NRMJ_9_3_214-237

Introduction

UF-cheese permeate is recognized as a significant byproduct of the cheese manufacture sector, derived through an ultrafiltration (UF) process. This permeate primarily consists of lactose, along with vitamins that are soluble in water and various milk minerals (Gantumur et al., 2025). It typically contains at least 76 % lactose, 14 % ash, and generally 2-7 % proteins. UF-cheese permeate serves as a valuable resource of essential vitamins and minerals that are beneficial to the human health. Nevertheless, its disposal poses challenges for the dairy industry, contributing to environmental pollution. As a result, significant investments have been made to explore the utilization of permeate in the development of advantageous products (Premović et al., 2024). Whey permeate can be considered as a carrier of prebiotics and various bioactive compounds, including peptides, poly- and oligosaccharides, and organic acid that may play a functional role in skin care (Augustyniak et al., 2023).

The dairy sector is commonly regarded as a carbon-intensive industry with a significant global environmental impact, contributing to considerable greenhouse gas (GHG) emissions and aggravating global warming. Previous studies concluded that without comprehensive actions to attain near “net-zero” emissions, global climate changes will be intensified, leading to several climatic disasters and serious problems to food security and even human existence (Lam et al., 2021; Cheng et al., 2023).

A carbon or greenhouse gas emissions frequently has a close correlation with energy use. Thus, given that dairy is a significant energy user, carbon emissions at each stage of dairy supply chain may be estimated based on energy consumption levels (Malliaroudaki et al., 2022). Since climate change is the most pressing global concern currently, significant efforts have been devoted to mitigating carbon emissions in the dairy industry, which can be divided into two facets: (i) at the component level, novel techniques and strategies are being used that can reduce emissions at individual stages of the dairy supply chain, and (ii) at the system level, focusing on holistic improvements throughout the entire dairy supply chain (Chen et al., 2021).

Lactose intolerance is a common medical condition that impacts individuals across various ethnicities globally. β-galactosidase is important for numerous applications; particularly within the food industry linked to healthcare, as it facilitates the creation of lactose-free dairy products for individuals with lactose intolerance due to insufficient levels of this enzyme (Chengolova et al., 2024). Deficiency in lactase may lead to a range of medical symptoms, such as gastrointestinal disturbances, bloating, abdominal discomfort, and diarrhea (Khalid et al., 2024; Borralho and Marcos, 2025).

β-galactosidase, commonly referred to as lactase (β-D-galactoside galactohydrolase; EC 3.2.1.23) is an intracellular enzyme that facilitates the hydrolysis of lactose, a disaccharide present in milk and dairy products. This enzymatic process breaks down lactose into its monosaccharide components, galactose and glucose, which are readily absorbable by the majority of organisms, including human (Chengolova et al., 2024).

β-galactosidase is used in the food, pharmaceutical, and dairy industries for producing low-lactose-containing food products, sweeteners, and galacto-oligosaccharides (GOS), in addition to being utilized for dairy waste treatment, and biosensor and ethanol production that is a challenging process in this century (Santra and Banerjee, 2021; Movahedpour et al., 2022). Additionally, consumption of GOS has been linked to various health benefits for humans, including potential anti-carcinogenic properties within the colon, enhanced absorption of minerals, improved lipid metabolism, and anti-inflammatory and immune-boosting effects (Nadeem et al., 2024).

Immobilization of β-galactosidase by nanobiocatalysts has evolved as a novel field for enhancing enzyme stability in biotechnology applications. The immobilized enzyme demonstrated a high degree of hydrolysis, which may be successfully used to hydrolyze lactose in milk and whey. Utilizing β-galactosidase offers a cost-effective alternative for biotechnology and waste management (Alshanberi et al., 2021). Immobilization has proven to be an excellent alternative to the previously described techniques for enzyme stabilization, owing to its lower cost, simplicity, and increased chances of reusing and recovering the enzyme. It is the process by which enzymes are attached or incorporated into a support material. An insoluble, reusable, and more resistant version of the enzyme is generated, capable of participating in chemical reactions under a variety of processing conditions, ideally without considerable loss of stability or activity (Robescu and Bavaro, 2025). Immobilized enzymes (IE) are used in several fields, such as the food and pharmaceutical industries, medicine, for the production of biofuels, detergents, and cleaning products, and in bioremediation and wastewater treatment. There are several previous studies on this topic (Bié et al., 2022; Maghraby et al., 2023).

Microbial sources are considered the most efficient ones for enzyme production due to several reasons, including ethical issues concerning plants and animals, microbial fast growth, and high yield of the enzyme. Out of the producer microorganisms, LAB were found to be the best choice for enzyme production; especially for food applications (Kumar et al., 2024). LAB; especially species in the Lactobacillus genus, have become a prominent focus of research among the different microbial producers of this enzyme because they are safe for both humans and animals; thus, their relevance is continually expanding. They are generally recognized as safe (GRAS), (Kittibunchakul et al., 2020). LAB are frequently employed as probiotics, which offer health benefits to the host when taken in appropriate doses, where they display several health benefits. LAB play a significant role in biopreservation as they produce various antimicrobial metabolites during their development and fermentation processes. Among the most common antimicrobials are bacteriocins, which are peptides that can kill or inhibit undesirable bacterial strains, regardless of their relatedness, without harming the LAB themselves (Ahansaz et al., 2023). The utilization of LAB strains, namely Enterococcus spp., Lactococcus spp., and Lactobacillus spp., possessing antibacterial capabilities, has been employed in biocontrol approaches aimed at diminishing mycotoxins and augmenting bioavailability. Formation of organic acids, carbon dioxide, ethanol, hydrogen peroxide, antifungal chemicals, and antibiotics protects foods (Saleem et al., 2024). Additionally, the utilization of probiotic strains as biofactories for the production of enzymes has gained substantial attention recently, as their application in the food and pharmaceutical industries typically requires minimal purification procedures (Carevic et al., 2018). Lactiplantibacillus plantarum represents a significant component in the LAB species. Classified as a facultative anaerobic heterofermentative bacterium, L. plantarum falls under the Group B Lactobacillus classification that is predominantly originated from vegetable-derived food items (Liu et al., 2024). This bacterium plays a dual role, as a starting culture for different fermented foods and a probiotic agent (Ma et al., 2021).

Numerous variables affect the synthesis of lactase, including temperature, pH levels, duration of incubation, and composition of the production medium. The refinement of the fermentation medium is vital for effective generation of β-galactosidase, as highlighted by Afolabi et al. (2022). Availability of carbon and nitrogen inputs is crucial for promoting enzyme synthesis by the LAB (Ayad et al., 2020). Various studies have examined these variables that impact β-galactosidase fabrication, as discussed by Karlapudi et al. (2018).

The objectives of this investigation were to isolate native LAB capable of generating β-galactosidase, identify the specific bacterial strains responsible for its production, and optimize the conditions for enzyme synthesis; utilizing permeate as a substrate via a statistical optimization methodology.

Materials and Methods

Isolation of β-galactosidase -producing bacteria

Eighteen dairy products samples were collected from local markets in Giza governorate, Egypt, including 6 yoghurt, 3 raw milk, 5 Rayeb milk, and 4 types of cheese (i.e., 2 Kareish, 1 Romy, and 1 Cheddar). For bacterial isolation, two selective media were used, mainly MRS (De Man Rogosa-Sharpe) and M17 agar media (Biolife Italiana S.R.L. Milan, Italy). The MRS agar medium was employed for the isolation of lactobacilli bacteria, as elaborated by Chandel et al. (2020), while isolation of lactococci and streptococci bacteria was conducted utilizing the M17 agar medium in reference to Waiel et al. (2020). For bacterial isolation and colony purification, a serial dilution agar plate technique was employed in reference to Ismail et al. (2018). 1 ml from dilutions 10-5, 10-6, and 10-7 was pipetted into sterile petri plates and then MRS and M17 agar medium were aseptically poured, followed by horizontal rotation for homogenous mixing. The plates were incubated at 37 ºC for 48 h under anaerobic conditions using the anaerobic candle jar. After incubation, the developing colonies were purified by successive sub-culturing onto MRS agar and then stored in 20 % glycerol at -80 oC (Naziri et al., 2023).

Screening of bacterial isolates for β-galactosidase production

Qualitative screening: X-gal (5-Bromo-4-chloro-3-indoxyl-β-D-galactopyranoside) (Sigma-Aldrich Chemical Co. located in St. Louis, MO, USA) served as a colorimetric substrate and had been utilized for identifying bacteria that produce β-galactosidase (Vinderola and Reinheimer, 2003). The purified isolates were cultured on MRS and M17 agar petri plates in triplicate with the incorporation of 50 μl of X-gal (20 mg/ml in DMSO), followed by incubation at 37°C for 24 to 72 h under anaerobic conditions. After incubation, the bacterial strains exhibiting β-galactosidase activity produced blue colored colonies (Gheytanchi et al., 2010; Sharma and Singh, 2014). The assay was conducted in triplicate.

Quantitative screening: The bacterial colonies displaying a blue color on X-gal agar medium were quantitatively evaluated for β-galactosidase synthesis to identify the potent isolates achieving the highest enzyme yield. Hundred ml Erlenmeyer flasks, individually containing 50 ml of MRS and M17 broth were enriched with 1% lactose and 0.05% L-cysteine, followed by sterilization. Under aseptic conditions, the flasks were inoculated with 2 % (v/v) of the bacterial inoculum (5 × 107 cfu/ ml) followed by incubation at 37 oC for 24h under anaerobic conditions using an anaerobic jar (Shrushti et al., 2017). Post-incubation, the bacterial cells were harvested via centrifugation at 2.862 g for 20 min at 4 °C. The activity of β-galactosidase enzyme of the isolates was measured according to the procedure described by Hsu et al. (2005), with little modifications. The reaction mixture contained 0.5 ml of supernatant containing the extracted enzyme (intracellular enzyme), 0.5 ml 15 mM O-nitrophenyl β-D-galactopyranoside (ONPG) (sigma-Aldrich Chemical Com. MO, USA) in 0.03 M sodium phosphate buffer (pH 6.8). After incubation at 37 °C for 30 min., 2.0 ml of 0.1 M sodium carbonate was added to the mixture to stop the reaction. Absorbance was measured at 420 nm using a spectrophotometer (Shimadzu UV-vis spectrophotometer, Model UV-1201, Japan). One unit of β-galactosidase was defined as the amount of enzyme that produced 1 μM of O-nitrophenol/ min. under the assay condition. All treatments were conducted in triplicate.

