# Tuning peptide self-assembly patterns in Tilapia scale gelatin hydrolysates through Cu2+ coordination: Characterization, identification and antioxidant evaluation

Jairo Andrés Camaño Echavarría, Raliat O Abioye, Samanta Sarahí Reyes, Katalin Selmeczi, Laetitia Canabady-Rochelle, Chibuike C Udenigwe

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## ► To cite this version:

Jairo Andrés Camaño Echavarría, Raliat O Abioye, Samanta Sarahí Reyes, Katalin Selmeczi, Laetitia Canabady-Rochelle, et al. Tuning peptide self-assembly patterns in Tilapia scale gelatin hydrolysates through Cu2+ coordination: Characterization, identification and antioxidant evaluation. Journal of Functional Foods, 2025, 127, pp.106747. 10.1016/j.jff.2025.106747. hal-05151479

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# Tuning peptide self-assembly patterns in Tilapia scale gelatin hydrolysates through Cu²⁺ coordination: Characterization, identification and antioxidant evaluation

Jairo Andrés Camaño Echavarría<sup>a,b,*</sup>, Raliat O. Abioye<sup>b,c</sup>, Samanta Sarahí Reyes<sup>b</sup>, Katalin Selmeczi<sup>d</sup>, Laetitia Canabady-Rochelle<sup>a,**</sup>, Chibuike C. Udenigwe<sup>b,c,*</sup>

## ARTICLE INFO

### Keywords:

Cu²⁺-binding peptides
food hydrolysate
functional nanomaterials
self-assembled peptides
enzymatic hydrolysis

## ABSTRACT

We investigated the self-assembly pattern of Tilapia scale gelatin hydrolysates through Cu²⁺ coordination and their in vivo antioxidant properties by Cu²⁺-induced oxidative stress using the *Caenorhabditis elegans*. Two treatments (Alcalase®, Alc; and Alcalase® followed by Flavourzyme®, Alc+Flav) were used to prepare whole and ≤ 1 kDa hydrolysates. Upon Cu²⁺ coordination, the fibrillation and surface hydrophobicity of all hydrolysates decreased, suggesting a degradation of β-sheet structures and the formation of amorphous aggregates. Rheological studies confirmed that the structural and mechanical properties of the resulting supramolecular assemblies are tunable after Cu²⁺ coordination. Due to the Cu²⁺-chelating and self-assembly properties, peptides present in the Alc hydrolysate significantly reduced endogenous ROS levels through Cu²⁺ coordination, thereby extending the lifespan of *C. elegans*. The results provide valuable insights into the influence of Cu²⁺ coordination on the progression of peptide self-assembly and Cu²⁺-induced oxidation in worms and prospects for food self-assembled peptides in biomaterial and nutraceutical applications.

## 1. Introduction

Over the past decade, aquaculture has experienced significant growth, driven by the rapid increase in the world's human population. In 2022, production had reached 223.2 million tons, with 62.6 % coming from capture fisheries (FAO, 2024). Approximately 50–70 % of the total weight of fresh fish ends up as waste, which has a significant negative impact on the environment (Sierra-Lopera & Zapata-Montoya, 2021). Tilapia is the third largest fish production in the world and the global market is growing at 10–12 % annually: with 6 million tons in

2020, its production is expected to reach 7.3 million tons by 2030 (Munguti et al., 2022). The production of red Tilapia generates significant waste, particularly scales, which are typically discarded during the filleting process. Fish scales, consisting of 30–50 % collagen and mainly hydroxyapatite (Ca₅(PO₄)₃OH) (30–40 %), are highly valuable for gelatin production. Gelatin, a fibrous protein derived from the thermal degradation of collagen, is widely used in the food, pharmaceutical and cosmetic industries due to its excellent functional and biological properties (Viji et al., 2019).

Encrypted within the primary sequence of parent proteins, bioactive

**Abbreviations:** AA, Amino acid; Alc, Alcalase®; Alc + Flav, Alcalase® followed by Flavourzyme®; ANS, 8-anilino-1-naphthalenesulfonic acid; BAPs, Bioactive peptides; CD, Circular dichroism spectroscopy; cp, Crossover point; CT, Charge transfer transition; d-d transition, d level to another d level; DCF, 2',7'-dichlorofluorescin diacetate; DH, Degree of hydrolysis; DLS, Dynamic light scattering; EC₅₀, Half maximal effective concentration; EDTA, Ethylenediaminetetraacetic acid; G1, First generation; G2, Second generation; G3, Third generation; G', Elastic modulus; G'', Loss modulus; GRAVY, Grand average of hydropathicity; LMWGs, Low molecular weight peptide hydrogels; MCPs, Metal-chelating peptides; MW, Molecular weight; MWCO, Molecular weight cut-off; NGM, Nematode growth medium; OPA, o-phthalaldehyde; pI, Isoelectric point; PV, Pyrocatechol violet; ROS, Reactive oxygen species; TEM, Transmission electron microscopy; ThT, Thioflavin T; TSF, Tilapia scale flour; TSG, Tilapia scale gelatin; TSGH, Tilapia scale gelatin hydrolysate; ≤ 1 kDa, Ultrafiltrated hydrolysate.

<footnote><sup>a</sup> Université de Lorraine, CNRS, LRGP, F-54000 Nancy, France</footnote>

<footnote><sup>b</sup> School of Nutrition Science, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada</footnote>

<footnote><sup>c</sup> Department of Chemistry and Biomolecular Sciences, Faculty of Science, University of Ottawa, Ottawa, Ontario K1N 6N5, Canada</footnote>

<footnote><sup>d</sup> Université de Lorraine, CNRS, L2CM, F-54000 Nancy, France</footnote>

<footnote>* Corresponding author at: School of Nutrition Science, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario K1H 8M5, Canada.</footnote>

<footnote>** Corresponding author.</footnote>

<footnote>E-mail addresses: laetitia.canabady-rochelle@univ-lorraine.fr (L. Canabady-Rochelle), cudenigw@uottawa.ca (C.C. Udenigwe).</footnote>
peptides released during the protein hydrolysis have been reported for their antioxidant, antihypertensive, anticancer, anti-inflammatory, antimicrobial, antidiabetic and metal-chelating activities (Camaño Echavarría et al., 2024; Wen et al., 2020). The past two decades, there has been a surge of research into the discovery of bioactive peptides derived from food processing by-products. For example, numerous studies have used enzymatic hydrolysis to release encrypted bioactive peptides from fish gelatin as one of the effective strategies to increase the added value of fish waste (Viji et al., 2019; Zhang et al., 2019).

