Water-extractable organic matter from tropical soils and biochar amendment tailors the colloidal behavior of nanoparticles and mitigates their toxicity through molecular eco-corona formation

Abstract

Understanding the interactions between nanoparticles and organic matter is crucial for environmental nanoscience and agricultural innovation, whether from intentional applications (fertilizers and agrochemicals) or unintentional release through widespread commercial use in many products. Molecular eco-corona formation on nanoparticle surfaces is a key element governing nano-bio interactions. Here, we investigated how water-extractable organic matter (WEOM) from tropical soils (i.e., oxisol and Amazonian dark earth) and biochar-amended oxisol affects eco-corona formation on copper oxide nanoparticles (CuONP) and how this impacts their colloidal stability and modulates their toxicity in a zebrafish model. Fluorescence spectroscopy, cryogenic electron transmission microscopy and ultrahigh-resolution mass spectrometry showed that the molecular structure and functionality of carbon compounds from WEOM are the main drivers of eco-corona rather than carbon content. Small, highly functionalized conjugated aromatic compounds exhibited the highest potential to form a strong eco-corona, which was positively correlated with nanoparticle stability. The interaction between CuONP and WEOM from Amazonian soil effectively inhibited nanoparticle aggregation at higher ionic strengths, thereby avoiding agglomeration and resulting in no significant impact on the embryo hatching rate. A correlative microscopy approach enabled the identification of different deposition patterns of nanoparticle association with the chorion membrane of zebrafish embryos. The mitigation of CuONP toxicity by strong eco-corona highlights the decisive role of the organic matter source and carbon chemistry in modulating nano-bio interactions and eco-corona composition, with implications for biological membrane attachment (i.e., chorion binding) linked to toxicological effects (i.e., embryotoxicity). These findings carry significant implications for risk assessment, safety, and the regulation of nanoparticles in tropical environments.

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Environmental significance

Study emphasizes the importance of molecular eco-corona characterization by directly linking corona-induced changes in nanoparticle bioavailability, colloidal stability and toxicity mitigation in zebrafish embryos. The use of highly distinctive soils from tropical environments, underscoring Amazonian dark earth soils from the Amazon basin, together with biochar amendments, reveals an unexplored pathway governing nanoparticle transformation through eco-corona formation. The insights gained from this study provide well-defined strategies for the safe and sustainable application of nanoparticles in tropical systems connected with global nano-environmental challenges.

1 Introduction

Nanoparticles (NP) have been increasingly used in agriculture, especially as fertilizers and pesticides,^1–5 raising questions about their environmental behavior and fate. Copper oxide nanoparticles (CuONP) have been incorporated into agrochemical formulations, such as nanofertilizers and nanopesticides, because of copper's antifungal properties and its role as an essential micronutrient required for plant development.^6–8 Once applied to soils, such nanoparticles encounter a complex mixture of natural organic molecules, primarily from the dissolved organic fraction, which is considered the most reactive component. These biomolecules rapidly adsorb onto the NP surface, forming “eco-corona”, a dynamic, environmentally derived molecular layer that shapes nanoparticle identity, behavior, and toxicity.^9,10 This adsorbed layer on the nanomaterial surface is a multi-layered structure composed of different layers of biomolecules, termed hard and soft corona, based on their interaction with the nanoparticle and the forces attaching them to it.^11–13 The hard corona consists of biomolecules that interact directly with the nanomaterial surface (nanoparticle–molecule interaction), while the soft corona generally comprises molecules that interact with the hard corona (molecule–molecule interaction).^12,14 The complexity of environmental matrices (e.g., soils and headwater streams) significantly expands the diversity of biomolecules derived from various carbon pools, including dissolved organic matter, humic substances, and other constituents of natural organic matter (NOM), which are available for corona formation, thereby rendering eco-corona characterization particularly challenging.^14,15 By contrast, protein corona is a well-established concept referring to the adsorption of proteins onto the surface of nanomaterials in biological systems (e.g., plasma and serum), explored especially in the field of nanomedicine as a potential tool for disease diagnosis and prognosis.^16–18 Despite the abundance of data on nanoparticle–protein interactions, it remains uncertain whether these insights translate to the more complex and heterogeneous conditions found in environmental matrices.

Exploring soil environments broadens the range of biomolecules capable of binding to nanoparticle surfaces to form eco-corona. Eco-corona formation is known to depend on both the intrinsic properties of the nanomaterial and the composition of the surrounding medium. Notably, selective nanoparticle interactions with NOM have been reported, for example, in studies involving AgNPs and PtNMs.^19,20 Sulfur-containing groups dominated the AgNP corona,¹⁹ while high-molecular-weight, heteroatom-rich compounds were predominant in the PtNM corona.²⁰ NOM has been used as a model to study eco-corona formation,^19,21–23 evaluating nanoparticle aggregation,²⁴ mobility,²⁵ and toxicity.²² A comparison between fulvic and humic acids isolated from NOM revealed that fulvic-like substances more effectively inhibit nanoparticle aggregation, thereby enhancing dispersion.²⁶ The affinity of NP for specific NOM compounds can also increase their colloidal stability and reduce their dissolution rates.²⁷ However, most investigations on NP–NOM interactions overlook the eco-corona effect when evaluating aspects such as colloidal stability,^28–30 focusing primarily on the organic matter content in the medium and emphasizing the relevance of the NOM composition^31,32 and environmental conditions³³ in governing nanoparticle behavior and dissolution.

Much of our current understanding of how corona formation influences nanoparticle behavior, including stability and toxicity, is based on studies on protein-rich media,^34,35 whereas complex organic systems like soils remain underexplored. A few studies have attempted to simulate soil media using standard mud,³⁶ the soil metabolome,³⁷ or extracellular polymeric substances extracted from soil.³⁸ However, these models neglect the molecular heterogeneity of soil organic matter across regions and climate conditions^39,40 especially in tropical soils, such as those in the Amazon. Given the medium-dependent nature of nanoparticle–biomolecule interactions, what can be expected in highly heterogeneous environments like soils? While oxisol generally exhibits low fertility levels and low-quality organic matter, Amazonian dark earth (ADE) soils show high fertility levels and contain high-quality organic matter. Even fewer studies have examined how agricultural amendments, such as biochar, alter soil organic matter composition and, in turn, influence nanoparticle interactions.^41–47 The use of biochar as a soil amendment to improve soil quality has gained popularity in agriculture, partly inspired by the hypothesis that ADE, the highly fertile anthropogenic soil found in localized areas along the Amazon basin, resulted from the historical application of nutrient-rich biomass pyrolysis products.⁴⁸ Therefore, by comparing the effects of organic matter from ADE on eco-corona formation with those of organic matter from biochar-amended oxisol, it will be possible to infer the extent to which biochar can reshape soil dissolved organic matter toward conditions associated with higher fertility.

Biochar, increasingly used to enhance soil fertility and carbon storage,^49–51 can substantially modify soil organic matter (SOM) chemistry by introducing labile and recalcitrant carbon forms, some of which are highly soluble and readily available in soil solutions.^52,53 A number of key questions are addressed in this work, including: (1) whether evaluating bulk biochar provides sufficient insights to enable assessment and an understanding of its potential contributions to soil quality based on soil application. (2) Due to its high adsorption capacity, biochar can modify SOM composition through the release of aromatic compounds and the adsorption of small molecules,^43,54 but can these changes impact eco-corona formation in the short-term? WEOM, obtained via water extraction, represents the most dynamic and bioavailable component of SOM. SOM includes a diverse pool of organic molecules with varying sizes and chemical compositions, typically characterized by smaller molecular size and greater lability compared to humic acids.^55–57 Cold- and hot-water extraction approaches are commonly used to compare distinct scenarios of lability and biodegradability of soil organic carbon and amplify the diversity of extracted organic molecules.^55–57 Each approach targets distinct fractions of SOM that differ in availability, stability and origin.^58,59 Cold extraction is primarily associated with more soluble and labile compounds, including recently produced plant-derived and microbially derived metabolites, as well as organic matter weakly associated with soil particles.^58–60 In contrast, hot extraction enhances the extraction of mineral-associated organic matter and provides access to a pool of potentially mobilizable carbon reserves.^59–61 (3) The combined effects of tropical SOM composition and biochar amendments on nanoparticle transformation remain largely unexplored. Considering this, how does the molecular composition of SOM determine the nature of the eco-corona? (4) Are the molecular compositions of SOM significantly different among soils such that they form distinct eco-coronas on nanoparticles, impacting NP stability? If so, is eco-corona formation primarily influenced by the abundance of specific compounds or by the affinity of the compounds for the NP surface?

