# Investigation into heat-induced lentil globulin–porcine albumin protein interactions

Coline Schiell, Stéphane Portanguen, Idrissa Diakite, Angélina D'orlando,
Pierre-Sylvain Mirade, Thierry Astruc

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Coline Schiell, Stéphane Portanguen, Idrissa Diakite, Angélina D'orlando, Pierre-Sylvain Mirade, et al. Investigation into heat-induced lentil globulin–porcine albumin protein interactions. Food Hydrocolloids, 2025, 10.1016/j.foodhyd.2025.111811. hal-05194259

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# Investigation into heat-induced lentil globulin–porcine albumin protein interactions

Coline Schiell<sup>a,b</sup>, Stéphane Portanguen<sup>b,D</sup>, Idrissa Diakite<sup>b</sup>, Angélina D'Orlando<sup>c,d,D</sup>, Pierre-Sylvain Mirade<sup>b,D</sup>, Thierry Astruc<sup>b,* D</sup>

## ARTICLE INFO

### Keywords:

- Hybrid foods

- Heat-induced gels

- Protein-protein interactions

- Rheology

- DSC

- SEM

- AFM-FS

## ABSTRACT

Hybrid food systems can be mobilized to enhance or develop specific textural attributes as part of food industry efforts to transition toward more sustainable and innovative solutions. In an unprecedented way, the study aimed characterizing and understanding the impact of porcine liver albumin (PA) and lentil globulins (i.e., lentil protein isolate; LPI) thermal denaturation on their mixture interactions using a panel of experimental characterization methods such as differential scanning calorimetry (DSC), rheology, scanning electron microscopy (SEM), and atomic force microscopy–force spectroscopy (AFM-FS). DSC was used to determine the denaturation temperatures of LPI and PA alone, which were 85 °C and 80 °C, respectively. We then evaluated the rheological properties and microstructure of thermal gels from 5 % protein solutions at different LPI:PA protein ratios (0:100, 30:70, 50:50, 70:30 and 100:0). The mixed-protein combinations showed synergistic interactions. Up to concentrations of 50 % LPI in the gels, the mixed gels showed lower enthalpy change, higher elastic modulus (G'), higher critical strain, and much lower frequency dependency that together demonstrated a stable elastic structure with superior resistance to deformation. The mixed gels also had a more compact and structured protein network. Using AFM-FS showed that protein-protein interactions were enhanced by thermal denaturation, and the forces measured were consistent with hydrophobic interactions and hydrogen bonds. This work opens up prospects for new ways of adding value to albumin-rich animal by-products.

## 1. Introduction

Growing health and environmental sustainability concerns have prompted intensive research into the partial replacement of animal proteins by plant proteins in our diet (Floreto et al., 2021; Grasso & Goksen, 2023). In this context, the development of mixed animal-source and plant-source food proteins is a relevant alternative. Besides nutritional value, food proteins have techno-functional properties that drive food structure and consequently food-industry innovation efforts. Therefore, a better understanding of interaction between animal proteins and plant proteins in mixed protein systems, will allow to modulate them and exploit their potential in diverse food applications (Alves & Tavares, 2019).

Protein gelation is generally initiated by heating to a temperature

equal to or higher than the protein's denaturation temperature, which causes the polypeptide chains to unfold, thus exposing the amino acids (hydrophobic groups, sulfhydryl bonds, thiol groups) that were buried in the native protein. Then, the unfolded proteins aggregate (by intermolecular interaction) and agglomerate (Nicolai, 2019). Gelation occurs when the protein concentration is high enough (>4 %). At that point, a three-dimensional gel network can form and become stabilized by disulfide bonds and/or non-covalent interactions such as hydrogen, hydrophobic, or ionic bonds (Nicolai, 2019). The microstructural and mechanical properties of the resulting gels depend on the protein types, ratios and concentrations in the mixed system, as well as the conditions used for gelation, such as pH, temperature, and ionic strength.

Pork liver is a cheap slaughterhouse by-product that is rich in proteins and essential nutrients such as amino acids, iron and fatty acids.

<footnote><sup>a</sup> ADIV (Association pour le Développement de l'Institut de la Viande), 10 Rue Jacqueline Auriol, 63039, Clermont-Ferrand, France</footnote>

<footnote><sup>b</sup> Université Clermont Auvergne, INRAE, UR370 Qualité des Produits Animaux (QuaPA), Saint-Genès-Champanelle, 63122, France</footnote>

<footnote><sup>c</sup> INRAE, UR1268 Biopolymères Interactions Assemblages (BIA), 44300, Nantes, France</footnote>

<footnote><sup>d</sup> INRAE, PROBE Research Infrastructure, BIBS Facility, 44300, Nantes, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: coline.schiell@adiv.fr (C. Schiell), stephane.portanguen@inrae.fr (S. Portanguen), idrissadiakite569@gmail.com (I. Diakite), angelina.dorlando@inrae.fr (A. D'Orlando), pierre-sylvain.mirade@inrae.fr (P.-S. Mirade), thierry.astruc@inrae.fr (T. Astruc).</footnote>
However, its use has mainly been limited to liver paste products and animal feeds, even though it has functional properties, including gelling properties, that have potential value for food industry applications (Li et al., 2018; Steen et al., 2016). Pork liver contains mostly water-soluble protein (76%-79%), chiefly albumin (Nuckles et al., 1990; Steen et al., 2016). Albumin is a 69 kDa globular protein that also found in blood plasma and has long been known to readily form heat-induced gels (Dàvila, Parés, Cuvelier, & Relkin, 2007; Howell & Lawrie, 1985).

Lentils (Lens Culinaris) are among the most cultivated legumes in the world. They constitute a promising pulse crop with strong potential as a food ingredient, as they are high in protein, fiber, and other micro-nutrients such as iron and vitamin B, and low in fat (Jarpa-Parra, 2018; Oduro-Yeboah et al., 2023). Lentils contain 22%-31% protein, 80% of which are characterized as storage proteins. The fraction of storages protein in lentils are lentils globulins (70%) that contain both legumin (11S) and vicilin (7S)-like proteins (Khazaei et al., 2019). Previous studies have demonstrated that globulins have good emulsifying and foaming properties but less good gelling properties (Jo et al., 2020; Osemwota et al., 2022; Shrestha et al., 2023b).