Identification of the selected bacterial isolate

The selected bacterial isolate was identified morphologically and molecularly.

Morphological characterization: Morphological characteristics of the pure bacterial isolate were studied through Gram stain followed by microscopical investigation as described by Goyal et al. (2012).

Molecular identification: Identification of the selected isolate was achieved via sequencing of the 16S rRNA using polymerase chain reaction (PCR) (Lagacé et al., 2004). Gene sequencing services were provided by Macrogen laboratories, South Korea. The extraction of the DNA from the isolates was performed using a DNA purification kit, specifically the QIAamp DNA Mini Kit (Catalogue no. 51304). The oligonucleotide primer sequences used in the PCR were identified as follows: Forward primer (5’-AGAGTTTGATCMTGGCTCAG-3’) and Reverse primer (5’-TACGGYTACCTTGTTACGACTT-3’) (Metabion, Germany).

Testing UF-cheese permeate as a growth medium

The UF-cheese permeate was used as a fermentation medium to test the ability of the selected isolates to utilize it as a growth medium. The fresh permeate (pH 6.6-6.8) was obtained from the dairy industry unit at the Animal Production Research Institute, Ministry of Agriculture, Giza, Egypt. According to Johansen et al. (2002), UF-Cheese permeate comprises lactose concentration that varies from 4.4 to 5.2 %, proteins that constitute 0.6 to 0.8 %, and minerals found in concentrations of 0.43-0.95 %. Where, the pore size of the UV-cheese permeate membrane exceeded 30 bars under processing conditions, specifically at a temperature of 40-50 °C and a pressure range of 1-10 atm. To de-proteinize the permeate, the pH was adjusted with lactic acid to 4.5. Thereafter, the sample was heated at 90°C for 30 min. The resulting precipitated proteins were subsequently separated through the use of Whatman No. 1 filter paper, and the clarified permeate was preserved at -20 °C to prevent microbial and enzymatic degradation (El-Sawah et al., 2006). After sterilization at 121°C for 20 min., the pure supernatant was utilized as a substrate medium. The process of submerged fermentation (SmF) was executed using 100 ml Erlenmeyer flasks under anaerobic static culture conditions. The permeate was evaluated as a growth medium via the One Factor At a Time (OFAT) method to enhance the influence of carbon and nitrogen sources on β-galactosidase production in the fermentation medium. Three separate carbon sources were individually tested, mainly glucose, sucrose and starch alongside with the naturally occurring permeate lactose. The lactose concentration was assessed through various dilutions of the permeate, in accordance with the previous procedures outlined by El-Sawah et al. (2006); Murad et al. (2011). Additionally, the impact of 3 nitrogen sources, including yeast extract, beef extract, and potassium nitrate was examined individually, as reported by Sumit and Priyanka (2014); Carević et al. (2015). The indigenous lactose concentration within the permeate was assessed colorimetrically at wavelength 490 nm using the phenol sulfuric acid method described by Mohamed et al. (2012). Afterward, the production medium flasks were adjusted to pH 6.8, inoculated with 2 % (v/v) from the selected bacterial isolates that were cultured individually for 24 h in MRS and M17 broth, and maintained at the optimal temperature of 37 °C under anaerobic conditions for 24 h. After incubation, the production medium underwent centrifugation at 2.862 g for 20 min. at 4 °C to collect the bacterial cells. After the enzyme was extracted, the supernatant was subjected to enzyme assay using O-nitrophenyl β-D-galactopyranoside (ONPG) method.

Measurement of the lactose concentration

The estimation of lactose concentration was conducted following the methodology outlined by Mohamed et al. (2012). Initially, a volume of 2.0 ml of the permeate solution was transferred into a colorimeter tube for analysis, 2.0 ml of 80 % w/v phenol reagent were added (composed of 20 ml water and 80 g phenol dissolved at 50 °C). This reagent remained stable for minimum of 4 min. at room temperature. Subsequently, 5.0 ml of concentrated sulfuric acid were introduced gradually, enabling the acid to descend along the internal wall of the tube. The mixture was then swirled to ensure throughout mixing and allowed to cool for a period of 10 min. at ambient temperature. Absorbance readings were taken at 490 nm utilizing a UV/Vis spectrophotometer, with a blank sample created by substituting the diluted extract with 2 ml of distilled water. L-lactose served as the standard, while the concentration of lactose was evaluated by employing the regression equation derived from the standard curve (92.804x + 0.6703, R² = 0.995). The result was expressed in g/ 100 g of the sample. All treatments were performed in triplicate.

The β-galactosidase enzyme activity assay

Extraction of the β-galactosidase using sodium dodecyl sulfate (SDS) chloroform processing: Following 24 h of incubation, the bacterial cell cultures were collected through centrifugation at 2.862 g for 20 min. at 4 °C. The resulting supernatant was deemed to contain extracellular enzymes. Subsequently, the cell pellet was homogenized and subjected to two washes with 0.03 M sodium phosphate buffer, maintained at pH 6.8. The washed pellets were reconstituted in 5 ml of the identical phosphate buffer. The process of extracting the intracellular enzymes was accomplished through the application of Sodium Dodecyl Sulfate (SDS) and Chloroform treatments, in reference to Prasad et al. (2013).

Disruption of the bacterial cell membrane was achieved by vortexing a 5 ml suspension of cells with 250 μl of chloroform (Sigma-Aldrich Chemical Co., St. Louis, MO, USA) and 100 μl of 0.1 % SDS solution (Park Scientific Limited, 24 Low Farm Place, Moulton Park, Northampton, Northamptonshire, NN3 6HY, UK) for 30 min. at ambient temperature. Afterward, centrifugation of the mixture was conducted with a Harrier 18/180 refrigerated centrifuge (model MSE, U.K.) at 2.862 g for 20 min. at 4 °C. The supernatant produced was subsequently kept at -20 °C until the enzyme activity was determined, as indicated by Prasad et al. (2013).

Estimation of the β-galactosidase enzyme activity

β-galactosidase activity was assessed following the methodology outlined by Hsu et al. (2005), with slight modifications. The reaction mixture consisted of 0.5 ml of the supernatant that contained the extracted intracellular enzyme, 0.5 ml 15 mM O-nitrophenyl β-D-galactopyranoside (ONPG) solution (Sigma-Aldrich, Chemical Co., St. Louis, MO, USA), and dissolved in 0.03 M sodium phosphate buffer at pH 6.8. Following 30 min. incubation at 37 °C, 2.0 mL of 0.1 M sodium carbonate were added to halt the reaction. The value of absorbance was subsequently recorded at 420 nm using a Shimadzu UV-vis spectrophotometer (Model UV-1201, Japan). One unit of β-galactosidase is defined as the amount of enzyme that catalyzes the formation of 1 μM of O-nitrophenol / min. within the specified test aspects (Gomes et al., 2021). All tests were performed in triplicate.

Assessment of the specific activity of β-galactosidase

The specific activity of β-galactosidase is defined in terms of U/ mg protein/ ml, utilizing the following formula reported by Geiger et al. (2016):

Specific activity (U/ mg) = enzyme activity (U/ ml)/ protein content (mg/ ml)

Protein assay

The overall protein concentrations of the bacterial isolates were evaluated utilizing the methodology reported by Yglesias-Rivera et al. (2020), employing Bovine Serum Albumin (BSA) at a concentration of 0.2 mg/ ml as the standard protein reference. Reagent A: 2 % sodium carbonate (Na₂CO₃) in 0.1 N sodium hydroxide (NaOH) containing 2 g anhydrous Na₂CO₃ dissolved in 100 ml of 0.1M NaOH. Reagent B: 1 % sodium potassium tartrate in distilled water, containing 1 g of sodium potassium tartrate dissolved in 100 ml distilled water. Reagent C: 0.5 % CuSO₄.5H₂O in distilled water containing 0.5 g of copper sulfate hepta hydrate (CuSO₄.5H2O) dissolved in 100 ml distilled water. Reagent D (Lowry solution) containing 98 ml of A +1 ml of B + 1 ml of C, while Reagent E contained 1 part Folin: 1 part distilled water. Reagent D (4.5 ml) were added to 1 ml of each properly diluted crude enzyme filtrate, mixed by vortexing and incubated at room temperature for 10 min, After incubation, 0.5 ml of Reagent E was added to the mixture, mixed well, and incubated at room temperature for 30 min. The absorbance of the resulting colored fluid was measured using a spectrophotometer (Shimadzu UV-vis spectrophotometer, Model UV-1201, Japan) at 660 nm against a control without the sample. All testes were carried out in triplicate.

Optimization of the culture conditions for β-galactosidase biosynthesis

Five process parameters (factors), mainly temperature, pH, inoculum volume, nitrogen resource, and growth time were systematically tailored to enhance the yield of β-galactosidase, using UF-cheese permeate as a growth environment via Response Surface Methodology (RSM) (Deng et al., 2020). The optimization procedures were carried out utilizing the Minitab (18-1) software package.

Application of response surface methodology for bacterial culture optimization using central composite design

Analysis of the data was conducted utilizing Minitab Statistical Software (version 18-1) developed by Minitab®, State College, PA, USA. To ascertain the optimal levels of the five tested parameters impacting enzyme generation, a response surface methodology (RSM) was employed, based on findings from our one-factor at a time (OFAT) tests and previous studies reported by Wang et al. (2004), Hsu et al. (2007), Murad et al. (2011), Shrushti et al. (2017).The experimental design consisted of a single replicate. Each parameter was assigned five level codes: -α, -1, 0, +1, and +α. From the combinations of these five variables at the corresponding levels, a total of 54 experimental designs were created. The study utilized a central composite design (CCD), which is a preferable method compared to other methods such as Box–Behnken design etc., because CCD methodology provides better information within or beyond the limits of the spinning process. The CCD contains a combination of extreme factors, whereas the box Behnken does not examine the boundary area. Therefore, the CCD is considered more accurate and does not require a three-level factorial experiment in the operation of the quadratic model (Safira and Purbasari, 2023).

The CCD incorporated five unrelated factors, each with five distinct tiers along with 32 star points (α= 2.366) with eight repetitions at the center points. This design was implemented to formulate a prototype, which would identify the ideal levels for the parameters influencing the β-galactosidase production. The experiments were conducted in 100 ml Erlenmeyer flasks, where each flask contained 50 ml of the generating medium. The variables tested, along with their coded and non-coded values are presented in Table 1.

