Lactococcus lactis enhances the flavor of fermented milk by producing 4-hydroxy-2-butanone

Lactococcus lactis enhances the flavor of fermented milk by producing 4-hydroxy-2-butanone | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Lactococcus lactis enhances the flavor of fermented milk by producing 4-hydroxy-2-butanone Chuan Zhang, Haiyang Shi, Fengwei Tian, Xiaomei Lyu, Gang Wang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8656461/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The fermentation of dairy products is a complex biotransformation process, with flavor characteristics linked to the metabolic activities of specific strains, highlighting the necessity of identifying unique strains to enhance product quality. Here, 50 Lactococcus lactis ( L. lactis ) strains were isolated from traditional dairy products collected from four major pastoral regions in China, namely Xinjiang, Yunnan, Inner Mongolia, and Tibet. Based on the physiological characteristic indices of the strains, combined with the TOPSIS-entropy weight method, NZZ1 and RB12 with excellent fermentation performance were screened out. Among these, strain NZZ1 was identified as a significant producer of 4-hydroxy-2-butanone, the key volatile compound with the highest variable importance in projection, due to its complete coding genes for acetolactate synthase and acetolactate decarboxylase, enabling the biosynthesis of this compound. Comparative analysis with commercial starter cultures demonstrated that NZZ1 exhibits a shorter milk coagulation time (6 h), a faster fermentation rate (8 h), strong water holding capacity, and no excessive post-acidification (90.16 °T), along with outstanding sensory preference scores. Furthermore, co-fermentation with commercial starters significantly increased the yield of 4-hydroxy-2-butanone by more than threefold. These findings highlight the potential of NZZ1 as a distinctive starter culture, offering innovative strategies for enhancing dairy product quality. Biological sciences/Biochemistry Biological sciences/Biotechnology Biological sciences/Microbiology Starter cultures Lactococcus lactis Flavor 4-hydroxy-2-butanone Fermented milk Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Fermented dairy products have long been an integral part of the daily diet for people worldwide, serving as an excellent source of nutrients and beneficial microorganisms in modern life 1 , 2 . The unique flavors of these products not only enhance the dining experience but also significantly influence consumer choices 3 – 5 . However, the enhancement of fermented dairy product flavors currently relies primarily on the addition of natural flavorings and flavor enhancers 6 . Research on enhancing the flavor of fermented dairy from a strain perspective is scarce and time-consuming, facing challenges such as a broad selection scope and numerous interfering factors 3 , 7 . As the public places greater emphasis on healthy eating and the concept of “no-additive” foods 8 . Developing fermentation strains with superior flavor profiles not only reduces reliance on flavorings and enhancers while lowering production costs, but also enhances the sensory qualities of dairy products and ensures their quality, thereby promoting sustainable food production 3 , 7 . Naturally fermented dairy products are produced through the interaction between the microbial flora of raw dairy and indigenous microorganisms in the environment 3 . To accelerate fermentation, inoculation technology was ultimately adopted, which involves using a small amount of the previous fermentation liquid as the “starter culture” for the next stage 9 . This process employs natural selection to identify highly adaptable and productive microorganisms, thereby shortening fermentation time and enhancing fermentation quality, providing a robust system for the selection and breeding of superior strains for fermented dairy products 9 , 10 . Traditional dairy fermentation primarily relies on a mixed culture of Streptococcus thermophilus and Lactobacillus bulgaricus 11 . During fermentation, these two strains metabolize lactose to produce lactic acid 12 . Lactobacillus bulgaricus , as a classic strain, rapidly lowers the pH of the fermentation system through its potent acid-producing capacity. This not only suppresses the growth of unwanted microorganisms and extends product shelf life, but also imparts the characteristic sweet-and-sour flavor profile to fermented dairy 13 . The combination of these classic strains forms the foundation of traditional fermented dairy's quality. Nevertheless, as consumer demand for diverse flavors rises, the traditional single-strain combination struggles to meet the market's pursuit of distinctive flavors. Lactococcus lactis is a commonly used starter culture in fermented dairy products. Unlike strains focused on acid production or probiotic functions, the core value of Lactococcus lactis lies in its precise shaping of fermented dairy flavor, making it highly valuable for application 14 . Specifically, it demonstrates outstanding application performance in the production of dairy products such as cheese and fermented dairy 14 , 15 . Research indicates that Lactococcus lactis can express α-keto acid decarboxylase and α-keto acid dehydrogenase to promote amino acid conversion into flavor compounds 16 , 17 . During cheese fermentation, it