In mixed food systems, protein-protein interactions are common phenomena during food processing that can modify the gelling properties of single proteins and consequently improve or reduce the sensory and mechanical properties of the mixed gels formed (Wu et al., 2021). Indeed, the gel strength of proteins largely depends on the protein-protein interactions occurring in the gels after heat-induced denaturation (Ge et al., 2023). Howell (1994) was the first to study protein-protein interactions in gels in order to elucidate the structure-function relationships, optimize product components, improve food quality, and formulate new food products. Proteins interactions with other biopolymers can be characterized in three ways: synergistic interactions, aggregation, and phase separation. Synergistic interaction refers to the phenomenon where the combined effect of two proteins is greater than the sum of the effects caused individually by each protein (Alrosan et al., 2022). In recent years, numerous studies have focused on the interactions between proteins coming from different sources. The reviews of Alves and Tavares (2019) and of Wu et al. (2021) compile the described mechanisms related to the behavior of animal and plant proteins in mixed systems, featuring the main strategies applied to enhance their techno-functional synergism and highlighting future challenges for this scientific field. For example, lentil proteins have been studied in mixed systems, mainly with other plant-source proteins from cereals and pulses such as hemp, pea, oat, and faba bean proteins (Guidi et al., 2022; Johansson et al., 2021; Sales et al., 2024), but also in association with dairy proteins (Tang et al., 2025). Research on porcine albumin in mixed systems dates back further, and has mainly focused on the interactions between different fractions of blood plasma proteins (Dàvila, Parés, & Howell, 2007; Michnik & Drzazga, 2010) blended with other dietary proteins such as egg albumen (Howell & Lawrie, 1985) and whey proteins (Havea et al., 2001). However, none of these studies address the use of liver proteins in the design of hybrid foods, either with plant or animal proteins, highlighting the originality of the present study.

To our knowledge, no study has addressed the interactions between lentil proteins and liver proteins. To address this gap, the aim of this study was to investigate the interactions between lentil globulins and porcine albumin in mixed heat-induced gel systems in order to better characterize these interactions and better understand the phenomena involved. In the context of the food transition to more sustainable diets, the results obtained here could open new perspectives for the valorization of animal by-products such as blood and liver that hold the potential to enhance or develop textural attributes of value to the food industry. The denaturation temperatures of single and mixed proteins were determined by differential scanning calorimetry (DSC) and rheology. The heat-induced interactions between lentil globulins and porcine albumin in mixed gels were characterized by DSC, rheology, and scanning electron microscopy (SEM), and the interaction forces between the

proteins were measured by atomic force microscopy-force spectroscopy (AFM-FS).

## 2. Materials and methods

### 2.1. Materials

A commercial porcine albumin (PA) powder (purity reported on the label as 98%) was purchased from Sigma-Aldrich (A1830, St. Louis, MO). Lentil globulins (LPI) were extracted from red lentil seeds (Lens culinaris L., Sabarot, Chaspuzac, France). We used Kjeldhal analysis (AOAC, 2006) to determine the protein content of the LPI and PA, which was 84% (N x 5.7) and 98% (N x 5.6), respectively, according to Mariotti et al. (2008). These protein assay values were then used to calculate mass ratios for all experiments. All solutions were prepared in ultrapure water and all chemicals and reagents used were analytical-grade.

### 2.2. Methods

#### 2.2.1. Extraction of lentil proteins

Lentil proteins, and specifically globulins, were extracted from red lentil seeds using an isoelectric precipitation method adapted from Osemwota et al. (2021) and Lee (2021). Dry red lentils were ground down in a cutting mill (SM 300, Retsch, Haan, Germany) at 3000 rpm with a 0.5 mm screen aperture size to obtain a fine flour. The flour was then sieved using a laboratory sieve shaker (AS 200 Basic, Retsch, Haan, Germany) with a sieve opening of 0.5 mm to remove any courser particles. The particle size distribution of the lentil flour, determined by image analysis using ImageJ software (version 1.49v) (Schneider et al., 2012) from light microscopy acquisitions (Olympus BX61, Tokyo, Japon), was 5 µm-40 µm with a median diameter of 18 µm. Lipids and phytochemicals responsible for coloring were removed from the flour by acetone extraction (ratio 1:10, w/v) for 2 h under stirring. The mixture was filtered first through a cheesecloth (grade 90, 44 x 36 thread count) then through a Whatman filter (grade 540, 8 µm) before being dried overnight in a fume hood to remove the acetone. The delipidated flour was then dispersed in ultrapure water (ratio 1:10 w/v) and the pH was adjusted to 9.0 using 1M NaOH to solubilize the proteins. The solution was stirred continuously for 30 min, then centrifuged at 12000×g for 5 min at 4 °C. The supernatant was collected and adjusted to pH 4.5 with 1M HCl corresponding to the isoelectric point (pI) of lentil globulins in order to precipitate the proteins. The mixture was again stirred continuously for 30 min, then centrifuged at 12000×g for 5 min at 4 °C. The resulting pellet was washed with deionized water to remove non-protein materials, and then filtered (Whatman, grade 540, 8 µm) and freeze-dried. The final extraction yield of the freeze-dried powder from lentil flour was 13.4%. The final powder, designated as 'lentil protein isolate' (LPI), was stored at -80 °C until analysis. An SDS-PAGE gel of the PA and LPI protein fractions showed the presence of the major proteins consistent with our expectations (Fig. S1).