This work represents a step-change in knowledge and understanding by systematically evaluating how the organic composition of WEOM from tropical soils, with or without biochar amendments, modulates the composition of eco-corona on CuONP, which in turn affects their colloidal stability. However, despite the complexity of environmental matrices, there is also a critical gap in understanding how soil organic compounds drive eco-corona development and thereby affect nanoparticle fate and ecotoxicity. Accordingly, the fish embryo toxicity test (FET) utilizing Danio rerio (zebrafish) is a powerful model to assess nanoparticle toxicity, correlating it with the eco-corona composition and ensuring that the resulting changes in nanoparticle stability, aggregation and consequent bioavailability are effectively considered. This approach directly links eco-corona-induced changes in nanoparticle bioavailability and colloidal stability to toxicity, bridging critical gaps between environmental chemistry and ecotoxicology. By focusing on tropical soils, this study aims to make a significant, novel contribution to environmental nanoscience by revealing how SOM influences nanomaterial behavior through eco-corona formation in a tropical environment for the first time. The insights gained from this study provide well-defined strategies for the safe and sustainable application of nanomaterials in soil, supporting the development of safer and more effective nanomaterials tailored for agricultural and environmental use. More importantly, it underscores the relevance of synergic efforts across interdisciplinary fields, such as soil science and nanotechnology, providing meaningful insights that bridge knowledge domains and advance the development of nano-enabled agriculture.⁶² Ultimately, this work deepens our understanding of the environmental identity and impact of engineered nanomaterials in tropical soil systems, offering valuable guidance for environmental chemistry, ecotoxicology, and risk assessment, essential to advancing nano-bio-ecological science and technology.

2 Materials and methods

2.1 Tropical soils and biochar

Two tropical soil types were selected for this study: an oxisol sample (S 22°48.277′ W 47°03.178′), collected in Campinas, São Paulo state, Brazil, and an Amazonian dark earth sample (S 3°15′10.03″ W 60°13′42.10″), obtained from the Caldeirão experimental site in Iranduba, Amazonas state, Brazil, within the Amazonian basin (authorization for collection registered with the National System for the Management of Genetic Heritage and Associated Traditional Knowledge – SISGen, No. AD13FB3).

Biochar was obtained from sugarcane bagasse and produced by Bioware (Campinas, Brazil). For the amendment studies, the biochar was mixed with oxisol at an application rate of 0.5% (w/w). The resulting oxisol–biochar system was incubated for 6 months in an acclimated room under controlled temperature and humidity conditions (28 ± 2 °C, 60% of water field capacity).

The physicochemical properties of the biochar were characterized using multiple analytical techniques: Fourier transform infrared spectroscopy (FTIR) (Cary 600 Series, Agilent Technologies), Raman spectroscopy (Confocal XploRA Plus, Horiba), and X-ray photoelectron spectroscopy (XPS) (K-Alpha XPS, Thermo Scientific). The biochar ash content was determined by thermogravimetric analysis (TGA) (STA 449 F3, Netzsch), and the crystalline structure was evaluated by X-ray diffraction (XRD) (D8 Advance ECO, Bruker). The characterization results are shown in Fig. S1.

For all soil samples, i.e., oxisol, oxisol–biochar system, and ADE, the ash content was determined by TGA using the same protocol applied to the biochar alone, and the results are presented in Fig. S2.

Further methodological details, including instrument settings and analytical conditions, are available in the SI (sections 1 and 2).

2.2 Copper oxide nanoparticles

Copper oxide nanoparticles (CuONP, ∼7 nm) were synthesized according to the protocol described by Zhang et al.,⁶³ using CuCl₂·2H₂O as the precursor. Briefly, 0.51 g of CuCl₂·2H₂O was dissolved in 150 mL of ultrapure water at room temperature, followed by the addition of 500 μL of CH₃COOH. The mixture was heated to 100 °C, after which 0.6 g of NaOH was added. The reaction mixture was maintained at 100 °C for 10 min and then allowed to cool to room temperature. The resulting suspension was transferred into centrifuge tubes and centrifuged at 14 000 rpm for 10 min at 4 °C. The precipitated nanoparticles were washed with ultrapure water, resuspended and centrifuged; the washing step was repeated four times.

The surface elemental composition of the nanoparticles was analyzed by XPS, applying Al Kα X-rays. Survey spectra were collected with a spatial resolution of 400 μm and pass energies of 50.0 eV, and the high-resolution spectra for Cu 2p were measured. Data analysis was performed using Thermo Avantage software (version 5.957, ThermoFisher). The crystalline structure was assessed by XRD with CuKα radiation (λ = 15 406 Å) in the range of 10–90° (2θ) with steps of 0.04° and an accumulation time of 0.6 s per step. Transmission electron microscopy (TEM) images were obtained using a microscope (JEM 2100F, JEOL) operated at 200 kV in the bright field mode. Before imaging, the nanoparticle suspension was sonicated for 15 min, dropped onto a copper grid coated with an ultrathin holey carbon film (400 mesh), and allowed to dry at room temperature. The hydrodynamic diameter distribution and zeta (ζ) potential of the CuONP in an aqueous suspension were determined using a zeta potential analyzer (Zetasizer Ultra, Malvern). The results of all these analyses are presented in Fig. S3.

2.3 Water-extractable organic matter extraction and characterization

Water-extractable organic matter was used as a proxy for soil dissolved organic matter (DOM), and it was extracted from four sources: oxisol (S), biochar (B), oxisol–biochar system (SB), and ADE, using a standardized water-extraction protocol involving hot- and cold-water treatments. A solid-to-liquid ratio of 1 : 5 (w/v) was used, with extractions conducted at 100 °C for 1 h (hot-water extraction) or 23 °C for 24 h (cold-water extraction). The resulting suspensions were centrifuged at 7000 rpm for 10 min at 20 °C. The supernatants were vacuum filtered using a qualitative filter paper, followed by filtration through 0.45 μm (PVDF, hydrophilic, Durapore®) and 0.22 μm (PVDF, hydrophilic, Durapore®) membrane filters.⁵⁶ The extracts were labeled based on their source extraction conditions (e.g., SBH denotes the hot-water extract from the oxisol–biochar system).

Dissolved organic carbon (DOC) concentrations were quantified using a total organic carbon analyzer (TOC-VCSN, Shimadzu). Ultraviolet-visible (UV-vis) specific absorbances were recorded (Multiskan GO spectrophotometer, Thermo Scientific) to calculate the E₂/E₄ and E₄/E₆ ratios and determine the specific ultraviolet absorbance at 254 nm (SUVA₂₅₄). Fluorescence characteristics were assessed by fluorescence spectroscopy operated in the excitation–emission matrix (EEM) mode (Cary Eclipse spectrofluorometer, Varian) with emission and excitation wavelengths in the ranges of 240–700 and 220–510 nm, respectively. The instrument settings included fixed slit widths of 10 nm, a scan speed of 1200 nm min⁻¹, and a detector voltage set to 700 V. The results are presented in Fig. S5 and S6. Liquid-state ¹H nuclear magnetic resonance (NMR) spectra were acquired using a 400 MHz Bruker AVANCE III (Bruker) equipped with a 5 mm broad-band inverse probe. Additional details on sample preparation, acquisition parameters, and spectral integration procedures are provided in the SI (section 4). High-resolution mass spectra of WEOM samples were acquired using a 10T Bruker Daltonics Apex Qe FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization (ESI) source. Samples were injected at 120 μL h⁻¹ and analyzed in the negative-ion mode (ESI). External calibration was performed using polyethylene glycol,⁶⁴ while Suwannee River fulvic acid was used to validate instrument tuning.⁶⁵ Detailed information on instrumentation, blank subtraction, data acquisition, and processing is available in the SI (section 4). Molecular formulas were categorized based on i) heteroatom composition, including CHO, CHON, CHOS, and CHOP groups, and ii) the likely compound classes they could represent, such as condensed aromatic compounds (ConAC; AI_mod ≥ 0.67), lignin-like compounds (AI_mod < 0.67; H/C < 1.5; 0.1 > O/C < 0.67), tannin-like compounds (H/C < 1.5; O/C ≥ 0.67; AI_mod < 0.67), sulfonic acid-like compounds (H/C ≥ 2.0 O/C < 0.67; S > 0), sugar-like compounds (H/C ≥ 1.5; O/C ≥ 0.55; N > 0), protein-like compounds (H/C ≥ 1.5; O/C < 0.55; N > 0), lipid-like compounds (H/C ≥ 1.5; O/C < 0.67; N = 0), and unsaturated compounds (H/C < 1.5; 0 > AI_mod < 0.67; O/C < 0.1).^66,67 Molecular compositions were visualized using van Krevelen diagrams.⁶⁸

2.4 Eco-corona studies

2.4.1 Fluorescence quenching: assessing eco-corona formation from CuONP and WEOM interactions. The interaction between CuONP and WEOM was assessed using fluorescence quenching assays. WEOM solutions were prepared at a concentration of 5 mg_C L⁻¹ in a buffered solution (pH = 7.0). The concentration of WEOM was fixed based on the carbon concentration of the water extracts and applied to all the samples to ensure that differences in both nanoparticle interaction and quenching effects were mainly due to the distinct carbon structure of the biomolecules in the samples. Titration experiments were performed by incrementally adding CuONP at concentrations ranging from 0 to 20 mg L⁻¹. An equilibrium time of 30 minutes was established based on the stabilization of the fluorescence signal. EEM-fluorescence spectra were acquired as described before. The EEM datasets were analyzed using PARAllel FACtor analysis (PARAFAC) implemented in the PROGMEEF software developed in MATLAB.⁶⁹ Before modeling, the spectra were corrected for diffusion signals by removing Rayleigh scattering within a 15 nm band and applying the Zeep method to eliminate first- and second-order Raman scattering.^70,71 The optimal number of components was determined using the core consistency diagnostic (CORCONDIA), with the best model defined as the model yielding the highest number of components while maintaining a CORCONDIA value above 60%.⁷⁰ The excitation and emission loadings of the PARAFAC components were subsequently compared against reference spectra in the OpenFluor database, considering a Tucker congruence exceeding 0.95 on the excitation and emission spectra simultaneously.⁷² To avoid misassignments in component separation, the samples were grouped into two categories: i) soil-derived WEOM (i.e., oxisol, oxisol–biochar system, and ADE), and ii) biochar-derived WEOM (Fig. S5). The complexation between WEOM and CuONP was modeled using the 1 : 1 equilibrium binding model developed by Ryan and Weber,⁷³ allowing for the estimation of the conditional stability constant (K) and total ligand site concentration (CL). Furthermore, the complexation capacity (CC) was expressed as the ratio of CL to DOC in the extract.⁷⁴ Methodological details are provided in the SI (section 5).

