In vitro adsorption of Fumonisin B1 by multiple algae-modified clay formulations

TL;DR

This study explores using algae-modified clay to reduce fumonisin B1 in animal feed, showing that algae, especially green algae, effectively bind the toxin.

Contribution

The study introduces algae-modified clay as a novel and effective adsorbent for fumonisin B1 in feed.

Findings

Algae-based products, particularly those with green algae, showed high adsorption capacity for fumonisin B1.

The presence of polysaccharides in algae cell walls contributes to mycotoxin binding.

Adsorption efficacy was influenced by factors like pH and mycotoxin concentration.

Abstract

Mycotoxins are toxic secondary metabolites produced by fungi, and frequently encountered in cereals that compose a major part of livestock diets. Fumonisin B1 (FB1) is one of the most prevalent toxins in feed, posing a risk to animal health and productivity. Considering mycotoxin mitigation strategies, adsorbents are an advantageous alternative for reducing mycotoxin uptake by animals. In this context, the main objective of this study was to develop an in vitro protocol for FB1 adsorption and assess the binding efficacy of five formulated products composed of inorganic clay and algae extracts. For this purpose, algae-based formulations were provided by Olmix (Bréhan, France), and multiple parameters were evaluated for in vitro testing, such as pH and mycotoxin concentration. After the selection of adequate conditions, the adsorption capacities of five algae-based products were compared. Results indicate that the adsorption capacity of the algae-based products is mainly linked to the presence of algae, especially green algae; which present a high polysaccharide content in their cell walls as binding sites for mycotoxins. The use of algae for mycotoxin adsorption remains underexplored, but the findings of the present work indicate that algae-based products are effective for FB1 control in animal feed.

The online version contains supplementary material available at 10.1007/s12550-026-00643-3.

Figures

Effect of FB_1_ concentration on adsorption efficiency of A2 compared to activated charcoal (AC). Adsorption was evaluated at pH 5. Bars represent mean values and error bars indicate standard deviation (*n* = 3); error bars are not clearly visible due to their small magnitude

Adsorption isotherm FB_1_ obtained at pH 5, showing experimental equilibrium data (symbols) and model fits using the Freundlich (green line) and Hill (purple line) equations

In vitro adsorption of FB_1_ by five different algae-based formulations (A1-A5) and activated charcoal (AC) at pH 5. Boxplots show FB_1_ adsorption values from technical replicates (n). Green boxes represent green algae-based formulations (A1–A3), red boxes represent red algae-based formulations (A4–A5), and AC represents activated charcoal

Full text

Introduction

Mycotoxins are toxic secondary metabolites produced by filamentous fungi, including species within the Aspergillus, Penicillium and Fusarium genera. These microorganisms are known to infect cereals at multiple stages of production, ranging from field to storage; and result in a persistent risk of mycotoxin contamination throughout the entire production chain (Daou et al. 2021; Xu et al. 2023). Considering that cereals are major components of regular livestock diets, animals become vulnerable to the ingestion of contaminated grains. This exposure may lead to reduced performance, such as lower feed intake, milk yield, and growth efficiency and/or fertility (Vila-Donat et al. 2018; Xu et al. 2022a; Kihal et al. 2022).

Among the most commonly detected toxins in feed are Aflatoxins (AFs), Ochratoxin A (OTA), Trichothecenes, Zearalenone (ZEN) and Fumonisins (FBs) (Awuchi et al. 2022). Considering FBs, Fumonisin B_1_ (FB_1_) is the predominant compound encountered, especially in maize and its by-products (Beccaccioli et al. 2021; Pamphile and Azevedo 2002). Therefore, the occurrence of FB_1_ in animal feed has been documented worldwide, with reports from Europe, the Americas, Asia and Africa showing contamination levels ranging from 24.5% to 100% (Gao et al. 2023).

The presence of FB_1_ in products intended for animal consumption is concerning, as it has been linked with equine leukoencephalomalacia and porcine pulmonary edema. Additionally, its ingestion can also result in the reduction of feed intake, lower egg production, hepatic necrosis, and thymic cortical atrophy in poultry (Awuchi et al. 2021; Chen et al. 2021; Schrenk 2022; Yang et al. 2020). Effects on ruminants are briefly described, with previous studies showing lower milk yield after FB_1_ ingestion by dairy cattle; whereas adult beef cattle seem to be more resistant, exhibiting only mild hepatic necrosis (Osweiler et al. 1993; Smith 2018). Beyond its impact on animal health, FB_1_ is classified by the International Agency for Research on Cancer (IARC) as possibly carcinogenic to humans (Group 2B) and has been mainly associated with human esophageal cancer (IARC 2002; Yu et al. 2021).

