Introduction

Cheese is one of the most widely consumed dairy products worldwide, available in diverse varieties differing in morphology, texture, and sensory properties1,2. Among these, Iranian white cheese, commonly known as breakfast cheese, holds a prominent place in Iranian cuisine. It shares similarities in texture with Turkish white cheese and Feta; however, notable differences exist in its production process compared to Feta cheese3. Given its widespread consumption, Iranian white cheese presents considerable potential for development as a functional food. Incorporating probiotics and prebiotics into this cheese may offer promising benefits for enhancing public health4.

Probiotic dairy products, especially those formulated with fermented milk, are manufactured at large scales globally, owing to the greater compatibility of dairy matrices with probiotic microbes over other food carriers5. L. acidophilus is among the most widely used probiotics in the dairy industry. This well-established probiotic is commonly added to milk, yogurt, cheese, infant formula, and dietary supplements. Numerous studies have confirmed its safety and effectiveness, particularly in alleviating gastrointestinal disorders such as diarrhea. Moreover, the inclusion of prebiotics can further enhance the activity and health benefits of probiotic bacteria6,7.

Flaxseed (Linum usitatissimum L.) gum is a natural heteropolysaccharide extracted from the outer mucilaginous layer of flaxseeds, constituting about 8% of the seed weight. It contains neutral and acidic monosaccharides and shares properties with gums like guar, arabic, tragacanth, and carrageenan8,9,10. Known for its prebiotic effects and texture-modifying properties, flaxseed gum (FG) can stimulate probiotic bacterial growth and has been associated with health benefits including lowering blood cholesterol and triglycerides and improving gastrointestinal and cardiovascular conditions11. Incorporating FG into Iranian white cheese may enhance texture, support probiotic viability, and influence the expression of genes related to probiotic functions.

Gene expression is of critical importance in differentiation and functional characteristics of living organisms. In foods, an analysis of gene expression offers valuable information on microbial physiology, particular functionality, and association with sensory and structural food properties12,13. Investigating the expression of probiotic genes can facilitate the development of functional dairy products and establish links between bacterial growth and health-promoting attributes14.

This project discusses prominent genes that occur in probiotics, which include Aspartate kinase, SOS response-related peptidase, ROK family protein, and LytR-CpsA-Psr (LCP). Aspartate kinase enables the initial step in biosynthesis of fundamental amino acids (lysine, threonine, isoleucine, and methionine). Control of its activity by a feedback inhibition pathway through lysine promotes a balance production of amino acids15,16,17,18. The SOS response pathway, which is induced by DNA damage, is also significant in repairing DNA, cell cycle regulation, and genome stability. It enhances the viability of probiotic bacteria like L. acidophilus, thus their probiotic characteristics19,20,21.

The ROK family of proteins functions as repressors and kinases, effectively suppressing pathogenic bacteria such as Escherichia coli, other species of Staphylococcus, and Haemophilus influenzae. Such microorganisms are commonly associated with gastrointestinal symptoms and opportunistic infections, particularly among those who have weakened immune systems and in children22,23,24,25,26. Meanwhile, LCP proteins assist in ensuring the integrity of bacterial cell walls during stressful environments, including beta-lactam antibiotic resistance, thereby enhancing the viability and survival of probiotics27,28.

Although other genes such as those related to adhesion to intestinal epithelial cells, bile salt tolerance, or acid resistance are also important for defining probiotic functionality and could provide valuable insights into bacterial persistence within the gastrointestinal tract, our study prioritized genes representing the three fundamental domains of metabolism, structural integrity, and stress response. These genes not only contribute to the survival of microorganisms under the adverse conditions of the cheese matrix but also play a direct role in enhancing metabolic activity, maintaining cell wall stability, and supporting adaptation to environmental fluctuations. Therefore, their analysis offers a more integrated and comprehensive view of L. acidophilus adaptation and performance during cheese ripening, while simultaneously providing a mechanistic basis for understanding the interaction between prebiotics and the molecular responses of probiotics in dairy products. This approach, in addition to the novelty of the selected targets, lays the foundation for future studies on other functional genes related to host–microbe interactions and gastrointestinal persistence.

The objective of this study was to elucidate the effects of FG supplementation at 2.5% and 5% concentrations on the expression of key functional genes involved in stress response, metabolism, and cell wall integrity of L. acidophilus in Iranian white cheese. Furthermore, the research aimed to assess how FG influences probiotic viability, sensory attributes, textural properties, and microstructural characteristics throughout cheese ripening. By integrating molecular gene expression analysis with physicochemical and sensory evaluations, this study seeks to provide comprehensive insights into the role of FG in enhancing probiotic stability and improving the overall quality of synbiotic dairy products, thereby contributing to the development of functional foods with optimized health benefits and consumer acceptance.