2.4.2 Eco-corona characterization. To induce eco-corona formation, CuONP (100 mg L⁻¹) was incubated with WEOM solutions under continuous stirring on a vertical rotating mixer (AP-22, Phoenix Luferco) for 24 h at 23 °C to ensure that the interaction equilibrium was achieved. After incubation, the mixture was centrifuged (5810 R, Eppendorf) at 10 000 rpm for 1 h at 4 °C, followed by three washing steps with ultrapure water (UPW) (centrifugation at 10 000 rpm for 30 min at 4 °C) to remove poorly bound and unbound biomolecules. The final pellet, representing CuONP with strongly bound biomolecules (i.e., hard corona), was transferred to a silicon substrate and air-dried for surface analysis. High-resolution XPS (C 1s) and FTIR were used to analyze the elemental and functional group composition. The instrument settings are detailed in the SI (section 5).

The CC value, obtained by fluorescence quenching from the interaction between CuONP and WEOMs, served as a reference for investigating the eco-corona structure in the hydrated state by cryogenic transmission electron microscopy (cryo-TEM). Since the highest values of CC were obtained from the hot-water extraction of WEOM, these samples were evaluated first. Based on eco-corona identification, the corresponding cold-water extraction sample was subsequently analyzed. Thus, the CuONP pellet was resuspended in 100 μL of UPW and dropped onto a lacey carbon-coated copper grid, previously subjected to a glow discharge treatment (PELCO easiGlow™ discharge system, Ted Pella), using a controlled environment vitrification system (VitrobotMark IV, Thermo Fischer Scientific). Cryo-TEM was performed using a transmission electron microscope (JEM 1400 Plus, JEOL), operating at 120 kV under low-dose conditions (15 e⁻ Å⁻²). The images were acquired with a 4k × 4k CMOS OneView (Gatan) camera.

2.4.3 Impact of WEOM on CuONP colloidal stability and aggregation kinetics. Nanoparticle stability was evaluated at 100 mg L⁻¹ CuONP, with and without WEOM (5 mg_C L⁻¹), by measuring absorbance changes at 396 nm over 0 to 96 h (Multiskan GO spectrophotometer, Thermo Scientific), as shown in Fig. S15. The CuONP aggregation kinetics were assessed via dynamic light scattering (DLS; Zetasizer Ultra, Malvern). The increase in the nanoparticle hydrodynamic diameter (D_h) was monitored by DLS to 1.2–3.0 times the initial D_h, using NaCl as a destabilization electrolyte. The CuONP suspensions (100 mg L⁻¹) were prepared from a stock (1 g L⁻¹) by adding a NaCl aqueous solution to reach the desired concentration (0–1000 mM), sonicated for 1 min, and transferred to a cuvette (model DTS0012) and analyzed.^75,76 The D_h was recorded for 30 min (a total of 60 measurements, one every 30 seconds over 30 minutes).

The aggregation behavior of CuONP in the different WEOM environments was evaluated by comparing the different extracts at the same carbon concentration (5 mg_C L⁻¹). Briefly, CuONP suspensions (100 mg L⁻¹) were added to WEOM (5 mg_C L⁻¹), followed by the addition of a NaCl aqueous solution to achieve the desired ionic strength (0–1000 mM).^76–78 The mixture was sonicated for 1 min and transferred to a cuvette, and the increase in D_h was recorded as previously described. The aggregation attachment efficiency (α) was calculated for CuONP in UPW at each NaCl concentration, as well as in the presence of WEOM solutions (5 mg_C L⁻¹). The critical coagulation concentration in NaCl (CCC_NaCl) was calculated by extrapolating the linear regressions corresponding to the reaction-limited aggregation (RLA) and diffusion-limited aggregation (DLA) regimes in logarithmic plots of α versus NaCl concentrations.^76,79,80 Detailed information on the method is provided in the SI (section 6). The zeta potential of the WEOM solutions (5 mg_C L⁻¹), both alone and after interaction with CuONP (100 mg L⁻¹), was measured (cuvette model DTS1070) (Zetasizer Ultra, Malvern).

2.5 Ecotoxicity

2.5.1 Toxicity assessment using zebrafish (Danio rerio) embryos. Toxicity assessment was conducted using zebrafish (Danio rerio) embryos following the fish embryo toxicity (FET) assay by OECD Guideline 236.⁸¹ The embryos were sourced from the Nanotoxicology and Nanosafety Facility at LNNano/CNPEM. All procedures involving the animals were conducted under a protocol approved by the CNPEM Ethics Committee (protocol number #110), ensuring compliance with institutional and international standards for the care and use of laboratory animals. Wild-type zebrafish (AB strain) were maintained in accordance with established animal welfare guidelines. The zebrafish eggs were collected 1 hour after the natural mating of adult fish, using a ratio of two females to one male. Following collection, the eggs were washed with reconstituted water (96 mg L⁻¹ NaHCO₃, 60 mg L⁻¹ MgSO₄, 4 mg L⁻¹ KCl, and 60 mg L⁻¹ CaSO₄, pH = 7.5 ± 0.5) and selected for viability. Embryos were considered non-viable if they exhibited developmental delays, malformations, or signs of mortality (e.g., coagulated eggs). Embryos were exposed to CuONP (0–10 μg L⁻¹) 4 hours post-fertilization (hpf) in reconstituted water with and without WEOM (5 mg_C L⁻¹). To ensure that the observed toxicity effects were not caused by the WEOM, a control group was exposed to 5 mg_C L⁻¹ of the extracts alone. Additionally, a negative control using only reconstituted water was included. The assays were performed in triplicate and in 24-well plates, with 2 mL of the test solution and one embryo per well, totaling 20 embryos per treatment. The tests were maintained under controlled temperature conditions (28 °C) and a photoperiod of 14 hours light and 10 hours dark. The test lasted 96 hours, during which embryo mortality, hatching rate, malformations, and edema were recorded daily using a stereomicroscope (Stereo Discovery V20, Zeiss). At 48 hpf, the embryos were photographed, and the larvae were photographed and measured for total length at the end of the assay.

The statistical analysis of the data was performed using OriginPro 2022b (OriginLab Corporation). The Kolmogorov–Smirnov test was used to assess data normality. When the data met the assumption of normality, a two-way ANOVA, followed by Tukey's post hoc test, was conducted. Differences were considered statistically significant at p < 0.05. The EC₅₀ values were calculated using Origin software by applying a sigmoidal nonlinear regression curve fitting model.