Therefore, economic pressures, particularly in the livestock industry, are motivating producers to seek effective solutions to prevent the adverse effects of mycotoxins on animal health and productivity. However, if grain contamination has already occurred, preventative measures are no longer feasible. Consequently, the implementation of mitigation strategies intended for the removal, degradation or inactivation of toxins becomes crucial. Therefore, integrated approaches that combine multiple strategies are essential to guarantee safe mycotoxin levels in animal feed (Shi et al. 2018; Xu et al. 2022a).

Described methods include chemical, biological and physical treatments of grain. Chemical agents, such as ammonia, hydrogen peroxide, and organic acids, are highly effective in reducing mycotoxin levels. Nevertheless, the use of such reagents can make raw materials inedible for animals and contributes to environmental pollution. Biological strategies involve the use of enzyme-producing microorganisms to degrade or bio-transform toxins, which presents challenges for in-field application due to environmental interactions. Lastly, physical methods include sorting and separation, floating and segregation by density, irradiation, ultrasound treatment, dehulling, milling and adsorption (Acosta et al. 2025; Khan et al. 2024; Peng et al. 2018).

Adsorption involves the use of an adsorbing agent (AA), which forms mycotoxin–adsorbent complexes through direct binding with the toxins. This process reduces mycotoxin bioaccessibility and, therefore, intestinal absorption; as the formed complexes are excreted via feces. As a consequence, this also leads to a decrease in mycotoxin uptake and in its spread to target organs (Boudergue et al. 2009; Xu et al. 2022a). In contrast with other mitigation strategies, which aim to diminish mycotoxin levels during feed production, AAs are used as feed additives. Additionally, the main advantages of such binders are their cost, safety and ease of administration through inclusion in feed (Acosta et al. 2025).

Among employed AAs are organic (yeast cell wall, yeast cell wall beta-D-glucan fraction, oat and alfalfa fibers) and inorganic (bentonites, montmorillonites, zeolite and activated carbon) compounds (Kihal et al. 2022). In general, inorganic binders are highly efficient in adsorbing AFs, due to the high polarity and small molecule size of these toxins. However, such products are relatively inefficient in adsorbing other mycotoxins, especially Fusarium toxins, such as Deoxynivalenol (DON) and ZEN. In this context, the use of organic binders is recommended (Vila-Donat et al. 2018).

Considering the FB_1_ molecule size and its structural conformation, adsorption may be a challenging issue, especially with inorganic products. To address this limitation, adsorption can be increased through the incorporation of biological components, such as algae extracts, to inorganic binders. This modification enhances the interlayer spaces of clays, increasing surface area and resulting in more binding sites for mycotoxins (Cai et al. 2024; Oguz et al. 2022; Rasheed et al. 2020; Wang et al. 2023; Xu et al. 2022b).

Algal extracts are appealing options for AAs, as they are well-known for their biosorption/bioremediation of heavy metals (Cheng et al. 2019; Lin et al. 2020). These organisms’ cell walls contain a wide range of proteins and polysaccharides, such as β-D-glucans, that are potential binding sites for mycotoxins. Additionally, other algal compounds could also be responsible for adsorption capacity, such as chlorophyll and chlorophyllin; which may also form complexes with mycotoxins, reducing their bioaccessibility (Simonich et al. 2007).

Furthermore, the inclusion of algae as feed additives may not only help prevent the adverse effects of mycotoxins but also promotes improved animal health (Perali et al. 2020). Algae display high bioactive compound content, which can act as prebiotics and therefore enhance animal immunity. In addition, production performance (i.e. weight gain, feed intake, and feed conversion rate) may also be increased, since algae are rich in proteins, vitamins, and minerals (Fraga-Corral et al. 2023; Yadavalli et al. 2023).