Table 1: The various values of the factors utilized in the experimental design.

The variables	The source code	The tested levels					Unit
The variables	The source code	-2	2	0	+1	+2	Unit
Nitrogen concentration	N	0.634	2	3	4	5.366	%
pH	pH	3.634	5	6	7	8.366	pH
Inoculum size	IS	1.634	3	4	5	6.366	%
Temperature	T	25.219	30	33.5	37	41.781	o C
Incubation period	IP	7.608	24	36	48	64.392	h

Statistical analysis

The experiments were executed with triplicate to improve the credibility of the findings. The outcomes were articulated as mean ± standard deviation (SD). In the context of CCD tests, multiple runs were replicated, and the mean results served as the input for further analysis. Regression analysis, along with the significance testing of the regression coefficient and the identification of significant differences among the assessed variables was conducted by studying the analysis of variance (ANOVA) through Minitab (18-1) Statistical Software.

Results and Discussion

Isolation of β-galactosidase -producing bacteria

Seventeen different bacterial isolates were picked up from the surfaces of M17 and MRS (De Man-Rogosa-Sharpe) agar plates. After purification, the obtained isolates were evaluated qualitatively for their capability to generate the target enzyme.

Screening of isolates for β-galactosidase production

Qualitative screening: Upon qualitative screening of the seventeen bacterial isolates obtained using the X-gal technique, eleven isolates demonstrated positive results for β-galactosidase production, exhibiting blue or white-blue colonies when plated on MRS and M17 agar. These isolates were subsequently selected for further studies.

Quantitative screening: Following the qualitative screening, eleven isolates that showed positive for β-galactosidase production using the X-gal method were quantitatively evaluated for their levels of β-galactosidase production by employing ONPG substrate estimation. The isolates that produced β-galactosidase enzyme gave a yellow color. Upon colorimetric estimation, the best enzyme producers were isolates 3ay, 9bR, 5aY and 8aR1; while upon estimating the enzyme activity, the 3aY isolate displayed the superiority compared to the other isolates, recording 14.154 U/ ml (Figure 2).

Identification of the bacterial isolates

Morphological characterization: All the selected LAB isolates showed the colony morphology of LAB colonies, which was cream-white, round, and smooth surface colonies on MRS agar in agreement with Kouadio et al. (2024). Meanwhile, the Lactococcus colonies on M17 agar were yellowish in color, small in size, and circular, in accordance with Taye et al. (2021). Upon Gram staining, the isolates obtained from MRS plates were Gram (+), characterized by being rod-shaped cells arranged either individually or in short chains.

Molecular characterization

The identification of the selected bacterial isolates at the species level was confirmed and validated through the application of a molecular technique. Four bacterial isolates that revealed higher β-galactosidase activity were identified via partial sequencing of their 16S rRNA. According to the alignment results, all the sequenced samples were assigned to 2 distinct species within the genus Lactiplantibacillus, as illustrated in Table 2. The potent enzyme producer was identified as Lactiplantibacillus plantarum strain S1 and assigned an accession no. of PQ722056. Phylogenetic studies focusing on 16S rRNA amplification were primarily performed, and the acquired partial 16S rRNA sequence was deposited in a Genbank database for verifying the homology alignment. The phylogenetic tree was constructed using MEGA11: Molecular Evolutionary Genetics Analysis version 11, and visualized and annotated using the interactive online tool iTOL v7 (Tamura et al., 2021; Letunic and Bork, 2024). The phylogenetic tree alignment of the Lactiplantibacillus plantarum strain S1 is presented in the Figure 1.

Table 2: Identification of the selected bacterial isolates for β-galactosidase production using 16S rRNA sequencing.

Isolate code	Identification	Accession number	Similarity
3aY	Lactiplantibacillus plantarum strain S1	PQ722056	98.26%
9bR	Lactiplantibacillus pentosus strain S2	PQ722057	98.08%
5aY	Lactiplantibacillus plantarum strain S3	PQ722058	89.29%
8aR1	Lactiplantibacillus plantarum strain S4	PQ722059	97.33%

Testing UF-cheese permeate as a growth medium

Under anaerobic static conditions, the submerged fermentation (SmF) process was executed in 100 ml Erlenmeyer flasks. These anaerobic static cultures facilitated greater outputs of biomass and enzymes. The enhanced biomass production is ascribed to the microorganism’s ability to effectively utilize different carbon sources; particularly glucose, as documented by Tesfaw (2023). Anaerobic environments usually trigger the activation of the pyruvate-formate lyase system, which via the actions of acetyl phosphate and acetyl kinase, promotes a higher ATP release per glucose molecule metabolized (Taggar et al., 2024). The occurrence of this feature has been observed in

various lactobacilli, such as L. johnsonii and L. gasseri, as reported by Maresca et al. (2018), along with L. plantarum as stated by Deng et al. (2020).

Additionally, the role of the carbon resource in enzyme production is dependent on the specific microbial species examined (Ray et al., 2023). The characteristic and concentration of the carbon substrate are recognized as two of the most crucial determinants for β-galactosidase fabrication in lactobacilli in accordance with Mukherjee et al. (2024).

The data obtained demonstrated that the most potent carbon resource for β- galactosidase activity stimulation was lactose. Afterward, glucose and sucrose contributed to lower levels of enzyme activity, while starch inhibited this activity, as shown in Figure 3. Our findings coincide with the previous study conducted by Gomes et al. (2021), who identified lactose as the prime carbon substrate for achieving optimal β-galactosidase production in Bifidobacteria.

Measurement of the lactose concentration

The results depicted in Figure 3 demonstrate that the production of β-galactosidase by the selected bacterial strain rose in correlation with the level of cheese permeate, reaching its peak at 12 %. The peak enzyme activity was achieved at a lactose content of 4.0 % existing in the 12% permeate concentration, and then decreased when the lactose content in 15 % permeate concentration increased more than 4 %. Similarly, Candida pseudotropicalis exhibited maximum enzyme production at cheese whey concentrations between 10 % and 12 %, corresponding to lactose levels of 7.3 % to 8.7 % (Carvalho et al., 2021) Furthermore, in another study, the maximal lactase yield from S. thermophilus was obtained at a permeate concentration of 10 % according to Chandel and Sharma (2020). Recently, a 4% lactose concentration effectively elicited the optimal levels of β-galactosidase expression within the parameters of the study reported by Hooda et al. (2025). However, further increments in lactose concentration resulted in diminished β-galactosidase activity. This may be ascribed to the fact that elevated levels of glucose generated inhibited the generation of lactase enzyme in the microorganism being tested (catabolite repression). This finding is in harmony with the study performed by Sahoo et al. (2023). Furthermore, Da Silva et al. (2020) reported that the best concentration of lactose for β-galactosidase fabrication by Enterococcus faecium was 5.35 %. In contrast, it was reported that 7.0 % lactose is the ideal concentration to produce lactase from Lactobacillus spp. (Chandel and Sharma, 2020).

Several previous studies reported by Li et al. (2023); Wahab et al. (2024) indicated that the inclusion of lactose as a carbon source in the growth medium performs a significant part in the synthesis of β-galactosidase by bacteria in consistence with our experimental findings. Moreover, the results documented by Chandel and Sharma (2020), Gomes et al. (2021) revealed how lactose sugar facilitates enzyme production in Bifidobacteria spp., Lactobacillus reuteri, and Streptococcus thermophilus. Furthermore, it has been reported that lactose is a substrate that significantly enhances the yield of lactase enzyme in L. acidophilus ATCC 4356, L. plantarum B110, and various Lactobacillus species (Chandel and Sharma, 2020, Ayivi and Ibrahim, 2022).

The existence of lactose sugar is recognized as the best effective supply of carbon for inducing high levels of β-galactosidase production. This phenomenon is attributed to the fact that lactose substrate particularly in the allolactose isomer configuration, promotes the expression of the lacZ gene by attaching the Lac repressor protein, which in turn obstructs the activation of an operative zone of the lac operon as revealed by Deng et al. (2020). According to Lappa et al. (2019), lactose derived from cheese whey serves as the best sugar precursor for the generation of β-galactosidase by L. acidophilus.

The majority of microbial species assimilate nitrogen at its organic and inorganic states to facilitate the creation of amino acids, nucleic acids, proteins, and cell wall constituents. The impact of nitrogen sources on β-galactosidase output has been previously assessed utilizing One Variable at a Time (OFAT) methodology (Vithalani et al., 2024; Malos et al., 2025). The current results indicated that potassium nitrate (KNO₃) emerged as the optimal form of nitrogen for achieving the highest levels of β-galactosidase production by the Lactiplantibacillus plantarum strain S1 at a concentration of 2 %, as illustrated in Figure 4. These findings align with those of (Singh and Sambyal, 2023) who similarly identified (NH₄)₂NO₃ and KNO₃ as the most effective nitrogen sources for various L. plantarum strains. It has been revealed that sodium nitrate is the most suitable nitrogen source for Aspergillus oryzae’s β-galactosidase synthesis (Akcan, 2018). However, excessive nitrogen levels may contribute to microbial cell mortality (Sun et al., 2024).

The β-galactosidase enzyme assay

Extraction of β-galactosidase utilizing sodium dodecyl sulfate (SDS)-chloroform processing: During this investigation, β-galactosidase enzyme was extracted utilizing SDS-chloroform treatment. SDS is classified as an inert cleaner that denaturates and alters the proteins’ original structure by dissolving the non-covalent links within them. Due to its low reactivity, convenient volatility, and miscibility with various biological solvents, the chloroform solution is a liquid that is widely utilized. As a result, SDS and chloroform may operate in concert to enhance cell wall permeabilization and facilitate the development of enzymes (Mahadevaiah et al., 2020).

Estimation of the enzyme activity: The eleven isolates that showed blue-colored colonies on X-gal agar plates were examined for their β-galactosidase production. The β- galactosidase activity with the corresponding specific activity for the eleven bacterial isolates is depicted in Figure 5. Among the bacterial strains analyzed, strain (3aY) demonstrated the greatest level of lactase activity (14.154 U/ ml) and specific activity (114.15 U/ mg) compared to the other tested isolates, when cultivated on an optimized MRS media. This is in agreement with the results reported by Nawal et al. (2018) on the L. plantarum P4 strain producing β-galactosidase with a value of 14. 84 U/ mL.