Materials and methods

Materials

Standard milk with 1.5% fat content was obtained from a local dairy factory for cheese production. Flaxseed was sourced from the Kermanshah Agricultural Research Center. The probiotic strain L. acidophilus (ATCC 53544) was provided by the Research Organization for Science and Technology of Iran (Center for Industrial Microorganisms Collection). Other chemicals and reagents used in this study including trisodium citrate, Tris buffer, EDTA, calcium chloride, DEPC, D-sorbitol, nalidixic acid, neomycin sulfate, lithium chloride, paramomycin, propidium monoazide (PMA), phosphate-buffered saline tablets (Sigma-Aldrich, USA), agarose, boric acid, MRS agar medium, peptone water, gas packs (Merck, Germany), cheese starter culture includes Lactococcus lactis and Lactococcus cremoris (Chr. Hansen, Denmark), nucleic acid extraction kits (Kiagene, Iran), loading buffer, DNA ladders, Safe Stain, primers (Sinnaclone, Iran), SYBR Green Master Mix/Rox kit, and DNase I enzyme (Ampliqon, Denmark) were purchased from standard commercial suppliers.

Flaxseed gum extraction

FG was extracted by soaking 500 g of flaxseeds in 4 L of distilled water at 85–90 °C and with continuous stirring for 24 h. The optimal pH for extraction was 5.6 to 7. The mucilage was separated from the seeds using a mesh cloth with medium-sized pores. The collected mucilage was then centrifuged at 2700 rpm for 25 min at 0 °C to remove insoluble particles. Subsequently, the supernatant was precipitated by adding 100% ethanol, followed by centrifugation at 3000 rpm for 25 min at 0 °C to isolate the polysaccharide. The precipitated FG was washed with distilled water and stored at − 20 °C until further use29,30,31.

Bacterial activation

A 100 µL aliquot of L. acidophilus suspension was inoculated into 10 mL of MRS broth and incubated at 37 °C for 18 h. The subculturing was repeated two to three times in fresh MRS broth until the bacterial population reached approximately 108–109 CFU/mL. Cells in the logarithmic growth phase were then harvested by centrifugation at 3000 rpm for 5 min at 4 °C, followed by two successive washes with 0.1% peptone water to ensure purification32.

Cheese production

Laboratory-scale cheese samples were produced using a Manizan dairy factory pilot system. Initially, the microbial and physicochemical properties (pH, fat content, protein content, total solids, titratable acidity, ash content, freezing point, and density) of the raw milk were evaluated before transferring 4 L into the equipment. The fat content was adjusted to 1.5%, and essential additives for cheese production, including calcium chloride (0.02 g/L) and FG (at specified concentrations), were incorporated into the milk33. The milk was then pasteurized and cooled to 35 °C. Subsequently, 0.04 g/100 mL of a starter culture (Lactococcus lactis and Lactococcus cremoris) and 1 mL of a L. acidophilus probiotic suspension were added. The mixture was incubated at 35 °C for 55 min to allow bacterial growth. The curds were cut into 1 cm cubes and left for 10 min to allow whey drainage. After that, they were gently stirred for 10 min to improve whey expulsion, and then pressed for 2.5 h to remove excess moisture34,35. The cheese was cut into pieces measuring 6 × 6 × 4 cm and soaked in 20% brine for 8 h. It was then transferred to 8% brine, vacuum-sealed in pasteurized bags, and underwent a 15-day ripening period at 22 °C, known as the early (green) storage phase. After ripening, the cheese was stored at 4 °C for 60 days until it was ready to be consumed36,37.

To enable accurate comparison of parameters, three types of cheese were produced: (1) control cheese containing only the starter culture, (2) probiotic cheese with starter and L. acidophilus (PSL), and (3) synbiotic cheese with starter, L. acidophilus, and FG at concentrations of 2.5% (SSL-FG 2.5%) and 5% (SSL-FG 5%).

Gene expression of L. acidophilus

The molecular response of L. acidophilus to the addition of FG in Iranian white cheese was analyzed by assessing the expression of Aspartate kinase, SOS response-associated peptidase, ROK family, and LCP (LytR-CpsA-Psr) genes. Gene expression was evaluated at two time points: the end of the green storage period (The 15th day) and market entry (The 60th day).

To ensure RNA integrity and prevent degradation, all tools needed for RNA extraction were sterilized to inhibit Rnases38. For total RNA extraction, 2 g of cheese sample was homogenized with 8 mL of a 2% (w/v) trisodium citrate solution, followed by centrifugation (4 °C/6000 rpm/5 min). The supernatant was discarded, and RNA extraction continued using the RNA kit39. The quantity, and concentration of RNA were determined by NanoDrop device (model 2000 C, Thermo Fisher Scientific, USA). The quality of the total RNA extracted was then verified through 1% agarose gel electrophoresis39,40.