#### 2.2.2. Differential scanning calorimetry (DSC)

The thermal properties of the proteins were studied using a DSC 3 STAR System (Mettler Toledo, Columbus, OH). Protein solutions were prepared by dispersing LPI and PA powders in LPI:PA ratios of 0:100, 30:70, 50:50, 70:30 and 100:0 in 0.1 M phosphate buffer (pH 7) to a final protein concentration of 5% (w/v) in order to allow the gel formation, according to Veerman et al. (2023). The proportion of the mixtures is presented in Table 1.

Each sample was weighed (to 60-80 mg) in a 100 µL aluminum pan before being hermetically sealed. The DSC was pre-calibrated with indium. The pans were heated from 25 °C to 100 °C at a heat ramp of 5 °C/min (cycle 1) under inert atmosphere (20 mL/min of N₂ gas). A reference pan with phosphate buffer was adjusted to within ±1 mg of the same weight. The sample was then immediately reheated (cycle 2) to test the
<table><caption>**Table 1**
Nomenclature used to designate pure and mixed gels based on proportion (w/w) of lentil protein isolate (LPI) and porcine albumin (PA).</caption><thead><tr><th>Nomenclature</th><th>LPI (%)</th><th>PA (%)</th></tr></thead><tbody><tr><td>100L:0A</td><td>100</td><td>-</td></tr><tr><td>70L:30A</td><td>70</td><td>30</td></tr><tr><td>50L:50A</td><td>50</td><td>50</td></tr><tr><td>30L:70A</td><td>30</td><td>70</td></tr><tr><td>0L:100A</td><td>-</td><td>100</td></tr></tbody></table>

reversibility of denaturation. Onset temperature (T₀), i.e. initiation of unfolding of the protein structure, and denaturation temperature (T₉), i. e. temperature at peak maximum, were computed using STARE system software v6.11 (Mettler Toledo). Enthalpy of denaturation (ΔH) was measured by integrating the area under the peak. Results are presented as the mean of three replicates.

### 2.2.3. Heat-induced gel protein preparation

Gels at the different LPI:PA ratios were prepared in glass tubes, then heated in a water bath for 1 h at 85 °C for 100L:0A and 80 °C for the other gels. These temperatures correspond to the denaturation temperatures of the proteins, determined beforehand by DSC. The tubes were cooled by immersion in melting ice for 10 min then re-equilibrated at room temperature, and analyzed. This sample preparation was used for rheology (strain sweep and frequency sweep) and SEM.

### 2.2.4. Rheology

The rheological behavior of the gel proteins was determined using a HAAKE MARS iQ Air rheometer (Thermo Scientific, Karlsruhe, Germany) equipped with a Peltier temperature unit. As the samples had a gradient of fluidities depending on the experimental conditions, a 35-mm-diameter striated plane-plane geometry was used for solid samples (1.5 g) and a 60-mm-diameter plane-plane geometry was used for fluid samples (5 mL). Gap size was 1 mm for both geometries.

**Strain sweep.** A strain-sweep experiment was carried out at 25 °C with a constant angular frequency of 1 Hz to identify the linear viscoelastic region (LVR) for each sample. Storage modulus (G') and loss modulus (G'') were monitored over a strain range of 0.01–1000 %.

**Frequency sweep.** To study the time-dependent behavior of the samples, a dynamic-frequency sweep was performed at 25 °C, with frequency (ω) oscillating from 0.1 to 10 Hz within the identified LVR.

**Temperature sweep.** To complement the DSC measurements, protein gelation properties were determined by temperature sweep at 1 Hz frequency and 1 % strain in order to make measurements within the LVR. The sample was placed on the stator and 3 mL of mineral oil (M3516; Sigma-Aldrich, St. Louis, MO) was spread in a thin layer over its edge to seal it and prevent water evaporation during heating. The sample were heated from 25 °C to 100 °C at a scanning rate of 1 °C/min.

Changes in storage modulus (G'), loss (G'') modulus and loss tangent (tan δ = G''/G') as a function of strain, frequency and temperature were recorded by RheoWin™ software (Karlsruhe, Germany) for all the samples in Table 1. For strain sweep, critical strain (γc) and G' max in the LVR, and G', G'' and γ at the flow point (G' = G'') were computed. All measurements were performed at least three times.

### 2.2.5. Scanning electron microscopy (SEM)

SEM was used to analyze the microstructures of the protein gels. The gels were sliced into 3 mm³ cubes and fixed with 2.5 % glutaraldehyde in ultrapure water for 24 h at room temperature. Samples were then washed three times (10 min each time) with ultrapure water, then dehydrated in ethanol solutions for 10 min at serial concentrations of 30 %, 50 %, 75 %, and three times for 10 min at 100 %. To complete dehydration, the samples were immersed in a solution of v/v anhydrous ethanol 100 % and hexamethyldisilazane (HMDS) for 10 min and then 100 % HMDS until complete evaporation of HMDS. Once dehydrated,

the samples were fractured, mounted on specimen stubs using adhesive carbon tabs, and coated with 10 nm platinum (Q150 TES, Quorum Technologies, Laughton, UK). Observations were carried out using a Regulus model 8230 field emission scanning electron microscope (Hitachi, Japan) at 2 kV with the secondary electron detector.