Assessment of the protein and specific activity for β-galactosidase

The protein contents and specific activity of the β-galactosidase enzyme for the selected isolates were evaluated as shown in Figure 5. Based on the results obtained, we observed that when the enzyme activity of each bacterial isolate increased and protein content declined, the specific activity increased. There is a direct relationship between enzyme activity and specific activity, and an inverse relationship between them and protein content. Currently, the bacterial isolate (3ay) was the best enzyme producer compared to the other tested isolates, recording enzyme activity (14.154 U/ml), specific activity (114.15 U/mg), and protein content (0.124 mg/ml). The currently obtained results of the isolate (3ay) displayed that β-galactosidase enzyme’s activity and specific activity increased with decreasing protein concentration, in accordance with the previous study reported by Nawal et al. (2018) on the L. plantarum P4 strain recording β-galactosidase activity of 14.10 U/ ml. The increasing bacterial biomass correlated with the specific enzyme activity, which reached a maximum of 114.15 U/ mg after 24 h of growth. This time point corresponds with the early stationary phase of bacterial growth. The fact that β-galactosidase levels were highest in the initial stationary phase is consistent with the findings of a previous study involving lactobacilli (Deng et al., 2020).

Optimization of the culture conditions for β-galactosidase biosynthesis using response surface methodology

Based on the data obtained through the common One Factor at a Time (OFAT) approach, lactose was selected as a carbon supply, while potassium nitrate (KNO₃) used as a nitrogen source for the current experimental setup. A pivotal, widely employed mathematical design that facilitates the development of quadratic response surface models is the response surface methodology (RSM), as reported by Abdella and Ibrahim (2024) within the framework of RSM, the Central Composite Design (CCD) is a frequently utilized technique used to investigate how the experimental parameters affect the synthesis of β-galactosidase (Sharma et al., 2023; Bella et al., 2024).

Our study aimed to enhance the medium’s composition by evaluating the different levels of several factors previously identified as key contributors to β-galactosidase production. The implementation of RSM, enabled efficient improvement more than the conventional one-variable-at-a time approach (Devi et al., 2022; Bhatia et al., 2023). The CCD was utilized within the scope of the RSM to enhance enzyme production. Afterward, we aimed to optimize growth conditions for the manufacture of β-galactosidase using the Lactiplantibacillus plantarum strain S1. This investigation considered five independent variables, mainly nitrogen, pH, inoculum size, incubation time, and temperature, with the corresponding predicted and observed activity of β-galactosidase presented in Table 3. All observed values for β-galactosidase activity spanned from 0 to 5.523 U/ ml. Every parameter was investigated in two specific tiers (−1, +1) in addition to the central point (0), acting as the midway within the range of every component. Assessment of each variable was conducted at five levels, and the interactions affecting the creation of β-galactosidase were evaluated through a total of 54 experiments, as detailed in Table 3.

The currently used independent variables (i.e., pH, incubation temperature, inoculation volume, nitrogen level, and cultivation period), and the corresponding responses of the activity of β-galactosidase are detailed in Table 3. Observed values for β-galactosidase activity varied between 0.007 and 5.523 U/ ml. Notably, a reduction in lactase activity was recorded at pH 6, whereas a peak activity of 5.523 U/ ml was achieved at pH 7 (level 2, run 28). In consistence

Table 3: Central composite design (CCD) values for β-galactosidase activity obtained by Lactiplantibacillus plantarum strain S1.

Run order	N	PH	IS	T	IP	E.A	Fit values
1	2	5	3	30	24	0.112	0.06116
2	4	7	3	30	24	0.045	-0.14099
3	4	5	5	30	24	0.030	-0.26927
4	2	7	5	30	24	0.648	0.88516
5	4	5	3	37	24	0.171	0.53146
6	2	7	3	37	24	2.996	2.83038
7	2	5	5	37	24	1.752	2.06861
8	4	7	5	37	24	4.673	4.36696
9	4	5	3	30	48	1.185	1.69924
10	2	7	3	30	48	0.060	0.06666
11	2	5	5	30	48	0.097	0.12088
12	4	7	5	30	48	0.030	-0.45426
13	2	5	3	37	48	0.119	0.03461
14	4	7	3	37	48	0.067	-0.02954
15	4	5	5	37	48	0.052	-0.11732
16	2	7	5	37	48	0.827	1.09361
17	3	6	4	33.5	36	0.097	0.12616
18	3	6	4	33.5	36	0.097	0.12616
19	3	6	4	33.5	36	0.097	0.12616
20	3	6	4	33.5	36	0.097	0.12616
21	4	5	3	30	24	0.030	-0.10646
22	2	7	3	30	24	0.134	0.19846
23	2	5	5	30	24	0.000	-0.17557
24	4	7	5	30	24	0.231	0.61704
25	2	5	3	37	24	0.760	0.94191
26	4	7	3	37	24	1.998	2.24551
27	4	5	5	37	24	1.632	1.72948
28	2	7	5	37	24	5.523	4.87791
29	2	5	3	30	48	1.588	1.58068
30	4	7	3	30	48	0.067	0.01079
31	4	5	5	30	48	0.052	0.31076
32	2	7	5	30	48	0.030	-0.47232
33	4	5	3	37	48	0.082	-0.09226
34	2	7	3	37	48	0.142	0.26916
35	2	5	5	37	48	0.089	-0.06437
36	4	7	5	37	48	0.581	0.86624
37	3	6	4	33.5	36	0.075	0.12551
38	3	6	4	33.5	36	0.075	0.12551
39	3	6	4	33.5	36	0.075	0.12551
40	3	6	4	33.5	36	0.075	0.12551
41	0.634	6	4	33.5	36	0.157	0.35484
42	5.366	6	4	33.5	36	0.030	-0.1109
43	3	3.634	4	33.5	36	0.015	-0.23629
	Table continues on next column.............
Run order	N	PH	IS	T	IP	E.A	Fit values
44	3	8.366	4	33.5	36	0.783	1.09122
45	3	6	1.634	33.5	36	0.030	-0.23913
46	3	6	6.366	33.5	36	0.216	0.54206
47	3	6	4	25.219	36	0.015	0.14816
48	3	6	4	41.781	36	2.830	2.75378
49	3	6	4	33.5	7.608	2.460	2.45208
50	3	6	4	33.5	64.39	0.045	0.10986
51	3	6	4	33.5	36	0.007	-0.06417
52	3	6	4	33.5	36	0.007	-0.06417
53	3	6	4	33.5	36	0.007	-0.06417
54	3	6	4	33.5	36	0.007	-0.06417

Where N: Nitrogen concentration, IS: Inoculum size, IP: Incubation period, T: Temperature degree, EA: Enzyme activity

with Boukezzoula et al. (2019), the peak enzyme output for β-galactosidase reached 6.80 U/ ml for Bifidobacterium animalis ssp. lactis Bb12 and 7.77 U/ ml for L. delbrueckii ssp. bulgaricus ATCC 11842. Both strains were grown in cheese whey at a pH of 6.8 for 18 h at 37 ºC. The peak yield of β-galactosidase generated by S. thermophilus cultivated on a permeate-based environment reached 7.85 U/ ml. This was achieved under specific culture conditions of 10 % lactose concentration within the permeate medium, a pH range of 6.0-6.5, utilizing ammonium phosphate as the nitrogen supply, and incubation at 35 °C for 24 h (Chandel and Sharma, 2020). Furthermore, the productivity of lactase created by Bifidobacteria sp. increased when the cultivation temperature rose above 22 °C – 37 °C (Gomes et al., 2021). Elevated cultivation temperatures led to declined enzyme synthesis. The results of the study conducted by Boukezzoula et al. (2019) on the β-galactosidase production from Bifidobacterium animalis ssp. lactis Bb12 and Lactobacillus delbrueckii spp. bulgaricus ATCC 11842 that were grown in cheese whey are consistent with our results for β-galactosidase biosynthesis by the selected isolate of Lactiplantibacillus plantarum strain S1; yielding 5.523 U/ ml, under culture conditions of pH 7, temperature 37 °C, and incubation for 24 h, when cultivated in UV-cheese permeate medium. Where, lactose in cheese permeate served as a carbon source and KNO₃ used as a nitrogen source. This is also compatible with Chandel and Sharma (2020) investigation on β-galactosidase production by Streptococcus thermophilus in a permeate-based environment.

Several previous studies emphasized the significance of cultural conditions, including the starting pH and the amounts of lactose and nitrogen suppliers for the enzyme synthesis process (Amin et al., 2023; Zuhri and Wilda, 2024; Kazemi et al., 2025). Investigations focused on the production of β-galactosidase from lactic acid-producing bacteria identified the optimal pH values for culture media ranging between 6.0 and 7.5 (Ohaegbu et al., 2023; Valenzuela et al., 2024). The pH levels recorded in our study varied from 3.6 to 8.4, with an optimal enzymatic activity noted within the range of 5-7. Given that β-galactosidase can be induced, it is essential for the growing environment to contain lactose as a carbon source, in addition to the amino acids necessary for the synthesis process (Mukherjee et al., 2023; Nawaz et al., 2024). ANOVA revealed that both the response data and the interaction among the five variables were statistically important (p < 0.05). The method used for assessing the quadratic model’s significance is detailed in Table 4. The coefficient of determination (R²) was found to be 96.09 %, while the adjusted coefficient of determination (R² adj) was 93.31 %. These outcomes are in alignment with those reported by Da Silva et al. (2020).

According to Danbaba et al. (2019), a system with a coefficient of determination (R²) value greater than 75 % is considered acceptable, indicating its effectiveness. This suggests that RSM is efficient for enhancing the culture environment composition required for β-galactosidase expression from the Lactiplantibacillus plantarum strain S1. This model accounts for 96.09 % of the diversity in the final result. Additionally, the model displays statistical importance at the 95 % confidence interval (p ≤ 0.05). A higher R² value, approaching 1, indicates a more accurate prediction of the output. The adjusted coefficient of determination of 0.9331 demonstrated a strong correlation with the R², underscoring the model’s substantial significance. The fit value (F) for the regression analysis reached its significance at the 5 % threshold (p < 0.05), which confirms that the model is well-suited to account for the variability in enzyme synthesis as influenced by the five identified factors. Thus, the substantial F- value of 34.62 and the corresponding small predicted value (P) suggest that the system is indeed relevant.