To eliminate any genomic DNA contamination from the RNA samples, all RNA samples were treated with a DNase kit. Subsequently, cDNA synthesis was conducted using a Reverse Transcription Kit. The necessary components were added to the appropriate tube from the cDNA synthesis kit and incubated at 55 °C for 60 min. The samples were then incubated at 95 °C for 5 min in a water bath, followed by cooling on ice and storing at − 80 °C40,41. Real-time PCR was performed using a SYBR Green master mix/Rox kit. To evaluate the efficiency of each primer pair, a mix of all treatments and replicates of the synthesized cDNA was prepared. Various dilution factors were tested for each primer pair. After determining the optimal concentration of primer and cDNA, gene expression was assessed using Real-time PCR (StepOne, Applied Biosystems, USA)41,42.

For each sample, individual reaction volumes were prepared in separate wells of the MicroAmp Fast Optical 48-Well Reaction Plate, and PCR was performed under the following conditions: (1) Predenaturation: 95 °C for 5 min, (2) PCR reaction: 95 °C for 30 s, 60 °C for 30 s, 72 °C for 30 s for 40 cycles, 3), final extension 72 °C for 5 min, 4) melting curve analysis: 95 °C for 15 s, 60 °C for 1 min, 95 °C for 15 s (0.5 °C), followed by cooling to 4 °C43,44.

In this study, Rec A gene was used as the reference45. Primer design was performed using Oligo7 and Primer3 software, followed by validation with Primer-BLAST for final confirmation. The targeted genes and primer characteristics are presented in Table 1. Relative gene expression levels were calculated using the 2^−ΔΔCT method, utilizing the melting temperatures determined for each primer46.

Viability assays of L. acidophilus

Plate count

The viability of L. acidophilus probiotic bacteria in each cheese sample was assessed at different ripening stages (days 0, 15, 30, and 60)47. For this purpose, 10 g of homogenized cheese was suspended in 90 mL of peptone water and then serially diluted down to 10−9. 1 ml from each dilution was plated on MRS agar using the pour plate technique48. The plates were incubated under anaerobic conditions at 37 °C for 72 h, after which bacterial colonies were counted to determine viability49. To selectively promote the growth of L. acidophilus, D-sorbitol (10 mL of a 10% solution per 90 mL of MRS agar) was added to the medium50,51.

PMA-real-time PCR

To quantify L. acidophilus using Real-Time PCR, the bacteria were initially cultured in MRS medium and incubated at 37 °C for 24 h. This process was repeated three times to ensure optimal bacterial growth52. Subsequently, serial dilutions (V1–V12) of the original culture were prepared. Cheese samples (5 g) were homogenized in 45 mL of phosphate buffer and centrifuged at 6000 rpm for 10 min. The supernatant was discarded, and the pellet was resuspended in ultrapure water53.

A 20 mM PMA stock solution (1 mg PMA in 20% dimethyl sulfoxide) was prepared and stored at − 20 °C. PMA was added to the bacterial dilutions and homogenized cheese samples to a final concentration of 50 µM. Samples were incubated in the dark for 5 min, followed by exposure to halogen light (500 W) for 15 min to cross-link free DNA. Afterward, samples were centrifuged and subjected to DNA extraction54.

DNA extraction was performed using a commercial kit following the manufacturer’s protocol55. Briefly, 180 µL of lysing enzyme buffer was added to the bacterial pellet, followed by 20 µL of proteinase K, and incubated at 56 °C for 30 min. An additional 200 µL of lysing enzyme buffer was then added before proceeding with DNA precipitation and washing steps. Finally, the DNA was recovered by transferring the mixture to a sterile tube and centrifuging at 6000 rpm for one minute. Real-Time PCR amplification was carried out as previously described, using 16 S rRNA as the target gene for bacterial quantification and RecA as the reference gene (Table 1). The total reaction volume was 20 µL, and cycle threshold (CT) values were determined in triplicate using the SYBR Green master mix/Rox kit. A standard curve was generated based on CT values from serial dilutions, enabling quantification of L. acidophilus at days 0, 15, 30, and 60 of cheese ripening.