Estimating the adsorbent efficiency of different products is indispensable, since it depends on the type of adsorbent, its physico-chemical properties, and the target mycotoxins. In vivo testing of mycotoxin binding efficacy of a large number of adsorbents is challenging, due to the complexity and cost; making in vitro analyses powerful tools for assessing and ranking the efficacy of various AAs. Nevertheless, experimental conditions for in vitro tests reported in the literature may vary widely, making it difficult to establish reliable protocols (Boudergue et al. 2009; Faucet-Marquis et al. 2014). Considering the information cited above, the aim of this study is to develop an in vitro protocol for FB1 adsorption to evaluate and compare the binding efficacy of products composed of inorganic clay and algae extracts, in order to identify the most effective formulation for FB_1_ adsorption in livestock feed.

Materials and methods

Mycotoxin binders

Five AA formulations used in the current study, were provided by Olmix (Bréhan, France). All formulations were labeled with codes (A1 to A5) and consisted of inorganic clay combined with algal-derived materials (Table 1). The tested products are based on a patented technology (Olmix 2013), in which algoclay formulations are produced by grinding macroalgal biomass followed by shear mixing with clay, at algae: clay mass ratios ranging from approximately 0.25 to 1.6 (Olmix 2013).

Table 1. Products used for FB1 adsorption in the current studyCodeClay variationAlgae typeAlgal source materialDevelopment statusA1BentoniteGreen algaeDry biomassUnder developmentA2BentoniteGreen algaeCrude aqueous extractUnder developmentA3BentoniteGreen algaeCrude aqueous extractCommercial productA4BentoniteRed algaeCrude aqueous extractUnder developmentA5BentoniteRed algaeCrude aqueous extractCommercial product

Due to intellectual property constraints, the exact composition, processing parameters, and structural characteristics of the commercial and under development formulations tested in the present study could not be disclosed and were not directly measured. Therefore, the formulations were differentiated according to their compositional features, especially the algal source, and were evaluated comparatively based on their adsorption performance rather than on detailed structural parameters.

For the development and validation of the in vitro method, only A2 (green algae crude aqueous extract plus bentonite) was employed; with the other formulations used only for efficacy testing. Additionally, activated charcoal (AC) was used as a positive control for adsorption tests.

Chemicals and reagents

FB_1_ external standards were acquired from Sigma-Aldrich (Fallavier, France), with stock solutions prepared in acetonitrile/water (50/50; v/v) for long-term storage at -20 °C and further dilution (calibration curves and experiments). The solvents used for the FB_1_ external standard dilution, mobile phase and buffer preparation for subsequent analysis by high-performance liquid chromatography coupled with a triple quadrupole mass spectrometry (LC-MS/MS), were HPLC grade and purchased from J.T. Baker (Phillipsburg, USA). In addition, validation of the in vitro method was performed using citrate buffer (C_6_H_8_O_7_ • H_2_O and C_6_H_5_O_7_Na_3_ • 2H_2_O; 0,1 M) containing 10% methanol, adjusted to pH 3, 5 and 7.

Chromatographic conditions and method validation

LC-MS/MS for mycotoxin quantification was carried out in the Agilent 1290 Infinity LC-System (Agilent Technologies, Santa Clara, USA) coupled to a 6460 triple quadrupole (Agilent Technologies, Santa Clara, USA) mass spectrometer, at the Food Toxicology Laboratory, Food Engineering School, University of Campinas (UNICAMP).

Chromatographic separation was conducted using the Zorbax SB-C8 column (3.0 × 100 mm, 1.8 μm) at 25 °C under isocratic conditions, using a mobile phase composed of 30% 0.1% (v/v) formic acid in water (A) and 70% 0.1% (v/v) formic acid in methanol (B), at a flow rate of 0.35 mL/min and an injection volume of 3 µL. Mass spectrometry analysis was performed using electrospray ionization in positive ion mode (ESI+), with following settings: gas temperature 300 °C, gas flow 10 L/min, nebulizer pressure 35 psi, sheath gas flow 10 L/min, sheath gas temperature 350 °C, capillary voltage 3.0 kV, and nozzle voltage 0.5 kV. Ultrapure nitrogen was used as both nebulizing and collision gas. FB_1_ was monitored in selected reaction monitoring (SRM) mode using the transitions m/z 353 (quantifier) and m/z 334 (qualifier), with m/z 722 as a precursor. Fragmentor voltage was 185 V and collision energy set at 40 eV. Finally, data acquisition and processing were performed using MassHunter software (version 7.00).

