
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39232102
71513
10.1038/s41598-024-71513-0
Article
Nymphaea alba leaf powder effectiveness in removing nisin from fermentation broth using docking and experimental analysis
Khazravi Leila 1
Hamedi Javad jhamedi@ut.ac.ir

2
Attar Hossein 1
Ardjmand Mehdi 3
1 grid.411463.5 0000 0001 0706 2472 Department of Petroleum Engineering, Faculty of Petroleum and Chemical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 https://ror.org/05vf56z40 grid.46072.37 0000 0004 0612 7950 Department of Microbial Biotechnology, School of Biology, College of Science, University of Tehran, Tehran, Iran
3 grid.472433.5 0000 0004 0612 0652 Chemical Engineering Department, Islamic Azad University, South Tehran Branch, Tehran, Iran
4 9 2024
4 9 2024
2024
14 2064513 9 2023
28 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The accumulation of nisin in the fermentation medium can reduce the process's productivity. This research studied the potential of Nymphaea alba leaf powder (NALP) as a hydrophobic biosorbent for efficient in-situ nisin adsorption from the fermentation medium by docking and experimental analysis. Molecular docking analysis showed that di-galloyl ellagic acid, a phytochemical compound found in N. alba, had the highest affinity towards nisin. Enhancements in nisin adsorption were seen following pre-treatment of NAPL with HCl and MgCl2. A logistic growth model was employed to evaluate the growth dynamics of the biosorption capacity, offering valuable insights for process scalability. Furthermore, optimization through Response Surface Methodology elucidated optimal nisin desorption conditions by Liebig's law of the minimum, which posits that the scarcest resource governs production efficiency. Fourier Transform Infrared (FTIR) spectroscopy pinpointed vital functional groups involved in biosorption. Scanning electron microscopy revealed the changing physical characteristics of the biosorbent after exposure to nisin. The findings designate NALP as a feasible adsorbent for nisin removal from the fermentation broth, thus facilitating its application in the purification of other biotechnological products based on growth and production optimization principles.

Keywords

Biosorption
Nisin
Nymphaea alba
Molecular docking
Response surface methodology
Luedeking–Piret and logistic growth models
Subject terms

Biological techniques
Biotechnology
Microbiology
issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

The escalating challenge of antibiotic resistance has intensified the search for viable alternatives, with antimicrobial peptides (AMPs), particularly nisin produced by Lactococcus lactis, emerging as potent candidates due to their broad-spectrum antibacterial properties1–4. Nisin, characterized by its low molecular weight, hydrophobicity5, stability under harsh conditions, non-toxicity, and GRAS (generally recognized as safe) status, is widely utilized as a natural preservative in the global food industry6. Nonetheless, its biotechnological production encounters significant challenges, chiefly the inhibitory effects of nisin accumulation in fermentation medium7. While effective, conventional extraction and purification methods are often hampered by high costs and potential environmental risks associated with solvent use1,8. In response, in-situ product removal (ISPR) technologies have emerged as a sustainable and efficient alternative, providing innovative solutions for recovering bioproducts9–12. Among the various ISPR techniques, solid–liquid systems using biosorbents, ranging from agricultural waste to plant leaf and microbial biomass, have shown exceptional efficiency and environmental sustainability13,14. Previous studies have explored the in-situ recovery of nisin from fermentation broth using methods like foam fractionation15 and aqueous two-phase micellar systems16. Some hydrophobic biosorbents, such as rice hull ash and silicic acid, have been investigated for nisin removal from fermentation broth. Silicic acid (H3SiO4) is the simplest soluble form of silica, with weakly acidic and superhydrophobic characteristics17. Nymphaea alba (White water Lily) is a freshwater living plant distributed over Europe, the Middle East, and some parts of Africa18. The superhydrophobic surfaces of N. alba leaf help their buoyancy on the water surface19. N. alba leaf is known for its medicinal properties and proven effectiveness in wastewater detoxification20,21. However, there is no report on the applications of N. alba as an ISPR sorbent, including nisin recovery.

By leveraging the unique properties of this aquatic plant, the current research aims to explore the capability of N. alba leaf as an eco-friendly, cost-effective sorbent for the in-situ removal of nisin from fermentation broths using docking, fermentation, and mathematical modeling approaches.

Material and methods

Preparation and chemical modification of N. alba leaf powder

N. alba leaf was sourced from fish farming pools in the southern region of Tehran, Iran. This species was not considered in Iran's red list of plants22. Furthermore, its collection and use were by all the relevant guidelines. The leaf (500 g) was cleansed with deionized water, air-dried at ambient temperature, ground to reach a fine powder, and sieved through a mesh to ensure the uniformity of the final product (50 g)21. To enhance the adsorption capacity of N. alba leaf powder (NALP), it was treated with various concentrations (0.05, 0.1, 0.15, and 0.2 mol/L) of MgCl2, KCl, CaCl2, CH3COOH, C2H5COOH, HCl, and H2SO4. The leaf was immersed in the Erlenmeyer flasks containing one of the treatment agents and incubated for 2 h at room temperature. After soaking, the treated leaf was separated via a 0.45 µm membrane filter. Subsequently, the residual material of each sample was washed with deionized water (dH2O) twice and then was suspended in 10 mL dH2O and autoclaved at 121°C for 15 min, after that referred to as the biosorbent21.

Point of zero charge (pH-PZC)

Nine Erlenmeyer flasks, each containing 25 ml of 0.01 mol/L NaCl solution adjusted to varying pH levels (1–9) using 1 mol/L HCl or NaOH, were prepared. NALP (0.1 g) was added into each Erlenmeyer flask and agitated at 80 rpm, with a room temperature of 48 h. The final pH of the filtrate was measured and plotted against the initial pH. The pH at which the curve crosses the line pHinitial = pHfinal was considered the pH-PZC23.

Zeta potential (pH-ZPC)

The zeta potential of NALP was quantified using a ZetaSizer Nano ZS (Malvern, United Kingdom) to evaluate the surface charge, which influences adsorption capabilities24.

Functional groups

To identify the key functional groups participating in nisin adsorption, FTIR spectroscopy was conducted. A thin film of NALP alone and the NALP-nisin complex was created using KBr pellets, and their spectra were captured between 400 and 4000 cm−1 on a Bruker Tensor 27 FTIR spectrometer25.

Surface morphological characteristics

Morphological characteristics of NALP before and after exposure to nisin were analyzed by scanning electron microscopy (SEM, Tescan, Vega3, Czech). The samples were fixed on a glass slide with 2% glutaraldehyde, dehydrated in a series of ethanol concentrations (25%, 50%, 75%, 90%, 95%, and 100% v/v), and were coated by gold25.

Molecular docking

The three-dimensional (3D) structure of nisin was retrieved from the Swiss-Model repository. The protein ID 1WCO was selected based on the highest identity and query coverage. The methodology for using the Swiss Dock model for protein structure prediction involves blind docking. This approach explores the entire protein surface without prior knowledge of the binding site. Blind docking in Swiss Dock predicts binding modes and interactions by generating multiple modes across the protein surface, evaluating them based on energies, and clustering to identify the most favorable interactions26. Phytochemical compounds in N. alba leaf were drawn using Chem Draw Professional v17.127, a leading chemical drawing and analysis software.

The pre-docking analysis was done by Molegro Molecular Viewer v.2.5 software to optimize the parameters and settings for the subsequent docking simulations, ensuring accurate and reliable results. For each ligand, five poses are assigned based on the default settings of the molecular virtual docking program. The best complex between the ligand and protein is selected based on the most negative energy. This meticulous selection process ensures that the optimal complex between the ligand and protein is chosen, enhancing the accuracy and reliability of the docking predictions28.

The docking of the identified phytochemical ligands into the active site of nisin was facilitated using Molegro Molecular Viewer v.2.5 software, which employs a virtual screening tool for docking ligands to proteins by evaluations the binding energies, interaction types (e.g., hydrogen bonding, steric interactions), and the stability of the ligand–protein complexes. This step assesses the potential of phytochemical compounds to bind at specific sites on nisin, thereby influencing its activity. The software evaluates poses to find the ligand with the most negative binding affinity or ΔG in the active site of receptors, making it ideal for comprehensive docking studies due to its ability to handle multiple ligands and iterations29.

Microorganisms and culture medium

Lactococcus lactis subsp. lactis UTMC 106 and Micrococcus luteus UTMC 1428, serving as nisin-producing and nisin-sensitive strains, respectively, were procured from the University of Tehran Microorganisms Collection (UTMC). The seeding medium composition was as follows (g/L): sucrose 10, yeast extract 10, peptone 10, K2HPO4 10, NaCl 2, and MgSO4 0.2, with the pH adjusted to 7.030. The fermentation medium was M17 broth supplemented with 0.5% glucose (GM17)31.