The overall linear, quadratic, and the two ways interaction effects of all the investigated factors were significant. The obtained results are fitted with the following:

Regression equation depicted by Mehiaoui et al. (2023):

E.A = 38.74+ 0.260 N- 4.513 PH- 3.922 IS- 1.890 T + 0.6136 IP + 0.0333 N*N + 0.0878 PH*PH+ 0.0385 IS*IS + 0.02209 T*T + 0.001669 IP*IP - 0.0433 N*PH + 0.0182 N*IS - 0.0174 N*T+ 0.00593 N*IP + 0.2305 PH*IS + 0.1250 PH*T - 0.03443 PH*IP + 0.0973 IS*T- 0.02551 IS*IP - 0.01445 T*IP

Where; E.A= β-galactosidase activity (U/ ml), N= Nitrogen concentration (g/ ml), IS= Inoculum size (v/ ml), T= Temperature (oC), and IP= incubation duration (h).

Table 4: Statistical analysis of variation for the experimental results of the quadratic model obtained by CCD for β-galactosidase activity produced by Lactiplantibacillus plantarum strain S1.

Source	DF	Adj SS	Adj MS	F-value	p-value
Blocks	2	0.3744	0.1872	2.07	0.143
N	1	0.4184	0.4184	4.63	0.039
pH	1	3.3996	3.3996	37.58	0.000
IS	1	1.1772	1.1772	13.01	0.001
T	1	13.0971	13.0971	144.79	0.000
IP	1	10.5830	10.5830	117.00	0.000
N*N	1	0.0659	0.0659	0.73	0.400
PH*PH	1	0.4599	0.4599	5.08	0.031
IS*IS	1	0.0885	0.0885	0.98	0.330
T*T	1	4.3678	4.3678	48.29	0.000
IP*IP	1	3.4426	3.4426	38.06	0.000
N*PH	1	0.0599	0.0599	0.66	0.422
N*IS	1	0.0105	0.0105	0.12	0.735
N*T	1	0.1192	0.1192	1.32	0.260
N*IP	1	0.1623	0.1623	1.79	0.190
PH*IS	1	1.7006	1.7006	18.80	0.000
PH*T	1	6.1241	6.1241	67.70	0.000
PH*IP	1	5.4623	5.4623	60.39	0.000
IS*T	1	3.7108	3.7108	41.02	0.000
IS*IP	1	2.9982	2.9982	33.15	0.000
T*IP	1	11.7916	11.7916	130.36	0.000
Error	31	2.8041	0.0905
Lack of fit	22	2.8041	0.1275	-	-
Pure error	9	0.0000	0.0000
Total	53	71.7019

Where DF: Degrees of freedom, AdjSS: Adjusted Sum of Squares, Adj MS: Adjusted Mean Square, F-value: actual response, p-value: Predicted response.

Results of regression analysis concerning the enzymatic activity indicated that the tested factors of pH, nitrogen concentration, inoculum size, incubation duration, and temperature had substantial positive impacts on the enzyme synthesis (p < 0.05) as shown in Table 5.

Table 5: Estimated regression coefficients for enzymatic activity of Lactiplantibacillus plantarum strain S1.

Term	Coefficient	SE coefficient coeffiecient	T value	p value	VIF
Constant	0.0625	0.0867	0.72	0.476
Blocks
1	0.0637	0.0568	1.12	0.271	1.19
2	0.0630	0.0568	1.11	0.276	1.19
N	-0.0984	0.0458	-2.15	0.039	1.00
PH	0.2805	0.0458	6.13	0.000	1.00
IS	0.1651	0.0458	3.61	0.001	1.00
T	0.5506	0.0458	12.03	0.000	1.00
IP	-0.4950	0.0458	-10.82	0.000	1.00
N*N	0.0333	0.0389	0.85	0.400	1.01
PH*PH	0.0878	0.0389	2.25	0.031	1.01
IS*IS	0.0385	0.0389	0.99	0.330	1.01
T*T	0.2707	0.0389	6.95	0.000	1.01
IP*IP	0.2403	0.0389	6.17	0.000	1.01
N*PH	-0.0433	0.0532	-0.81	0.422	1.00
N*IS	0.0182	0.0532	0.34	0.735	1.00
N*T	-0.0610	0.0532	-1.15	0.260	1.00
N*IP	0.0712	0.0532	1.34	0.190	1.00
PH*IS	0.2305	0.0532	4.34	0.000	1.00
PH*IP	-0.4132	0.0532	-7.77	0.000	1.00
IS*T	0.3405	0.0532	6.40	0.000	1.00
IS*IP	-0.3061	0.0532	-5.76	0.000	1.00
T*IP	-0.6070	0.0532	-11.42	0.000	1.00
					1.00

Where, SE Coeffiecient: standard error coeffiecient, T-value: observed response value, p-value: predicted response value, VIF: variance inflation factor.

The Pareto chart serves as a tool for illustrating the impact of the independent variables under investigation; along with their interactions, on the response variables (Duan et al., 2021). Moreover, its analysis demonstrated that all variables (A-E) investigated had a statistically substantial influence on the β-galactosidase enzyme’s output and specific activity as indicated in Table 4 and Figure 6. This is evidenced by their p-values being below 0.05 and their corresponding F-values being notably high, as detailed in Table 4 for ANOVA results.

The residuals plotted against the predicted responses demonstrate the lack of any identifiable patterns or trends, indicating that the disparity in the initial data analysis is consistent. Furthermore, the fact that the majority of residuals were below 0.5 % suggests that the design is appropriate for characterizing the β-galactosidase synthesis within the parameters being investigated.

Figure 7a-j, represents the response surface charts, developed to investigate the best values of each variable and their interactions concerning enzyme production, based on the regression model. Notably, the optimal yield of β-galactosidase obtained within a pH range of 6 to 8 with a nitrogen concentration maintained at 2 % as illustrated in Figure 7a. Among the variables examined, pH emerged as a highly critical component affecting enzyme function and nutrients uptake by the cell, which in turn impacts RNA and protein synthesis. This study indicated that lower nitrogen concentrations correlated with increased β-galactosidase production, whereas higher nitrogen levels resulted in a decreased enzyme activity. Meanwhile, elevated levels of nitrogen can result in cellular apoptosis (Yi et al., 2025). It was indicated that a higher inoculum size of 4 % was effective for biosynthesis of β-galactosidase using Enterobacter cloacae B5 (Chandel and Sharma, 2020), as depicted in Figure 7b.

Temperature emerged as the most critical factor influencing β-galactosidase production, with activity levels that increased within the ideal temperature level of 25-40 °C on a chart, and peaked at 37° C (Figure 7c). The study conducted by Singh and Sambyal (2023) demonstrated that β-galactosidase production in Bifidobacterium animalis had been maximized at 37 oC. The current optimal temperature for β-galactosidase synthesis aligns with the findings of Niamah et al. (2023) on their study of Bacillus spp. The levels of β-galactosidase production and the final population size significantly rose as the

incubation time increased, peaking at 24 h (Figure 7d). This observation corroborates with the previous results presented by Oparaji (2022) on their study on Bifidobacteria sp. Moreover, these results are in harmony with the previous conclusions drawn by Singh and Sambyal (2023) regarding L. plantarum.

Figure 7a, e, f, g, indicate that the perfect pH for the Lactiplantibacillus plantarum strain S1 to release β-galactosidase lied between pH 6.8 and 7; with pH 7 identified as the most suitable. These outcomes are in consistence with those of Choi et al. (2021), who found that the highest growth of L. plantarum 200655 was observed at pH 7 and that low pH levels (< 4.4) may influence bacterial growth and diminish it. Furthermore, similar neutral pH optima have been documented for various LAB species, including L. acidophilus (Abdaltef et al., 2023).

In Figures 7h, i, j, it is evident that the yield of lactase enzyme reached its peak at 37 °C. This finding aligns with the previous studies conducted by Chandel and Sharma (2020), Gomes et al. (2021) which showed that temperatures under 40 °C were optimal for the synthesis of β-galactosidase by L. reuteri, S. thermophilus, and B. longum. In contrast, enzyme production was enhanced with larger inoculum sizes; particularly between 3 % and 5 %, but declined as the duration of incubation increased.

Following the statistical analysis results, additional tests were conducted as detailed in Table 6 and Figure 8. The ideal parameters for β-galactosidase fabrication were found to be 37 °C, pH 7.0, 2 % nitrogen concentration, 5 % inoculum size, 4.6 % lactose as the medium’s carbon source. In the context of the given conditions, the recorded level of β-galactosidase yield was 5.523 U/ ml, which marginally deviated from the anticipated range of 4.8149 U/ ml. This indicates that the system was established is both a precise and dependable manner for forecasting the perfect culture conditions for enhancing β-galactosidase biosynthesis.

Table 6: Multiple response prediction of β-galactosidase enzyme activity for Lactiplantibacillus plantarum strain S1.

Variable	Setting
N	2
PH	7
IS	5
T	37
IP	24
Response	Fit	SE Fit	95% CI	95% PI
E.A	4.815	0.202	(4.403; 5. 22)	(4.076; 5.554)

Where SE Fit: Standard error fit, 95%CI :95 % Confidence interval, 95 % PI: Predicted interval.

The integration of the Plackett–Burman designs with RSM is prevalent in the field of experimental analysis; particularly for enhancing enzyme production from the microorganisms (Abdella and Ibrahim, 2024; Karamchandani et al., 2025).

Conclusions and Recommendations

The production of bacterial β-galactosidases has significant applications owing to their activity across a broad spectrum of pH levels and temperatures. The selection of LAB as an appropriate β-galactosidase resource is attributed to their recognized safety for use in food industry applications. Consequently, it has been deduced that cheese permeate; an industrial dairy byproduct, can be effectively utilized for the biosynthesis of β-galactosidase by the Lactiplantibacillus plantarum strain S1, yielding 5.523 U/ ml, when grown at initial pH 7, lactose as carbon source in the medium (4.6 %), potassium nitrate as a nitrogen source (2.0 %), and an incubation temperature of 37 °C for 24 h. RSM is a highly effective approach used for the optimization of the fermentation media aimed at enhancing β-galactosidase production from the Lactiplantibacillus plantarum strain S1.

In response to global climate change and other environmental issues, new emission reduction strategies and development models for the dairy industry (a significant energy-intensive food sector) must be established in order to meet net-zero objectives. The dairy sector currently lacks worldwide standards and hence requires further efforts to thoroughly address sustainability challenges. β-galactosidase enzyme is a crucial product for the dairy sector and expensive to get. It is therefore recommended that more efforts should be undertaken to pursue further exploration and evaluation of superior β-galactosidase-generating microbial species. Other β-galactosidase-producing microorganisms should also be explored for deployment and application in our home-developed dairy industries.

