge *Chironomus riparius* from a holobiont perspective. The new generation of nano-pesticides used in agriculture are developed to improve their biocide efficiency *via* a better control of their release in the environment. To differentiate the nano-formulations from the conventional one, adequate characterizations of nanoparticles and their effects are essential and relevant due to the safety concerns attributed to the nano-properties. Our results demonstrated alterations in host life history traits in connection with impairments of the associated microbial community structure at environmentally relevant concentrations (50 µg Cu/L). Due to the closely-related biological effects observed between the two compounds and the increased copper accumulation in organisms exposed to the nano-formulation, our results do not support the use of copper-based nano-formulations as safer alternatives to conventional products for aquatic organisms.

Although chironomids are known for their tolerance of certain
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**Fig. 5.** Effects of an exposure to conventional (conv) or nano-formulated (nano) copper-based pesticide on *C. riparius* adult life history traits (A) Effects on survival considering fully emerged adults and surviving larvae after 24 days (B) Emergence dynamics over exposure duration (C) Overall emergence rate measured (D) Sex-ratio determined on fully emerged adults (E) Proportion of females emerged (F) Copper load detected in emerged adults following exposure to 50 µg Cu/L of conv or nano copper-based pesticide compared to adults from the control group. Data are presented as mean ± s.e.m. Statistical analysis was conducted using ANOVA, followed by post hoc Tukey test when p < 0.05. “*” indicates significant differences compared to the negative control (Ctrl) with *: p ≤ 0.05; **: p ≤ 0.01; ***: p ≤ 0.001; ****: p ≤ 0.0001.
<figure><img src="image_24.png" /><figcaption>**Fig. 6.** Response of commensal microbiota associated to emerged male chironomids after exposure to conventional (conv) or nano-formulated (nano) copper-based pesticide during aquatic life stage. (A-B) Observed microbial richness and Shannon alpha diversity indexes in adult microbiota. (C) Principal component analysis (PCoA) based on Bray-Curtis dissimilarities calculated from 16S rDNA sequencing. (D) Bray-Curtis distances calculated. (E) Stacked bar plot representation of bacterial relative abundance at phylum level. (F) Relative abundances of bacteria from the phylum Proteobacteria in the microbiota. (G) Bacterial taxa differentially enriched identified using LEfSe pipeline with LDA score > 3.0. Data are mean ± s.e.m. significance was determined using one-way ANOVA followed by post-hoc Tukey test for multiple comparisons. Bray-Curtis distances were compared using PERMANOVA; \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001.</figcaption></figure>
<figure><img src="image_25.png" /><figcaption>**Fig. 7.** Response of the commensal microbiota associated to emerged female chironomids after exposure to conventional (conv) or nano-formulated (nano) copper-based pesticides during aquatic life stage. (A-B) Observed microbial richness and Shannon alpha diversity indexes in adult microbiota. (C) Principal component analysis (PCoA) based on Bray-Curtis dissimilarities calculated from 16S rDNA sequencing. (D) Bray-Curtis distances calculated. (E) Stacked bar plot representation of bacterial relative abundance at the phylum level. (F) Bacterial taxa differentially enriched identified using LEfSe pipeline with LDA score > 3.0. (G) Correlations between observed microbial richness and time to emergence of female chironomids. Data are mean ± s.e.m. Significance was determined using one-way ANOVA followed by post-hoc Tukey test for multiple comparisons. Bray-Curtis distances were compared using PERMANOVA; \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001.</figcaption></figure>
environmental pollutants [55]. *C. riparius* has been shown to be more sensitive to copper exposure compared to other benthic invertebrate species following water exposure, while exhibiting a greater tolerance than species with higher bioturbation activity when exposed through sediment [56,57]. Since contamination in our study occurred through water exposure, organisms experienced a scenario resulting in more marked toxic effects. Interestingly, the presence of organisms in the test systems increased Cu concentration in the water column. This finding is in line with previous studies using other bioturbators such as tubificids, showing increased Cu release over the first week [58]. The presence of chironomid larvae promotes the release of dissolved organic matter (DOM) due bioturbation activities and biological processes. This influences the Cu behavior in the test systems, especially under the applied conditions using artificial sediment devoid of organic matter [59,60].