2.5.2 Evaluation of nano-bio interactions using a correlative microscopy approach. To study the interactions between eco-corona-coated nanoparticles and the chorion membrane of the zebrafish embryos, a correlative microscopy approach was explored. First, hyperspectral imaging was used to analyze the interaction between the chorion membrane and CuONP (CytoViva microscopy, CytoViva, Inc.). Images were acquired with a visible and near-infrared (VNIR) hyperspectral camera at 100× magnification (Olympus, Model BX53). A spectral library of CuONP was first generated using the same system. Subsequently, images of the chorion membrane were captured and analyzed. Using the CuONP spectral library, hyperspectral mapping was conducted to confirm the presence and interaction of nanoparticles with the chorion membrane. Second, to investigate the interaction at a higher resolution and assess the potential association of nanoparticles with the chorion pores, scanning electron microscopy (SEM) was employed. The embryos were exposed to the nanomaterials for 24 hours and then fixed in 4% paraformaldehyde. The samples were dehydrated using a graded ethanol series (30% to 100%, 15 minutes per step, with three washing steps at 100%) and subjected to critical point drying. SEM images were acquired using a Quanta 650 FEG (ThermoFisher Scientific) microscope at a voltage of 5 kV. Third, to analyze the amount of CuONP adhered to the chorion, synchrotron X-ray fluorescence mapping (SR-XFM) was performed at the CARNAÚBA (Coherent X-ray NAnoprobe Beamline)⁸² of the Sirius 4th-generation synchrotron radiation source at the LNLS (Sirius-LNLS). The analyses were conducted at the Tarumã endstation using a highly focused X-ray beam (i.e., ∼300 nm × 500 nm) with a Kirkpatrick–Baez (KB) mirror system. The energy of the incoming beam was set above the absorption K-edge energy of copper (E_in = 9.0 keV). The samples were placed on standard holders, and the X-ray fluorescence and scattered radiations coming from the samples were recorded using two four-element silicon drift detectors (SDD, Vortex-ME-4, Hitachi High-Tech America, USA) placed on opposite sides of the sample surface. The resulting data were primarily processed using the imaging tools available in the PyMca software package (version 5.9.2), which is specifically designed at the European Synchrotron Radiation Facility (ESRF) for XRF data analysis.⁸³

3 Results and discussion

3.1 Eco-corona evaluation and characterization

Fluorescence quenching is an effective approach for evaluating molecular eco-corona formation on CuONPs by revealing WEOM interactions with nanoparticle surfaces. As fluorescent WEOM components bind to CuONP, their emission intensity decreases because of energy transfer or nonradiative decay.^84–87 Analyzing the extent and pattern of this quenching enables the assessment of binding affinities, interaction mechanisms, and the relative contributions of specific DOM fractions to eco-corona formation. Parallel Factor analysis (PARAFAC) identified three main components within the soil-derived WEOM, while a fourth, likely noise-related, showed no variation during quenching and was excluded from the discussion.⁸⁸ Components C1, C2, and C3 match 125, 105, and 77 PARAFAC models from the OpenFluor database, respectively. Components C1 [λ_Ex 275(330)/λ_Em 475] and C2 [λ_Ex 250(325)/λ_Em 425] corresponds to humic-like substances (Fig. S7). The blueshift of C2 compared to C1, towards lower wavelengths, indicates simpler, less aromatic, lower-molecular-weight compounds, while C1 reflects more complex, highly aromatic structures.^89–92 Component C3 [λ_Ex 290/λ_Em 350] represents protein-like substances showing the presence of labile organic matter.^93,94 This range of components highlights the chemical diversity of soil WEOM and suggests that CuONP may interact differently with complex, aromatic, simpler aliphatic, and protein-like molecules, which could affect CuONP behavior and stability in soils. These interactions can be further evaluated by examining the contribution of each component across samples and CuONP concentrations.

The fluorescence intensity decreased with increasing CuONP concentrations (titration plots in Fig. 1), although the extent of quenching varied across samples. Eco-corona composition will be a combination of the characteristics of the compounds in WEOM, associated with the complexation capacity (CC) of each identified component, i.e., the quantity of available sites for complexation able to interact with nanoparticles and the strength of this interaction (log K) obtained from titration experiments (Table 1). A comparison among the equilibrium parameters of each WEOM guides the understanding of how compositional differences lead to CuONP eco-corona formation. The 1 : 1 Ryan–Weber model fitted well for the WEOM samples, and the variations between the theoretical and experimental values (bias) ranged from 0.06 to 5.81 (Table 1). A higher log K indicates stronger binding, meaning that the WEOM component forms a more stable complex with the nanoparticle. Although the oxisol soil samples (i.e., SC and SH) showed higher log K values for the C1 and C2 components than the ADE, the low CC values indicate a low amount of available sites in WEOM to interact with nanoparticles. The addition of biochar to the oxisol soil (i.e., SBC and SBH) enhanced the CC value of both the C1 and C2 components, making them comparable to the ADE WEOM samples. This indicates that, even in the short-term application, biochar-derived organic matter was incorporated into the soil as humic-like compounds, altering the WEOM profile and increasing the availability of binding sites for the formation of stable NP–eco-corona complexes. Nevertheless, this enhancement was not observed for the C3 (protein-like) component, consistent with the absence of protein-like signals in the PARAFAC results for biochar WEOM (Fig. S7b). Interestingly, the increase in the extraction temperature enhanced the complexation capacity (CC) and lowered the log K of the soil samples (i.e., SH compared to SC, SBH compared to SBC, and ADEH compared to ADEC), while for biochar, the log K increased. This indicates that hot extraction probably did not enhance the release of organic compounds with higher affinity for CuONP.

Fig. 1 Fluorescence quenching of components C1, C2, and C3 obtained by the PARAFAC of quenching results (titration at a pH of 7.0) from the interaction of soil and biochar WEOM from cold- (samples SC, SBC, ADEC and BC) and hot-water (samples SH, SBH, ADEH and BH) extractions with CuONP. In the titration plots, the dots represent the experimental data, and the lines represent the theoretical values, with the concentration axis plotted as CuONP concentrations in μmol L⁻¹.

Table 1 Log K (conditional stability constant), binding site concentration (CL; μmol L⁻¹), complexation capacity (CC; μmol mg⁻¹ of TOC), and bias values for components C1, C2 and C3, derived from the PARAFAC analysis of fluorescence quenching titrations, representing the interaction between WEOM and CuONP

Sample		Component
Soil WEOM		C1	C2	C3
SC	log K	5.10	6.10	4.40
	CL	0.10	0.10	14.00
	CC	0.02	0.02	2.80
	Bias	0.07	0.25	2.62
SH	log K	4.50	4.80	4.40
	CL	3.00	3.00	12.00
	CC	0.60	0.60	2.40
	Bias	0.17	0.35	1.20
SBC	log K	5.50	5.50	5.10
	CL	9.20	9.00	9.60
	CC	1.84	1.80	1.92
	Bias	0.08	0.29	1.16
SBH	log K	4.90	4.70	4.50
	CL	8.00	4.00	13.00
	CC	1.60	0.80	2.60
	Bias	0.14	0.39	3.87
ADEC	log K	5.70	5.70	3.60
	CL	9.50	12.5	45.00
	CC	1.90	2.50	9.00
	Bias	0.14	0.06	4.75
ADEH	log K	5.00	5.00	8.00
	CL	13.40	22.90	39.00
	CC	2.68	4.58	7.80
	Bias	0.36	0.33	5.81

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Biochar WEOM		C1	C2
BC	log K	4.40	4.50
	CL	9.50	7.50
	CC	1.90	1.50
	Bias	0.44	0.44
BH	log K	4.60	4.80
	CL	20.90	0.05
	CC	4.18	0.01
	Bias	0.57	0.24

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Because no component remained unaffected by quenching (i.e., no “unquenched component” with stable fluorescence intensity was detected), two possible interpretations were considered. In the first interpretation, the strong affinity between CuONPs and protein-like compounds may cause immediate binding and rapid fluorescence loss. This is consistent with the rapid decrease in the fluorescence intensity of the C3 component upon the first CuONP addition. It is reported that the increase in temperature could enhance the extraction of nitrogen-rich compounds, such as amino acids and amino sugars.^95–97 This is consistent with the increase in the log K value of ADEH, compared to ADEC, resulting in the increased release of compounds with higher affinity for CuONP, thereby improving the availability of binding sites. On the other hand, the log K value remained unchanged in SH compared to SC, and for the oxisol–biochar system, no positive correlation was observed. These differences can be attributed to intrinsic compositional variation among soils, indicating the low availability of organic–nitrogen compounds in oxisol, as well as the inability of biochar to provide protein-like compounds. Although fluorescence quenching is commonly used to evaluate nanoparticle–protein interaction, the protein fluorescence yields are generally lower compared to organic fluorophores.^98–100 Nevertheless, the log K values clarify the high affinity between CuONP and protein-like compounds, and the CC values highlight the potential for protein-corona formation. In addition, from the protein corona perspective, the existing literature refers to nanoparticle–protein interactions as being strong interactions,^14,101,102 but the small size of the CuONP and their spherical shape might reduce the binding strength and conformational stability of the absorbed protein layer.^102,103 Because the process of eco-corona formation is dynamic, these weakly bound proteins might be easily displaced from the nanoparticle surfaces by other molecules of similar affinity but higher abundance.^36,104