Table 1 Characteristics of primers designed for L. acidophilus (ATCC 53544).
Full size table

Final evaluation for entering the consumer market

Sensory properties

Sensory evaluation of the cheese samples was conducted in the Quality Control Laboratory of the Faculty of Nutrition Sciences and Food Industries using a five-point hedonic scale ranging from “very good” to “very poor.” Fifteen trained panelists, aged 18 to 50 years old and regular consumers of dairy products, participated in the study. The assessment took place at the end of the ripening period (day 60), focusing on flavor, texture, color, and overall acceptability56. Prior to evaluation, panelists received training on the sensory testing protocol. Each participant was provided with a coded checklist and 30 g of each cheese sample, served in white containers with randomized order. The evaluations were carried out under controlled lighting and room temperature to ensure consistency. To prevent sensory fatigue and cross-sample contamination, panelists rinsed their mouths with water between samples. The acceptance scores were analyzed to identify the most preferred cheese formulations57,58.

Texture properties

Texture analysis was conducted on cheese samples at the conclusion of the 60-day ripening period. Each sample was cut into 2 × 2 × 2 cm cubes and evaluated for essential textural characteristics, such as adhesiveness, cohesiveness, stringiness, and chewiness. Before testing, the samples were allowed to stabilize at 25 °C for 30 min. The assessment was carried out using a TX-700 N texture analyzer from Lamy, France, with an aluminum probe that compressed the samples at a controlled rate until they reached 50% deformation of their diameter. To ensure accuracy, each measurement was repeated three times per sample47,59.

Scanning electron microscopy (SEM)

To evaluate the morphological characteristics of cheese samples at the end of the ripening period (day 60), each sample was sliced into approximately 0.5 cm pieces and fixed in 2.5% (w/v) glutaraldehyde solution for 3 h. After fixation, samples were rinsed with distilled water and dehydrated through a graded ethanol series (40%, 55%, 70%, 85%, 90%, and 96%), with each step lasting 30 min. Subsequently, lipid extraction was performed by immersing the samples in chloroform three times for 10 min each. The processed samples were then stored in ethanol at 4 °C until further analysis. Prior to scanning electron microscopy (SEM), cheese fragments were rapidly frozen using liquid nitrogen and fractured into smaller pieces (~ 1 mm). Finally, samples were mounted on aluminum stubs and observed under SEM (EVO 40, Carl Zeiss, Germany) at various magnifications to examine their microstructural features60,61.

Statistical analysis

Gene expression data were analyzed using a two-way factorial ANOVA within a completely randomized design, considering two independent factors: cheese type and time. The assumptions of ANOVA (normality and homogeneity of variances) were verified using the Shapiro Wilk and Levene’s tests, respectively. Mean comparisons were subsequently performed using Duncan’s multiple range test at a significance level of 1%. Sensory evaluation, texture, and structural features data were analyzed using a one-way factorial ANOVA within a completely randomized design (P ≤ 0.01), with the same assumption checks and Duncan’s post hoc test. Graphical visualizations were performed using GraphPad Prism 8 and XLSTAT. For integrated analysis of sensory and textural attributes, two-way cluster analysis was applied to classify samples and traits, simultaneously producing heatmap visualizations. This analysis was conducted using ClassVise software.

Results and discussion

Gene expression

In the present study, FG was incorporated into Iranian white cheese at concentrations of 2.5% and 5% to evaluate its modulatory effects on the expression of four functional genes in L. acidophilus: Aspartate kinase, SOS response-related peptidase, ROK family protein, and LytR-CpsA-Psr (LCP). These genes were selected based on their roles in amino acid biosynthesis, stress response, carbohydrate metabolism, and cell wall stability, which are critical for the survival and functionality of probiotic strains in food matrices. Gene expression levels were analyzed at two time points (days 15 and 60 of ripening), and the data obtained were subjected to analysis of variance.

The statistical analysis demonstrated that both the type of cheese and the ripening time had a highly significant effect on gene expression (p < 0.01), as did their interaction. The mean square values for the genes ranged from 8.70 to 12.59, with Aspartate kinase showing the highest variance, while ROK family protein had the lowest. Coefficient of variation (CV%) values were acceptably low (9.08–12.21), and residual error was minimal, indicating that the model was both reliable and statistically robust (Table 2).

Table 2 Variance analysis of gene expression during ripening time in cheeses produced.
Full size table

As shown in Fig. 1A, among the genes studied, Aspartate kinase exhibited the most notable upregulation, with fold-changes of 12.69 and 7.84 on day 15 in FG 5% and FG 2.5% samples, respectively. Although the expression decreased by day 60 (8.54 and 4.88, respectively), it remained significantly higher than in probiotic-only controls. This enzyme catalyzes the first step in lysine biosynthesis, which not only contributes to the metabolic activity of the bacteria but also potentially enhances the nutritional profile of the cheese. Similar trends have been observed in studies where Lactobacillus delbrueckii demonstrated upregulation of FolE in response to lactose as a prebiotic. This further confirms the connection between prebiotic compounds and amino acid biosynthesis62. The upregulation of such genes may also be indicative of greater metabolic vigor and microbial stability, contributing to improved probiotic viability throughout storage.