The linearity of the method was evaluated using matrix-matched calibration curves prepared in citrate buffer (0.1 M, 10% methanol) at pH 3, 5, and 7. FB_1_ standards were prepared at seven concentrations (0.5, 1, 2.5, 5, 7.5, 10, and 12.5 µg/mL) and analyzed in triplicates. All calibration curves showed linearities (R^2^) of ≥ 0.99 (Figure S1). Recovery was assessed in triplicates on the same day, with values ranging from 95% to 110% across all pH conditions, which are in accordance with EC guidelines (EC 2006).

Limits of detection (LOD) and quantification (LOQ) were determined based on signal-to-noise ratios of 3 and 10, respectively, and are reported in Table S1. Furthermore, method precision was evaluated at three FB_1_ concentrations (2.5, 5.0, and 7.5 µg/mL) in citrate buffer (pH 5) without adsorbent. Intra-day precision was assessed from five replicates analyzed on the same day, while inter-day precision was determined over three consecutive days. In this regard, coefficients of variation (CV%) were ≤ 20% for all tests, meeting SANTE/11,312/2021 (EC 2021) criteria (Table S2).

In addition, method selectivity was confirmed by analysis of blank and fortified samples (2.5 µg/mL FB_1_) at pH 3, 5, and 7. In this regard, fortified samples showed well-defined peaks at consistent retention times (1.928–1.955 min) with no interfering signals detected in blank matrices (Figure S2).

Effect of pH and FB1 concentration on adsorption capacity

pH

Three different pH levels (3, 5 and 7) were evaluated, to determine the optimal level to proceed with the trials. For this purpose, three FB_1_ working solutions (5 µg/mL) were prepared in citrate buffer with 10% methanol at pH 3, 5 and 7, separately. Next, 5 mL of each solution was pipetted into 50 mL polypropylene tubes containing either: 0.1% (w/v) of A2, according to manufacturer instructions; 0.1% (w/v) of AC (positive control); or no adsorbent (negative control); in triplicates (Faucet-Marquis et al. 2014).

Samples were then incubated (30 min; 37 °C; 8 x g) and centrifuged (15 min; 8586 x g). Subsequently, 1 mL of supernatant from each sample was retrieved, filtered by syringe filter (0.22 μm) and analyzed with HPLC-MS/MS, as described in the “Chromatographic conditions and method validation” section. After chromatographic analyses, the adsorption percentage of each test was calculated based on Eq. 1:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\%\:adsorption=\frac{{C}_{ads}}{{C}_{0}}\times\:100$$\end{document}

where Cads is the adsorbed mycotoxin yield (µg/mL) and C0 is the concentration of FB_1_ in the negative controls, without adsorbent (µg/mL) (Horky et al. 2020).

FB1 concentration

Four FB_1_ concentrations (1 µg/mL, 2.5 µg/mL, 5 µg/mL, and 10 µg/mL) were prepared in 5mL of pH 5 citrate buffer (10% methanol) as solvent. Considering the evaluated product should demonstrate a high affinity and capacity to adsorb mycotoxins at its low inclusion rate in livestock diets, 0.1% (w/v) of product A2 was employed.

The tests were performed in triplicates, using 0.1% (w/v) of AC as positive control and mycotoxin working solution without adsorbent as negative control. Next, the tubes were incubated (30 min; 37 °C; at 8 x g) and centrifuged (15 min; at 8586 x g). After, approximately 1 mL of the supernatant was withdrawn, filtered by syringe filter (0.22 μm), and taken for HPLC-MS/MS analysis using the conditions specified in the “Chromatographic conditions and method validation” section; and adsorption percentage was calculated based on Formula 1.

Isotherm curve

This step was conducted to determine an intermediate FB_1_concentration suitable for characterizing the adsorption capacity of different algae-based products. Considering the previously determined optimal pH, the adsorption behavior of FB_1_ was evaluated under this condition. In this respect, increasing concentrations of FB1 (0.5, 1, 2.5, 5, and 7.5 µg/mL) were incubated with 0.1% (w/v) of adsorbent A2, 0.1% (w/v) of AC (positive control), or without adsorbent (negative control). All assays were performed in triplicates and incubated at 37 °C, with rotation at 8 × g for 30 min. After incubation, samples were centrifuged (15 min; 8586 × g), and 1 mL of each supernatant was collected, filtered through a 0.22 μm syringe filter, and analyzed by HPLC–MS/MS as described in the “Chromatographic conditions and method validation” section.