The second interpretation is that the interaction of nanoparticles and WEOM occurs mainly by humic-like acids and large-size hydrophobic compounds, owing to the low stability of the CuONP attachment to protein-like compounds. This agrees with the improvement in the complexation capacity from biochar-derived compounds released to soil (SBC and SBH samples compared to the SC and SH samples), where changes to the molecular profile cannot be attributed to proteins. Biochar is a char material, and the complexation capacity of biochar-derived organic matter is associated with the pyrolysis temperature, and it is primarily attributed to humic-like compounds.^42,105 The two biochar components identified by PARAFAC analysis, C1 [λ_Ex 250(325)/λ_Em 425] and C2 [λ_Ex 270(375)/λ_Em 480] (Fig. S7b), corresponded to 185 and 29 models from the OpenFluor database, respectively. They are attributed to humic-like compounds, differing in the aromatic arrangements, functional groups, and molecular weights of the compounds, i.e., the blueshift of the C1 component is attributed to less conjugated and smaller, aromatic molecules.^43,46 Comparing SC and SH samples with SBC and SBH samples, respectively, there is evidence that the addition of biochar to Oxisol soil enhanced the binding site availability (a higher CC) by releasing compounds with higher affinity for CuONP (higher log K). Interestingly, the best quenching parameters (log K and CC) were observed for the biochar C1 component, which exhibited the main peaks at similar wavelengths to those of the soil C2 component, attributed to humic-like compounds of lower complexity. Such similarities reflect the higher affinity of these lower complexity humic-like compounds for CuONP compared to the other WEOM compounds. The CuONP affinity for compounds of higher aromaticity or with an amphiphilic structure, instead of protein-like substances, is in line with copper's binding preferences, which follows the order of humic-like > fulvic-like > protein-like compounds as reported for copper ions bound to organic matter, where carboxyl > C–O of polysaccharides > phenolic group > aryl > amide > aliphatic groups are the preferred functional groups for binding.¹⁰⁶ However, such preference changes with the compound's structure available in the system, as reported by Silva et al.,¹⁰⁷ showing that copper might bind not only to hydrophilic structures but also to the hydrophobic region of molecules (C=C of aromatics). Generally, condensed aromatic compounds show a higher density of carboxylic groups, which are considered active sites for copper binding. In the same way, the stronger binding affinity of phenolic groups to copper is highlighted.¹⁰⁸ Huang et al.⁴⁷ evaluated the dissolved organic matter from biochar, showing that phenolic groups participated more in the complexation process compared to carboxyl groups, categorizing the phenol bonds as strong and the carboxylic binding sites as weak. Thus, the complexation behavior of humic-like compounds is likely driven by both their condensed aromatic structure and functional groups. This molecular arrangement of compounds released from biochar can contribute to enhancing the complexation response observed for SBC and SBH samples.

Nanoparticle affinity for molecules with an aromatic-condensed structure has been reported for nano-TiO₂,¹⁰⁹ nano-CuO,¹¹⁰ or iron-based nanoparticles.¹¹¹ The functional groups containing π bonds and lone pairs of electrons, such as carboxylic acids, hydroxyl, and aromatic structures, are reported as the main groups responsible for the interactions.¹¹² Therefore, we hypothesize that the eco-corona formation on CuONPs occurs mainly through the interaction of molecules with an amphiphilic profile, owing to the higher binding affinity of nanoparticles to humic-like compounds, and that biochar application changes the WEOM profile of soils, introducing aromatic compounds that are of low complexity but high functionality.

Assuming that humic-like compounds dominate the WEOM from ADE and biochar, and play a central role in eco-corona formation, the distinct patterns of CuONP aggregation in the presence of WEOM are likely driven by differences in the molecular architecture of these compounds or by non-fluorescent complexing agents that are undetectable by fluorescence spectroscopy.⁴⁷ To elucidate the chemical nature of these interactions, the organic coatings acquired by the CuONP were investigated using XPS and FTIR analysis. Both techniques revealed subtle differences between the hot- and cold-water WEOM extracts, as well as across samples, such as the higher intensity of the O–H band at 3500 cm⁻¹, C=C band at 1620 cm⁻¹, and C–O band at 1100 cm⁻¹ for the hot-water extracted samples compared to the cold-water extracted samples (Fig. S8). Furthermore, the relative percentage of C–N functional groups identified by XPS (Fig. S9) was higher for hot-water extractions compared to cold-water extractions. XPS identified prevalent surface bonds, such as carbon–oxygen (C–O/C=O) and carbon–carbon (C–C/C=C), which could be attributed to hydroxyl, carboxyl, alcohol, ether, ester, and aromatic functional groups. The identification of C–O, C=O, and C=C adsorption bands agrees with the FTIR analysis, which revealed the presence of amine and imine groups (Fig. S8). Notably, similar chemical signatures have been reported for CuONPs interacting with root exudates,¹¹³ a complex mixture of plant-derived proteins, lipids, and carbohydrates known for their high reactivity and biological activity.¹¹⁴

Cryogenic transmission electron microscopy (cryo-TEM) was applied to visualize the eco-corona formation on CuONP, allowing the direct observation of the molecular conformations in a hydrated state, and to assess whether WEOM induces CuONP agglomeration or provides stabilization. As shown in Fig. 2a and b, CuONP in UPW exhibited uniform sizes and quasi-spherical shapes. Distinct eco-corona structures were visualized on CuONP incubated with WEOM from ADE (Fig. 2c and d) and biochar (Fig. 2e and f). The higher stability of the surface complexation between the organic compounds and CuONP, along with the abundance of available sites (Table 1), led to the formation of a strong hard corona that persisted after washing. Differences in the CuONP agglomeration pattern were identified among the WEOM samples, despite showing similar eco-corona thicknesses (Fig. S10). The eco-corona is likely a cloud of biomolecules surrounding nanoparticles, which, depending on the biomolecule size and rigidity, may promote nanoparticle agglomeration while preventing complete aggregation. While ADEC and ADEH samples tended to separate the nanoparticles into individual particles or small clusters, the CuONPs in BC and BH formed larger clusters, showing a random distribution but with higher nanoparticle density. Overlaps between clusters were observed, and it was unclear whether they resulted from the formation of organic matter tails connecting the clusters or from image overlay (Fig. 2g). Nevertheless, clusters of higher particle density can be a side effect of the washing steps, inducing nanoparticle interaction, as previously reported.¹¹⁵ In contrast, cryo-TEM could not visualize the eco-corona from the CuONP interaction with WEOM from oxisol (Fig. S11a) and the oxisol–biochar system (Fig. S11b), likely due to the weak interaction between the available organic compounds and CuONP. This weak binding may have led to the partial or complete removal of the eco-corona during the washing steps.

Fig. 2 Cryogenic transmission electron microscopy images of CuONPs in (a and b) ultrapure water, (c) ADEC, (d) ADEH, (e) BC, and (f) BH samples, illustrating structural changes following eco-corona formation. (g) Schematic of nanoparticle structural arrangements driven by eco-corona formation.

To further investigate the potential molecular drivers of eco-corona formation that enabled its visualization by cryo-TEM, a detailed compositional analysis was conducted on ADE and biochar-derived WEOM. The ¹H-NMR analysis of the biochar (Fig. 3b) showed a temperature-driven increase in aromaticity, accompanied by a relative decline in aliphatic content (Table S2). These changes indicate the enhanced extraction of oxygen-rich fulvic-like compounds at elevated temperatures, characterized by functional groups adjacent to electronegative atoms (e.g., carboxyl, carbonyl, and ester). ADE followed a similar thermal trend, with increases in both aliphatic and oxygenated components, but exhibited broader chemical diversity. Notably, ADE samples contained a higher content of aliphatic compounds and carbohydrates compared to biochar (Table S2), suggesting a distinct molecular fingerprinting potentially relevant to eco-corona formation.

Fig. 3 ¹H-NMR spectra and van Krevelen diagrams of WEOM from Amazonian dark earth (ADE) and biochar (B) following cold (C)- and hot (H)-water extractions. Peaks with asterisks (*) are off-scale for clarity. Panels (a) and (b) show the ¹H-NMR spectra; panels (c–f) show van Krevelen diagrams with molecular formulas colored according to the functional group class: CHO , CHON , CHOP , and CHOS . Black lines in the van Krevelen diagrams represent boundaries based on the modified aromaticity index (AI_MOD), indicating molecular double-bond density.

An ESI-FT-ICR-MS analysis revealed not only compositional differences between the ADE and biochar samples (e.g., N- and S-containing structures) but also distinct structural characteristics. For instance, unsaturated and condensed aromatic structures were predominantly found in biochar, whereas aliphatic and aromatic structures with low condensation were mostly found in the ADE samples. Biochar-derived WEOM (Fig. 3e and f) showed a reduced abundance of aliphatic molecular formulas (AI_mod > 0.0) and was instead dominated by unsaturated moieties, i.e., olefinic and aromatic structures, as also indicated by the ¹H-NMR data (Table S2). This profile aligns with the high proportions of condensed aromatic compounds (ConAC, 18–19%) and lignin-like formulas (69–74%) identified in the biochar samples (Table S2). The high values of double bond equivalent (DBE) index underscore the prevalence of unsaturated molecules rich in double bonds and/or rings, and the aromatic index (AI) values (Table S3) are related to C=C bonds density, confirming a more condensed aromatic character in biochar WEOM relative to ADE.^116,117 In contrast, the ADE samples displayed a more chemically diverse aromatic profile with a broader distribution of molecular formulas and structural motifs (Table S3). Tannin-like compound formulas were especially prominent in ADE samples, accounting for ∼13% and ∼22% in ADEC and ADEH, respectively, compared to just ∼5% and ∼3% in BC and BH, respectively (Table S3). The high O/C atomic ratios of tannin-like structures suggest greater oxygenation, which may enhance their binding affinity for CuONP surfaces. The ADE samples also contained a wider variety of lignin-like molecules, as well as aromatic structures with low to moderate condensation (0.0 < AI_mod < 0.67), some of which featured heteroatom substitution and partially conjugated systems, such as polycyclic aromatic hydrocarbons (Fig. 3c and d).