Beside their capability to stimulate positive health effects in the body, food-derived bioactive peptides are capable of forming ordered self-assembled nanostructures that can be arranged and combined in various architectures and functions using 20 natural amino acids (Li et al., 2023). Importantly, combining bioactivity and self-assembly properties of food-derived peptides has become a research hotspot for the development of novel functional nanomaterials in biomedicine, food and cosmetics (Chen et al., 2022). For example, various supramolecular soft materials have been used to encapsulate, protect and release therapeutic drugs, such as lipid-like vesicles, nanofibers and low molecular weight peptide hydrogels (LMWGs) (Cao et al., 2021; Wang et al., 2023). Particularly, in this last case, LMWGs have attracted the attention of researchers considering their favorable properties, their diversity, their ease of preparation and their compatibility with the environment and living systems (Bassan & Marchesan, 2023; Cao et al., 2021). Derived from food proteins, LMWGs can be formed during the peptide self-assembly process due to reversible noncovalent interactions such as hydrogen bonding, electrostatic interactions, hydrophobic interactions, etc. (Cao et al., 2019; Cao et al., 2021; Vahedifar & Wu, 2022). In most cases, the formation of LWMGs is controlled by intrinsic properties (i.e., number of amino acids, the amino acid side chain properties, and the peptide sequence) and external stimuli (i.e., changes in the pH, ionic strength, temperature, protein concentration, and metal ion coordination (Cao et al., 2021; Li et al., 2023). Metal ion coordination is a promising strategy to modify the self-assembly pattern of peptides, enabling the development of peptide-based biomaterials with potential biological applications (Sharma et al., 2019). Nowadays, a large number of studies concerning the induction of peptide self-assembly phenomena through metal ion coordination in synthetic peptides have been reported (Abioye et al., 2024; Fortunato & Mba, 2021; Rammal et al., 2023; Shao et al., 2020). However, to the best of authors' knowledge, there are no studies using this approach in fish protein hydrolysate. Moreover, there is no existing research on how Cu²⁺ coordination affects the physicochemical, mechanical, and in vivo antioxidant properties of self-assembled bioactive peptides derived from enzymatically digested fish gelatin hydrolysates. Therefore, the aim of the present study was to evaluate the effect of Cu²⁺ coordination on both the self-assembly patterns of peptides and the in vivo antioxidant potential of Tilapia scale by-product hydrolysates, using *Caenorhabditis elegans* as a model to assess Cu²⁺-induced oxidative stress.

# 2. Materials & methods

## 2.1. Chemicals and reagents

Red Tilapia (*Oreochromis* spp.) scales were supplied by El Gaitero SAS (Sopetrán, Colombia). Alcalase® (≥ 2.4 Alcalase® Units (AU)/g, Flavourzyme® (≥ 500 U/g), 37 % hydrochloric acid (HCl), ammonium bicarbonate, ethylenediaminetetraacetic acid (EDTA, Na₂·2H₂O), copper (II) sulphate pentahydrate, sodium acetate, thioflavin T (ThT), 8-anilino-1-naphthalenenesulfonic acid (ANS), juglone (5-hydroxy-1,4-naphthoquinone), 5-fluoro-2'-deoxyuridine, 2',7'-dichlorofluorescin diacetate, and sodium azide (NaN₃) were purchased from Sigma-Aldrich (St Louis, MO, USA). All the other reagents, including disodium phosphate (Na₂HPO₄), potassium dihydrogen phosphate (KH₂PO₄), sodium chloride, magnesium (II) sulfate heptahydrate (MgSO₄·7H₂O), sodium hydroxide and sodium hypochlorite, were of analytical grade (≥ 95 %)

and used without further purification.

## 2.2. Preparation of protein hydrolysate from Tilapia scale

### 2.2.1. Protein extraction from Tilapia scale flour

The Tilapia scale flour (TSF) was prepared according to the literature (Chen et al., 2019). Once produced, the TSF was submitted to bromatological analysis according to the AOAC specifications (AOAC, 2000). The protein extraction process first involved a demineralization of Tilapia scales flour followed by a hydrothermal extraction using ultra-pure water in order to obtain the Tilapia scale gelatin (TSG). The demineralization process was performed similarly to Chen et al. (2019).

### 2.2.2. Protein hydrolysis

The TSG Hydrolysates were obtained as previously described with some modification (El Hajj et al., 2023). The gelatin protein extracted from Tilapia scales was hydrolyzed using two different enzymatic treatments: Alcalase® alone (Alc) and a sequential treatment using Alcalase® followed by Flavourzyme® (Alc + Flav). For each proteolysis experiment, the TSG powder (5 g) was dissolved in 250 mL of ammonium bicarbonate buffer solution (50 mM) using a 1 % (w/w) enzyme-to-substrate ratio (E:S) with the following conditions: 55 °C, pH 8 and pH 7 for Alcalase® and Flavourzyme®, respectively. After 2 h of proteolysis, the corresponding protease was heat inactivated (95 °C, 15 min). In the sequential treatment, Alcalase® was heat inactivated just before Flavourzyme® treatment. Then, the solutions were centrifuged (10,000 g, 15 min, 25 °C) for removing enzymes. Finally, the supernatants were lyophilized (LABCONCO, Kansas City, USA) and stored at -20 °C for further analysis.

The two TSG hydrolysates were further fractionated by membrane ultrafiltration using an ultrafiltration stirred cell 47-mm system (XFUF04701; Millipore, Molsheim, France) under magnetic stirring and pressure of 5 bar of nitrogen. The ultrafiltration process was performed according to El Hajj et al. (2023). The resulting ultrafiltrates (≤ 1 kDa fractions) were lyophilized and stored at -20 °C until further use. The degree of hydrolysis (DH) of the whole hydrolysates only and the peptide concentration of the four hydrolysates (2 whole and 2 ultrafiltrated ones) and TSG, were expressed as mM eq. NH₂ (o-phthal dialdehyde analysis) and displayed in Table S1.

## 2.3. Investigation of peptide-Cu²⁺ interaction

UV-visible and CD spectroscopy measurements were performed at the PhotoNS Platform of the L2CM Laboratory, Université de Lorraine.

### 2.3.1. UV-visible spectroscopy

**UV-visible spectra:** The determination of the UV-visible (UV-vis) spectra of Cu²⁺ ions and peptide-Cu²⁺ complexes formed by peptides present in TSG hydrolysates were recorded on a PerkinElmer Lambda1050 UV-vis-NIR spectrophotometer (Perkin Elmer Corp, Massachusetts, USA) in a quartz cuvette with 1.0 cm path length, in a range of wavelengths varying from 300 to 800 nm at room temperature (25 °C). The samples were prepared by mixing 1500 µL of 50 mM HEPES buffer at pH 7.4 with 500 µL of 5 mM sample solution (expressed as mM eq. NH₂ for hydrolysates) and 62.5 µL of 10 mM CuSO₄ solution in order to have a 1:4 Cu²⁺-to-peptide molar ratio. The coordination modes of peptide-Cu²⁺ complexes were investigated by comparing the shifts in the absorption/UV-vis peaks of Cu²⁺-binding peptides alone with those of the corresponding peptide-Cu²⁺ complex using the same concentration.

**Pyrocatechol violet assay:** The Cu²⁺-chelating ability of the TSG hydrolysates was determined using the pyrocatechol violet (PV) spectrophotometric assay according to Latha et al. (2021), using EDTA as positive control. A 1 mM copper (Cu²⁺) sulphate solution (CuSO₄) was prepared in a 50 mM sodium acetate buffer, at pH 6.0 (using a 1 N HCl solution). The hydrolysate solutions were prepared in a range of
concentrations (0–1 mg/mL) in the former sodium acetate buffer. Then, 237 µL of hydrolysate solution, 50 µL of a 1 mM CuSO₄ solution and 13 µL of 2 mM PV solution prepared in the same buffer were mixed and incubated for 3 min at room temperature. The absorbance was measured at a wavelength of 632 nm corresponding to the PV-copper complex using a spectrophotometer MRX Multiskan Go (ThermoFicher Scientific, Vantaa, Finland) equipped with a microplate reader and 96-well microplates NuncIon™ delta surface (Thermo scientific, Roskilde, Denmark). The Cu²⁺-chelating ability was calculated using the Eq. (1).

$$Cu^{2+} \text{ chelating ability (\%)} = \left[ \frac{A_0 - A_s}{A_0} \right] \times 100 \quad (1)$$

where A₀ is the absorbance of the control (without sample, sample volume replaced by sodium acetate buffer), and Aₛ is the absorbance of either the sample or the positive control (EDTA).