Adsorption isotherms were then constructed to describe the relationship between the equilibrium concentration of FB_1_ in solution and the amount adsorbed by the tested product. Initially, the value of Qeq (amount of FB_1_ adsorbed per gram of adsorbent) was calculated using Formula 2:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{Q}_{eq}=\:\frac{({C}_{0}-{C}_{eq})}{m}\:\times\:V$$\end{document}

where C0 is the concentration of FB1 in the negative controls (µg/mL), Ceq is the the residual FB_1_ concentration after adsorption (µg/mL), m is the mass of adsorbent in grams and V is the final volume of the solution in liters (Horky et al. 2020).

Next, the data obtained was fitted into the Freundlich and Hill isotherm models (Al-Ghouti and Da’ana 2020). In this regard, the Freundlich model describes adsorption on a heterogeneous surface and is expressed by Formula 3:

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{Q}_{eq}={K}_{F}\times\:{C}_{eq}^{\raisebox{1ex}{$1$}\!\left/\:\!\raisebox{-1ex}{${n}_{F}$}\right.}$$\end{document}

where KF and nF are constants, with KF representing the adsorption capacity of the adsorbent (milligram ^1 −^ (^1 ∕ n^F) × liter ^1 ∕ n^F per gram) and nF being related to adsorbent affinity (Al-Ghouti and Da’ana 2020).

The Hill model was employed to describe cooperative adsorption behavior onto a heterogeneous substrate (Joannis-Cassan et al. 2011; Formula 4). In this model, Q_Hmax_, KD and nH are constants, where Q_Hmax_ is the maximum mycotoxin adsorption capacity (mg/g), KD is the Hill constant (mg/L) and nH corresponds to the cooperativity coefficient (Al-Ghouti and Da’ana 2020).

\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{Q}_{eq}=\:\frac{{Q}_{Hmax}\times\:\:{C}_{eq}^{{n}_{H}}}{{K}_{D}+\:{C}_{eq}^{{n}_{H}}}\:$$\end{document}

Evaluation of adsorption capacity of five algae-based products

The ideal conditions (pH and FB_1_ concentration) obtained from the last steps, were applied, to compare FB_1_ adsorption capacities of five different algae-based products (Table 1). Tests were performed using 0.1% (w/v) of each product (A1-A5), 0.1% (w/v) of AC (positive control) and no adsorbent (negative control) in triplicates. FB_1_ working solutions (2.5 µg/mL) were prepared in citrate buffer, pH 5 (0.1 M) with 10% methanol, and pipetted (5 mL) into 50 mL polypropylene tubes containing either the test products, AC (positive control), or no product (negative control). All tubes were incubated (30 min; 37 °C; 8 x g) and centrifuged (15 min; 8586 x g), followed by the removal of 1 mL of each supernatant. Samples were then filtered by syringe filter (0.22 μm) and taken for HPLC-MS/MS analysis according to the “Chromatographic conditions and method validation” section. Adsorption efficacy was calculated based on Formula 1.

Statistical analysis

Mean and standard deviation calculations of assay replicates were performed in Microsoft Excel 2016. The equilibrium point isotherm with two model fits (Freundlich and Hill model) was elaborated by plotting the experimental data and other resources in R software (R Core Team 2025). Lastly, unpaired t-test results for the adsorption of red algae and green algae-based products were obtained from GraphPad Prism software version 8, with no correction for multiple comparisons (GraphPad, 2018, v. 8.0.1).

Results

Effect of pH and FB1 concentration on adsorption capacity

Effect of pH

The pH level is an influential parameter for in vitro adsorption tests (Faucet-Marquis et al. 2014). Thus, three different assays were performed: at pH level 3, 5, and 7. All of the AC positive control samples showed adsorption levels above 90%, as expected (Table 2). Conversely, the A2 product adsorption performance varied greatly according to the pH.