Similarly, the expression of the LytR-CpsA-Psr (LCP) gene, which plays a role in maintaining the structural integrity of bacterial cell walls, significantly increased under the influence of FG. On day 15, fold-change values were 17.63 and 9.59 for FG 5% and FG 2.5%, respectively. These values decreased to 10.49 and 6.34 by day 60 (Fig. 1B). The increased expression of this gene may help the bacterium resist acidic and osmotic stresses, potentially leading to improved tolerance to gastrointestinal conditions. Similar protective roles have been observed for S-layer associated genes like SlpX and SlpA in L. acidophilus when exposed to salt stress, as their heightened expression enhances structural resilience63. This implies that FG may act not only as a metabolic stimulant but also as a structural modulator that helps maintain probiotic integrity during ripening and after ingestion.

The ROK family protein gene, which plays roles in sugar metabolism and transcriptional regulation, also exhibited a significant increase in expression during early ripening. On day 15, fold-change values reached 11.54 (FG 5%) and 7.91 (FG 2.5%), reducing to 7.52 and 5.07 on day 60 (Fig. 1C). The early increase in expression suggests that FG provided fermentable substrates that activated carbohydrate-utilizing pathways, enhancing bacterial competitiveness. The functional benefits may extend beyond microbial metabolism; prior studies have associated ROK proteins with suppression of pathogens such as E. coli and S. aureus and the modulation of host immune responses25,26. In cheese, such effects are especially valuable in improving microbial safety and probiotic functionality during storage and gastrointestinal transit.

The SOS response-related peptidase gene, responsible for DNA repair and cellular resilience under stress, also responded positively to FG supplementation. Expression peaked on day 15, with fold-changes of 12.07 (FG 5%) and 7.98 (FG 2.5%), then declined to 9.68 and 5.48 by day 60 (Fig. 1D). This pattern aligns with the known temporal dynamics of stress-response genes, which are typically activated during early exposure to environmental challenges and decrease as microbial adaptation progresses. The enhanced expression of this gene suggests that FG may help preserve the genomic integrity of probiotics during cheese ripening and storage, thereby improving their industrial stability and long-term viability. Similar patterns have been noted in L. paracasei in brined cheeses, where expression of stress-related genes such as dnaK and groES shifted throughout the ripening period64.

The temporal trend observed across all genes elevated expression at day 15 followed by a reduction at day 60 may reflect a combination of metabolic adaptation, substrate depletion, and reduced bioavailability of FG components over time. This trend is consistent with findings from Noutsopoulos et al.65where the expression of the nisA gene declined with prolonged fermentation. Nonetheless, the sustained gene activity, particularly in the FG 5% group, suggests that the synbiotic matrix successfully supported probiotic function over the full ripening period.

When contextualized within existing literature, the findings of this study contribute novel insights into the molecular-level functionality of L. acidophilus in traditional dairy matrices. While previous research has explored probiotic gene expression in cheeses for purposes such as antifungal peptide production, flavor enhancement, or survival in harsh environments, the specific genes analyzed in the present study particularly Aspartate kinase, LCP, ROK, and SOS-peptidase have not been previously investigated in Iranian white cheese. The modulation of these genes by FG underscores its potential as a bioactive component in synbiotic formulations. In summary, FG positively influenced the expression of key functional genes in L. acidophilus, reflecting improved metabolic activity, stress resilience, and structural integrity of probiotic cells during cheese ripening. These molecular findings not only support the use of FG as a functional ingredient but also highlight its role in enhancing the probiotic quality and health-promoting potential of traditional dairy products.

Fig. 1
figure 1

Relative expression levels of the studied genes, normalized to the reference gene Rec A, in synbiotic (SSL-FG 5% and SSL-FG 2.5%) and probiotic (PSL) cheeses.

Full size image

Viability assays

Microbial enumeration in MRS medium (Fig. 2) revealed that at the initial time point (0th day), all cheese samples exhibited a high probiotic load of approximately 109 CFU/g, confirming the successful inoculation of L. acidophilus. However, a gradual decline in bacterial viability was observed during the ripening and storage periods. Notably, after 15 days of green storage, the probiotic count in the PSL (probiotic cheese without FG) sample sharply decreased to 107 CFU/g, whereas synbiotic cheeses supplemented with FG (SSL-FG 2.5% and SSL-FG 5%) maintained higher viability levels of 108 CFU/g. This trend persisted on day 30, with the PSL group further declining to 106 CFU/g, while FG enriched samples sustained counts at 107 CFU/g. At the conclusion of the 60-day ripening period, the SSL-FG 5% sample preserved the highest bacterial population (~ 107 CFU/g), outperforming both the PSL and SSL-FG 2.5% samples, which stabilized at 106 CFU/g. These findings suggest that FG, particularly at a 5% concentration, acts as an effective prebiotic substrate that enhances the stability and survival of probiotic bacteria during cheese maturation, potentially by protecting cells from environmental stresses and nutrient depletion. Similar protective effects of plant-derived gums on probiotic viability have been documented, as exemplified by Alhssan et al.66who reported increased survival and growth rates of L. acidophilus and Bifidobacterium lactis in kefir fortified with gum arabic and flaxseed mucilage.