The effect of the biosorbent on nisin removal from fermentation broth

L. lactis UTMC 106 cells (~ 108 cells/mL) were inoculated into a 100-mL Erlenmeyer flask containing 20 mL of seeding medium and incubated at 30 °C and 80 rpm for 20 h. The seeding material was then inoculated at an OD625 (5% v/v) into 250-mL Erlenmeyer flasks, each containing 50 mL of fermentation medium with varying concentrations of the biosorbent (0.125–5 g/L). Incubation continued at 30 °C and 180 rpm for 12 h32.

Biomass measurement

Viable bacterial counts were determined by calculating colony-forming units (CFU) using the Tryptic Soy Agar (TSA) spread plate method.

Nissin assay

After removing the biomass by filtration of the fermentation broth throughout a 0.45 µm filter membrane, bioactivity and concentration of nisin in the permeate were measured by the Agar diffusion method and high-performance liquid chromatography (HPLC)31, respectively.

Bioassay by Agar Diffusion Method: One mL of permeate was boiled in 0.02 mol/L HCl (9 mL) and centrifuged at 3500×g for 10 min33. The supernatant was introduced into wells on TSA agar plates inoculated with 1% (v/v) M. luteus. The plates were kept overnight at 4 °C and then incubated at 37 °C for 24 h. The inhibition zone diameter was measured with a Vernier caliper, and nisin concentration was calculated using the standard curve equation. The antibacterial activity of the sediment was similarly assessed32. All experiments were conducted in triplicate.

HPLC: Protein fraction of the permeate was precipitated by (NH4)2SO4 (80%) and centrifugation at 12,000×g, 4 °C, for 30 min. The supernatant was discarded, and the pellet was dissolved in urea (3 M) and loaded on a C18 cartridge column. The column was washed with 10% acetonitrile in deionized water. The concentration of nisin in the eluted fraction was determined by HPLC (Cecil, UK) at 254 nm. Other conditions were acetonitrile (13%): water (87%) as mobile phase at 1.0 ml/min, column temperature 25 °C.

Nisin fermentation and adsorption

NALP (10 mg) was mixed with distilled water (10 mL), autoclaved (121 °C for 15 min), and added to 100 mL Erlenmeyer flasks containing 10 mL fermentation medium, with the pH adjusted to 6.8. The flasks were incubated at 30 °C and 80 rpm (upstream agitation rate) for 16 h. Antibacterial activity was assayed against M. luteus as described above21.

Nisin desorption

The biosorbent containing nisin was separated by centrifugation at 3500×g for 20 min, washed with sterile dH2O, and subjected to desorption by shaking in 20 mL dH2O at room temperature and 80 rpm for 30 min. After centrifugation at 3500×g for 15 min, the supernatant's pH was adjusted to 3 ± 0.2 and shaken at 80 rpm (downstream agitation rate) for 90 min (downstream agitation time). Following incubation in a water bath at 90 °C for 10 min, agar diffusion reassessed antibacterial activity34.

Nisin biosorption using silicic acid

Silicic acid (1 g, 5% w/v) was introduced into the fermentation medium (20 mL). After 10 h, the mixture was centrifuged at 11,180×g for 5 min. The sediment, considered nisin absorbed onto silicic acid, underwent pH adjustment to 3 for nisin desorption34.

Experimental design for optimization of nisin adsorption and desorption

An experimental design was implemented to optimize the adsorption and desorption of nisin by examining three independent variables: the up-stream agitation rate (stirring rate of fermentation broth containing NALP), down-stream agitation time (stirring time of harvested fermentation broth to release nisin from NALP), and down-stream agitation rate (stirring rate of harvested fermentation broth to release nisin from NALP). These variables were analyzed using Response Surface Methodology (RSM), a Box-Behnken design of experiments as implemented in Design Expert software (version 7.0.0, Stat-Ease, Inc., Minneapolis, MN, USA) (Table 1)35. The response variable (nisin removal efficiency) is calculated as the percentage of nisin removed from the fermentation broth. The statistical significance of the model and the interaction effects between variables were evaluated using ANOVA, with a significance level set at 95% (P < 0.05). Data analysis was performed to determine the optimal conditions using regression analysis and contour plots generated by the software.Table 1 Levels and variable codes were selected for nisin biosorption optimization by NALP using the Box-Behnken design.

Independent variables	Codes	Levels	
− 1	0	+ 1	
Up-stream agitation rate (rpm)	A	60	80	100	
Down-stream agitation time (min)	B	60	90	120	
Down-stream agitation rate (rpm)	C	80	115	150	

Microbial growth and product release kinetics

Growth kinetics:

The kinetics of L. lactis growth and nisin production were modeled using the Logistic and Luedeking–Piret equations, respectively. Since nisin production is pronounced during the logarithmic phase, the Logistic model was utilized to predict growth kinetics during the log and stationary growth phases36. The Logistic model is described as follows:

Logistic model Eq. (1):1 dxdt=μmaxX(1-XX_m)

where X is the biomass concentration (g/L), μmax represents the maximum specific growth rate (h−1), and Xm is the maximum achievable biomass concentration (g/L)37. Integration and rearrangement of Eq. (1) results in Eq. (2):2 LnXXm-X=μmt-lnXmX0-1

Luedeking–Piret model Eq. (3):3 dpdt=adxdt+βx

Incorporating the Logistic model into the Luedeking–Piret equation provides a framework to predict nisin production, as shown in Eq. (4):4 Pt=Po+αXoexpμot1-x0x0xmxm1-expμot-1+βx0xmln1-XoXm1-expμot

where α and β are related and unrelated growth coefficients that depend on growth conditions, respectively, x is the biomass concentration (g/L), and P is the product concentration (g/L).

Nonlinear regression using the least-square method was conducted using Microsoft Excel Solver 2010 to fit the experimental data to the Logistic and Luedeking–Piret models38.

Isotherm models

NALP (1 g/L) was introduced into 100 mL Erlenmeyer flasks containing 20 mL of nisin solution across various concentrations (1.4–2.3 mg/L) to investigate the adsorption isotherm. The Langmuir and Freundlich isotherm models were explored to describe the adsorption process:5 Langmuir isotherm:1qe=1qmklCe+1qm

6 Freundlich isotherm:lnqe=lnkf+1nlnCe

RL and Adsorption Affinity (Adsorption Affinity and RL Parameter).

The Langmuir dimensionless constant (RL) is pivotal for evaluating adsorption efficacy:RL=11+KlC0

where RL’s value dictates the adsorption nature: irreversible (RL = 0), favorable (0 < RL < 1), linear (RL = 1), or unfavorable (RL > 1)39.

Statistical analysis

Data were analyzed using SPSS software (version 21, SPSS Inc., Chicago, Illinois, USA). The results underwent analysis of variance (ANOVA), with mean comparisons conducted using the Tukey test at a significance level of 95% (P < 0.05).

Results

Molecular docking analysis

The steric interactions, hydrogen bonding, and electrostatic interactions in the amino acids of nisin have been considered the primary binding sites for the phytochemicals found in N. alba leaf. The results of docking analysis of the binding affinity of principal chemical compounds of N.alba leaf to nisin were summarized in Table 2.Table 2 Docking results of major phytocompounds of N. alba leaf and nisin.

Phytochemical /binding energy (kcal/mol)	Steric interaction	Hydrogen bond	
Di galloyl ellagic acid/− 118.94	Lys35, lys45, Asn43, Met40, Met44, Thr31, Thr36, Csy42	Cys42, lys45	
Chebulagic acid/− 115.48	Lys35, Cys42, Met40, Met44, Thr36	Lys35	
Ellagic acid-galloyl hexoside/− 107.43	Thr36, Cys42, Asn43, Lys35, Lys45, Met44	Lys35, lys45, Asn43, Met44	
Ellagic acid pentoside/− 102.97	Met40, Met44, Thr36, Asn43, Cys42, Lys35	Met44, Asn43, Cys42, Lys35	
The steric interactions and hydrogen bonds within the amino acids of nisin have been demonstrated to serve as the main binding locations for the phytochemicals present in N. alba leaf.