### 2.2.6. Atomic force microscopy (AFM-FS)

To study the effect of thermal denaturation on LPI-PA interactions, we used ATM (JPK NanoWizard 4XP BioScience, Bruker, Billerica, MA) in force spectroscopy mode (AFM-FS) to analyze LPI-PA interaction forces in two conditions, i.e. native and denatured proteins. Native protein powders of LPI and PA were solubilized in PBS solution (pH 7.3) at 4 °C. Under denaturing conditions, LPI and PA were heated in PBS solution (pH 7.3) for 1 h at 85 °C and 80 °C, respectively. AFM-FS quantifies the interactions between a functionalized tip and a nanoscale surface, often in a liquid medium to reproduce physiological conditions (Lostao et al., 2023). Here, native or denatured PA was attached to the AFM tip and native or denatured LPI was attached to the substrate, typically a freshly-cleaved mica. AFM tips (MLCT, Si₃N₄, nominal spring constant ~0.1 N/m, Bruker) underwent controlled chemical treatments for functionalization with native and denatured PA, while mica sheets served as substrates for attaching native and denatured LPI. MLCT tips were treated with piranha solution (10.5 mL 98 % H₂SO₄ and 4.5 mL 30 % H₂O₂) for 30 min to remove organic contaminants, then incubated in a solution of 2 % APTES (3-amino-propyltriethoxysilane) in acetone for 2 h, followed by a 2.5-h incubation in 2.5 % glutaraldehyde in PBS (pH 7.3) to introduce aldehyde functional groups. The functionalized tips were then incubated overnight in a 0.1 mg/mL PA solution in PBS (native and denatured). Unbound proteins were removed by rinsing with PBS. Similarly, freshly-cleaved mica sheets were incubated in 2 % APTES in acetone for 2 h, followed by incubation in a 2.5 % glutaraldehyde solution in PBS (pH 7.3) for 2.5 h. After treatment, the mica was rinsed with PBS to remove excess reagents. Native and denatured LPI were immobilized by immersing treated mica sheets in a 0.1 mg/mL globulin solution in PBS overnight. Unbound proteins were removed by rinsing with PBS.

AFM-FS measurements were carried out in PBS buffer (pH 7.3) at a stable 20 °C–22 °C. A controlled force of 250 pN was applied, with a contact time of 0.5 s between functionalized tip and substrate. Force curves were collected at several points on the sample and analyzed using JPK Data Processing v7.1.41 (Bruker). Sixty-four acquisitions were performed for each experimental condition, and parameters were extracted from 20 force curves. The main parameters measured were maximum adhesion force (maximum force of attraction during retraction), adhesion energy (area under the force curve corresponding to the energy required to remove the tip from the surface), unfolding length (distance covered before the last interaction is broken) and unbinding force (the force required to separate tip from sample, marking the final event on the retraction curve).

### 2.3. Statistical analysis

Results are expressed as mean ± standard error of the mean (SEM) from at least three repetitions. A Student's t-test was applied to compare means between two sample groups and determine whether they are significantly different. Comparisons of means between several sample groups (>2) used ANOVA followed by a post-hoc Tukey HSD test for significant result. All statistical analyses were performed using Statistica software (Statistica, version 13.5; TIBCO Software Inc., Palo Alto, CA). Threshold for significance was set at *p* < 0.05.

## 3. Results and discussion

### 3.1. Thermal properties

Thermal properties of proteins are known to indicate their heat-
induced unfolding and thermal stability in the transition from native to denatured state (Shrestha et al., 2023c), and so we used DSC to study the denaturation temperatures and enthalpy changes in the protein systems. The DSC thermograms and corresponding peak features of LPI, PA, and LPI-PA mixtures are reported in Fig. 1 and Table 2, respectively.

A single endothermic peak was observed for LPI, PA, and their mixtures (Fig. 1), which means that the extraction method maintained their native structure and functionality. We then proceeded to a second heating cycle, i.e. reheating each sample after cooling, which showed irreversible denaturation of the pure proteins and their mixtures (Fig. S2).

The temperature initiating structural unfolding ($T_o$) was higher for LPI (around 76 °C) than PA (around 69 °C) (Table 2). The $T_o$ value for LPI is in agreement with Osemwota et al. (2022) (75.89 ± 0.17 °C) and Shrestha et al. (2023c) (76.46 ± 0.27 °C). The $T_o$ values of mixed samples decreased significantly with increasing PA content.

The denaturation temperature ($T_p$) of red lentil globulins was close to 85 °C, which is in agreement with Aryee and Boye (2017) (85.67 ± 0.14 °C) and between the values reported by Osemwota et al. (2022) (82.52 ± 0.25 °C) and Shrestha et al. (2023c) (87.34 ± 0.15 °C). This $T_p$ value for LPI reflects the high thermal stability of the lentil globulins as a consequence of their compact tertiary and quaternary structures maintained by hydrogen bonds (Shrestha et al., 2023c). As plant globulins contain both legumin (11S) and vicilin (7S)-like proteins (Khazaei et al., 2019), previous studies have highlighted two independent denaturation peaks (Shrestha et al., 2023a). However, a water content above 2 kg water/kg dry basis can lead to peak melting (Lefèvre et al., 2022), which could also explain our results, as our samples were 10-fold more hydrated (20 kg water/kg dry basis).

The 80 °C $T_p$ found here for PA globular proteins was higher than the 67–70 °C $T_p$ determined in previous studies (Dávila, Parés, & Howell, 2007; Álvarez et al., 2009), possibly due to extraction method and environment conditions (Dávila, Parés, Cuvelier, & Relkin, 2007). Note, however, that Howell & Lawrie (1985) observed more complete unfolding of polypeptide chains and the formation of aggregates from 79 °C, which is more in line with our observations.

There were no significant differences in $T_p$ between 0L:100A and mixed systems containing up to 50 % globulins. Above 50 % globulins, $T_p$ increased progressively and significantly up to 85 °C for 100L:0A.

The enthalpy change (ΔH) was higher for pure proteins (0L:100A and 100L:0A) than mixed systems, which means that more energy is required to denature the proteins, which therefore reflects the relative compactness of the proteins and the hydrophobic/hydrophilic interactions that stabilize their structure (Sarbon et al., 2015; Shrestha et al., 2023c). There were no significant differences between the ΔH of the mixed systems at any ratio, and the ΔH values were significantly lower for mixed systems than for the two proteins alone. This decrease in

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** DSC thermograms of protein dispersions of lentil protein isolate (100L:0A), porcine albumin (0L:100A), and mixtures of lentil globulins (L) and porcine albumin (A) in several ratios (30:70, 50:50 and 70:30) in the first heating cycle.</figcaption></figure>

<caption>**Table 2**</caption>

Onset temperature ($T_o$), maximal peak temperature ($T_p$) and enthalpy change (ΔH) of protein dispersions of lentil protein isolate (100L:0A), porcine albumin (0L:100A), and mixtures of lentil globulins (L) with porcine albumin (A) in several ratios (30:70, 50:50 and 70:30).