Fig. 2
figure 2

Enumeration of L. acidophilus using the plate count on MRS agar.

Full size image

Complementing plate counts, quantitative PCR (qPCR) combined with propidium monoazide (PMA) treatment was employed to differentiate viable cells from dead bacteria, thus providing a more accurate viability assessment. The established standard curve (y = 1.1716x + 3.1302; R2 = 0.9899) enabled precise conversion of cycle threshold (CT) values into viable bacterial counts (Fig. 3). Consistent with culture-based methods, PMA-qPCR data revealed a significant decline in L. acidophilus viability over time in all samples (Table 3), with the synbiotic SSL-FG 5% group retaining the highest viable counts during ripening (2.09 × 108 CFU/g at day 15), reinforcing the notion of enhanced microbial stability via FG supplementation. These results are congruent with previous research employing PMA-qPCR for probiotic enumeration, such as García-Cayuela et al.53who validated the method’s specificity and reliability in fermented milk, and Desfossés-Foucault et al.67who documented similar viability patterns for Lactobacillus strains during cheddar cheese maturation.

The advantage of PMA-qPCR lies in its reduced time and higher sensitivity compared to conventional plate counting, while maintaining comparable accuracy, as demonstrated by Scariot et al.54. This molecular technique has also been effectively utilized for quantifying probiotic and pathogenic bacteria in diverse food matrices68,69. For instance, Do, Lao, and Le70 successfully applied PMA-qPCR to enumerate pathogenic bacteria in dairy products, highlighting its utility for live cell detection in complex microbiological assessments.

Overall, the integration of FG as a prebiotic ingredient in Iranian white cheese clearly contributed to the enhanced survival and persistence of L. acidophilus, suggesting promising implications for extending the functional shelf life and health benefits of synbiotic dairy products.

Fig. 3
figure 3

Standard curve obtained from dilution of extracted L. acidophilus DNA using the PMA-Real-time PCR method.

Full size image
Table 3 Enumeration of viable (cfu/g) L. acidophilus cells in probiotic and synbiotic cheeses using the PMA method.
Full size table

Sensory properties

Appropriate sensory characteristics are crucial for the successful market acceptance of food products. Even nutritionally valuable items may fail commercially if they do not meet consumer preferences71. In this study, sensory evaluation of Iranian white cheese supplemented with FG at 2.5% and 5% concentrations (SSL-FG 2.5% and SSL-FG 5%) was performed using a five-point hedonic scale, assessing attributes including taste, texture, color, and overall acceptance. The results, visualized through a heat map (Fig. 4), demonstrated that the control cheese (without probiotic or FG) generally scored highest across sensory parameters, with scores of 4.50 for taste, 4.31 for texture, 4.81 for color, and 4.56 for overall acceptance. Among treated samples, the probiotic cheese without FG (PSL) received the lowest ratings, particularly in taste (3.31) and texture (3.25), contributing to a reduced overall acceptance score (3.88). Incorporation of FG at 2.5% slightly diminished some sensory attributes, notably color and overall acceptance, compared to the control. However, increasing the FG concentration to 5% ameliorated these effects, resulting in the highest color score (4.88) among all samples and an overall acceptance score (4.19) approaching that of the control. This indicates that higher levels of FG may help alleviate some sensory issues related to probiotic addition and enhance product appeal.

These findings align with those of Habibi and Jooyandeh36who reported that Persian gum enhanced sensory properties and increased general acceptance in Iranian white cheese, underscoring the potential of plant-derived gums to improve product quality. Conversely, studies involving Lepidium perfoliatum seed gum and FG as fat replacers in cream cheese revealed a general decline in sensory attributes over storage, including color and odor, with scores lower than those of high-fat controls72. Similarly, the addition of basil seed and xanthan gums was associated with reduced sensory scores compared to controls73. However, evidence also exists supporting the beneficial effects of FG on sensory quality, as demonstrated by Akl et al.74who reported improved sensory attributes in dairy products supplemented with FG. Taken together, these results highlight the complex interactions between prebiotic polysaccharides and sensory characteristics, which may vary depending on gum type, concentration, and product matrix, emphasizing the need for optimization to balance functional benefits with consumer acceptability.