The results were expressed as the half maximal effective concentration (EC₅₀), i.e., the hydrolysate concentration required for 50 % copper (Cu²⁺) chelation.

### 2.3.2. Circular dichroism spectroscopy

Although circular dichroism (CD) spectroscopy is a well-established technique for the characterization of secondary structures in pure proteins and peptides such as the β-sheet formation, yet, its application to complex mixtures, such as enzymatic hydrolysates, is limited due to the heterogeneous nature of the sample. Thus, in our study, CD spectroscopy was instead used to confirm Cu²⁺-peptide coordination, as evidenced by changes in ellipticity beyond 260 nm. This approach provided direct insights into the coordination interactions underlying the self-assembly process. The circular dichroism (CD) spectral analysis of the four TSG hydrolysates (whole and 1 kDa fractions) in the presence and absence of Cu²⁺ ions was performed using a MOS-450 CD spectrometer (Bio-Logic Science Instruments, France) in a quartz cuvette with 1.0 cm path length in a range of wavelengths varying from 260 to 800 nm at room temperature (25 °C). The sample solutions were prepared at 5 mM (expressed as mM eq. NH₂ for hydrolysates) in 50 mM HEPES buffer at pH 7.4 and mixed with 10 mM Cu²⁺ (at 1:4 metal-to-ligand molar ratios, as UV–vis experiment), as previously reported (Csire et al., 2022). The coordination modes of peptide-Cu²⁺ complexes were investigated by comparing the shifts in the absorption/CD peaks of Cu²⁺-binding peptides alone with those of the corresponding peptide-Cu²⁺ complex using the same concentration.

### 2.3.3. Nano-LC-MS/MS identification analysis

To better understand the effect of sequential enzymatic treatment on the production of self-assembled peptide structures and also the effect of Cu²⁺ coordination on the peptide self-assembly, the peptide sequences of TSG hydrolysates were identified using the nano-LC-MS/MS bioinformatic analysis. Only the ≤1 kDa hydrolysate fractions (≤ 1 kDa Alc and ≤ 1 kDa Alc + Flav) were studied since they contained lower number of peptide sequences compared to whole hydrolysates, which facilitates the understanding of the peptide self-assembly of TSG hydrolysates and their chelating properties. The mass analysis were carried out by nano-LC-MS/MS on a Orbitrap Fusin mass spectrometer (Thermo Fisher Scientific, Waltham, MA, USA) coupled to an UltiMate 3000 nanoRSLC (Dionex, Thermo Fisher Scientific, Waltham, MA, USA) as previously reported (Risha et al., 2020).

Then, the raw Thermo data files resulting from the two ≤1 kDa fractions were processed in the Andromeda search engine of MaxQuant™ (version 2.4.13.0), a commonly used proteomic software tool (Boachie et al., 2022). The peptide sequences were searched against a restricted Tilapia proteins database (Oreochromis niloticus) containing 30 entries obtained from UniProtKB (https://www.uniprot.org/, accessed on 27th April 2024, Supplementary data, Table S2). The peptides identification was achieved by comparing the experimental fragment-ion mass value of the precursor ions with the theoretical fragment

masses; these latter ones were obtained from the protein sequences database and determined from the unspecified digestion rule with a mass tolerance of 10 ppm. The parameters of database searches were set up as previously reported (Table S3, Boachie et al., 2022).

In order to compute the physico-chemical properties of peptide sequences identified previously (e.g., length, amino acids composition with both individual and groups of AA, isoelectric point (pI) and grand average of hydropathicity (GRAVY) index), the MaxQuant™ output tables containing the identified peptide sequences were then loaded in the R software, version 4.0.2 (R Foundation for Statistical Computing, Viena, Austria) using a Peptides R package (Osorio et al., 2015).

## 2.4. Peptide self-assembly characterization

### 2.4.1. Thioflavin T binding assay

The effect of Cu²⁺ coordination on the amyloid fibril structures was investigated in the presence of TSG hydrolysates using the thioflavin T (ThT) analysis (Abioye et al., 2022). This analysis was conducted at 1:4 Cu²⁺-to-peptide (hydrolysate) molar ratio. The TSG hydrolysate solution (60 µL, 4 mM eq. NH₂) investigated in the absence (60 µL of ultrapure water) or presence of copper ions (60 µL, 1 mM CuSO₄) was mixed with 10 µL ThT solution (10 µM in ultrapure water) and stirred for 3 min. The fluorescence intensity of ThT alone, ThT with Cu²⁺ ions, ThT with hydrolysates and hydrolysates mixed with Cu²⁺ was measured in a black 96-well microplates with clear bottoms (6,005,570, PerkinElmer, Waltham, MA, USA), at a final volume of 200 µL. Samples were evaluated in triplicates using the Spark multimode microplate reader (Tecan, Stockholm, Sweden); the fluorescence intensity was measured from the bottom of the plate, at an excitation wavelength of 430 nm and an emission wavelength of 480 nm at 25 °C.

### 2.4.2. ANS binding assay

The variation in surface hydrophobicity of the TSG hydrolysates was measured using 8-anilino-1-naphthalenesulfonic acid (ANS) as a fluorescent probe as previously reported (Hayakawa & Nakai, 1985). The TSG hydrolysate samples were investigated in the absence (60 µL of hydrolysate solution, copper solution replaced by ultrapure water) and presence of copper ions (1:4 metal-to-ligand molar ratio using a 1 mM CuSO₄ solution in ultrapure water, vol, 60 µL) and were diluted in series with phosphate buffer (0.1 M, pH 7) to obtain hydrolysate concentrations ranging from 5 to 0.1 mM (eq. NH₂). Then, 200 µL of each sample solution were reacted with 10 µL of ANS solution (8 mM ANS in 0.1 M phosphate buffer, pH 7). The fluorescence intensity was measured in a black 96-well microplates with clear bottoms (6,005,570, PerkinElmer, Waltham, MA, USA) at the excitation wavelength of 390 nm and the emission wavelength of 470 nm using the Spark multimode microplate reader (Tecan, Stockholm, Sweden). The index of surface hydrophobicity (S₀) indicates a relative tendency of sample to prefer a nonaqueous environment over an aqueous one). This S₀ value was determined as the value of the slope of the plot presenting the fluorescence intensity vs. the hydrolysate concentration, using linear regression.