Among the phytochemicals analyzed, di-galloyl ellagic acid exhibited the highest binding affinity toward nisin, characterized by the lowest binding energy values. This interaction primarily involves hydrogen bonding and steric interactions, affecting the selectivity and efficiency of molecular adsorption (Fig. 1). No electrostatic interactions were seen between di-galloyl ellagic acid and nisin by Molegro Molecular Viewer. This suggests that hydrogen bonds and steric interactions play a crucial role in the binding process, highlighting the potential for enhanced adsorption efficiency through these interactions.Fig. 1 Interactions and binding sites of digalloyl ellagic acid (stock symbol), the best pose in N. alba leaf, to complex with nisin (ball and sticks symbol).

Effects of adsorbent amount on nisin adsorption

Figure 2 illustrates the impact of NALP concentrations on nisin adsorption. The maximum adsorption and subsequent desorption of nisin were observed with an adsorbent concentration of 1 g/L. There is no significant difference between total produced nisin (adsorbed nisin plus desorbed nisin) at this concentration and higher concentrations of NALP (p > 0.05). Therefore, from an economic point of view, NALP at a concentration of 1g/L was chosen for further experiments. This concentration provides an optimal balance between adsorption efficiency and cost-effectiveness.Fig. 2 Nisin biosorption in different concentrations of NALP, with desorbed nisin quantified as the concentration successfully removed from the adsorbent material. The quantity of nisin desorbed from the adsorbent material is quantified in International Units per milliliter (IU/mL). Adsorbed nisin + desorbed nisin = total produced nisin.

The effect of NALP pre-treatment on nisin adsorption

The comparative analysis of nisin adsorption by NALP subjected to various chemical pre-treatments is illustrated in Fig. 3.Fig. 3 The effect of various chemical pre-treatments on nisin desorption by NALP. No adsorption ability was seen after treatment by KCl and CaCl2; therefore, it is not shown in the Figure.

It was observed that NALP treated with KCl and CaCl2 exhibited no nisin adsorption capability. In contrast, pre-treatment with HCl, acetone (C3H6O2), acetic acid (C2H4O2), sulfuric acid (H2SO4), and magnesium chloride (MgCl2) significantly enhanced the adsorption capacity of NALP. Notably, HCl and MgCl2 pre-treatments improved nisin desorption efficiency from 46% to approximately 51%, underscoring their effectiveness. Furthermore, MgCl2 at a concentration of 0.15 M emerged as the most potent enhancer of the biosorbent's adsorption capacity, as depicted in Fig. 4. FTIR spectra before and after treated NALP with HCl and MgCl2 were compared in Fig. S3 and FTIR analysis of functional group modifications in NALP treated with MgCl2 and HCl was presented in Table S1. While both MgCl2 and HCl increased the presence of functional groups, including hydroxyl (-OH) and amine (-NH) groups, the FTIR data shows distinct differences in the ranges and types of functional groups introduced (Table S1). MgCl2 appears to provide stronger interactions due to its ability to introduce a broader range of functional groups, such as C–H stretching and C=O stretching, and more effectively modify the surface characteristics compared to HCl. The presence of these functional groups suggests that both treatments may influence the overall adsorption capacity of the NALP.Fig. 4 Impact of NALP pre-treatment with various concentrations of HCl and MgCl2 on the desorption process of nisin, illustrating the optimal conditions for nisin recovery.

Nisin adsorption by silicic acid and NALP

The comparative assessment of nisin production in the presence of NALP and silicic acid is presented in Fig. 5. The results demonstrated ∼a 22% increase in nisin production in the media containing NALP and silicic acid compared to the control group (no silicic acid or NALP) (p < 0.05). Moreover, the desorption capability of NALP was marginally superior to silicic acids', although this difference was not statistically significant (p > 0.05).Fig. 5 Comparative analysis of nisin desorption capabilities between NALP and silicic acid. Statistical significance was denoted by an asterisk (*p < 0.05).

Biosorption optimization analysis via RSM

The optimization of nisin adsorption from fermentation broth utilizing the RSM is comprehensively detailed in Table 3. The desorption efficiency of nisin, denoted as Y, was accurately predicted by the regression Eq. (7)Table 3 Analysis of variance of the RSM model.

Source	Sum of squares	Df	Mean square	F-value	P-value
Prob > F		
Model	1.899E+009	9	2.110E+008	15.49	0.00	Significant	
 A: Up-stream agitation rate (rpm)	1.270E+007	1	1.270E+007	0.93	0.36		
 B: Down-stream agitation time (min)	1.030E+007	1	1.030E+007	0.76	0.41		
 C: Down-stream agitation rate (rpm)	2.877E+008	1	2.877E+008	21.13	0.00		
 AB	7.463E+006	1	7.463E+006	0.55	0.48		
 AC	4.237E+007	1	4.237E+007	3.11	0.12		
 BC	1.349E+009	1	1.349E+009	99.10	 < 0.00		
 A2	3.682E+007	1	3.682E+007	2.70	0.14		
 B2	1.103E+008	1	1.103E+008	8.10	0.02		
 C2	5.118E+007	1	5.118E+007	3.76	0.09		
Residual	9.532E+007	7	1.362E+007			Not significant	
 Lack of fit	2.035E+006	3	6.782E+005	0.029			
 Pure error	9.329E+007	4	2.332E+007		0.99		
Cor total	1.994E+009	16					

7 Y1.8=1.103E+005+1259.96A-1134.74B+5997.35C+1365.95AB+3254.55AC-18367.33BC-2957.30A2+5118.17B2-3486.27C2

A, B, and C represented the upstream agitation rate, downstream agitation time, and downstream agitation rate, respectively. This equation illustrated the intricate interactions between these operational parameters and their impact on nisin desorption efficiency.

The coefficient of determination (R2), measuring the proportion of variability in the response variable that the model can explain, was recorded at an impressive 0.95. This high R2 value signifies that 95% of the variance in nisin desorption efficiency is predictable from the independent variables. Furthermore, the adjusted R2, which adjusts R2 for the number of predictors in the model, was 0.89. This adjustment is crucial for models with multiple predictors, providing a more accurate measure of the model's explanatory power. The high adjusted R2 further showed the model's accuracy and reliability in predicting nisin desorption efficiency.

Predictive model validation

The normal distribution and scattered plots of predicted versus experimental values of nisin desorption were illustrated in Fig. 6a,b, respectively, demonstrating a high degree of concordance and validating the predictive power of the optimization model.Fig. 6 The normal distribution (a) and scattered (b) plots of predicted versus experimental values of nisin desorption.

The robustness of the RSM model was rigorously assessed through variance analysis, a statistical method that decomposes the total variance observed in the response into components attributable to specific sources of variation. The analysis revealed a non-significant lack of fit, underscoring the model's strong predictability. This outcome indicated that the model can reliably explain the variance in nisin desorption efficiency without overfitting the data to random noise or unaccounted variability.

The statistical significance of the RSM model was further evaluated by examining the p-value associated with the model's F-statistic. A p-value of less than 0.0001 significantly rejects the null hypothesis that the model's regression coefficients are all zero, implying that at least one of the model's predictors is significantly related to the response variable. This result unequivocally supports the model's relevance and explanatory power regarding nisin desorption efficiency.

Combinatorial impacts of factors affecting biosorption

The combinatorial effects of downstream agitation rate, downstream agitation time, and upstream agitation rate on nisin desorption are shown in Fig. 7. An increase in the downstream agitation rate and a concurrent decrease in agitation time resulted in enhanced nisin desorption (Fig. 7A). Also, decreasing the downstream and upstream agitation rates increased nisin desorption (Fig. 7B). The average numerical value of downstream agitation time and upstream agitation rate decreased the nisin desorption (Fig. 7C). These findings highlight the significant impact of agitation rates and times on nisin desorption efficiency.Fig. 7 Three-dimensional response surface methodology (RSM) plot depicting the interaction effects between (A) downstream agitation rate and time, (B) downstream agitation rate and upstream agitation rate, (C) downstream agitation time and upstream agitation rate on efficiency of nisin desorption from NALP.

Optimization of fermentation parameters

Following the optimization of fermentation parameters, significant enhancements in nisin production and microbial growth were observed in the presence of the optimized biosorbent (NALP), as shown in Fig. 8. Nisin production increased from 500 to 630 IU/ml, and CFU numbers surged from 2 to 4 × 109, both changes being statistically significant improvements (p < 0.05). However, no significant pH alterations were detected in the presence versus absence of the biosorbent (p > 0.05).Fig. 8 Growth dynamics of L. lactis in the presence and absence of the optimized biosorbent (NALP). (A) pH, (B) nisin concentration and (C) biomass production were shown.