The ADEC and ADEH samples (Fig. 3c and e) showed a higher relative abundance of nitrogen-containing molecules (CHON formulas), but these molecules were nearly absent in biochar WEOM (Fig. 3d and f), consistent with the main fluorescence peaks identified by EEM-fluorescence data. These N-rich compounds were primarily located in the aromatic region. Thermal treatment appeared to degrade these molecules, producing shorter carbon chains with altered structures, evident in ADEH's higher abundance of CHON formulas with elevated H/C ratios and an increase in oxygen-rich species (from 51% in ADEC to 65% in ADEH), likely reflecting oxidative breakdown (higher NOSC, Table S3). Sulfur-containing compounds accounted for 11–13% of the molecular formulas in ADE samples, compared to only 0.8–3% in biochar, further highlighting ADE's chemical complexity. These heteroatom-rich molecules are known to exhibit strong affinities for nanoparticles, influencing eco-corona composition. For example, N- and S-containing compounds have been shown to preferentially bind to PtNMs,²⁰ while S-containing groups with low molecular weight and saturation indices dominate the eco-corona on Ag nanoparticles.¹⁹ The C–N and C–O bonds were the main bonds identified by XPS on the CuONP surface from eco-corona acquisition, followed by C–C/C=C bonds (Fig. S9), and consistent with the bands identified by FTIR (Fig. S8) on eco-corona evaluation.

Compositional differences in WEOM can affect the conformational arrangement of dissolved organic matter.¹¹⁸ Highly functionalized molecules might assume new conformations, hindering the binding sites from nanoparticle interaction due to self-aggregation.^119,120 Based on the compositional similarities and distinctions between the compounds present in ADE and biochar WEOM, we hypothesize that both heteroatom-rich and condensed aromatic compounds contribute to eco-corona formation. In this context, CuONP exhibits preferential binding to amphiphilic molecules, where N- and O-containing functional groups serve as the primary interaction sites. When CuONP surfaces become saturated with these molecules, their conformation may shift, exposing hydrophobic domains, i.e., aliphatic chains or small aromatic fragments that do not adhere directly to the nanoparticle surface.^34,36,121 These hydrophobic moieties can stabilize the nanoparticles via steric or electrostatic repulsion, thereby preventing aggregation and promoting the formation of small and stable CuONP clusters. Conversely, interactions between CuONP and more condensed aromatic compounds or less functionalized aromatic moieties might result in partial nanoparticle coverage, promoting aggregation rather than stabilization. Partial coverage or irregular distribution over the nanoparticle surfaces by the N- and O-containing functional groups from larger molecules (such as humic-like compounds) can promote agglomeration through a patch mechanism. Additionally, O-containing groups like carboxylic acids, phenols, and ketones located around aromatic structures in humic-like compounds can bind to multiple nanoparticles at once, facilitating agglomeration via bridging mechanisms.¹²² Cluster formation can also result from biomolecules that remain bound to each other while simultaneously interacting with nanoparticles.^115,121

Changes in zeta potential provided additional evidence of interactions between WEOM and CuONPs, showing a good correlation between the extent of adsorption and the zeta potential values.¹²³ All the WEOM samples exhibited negative zeta potential values, whereas CuONP displayed positive zeta potential (Fig. S12). Upon interaction with WEOM, the zeta potential of CuONP decreased, remaining positive after the addition of WEOM from the SC, SH, SBC, and SBC samples but becoming negative following an interaction with WEOM from the ADEC, ADEH, BC, and BH samples. This shift suggests that the variation in zeta potential can be linked to the degree of nanoparticle surface coverage and the availability of binding sites in the WEOM. When the zeta potential remained positive but decreased in magnitude, there is a tendency for nanoparticle aggregation due to a weaker stabilization force (repulsion) among them. The adsorption of biomolecules onto nanoparticles is influenced by the availability of specific compounds,^113,124 their molecular size,^36,124 and the selective affinity of the nanoparticle for specific functional groups or structural motifs.^19,20 Generally, the structural complexity of the organic compounds governs the nature and strength of their interactions with nanoparticles. Larger molecules are more effective at stabilizing nanoparticles under high ionic strength conditions. These can create steric hindrance and stronger repulsive forces, partially due to conformational changes upon interaction, thereby reducing nanoparticle agglomeration.^24,125,126

3.2 Evaluation of CuONP colloidal behavior due to eco-corona formation

The agglomeration behavior of CuONP following WEOM addition was evaluated under different ionic strength conditions by monitoring the hydrodynamic diameter over time (Fig. S13 and S14). It is reported that eco-corona formation can prevent nanoparticle agglomeration induced by electrolytes of natural occurrence in the environment, such as Na⁺ and Ca²⁺ (ref. 36, 124 and 127) and that the hydrophobic character of soil organic matter may be a key factor in nanoparticle stabilization.¹²⁵ When dispersed in UPW, CuONP exhibited strong stability for up to 30 min. However, the addition of NaCl induced their homo-agglomeration (Fig. S13 and S14). The addition of WEOM influenced CuONP behavior similarly across most conditions, but as ionic strength increased, agglomeration became strongly dependent on the WEOM source. Previous studies have shown that organic matter can stabilize CuONP through mechanisms, such as electrostatic and hydrophobic interactions.^28,112,119 Electrostatic interactions were likely the dominant stabilization mechanism in our system, but the lower density charge of some WEOM samples probably provided weaker interactions, leading to a small surface coverage and allowing NaCl to rapidly induce CuONP agglomeration.^28,34

The critical coagulation concentration (CCC) of NaCl was 6 mM for SC, 9 mM for SH, 4 mM for SBC, and 10 mM for SBH, values comparable to those of bare CuONP (9 mM NaCl). WEOM from ADE and biochar (Fig. 4B) presented remarkable stabilization, requiring much higher NaCl concentrations to induce agglomeration. The enhancement of CuONP stability was assumed to arise from steric effects, resulting from eco-corona formation. Steric stabilization from surface coatings confers greater resistance to aggregation compared to the stabilization based solely on electrostatic forces.^28,121 The CCC_NaCl values for the biochar samples were 166 mM for BC and 250 mM for BH, while the ADE samples showed CCC_NaCl of 406 mM (ADEC) and 107 mM (ADEH). It is also known that increased ionic strength can lead to the desorption of humic acids due to competition between ions and organic molecules for binding sites on nanoparticle surfaces.³⁴ WEOM with lower binding affinities (lower log K values, Table 1) leads to weakly bound eco-coronas, requiring lower NaCl concentrations to induce CuONP aggregation. In contrast, WEOM with higher complexation capacity (higher log K values) required higher ionic strength to induce nanoparticle agglomeration. The replacement of organic compounds by ions becomes significant when the molecules have a weaker affinity for the nanoparticle surface. Such a replacement can diminish hydrophobic interactions between molecules, thereby promoting nanoparticle aggregation. A comparison between the ADE and biochar samples revealed that differences in the log K values helped to explain the higher NaCl concentrations required to induce agglomeration in the ADE WEOM medium. Molecules with strong binding affinity (higher log K) are not easily displaced, and higher ionic strength is needed to generate sufficient ion competition to overcome their attachment to the nanoparticle surface.³⁴

Fig. 4 A) Schematic of the enhancement of the critical coagulation concentration (CCC) of CuONP and (a) no eco-corona formation, (b) weakly bound eco-corona, (c) strongly bound eco-corona but with low-diversity composition, and (d) strong and high-diversity eco-corona at an increasing ionic strength. B) Agglomeration attachment efficiencies of CuONP in UPW and WEOM extracted from (a) oxisol, (b) oxisol–biochar system, (c) Amazonian dark earth, and (d) biochar, as a function of NaCl concentration (0–1000 mM) at pH 5–6.