### 2.4.3. Dynamic light scattering measurements

The TSG hydrolysates were investigated by dynamic light scattering (DLS) for their particle size distribution and polydispersity index (PDI) in the absence and presence of copper ions at 1:4 metal-to-ligand molar ratio. Experiments were carried out at 25 °C using a Zetasizer Nano ZS (Malvern Instruments Ltd., Worcestershire, UK) according to the method described by Abioye et al. (2022). The samples were prepared at 4 mM eq. NH₂ with ultrapure water (pH 7, refractive index 1.33, viscosity 0.88 cP and dielectric constant 78.5), similarly as in section 2.4.1 with a final volume of 1 mL (500 µL of hydrolysate, 500 µL of Cu²⁺ solution), in the absence of Cu²⁺, 500 µL of ultrapure water were added. Subsequently, the resulting solution were transferred into a plastic disposable cuvette (Malvern Instruments Ltd., Worcestershire, UK) for DLS measurements.
The DLS effect was analyzed with the Smoluchowski model at F(ka) 1.50 (term of Henry's equation) and backscattered angle of 173°.

### 2.4.4. Mechanical properties measurements

To evaluate the effect of Cu²⁺ coordination on the mechanical properties (i.e., G' elastic and G'' loss moduli) of the TSG hydrolysates, rheology experiments were carried out. The amplitude sweeps and frequency sweeps analyses were conducted using the Discovery Hybrid Rheometer HR-2 (TA Instruments Ltd., New Castle, USA). This equipment contained a cone (2°, 40 mm diameter, 50 µm truncation gap) and a Peltier plate steel measuring system, separated with a gap height set to 1 mm, according to the method of Abioye et al. (2022). The solution of TSG hydrolysates in the presence and absence of Cu²⁺ ions (at 1:4 metal-to-ligand molar ratio, prepared as in section 2.4.3) were delicately loaded onto the lower testing plate and equilibrated for 5 s at 25 °C. The amplitude sweeps and frequency sweeps were recorded as a function of mechanical strain (0.001–5000 %, at a fixed frequency of 10 rad/s) and with an angular frequency (0.1–100 rad/s, at a fixed strain of 1 %), respectively. Before starting a test, the excess of sample was removed with a Kimwipe to ensure a clear and smooth interface.

### 2.4.5. Transmission Electron microscopy

To gain further information about the particular structures of the self-assembled peptides present in the TSG hydrolysates, the morphology of only two hydrolysates (the Alc + Flav and ≤ 1 kDa Alc, based on former mechanical properties analysis) was studied by transmission electron microscopy (TEM) as formerly described (Abioye et al., 2022; Schindelin et al., 2012). Briefly, a 10-µL aliquot of TSG hydrolysate solutions (4 mM eq. NH₂ in water) in the presence and absence of copper ions at 1:4 metal-to-ligand molar ratio (prepared in the same way as in section 2.4.1) was placed on 300-mesh Formvar-carbon coated copper grid and incubated for 5 min for absorption. The sample in excess was blotted with a Kimwipe, and the grids were finally counterstained with TEM staining solution (Micro To Nano®, Haarlem, Netherlands) for 1 min in the dark. The excess stain was blotted again, and the loaded grids were examined using the JEM-1400 Flash Electron Microscope (JEOL, Tokyo, Japan) at an accelerating voltage of 120 kV. Imaging was performed using ImageJ 1.53c software (NIH, Bethesda, MD, USA) under standard operating conditions (Abioye et al., 2022).

## 2.5. Assessment of antioxidant activity in *C. elegans* in vivo model

### 2.5.1. Handling and synchronization

The in vivo antioxidant assay was carried out by the method of Sangha et al. (2013) with some modifications. Briefly, the wild-type *C. elegans* strain (isolate N2 from Bristol, UK) was maintained at 22 ± 2 °C on nematode growth medium (NGM, Mt. Prospect, IL, USA). This medium contained 200 µL of *Escherichia coli* (OP50) (Caenorhabditis Genetics Center, University of Minnesota, Minneapolis, MN, USA) as food for the *C. elegans*. To synchronize the nematodes at a consistent larval stage for further assays, the *C. elegans* eggs were collected. The nematodes pass through four larval life stages (L1, L2, L3, and L4), primarily characterized by increasing worm size (Mudd & Liceaga, 2022). On the third day of growth, the L4 stage adult nematodes were washed 2 times with M9 buffer solution pH 7 (6 g/L Na₂HPO₄, 3 g/L KH₂PO₄, 5 g/L NaCl, 0.215 g/L MgSO₄·7H₂O) to remove both contaminants and remaining *E. coli* OP50. Then, the samples were centrifuged at 2602 g at 4 ± 1 °C for 3 min using a Lynx 4000 Centrifuge (ThermoFisher, Canada). After two rounds of washing, a first one with M9 buffer containing 1 M NaOH and a second one with M9 buffer containing both 1 M NaOH and 5 % NaClO to lyse them, the eggs were washed 2 more times with M9 buffer solution only. Thereafter, the eggs were placed on fresh NGM plates supplemented with 200 µL *E. coli* OP50 and incubated at 22 °C ± 2 °C until further experiments. All experiments were carried out at this temperature based on literature data (Guo et al., 2020; Mudd & Liceaga, 2022), which demonstrated that 22 °C is within

the optimal growth range for *C. elegans*, promoting healthy development and consistent experimental conditions.

### 2.5.2. Mean life and survival assay

The oxidative stress resistance assay was performed as previously described (Sangha et al., 2013) with slight modifications. The synchronized nematodes were divided into distinct groups: a negative control group (without hydrolysate sample, 200 µL of water), a positive control group (EDTA at 0.5 mM, 200 µL), and the sample group (200 µL of each investigated TSG hydrolysate at 2 mM eq. NH₂). Approximately 60 ± 5 L2 *C. elegans* nematodes were exposed to each group treatment and then transferred to fresh NGM plates containing 100 µL of 1 mM copper (Cu²⁺) sulphate solution, a standard dose to induce oxidative stress. For each group (i.e., negative control, positive control and sample group), the nematodes were counted every hour for 8 h, assessing their viability by pricking them with a platinum wire. Adult L4 stage nematodes from the same group (corresponding to the same plates) were synchronized, and the eggs obtained were transferred to fresh NGM plates containing *E. coli* in order to repeat the above-mentioned process (first generation: G1). The plates were incubated at 22 °C ± 2 °C until the nematodes reached the L4 stage again. On total, this sequence (egg, larval L1 to larval L4, adult) was repeated to evaluate the oxidative stress resistance over three consecutive generations (G1 to G3). The *C. elegans* survival and lifespan curves were analyzed by Kaplan-Meier method and log-rank test using GraphPad Prism version 8.0, GraphPad Software (La Jolla, California, United States, www graphpad com). All experiments were conducted in triplicate.

### 2.5.3. Reactive oxygen species production by fluorometry

The ability of TSG hydrolysates to reduce the reactive oxygen species (ROS) production in *C. elegans* model was carried out using fluorometry. The G1 synchronized populations of worms were harvested and washed before being resuspended in M9 buffer. The eggs were placed on new NGM plates with 200 µL *E. coli* OP50 bacteria and 200 µL of samples (ultrapure water, 0.5 mM EDTA and hydrolysates at 2 mM eq. NH₂: Alc, Alc + Flav, ≤ 1 kDa Alc and ≤ 1 kDa Alc + Flav) and incubated at 22 ± 2 °C until reaching the L3 stage. The ROS production was stimulated by exposure to a mixed solution of 200 µL of 1 mM copper (Cu²⁺) sulfate. A 250 µM 2',7'-dichlorofluorescin diacetate (DCF) stock solution was prepared in DMSO and diluted in the assay buffer to achieve the final concentration of 100 µM for the detection of general oxidative stress. The worms were then incubated at 22 ± 2 °C for 2 h with the DCF solution, allowing its penetration into *C. elegans* and its reaction with ROS. The fluorescence intensity was measured using a Spark multimode spectrophotometer (Tecan, Stockholm, Sweden) with an excitation and an emission wavelength set at around 485 nm and 535 nm, respectively.