Analysis of zeta potential and point of zero charge

The zeta potential of the NALP (pH-ZPC) was measured at − 40.9 mV at pH 6.5, aiding in understanding the surface charge characteristics of NALP. The point of zero charge (pH-PZC), determined to be 6.3, provides insights into the peptide adsorption process by indicating the pH at which the initial and final pH values converge, as depicted in Fig. 9.Fig. 9 Determination of the point of zero charge (pH-PZC) of the biosorbent (NALP), indicating its surface charge properties under different pH conditions.

FTIR analysis

The FTIR Spectroscopy analysis, aimed at identifying the functional groups involved in nisin adsorption onto NALP, is depicted in Fig. 10. Significant alterations in peak positions and intensities upon nisin adsorption indicate the involvement of specific functional groups: C–H stretching: A shift from 2962 to 2924 cm−1, attributable to the C–H stretching vibrations in CH, CH2, and CH3 groups, was observed, suggesting their role in adsorption.Fig. 10 Fourier-transform infrared spectroscopy (FTIR) spectra of the biosorbent (NALP) before and after adsorption, highlighting functional group interactions and chemical changes upon nisin binding.

C–H deformation: The peak initially at 660 cm−1, indicative of C–H deformation, moved to 672 cm−1 post-adsorption.

OH or NH stretching: An alteration from 3221 to 3236 cm−1 was noted, along with a shift in the O–H bending peak from 709 to 678 cm−1.

These shifts imply the engagement of the aforementioned functional groups in the nisin adsorption process, providing insights into the chemical interactions underpinning the biosorption mechanism (Fig. 10).

SEM analysis

The SEM analysis of nisin and NALP revealed significant morphological changes after nisin adsorption (Fig. 11). Sparse pores were seen on the surfaces of intact NALP. Following its exposure to nisin adsorption, the surface became rougher and more heterogeneous.Fig. 11 Scanning electron micrograph: intact NALP (A,B) biosorbed nisin on NALP (C,D).

Isotherm results and interpretation

The adsorption isotherm studies on the adsorption of nisin on NALP revealed that the Langmuir and Freundlich isotherm models were good fits for the experimental data (Table 4).Table 4 Langmuir and Freundlich parameters for nisin adsorption by NALP.

Isotherm	Langmuir	Freundlich	
Parameter	R2	qm (mg/g)	KL (L/mg)	RL	R2	Kf (L/mg)	1/n	
Amount	0.9969	105.25	0.29	0.6–0.7	0.9981	24.17	0.81	

The Langmuir isotherm model indicated a monolayer adsorption process with a maximum capacity of 105.26 mg/g, supported by a high regression coefficient (R2 0.9969) and a Langmuir constant (kl 0.29 L/mg). On the other hand, the Freundlich isotherm model also showed a good fit (R2 0.9981), emphasizing the heterogeneous nature of the adsorbent surface. The parameter 1/n in the Freundlich isotherm model was found to be 0.8, indicating a favorable adsorption process, which further supports the efficiency of N. alba as a biosorbent for nisin. These results provide valuable insights into the adsorption mechanisms of nisin on NALP (Fig. 12).Fig. 12 Langmuir (A) and Freundlich (B) isotherm analysis of nisin adsorption by NALP.

Model-based analysis of microbial growth and nisin production

The microbial growth and nisin production during fermentation were modeled to assess the impact of the biosorbent. Using Eq. (2), the analysis indicated significant microbial colonization within the first 10 h of fermentation, achieving a maximum colony formation (Xm) of 4.01 × 109 CFU/ml. The microbial growth rate (μm) and initial microbial concentration (X0) were derived from the plot of ln x/(xm − x) against time, revealing enhanced growth in the presence of the biosorbent. In the biosorbent's presence, the microbial growth rate (μm) was 1.12 h−1, surpassing the control's growth rate and indicating a favorable environment for microbial proliferation. Initial microbial concentration (X0) was determined as 0.005 CFU/ml, confirming the biosorbent's positive effect on microbial initiation.

Correlation analysis between predicted and experimental values showcased a robust model fit, with R2 values of 0.95 in the biosorbent's presence and 0.93 in its absence. The Luedeking–Piret model parameters, illustrated in Table 5, underscored the model's accuracy in both scenarios (R2 of 98% with biosorbent, 96% without), affirming the biosorbent's efficacy in enhancing nisin production and microbial growth.Table 5 Estimated parameters based on logistic and Luedeking–Piret models.

Model name	Parameters	Nisin (control)	Nisin + adsorbent	
Logistic	μ (h−1)	0.98	1.12	
R2	93%	95%	
Luedeking–Piret	Α	0.23	0.21	
Β	0.03	0.01	
R2	96%	98%	

Discussion

This study explored the effectiveness of NALP as a super-hydrophobic plant-based biosorbent for in-situ nisin removal, positioning it as a groundbreaking approach to minimize downstream process costs in L. lactis production, unlike conventional methods that rely on chemical compounds such as silicic acid and amberlite XAD-4 resin40. There is no significant difference in the efficiency of NALP and silicic acid in nisin removal from fermentation broth (p > 0.05). NALP demonstrates a comparable adsorption capacity (573 IU/ml) to silicic acid (540 IU/ml). However, it is a more cost-effective and environmentally friendly absorbent for nisin than sialic acid. This observation underscores the potential of plant-based biosorbents in biotechnological applications, particularly considering their economic and ecological benefits. The economic implications are significant, as utilizing a plant-based biosorbent could reduce costs associated with chemical sorbents and waste disposal while also providing a renewable resource that supports eco-friendly production processes41. Results of nisin-NALP interaction study by molecular docking analysis highlighted di-galloyl ellagic acid as a critical mediator of nisin adsorption, a compound prevalent in various plants known for its adsorptive properties. Ellagic acid and its derivatives possess unique structural features that make them effective biosorbents. Their polyphenolic structure with multiple OH groups, efficient stacking interactions with other molecules due to their planar configuration, and biocompatibility, combined with multiple adsorption mechanisms, make them promising candidates for biosorption42.

Recovery conditions can result in negative effects on the bioactivity and efficiency of biologics43 that cannot be detected by a quantitative chemical method, e.g., HPLC44. Nisin can be measured in fermentation broth using HPLC and a microbial assay. However, HPLC is more precise and quantitative than bioassay and is used to determine the concentration and purity of produced nisin. However, bioassays are more sensitive in detecting changes in the bioactivity of nisin. However, no adverse effect was seen on the bioactivity of nisin after adsorption and desorption of nisin on NALP (Fig. S2).

Chemical pretreatments of biosorbents modified their functional groups and improved biosorption efficiency. For example, C2H5COOH, NH3, and H2SO4 enhanced the biosorption potential of rice straw45, Lagenaria breviflora seeds46, and Euphorbia rigida47, respectively, resulting in increased biosorption efficiency. The biosorption capacity of NALP was increased by MgCl2 and HCl treatment modifications. Maximum heavy metal removal by NALP21 and biochar48 were seen after their modification by MgCl2. The enhancement of adsorption capacity through these treatments suggests potential modifications in surface charge and functional group availability, which may warrant further investigation for optimization. In a similar vein, the presence of Mg2+ ions can lead to stronger cationic interactions with the adsorbent surface, altering the surface charge and creating a more hydrophobic environment. This change in hydrophobicity makes the adsorbent less attractive to water and more favorable for the adsorption of hydrophobic organic compounds49.

To optimize the in-situ separation process, it is essential to balance the upstream agitation rate, which is crucial for adsorption, with the downstream agitation rate and time, which enhances effective desorption. Proper agitation in the upstream phase promotes cell growth and nisin production by improving mass transfer and nutrient distribution. Conversely, the downstream agitation rate is vital for facilitating the release of nisin from the NALP. While adequate agitation can significantly improve yields, excessive agitation may induce shear stress and reduce nisin production, as seen in the nisin measured in the desorption section. By carefully tuning these agitation parameters, the efficiency of the in-situ separation process can be maximized while also addressing the challenges associated with product condensation due to cost and time constraints. Effective removal of sorbent from absorbent is a critical step in ISPR. Strong interaction or equilibrium states in favor of the adsorption of compounds can hinder sorbent release during desorption processes50,51. The result of the current research revealed that ISPR optimization by RSM enhanced the productivity and yield of the nisin production by decreasing the downstream agitation rate and increasing the upstream agitation rate, which may be due to the changing the flow velocity and mass transfer rates in the adsorption and desorption processes yield. A comparison of the current findings with the DamKohler number (Da) confirms that higher agitation rates and shorter desorption times improved the process's productivity, which is attributed to the accelerated mass transfer52. Da is calculated by comparing the transport time scale to the reaction time scale and is a valuable tool for determining whether a reversible chemical reaction is fast enough to be treated as being in instantaneous equilibrium or slow enough to disregard the adsorption/desorption of the chemical associated with the particle53. These findings align with the recent study that indicates the Da is significantly influenced by internal and external mass transfer coefficients, which are affected by compression forces and stirrer speeds.