Acknowledgments

The authors express their sincere acknowledgement and gratitude to the Dairy Research and Technology Department, Food Technology Research Institute, Agricultural Research Center, for supporting and providing the requirements necessary for conducting this study.

Novelty Statement

This study is the first to isolate and characterize a novel lactic acid bacterium such as Lactiplantibacillus plantarum strain S1, which produced β-galactosidase enzyme by using a dairy waste cheese permeate as a growth medium.

Author’s Contribution

Safaa Salah El-Din Taha: Methodology, investigations, and writing the original draft.

Osama Abd El-Hamid Ibrahim: Supervision, Research design and editing the data.

Einas Hamed El-Shatoury and Amany Mohamed El-Deeb: Supervision, research design, and revision.

Hayam Abd El-Naby Sayed: Supervision, statistical study design and analysis, molecular data analysis, revision and editing the manuscript.

All authors approved the final version the manuscript.

Funding source

No funds, grants, or other support were received during preparation of this study.

Ethical approval

Ethical approval is not required for this study as it is purely computational and does not involve human subjects and/or animals.

Conflict of interests

The authors have declared no conflicts of interest.

References

Abdaltef, M.J., Al-Temimi, W.K. and Al-Shawi, S.G., 2023. Extraction of B-galactosidase enzyme from lacticacid bacteria. IOP Conf. Ser. Earth Environ. Sci., IOP Publ., 1262(6): 062018. https://doi.org/10.1088/1755-1315/1262/6/062018

Abdella, M.A. and Ibrahim, G.E. 2024. Application of statistical designs strategy to improve cellulase production using agro-waste residue by a novel isolate Bacillus licheniformis strain-MA1 and assessing the enzyme effect on apple juice quality. BMC Microbiol., 24(1): 511. https://doi.org/10.1186/s12866-024-03656-z

Afolabi, F.T., Adewale, O.P. and Adeyemo, S.M., 2022. Isolation, production and optimization of beta-galactosidase by utilizing yeasts isolated from selected dairy products. J. Food. Saf. Hyg., 8(3): 170-182. https://doi.org/10.18502/jfsh.v8i3.11019

Ahansaz, N., Tarrah, A., Pakroo, S., Corich, V. and Giacomini, A., 2023. Lactic acid bacteria in dairy foods: Prime sources of antimicrobial compounds. Fermentation, 9(11): 964. https://doi.org/10.3390/fermentation9110964

Akcan, N., 2018. Cultural conditions optimization for production of β-galactosidase from Bacillus licheniformis ATCC 12759 under solid-state fermentation. Turk. J. Biochem., 43(3): 240-247. https://doi.org/10.1515/tjb-2017-0153

Alshanberi, A.M., Al-Shaeri, M.A. and Ansari, S.A., 2021. Overviewing the application of β-galactosidase “Immobilized on nanoparticles” in dairy industries. Braz. Arch. Biol. Technol., 64: e21180747. https://doi.org/10.1590/1678-4324-2021180747

Amin, A.A., Olama, Z.A. and Ali, S.M., 2023. Characterization of an isolated lactase enzyme produced by Bacillus licheniformis ALSZ2 as a potential pharmaceutical supplement for lactose intolerance. Front. Microbiol., 14: 1180463. https://doi.org/10.3389/fmicb.2023.1180463

Augustyniak, A., Gottardi, D., Giordani, B., Gaffey, J. and Mc Mahon, H., 2023. Dairy bioactives and functional ingredients with skin health benefits. J. Funct. Foods, 104: 105528. https://doi.org/10.1016/j.jff.2023.105528

Ayad, A.A., Gad El-Rab, D.A. Ibrahim, S.A. and Williams, L.L. 2020. Nitrogen sources effect on Lactobacillus reuteri growth and performance cultivated in date palm (Phoenix dactylifera L.) by-products. Fermentation, 6(3): 64. https://doi.org/10.3390/fermentation6030064

Ayivi, R.D. and Ibrahim, S.A., 2022. Lactic acid bacteria: An essential probiotic and starter culture for the production of yoghurt. Int. J. Food Sci. Technol., 57(11): 7008-7025. https://doi.org/10.1111/ijfs.16076

Bella, K., Pilli, S., Venkateswara Rao, P. and Tyagi, R.D., 2024. Bio-conversion of whey lactose using enzymatic hydrolysis with β-galactosidase: An experimental and kinetic study. Environ. Technol., 45(6): 1234-1247. https://doi.org/10.1080/09593330.2022.2139639

Bhatia, S.K., Kumar, V., Kumar, V., Bhatia, R.K. and Yang, Y.H., 2023. Microbial activity and productivity enhancement strategies. In: Basic biotechniques for bioprocess and bioentrepreneurship. Acad. Press, pp. 85-104. https://doi.org/10.1016/B978-0-12-816109-8.00004-0

Bié, J., Sepodes, B., Fernandes, P.C. and Ribeiro, M.H., 2022. Enzyme immobilization and co-immobilization: Main framework, advances and some applications. Processes, 10(3): 494. https://doi.org/10.3390/pr10030494

Borralho, A.I. and Marcos, P., 2025. Lactose intolerance and malabsorption revisited: Exploring the impact and solutions. GE. Port. J. Gastroenterol., https://doi.org/10.1159/000545923

Boukezzoula, N., Chaalel, A., Gerard, P., Tefiani, C., Bruneau, A., Bouziane, N. and Riazi, A., 2019. Evaluation of lactase activity in new isolated Lactobacillus strains. S.A. J. Exp. Biol., 8(4), p.154-161. https://doi.org/10. 38150/sajeb.8(4).p154-161

Carević, M., Vukašinović-Sekulić, M., Ćorović, M., Rogniaux, H., Ropartz, D. Veličković, D. and Bezbradica D., 2018. Evaluation of β-galactosidase from Lactobacillus acidophilus as biocatalyst for galacto-oligosaccharides synthesis: Product structural characterization and enzyme immobilization. J. Biosci. Bioeng., 126: 697-704. https://doi.org/10.1016/j.jbiosc.2018.06.003

Carević, M., Vukašinović-Sekulić, M., Grbavčić, S., Stojanović, M., Mihailović, M., Dimitrijević, A. and Bezbradica, D., 2015. Optimization of β-galactosidase production from lactic acid bacteria. Hemijska Industrija. 69(3): 305-312. https://doi.org/10.2298/HEMIND140303044C

Carvalho, P., Costa, C.E., Baptista, S.I.L. and Domingues, L., 2021. Yeast cell factories for sustainable whey-to-ethanol valorisation towards a circular economy. Biofuel Res. J., 8(4): 1529-1549. https://doi.org/10.18331/BRJ2021.8.4.4

Chandel, H. and Sharma, N., 2020. Optimization of β-Galactosidase produced by a potential lactic acid Bacteria Lactobacillus casei MB2 isolated from traditional dairy product of Himachal Pradesh. Int. J. Curr. App. Sci., 9(6): 2819-2832. https://doi.org/10.20546/ijcmas.2020.906.341

Chen, W., Jafarzadeh, S., Thakur, M., Ólafsdóttir, G., Mehta, S., Bogason, S. and Holden, N.M., 2021. Environmental impacts of animal-based food supply chains with market characteristics. Sci. Total Environ., 783: 147077. https://doi.org/10.1016/j.scitotenv.2021.147077

Cheng, P., Tang, H., Lin, F. and Kong, X., 2023. Bibliometrics of the nexus between food security and carbon emissions: hotspots and trends. Environ. Sci. Pollut. Res., 30(10): 25981–25998. https://doi.org/10.1007/s11356-022-23970-1

Chengolova, Z., Ivanova, R. and Gabrovska, K., 2024. Lactose intolerance–single nucleotide polymorphisms and treatment. J. Am. Nutr. Assoc., 43(2): 213-220. https://doi.org/10.1080/27697061.2023.2251557

Choi, G.H., Lee, N.K. and Paik, H.D., 2021. Optimization of medium composition for biomass production of Lactobacillus plantarum 200655 using response surface methodology. J. Microbiol. Biotechnol., 31(5): 717–725. https://doi.org/10.4014/jmb.2103.03018

Da-Silva, E.C., De Andrade Calaça, P.R., Porto, A.L.F., Bezerra, R.P. and Soares, M.T.C.V., 2020. Optimization by response surface methodology for production of β-galactosidase from Enterococcus faecium using recycled medium. Res. Soc. Dev., 9(10): e479108135. https://doi.org/10.33448/rsd-v9i10.8135

Danbaba, N., Nkama, I., Badau, M.H. and Idakwo, P.Y., 2019. Predictive modeling and optimization of extrusion cooking process for color characteristics and consumer acceptability of fortified rice snacks. IOSR J. Environ. Sci. Toxicol. Food Technol., 13(1): 33-43.

Deng, Y., Xu, M., Ji, D. and Agyei, D., 2020. Optimization of β-galactosidase production by batch cultures of Lactobacillus leichmannii 313 (ATCC 7830™). Fermentation, 6(1): 27. https://doi.org/10.3390/fermentation6010027

Devi, S., Chhibber, S. and Harjai, K., 2022. Optimization of cultural conditions for enhancement of anti-quorum sensing potential in the probiotic strain Lactobacillus rhamnosus GG against Pseudomonas aeruginosa. 3 Biotech, 12(6): 133. https://doi.org/10.1007/s13205-022-03187-2

Duan, F., Zhao, R., Yang, J., Xiao, M. and Lu, L., 2021. Integrated utilization of dairy whey in probiotic β-galactosidase production and enzymatic synthesis of galacto-oligosaccharides. Catalysts, 11(6): 658. https://doi.org/10.3390/catal11060658

El-Sawah, M.M.A., Menshawy, A.S.A., Kassem, M.M., Ismail, I.I. and Afify, A.H., 2006. Optimization of β-galactosidase production by Streptococcus salivarius subsp. thermophilus using whey. J. Agric. Sci. Mansoura Univ., 31(3): 1585-1603. https://doi.org/10.21608/jacb.2006.203074

Gantumur, M.A., Sukhbaatar, N., Bilawal, A., Gankhuyag, J., Gao, C., Enkhtuya, E. and Jiang, J., 2025. Elucidating fermentation characteristics, key volatile compounds, and safety evaluations of whey permeate-derived alcoholic beverages. Food Biosci., 68: 106448. https://doi.org/10.1016/j.fbio.2025.106448

Geiger, B., Nguyen, H.M., Wenig, S., Nguyen, H.A., Lorenz, C., Kittl, R. and Nguyen, T.H., 2016. From by-product to valuable components: Efficient enzymatic conversion of lactose in whey using β-galactosidase from Streptococcus thermophilus. Biochem. Eng. J., 116: 45-53. https://doi.org/10.1016/j.bej.2016.04.003

Gheytanchi, E., Heshmati, F., Shargh, B.K., Nowroozi, J. and Movahedzadeh, F., 2010. Study on β-Galactosidase enzyme produced by isolated Lactobacilli from milk and cheese. Afr. J. Microbiol. Res. 4(6): 454-458.