Table 2. Effect of pH and Mycotoxin concentration in FB_1_ adsorption by the A2 algae-based productExperimentpHFB_1_ concentration (µg/mL)AdsorbentMean adsorption (%) ± SDMean recovery (%) ± SDpH effect35A288.06 ± 0.01195.63 ± 0.0455A248.06 ± 0.03296.59 ± 0.03975A22.8 ± 0.018110.97 ± 0.02635AC91.8 ± 0.00195.63 ± 0.0455AC91.72 ± 0.00296.59 ± 0.03975AC95.12 ± 0.001110.97 ± 0.026Concentration effect51A233 ± 0.01109 ± 0.0252.5A244 ± 0.0297 ± 0.1455A245 ± 0.0498 ± 0.03510A236 ± 0.04103.1 ± 0.0451AC86 ± 0.0005109 ± 0.0252.5AC80 ± 0.00197 ± 0.1455AC92 ± 0.00398 ± 0.03510AC95 ± 0.0002103.1 ± 0.04

At a lower pH level (3), FB_1_ adsorption was the highest (88.06%±0.011) and the closest to the AC positive control samples. When pH was increased to 5, the adsorption was reduced almost by half to 48.06%±0.032. Lastly, at pH 7, FB_1_ adsorption was the closest to 0% (2.8%±0.018), and showed a very high coefficient of variation, ruling it out as an alternative.

Between pH levels 3 and 5, the former presented a lower coefficient of variation and standard deviation. However, its adsorption level is too high and similar to AC, which could hinder comparisons among products. Alternatively, pH 5 presented an ideal and intermediate adsorption rate, with an adequate coefficient of variation and higher recovery, when compared to pH 3. In this context, all further assays were carried out at pH 5.

Effect of FB1 concentration

To evaluate the effect of FB_1_ concentration on the adsorption capacity, 1 µg/mL, 2.5 µg/mL, 5 µg/mL, and 10 µg/mL of FB_1_ were tested, considering 0.1% (w/v) of the product A2 and citrate buffer at pH 5. All the recovery tests were acceptable, ranging between 97% and 109% (EC, 2006). Assays using AC as positive control exhibited the highest adsorption rates, whereas FB_1_ adsorption by A2 increased from 33%±0.01 at 1 µg/mL to 45%±0.04 at 5 µg/mL (Table 2; Fig. 1). Nevertheless, at the FB_1_ concentration of 10 µg/mL, the mean adsorption decreased by approximately 10% (Table 2; Fig. 1), suggesting that higher FB_1_ concentrations may lead to saturation of the product’s binding sites (i.e., 10 mg of FB1 per 1 g of product).

Fig. 1. Effect of FB_1_ concentration on adsorption efficiency of A2 compared to activated charcoal (AC). Adsorption was evaluated at pH 5. Bars represent mean values and error bars indicate standard deviation (n = 3); error bars are not clearly visible due to their small magnitude

Equilibrium point and isotherm curve

After selecting pH 5 for the in vitro adsorption test, an equilibrium isotherm curve was elaborated with different FB1 concentrations (Fig. 2). As a result, the experimental data shows an exponential relationship among Ceq, Qeq and non-saturation of the adsorbent’s binding sites. Considering the two models applied for curve fitting, the Freundlich model demonstrates agreement with the experimental data; predominantly at lower FB1 concentrations. In contrast, the Hill model displays a better fit at higher mycotoxin levels. Thus, the Freundlich model seems to be the most suitable for the acquired experimental data due to its significant n factor; which reflects the non-linear nature of the adsorption. Additionally, the Hill model is mostly related to the binding of multiple species and presents many uncertainties in the conditions of the present study; contributing to its unsuitability to the experimental data (Joannis-Cassan et al. 2011).

Fig. 2. Adsorption isotherm FB_1_ obtained at pH 5, showing experimental equilibrium data (symbols) and model fits using the Freundlich (green line) and Hill (purple line) equations

The highest adsorption percentage was observed at 7.5 µg/mL (61%±0.03), followed by 5 µg/mL (40%±0.01), 1 µg/mL (32%±0.01), 2.5 µg/mL (30%±0.04) and 0.5 µg/mL (29%±0.01). Despite observing higher adsorption rates for FB1 at higher concentrations during this experiment, the recovery tests approached the upper limit of 110% for concentrations of 0.5, 1, 5, and 7.5 µg/mL. In contrast, a recovery rate of 97% was achieved at 2.5 µg/mL. Consequently, this concentration was selected for the comparison of the five different algae-based products. In addition, while conducting the previous experiment, the FB1 concentration of 2.5 µg/mL achieved a mean adsorption of 44%±0.02; therefore, further corroborating this choice for future product comparisons.