By consideration of the isoelectric point of nisin (> 8.5)54 and NALP (6.3) (Fig. 9), nisin desorption from the surface of NALP was effectivity achieved by an acidic solution (pH 3 ± 0.2). The zeta potential (ZPC) of NALP (− 40.9), which makes it a suitable biosorbent for nisin (Fig. 9), and the ZPC of nisin (− 10 mv)55, showed the high electrostatic interaction between them. Despite not being explicitly quantified in some docking analyses, electrostatic interactions can dominate the binding energy terms, as seen in studies involving charge-charge interactions across protein interfaces, and the polarization of polar groups, which is often neglected in traditional force fields, also significantly contributes to electrostatic interaction energy56.

ISPR can significantly impact microbial strains' growth kinetics and biologics' overall production efficiency. In-situ nisin removal by NALP increased biomass and nisin production by 100% and 26%, respectively (Fig. 8), suggesting that nisin binding may mitigate its inhibitory effects on bacterial growth. In the presence of the biosorbent, the growth rate (μ) is 14% higher compared to its absence. That may be due to cell immobilization and the attachment of L. lactis cells to NALP as a support matrix. The present result demonstrated biochar's potential as a microbial carrier for agriculture and environmental applications57.

Nisin adsorption on NALP is a complex process, and the high regression coefficients for Langmuir and Freundlich indicate that both models adequately describe the adsorption behavior, suggesting a heterogeneous adsorption system with varying binding sites and affinities58. Both monolayer and multilayer adsorption indicate a dynamic and complex adsorption system. The involvement of various functional groups on the surface of NALP and its heterogeneous surface creates a complex adsorption mechanism. The strong interactions facilitated by OH or NH groups promote monolayer adsorption, while the weaker interactions mediated by C–H groups allow multilayer adsorption. Scanning electron microscopy (SEM) analysis also revealed a heterogeneous surface of NALP that may further support the adsorption process's complexity. Further studies, including additional spectroscopic techniques such as X-ray photoelectron spectroscopy (XPS) or surface-enhanced Raman spectroscopy (SERS), could provide more detailed insights into the bonds between nisin and NALP. These studies would help understand the specific interactions involved and the adsorption dynamics.

Using FTIR and SEM in tandem provides a comprehensive approach to studying the adsorption mechanisms of nisin to NALP. FTIR offers insights into the chemical interactions at the molecular level, showing the contributions of C–H, OH, and NH groups in the adsorption of nisin to NALP (Fig. 11). The contributions of hydrogen bonding and electrostatic interactions of nisin in adsorption have been previously demonstrated by FTIR59. Meanwhile, SEM provides valuable information about the physical changes in NALP's surface. By the current research, physical and chemical changes in NALP were observed after the adsorption of heavy metals. However, the morphology of leaf protrusions after attaching to NALP differed from that of heavy metals21. The SEM images likely reveal a distinct coating or layer on the external surface of the leaf following heavy metal biosorption, suggesting that the ions are binding to the external functional groups. In contrast, nisin, which contains both polar and non-polar amino acid residues, can engage in hydrophobic interactions with the hydrophobic regions of NALP. This interaction can facilitate internal binding, as nisin molecules may draw into the internal spaces of the biosorbent, owing to their smaller molecular size compared to heavy metal ions.

Acknowledging the limitations of this study, such as the scalability of using NALP on an industrial scale and the potential variability in biosorbent performance due to environmental factors, is crucial. Future research should focus on exploring these aspects: the culture of N. alba, optimizing biosorbent treatments, biosorption recycling, and investigating the underlying mechanisms of adsorption at a molecular level to improve efficiency and applicability. Integrating molecular mechanics generalized born surface area (MM-GBSA) calculations and molecular dynamics (MD) simulations into studying phytochemicals like di-galloyl ellagic acid can significantly enhance our understanding of their interactions with targets such as nisin. Also, future research should focus on elucidating the mechanisms by which NALP enhances microbial growth and nisin production, exploring its long-term effects in various fermentation systems, and assessing its scalability for industrial applications.

Conclusion

Developing innovative methods for producing and extracting bio-compounds from fermentation broth is crucial for enhancing the efficiency and cost-effectiveness of biotechnological processes. This study presents a novel approach that utilizes NALP as a biosorbent for the in-situ extraction of nisin during fermentation. Hydrophobic and electrostatic interactions, hydrogen bonds, and reversible and fast chemical reactions facilitate the adsorption/desorption of nisin to NALP. The agitation rate in fermentation and recovery processes can be increased to enhance adsorption and desorption activities. The adsorption process is growth-related, producing higher L. lactis growth and nisin. The isotherm study confirms the heterogeneity of the biosorbent surface. The current research results are consistent with various green chemistry principles, including using safer solvents and auxiliaries, design for energy efficiency, use of renewable feedstocks, and design for degradation. In situ, nisin recovery by NALP may have practical implications in biotechnology.

Supplementary Information

Supplementary Information.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-024-71513-0.

Author contributions

We confirm that this manuscript has not been published elsewhere and is not under consideration by another journal. All authors participated in the research. L. Khazravi (PhD candidate) was done the experiments and wrote the manuscript, and J. Hamedi, H. attar and M. Ardjmand designed and supervised the experiments and edited and revised the manuscript.

Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Torres MDT Sothiselvam S Lu TK de la Fuente-Nunez C Peptide design principles for antimicrobial applications J. Mol. Biol. 2019 431 18 3547 3567 10.1016/j.jmb.2018.12.015 30611750
Torres, M. D. T., Sothiselvam, S., Lu, T. K. & de la Fuente-Nunez, C. Peptide design principles for antimicrobial applications. J. Mol. Biol. 431(18), 3547–3567 (2019).30611750 10.1016/j.jmb.2018.12.015
2. de Pontes JTC Toledo Borges AB Roque-Borda CA Pavan FR Antimicrobial peptides as an alternative for the eradication of bacterial biofilms of multi-drug resistant bacteria Pharmaceutics. 2022 14 3 642 10.3390/pharmaceutics14030642 35336016
de Pontes, J. T. C., Toledo Borges, A. B., Roque-Borda, C. A. & Pavan, F. R. Antimicrobial peptides as an alternative for the eradication of bacterial biofilms of multi-drug resistant bacteria. Pharmaceutics. 14(3), 642 (2022).35336016 10.3390/pharmaceutics14030642
3. Wang T Liang C Xing W Wu W Hou Y Zhang L Xiao S Xu H An Y Zheng M Transcriptional factor engineering in microbes for industrial biotechnology J. Chem. Technol. Biotechnol. 2020 95 12 3071 3078 10.1002/jctb.6512
Wang, T. et al. Transcriptional factor engineering in microbes for industrial biotechnology. J. Chem. Technol. Biotechnol. 95(12), 3071–3078 (2020).10.1002/jctb.6512
4. Dischinger J Chipalu SB Bierbaum G Lantibiotics: Promising candidates for future applications in health care Int. J. Med. Microbiol. 2014 304 1 51 62 10.1016/j.ijmm.2013.09.003 24210177
Dischinger, J., Chipalu, S. B. & Bierbaum, G. Lantibiotics: Promising candidates for future applications in health care. Int. J. Med. Microbiol. 304(1), 51–62 (2014).24210177 10.1016/j.ijmm.2013.09.003
5. Sarkar P Bhunia A Yao Y Nisin adsorption in colloidal systems formed with phytoglycogen octenyl succinate Food Biophys. 2016 11 311 318 10.1007/s11483-016-9436-5
Sarkar, P., Bhunia, A. & Yao, Y. Nisin adsorption in colloidal systems formed with phytoglycogen octenyl succinate. Food Biophys. 11, 311–318 (2016).10.1007/s11483-016-9436-5
6. Müller-Auffermann K Grijalva F Jacob F Hutzler M Nisin and its usage in breweries: A review and discussion J. Inst. Brew. 2015 121 3 309 319 10.1002/jib.233
Müller-Auffermann, K., Grijalva, F., Jacob, F. & Hutzler, M. Nisin and its usage in breweries: A review and discussion. J. Inst. Brew. 121(3), 309–319 (2015).10.1002/jib.233
7. Pongtharangkul Th Demirci A Effects of fed-batch fermentation and pH profiles on nisin production in suspended-cell and biofilm reactors Appl. Microbiol. Biotechnol. 2006 73 1 73 79 10.1007/s00253-006-0459-6 16733734
Pongtharangkul, Th. & Demirci, A. Effects of fed-batch fermentation and pH profiles on nisin production in suspended-cell and biofilm reactors. Appl. Microbiol. Biotechnol. 73(1), 73–79 (2006).16733734 10.1007/s00253-006-0459-6
8. Arruda, E. J., & Santana, C. C. Phenylboronate-chitosan resins for adsorption of ß-amylase from soybean extracts. In Biotechnology for Fuels and Chemicals, pp. 829–842 (Springer, 2003).
9. Dafoe JT Daugulis AJ In situ product removal in fermentation systems: Improved process performance and rational extractant selection Biotechnol. Lett. 2014 36 3 443 460 10.1007/s10529-013-1380-6 24141707
Dafoe, J. T. & Daugulis, A. J. In situ product removal in fermentation systems: Improved process performance and rational extractant selection. Biotechnol. Lett. 36(3), 443–460 (2014).24141707 10.1007/s10529-013-1380-6
10. Najmi Z Ebrahimipour G Franzetti A Banat IM In situ downstream strategies for cost-effective bio/surfactant recovery Biotechnol. Appl. Biochem. 2018 65 4 523 532 10.1002/bab.1641 29297935
Najmi, Z., Ebrahimipour, G., Franzetti, A. & Banat, I. M. In situ downstream strategies for cost-effective bio/surfactant recovery. Biotechnol. Appl. Biochem. 65(4), 523–532 (2018).29297935 10.1002/bab.1641
11. Salas-Villalobos UA Gómez-Acata RV Castillo-Reyna J Aguilar O In situ product recovery as a strategy for bioprocess integration and depletion of inhibitory products J. Chem. Technol. Biotechnol. 2021 96 10 2735 2743 10.1002/jctb.6797
Salas-Villalobos, U. A., Gómez-Acata, R. V., Castillo-Reyna, J. & Aguilar, O. In situ product recovery as a strategy for bioprocess integration and depletion of inhibitory products. J. Chem. Technol. Biotechnol. 96(10), 2735–2743 (2021).10.1002/jctb.6797
12. Cheng K-K Zhao X-B Zeng J Wu R-C Xu Y-Z Liu D-H Zhang J-A Downstream processing of biotechnological produced succinic acid Appl. Microbiol. Biotechnol. 2012 95 4 841 850 10.1007/s00253-012-4214-x 22707056
Cheng, K.-K. et al. Downstream processing of biotechnological produced succinic acid. Appl. Microbiol. Biotechnol. 95(4), 841–850 (2012).22707056 10.1007/s00253-012-4214-x
13. Huang Q Dalai AK Zhang L Niu CH Equilibrium study and analysis of site energy distribution of butanol sorption on a biosorbent Energy Fuels. 2016 35 8 6681 6690 10.1021/acs.energyfuels.0c03875
Huang, Q., Dalai, A. K., Zhang, L. & Niu, C. H. Equilibrium study and analysis of site energy distribution of butanol sorption on a biosorbent. Energy Fuels. 35(8), 6681–6690 (2016).10.1021/acs.energyfuels.0c03875
14. Rossetto R Maciel GM Bortolini DG Ribeiro VR Haminiuk CWI Acai pulp and seeds as emerging sources of phenolic compounds for enrichment of residual yeasts (Saccharomyces cerevisiae) through biosorption process Lwt. 2020 128 109447 10.1016/j.lwt.2020.109447
Rossetto, R., Maciel, G. M., Bortolini, D. G., Ribeiro, V. R. & Haminiuk, C. W. I. Acai pulp and seeds as emerging sources of phenolic compounds for enrichment of residual yeasts (Saccharomyces cerevisiae) through biosorption process. Lwt. 128, 109447 (2020).10.1016/j.lwt.2020.109447
15. Zheng H Zhang D Guo K Dong K Xu D Wu Z Online recovery of nisin during fermentation coupling with foam fractionation J. Food Eng. 2015 162 25 30 10.1016/j.jfoodeng.2015.04.006
Zheng, H. et al. Online recovery of nisin during fermentation coupling with foam fractionation. J. Food Eng. 162, 25–30 (2015).10.1016/j.jfoodeng.2015.04.006
16. Jozala AF Lopes AM Mazzola PG Magalhães PO Penna TCV Pessoa A Jr Liquid–liquid extraction of commercial and biosynthesized nisin by aqueous two-phase micellar systems Enzyme Microb Technol. 2008 42 2 107 112 10.1016/j.enzmictec.2007.08.005 22578859
Jozala, A. F. et al. Liquid–liquid extraction of commercial and biosynthesized nisin by aqueous two-phase micellar systems. Enzyme Microb Technol. 42(2), 107–112 (2008).22578859 10.1016/j.enzmictec.2007.08.005
17. Belton DJ Deschaume O Perry CC An overview of the fundamentals of the chemistry of silica with relevance to bio silicification and technological advances FEBS J. 2012 279 10 1710 1720 10.1111/j.1742-4658.2012.08531.x 22333209
Belton, D. J., Deschaume, O. & Perry, C. C. An overview of the fundamentals of the chemistry of silica with relevance to bio silicification and technological advances. FEBS J. 279(10), 1710–1720 (2012).22333209 10.1111/j.1742-4658.2012.08531.x
18. Bakr RO El-Naa MM Zaghloul SS Omar MM Profile of bioactive compounds in Nymphaea alba L. leaf growing in Egypt: Hepatoprotective, antioxidant and anti-inflammatory activity BMC Complement Altern. Med. 2017 17 1 1 13 10.1186/s12906-017-1561-2 28049463
Bakr, R. O., El-Naa, M. M., Zaghloul, S. S. & Omar, M. M. Profile of bioactive compounds in Nymphaea alba L. leaf growing in Egypt: Hepatoprotective, antioxidant and anti-inflammatory activity. BMC Complement Altern. Med. 17(1), 1–13 (2017).28049463 10.1186/s12906-017-1561-2
19. Ensikat HJ Ditsche-Kuru P Neinhuis C Barthlott A Superhydrophobicity in perfection: the outstanding properties of the lotus leaf Beilstein J. Nanotechnol. 2010 2 152 161 10.3762/bjnano.2.19
Ensikat, H. J., Ditsche-Kuru, P., Neinhuis, C. & Barthlott, A. Superhydrophobicity in perfection: the outstanding properties of the lotus leaf. Beilstein J. Nanotechnol. 2, 152–161 (2010).10.3762/bjnano.2.19