Gomes, T.A., Fontana, É., Zielinski, A.A.F., Nogueira, A. and Spier, M.R. 2021. Optimizing the growth-associated β-galactosidase production by probiotic Lactobacillus reuteri B-14171: Experimental design, culture medium volume increase, and cell growth modeling. Scientia Plena, 17(4). https://doi.org/10.14808/sci.plena.2021.040203

Goyal, R., Dhingra, H., Bajpai, P. and Joshi, N., 2012. Characterization of the lactobacillus isolated from different curd samples. Afr. J. Biotechnol., 11(79): 14448–14452. https://doi.org/10.5897/AJB11.310

Hooda, A., Nikam, P., Tripathi, A.D. and Bharadwaj, A., 2025. Effect of processing parameters on lactose hydrolysis. Lactose hydrolysis in dairy products, pp. 79-100. https://doi.org/10.3390/catal11060658

Hsu, C.A., Yu, R.C. and Chou, C.C., 2005. Production of beta-galactosidase Bifidobacteria as influenced by various culture conditions. Int. J. Food Microbiol., 104: 197–206. https://doi.org/10.1016/j.ijfoodmicro.2005.02.010

Hsu, C.A., Lee, S.L. and Chou, C.C., 2007. Enzymatic production of galacto-oligosaccharides by β-Galactosidase from Bifidobacterium longum BCRC 15708. J. Agric. Food Chem., 55: 2225-2230. https://doi.org/10.1021/jf063126

Ismail, Y.S., Yulvizar, C. and Mazhitov, B., 2018. Characterization of lactic acid bacteria from local cow’s milk kefir, IOP Conference Series: Earth Environ. Sci., 130(1): 012019. https://doi.org/10.1088/1755-1315/130/1/012019

Johansen, A.G., Vegarud, G.E. and Skeie, S., 2002. Seasonal and regional variation in the composition of whey from Norwegian cheddartype and Dutch-type cheeses. Int. Dairy J., 12: 621-629. https://doi.org/10.1016/S0958-6946(02)00054-7

Karamchandani, B.M., Maurya, P.A., Pawar, A.A., Pable, A., Awale, M., Dalvi, S.G. and Satpute, S.K., 2025. The role of statistical methods in optimizing and enhancing fungal chitosan commercial production. 3 Biotech, 15(3): 1-23. https://doi.org/10.1007/s13205-025-04236-2

Karlapudi, A.P., Krupanidhia, S., Rajeswara, R.E., Indira, M., Bobby, M.D.N. and Venkateswarulu, T.C., 2018. Plackett-Burman design for screening of process components and their effects on production of lactase by newly isolated Bacillus sp. VUVD101 strain from Dairy effluent. Beni-Suef. Univ. J. Basic Appl. Sci., 7: 543-546. https://doi.org/10.1016/j.bjbas.2018.06.006

Kazemi, S., Homayouni-Rad, A., Samadi Kafil, H., Sarabi-aghdam, V., Zeynolabedini, P., Pour Agha, B. and Allah-Madadi, S., 2025. Selection of appropriate probiotic yeasts for use in dairy products: a narrative review. Food Prod. Process. Nut., 7(1): 13. https://doi.org/10.1186/s43014-024-00293-x

Khalid, S., Amjad, Y., Zafar, L., Khan, O., Shahzadi, L. and Rafa, S.A. 2024. Systematic review: Diagnosis, treatment and management strategies of lactose intolerance. Open Access Res. J. Biol. Pharm., 12(1): 001-013. https://doi.org/10.53022/oarjbp.2024.12.1.0032

Kittibunchakul, S., van Leeuwen, S.S., Dijkhuizen, L., Haltrich, D. and Nguyen, T.H., 2020. Structural comparison of different galacto-oligosaccharides mixtures formed by β-galactosidases from lactic acid bacteria and bifidobacteria. J. Agric. Food Chem., 68(15): 4437-4446. https://doi.org/10.1021/acs.jafc.9b08156

Kouadio, N.J., Zady, A.L.O., Kra, K.A.S., Digută, F.C., Niamke, S. and Matei, F., 2024. In vitro probiotic characterization of Lactiplantibacillus plantarum strains isolated from traditional fermented dockounou paste. Fermentation, 10(5): 264. https://doi.org/10.3390/fermentation10050264

Kumar, A., Dhiman, S., Krishan, B., Samtiya, M., Kumari, A., Pathak, N. and Dhewa, T., 2024. Microbial enzymes and major applications in the food industry: A concise review. Food Prod. Process Nutr., 6(1): 85. https://doi.org/10.1186/s43014-024-00261-5

Lagacé, L., Pitre, M., Jacques, M. and Roy, D., 2004. Identification of the bacterial community of maple sap by using amplified ribosomal DNA (rDNA) restriction analysis and rDNA sequencing. App. Environ. Microbiol., 70(4): 2052–2060. https://doi.org/10.1128/AEM.70.4.2052-2060.2004

Lam, S., Dodd, W., Berrang-Ford, L., Ford, J., Skinner, K., Papadopoulos, A. and Harper, S. L. 2021. How are climate actions evaluated? A review of United Nations food security evaluations. Glob. Food Sec., 28: 100509. https://doi.org/10.1016/j.gfs.2021.100509

Lappa, I.K., Papadaki, A., Kachrimanidou, V., Terpou, A., Koulougliotis, D., Eriotou, E. and Kopsahelis, N., 2019. Cheese whey processing: Integrated biorefinery concepts and emerging food applications. Foods, 8(8): 347. https://doi.org/10.3390/foods8080347

Letunic, I. and Bork, P., 2024. Interactive tree of life (iTOL) v6: Recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res., 52(W1): W78-W82. https://doi.org/10.1093/nar/gkae268

Li, Y., Miros, S., Kiani, H., Eckhardt, H.G., Blanco, A., Mulcahy, S. and Halim, R., 2023. Mechanism of lactose assimilation in microalgae for the bioremediation of dairy processing side-streams and co-production of valuable food products. J. Appl. Phycol., 35(4): 1649-1661. https://doi.org/10.1007/s10811-023-03002-2

Liu, Y., Wang, S., Wang, L., Lu, H., Zhang, T. and Zeng, W., 2024. Characterization of genomic, physiological, and probiotic features of Lactiplantibacillus plantarum JS21 strain isolated from traditional fermented Jiangshui. Foods, 13(7): 1082. https://doi.org/10.3390/foods13071082

Ma, J., Xu, C., Liu, F., Hou, J., Shao, H. and Yu, W., 2021. Stress adaptation and cross-protection of Lactobacillus plantarum KLDS 1.0628. CyTA-J. Food, 19: 72–80. https://doi.org/10.1080/19476337.2020.1859619

Maghraby, Y.R., El-Shabasy, R.M., Ibrahim, A.H. and Azzazy, H.M.E.S., 2023. Enzyme immobilization technologies and industrial applications. ACS Omega, 8(6): 5184-5196. https://doi.org/10.1021/acsomega.2c07560

Mahadevaiah, S., Basavaiah, R., Parida, M. and Batra, H.V., 2020. Optimal production of β-galactosidase from Lactobacillus fermentum for the synthesis of prebiotic galactooligosaccharides (GOS). J. Pure Appl. Microbiol., 14(4): 2769-2780. https://doi.org/10.22207/JPAM.14.4.53

Malliaroudaki, M.I., Watson, N.J., Ferrari, R., Nchari, L.N. and Gomes, R.L., 2022. Energy management for a net zero dairy supply chain under climate change. Trends Food Sci. Technol., 126: 153–167. https://doi.org/10.1016/j.tifs.2022.01.015

Malos, I.G., Ghizdareanu, A.I., Vidu, L., Matei, C.B. and Pasarin, D., 2025. The role of whey in functional microorganism growth and metabolite generation: A biotechnological perspective. Foods, 14(9): 1488. https://doi.org/10.3390/foods14091488

Maresca, D., Zotta, T. and Mauriello, G., 2018. Adaptation to aerobic environment of lactobacillus johnsonii/gasseri strains. Front. Microbiol., 9: 157. https://doi.org/10.3389/fmicb.2018.00157

Mehiaoui, H., Roudj, S. and Hassaine, O., 2023. Application of box-wilson central composite experimental design, to optimize the autolysis conditions for Lactococcus lacfis LCL strain; Focus on temperature, pH and salt gradient. Acta Manilana, 71: 18-35. https://actamanilana.ust.edu.ph/, https://doi.org/10.53603/actamanil.71.2023.lgnv5021

Mohamed, T.H., Tammam, A.A. and Abd-El-Rahim, A., 2012. Electrical conductivity of raw milk and Kareish cheese. J. Food Dairy Sci. Mansoura Univ., 3(5): 315–323. https://doi.org/10.21608/jfds.2012.75395

Movahedpour, A., Ahmadi, N., Ghalamfarsa, F., Ghesmati, Z., Khalifeh, M., Maleksabet, A. and Savardashtaki, A., 2022. β‐Galactosidase: From its source and applications to its recombinant form. Biotechnol. App. Biochem., 69(2): 612-628. https://doi.org/10.1002/bab.2137

Mukherjee, P., Pal, S. and Sivaprakasam, S., 2024. Optimization of D-lactic acid biosynthesis from diverse carbon sources in mutant Lactobacillus delbrueckii subsp. bulgaricus via random mutagenesis. Syst. Microbiol. Biomanuf., 5: 702-721. https://doi.org/10.1007/s43393-024-00316-1

Mukherjee, P., Raj, N. and Sivaprakasam, S., 2023. Harnessing valorization potential of whey permeate for D-lactic acid production using lactic acid bacteria. Biomass Convers. Biorefin. 13(17): 15639-15658. https://doi.org/10.1007/s13399-023-05038-3