### 2.5.4. Reactive oxygen species production by fluorescence microscopy

In order to measure the ROS production in *C. elegans* model, fluorescence microscopy analysis were carried out in generation 1 G1 using the method reported by Yoon et al. (2018) with some modifications. The eggs of adult nematodes synchronized were placed on new NGM plates with 200 µL *E. coli* OP50 bacteria and 200 µL of samples (ultrapure water, 0.5 mM EDTA and hydrolysates at 2 mM eq. NH₂: Alc, Alc + Flav, ≤ 1 kDa Alc and ≤ 1 kDa Alc + Flav), followed by incubation at 22 ± 2 °C until reaching the L3 stage (24–36 h). Then, about 15 nematodes were transferred to new NGM plates added with 50 µL of 100 µM 5-fluoro-2'-deoxyuridine (to prevent offspring production) and 100 µL of 1 mM copper (Cu²⁺) sulfate to induce oxidative stress. The nematodes were incubated at 22 °C ± 2 °C for 12 more hours. Upon reaching L3 stage, the nematodes were transferred to a new NGM plates supplemented with 200 µL of DCF (100 µM) -containing M9 solution and incubated in the dark at room temperature for 1.5 h. Thereafter, 50 µL of M9 solution containing 10 mM sodium azide (NaN₃ used as an anesthetic) was added, and after 1 h of incubation the nematodes were transferred to new NGM plates. The plates were placed on a fluorescence
microscope using the Axio Imager 2 microscope equipped with an Axio 506 camera. Zen 2.3 pro software in order to capture the fluorescence of the oxidized DCF product.

## 2.6. Statistical analysis

The analyses of PV spectrophotometry, ThT, DLS, ANS and mechanical properties were conducted at least three times, and all the data

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** UV-visible and CD measurements of the peptide-Cu²⁺ interaction of different TSG hydrolysates. (A-B) Alc, (C-D) Alc + Flav, (E-F) ≤ 1 kDa Alc, (G-H) ≤ 1 kDa Alc + Flav. (I-J) Proposed modes of coordination for the copper chelating peptides present in the TSG hydrolysates based on CD data (adapted from Osz et al., 2002). Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate. Horizontal arrow indicates shift in wavelength after formation of peptide-Cu²⁺ complex while vertical arrow indicates Cotton effect of CD spectra.</figcaption></figure>
were presented as means ± standard deviation. The statistical analyses were one-way analysis of variance (ANOVA), and significant differences between means of samples were determined by Fisher's multiple range test. The differences at *p* < 0.05 were considered significant. The statistical calculations were conducted using the software Statgraphics Centurion XVI version 16.1.03 (Statgraphics Technologies Inc., Virginia, USA).

# 3. Results and discussion

## 3.1. Cu²⁺ coordination properties

### 3.1.1. Peptide-Cu²⁺ complex formation by UV-Vis and CD

UV-vis and CD were used for the structural characterization of complexes between peptides present in TSG hydrolysates and Cu²⁺ ions in solution at physiological pH (7.4). These techniques provide both d-d and charge transfer (CT) transitions that allow the determination of the binding mechanism of the formed complexes. Indeed, the characteristic spectral changes observed, such as shifts in absorbance and ellipticity, are indicative of Cu²⁺ coordination within the peptide complexes, confirming the presence of Cu²⁺ as the predominant species in the complexes. The UV-vis spectroscopy data shows that upon the Cu²⁺ complexation through peptides present in TSG hydrolysates and their ≤1 kDa fractions, the formation of peptide-Cu²⁺ complex results in a significant shift (horizontal arrow) of the initially d-d transition band centred from 805 to 580-607 nm (Fig. 1A, C, E, G, and Table S4) in all the hydrolysates, consistent with the coordination of three nitrogen donor atoms (3 N-coordinated complex, (Mital et al., 2020). Moreover, in addition to the d-d transition (560-580 nm), the CD data (Fig. 1B, D, F, H-and Table S4) reveal the presence of CT transitions with negative (280 nm) and positive (320 nm) Cotton effects which are characteristic of N⁻ → Cu²⁺ (amide nitrogen) and S → Cu²⁺ (methionyl residues), respectively (Osz et al., 2002). These CT transitions are observed in all hydrolysates (whole and < 1 kDa) and the intensities follow the same trend in most cases. In our study, the Cu²⁺ binding site in all hydrolysates can be described either by the (NH₂, N⁻, N⁻, COO⁻)-coordination mode in the case of the peptides containing N-terminal and/or internal Met residues, or (NH₂, N⁻, N⁻, S⁻)-coordination mode for peptides containing C-terminal Met residues (S → Cu²⁺) as previously reported (Fig. 1I, adapted from Osz et al., 2002).

Beyond the insights provided by CD spectra into the coordination modes of peptide-Cu²⁺ complexes in TSG hydrolysates, further interpretations can be made regarding peptide self-assembly or aggregation. Notably, a negative band located between 270 and 300 nm appears in all four TSG hydrolysates upon Cu²⁺ coordination (Fig. 1B, D, F, H).

This band strongly suggests the existence of supramolecular assembly (self-assembled peptides), as previously documented (Fortunato & Mba, 2021). Therefore, additional techniques are needed to gain a deeper understanding of the effect of Cu²⁺ coordination on self-assembled peptides present in TSG hydrolysates.

### 3.1.2. Cu²⁺-chelating ability

The pyrocatechol violet assay quantitatively validated the ability of the hydrolysates to chelate Cu²⁺, providing additional evidence for their interaction and confirming that Cu²⁺ remains the dominant oxidation state in the system. The Cu²⁺ chelation curves of TSG hydrolysates show a concentration-dependent equilibrium reaction, with a final Cu²⁺-chelating ability of 82 %, 75 %, 73 %, and 70 % for ≤1 kDa Alc + Flav, Alc + Flav, ≤ 1 kDa Prot, and Alc hydrolysates, respectively (Fig. 2A). From Fig. 2A, the EC₅₀ values of Cu²⁺-chelating ability were calculated for all hydrolysates and presented in Fig. 2B. According to the EC₅₀ values (i.e., lower values mean higher chelating ability), the Cu²⁺-chelating peptides are released from TSG in the single hydrolysis by Alcalase® (Alc). Yet, after sequential hydrolysis by Flavourzyme® (Alc + Flav), the Cu²⁺-chelating peptide production seems to be significantly (*p* < 0.05) higher, suggesting that small-sized peptides are more likely to be Cu²⁺ chelators. The Cu²⁺-chelating ability of TSG hydrolysates correlates positively with their DH and the peptide concentration expressed as mM eq. NH₂ (Table S1). Note that the EC₅₀ values of ≤1 kDa hydrolysates are lower (higher chelating ability) than those of their corresponding whole hydrolysates (*p* < 0.05), indicating that both sequential treatment and ultrafiltration process at 1 kDa enhance the Cu²⁺-chelating ability of TSG hydrolysates. This ability can be explained by the DH and also by their amino acid content. Both the amino or carboxyl group available at each terminal part of a peptide as well as other amino and carboxyl groups present in other amino acids (i. e., acidic amino acids: aspartate, glutamate; basic amino acids: lysine, arginine, and histidine, and sulfur amino acids: methionine and cysteine) can explain such ability. Similar to the literature, our results again demonstrate that peptides with low MW (≤ 1 kDa) have the highest metal-chelating ability. This trend was previously observed in various protein hydrolysates derived from Pacific cod skin gelatin (Wu et al., 2017), mung bean protein (Budseekoad et al., 2018) and casein (Miao et al., 2019).