20. Cudalbeanu M Furdui B Cârâc G Barbu V Iancu AV Marques F Leitão JH Sousa SA Dinica RM Antifungal, antitumoral and antioxidant potential of the danube delta Nymphaea alba extracts Antibiotics. 2019 9 1 7 10.3390/antibiotics9010007 31877815
Cudalbeanu, M. et al. Antifungal, antitumoral and antioxidant potential of the danube delta Nymphaea alba extracts. Antibiotics. 9(1), 7 (2019).31877815 10.3390/antibiotics9010007
21. Zahedi R Dabbagh R Ghafourian H Behbahanini A Nickel removal by Nymphaea alba leaves and effect of leaves treatment on the sorption capacity: A kinetic and thermodynamic study Water Resour. 2015 42 5 690 698 10.1134/S0097807815050152
Zahedi, R., Dabbagh, R., Ghafourian, H. & Behbahanini, A. Nickel removal by Nymphaea alba leaves and effect of leaves treatment on the sorption capacity: A kinetic and thermodynamic study. Water Resour. 42(5), 690–698 (2015).10.1134/S0097807815050152
22. Jalili, A., & Jamzad, Z. Red data book of Iran: A preliminary survey of endemic, rare and endangered plant species in Iran (1999).
23. Wong KT Wong VL Lim SS Bio-sorptive removal of methyl orange by micro-grooved chitosan (GCS) beads: Optimization of process variables using Taguchi L9 orthogonal array J. Polym. Environ. 2020 29 1 271 290 10.1007/s10924-020-01878-6
Wong, K. T., Wong, V. L. & Lim, S. S. Bio-sorptive removal of methyl orange by micro-grooved chitosan (GCS) beads: Optimization of process variables using Taguchi L9 orthogonal array. J. Polym. Environ. 29(1), 271–290 (2020).10.1007/s10924-020-01878-6
24. Lunardi CN Gomes AJ Rocha FS De Tommaso J Patience GS Experimental methods in chemical engineering: Zeta potential Can. J. Chem. Eng. 2021 99 3 627 639 10.1002/cjce.23914
Lunardi, C. N., Gomes, A. J., Rocha, F. S., De Tommaso, J. & Patience, G. S. Experimental methods in chemical engineering: Zeta potential. Can. J. Chem. Eng. 99(3), 627–639 (2021).10.1002/cjce.23914
25. Masoudi, R., Moghimi, H., Azin, E., & Taheri, R. A. Adsorption of cadmium from aqueous solutions by novel Fe(3)O(4)-newly isolated Actinomucor sp. bio-nanoadsorbent: Functional group study. Artif. Cells Nanomed. Biotechnol. 46(sup3), S1092–S1101 (2018).
26. Grosdidier, A., Zoete, V., & Michielin, O. SwissDock, a protein-small molecule docking web service based on EADock DSS. Nucleic Acids Res. 39(Web Server issue), W270–W277 (2011).
27. Mitra S Naskar N Chaudhuri P A review on potential bioactive phytochemicals for novel therapeutic applications with special emphasis on mangrove species Phytomed. Plus. 2021 1 4 1 10.1016/j.phyplu.2021.100107
Mitra, S., Naskar, N. & Chaudhuri, P. A review on potential bioactive phytochemicals for novel therapeutic applications with special emphasis on mangrove species. Phytomed. Plus. 1(4), 1 (2021).10.1016/j.phyplu.2021.100107
28. Scotti L Mendonca Junior FJ Ishiki HM Ribeiro FF Singla RK Barbosa Filho JM Da Silva MS Scotti MT Docking studies for multi-target drugs Curr. Drug Targets. 2017 18 5 592 604 10.2174/1389450116666150825111818 26302806
Scotti, L. et al. Docking studies for multi-target drugs. Curr. Drug Targets. 18(5), 592–604 (2017).26302806 10.2174/1389450116666150825111818
29. Cosconati S Forli S Perryman AL Harris R Goodsell DS Olson AJ Virtual screening with AutoDock: theory and practice Expert Opin. Drug Discov. 2010 5 6 597 607 10.1517/17460441.2010.484460 21532931
Cosconati, S. et al. Virtual screening with AutoDock: theory and practice. Expert Opin. Drug Discov. 5(6), 597–607 (2010).21532931 10.1517/17460441.2010.484460
30. Lv W Cong W Cai Z Nisin production by Lactococcus lactis subsp lactis under nutritional limitation in fed-batch culture Biotechnol. Lett. 2004 26 235 238 10.1023/B:BILE.0000013721.78288.1d 15049369
Lv, W., Cong, W. & Cai, Z. Nisin production by Lactococcus lactis subsp lactis under nutritional limitation in fed-batch culture. Biotechnol. Lett. 26, 235–238 (2004).15049369 10.1023/B:BILE.0000013721.78288.1d
31. Ariana M Hamedi J Enhanced production of nisin by co-culture of Lactococcus lactis sub sp. lactis and Yarrowia lipolytica in molasses-based medium J. Biotechnol. 2017 256 21 26 10.1016/j.jbiotec.2017.07.009 28694185
Ariana, M. & Hamedi, J. Enhanced production of nisin by co-culture of Lactococcus lactis sub sp. lactis and Yarrowia lipolytica in molasses-based medium. J. Biotechnol. 256, 21–26 (2017).28694185 10.1016/j.jbiotec.2017.07.009
32. Papiran R Hamedi J Adaptive evolution of Lactococcus Lactis to thermal and oxidative stress increase biomass and nisin production Appl. Biochem. Biotechnol. 2021 193 11 3425 3441 10.1007/s12010-021-03609-6 34196920
Papiran, R. & Hamedi, J. Adaptive evolution of Lactococcus Lactis to thermal and oxidative stress increase biomass and nisin production. Appl. Biochem. Biotechnol. 193(11), 3425–3441 (2021).34196920 10.1007/s12010-021-03609-6
33. Pongtharangkul T Demirci A Evaluation of agar diffusion bioassay for nisin quantification Appl. Microbiol. Biotechnol. 2004 65 3 268 272 10.1007/s00253-004-1579-5 14963617
Pongtharangkul, T. & Demirci, A. Evaluation of agar diffusion bioassay for nisin quantification. Appl. Microbiol. Biotechnol. 65(3), 268–272 (2004).14963617 10.1007/s00253-004-1579-5
34. Janes ME Nannapaneni R Proctor A Johnson MG Rice hull ash and silicic acid as adsorbents for concentration of bacteriocins Appl. Environ. Microbiol. 1998 64 11 4403 4409 10.1128/AEM.64.11.4403-4409.1998 9797298
Janes, M. E., Nannapaneni, R., Proctor, A. & Johnson, M. G. Rice hull ash and silicic acid as adsorbents for concentration of bacteriocins. Appl. Environ. Microbiol. 64(11), 4403–4409 (1998).9797298 10.1128/AEM.64.11.4403-4409.1998
35. Guo W Zhang Y Lu J Jiang L Teng L Wang Y Liang Y Optimization of fermentation medium for nisin production from Lactococcus lactis subsp. lactis using response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA) Afr. J. Biotechnol. 2010 9 38 6264 6272
Guo, W. et al. Optimization of fermentation medium for nisin production from Lactococcus lactis subsp. lactis using response surface methodology (RSM) combined with artificial neural network-genetic algorithm (ANN-GA). Afr. J. Biotechnol. 9(38), 6264–6272 (2010).
36. Diaz C Lelong P Dieu P Feuillerat C Salomé M On-line analysis and modeling of microbial growth using a hybrid system approach Process Biochem. 1999 34 1 39 47 10.1016/S0032-9592(98)00064-8
Diaz, C., Lelong, P., Dieu, P., Feuillerat, C. & Salomé, M. On-line analysis and modeling of microbial growth using a hybrid system approach. Process Biochem. 34(1), 39–47 (1999).10.1016/S0032-9592(98)00064-8
37. Rajasekar V Murty RV Muthukumaran C Development of a simple kinetic model and parameter estimation for biomass and nattokinase production by Bacillus subtilis 1A752 Austin J. Biotechnol. Bioeng. 2016 2 1 1
Rajasekar, V., Murty, R. V. & Muthukumaran, C. Development of a simple kinetic model and parameter estimation for biomass and nattokinase production by Bacillus subtilis 1A752. Austin J. Biotechnol. Bioeng. 2(1), 1 (2016).
38. Pongtharangkul T Demirci A Puri V Modeling growth and nisin production by Lactococcus lactis during batch fermentation Biol. Eng. Trans. 2008 1 3 265 275 10.13031/2013.25335
Pongtharangkul, T., Demirci, A. & Puri, V. Modeling growth and nisin production by Lactococcus lactis during batch fermentation. Biol. Eng. Trans. 1(3), 265–275 (2008).10.13031/2013.25335
39. Saadi R Saadi Z Fazaeli R Fard NE Monolayer and multilayer adsorption isotherm models for sorption from aqueous media Kor. J. Chem. Eng. 2015 32 787 799 10.1007/s11814-015-0053-7
Saadi, R., Saadi, Z., Fazaeli, R. & Fard, N. E. Monolayer and multilayer adsorption isotherm models for sorption from aqueous media. Kor. J. Chem. Eng. 32, 787–799 (2015).10.1007/s11814-015-0053-7
40. Tolonen M Saris P Siika-aho M Production of nisin with continuous adsorption to amberlite XAD-4 resin using Lactococcus lactis N8 and L. lactis LAC48 Appl. Microbiol. Biotechnol. 2004 63 659 665 10.1007/s00253-003-1413-5 12910326