<table><thead><tr><th>Sample</th><th>T<sub>o</sub> (°C)</th><th>T<sub>p</sub> (°C)</th><th>ΔH (J/g)</th></tr></thead><tbody><tr><td>100L:0A</td><td>75.66<sup>a</sup> ± 0.06</td><td>84.90<sup>c</sup> ± 0.02</td><td>-0.53<sup>b</sup> ± 0.01</td></tr><tr><td>70L:30A</td><td>72.51<sup>d</sup> ± 0.14</td><td>81.29<sup>b</sup> ± 0.01</td><td>-0.44<sup>c</sup> ± 0.02</td></tr><tr><td>50L:50A</td><td>71.27<sup>c</sup> ± 0.19</td><td>79.57<sup>a</sup> ± 0.18</td><td>-0.47<sup>bc</sup> ± 0.01</td></tr><tr><td>30L:70A</td><td>70.50<sup>b</sup> ± 0.16</td><td>79.38<sup>a</sup> ± 0.07</td><td>-0.44<sup>c</sup> ± 0.01</td></tr><tr><td>0L:100A</td><td>69.13<sup>a</sup> ± 0.11</td><td>79.69<sup>a</sup> ± 0.09</td><td>-0.65<sup>a</sup> ± 0.02</td></tr></tbody></table>

Data are expressed as means ± SEM (n=3). In each column, lowercase superscript letters (a to e) indicate significant differences between samples (p < 0.05).

ΔH could reflect a lower thermal stability of LPI and PA in mixture, and therefore the presence of interactions between these two types of proteins (Dávila, Parés, & Howell, 2007). Indeed, these lower ΔH values may reflect a decrease in the number of junction zones (Sarbon et al., 2015), which would mean that a fraction of the LPI and PA were bound non-covalently and that these interactions compete with stronger interactions between proteins of the same source (Badii & Howell, 2006).

## 3.2. Rheology

### 3.2.1. Strain sweep

Strain sweeps were performed on protein gels after heat-set to evaluate their resistance to deformation, and hence the relative quantity and strength of junction zones in the network structure (Ge et al., 2023). Fig. 2 shows the strain sweep profiles of the heat-induced gels.

In the initial plateau phase, which corresponds to the LVR, $G' > G''$ regardless of LPI:PA ratio, indicating a solid viscoelastic gel behavior (Tunick, 2011).

$0L:100A$ and mixed gels had a much higher $G'$ in the LVR, indicating a stronger gel than 100L:0A (Table 3). This result means that PA increased gel strength in mixed gels. Moreover, the 50L:50A mixed gel was found to be as strong as the gel containing 100 % PA, and the 30L:70A mixed gel was even significantly stronger (p < 0.05) than the gel containing 100 % PA. This result suggests that there were interactions between LPI and PA, and these interactions have a synergistic effect when there is at least 50 % PA or at most 50 % LPI in the gel.

As shown in Fig. 2, the $G'$ of all gels remained constant until strain reached a critical point after which $G'$ started to decline and the gel network structure subsequently began to break down. This point is defined as the critical strain ($\gamma_c$), which provides information on the cohesive properties or deformability of the gel (Ge et al., 2023). The $\gamma_c$ (%) parameter was higher for all mixed gels than for pure LPI and PA

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Strain sweep profiles of heat-induced gels of lentil protein isolate (100L:0A), porcine albumin (0L:100A) and mixtures of lentil globulins (L) with porcine albumin (A) in several ratios (30:70, 50:50 and 70:30). Data are expressed as means ± SEM (n=3). Temperature during experiments was 25 °C.</figcaption></figure>
<caption>**Table 3**</caption>

Parameters of the linear viscoelastic range (LVR) and of the flow point for heat-induced gels of lentil protein isolate (100L:0A), porcine albumin (0L:100A) and mixtures of lentil globulins (L) with porcine albumin (A) in several ratios (30:70, 50:50 and 70:30).

<table><thead><tr><th rowspan="2">Samples</th><th colspan="2">LVR</th><th colspan="2">Flow point (G' = G'')</th></tr><tr><th>G' max (Pa)</th><th>γ<sub>c</sub> (%)</th><th>G' = G'' (Pa)</th><th>γ (%)</th></tr></thead><tbody><tr><td>100L:0A</td><td>2.59<sup>a</sup> ± 1.12</td><td>4.07<sup>a</sup> ± 0.10</td><td>1.15<sup>a</sup> ± 0.46</td><td>10.23<sup>a</sup> ± 1.49</td></tr><tr><td>70L:30A</td><td>137.70<sup>b</sup> ± 4.94</td><td>12.10<sup>c</sup> ± 0.72</td><td>14.20<sup>b</sup> ± 0.27</td><td>447.50<sup>c</sup> ± 12.93</td></tr><tr><td>50L:50A</td><td>352.57<sup>c</sup> ± 23.64</td><td>11.47<sup>c</sup> ± 0.22</td><td>28.16<sup>c</sup> ± 0.87</td><td>540.17<sup>d</sup> ± 4.74</td></tr><tr><td>30L:70A</td><td>583.93<sup>d</sup> ± 12.10</td><td>11.40<sup>c</sup> ± 0.33</td><td>41.85<sup>d</sup> ± 0.99</td><td>555.63<sup>d</sup> ± 14.52</td></tr><tr><td>0L:100A</td><td>399.00<sup>c</sup> ± 30.30</td><td>6.40<sup>b</sup> ± 0.71</td><td>60.07<sup>e</sup> ± 3.75</td><td>124.10<sup>b</sup> ± 11.06</td></tr></tbody></table>

Data are expressed as means ± SEM (n=3). In each column, lowercase superscript letters (a to d) indicate significant differences between samples (p < 0.05). Temperature during experiments was 25 °C.

gels, which means that mixed gels were more resistant to deformation and thus more difficult to fracture than pure gels under the same stress. Furthermore, the high value of γ<sub>c</sub> in mixed gels reflects a relatively dense network structure, while the high G' with lower γ<sub>c</sub> for 0L:100A indicates a stiffer and more brittle gel (Ge et al., 2023).