### 3.1.3. Nano-LC-MS/MS bioinformatics analysis

To better understand how sequential enzymatic treatment influences the formation of self-assembled peptide structures and to gain further insight into the role of Cu²⁺ coordination in peptide self-assembly, the peptide sequences in TSG hydrolysates were identified using nano-LC-

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Cu²⁺-chelating ability of different TSG hydrolysates determined with pyrocatechol violet assay. (A) Chelating ability as function of hydrolysate concentration. (B) EC₅₀ values expressed as the quantity (mg/mL) of hydrolysate that is required to chelate 50 % of Cu²⁺ ions from CuSO₄. Different letters indicate significant differences (*p* < 0.05). Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
MS/MS bioinformatics analysis. Only the ≤1 kDa hydrolysate fractions (≤1 kDa Alc and ≤1 kDa Alc + Flav) were evaluated since they contain fewer peptide sequences than the whole hydrolysates, making it easier to understand their self-assembly pattern and their chelating properties. In addition, these ≤1 kDa hydrolysate fractions showed the highest Cu²⁺-chelating ability.

The peptide sequences identified in ≤1 kDa Alc and ≤1 kDa Alc + Flav hydrolysates are shown in Table S5. A total of 88 peptides were identified from the single treatment (≤1 kDa Alc) and 34 peptides from the sequential treatment (≤1 kDa Alc + Flav), with 17% (15 peptides) of the peptide sequences overlapping (Fig. 3A, Table S5). On all identified peptides, 11 peptides in ≤1 kDa Alc and 5 peptides in ≤1 kDa Alc + Flav contain His or Met residues (Table S6). These peptides could serve as potential Cu²⁺ chelating candidates because they contain imidazole (His) or thioether (Met) groups, respectively, which are known for their ability to complex Cu²⁺ ions (Sóvágó et al., 2012). Moreover, in our study, the ≤1 kDa fractions, with the highest Cu²⁺-chelating ability, have 34% and 41% of peptide sequences containing the GPA motif over the total peptide sequences identified for ≤1 kDa Alc and ≤1 kDa Alc + Flav hydrolysates, respectively (Table S5). However, several His-containing peptides as well as peptides with such a GPA motif have been previously reported for their high metal-chelating properties in protein hydrolysates produced from Alaska pollock skin gelatin (AGPAGPR, GPAGPR, GPAGPHGPPG, (Guo et al., 2015), Pacific cod skin (GPAGPHGPPGKDGR, AGPHGPPGKDGR, AGPAGPAGAR (Wu et al., 2017) and Tilapia skin collagen (GPAGPAGEK, Lin et al., 2021). Altogether, the presence of His or Met-containing peptides and peptides with GPA motif supports the high Cu²⁺-chelating ability of ≤1 kDa TSG fractions determined in the PV assay (Fig. 2).

Various intrinsic factors, such as peptide length, amino acid composition and physicochemical properties of peptide sequences, can influence copper-induced peptide self-assembly (Abioye et al., 2024). Therefore, the size, AA composition, pI and GRAVY index were also determined for all identified peptides (based on the peptide list in Table S5). As shown in Fig. 3B, more than 50% of the peptide sequences have between 7 and 11 amino acid residues. Meanwhile, the AAs composition (Fig. 3C) of ≤1 kDa fractions reveals that the identified peptides are rich in glycine, proline and alanine, which is similar to the study of Zhang et al. (2019) in hydrolysates obtained from Tilapia scales (Oreochromis niloticus). Besides, in terms of residue types, a high content of tiny (Ala, Cys, Gly, Ser, Thr), small (Ala, Cys, Asp, Gly, Asn, Pro, Ser, Thr and Val) and nonpolar (Ala, Cys, Phe, Gly, Ile, Leu, Met, Pro, Val, Trp, Tyr) AAs is demonstrated in both hydrolysates (Fig. 3D).

Peptide self-assembly can be driven by noncovalent intermolecular interactions, especially those involving hydrophobic amino acid residues such as the nonpolar AAs (Leu and Ala), π-π stacking with aromatic AAs (Phe, Trp, and Tyr), hydrogen bonding (via amide, amino, and carboxyl groups), and electrostatic interactions involving both acidic (Asp and Glu) and basic AAs (His, Lys, and Arg; Li et al., 2023). Therefore, TSG hydrolysates may exhibit interesting peptide self-assembly properties.

Regarding the physicochemical properties calculated from the sequences listed in Table S5 (all peptide sequences identified), Fig. 3E illustrates that in both hydrolysates, most of the peptides have a pI value comprised between 3.7 and 6.4 (more than 50%). Therefore, at neutral pH 7 (as in our study), the peptides exhibit an increase in negative charge due to the complete deprotonation of aspartic acid (pKa: 3.8) and glutamic acid (pKa: 4.2) residues. This increase in negative charge could promote the formation of self-assembled peptide structures through electrostatic interactions with positively charged amino acid residues.

Furthermore, as shown in Fig. 3F, the hydrophobicity of the identified peptides was assessed using the GRAVY index (values below 0 indicate hydrophilicity and values above 0 indicate hydrophobicity, (Boachie et al., 2022). In our study, the GRAVY index value reveals that although both hydrolysates (≤1 kDa Alc and ≤1 kDa Alc + Flav) contain a mixture of hydrophilic and hydrophobic peptides (GRAVY

index ranging from -1.8 to 1), there is a noticeable tendency towards negative GRAVY index values in both hydrolysates, indicating low hydrophobicity. High hydrophobicity promotes attractive hydrophobic interactions between peptides, leading to the formation of stable, ordered nanoarchitectures from food hydrolysates. At the same time, peptides in TSG hydrolysates that contain hydrophilic regions in their sequences could be excellent candidates for the design of peptide-based self-assembled nanostructures, which are commonly used in drug delivery applications (Vahedifar & Wu, 2022).

Taken together, a comprehensive understanding of the relationship between the size, AAs composition, charge of peptides and their hydrophobicity profile with Cu²⁺ coordination in peptide self-assembly of TSG hydrolysates will be based on the present study (section 3.2).

## 3.2. Physico-chemical properties of self-assembled peptides

To decipher the actual role of Cu²⁺ coordination through TSG hydrolysates on the formation of self-assembled peptide structures, a wide range of analytical techniques such as ThT fluorescence, ANS, DLS, rheology and TEM were studied in the presence and absence of Cu²⁺ ions.