Adsorption capacity of five algae-based products

To compare five different algae-based formulations, in vitro adsorption tests that employed the ideal conditions from previous analyses (pH 5; 2.5 µg/mL FB1) were performed, and the results are shown in Fig. 3. Disregarding the AC positive control, the greatest adsorption performance was achieved by A2 (48%±0.05), followed by A3 (42%±0.04), A1 (38.5%±0.03), A4 (38%±0.03) and A5 (34%±0.05). Additionally, the Qeq of the tested products showed the same pattern as the adsorption percentage, where A2 exhibited the highest values (1.022 µg of FB1 adsorbed per mg of product) and A5 the lowest (0.718 µg of FB1 adsorbed per mg of product).

Fig. 3. In vitro adsorption of FB_1_ by five different algae-based formulations (A1-A5) and activated charcoal (AC) at pH 5. Boxplots show FB_1_ adsorption values from technical replicates (n). Green boxes represent green algae-based formulations (A1–A3), red boxes represent red algae-based formulations (A4–A5), and AC represents activated charcoal

Three green algae-based and two red algae-based formulas were tested. In this regard, a significant difference (p < 0.05) was found between the adsorption performance of products containing green algae (mean adsorption = 43.06 ± 0.06) and red algae (mean adsorption = 36.25 ± 0.05); suggesting that green algae-based formulations may be more efficient in adsorbing FB1.

Discussion

In vitro adsorption tests are generally used as a screening method for the efficacy assessment of mycotoxin binders. Some of the main advantages of performing such assays are their lower cost and quicker results, when compared to in vivo analyses. However, most of the studies on in vitro adsorption trials do not present standardized and repeatable conditions, especially regarding the pH levels and mycotoxin concentration (Faucet-Marquis et al. 2014; Kihal et al. 2022). This is particularly important, considering the medium’s pH level can drastically affect the adsorption performance of mineral products. In this regard, when the pH is lower than the pKa of the adsorbent, it results in a loss of charge and lower adsorption potential. Conversely, when the medium’s pH level is higher than the bentonite’s pKa, it becomes more electronegative and adsorption capacity is increased (Du et al. 2021; Kihal et al. 2022).

The results of the present study, show that adsorption was higher at pH 3, which is not consistent with the physico-chemical characteristics of FB_1_, which is protonated in acidic conditions, and bentonites. At this pH range, the cation exchange capacity and electronegativity of the AA should be low; which considerably reduces the binding performance when only bentonite is utilized (Barrientos-Velázquez et al. 2016; Schlösser et al. 2025). Therefore, results here obtained suggest that the adsorption of FB_1_ by the algae-clay product occurs mainly due to the presence of algae in the interlayers of bentonites.

Algae mycotoxin adsorption mechanisms are not yet well understood. However, it is known that algal cell walls contain polymers, such as β-D-glucans, xylans, galactanes and mannans. These components are likely key contributors to the adsorption capacity of algae, as they can bind to mycotoxins through Van der Walls interactions or hydrogen bonds (Cheng et al. 2019; Fraga-Corral et al. 2023). Such interactions are not based on charge exchange but rather rely on the structural stability of the polysaccharide molecules, which is pH-dependent. Under acidic conditions (pH 3), the structural rigidity of these polysaccharides increases, which improves their ability to bind to mycotoxins. Conversely, at neutral pH levels (5–7), the molecules are less stable and can suffer conformational changes, which might hinder mycotoxin adsorption (Bruinenberg and Castex 2022; Faucet-Marquis et al. 2014; Yiannikouris 2006).

Therefore, the low FB_1_ adsorption observed at pH 5–7 likely reflects the reduced activity of the algae component, due to pH-sensitive structural changes. Simultaneously, the bentonite may not have attained sufficient surface electronegativity to effectively contribute to adsorption at this pH interval. Altogether, this suggests that pH 5–7 likely represents an intermediate zone, where neither components perform optimally, leading to the observed decrease in overall adsorption efficiency. Moreover, our results also support the evidence that the modification of inorganic mineral products (i.e. bentonites) by adding organic extracts may increase their adsorption capacity; since previous reports indicate FB_1_ adsorption by clays alone is moderate to low (Elliott et al. 2020).