Flow point (G' = G''), which represents the irreversible transition from solid to liquid-like behavior, corresponds to the point at which the gel is completely destructured (Feroussier et al., 2024; Tunick, 2011). In agreement with previous observations, the values of γ at the crossover point G'-G'' were much higher for all mixed gels than pure gels (Table 3), again confirming their superior resistance to deformation compared to pure gels. Mixed gels thus displayed a relatively more elastic behavior after the LVR and a more gradual transition to plastic behavior (Xia et al., 2022). These results showed synergistic interactions between LPI and PA after heat treatment.

### 3.2.2. Frequency sweep

Frequency sweeps were performed to examine the structural stability as a function of frequency and state of chains relaxation, thus helping to predict the short- and long-term structural integrity and mechanical strength of the gels (Cheng et al., 2022). This type of analysis is particularly informative for predicting the rheological behavior of gels during storage. Fig. 3 shows the frequency sweep profiles of the heat-induced gels.

Similarly to strain sweep, storage modulus (G') was higher than loss modulus (G'') at all frequencies regardless of LPI:PA ratio, indicating that the heat-induced gels showed viscoelastic behavior of (Ge et al., 2023; Tang et al., 2024).

As shown in Fig. 3, the G' of the 100L:0A gel (red curves) decreased and G'' increased with increasing frequency until crossing G'' at 20 rad/s. This gel thus showed frequency dependency, suggesting a material structure with molecular entanglements that behaves more like a liquid

at high frequencies, i.e. short-term, but more like a solid at low frequencies, i.e. long-term (Cheng et al., 2022). According to Tunick's (2011) framework, this gel can therefore be considered as weak. These results are in line with Du et al. (2023) who observed an increase of G'' with frequency and the crossover of G' and G'' for a lentil protein gel at pH 7 heated for 1h at 85 °C.

The G' and G'' of PA and mixed gels showed a much weaker frequency dependency, proving that the highly stable elastic structure and stabilization are likely caused by covalent bonds in the gel matrix (Tang et al., 2024). The fact that the G'' for 70L:30A decreased at high frequencies may indicate a loss of cohesion in the gel (Fig. 3). Based on the frequency dependence of the gels, the ranking from most structured to least structured would be 30L:70A > 50L:50A > 0L:100A > 70L:30A > 100L:0A. Given that the 30L:70A, 50L:50A and 0L:100A gels were strong and had little frequency dependence and no G'-G'' crossover, they can be classified as physical gels, i.e. midway between strong and weak gels with noncovalent bonds (Tunick, 2011; Xia et al., 2022). Our results are therefore consistent with previous observations indicating that the interaction between LPI and PA is synergistic up to a concentration of 50 % LPI in the gels.

### 3.2.3. Temperature sweep

To complement the DSC thermograms, we monitored key viscoelastic properties, i.e. storage modulus (G'), loss modulus (G'') and loss tangent (tan δ = G''/G'), of the different protein dispersions for each LPI: PA ratio as a function of temperature. Fig. 4 shows the temperature sweep profiles from 25 °C to 100 °C.

There were no significant differences between G' and G'' up to 40 °C (Fig. 4A and B). Above 40 °C, the G' was higher than G'' for all conditions, indicating the predominantly solid-like properties of the gels (tan δ < 1) (Tang et al., 2024). Overall, the G' and G'' curves were consistent with the protein denaturation temperatures determined previously by DSC.

For 100L:0A, G' and G'' gradually increased up to 70 °C then decreased to 85 °C (Fig. 4A and B). This decrease in G' and G'' approaching globulin denaturation temperature was reported as due to the reordering of polypeptides and rupture of hydrogen bonds losing stability as temperature decreases (Shrestha et al., 2023c). Above 85 °C, G' and G'' increased and tan(δ) decreased, which corresponds to the gradual development of the three-dimensional network, mainly through hydrophobic interactions and hydrogen bonds during LPI aggregation (Moreno et al., 2020; Tunick, 2011).

G' and therefore tan(δ) oscillated strongly up to around 60 °C for 0L:100A, then G' increased slowly up to 80 °C (Fig. 4A and C). As temperature rises, protein bonds become unstable, leading to protein unfolding associated with increased molecular mobility (Li et al., 2018). This phenomenon is also associated with the decrease in α-helix structure, the formation of a β-sheet structure, and exposure of the buried hydrophobic core (Dávila, Parés, & Howell, 2007; Shi et al., 2024). The subsequent sharp increase of G' (250 Pa) above 80 °C indicates gelation of the denatured albumin (Dávila, Parés, Cuvelier, & Relkin, 2007; Wang et al., 2014). Moreover, the decrease in tan(δ) and its stabilization around 0.1 reflect the formation of an ordered gel network (Li et al.,

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Frequency sweep profiles of heat-induced gels of lentil protein isolate (100L:0A), porcine albumin (0L:100A), and mixtures of lentil globulins (L) with porcine albumin (A) at several ratios (30:70, 50:50 and 70:30). Data are expressed as means ± SEM (n=3). Temperature during experiments was 25 °C.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Fig. 4. Changes in (A) storage modulus (G'), (B) loss modulus (G''), and (C) loss tangent (tan δ) of protein dispersions of lentil protein isolate (100L:0A), porcine albumin (OL:100A), and mixtures of lentil globulins (L) with porcine albumin (A) at several ratios (30:70, 50:50 and 70:30) as a function of temperature. Data are expressed as means ± SEM (n=3).</figcaption></figure>

2018; Tang et al., 2024). These results are in agreement with the mechanism highlighted by Howell and Lawrie (1985), who reported that from 50 °C onwards, albumin aggregates form linear chains as monomers unfold, and between 50 °C and 79 °C these chains could assemble into a reversible gel stabilized by non-covalent bonds, including hydrogen, hydrophobic, and electrostatic interactions. Above 79 °C, further unfolding led to the formation of an opaque, irreversible gel network stabilized mainly by strong covalent disulfide bonds, as well as by hydrogen and hydrophobic bonds. These same observations can also be applied to mixed systems, whose modulus curves are close to those of PA. The protein dispersions changed from a viscous liquid to a semi-solid structure and then to a gel-like structure during gelation induced by heat-setting at over 80 °C. This could mean that the albumin proteins dictate the formation of the mixed gels. At the end of the heat ramp, although all mixed gels and PA has similar tan(δ), the G' values of 30L:70A and 50L:50A gels were statistically identical to PA, but decreased sharply after 50 % globulin in the gel.