**Fluorescence.** The ThT fluorescence was performed to observe the presence of amyloid-like fibrils in TSG hydrolysates. The Fig. 4A reveals the variation of ThT fluorescence as a function of hydrolysate. Irrespective of the hydrolysate, maximum fluorescence intensities are obtained for hydrolysates treated with a single enzyme (Alc and ≤1 kDa Alc), suggesting that sequential hydrolysis with Flav reduces the formation of amyloid-like fibrils (β-sheet fibrils). Interestingly, the presence of these β-sheet fibrils is reduced upon Cu²⁺ coordination, confirming the formation of other types of self-assembled structures such as amorphous aggregates. This transition might be attributed to the unique interactions between Cu²⁺ ions and the peptide backbone or specific amino acid residues present in gelatin hydrolysates. In our study, the metal ion's interaction with His-containing peptides from gelatin likely occurs via histidine (i.e., SGPRGPAGPH, Table S5). This interaction leads to changes in the overall spatial arrangement of peptides during self-assembly due to their complex geometry, stoichiometry, and affinity with Cu²⁺. These factors may disrupt the organized β-sheet conformations (Sharma et al., 2019). Indeed, β-sheets are primarily stabilized by hydrogen bonds. Nevertheless, Cu²⁺ coordination introduces peptide-metal interactions that can compete with these stabilizing forces, favoring the formation of aggregates with less defined structure (Fortunato & Mba, 2021). Furthermore, it is possible that Cu²⁺ coordination may induce π-π stacking changes of peptides containing aromatic AAs (i.e., FPGLPGPS, FVSQPL and PFRMY, Table S5). Changes in these interactions may not favor the formation and stabilization of β-sheet structures (Shen et al., 2014). Similar to the ThT assay, the hydrophobicity of TSG hydrolysates and their complexes with Cu²⁺ was evaluated by the ANS probe assay (Fig. 4B). Note that the sequential enzymatic hydrolysates (Alc + Flav and ≤1 kDa Alc + Flav) have lower surface hydrophobicity (S₀) than the single enzymatic hydrolysates (Alc and ≤1 kDa Alc), implying that small-sized peptides have higher solubility than larger-sized peptides in TSG hydrolysates. Meanwhile, in the present study, the involvement of Cu²⁺ coordination corresponds to a significant decrease in surface hydrophobicity (S₀ of peptide-Cu²⁺ complex = 0), suggesting the presence of highly soluble complexes between peptides in TSG hydrolysates and Cu²⁺. This observation confirms a trend observed throughout the ThT and ANS analysis, indeed, higher surface hydrophobicity may lead to a greater tendency to form amyloid aggregates (Es-Haghi et al., 2012). Besides, ANS data are consistent with the physicochemical properties of the peptides identified in the 1 kDa fractions by nano-LC-MS/MS and bioinformatic analysis, where the single enzymatic hydrolysate (Alc) showed a higher hydrophobicity profile (lower solubility) than the sequential hydrolysate (Alc + Flav) (Fig. 3F).

**DLS.** The average particle size (d, nm), the particle size distribution
<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Nano-LC-MS/MS identification of peptide sequences present in different TSG hydrolysates. (A) number of peptides identified, (B) percentage of lengths of identified peptides, (C) distribution of amino acid (AAs) residues of identified peptides, (D) percentage of AAs residue group types, (E) distribution of peptides isoelectric point (pI), and (F) distribution of hydropathicity GRAVY index. Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate. Tiny: alanine, cysteine, glycine, serine, threonine; small: alanine, cysteine, aspartic acid, glycine, asparagine, proline, serine, threonine and valine; aliphatic: alanine, isoleucine, leucine and valine; Aromatic: phenylalanine, histidine, tryptophan and tyrosine; non-polar: alanine, cysteine, phenylalanine, glycine, isoleucine, leucine, methionine, proline, valine, tryptophan and tyrosine; polar: aspartic acid, glutamic acid, histidine, lysine, asparagine, glutamine, arginine, serine and threonine; charged: aspartic acid, glutamic acid, histidine, lysine and arginine; basic: histidine, lysine and arginine; acidic: aspartic acid and glutamic acid.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Thioflavin T (ThT) intensity, surface hydrophobicity ($S_o$), particle size, polydispersity index (PDI) and particle size distribution of different TSG hydrolysates upon the Cu²⁺ complexation. (A) Thioflavin T (ThT) assay, (B) Surface hydrophobicity ($S_o$), (C) average particle size, (D-G) particle size distribution, (H) PDI values. Different letters indicate significant differences ($p < 0.05$). Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; $\le 1$ kDa: 1 kDa ultra-filtrated hydrolysate. *means surface hydrophobicity $S_o$: 0. Horizontal arrow indicates shift in particle size of peptides upon the Cu²⁺ coordination.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Effect of Cu²⁺ complexation on mechanical strength and viscoelastic behaviour study by amplitude sweeps and frequency sweeps measurements of different TSG hydrolysates. (A-D) amplitude sweeps, (E-H) frequency sweeps. G' and G'' are the elastic modulus and loss modulus, respectively. Mechanical strength indicated by the cross-over point (cp, G' = G''), while gel formation indicated by G' > G'' (blue above red and dashed blue above dashed red without and with Cu²⁺ ions, respectively. Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate. Blue lines represent the elastic modulus (G') and red lines represent the loss modulus (G''). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Transmission electron microscopy (TEM) of TSG hydrolysates (only Alc + Flav and ≤ 1 kDa Alc) with and without Cu²⁺ ions. Scale bars represent 0.5 µM. Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate.</figcaption></figure>

<table><caption>**Table 1**
Effects of Cu²⁺ coordination by EDTA and peptides present in TSG hydrolysates on the lifespan-extension of Cu²⁺-exposed nematodes.</caption><thead><tr><th rowspan="2">Sample</th><th colspan="6">Mean life (h)</th></tr><tr><th>G1</th><th>%</th><th>G2</th><th>%</th><th>G3</th><th>%</th></tr></thead><tbody><tr><td>(– control)</td><td>23.25</td><td></td><td>23.16</td><td></td><td>24.1 ±</td><td></td></tr><tr><td>Cu²⁺</td><td>± 0.06<sup>c</sup></td><td></td><td>± 0.05<sup>d</sup></td><td></td><td>0.01<sup>c</sup></td><td></td></tr><tr><td>(+ control)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>[EDTA-Cu²⁺]</td><td>25.68</td><td>10.45</td><td>26.78</td><td>15.63</td><td>25.68</td><td>10.88</td></tr><tr><td></td><td>± 0.26<sup>d</sup></td><td></td><td>± 0.01<sup>e</sup></td><td></td><td>± 0.02<sup>e</sup></td><td></td></tr><tr><td>[Alc-Cu²⁺]</td><td>26.77</td><td>15.13</td><td>21.47</td><td>-7.46</td><td>25.06</td><td>8.2</td></tr><tr><td></td><td>± 0.01<sup>e</sup></td><td></td><td>± 0.03<sup>e</sup></td><td></td><td>± 0.03<sup>d</sup></td><td></td></tr><tr><td>[Alc + Flav-Cu²⁺]</td><td>20.72</td><td>-10.88</td><td>20.96</td><td>-9.49</td><td>26.78</td><td>15.63</td></tr><tr><td></td><td>± 0.01<sup>a</sup></td><td></td><td>± 0.01<sup>b</sup></td><td></td><td>± 0.01<sup>f</sup></td><td></td></tr><tr><td>[≤ 1 kDa Alc-Cu²⁺]</td><td>21.45</td><td>-7.74</td><td>23.3 ± 0.18<sup>d</sup></td><td>0.6</td><td>23.38 ± 0.02<sup>b</sup></td><td>-0.94</td></tr><tr><td></td><td>± 0.06<sup>b</sup></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>[≤ 1 kDa Alc + Flav-Cu²⁺]</td><td>23.18 ± 0.01<sup>c</sup></td><td>-0.30</td><td>19.41 ± 0.15<sup>a</sup></td><td>-16.19</td><td>22.75 ± 0.06<sup>a</sup></td><td>-1.77</td></tr></tbody></table>