Fig. 4
figure 4

Comparison of sensory evaluation of cheeses prepared with FG and L. acidophilus using heat map analysis.

Full size image

Texture properties

FG is not only known for its health benefits and nutritional value, but also for its gelling properties that help improve the texture of various food products, such as dairy items and cheeses. This functional polysaccharide enhances viscosity, primarily due to its arabinoxylan content, which consists of neutral, high molecular weight polysaccharides11. In the present study, variance analysis (Table 4) revealed significant effects (p < 0.01) of FG addition on key textural parameters of synbiotic Iranian white cheese. These parameters include springiness (mean square: 0.56 mm), cohesiveness (0.0043 N), and chewiness (21.393 mJ). Adhesion, however, showed no significant difference (0.0001 N.m), indicating random variation unaffected by treatments. Multi-domain mean comparisons showed that the probiotic cheese sample without FG (PSL) was different from the other groups. It had the highest adhesion (0.1029 N.m), although this difference was not statistically significant. In comparison, the commercial market sample (CMS) and the control group had the lowest adhesion values (0.0872 and 0.0871 N.m, respectively). Springiness of SSL-FG 5% (3.6333 mm) closely resembled control (3.7666 mm) and CMS (3.6333 mm) samples (p < 0.01). Cohesiveness was significantly higher in PSL (0.2501 N) than in SSL-FG 2.5% (0.1910 N), SSL-FG 5% (0.1930 N), control (0.1967 N), and CMS (0.1940 N) (p < 0.01). Likewise, chewiness values placed PSL (5.0275 mJ) as furthest from control (4.5666 mJ) and CMS (4.5451 mJ), while SSL-FG 5% (4.5167 mJ) and SSL-FG 2.5% (4.4667 mJ) were closest, indicating that FG addition preserves desirable textural properties. These findings support the use of FG for formulation optimization aiming to enhance cheese texture. Similar results were reported by Akl et al.74who found that FG, as a fat replacer in probiotic cream cheese, increased viscosity and synergistically improved sensory attributes, making it a suitable alternative for consumers restricting fat intake. Likewise, Bazezew et al.75 successfully employed Ximenia americana seed gum as a fat substitute in cheddar cheese without compromising texture or flavor. However, gum addition does not universally enhance texture; for example, Hesarinejad et al.76 demonstrated that gelatin and guar gum had no significant impact on ricotta cheese texture.

To comprehensively analyze the relationship between sensory and textural attributes, cluster analysis was performed, a statistical technique frequently utilized in dairy product characterization to group samples based on similarities across multiple attributes77. The cluster analysis results (Fig. 5) indicated that SSL-FG 2.5% and SSL-FG 5% samples clustered closely, reflecting high similarity in texture and color. SSL-FG 5% exhibiting notably higher scores, including general acceptance. The control sample joined this cluster but exhibited distinct differences, particularly in adhesiveness and taste, highlighting subtle yet important sensory-textural divergences. The PSL sample appeared as the most distant member, underscoring its significant divergence in these characteristics. The analysis further classified measured traits into two principal groups: the first comprising adhesiveness, cohesiveness, texture, and color, likely linked through molecular interactions within the cheese matrix, and the second including springiness, chewiness, taste, and general acceptance, reflecting the interplay between textural and sensory perception. This grouping suggests that FG addition contributes to a balanced enhancement of mechanical and sensory properties, ultimately improving consumer acceptance. Such applications of cluster analysis align with prior studies, such as de la Haba Ruiz et al.78who employed this method to group cheeses by physicochemical characteristics, and Bittante et al.79who used cluster and factor analyses on 1050 cheese varieties to reveal latent structures and facilitate classification based on multidimensional properties. Overall, these results emphasize cluster analysis as a powerful tool for elucidating complex relationships in food matrices and support the beneficial role of FG in improving the texture and sensory appeal of synbiotic Iranian white cheese.

Table 4 Variance analysis of textural characteristics of produced probiotic and synbiotic cheeses.
Full size table
Fig. 5
figure 5

Cluster analysis for grouping produced cheeses and sensory-textural characteristics.