Murad, H.A., Refaea, R.I. and Aly, E.M., 2011. Utilization of UF-permeate for production of β-galactosidase by lactic acid bacteria, Polish J. Microbiol., 60 (2): 139-144. https://doi.org/10.33073/pjm-2011-019

Nadeem, R., Imran, A., Wei, C.R., Naz, S., Waheed, W., Akram, M.A. and Befa Kinki, A., 2024. A review on the potential impact of probiotics and prebiotics in enhancing health benefits. Cogent Food Agric., 10(1): 2409831. https://doi.org/10.1080/23311932.2024.2409831

Nawal, B., Abdelmalek, C., Choukri, T., Aurélia, B., Philippe, G., Nabil, B. and Ali, R., 2018. Evaluation of lactase activity in new isolated Lactobacillus strains. South Asian J. Exp. Biol., 8(4): 154-161. https://doi.org/10.38150/sajeb.8(4).p154-161

Nawaz, T., Gu, L., Fahad, S., Saud, S., Harrison, M. T. and Zhou, R., 2024. Sustainable protein production through genetic engineering of cyanobacteria and use of atmospheric N2 gas. Food Energy Secur., 13(2): e536. https://doi.org/10.1002/fes3.536

Naziri, E., Papadaki, E., Savvidis, I., Botsaris, G., Gkatzionis, K., Mugampoza, E. and Mantzouridou, F.T., 2023. Exploring the potential of halloumi second cheese whey for the production of lactic acid cultures for the dairy industry. Sustainability, 15(11): 9082. https://doi.org/10.3390/su15119082

Niamah, A.K., Al-Sahlany, S.T.G., Verma, D.K., Singh, S., Tripathy, S., Baranwal, D. and Aguilar, C.N., 2023. Chemistry and sources of lactase enzyme with an emphasis on microbial biotransformation in milk. In: Microbial bioreactors for industrial molecules, pp. 315-332. https://doi.org/10.1002/9781119874096.ch15

Ohaegbu, C.G., Achi, O.K., Nwachukwu, E., Ngene, A.C. and Achi, N.K., 2023. Optimization of culture conditions and partial purification of phytase enzyme isolated from three lactic acid producing bacteria. Pharmacol. Toxicol. Natl. Med., 3(3-4): 1-11. https://doi.org/10.52406/ptnm.v3i3-4.63

Oparaji, E.H., 2022. Molecular screening and identification of Lactobacillus acidophilus producing β-galactosidase. J. Enzy. Eng., Clausius Scientific Press, Canada. ISSN 2616-2962 Vol. 1 No. 1

Prasad, L.N., Ghosh, B.C., Sherkat, F. and Shah, N.P., 2013. Extraction and characterisation of β-galactosidase produced by Bifidobacterium animalis spp. lactis Bb12 and Lactobacillus delbrueckii spp. bulgaricus ATCC 11842 grown in whey. Int. Food Res. J., 20: 487-494.

Premović, T., premović, J. and Ilić, I., 2024. Application of permeate and lactose from whey for sustainable cheese production. Publishers: Faculty of economics and engineering management–fimek, novi sad, serbia; educational and business center for development of human resources, pp. 482.

Ray, M., Manjunath, A., Baruah, R. and Halami, P.M., 2023. Enzymes from lactic acid bacteria for nutraceuticals production. In: Microbial enzymes in production of functional foods and nutraceuticals. CRC Press. pp. 25-44. https://doi.org/10.1201/9781003311164-4

Robescu, M.S. and Bavaro, T., 2025. A comprehensive guide to enzyme immobilization: All you need to know. Molecules, 30(4): 939. https://doi.org/10.3390/molecules30040939

Safira, A.B. and Purbasari, A., 2023. Optimization and characterization of biodegradable film based on glutinous flour/glycerol/chitosan/ZnO using response surface methodology (RSM)-central composite design (CCD). J. Kimia Sains dan Aplikasi, 25(10): 368-381. https://doi.org/10.14710/jksa.25.10.368-381

Sahoo, M., Aradwad, P., Sanwal, N., Sahu, J.K., Kumar, V. and Naik, S.N., 2023. Fermented foods in health and disease prevention. Microbes in the food industry, pp. 39-85. https://doi.org/10.1002/9781119776406.ch2

Saleem, G.N., Gu, R., Qu, H., Bahar, K.G., Rashid, R.I., Qasim, M. and Chen, X., 2024. Therapeutic potential of popular fermented dairy products and its benefits on human health. Front. Nutr., 11: 1328620. https://doi.org/10.3389/fnut.2024.1328620

Santra, H.K. and Banerjee, D., 2021. Extremophilic microbes and their extremozymes for industry and allied sectors. Microb. Extreme Environ. CRC Press. pp. 1-42. https://doi.org/10.1201/9780429328633-1

Sharma, K.B., Lata, P., Thakur, R. and Rangra, S., 2023. Quadratic model analysis of β-galactosidase from kluyveromyces marxianus isolated from indigenous fermented dairy product. Trends Carbohydr. Res., 15(2): 22.

Sharma, S. and Singh, P., 2014. Isolation and characterization of β-galactosidase enzyme producing microbe and optimization of its enzyme activity under different culture conditions. Int. J. Curr. Microbiol. Appl. Sci., 3(7): 148-155.

Shrushti, M., Subrota, H., Heena, P. and Aparnathi, K.D., 2017. Process optimization for the production of β-galactosidase using potential Lactobacillus cultures. Int. J. Curr. Microbiol. Appl. Sci., 6(8): 1454-1469. https://doi.org/10.20546/ijcmas.2017.608.176

Singh, R.V. and Sambyal, K., 2023. β-galactosidase as an industrial enzyme: Production and potential. Chem. Pap., 77(1): 11-31. https://doi.org/10.1007/s11696-022-02507-3

Sumit, S. and Priyanka, S., 2014. Isolation and characterization of β-galactosidase enzyme producing microbe and optimization of its enzyme activity under different culture conditions. Int. J. Curr. Microbiol. Appl. Sci., 3(7): 148-155.

Sun, F., Liu, S., Che, X., Wang, G., Wang, X., Li, Y. and Chen, H. 2024. High-density fermentation of Lactobacillus plantarum P6: Enhancing cell viability via sodium alginate enrichment. Foods, 13(21): 3407. https://doi.org/10.3390/foods13213407

Taggar, M.S., Kaur, A., Jain, C., Kalia, A. and Sooch, S.S., 2024. Hydrogen production via dark fermentation: A review of influential factors. Cell. Chem. Technol., 58(9-10): 1051-1063. https://doi.org/10.35812/CelluloseChemTechnol.2024.58.90

Tamura, K., Stecher, G. and Kumar, S., 2021. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol., 38(7): 3022-3027. https://doi.org/10.1093/molbev/msab120

Taye, Y., Degu, T., Fesseha, H. and Mathewos, M., 2021. Isolation and identification of lactic acid bacteria from cow milk and milk products. Sci. World J., 2021: 4697445. https://doi.org/10.1155/2021/4697445

Tesfaw, A., 2023. The current trends of bioethanol production from cheese whey using yeasts: Biological and economical perspectives. Front. Energy Res., 11: 1183035. https://doi.org/10.3389/fenrg.2023.1183035

Valenzuela, J.A., Vázquez, L., Rodríguez, J., Flórez, A.B., Vasek, O.M. and Mayo, B., 2024. Phenotypic, technological, safety, and genomic profiles of gamma-aminobutyric acid-producing Lactococcus lactis and Streptococcus thermophilus strains isolated from cow’s milk. Int. J. Mol. Sci., 25(4): 2328. https://doi.org/10.3390/ijms25042328

Vinderola, C.G. and Reinheimer, J.A., 2003. Lactic acid starter and probiotic bacteria, a comparative in vitro study of probiotic characteristics and biological barrier resistance. J. Food Res. Int., 36: 895–904. https://doi.org/10.1016/S0963-9969(03)00098-X

Vithalani, P., Mahla, P., Padhiar, J., Bhanushali, U. and Bhatt, N., 2024. Microbial inventions and improvement in industrial bioprocess development. In: Industrial microbiology and biotechnology: A new horizon of the microbial world. Singapore: Springer Nature Singapore. pp. 551-572. https://doi.org/10.1007/978-981-97-6270-5_18

Wahab, W.A.A., Saleh, S.A., Elzairy, N.H., Ahmed, S.A., Zaki, E.R., Salama, W.H. and Mostafa, F.A., 2024. Aspergillus foetidus as a potent producer for β-galactosidase utilizing lemon peels and coffee waste powder: Production optimization, purification, kinetic and thermodynamic characterization. Microb. Cell Fact., 23(1): 330. https://doi.org/10.1186/s12934-024-02600-0

Waiel, F.S., Wesam, M.S., Zeinab, A.S. and Abdelmoneim, K.A., 2020. Production of lactic acid from whey permeate using lactic acid bacteria isolated from cheese. Int. J. Vet. Sci., 3(2): 78-95. https://doi.org/10.21608/svu.2020.35000.1064

Wang, C.L., Li, D.F., Wang, W.Q. and Lai, C.H., 2004. Influence of cultivation conditions on the β-galactosidase biosynthesis from a novel strain of Penicillium sp. in solid-state fermentation. Letters in Applied Microbiology, 39: 369–375. https://doi.org/10.1111/j.1472-765X.2004.01594.x

Yglesias-Rivera, A., Viera-Morales, A.Z., Suárez-Pérez, Y., Torres-Viltres, J.R. and Ochoa-Cardentey, R., 2020. Validation of modified lowry for the determination of total protein concentration of Rhopalurus junceus scorpion venom. Biomed. J. Sci. Tech. Res., 28(3): 21627-21632. https://doi.org/10.26717/BJSTR.2020.28.004655

Yi, Z., Xu, M., Hong, W., Zhang, Z., Yao, X., Zhou, Z. and Han, Y., 2025. Comparative genomics of transporter proteins in lactic acid bacteria. Processes, 13(4): 1204. https://doi.org/10.3390/pr13041204

Zuhri, A.R. and Wilda, S., 2024. An overview of lactase enzyme: Microbial sources, substrate range, fermentation approaches, extraction techniques, and industrial applications. J. Integr. Environ. Sci., 1(1): 1-9. https://ejournal.unsika.ac.id/index.php/JoINS