Data are expressed as the mean ± standard deviation. Values with different lowercase letters in the same column indicate significant differences at *p* < 0.05. Alc: Alcalase® hydrolysate; Alc + Flav: Alcalase® followed by Flavourzyme®; ≤ 1 kDa: 1 kDa ultrafiltrated hydrolysate; G1: first generation; G2: second generation; G3: third generation.

affect the ROS level of *C. elegans* (Fig. 7-G). This phenomenon could be due to a weak interaction between peptides and Cu²⁺ ions in these hydrolysates (i.e., Alc + Flav hydrolysate and its 1 kDa fraction). Taken together, these results interestingly confirm that the antioxidant properties of Alc hydrolysate associated with its Cu²⁺-binding ability, are relevant to prolonging the lifespan of worms by reducing ROS levels. Indeed, in agreement with our results, Chen et al. (2023), Shi et al. (2021) and Guo et al. (2020) found that the intracellular ROS level of *C. elegans* was negatively correlated with the lifespan of the worm co-treated with sea cucumber protein, marine protein and fish protein hydrolysates, respectively; this is due to the accumulation of oxidative damage that affects the aging of *C. elegans*.

## 4. Conclusion and perspectives

In this study, the peptides from TSG hydrolysates prepared with Alcalase® and Alcalase® followed by Flavourzyme®, respectively, were characterized and identified for their Cu²⁺-chelating, self-assembly and in vivo antioxidant properties. For the first time, to the author's knowledge, we carried out a physico-chemical characterization of self-assembled peptides in TSG hydrolysates tuned through Cu²⁺ coordination. We found that Cu²⁺ coordination by His and Met-containing peptides present in TSG hydrolysates contributes to the formation of tunable supramolecular assemblies. In this work, we demonstrated that the stiffness of supramolecular materials from TSG hydrolysate can be greatly enhanced by using Cu²⁺ coordination approach. The formation of multiple metal coordination bonds in each cross-linking ligand (peptide-Cu²⁺) compared to the single bond cross-linkers (hydrolysate), allows them to exhibit greater structural strength. Moreover, the study revealed the in vivo antioxidant properties based on Cu²⁺-induced oxidative stress of TSG hydrolysates using the nematode *C. elegans* as a model organism. Peptides present in TSG hydrolysate produced with Alcalase® were found to significantly reduce endogenous ROS levels through Cu²⁺ coordination, which prolonged the lifespan of *C. elegans*. The results of this study suggest that red Tilapia scale gelatin can be used to prepare Cu²⁺-chelating peptides endowed with tuned self-assembly and antioxidant properties through a single enzymatic treatment with Alcalase®. These peptides can serve as theoretical models for the development of innovative food-derived functional nanomaterials in the fields of biomedicine, food, and cosmetics. Note that the pH variations may affect the stability and binding affinity of Cu²⁺ to the peptides, since protonation or deprotonation of coordinating amino acid residues may modify the complex geometry and functionality. Likewise, the presence of competing ions such as Zn²⁺, Fe³⁺, or Mg²⁺ in biological or environmental matrices could interfere with Cu²⁺ binding and affect the structural integrity of the complexes. Therefore, future studies will aim to address these factors by evaluating the stability of peptide-Cu²⁺ complexes over a range of pH values and in the presence of physiologically relevant ions. These investigations would not only improve the understanding of the stability of the complexes under variable conditions, but also provide valuable insights for their daily application. Additionally, a comparative study using different metal ions could be interesting, especially in terms of self-assembly properties of food-derived peptides upon metal coordination. In fact, this is a potential research avenue to further enrich the mechanistic understanding of peptide self-assembly processes from food proteins, as there is currently no literature available that addresses this specific comparison. Therefore, this remains a promising area for future research. Finally, a better understanding of self-assembly triggered by peptide to Cu²⁺ molar ratio in TSG peptides is needed to design novel food-derived self-assembled peptides under the most suitable conditions.

### CRediT authorship contribution statement

**Jairo Andrés Camaño Echavarría:** Writing – original draft, Software, Resources, Methodology, Formal analysis, Data curation, Conceptualization. **Raliat O. Abioye:** Methodology, Data curation. **Samanta Sarahí Reyes:** Methodology, Data curation. **Katalin Selmeczi:** Writing – review & editing, Methodology. **Laetitia Canabady-Rochelle:** Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Chibuike C. Udenigwe:** Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition, Formal analysis, Data curation, Conceptualization.

### Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence
<figure><img src="image_10.png" /><figcaption>**Fig. 7.** Alleviation of oxidative stress by EDTA, Alc, Alc + Flav, ≤ 1 kDa Alc and ≤ 1 kDa Alc + Flav hydrolysates in oxidation-damaged *C. elegans*. (A) Effects of Cu²⁺ coordination by EDTA and peptides present in TSG hydrolysates on ROS level in Cu²⁺-exposed nematodes. L3-stage nematodes were treated with and without samples treatment (negative control nematodes) for 24 h at 22 ± 2 °C, and then exposed to 1 mM Cu²⁺ sulphate for another 12 h. (B-G) Representative images of Cu²⁺-exposed L3-stage nematodes untreated control (only with Cu²⁺), EDTA, Alc, Alc + Flav, ≤ 1 kDa Alc and ≤ 1 kDa Alc + Flav-treated groups captured by an Axiocam 506 camera. Data are expressed as ROS level mean obtained from three independent experiments with approximately 15 worms in each experimental group. Different letters indicate significant differences (*p* < 0.05).</figcaption></figure>

the work reported in this paper.

## Acknowledgements

The authors thank the C.C.U. research program supported by the University Research Chair Program of the University of Ottawa, and the Discovery Grant Program (RGPIN-2018-06839) of the Natural Sciences and Engineering Research Council of Canada (NSERC). The authors also thank the ANR JCJC MELISSA (project number: ANR-20-CE43-0002, 2020-2024), the “Impact Biomolecules” project of the “Lorraine

Université d'Excellence" (Investissements d'avenir-ANR project number 15-004), in particular with project DrEAM 9, which financially supported the doctoral mobility of Jairo Andrés Camaño Echavarría at the University of Ottawa, Canada. The author acknowledge the PhotoNS Platform of the L2CM Laboratory, Université de Lorraine.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jff.2025.106747.
# Data availability

Data will be made available on request.

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