Depending on the biological model used, discrepancies are noted in the literature when comparing the toxic profiles of copper metal ions and nanoparticles of Cu (CuNPs) and the toxicity of commercial formulations is poorly evaluated. For example, similar toxicities were reported in the amphipod *Leptocheirus plumulosus* and the oligochaete *Enchytraeus crypticus* [61,62], while higher toxic effects occurred in zebrafish and the *Daphnia magna* [63,64]. Conversely, nano-formulation was indicated to be less toxic towards the terrestrial isopod *Porcellionides pruinosus* [65]. To our knowledge, the effects of commercial formulations of nano or non-nano Cu on the entire life cycle of chironomids have not been described. Similar toxic levels were measured in *Chironomus tentans* exposed through water to different copper salts (CuSO₄, CuNO₃ and CuCl₂), with LC₅₀-96h reaching ~18 mg/L [66]. However, sensitivity to metals, including Cu, may greatly vary between chironomid species, with LC50-96h previously measured ranging from 2.3 g/L of CuSO₄ for *Propsilocerus akamusii*, 7.42 mg/L for *Chironomus tentans* or 1.9 mg/L of CuCl₂ for *Tanypus complanatus* [66-68]. This sensitivity differences might be due to differential antioxidant protection capacities among species [69], as Cu was previously indicated to induce oxidative stress mediating genotoxic effects [70], which may contribute to impact larvae survival. Interestingly, the development stage at which exposure to metals begins influences the toxicity, first-stage larvae being the most sensitive [71,72]. In addition, the exposure duration also influence the toxicity as the LC₅₀-96h for *C. riparius* exposed at the second larval instar is within the range of 0.7 mg/L and decreases to 0.2 mg/L for LC₅₀-24₀h [73]. Thus, given that 100 % of mortality was reached prior 7 days of exposure to the test products at the concentration of 500 µg Cu/L under our experimental conditions, it is highly probable that other elements, including unknown proprietary ingredients composing the formulation, together with Cu, contribute to the overall product toxicity or modifying Cu toxicity in an unpredictable manner. Previous studies have described the presence of carbon, oxygen, sodium, aluminum, silicon, sulfur and Chlorine (C, O, Na, Al, Si, S and Cl respectively) in the formulation [74], that can induce toxicity or influence the toxicity of other elements [75]. Cu uptake in chironomids was previously indicated to induce a slight decrease of larval growth following exposure to Cu at 100 µg/L or over 100 mg/kg of sediment [76,77], which is consistent with the lack of larval growth inhibition detected in the current study following exposure to 50 µg Cu/L.

Copper from Cu(OH)₂-based nanopesticides is expected to generate a pool of dissolved Cu. Literature indicates that similar test products dissolve within hours under freshwater conditions, producing bioavailable dissolved Cu, while relative proportions of free Cu²⁺ and complexed species (e.g., hydroxo and carbonate complexes) remain condition-dependent [16,78,79]. Otherwise, remaining Cu nanoparticles can be dissolved post-ingestion within the digestive tract and entry as ionic Cu (e.g., Cu²⁺), contributing to organism's body burden rather than from epithelial translocation of particles, as previously observed with pure copper nanoparticles in the isopod *Porcellio scaber* [80]. Based on mechanistic evidence across invertebrates, intracellular handling of Cu is governed by metallothioneins, which rapidly form Cu(I)-thiolate clusters and drive sequestration within detoxification compartments

such as lysosomes in digestive tissues [81,82]. Previous studies demonstrated that chironomids larvae can accumulate substantial amounts of metals including Cu, but only small levels are recovered after metamorphosis in adults, suggesting excretory mechanisms lowering body burden through tissue remodelling during metamorphosis [83,84]. Thus, these data suggest that the adult Cu burden we measured is more likely to be interpreted as resulting from dissolved copper internalized during larval exposure, especially as pupal and adult stages are non-feeding and rely on energy reserves accumulated during the larval stage to complete their life-cycle [85]. However, the nano-formulation can either contribute in the increase of Cu bioavailability, enhancing larval assimilation, or to diminish Cu elimination during metamorphosis.