Tolonen, M., Saris, P. & Siika-aho, M. Production of nisin with continuous adsorption to amberlite XAD-4 resin using Lactococcus lactis N8 and L. lactis LAC48. Appl. Microbiol. Biotechnol. 63, 659–665 (2004).12910326 10.1007/s00253-003-1413-5
41. Liu Y Biswas B Hassan M Naidu R Green adsorbents for environmental remediation: Synthesis methods, ecotoxicity, and reusability prospects Processes 2024 12 6 1195 10.3390/pr12061195
Liu, Y., Biswas, B., Hassan, M. & Naidu, R. Green adsorbents for environmental remediation: Synthesis methods, ecotoxicity, and reusability prospects. Processes 12(6), 1195 (2024).10.3390/pr12061195
42. Evtyugin DD Magina S Evtuguin DV Recent advances in the production and application of ellagic acid and its derivatives A review Molecule. 2020 25 12 2745 10.3390/molecules25122745
Evtyugin, D. D., Magina, S. & Evtuguin, D. V. Recent advances in the production and application of ellagic acid and its derivatives A review. Molecule. 25(12), 2745 (2020).10.3390/molecules25122745
43. Kumar M Tomar M Potkule J Verma R Punia S Mahapatra A Kennedy JF Advances in the plant protein extraction: Mechanism and recommendations Food Hydrocolloids 2021 115 106595 10.1016/j.foodhyd.2021.106595
Kumar, M. et al. Advances in the plant protein extraction: Mechanism and recommendations. Food Hydrocolloids 115, 106595 (2021).10.1016/j.foodhyd.2021.106595
44. Baertschi SW Pack BW Hyzer CSH Nussbaum MA Assessing mass balance in pharmaceutical drug products: New insights into an old topic TrAC Trends Anal. Chem. 2013 49 126 136 10.1016/j.trac.2013.06.006
Baertschi, S. W., Pack, B. W., Hyzer, C. S. H. & Nussbaum, M. A. Assessing mass balance in pharmaceutical drug products: New insights into an old topic. TrAC Trends Anal. Chem. 49, 126–136 (2013).10.1016/j.trac.2013.06.006
45. Zhao R Zhang Z Zhang R Li M Lei Z Utsumi M Sugiura N Methane production from rice straw pretreated by a mixture of acetic–propionic acid Bioresour. Technol. 2010 101 3 990 994 10.1016/j.biortech.2009.09.020 19804968
Zhao, R. et al. Methane production from rice straw pretreated by a mixture of acetic–propionic acid. Bioresour. Technol. 101(3), 990–994 (2010).19804968 10.1016/j.biortech.2009.09.020
46. Abugu HO Eze SI Ezugwu AL Ali IJ Ihedioha JN Chemical pretreatment of Lagenaria breviflora seeds used as biosorbents for the removal of aqueous-bound Ni2+ Water Pract. Technol. 2023 18 11 2514 2535 10.2166/wpt.2023.192
Abugu, H. O., Eze, S. I., Ezugwu, A. L., Ali, I. J. & Ihedioha, J. N. Chemical pretreatment of Lagenaria breviflora seeds used as biosorbents for the removal of aqueous-bound Ni2+. Water Pract. Technol. 18(11), 2514–2535 (2023).10.2166/wpt.2023.192
47. Gerçel Ö Özcan A Özcan AS Gercel HF Preparation of activated carbon from a renewable bio-plant of Euphorbia rigida by H2SO4 activation and its adsorption behavior in aqueous solutions Appl. Surf. Sci. 2007 253 11 4843 4852 10.1016/j.apsusc.2006.10.053
Gerçel, Ö., Özcan, A., Özcan, A. S. & Gercel, H. F. Preparation of activated carbon from a renewable bio-plant of Euphorbia rigida by H2SO4 activation and its adsorption behavior in aqueous solutions. Appl. Surf. Sci. 253(11), 4843–4852 (2007).10.1016/j.apsusc.2006.10.053
48. Qin X Cheng S Xing B Xiong C Yi G Shi C Zhang C Preparation of high-efficient MgCl2 modified biochar toward Cd (II) and tetracycline removal from wastewater Sep. Purif. Technol. 2023 325 124625 10.1016/j.seppur.2023.124625
Qin, X. et al. Preparation of high-efficient MgCl2 modified biochar toward Cd (II) and tetracycline removal from wastewater. Sep. Purif. Technol. 325, 124625 (2023).10.1016/j.seppur.2023.124625
49. Dos Reis GS Guy M Mathieu M Jebrane M Lima EC Thyrel M Larsson S HA comparative study of chemical treatment by MgCl2, ZnSO4, ZnCl2, and KOH on physicochemical properties and acetaminophen adsorption performance of biobased porous materials from tree bark residues Colloids Surf. A Physicochem. Eng. Aspects 2022 642 128626 10.1016/j.colsurfa.2022.128626
Dos Reis, G. S. et al. HA comparative study of chemical treatment by MgCl2, ZnSO4, ZnCl2, and KOH on physicochemical properties and acetaminophen adsorption performance of biobased porous materials from tree bark residues. Colloids Surf. A Physicochem. Eng. Aspects 642, 128626 (2022).10.1016/j.colsurfa.2022.128626
50. Michalak I Chojnacka K Witek-Krowiak A State of the art for the biosorption process a review Appl. Biochem. Biotechnol. 2013 170 1389 1416 10.1007/s12010-013-0269-0 23666641
Michalak, I., Chojnacka, K. & Witek-Krowiak, A. State of the art for the biosorption process a review. Appl. Biochem. Biotechnol. 170, 1389–1416 (2013).23666641 10.1007/s12010-013-0269-0
51. Torres E Biosorption: A review of the latest advances Processes 2020 8 12 1584 10.3390/pr8121584
Torres, E. Biosorption: A review of the latest advances. Processes 8(12), 1584 (2020).10.3390/pr8121584
52. Bold S Kraft S Grathwohl P Liedl R Sorption/desorption kinetics of contaminants on mobile particles: Modeling and experimental evidence Water Resour. Res. 2003 39 12 1 10.1029/2002WR001798
Bold, S., Kraft, S., Grathwohl, P. & Liedl, R. Sorption/desorption kinetics of contaminants on mobile particles: Modeling and experimental evidence. Water Resour. Res. 39(12), 1 (2003).10.1029/2002WR001798
53. Sun Y Zhou Z Zhong C Lei Z Langrish TA Comparing mass transfer and reaction rate kinetics in starch hydrolysis during food digestion Appl. Res. 2024 1 e00023
Sun, Y., Zhou, Z., Zhong, C., Lei, Z. & Langrish, T. A. Comparing mass transfer and reaction rate kinetics in starch hydrolysis during food digestion. Appl. Res. 1, e00023 (2024).
54. Tai YC Joshi P McGuire J Neff JA Nisin adsorption to hydrophobic surfaces coated with the PEO–PPO–PEO triblock surfactant Pluronic® F108 J. Colloid Interface Sci. 2008 322 1 112 118 10.1016/j.jcis.2008.02.053 18359037
Tai, Y. C., Joshi, P., McGuire, J. & Neff, J. A. Nisin adsorption to hydrophobic surfaces coated with the PEO–PPO–PEO triblock surfactant Pluronic® F108. J. Colloid Interface Sci. 322(1), 112–118 (2008).18359037 10.1016/j.jcis.2008.02.053
55. Gruskiene R Kavleiskaja T Staneviciene R Kikionis S Ioannou E Serviene E Sereikaite J Nisin-loaded ulvan particles: Preparation and characterization Foods 2021 10 5 1007 10.3390/foods10051007 34064524
Gruskiene, R. et al. Nisin-loaded ulvan particles: Preparation and characterization. Foods 10(5), 1007 (2021).34064524 10.3390/foods10051007
56. Duan G Ji C Zhang JZ Developing an effective polarizable bond method for small molecules with application to optimized molecular docking RSC Adv. 2020 10 26 15530 15540 10.1039/D0RA01483D 35495446
Duan, G., Ji, C. & Zhang, J. Z. Developing an effective polarizable bond method for small molecules with application to optimized molecular docking. RSC Adv. 10(26), 15530–15540 (2020).35495446 10.1039/D0RA01483D
57. Bolan S Hou D Wang L Hale L Egamberdieva D Tammeorg P Bolan N The potential of biochar as a microbial carrier for agricultural and environmental applications Sci. Total Environ. 2023 886 163968 10.1016/j.scitotenv.2023.163968 37164068
Bolan, S. et al. The potential of biochar as a microbial carrier for agricultural and environmental applications. Sci. Total Environ. 886, 163968 (2023).37164068 10.1016/j.scitotenv.2023.163968
58. Amrutha A Jeppu G Girish CR Prabhu B Mayer K Multi-component adsorption isotherms: Review and modeling studies Environ. Process. 2023 10 2 38 10.1007/s40710-023-00631-0
Amrutha, A., Jeppu, G., Girish, C. R., Prabhu, B. & Mayer, K. Multi-component adsorption isotherms: Review and modeling studies. Environ. Process. 10(2), 38 (2023).10.1007/s40710-023-00631-0
59. Ibarguren C Naranjo PM Stötzel C Audisio MC Sham EL Torres EMF Müller FA Adsorption of nisin on raw montmorillonite Appl. Clay Sci. 2014 90 88 95 10.1016/j.clay.2013.12.031
Ibarguren, C. et al. Adsorption of nisin on raw montmorillonite. Appl. Clay Sci. 90, 88–95 (2014).10.1016/j.clay.2013.12.031