### 3.3. Scanning electron microscopy (SEM)

The microstructure of heat-induced protein gels of LPI, PA and their mixtures were investigated by SEM to compare their network structures, as illustrated in Fig. 5.

The three types of gel (100L:0A, 50L:50A and 0L:100A) showed very distinct network structures.

100L:0A displayed a coarse gel network with large cavities and discontinuities (Fig. 5A and D). Globular protein gels are generally classified as fine-stranded, mixed or particulate based on microstructural properties, which are affected by pH, surface charge, and type of aggregate formed (Ge et al., 2023). Lentil proteins formed spherical particulate aggregates as a result of the random aggregation of lentil globulin, giving the gel a rough surface (Moreno et al., 2020). Indeed, when pH is far from the isoelectric point of the proteins – as with gels at pH 7 and pI 4.5 here – the electrostatic repulsions are relatively weak and lead to random protein aggregation, which reduces the number of possible interactions among aggregates, leading to weaker and less interconnected gel networks (Jo et al., 2020). Moreover, the degree of aggregation depends on the rate of aggregation. If aggregation rate is slower than unfolding rate, then a coarse gel network with larger pores is formed (Wang et al., 2014). However, Jarpa-Parra et al. (2014) demonstrated that the surface charge of globulins was sufficiently high at pH 7 to allow the development of hydrogen bonding and hydrophobic interactions during gel formation. This coarser and looser structure explains why 100L:0A showed lower G' and lower critical strain (γc) than albumin-based gels, since their less strongly connected and more porous network could be less resilient to deformation.

0L:100A formed an opaque and slightly more particulate gel with better-defined aggregates and smaller pores (Fig. 5C and F). Fort et al. (2007) observed this type of gel for porcine plasma protein mixed with cysteine. Li et al. (2018) also noted a 'particulate gel' with an opaque coagulum in heat-induced liver protein gel. Once again, protein molecules randomly associated into large and almost spherical aggregates which then linked together to form the threads of a gel network (Li et al., 2018). These results are consistent with the results of rheology analysis, since a higher G' reflects a more ordered network structure (Somjid et al., 2022).

The mixed gels showed an even finer protein network with well-defined spherical aggregates in some areas whereas other areas had coarse heterogeneous zones similar to the structure of pure gels (Fig. 5B and E). The many ramifications visible in the network with smaller pores were probably due to more extensive protein-protein interactions. Indeed, the 0L:100A and 50L:50A gels had similar G' and G'' values but the 50L:50A gel had a significantly higher critical strain (γc). Under deformation, the numerous strands could be more difficult to break, increasing the range of the LVR. In addition, noncovalent interactions can readily re-form, which would enable these gels to retain more elasticity even at very high strain (Xia et al., 2022). The addition of albumin in specific proportions – at least 50 % – made the protein gel network more compact and ordered, and improved the structural integrity of the protein gel network.

### 3.4. Atomic force microscopy (AFM-FS)

Interaction forces between LPI and PA were measured by AFM-FS with native and denatured proteins. Fig. 6 gives an illustrative example of the force curves obtained.

The quality of LPI deposition on mica was first verified by AFM imaging (Fig. S3). Control experiments using AFM tips functionalized only with glutaraldehyde showed no interaction peaks with LPI on mica, thus confirming that the signals measured were due to LPI-PA interactions (Fig. 6A).

Further investigation into the interactions between LPI and PA in their native and denatured states revealed slight but significant (p < 0.05) differences in measured unbinding forces (Fig. 7).
<figure><img src="image_7.png" /><figcaption>**Fig. 5.** Scanning electron micrographs of heat-induced gels of lentil protein isolate (100L:0A), porcine albumin (0L:100A) and a 50% lentil protein isolate/50% porcine albumin mixture (50L:50A). Magnification: 2,000x (A,B,C) and 10,000x (D,E,F). Scale bars: 5 µm for A, B, C; 2 µm for D, E, G.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Force curves obtained by AFM illustrating the interactions between LPI and PA under different conditions. (A) Interaction between a glutaraldehyde-functionalized tip and LPI immobilized on a mica surface; (B) Interaction between native LPI and native PA; (C) Interaction between denatured LPI and denatured PA. Black curves: approach phase. Red curves: retraction phase. (For interpretation of the references to color 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. 7.** Distribution of unbinding forces measured between LPI and PA using AFM force spectroscopy (AFM-FS). In black: distribution of unbinding force between native LPI and native PA; In hatched red: distribution of unbinding force between denatured LPI and denatured PA. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

In the case of native proteins, unbinding forces ranged from 13 pN to 177.1 pN, with a of 73.54 ± 9.89 pN. The distribution showed a marked peak around 50 pN and significant forces above 100 pN. In contrast, for denatured proteins, the unbinding forces were distributed around a lower mean of 48.57 ± 6.34 pN, with a peak centered around 40 pN. Although the peak around 50 pN common to both conditions indicates the existence of interactions that persist irrespectively of denaturation, the fact that forces around 100 pN and above were more frequently observed for native proteins suggests that protein denaturation slightly altered the distribution of breaking forces.