As the host-associated microbiota plays a role in food digestion and host metabolism, alteration of the microbial community structure is suggested to affect host development [86,87], which is in line with the obtained results. The chironomid microbiota has been shown to undergo dynamic changes during host development, likely due to the distinct habitats encountered and in response to modifications of feeding behaviors associated with different life-cycle stages [88,89]. Thereby, consistently with our observations, it is highly probable that early microbiota alteration disrupts normal microbial population dynamics, impairing host traits during development. We determined that exposure to 50 µg Cu/L significantly altered the microbiota composition of larvae, without significantly affecting alpha diversity, highlighting the sensitivity of certain bacterial taxa rather than causing a broad reduction in microbial diversity. These effects are in line with a previous study describing alterations of the larval gut microbiota in *Chironomus transvaalensis* exposed to Cu at concentrations up to several tens of mg/L from the 4th instar for 6 days. However, except mortality, no host related physiological endpoints are presented in this study, which do not allow to establish potential links between the impairment of commensal communities and alterations in host traits. Under our experimental conditions, the relative abundance of three taxa increased in the larval microbiota following exposure to the conventional product at 50 µg Cu/L. Interestingly, *Shinella* sp. Has been previously isolated from the gut microbiota of daphnids [90], and has been shown to degrade the fungicides chlorothalonil and pyridine, both of which are used for the production of agrochemicals [91-93]. In addition, bacteria from the taxa *Brevundimonas* have been described as efficient for copper removal in soils [94], while the growth of *Bdellovibrio* sp. is stimulated by Cu at concentrations up to 1 mg/L [95]. These results suggest that exposure to the conventional product induces a more marked shift in the gut microbiota toward a profile enhancing copper tolerance compared to the microbiota of organisms exposed to the nano-formulation. This adaptive response is likely improves host protection by decreasing susceptibility to Cu stress and allowing further larval development until the adult stage [96]. Differential effects of CuNPs compared to their metal counterparts were previously indicated to differentially affect microbial communities from different environments, including soil microbiota [97,98], the gut microbiota of collembolans living in contaminated soils [99], or isolated culture of *Escherichia coli* [100]. Microbial alterations are often associated with broader ecological consequences, including impaired ecosystem functioning and/or host homeostasis for commensal communities. However, deciphering the nanoparticle-specific pathways involved in toxic responses of complex microbial communities is remaining challenging while of importance for the ecological risks assessment of metal-based nanomaterials.

The whole life-cycle approach applied in this study revealed substantial effects that would have been failed to observe in short-term toxicity assays. Since host-associated microbiota assemblages have been shown to influence mosquito emergence rate [101,102], the reduced adult emergence observed in our experiment may be attributed to indirect effects mediated by the microbiota alteration due to the copper bactericidal properties. Reduced adult emergence following exposure to both Cu formulations at 50 µg Cu/L indicates that copper contamination may
impair population dynamics and lead to population declines over multiple generations. This effect has been observed in *Daphnia* sp., where chronic exposure to copper at sub-lethal concentrations was shown to induce population extirpation due to genetic erosion [103], delayed maturity [104], while promoting epigenetic transgenerational inheritance through DNA methylation of genes involved in counteracting Cu effects [105].