In this context, the addition of orange peel extracts to pure bentonite, resulted in efficient in vitro adsorption of Aflatoxin B1 (AFB_1_), FB_1_, and OTA. FB_1_ adsorption exceeded 80% in buffered solutions at pH 2.5, as well as in simulated gastric fluids (acidic conditions). Nevertheless, adsorption efficiency decreased to below 20% in simulated intestinal fluids with near-neutral pH (Rasheed et al. 2020). Similarly, the incorporation of glucomannans into clay mixtures enhanced FB_1_ adsorption capacity by 20% compared to glucomannans alone, particularly at pH 3, where FB_1_ adsorption reached 54.61% (Oguz et al. 2022). Overall, these finding are consistent with the results obtained in the current study, which describe a higher adsorption of FB_1_ by organically modified clays in acidic conditions.

An isotherm curve was constructed to characterize FB_1_ adsorption by one algae-based formulation, to select an optimal concentration for testing different products (Al-Ghouti and Da’ana 2020; Rajahmundry et al. 2021).The shape of the curve resembled those observed in other studies involving FBs and organically modified clays, and indicates the binding of the mycotoxin to specific sites (Al-Ghouti and Da’ana 2020; Baglieri et al. 2013; Rajahmundry et al. 2021). Furthermore, the data revealed that binding site saturation was not achieved at the tested concentrations; however, our preliminary results suggest that an FB_1_ concentration of 10 µg/mL combined with 0.1% (w/v) of adsorbent may saturate the binding sites of the product.

After determining the FB_1_ concentration to be 2.5 µg/mL from the isotherm curve, five different algae-based products were tested. The results showed adsorption percentages from 48% (A2) to 34% (A5). Moreover, green algae-based products exhibited significantly higher adsorption compared to those derived from red algae. This contrast may be attributed to the distinct compositions of the red and green algae cell walls. Red algae cell walls contain sulfated polysaccharides composed of galactanes serving as potential adsorption sites, whereas green algae have glycoprotein-rich walls with diverse functional groups (amino, carboxyl, sulfate, hydroxyl) acting as binding domains (Fuertes-Rabanal et al. 2025). At present, there are no studies comparing mycotoxin adsorption by multiple products containing different types of algae. However, both algal extracts and live algae have been widely used for heavy metal biosorption, with results showing that green algae generally display higher adsorption capacity than red algae, consistent with our findings (Boukarma et al. 2024).

Considering the use of only algae or algae-based products for mycotoxin adsorption, Lithothamnium calcareum has been tested for AFB_1_ adsorption in broiler chicks. As a result, not only a reduction of adverse effects related to mycotoxin ingestion was observed, but also an improved body weight, weight gain, and feed intake in the animals treated with L. calcareum (Perali et al. 2020). Conversely, another study involving DON and algae-modified clay, showed that the AA was not effective in adsorbing the toxin nor in avoiding the adverse effects related to DON in nursery pigs; possibly due to a low affinity of the product to this mycotoxin (Frobose et al. 2016).

Altogether, when preventive measures against mycotoxin contamination in animal feed are ineffective, adsorbents are recommended to reduce toxin uptake and prevent productivity losses (Khan et al. 2024; Vila-Donat et al. 2018). FB_1_, one of the most commonly found toxins in feed, has a complex and elongated structure, which makes its adsorption challenging. Therefore, it is essential to test and evaluate novel AAs to mitigate its adverse effects and enhance livestock performance (Gao et al. 2023; Oguz et al. 2022; Shi et al. 2018; Xu et al. 2022a). In this context, incorporating algae into livestock diets may simultaneously contribute to mycotoxin adsorption and improve animal health and immunity (Fraga-Corral et al. 2023; Yadavalli et al. 2023).

In vitro adsorption tests are useful tools for evaluating the adsorption capacity of multiple agents on a small scale, with lower cost and analysis time when compared to in vivo assays. In this regard, the evaluation of diverse test parameters in the present study resulted in an adequate in vitro FB_1_ adsorption protocol to screen different algae-based products. The results also showed different adsorption capacities of the formulations evaluated, showing that green algae were more efficient than red algae-based products. Such findings may indicate that the different compositions of these organisms’ cell walls can influence their performance in FB_1_ adsorption. In summary, the evaluated products, particularly those containing green algae, show promising potential for reducing FB_1_ exposure in livestock. However, further research is needed to assess their efficacy across different feed matrices and under simulated digestion conditions, as well as through in vivo studies on FB_1_ bioavailability. This is especially relevant given that the inclusion of algae in livestock diets has already been linked to improvements in animal health.

Electronic Supplementary Material

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Supplementary Material 1