Full size image

Structural characterization

The microstructural characteristics of control, PSL, SSL-FG 2.5%, and SSL-FG 5% cheese samples were investigated using scanning electron microscopy (SEM), revealing notable differences aligned with textural assessments. As illustrated in Fig. 6A–D, the control cheese exhibited a denser and more compact matrix structure, whereas the PSL sample demonstrated a significantly reduced matrix density, resulting in a looser and more porous structure. This observation corroborates the texture analysis, where PSL deviated most from the control. The incorporation of FG notably enhanced matrix cohesion, likely due to its role as an active filler that disperses within the cheese matrix similarly to fat, disrupting casein bonds and creating a cream cheese-like texture with improved mouthfeel72. These findings align with Shahraki et al.72who reported similar microstructural improvements in low-fat probiotic cream cheese upon FG addition. Furthermore, Habibi and Jooyandeh80 demonstrated that Persian gum enhanced the texture of Iranian white cheese by promoting a more dispersed matrix structure, attributed to increased hydration capacity and consequent reduced compactness, consistent with our results.

Fig. 6
figure 6

Microstructure of the cheese samples produced using SEM: Control (A), PSL (B), SSL-FG 2.5% (C), and SSL-FG 5% (D).

Full size image

Quantitative image analysis of cheese porosity, surface roughness, and fat globule diameter was conducted using ImageJ software (Fig. 7A–C), providing detailed microstructural metrics. The PSL sample exhibited significantly increased porosity both in size (µm) and percentage, exceeding that of the control, while FG supplementation reduced porosity closer to control levels; specifically, SSL-FG 2.5% and SSL-FG 5% samples showed porosity percentages of 9% and 7%, and pore sizes of 15 μm and 10 μm, respectively. Surface roughness measurements followed a similar trend, with PSL exhibiting the highest roughness diameter (2.25 μm), decreasing progressively with higher gum content 1.75 μm in control, 1.65 μm in SSL-FG 2.5%, and 1.25 μm in SSL-FG 5%. Fat globule diameter decreased from 18 μm in the control to 16 μm (PSL), 14 μm (SSL-FG 2.5%), and 10 μm (SSL-FG 5%). This reduction is attributed to the emulsifying properties of FG, which increases the viscosity of the aqueous phase and interacts with the protein network, forming a protective layer around fat globules that prevents coalescence and restricts their movement, thereby resulting in finer fat dispersion within the cheese matrix81.

The application of ImageJ for microscopic image analysis offers a robust, non-destructive quantitative method to evaluate cheese microstructure, including porosity, fat particle distribution, and protein network uniformity. This tool has been widely used across various cheese types to elucidate the impact of processing variables on texture and quality82,83. For instance, Wu et al.84 utilized ImageJ to assess porosity changes in cream cheese induced by calcium reduction, demonstrating a correlation between decreased porosity and softer cheese texture. These insights reinforce the utility of microstructural analysis in optimizing cheese formulation and highlight the beneficial role of FG in improving synbiotic Iranian white cheese by modulating its microstructure and consequently its sensory and textural properties.

Fig. 7
figure 7

Structural characteristics of the cheeses sample produced: porosity (A), roughness (B), and fat (C) diameter.

Full size image

Conclusion

The production of synbiotic Iranian white cheese offers a valuable opportunity to improve consumer health through the daily intake of functional dairy products. This study demonstrated that incorporating of FG at 2.5% and especially 5% may significantly enhanced the expression of critical functional genes (Aspartate kinase, SOS response-related peptidase, ROK family protein, and LytR-CpsA-Psr) in L. acidophilus. This upregulation was closely associated with improved probiotic viability, metabolic activity, and microbial stability throughout the ripening period, particularly peaking at day 15 and gradually declining by day 60. These molecular changes translated into enhanced cheese texture, as evidenced by improved cohesiveness, springiness, and chewiness, as well as favorable microstructural modifications such as decreased porosity and fat globule size, which collectively contributed to a more stable and appealing product. Sensory evaluation further confirmed that the addition of FG positively influenced consumer acceptance, balancing functional benefits with desirable organoleptic properties. The application of PMA-qPCR for microbial quantification validated the superior survival of probiotic bacteria in FG -enriched samples, underscoring its protective role during storage. Notwithstanding the important contributions of this research, a number of limitations should be noted. The study was only undertaken in one strain of L. acidophilus because the study was originally designed to assess the initial impacts of FG and the nature of the nutritive components on gene expression and ccharacteristics of the cheese produced. While observations made may relate to other strains, testing several would require significant time and resources. In the sensory evaluation, a small panel with a 5-point scale was adopted due to limited access to consumers and study design practicality, which reduces the opportunity for consumer preference data granularity. Additionally, the mechanistic effect of FG on gene expression has yet to be fully revealed, and broader molecular studies, such as transcriptomic profiling, should be considered for further investigation.

Scaling such approaches could enhance the commercial viability of functional cheeses. This would contribute to public health promotion by delivering dairy products with prolonged shelf life, enhanced nutritional value, and improved sensory quality. Therefore, FG presents a promising natural ingredient for the design of next-generation synbiotic dairy products with significant health and economic benefits.