Maximum adhesion forces were not significantly different between native and denatured proteins. However, adhesion energy was significantly (*p* < 0.05) higher for denatured proteins (4.40 ± 0.57 × 10⁻¹⁷ J) compared to native proteins (2.64 ± 0.21 × 10⁻¹⁷ J). Moreover, protein unfolding length showed a significant (*p* < 0.05) increase in the
denatured state (1.39 ± 0.08 µm) compared to native state (0.15 ± 0.01 µm) (Fig. 6B and C). These results suggest that as protein denaturation alters the native conformation, it induces a major structural reorganization that exposes hydrophobic residues previously buried in compact conformations, thus enhancing their ability to interact with other proteins (Nicolai, 2019). The interaction rate increased significantly, from 39.06 % for native proteins to 70.31 % after denaturation, which further points to enhanced ability of unfolded proteins to establish intermolecular interactions. Note that heat treatments in other protein systems have been shown to promote the formation of stable complexes (Badii & Howell, 2006; Havea et al., 2001; Tang et al., 2025), which is further evidence that denaturation enhances protein-protein interactions. In contrast, native proteins maintain a compact, ordered structure, thus exposing fewer sites available for interactions (Turoverov et al., 2010).

LPI exhibit a degree of hydrophobicity, and denaturation exposes their internal hydrophobic sites (Osemwota et al., 2022), thus facilitating interactions with PA. As plant proteins have a low sulphur amino acid content, it is reasonable to assume that the increase in interactions during gelation comes mainly from hydrophobic interactions rather than disulfide bonds (Ge et al., 2023; Osemwota et al., 2022; Tang et al., 2024). Disulfide bridges, which are known to significantly enhance the mechanical stability of proteins by forming more robust bonds (Manteca et al., 2017), do not appear to be involved in system studied here. The forces measured in the present study are well below those generally observed for these interactions. These low force values (no more than a few hundred pN) point to intermolecular dipole-dipole-type interactions (electrostatic attraction between groups of opposite charge and hydrogen bonds) or hydrophobic interactions, rather than covalent bond-type interactions which would have higher force values (above 500–1000 pN), especially in the case of short contact times (Fahs & Louarn, 2013; Xu et al., 2005).

## 4. Conclusion

Here we investigated protein-protein interactions between LPI and PA in aqueous media at around pH 7. As heating proteins enables them to unfold and exposes their active sites, this work was focused on the effect of heat treatment on these interactions.

First, DSC was used to identify the denaturation temperatures of LPI and PA alone, which were 85 °C and 80 °C, respectively. AFM demonstrated not only that the two types of protein interacted but that the heat treatment of LPI and PA at 85 °C and 80 °C, respectively, further enhanced these interactions. Indeed, unbinding forces, adhesion energy, and protein unfolding length were all significantly higher with denatured proteins compared to native proteins. The interaction forces measured were of the order of tens to hundreds of pN, which could correspond to hydrophobic interactions and/or hydrogen bonds.

In addition, we used DSC to evaluate the thermal properties of LPI and PA mixed in aqueous media from 5 % protein solutions at different LPI:PA protein ratios (0:100, 30:70, 50:50, 70:30 and 100:0), as well as the rheological properties and microstructure of heat-induced protein gels prepared from the same ratios. Results demonstrated that although LPI has limited gelling properties alone, blending it with PA proved technologically beneficial as it enabled synergistic interactions. The presence of PA increased the strength of the gels. However, the mixed gels were more resistant to deformation (higher γc and γ parameters at the flow point) and more elastic than the pure gels. Furthermore, at up to 50 % LPI content in the gels, the mixed gels were even stronger (higher G' in the LVR) and more structured (low frequency dependence) than the PA gel. These rheological properties can be correlated to differences in the gel microstructure, as 50L:50A mixed gels had a more ramified and ordered gel network. The lower enthalpy change of mixed systems compared to pure proteins may be a further argument for beneficial interaction between the two types of protein.

This work raises prospects for exploiting complementarities between animal-source proteins and plant-source proteins for the development of

sustainable hybrid foods that valorize animal by-products such as liver or blood and that rebalance the animal protein/plant protein ratio in human diet. Given that plant globulins are composed of two main fractions, 11S and 7S, which have different structures, we have further investigations underway to identify the interactions at play for each of these fractions and thus refine the present conclusions. More specifically, the implementation of advanced techniques for deeply characterizing macromolecular interactions as applied in the medical sector (Gan et al., 2024, 2025; Li et al., 2025), will allow to acquire more knowledge on the molecular behavior set up during the processing of hybrid foods. Understanding the underlying mechanisms should allow to better control the design of these future foods.

## CRediT authorship contribution statement

**Coline Schiell:** Writing – original draft, Methodology, Investigation, Funding acquisition, Formal analysis, Conceptualization. **Stéphane Portanguen:** Writing – review & editing, Methodology, Investigation.

**Idrissa Diakite:** Writing – review & editing, Investigation, Formal analysis. **Angélina D'Orlando:** Writing – review & editing, Resources, Methodology, Investigation, Formal analysis. **Pierre-Sylvain Mirade:** Writing – review & editing, Validation, Supervision, Project administration, Funding acquisition. **Thierry Astruc:** Writing – review & editing, Validation, Supervision, Project administration, Conceptualization.

## Funding

This work received funding support from the Association Nationale de la Recherche et de la Technologie (2021/1267) and Bpifrance (grant No. DOS0191062/00).

## Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

C. Schiell reports financial support was provided by BPI (Public bank for investment France). C. Schiell reports financial support was provided by National Association of Technical Research.

## Acknowledgments

The authors thank Christelle Blavignac at the Clermont Auvergne University 'Centre d'Imagerie Cellulaire Santé' (CICS) for running the SEM observations, Frédéric Anglard, Adeline Berger and Laurent Aubry from INRAE for technical support, and Metaform Langues for proofreading the paper for good English.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.foodhyd.2025.111811.

## Data availability

Data will be made available on request.

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