Furthermore, organic compounds that do not participate in eco-corona formation remain in the medium and are essential for interacting with corona-forming molecules to prevent nanoparticle agglomeration. As previously mentioned, the agglomeration patterns observed via cryo-TEM may result from the washing step, as the presence of free organic matter in the system is crucial for maintaining nanoparticle stability.³⁶ This effect became more evident when comparing CCC_NaCl values (Fig. 4B) across samples. Those with weakly bound eco-corona (e.g., S samples) showed lower CCC_NaCL values, while samples with strongly bound eco-coronas (e.g., BC and ADE samples) required significantly higher ionic strength to induce agglomeration (Fig. 4Bc and d). Barbero et al.³⁶ described this dynamic equilibrium between organic matter covering nanoparticle surfaces and free organic matter in the system that contributes to stabilizing nanoparticles. Organic compounds that are strongly bound to the nanoparticle surface, forming a hard corona, are barely able to inhibit nanoparticle agglomeration, which is consistent with our cryo-TEM images. However, Barbero et al.³⁶ linked soft corona formation primarily to the concentration of organic matter, using different concentrations of a single humic acid sample. While soft-corona stabilization has been associated with carbon content rather than binding site availability,^36,128 our results suggest that additional factors influence outer-layer (soft corona) formation. Importantly, all the WEOM samples were tested at the same carbon concentration, yet they exhibited different capacities to stabilize CuONP over time and at increasing NaCl concentrations. These findings highlight that the structural characteristics of the NOM compounds, such as molecular size, conformational structure, charge, and polarity, as well as nanoparticle surface specificity, may play a role in stabilization rather than stabilization being controlled by carbon content alone.¹²⁴

Considering the oxisol WEOM samples (i.e., SC and SH), the organic compounds exhibited lower affinity for CuONP, resulting in the formation of a weakly bound eco-corona. Their soft coronas were insufficient to prevent CuONP agglomeration, as evidenced by the lower NaCl concentrations required to induce CuONP agglomeration compared to the ADE WEOM samples, despite their identical carbon concentration. A similar trend was observed when comparing the WEOM of SBC and SBH with those of ADEC, ADEH, BC, or BH. The results indicate that carbon content alone does not govern CuONP stabilization or soft corona formation. Instead, the molecular structure of the organic matter plays a central role in guiding the development of outer layers of the acquired eco-corona through an equilibrium between strongly bound compounds and freely dissolved molecules in the system. Our findings suggest that small conjugated aromatic compounds and functional groups containing oxygen and nitrogen exhibit higher affinity for CuONP surfaces, promoting hard-corona formation. For instance, the N compounds in ADEC were predominantly aromatic (Fig. 3c), which helps explain the increased resistance to nanoparticle agglomeration observed with ADEC WEOM (Fig. 5Bc), in contrast to ADEH, whose N compounds were mostly aliphatic (Fig. 3d). In addition, the AI and DBE values of WEOM are relevant indicators of compound structure that may promote nanoparticle stability. For instance, the CCC_NaCl values follow the order of ADEH < BC < BH < ADEC. The WEOM of the biochar samples exhibited higher AI and DBE values (Table S3), indicating that highly unsaturated and aromatic molecular structures, characterized by condensed ring systems, can enhance nanoparticle resistance to agglomeration, though to a lesser extent than aromatic N-containing compounds. Nonetheless, the contribution of long-chain aliphatic compounds, although less detected via fluorescence, cannot be neglected, as they represent a significant portion of ADEC's WEOM composition (Table S2). Overall, our results demonstrate that the formation of a stable soft corona is essential for nanoparticle stabilization and that the molecular structure, rather than the carbon concentration, is the key factor influencing forces that inhibit nanoparticle agglomeration in aqueous media.

Fig. 5 Correlative microscopy approach illustrating different patterns of CuONP deposition onto the chorion membrane of zebrafish embryos at 48 hours post-fertilization (hpf) in UPW (CuONP) and response to different eco-coronas formed from nanoparticle interaction with WEOM extracted from oxisol (CuONP + SC) and Amazonian dark earth (CuONP + ADEC) in cold water. Panels (a)–(d) show hyperspectral microscopy (CytoViva) images of the outer surface of the chorion, whereas panels (e)–(h) display the corresponding copper distribution maps. Panels (i)–(l) present scanning electron microscopy (SEM) images of the outer chorion layer, and panels (m)–(p) show the SEM images of the inner layer. Copper localization was further confirmed using synchrotron X-ray fluorescence mapping (SR-XRM) (panels (q)–(x)).

3.3 Nano-bio interactions: CuONP toxicity assessment of zebrafish from eco-corona formation

Nanoparticle agglomeration patterns resulting from eco-corona formation were strongly correlated with CuONP toxicity. A zebrafish toxicity model was employed to confirm that the toxicity of CuONP was indeed dependent on its bioavailability, ensuring that the influence of eco-corona formation on CuONP stability was effectively evaluated. This zebrafish embryo model is particularly suitable for such assessments for two main reasons. First, during the FET assay, the chorion acts as a selective barrier, with pore sizes ranging from 0.5 to 0.7 micrometers, limiting the penetration of large nanoparticle agglomerates.^129,130 Second, after hatching, the embryo is capable of swimming freely in the water column, allowing it to avoid sedimented particles. Therefore, this model provides a reliable means of assessing how nanoparticle availability, affected by eco-corona formation and colloidal stability, influences toxicity. The distribution (Fig. 5e–h) and concentration (Fig. 5q–t) of CuONP on the zebrafish chorion membrane varied according to the nature of the eco-corona. In general, nanoparticle toxicity is linked to chorion pore blockage, which induces hypoxia and, consequently, bradycardia in the embryos.^131–134 Larger nanoparticles can effectively block the micropyles of the chorion by creating a barrier, affecting its mechanical property and reducing the oxygen availability, which compromises the antioxidant system of embryos.^130,135 Besides, pore obstruction can occur because of nanoparticle agglomeration and cluster formation. For the WEOM samples that showed a weak interaction among biomolecules and CuONP (e.g., CuONP + SC, CuONP + SH, CuONP + SBC, and CuONP + SBH), massive agglomerates were observed to adhere to the chorionic outer layer (Fig. 5g), resembling a multilayered nanoparticle deposition (Fig. 5k). This affected the hatching success (Fig. 6a), which is a biological endpoint often used at sublethal doses of nanomaterials to indicate toxic effects on zebrafish embryos.

Fig. 6 Heatmaps showing the effects of CuONP (0–10 μg L⁻¹) and WEOM from cold (C)- and hot (H)-water extractions from oxisol (S), biochar (B), oxisol–biochar system (SB), and Amazonian dark earth (ADE) on zebrafish embryos: (a) hatching rate, (b) malformation, (c) total body length, and (d) survival rate.

In addition to pore obstruction, the toxicity of nanomaterials can result from an induced deficiency of proteolytic enzymes, which are involved in “chorion softening” at the pre-hatching stage, to facilitate the breaking of the chorion membrane. Zebrafish hatching enzyme 1 (ZHE₁) is inhibited by Cu²⁺, impairing the success of hatching.¹³⁶ Although these large nanoparticle agglomerates are excluded from entering through the chorion pores,¹³⁷ small individual nanoparticles, as well as small agglomerates and Cu²⁺ ions, could easily pass through the chorion membrane in zebrafish.^133,134 The distribution of particles over the chorion outer layer varied according to the characteristics of the eco-corona (Fig. 5 and S17) and agglomeration behavior identified through agglomeration kinetics data. A strongly bound eco-corona formation prevented nanoparticle agglomeration and decreased CuONP interaction with the chorion membrane (Fig. 5h and t). The inhibition of nanoparticle agglomeration through eco-corona formation (e.g., CuONP + ADEC, CuONP + ADEH, CuONP + BC, and CuONP + BH; Fig. 4B) could enhance nanoparticle internalization (Fig. 5p), considering the size of the chorion pores (0.6 μm in diameter), and the low amount and homogeneous distribution of CuONP over the chorionic membrane identified by μ-SXRF (Fig. 5t). Although a partial obstruction of the pores is observed with CuONP + ADEC (Fig. 5p), the hatching rate at all concentrations evaluated was superior to the treatment with only CuONP (Fig. S18), indicating at least a partial remediation of toxicity due to eco-corona formation.

Nanoparticle agglomeration and its massive deposition over the chorion surface were correlated with the failure to hatch for those samples from which WEOM forms a weakly bound eco-corona, even considering the possibility that small aggregates might pass through the chorion pores. Nanoparticle internalization likely occurs primarily in samples where WEOM induces a strongly bound eco-corona (i.e., CuONP interaction with ADEC, ADEH, BC, and BH), and, thus, in which nanoparticles do not smother the chorion outer layer. The lower interaction of CuONP with WEOM in SC and SH increases nanoparticle availability to rapidly interact with the chorion surface, and their high affinity to bind to the chorion diminishes their diffusion through chorionic pores.¹³⁶ On the other hand, when a strongly bound eco-corona is formed, the interaction between nanoparticles and the chorion surface decreases, possibly facilitating their internalization through pores. The smothering of the chorion correlation with a failure to hatch has been reported by other studies with CuO materials at similar concentrations but with nanoparticles of a larger size.^134,136 Nonetheless, when nanoparticles pass through the chorionic pore canals, the toxicity would come from copper release.^136,138 The copper suppression of ZHE₁ enzymes has been reported for (indefinitely long) exposure to 0.11 μg L⁻¹ dissolved Cu in the medium, decreasing its activity to 50%.¹³⁶ While the suppression of gas exchange through chorion pore blockage by nanoparticle aggregates rapidly compromises embryo development, the slow release of copper ions from CuONP is unlikely to accumulate in the perivitelline space and have any effect on ZHE₁ production. The EC₅₀ on hatching was around 0.6–4.9 μg L⁻¹ CuONP to the medium containing only CuONP, or CuONP with the SC, SH, and SBC samples, and >10 μg L⁻¹ for the others (Table S4). The high hatching levels in the samples forming a strongly bound eco-corona (ADEC, ADEH, BC, and BH WEOM) (Fig. 6a) show that the CuONP concentrations evaluated did not release the amount of copper necessary to impair zebrafish embryo development, which aligns with findings from other studies.^136,138,139

Positive outcomes from eco-corona formation include a reduction in CuONP–chorion interactions, minimization of pore blockages and hypoxia conditions induced by CuONP deposition, and a decrease in CuONP–organism interactions, by limiting the direct exposure of zebrafish embryos to copper, due to the biomolecular layer adsorbed on the CuONP surface. As the evaluation was carried out at low exposure doses of nanoparticles, for an environmentally relevant and realistic risk assessment,^140–143 the LC₅₀ was not determined once low mortality was found among the concentrations tested. It can be assumed that no eco-corona formation on CuONP is much more harmful to zebrafish than possible CuONP internalization to the perivitelline fluid. For instance, nanoparticle adherence to the chorion, due to the non-formation of eco-corona, decreased the hatching rates compared to the unexposed control (i.e., CuONP with SC, SH, SBC, and SBH treatments), increased the levels of malformation, and reduced the total length. Additionally, eco-corona formation (i.e., CuONP with ADEC, ADEH, BC, and BH) minimized the CuONP effect on malformation and total length (Fig. 6b and c). However, other toxic effects of CuONP after hatching should not be neglected, considering that the bioavailability of nanoparticles to larvae might increase compared to that of the zebrafish embryo in the chorion.