Current regulatory frameworks for pesticide risk assessment predominantly focus on direct toxicity in organisms and accumulation in environmental matrices but often neglect the potential for trophic transfer associated following bioaccumulation. For example, chronomids may act as vectors in exporting environmental pollutants from aquatic to terrestrial ecosystems due to their life cycle. They were shown to accumulate contaminants such as heavy metals, pesticides, and organic pollutants, from contaminated sediment or surrounding water bodies during the larval stages [106]. These contaminants may persist in their tissues over metamorphosis until the adult stage [107], allowing them to be transported into terrestrial food webs, as midges are prey for insectivorous birds, bats, spiders, and other terrestrial predators [108]. As exposure to copper-based nano-formulations led to significant higher retention levels of Cu in adults compared to conventional formulations, a decreased emergence would increase predation pressure on adults with higher Cu content, contributing to increase biomagnification of Cu across ecosystem boundaries. This could have deleterious implications for the wildlife health, particularly for insectivorous species that rely on chironomids as a primary food source.

To conclude, our findings highlight the need of a more holistic approach in ecotoxicology through the integration of a holobiont perspective. Analyzing the effects of contaminants on organism the entire life-cycle of organisms could enhance predictions of environmental consequences. This study demonstrates that nano-formulated Cu pesticides are not necessarily less toxic compared to the conventional formulations, and may pose a higher risk of bioaccumulation, warranting further investigations. While previous studies have highlighted the environmental risks associated with copper use in agriculture [2], the collected data show closely-related effects among the tested formulations. Given the growing interest in nano-formulations as "eco-friendly" alternatives, our results caution against assuming reduced toxicity based only on acute mortality endpoints.

## Environmental Implication

This study underscores critical concerns regarding ecological risks to freshwater ecosystems of copper-based nano-formulations. Despite constituting potential alternative to reduce copper use in agriculture, we demonstrate using *Chironomus riparius* as a holobiont model that environmentally relevant concentrations of nano-formulated copper pesticides induced comparable toxicity and even greater bioaccumulation than conventional counterparts. These findings suggest a higher risk of copper transfer through aquatic-terrestrial food webs, potentially impacting biodiversity and ecosystem health. This work emphasizes the need for holistic ecotoxicological assessments, integrating microbiome impacts to guide sustainable agricultural practices and inform regulatory frameworks for emerging nanotechnologies.

## CRediT authorship contribution statement

**Gaël Le Roux:** Validation, Formal analysis. **Florence Mouchet:** Writing – review & editing, Supervision, Funding acquisition. **Frédéric Candaudap:** Methodology, Formal analysis. **Marion Vivant:** Formal analysis, Data curation. **Lauris Evariste:** Writing – original draft, Visualization, Investigation, Formal analysis, Conceptualization. **Eric Houdeau:** Resources, Funding acquisition. **Florian Chapeau:** Investigation, Formal analysis. **Bruno Lamas:** Resources, Project administration, Funding acquisition. **Laurence Chevalier:** Validation, Methodology, Formal analysis, Data curation. **Eric Pinelli:** Supervision,

**Funding acquisition.** **Maialen Barret:** Resources, Methodology. **Thomas Moura:** Investigation, Formal analysis. **Camille Larue:** Funding acquisition. **Laury Gauthier:** Supervision, Funding acquisition. **Van-Xuan Nguyen:** Formal analysis, Data curation. **Eva Casale:** Funding acquisition.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgment

This action is led by the Ministries for Agriculture, Food Sovereignty and Forestry, for ecological Transition, Energy, Climate and Risk Prevention, for Health and Access to Care, and of Higher Education and Research, with the financial support of the French Office for Biodiversity, as part of the call for research projects "Plant protection products: from exposure to impacts on human health and ecosystems towards an integrated "one health" approach", with the fees for diffuse pollution coming from the Ecophyto II+ plan (grant number: OFB-22-1496). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees and Sigenees group for providing help and/or computing and/or storage resources thanks to Galaxy instance https://vm-galaxy-prod.toulouse.inra.fr. We thank Miguel Figueroa and Solène Duperray (CRBE) for their assistance with sample preparation in the CRBE clean lab, and the ICP-MS facility at OMP, particularly Camille Duquenoy (GET Toulouse).

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.jhazmat.2025.140294.

## Data availability

Data will be made available on request.

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