Two possible mechanisms of CuONP toxicity to zebrafish embryos were addressed from the eco-corona perspective and were strongly related to the WEOM profile. Weak interaction of the organic matter with CuONP enhances their agglomeration, facilitating the formation of clusters and resulting in chorion pore obstruction by the NP clusters. No or limited eco-corona formation enhances nanoparticle availability to associate with the chorion surface. When there is a strongly bound eco-corona, i.e., great interaction of organic matter with CuONP, the steric stability acquired by the nanoparticles prevents them from agglomerating under high ionic strength conditions. This increases their homogenous distribution in the medium and decreases their deposition onto the chorion, which might facilitate their diffusion through the chorionic pores. This highlights the source of organic matter as the main driver of nanoparticle behavior in the environment through the eco-corona effect. Thus, eco-corona formation plays a critical role in modulating CuONP colloidal stability and bioavailability, ultimately influencing toxicity outcomes.

4 Conclusion

The molecular structure and functionality of carbon compounds in WEOM are key determinants of eco-corona formation on CuONP, driven largely by amphiphilic molecules, particularly low-complexity humic-like compounds. Although biochar application changed the WEOM profile of Oxisol (i.e., SBC and SBH) by introducing aromatic compounds, ADE and biochar samples exhibited greater chemically diverse aromatic profiles and a higher content of binding sites. These differences were not improved by increasing the extraction temperature, which raised carbon concentrations but did not enhance the release of compounds with high CuONP affinity. Humic-like compounds with small condensed aromatic structures and highly functionalized compounds facilitated the formation of a strongly bound eco-corona, as confirmed by cryo-TEM. Notably, cluster formation was attributed to the absence of free organic molecules removed by washing steps. Organic compounds that do not participate directly in eco-corona formation (soft corona) and remain in the medium are essential for interacting with corona-forming molecules (hard corona) to maintain nanoparticle stability. WEOM composition played a central role in defining both the soft and hard eco-corona. Samples with lower binding affinities (e.g., SC, SH, SBC, SBH) formed weakly bound eco-coronas, resulting in CuONP agglomeration under high ionic strength conditions (lower CCC_NaCl). In contrast, WEOM rich in N compounds (predominantly aromatics, e.g., ADEC) significantly enhanced CuONP stability (higher CCC_NaCl), likely through conformational shifts that exposed hydrophobic domains, promoting steric and/or electrostatic stabilization. No or limited eco-corona formation facilitated nanoparticle adherence to the chorion, leading to pore obstruction. Conversely, strongly bound eco-coronas promoted more homogeneous dispersion of CuONP in the medium and reduced chorion deposition, minimizing hypoxia and direct CuONP exposure to zebrafish embryos. It is demonstrated that WEOM is strongly able to form a stable eco-corona, with different fractions having greater or lesser affinity for the nanoparticle surface and that the resulting eco-corona modulates the nanoparticle environmental behavior. Soil organic matter must be carefully evaluated as one of the potential factors for the successful application of nanoparticles because of the influence of organic matter-derived eco-coronas on nanoparticle stability, bioavailability and side effects, which can be strongly dependent on primary soil characteristics and environmental conditions. For the ecological risk assessment of engineered nanomaterials, the role of organic matter in the eco-corona cannot be neglected when considering their fate in natural environments. Our results highlight the central role of soil organic matter source and composition in eco-corona formation, which is a key factor for the environmental fate and application of engineered nanomaterials.

Author contributions

Laís G. Fregolente: conceptualization, methodology, formal analysis, investigation, writing – original draft, visualization, project administration, writing – review & editing. João Vitor dos Santos: methodology, investigation, writing – review & editing. Gabriela H. da Silva: formal analysis, investigation, writing – review & editing. Theodoro R. Salles: formal analysis, investigation, writing – review & editing. Simone G. S. dos Santos: formal analysis, writing – review & editing. Luel S. Costa: formal analysis, writing – review & editing. Gabriela A. Nogueira: formal analysis, writing – review & editing. Márcia C. Bisinoti: writing – review & editing. Carlos A. Pérez: formal analysis, investigation, writing – review & editing. Patrick G. Hatcher: validation, resources, writing – review & editing. Iseult Lynch: conceptualization, writing – review & editing. Diego S. T. Martinez: conceptualization, validation, resources, writing – review & editing, supervision, funding acquisition.

Conflicts of interest

There are no conflicts to declare.

Data availability

All raw and processed data supporting the findings of this study, including toxicity assay spreadsheets, physicochemical characterization files (DLS, zeta potential, FTIR spectroscopy, Raman spectroscopy, XPS, NMR, and FT-ICR MS), microscopy images, and datasets, will be deposited in a public repository (Zenodo) and made openly available under a DOI upon acceptance of the manuscript. Additional processed data used to generate the figures and tables in this article are provided in the supplementary information (SI).

Supplementary information: abbreviation list; section 1: biochar characterization (instrument settings for XRD, TGA, Raman spectroscopy, FTIR spectroscopy, XPS analyses and data presentation); section 2: soils characterization (TGA curves); section 3: copper oxide nanoparticle characterization (XRD, XPS, hydrodynamic diameter, TEM image); section 4: water-extractable organic matter characterization (FTIR, UV-vis, SUVA₂₅₄, EEM-fluorescence images and data discussion, fluorescence indices, ¹H-NMR instrument settings and data, and ESI-FT-ICR-MS instrument settings and data); section 5: eco-corona characterization (cryo-TEM images of eco-corona, XPS, and FTIR spectroscopy); section 6: nanoparticle and WEOM interaction (nanoparticle stability evaluation, aggregation kinetics description, and zeta potential values); and section 7: toxicity assessment (hyperspectral microscopy images, hatching rate data, and EC₅₀ data); references. See DOI: https://doi.org/10.1039/d5en01164g.

Acknowledgements

This work was funded by the National Institute of Science and Technology on Functional Complex Materials (INCT-Inomat, CNPq Proc. No. 465452/2014-0 and FAPESP Proc. No. 2014/50906-9); National Institute of Science and Technology on Nanotechnology for Sustainable Agriculture (INCT-NanoAgro, CNPq Proc. No. 405924/2022-4) and the Center of Molecular Engineering for Advanced Materials (CEMol-CEPID, FAPESP Proc. No. 24/00989-7). This study was financed, in part, by the São Paulo Research Foundation (FAPESP), Brazil, Proc. No. 2023/13881-7. L. G. F. appreciates and is grateful for the scholarships from the São Paulo Research Foundation (FAPESP) (grant 2023/13881-7 and 2024/18015-9) and National Council for Scientific and Technological Development (CNPq) (grant 152648/2022-4). J. V. S. and P. G. H. acknowledge support from the Frank Batten Endowment Fund, awarded to Dr. Patrick G. Hatcher by Old Dominion University (Norfolk, VA). The authors are grateful to the Brazilian Nanotechnology National Laboratory (LNNano/CNPEM) facilities (TEM, Cryo-TEM, Nanotox and Environmental Nano) and to the Brazilian Biorenewables National Laboratory (LNBR/CNPEM) – Biophysics of Macromolecules (BFM) facility. This research used the facilities of the Brazilian Synchrotron Light Laboratory (LNLS), part of the Brazilian Center for Research in Energy and Materials (CNPEM), a private non-profit organization under the supervision of the Brazilian Ministry for Science, Technology, and Innovation (MCTI). The Carnauba beamline staff is acknowledged for their assistance during the experiment proposal 20222079. D. S. T. M. is grateful for the research productivity scholarship from CNPq. In addition, the authors are grateful to Dr. Aleksander Westphal Muniz (Embrapa Ocidental) and to Dr. Tsai Siu Miu, M.Sc. Anderson Freitas, Dr. Guilherme Lucio Martins, and M.Sc. Solange dos Santos Silva-Zagatto (CENA/USP) for their assistance with ADE soil sampling.

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