significantly increases the content of 3-methylbutanal, enhancing the product's buttery flavor 17 . Therefore, this study aims to screen and identify superior Lactococcus lactis strains to enhance the flavor characteristics of fermented dairy products. Using Xinjiang milk curd and milk residue, Yunnan milk cake and milk fan, Inner Mongolia milk lump, and Tibet qula as research samples, Lactococcus lactis strains were isolated and purified. By measuring the strains' generation time characteristics, acid production rate, and β-galactosidase activity, combined with the TOPSIS entropy weight evaluation model, strains with excellent comprehensive fermentation performance were selected. Furthermore, solid-phase microextraction (SPME) was employed to characterize volatile compounds produced by superior strains in fermented dairy. Integrating whole-genome information with annotation from eggNOG, KEGG and CAZymes databases, specific flavor-compound biosynthetic pathways were elucidated to identify strains capable of synthesizing target flavor compounds. Differences in texture, water-holding capacity, acidity (titratable acidity, pH), and flavor were compared between commercially available composite starter cultures ( Lactobacillus bulgaricus + Streptococcus thermophilus ) and fermented dairy products. This clarified the application potential of superior strains and explored the impact of mixed fermentation on flavor compound changes. Result Screening of L. lactis and determination of fermentation characteristics L. lactis strains were isolated and purified using MRS medium from samples including Xinjiang milk tofu and milk resdue, Yunnan milk cake and milk fan, Inner Mongolia milk curd, and Tibet qula. A total of 50 target L. lactis strains were obtained through identification by 16S rRNA gene sequencing ( Fig. 1 A ). Notably, there was a significant variation in the capacity of different producing areas to yield L. lactis . The highest number of L. lactis strains were isolated from Tibet qula and Yunnan milk cake, with 15 and 17 strains respectively, while Xinjiang nazhaizi yielded the fewest, only 3 strains ( Fig. 1 B ). Furthermore, the generation times of the 50 L. lactis strains were determined, revealing obvious differences among strains with an average generation time of 3.76 hours ( Fig. 1 C ). Among them, strains such as RB8, NDF1, and RB16 exhibited generation times much lower than the average, indicating extremely rapid growth rates. In contrast, a small number of strains (e.g., NDF2) had generation times approaching 13 hours, which were significantly higher than the average. Analysis of acid production rates showed significant differences among the 50 L. lactis strains. High acid-producing strains were mainly derived from samples of Xinjiang, Inner Mongolia, and Tibet, while strains from Yunnan samples generally exhibited low acid production rates. Specifically, the average acid production rates of NDF3, NDF5, NGD2, NZZ6, and NZZ1 were all above 0.36, with the highest reaching 0.418 ( Fig. 1 D ). Determination of β-galactosidase activity indicated that among the top 10 strains with the highest enzyme activity (marked with yellow stars), 6 strains were isolated from Yunnan milk cake and milk fan, and 2 from Inner Mongolia milk curd. RB12 and NZZ1 showed the highest enzyme activities, at 991.51 U and 1108.83 U respectively. In contrast, L. lactis strains from Tibet and Xinjiang generally had low enzyme activities, most of which were below 200 U ( Fig. 1 E ). Construction and Result Evaluation of Lactic Acid Bacteria Screening System Based on TOPSIS-Entropy Weight Method Given the discrete distribution and low correlation of different L. lactis strains across the three evaluation indicators, this study introduced the TOPSIS-entropy weight method into the multi-index comprehensive evaluation of strains to avoid excessive bias toward "fermentation characteristics" (a popular indicator) during subjective weighting and to enhance the objectivity and reliability of screening results ( Fig. 2 A ). The ranking results of the TOPSIS-entropy weight method showed that strains NZZ1 and RB12 had significantly higher comprehensive scores than other strains, with 0.8476 and 0.7537 respectively. Although NZZ1 did not exhibit the optimal generation time, it achieved the highest comprehensive score for fermentation capacity through weighted calculation of the weight coefficients ( Table 1 & Fig. 2 B ). This indicates that NZZ1 received the highest recognition in terms of overall fermentation potential, with the most excellent and balanced performance. Table 1 Weight information of each indicator in the TOPSIS entropy weight model Indicator Information Entropy Coefficient of Variation Weight Proportion (%) β-Galactosidase activity 0.8534 0.1466 0.6724 67.24 Generation time 0.973 0.027 0.1236 12.36 Acid production 0.9555 0.0445 0.204 20.4 Analysis of flavor substances produced by key strains fermenting milk Based on the aforementioned comprehensive evaluation results of fermentation performance ( Fig. 3 ) , strains NZZ1 and RB12 with excellent performance were selected. Solid-phase microextraction (SPME) was further employed to analyze the volatile flavor compounds of milk fermented by these two strains. The results showed that esters accounted for the highest proportion (52.46%) among the main components, followed by aliphatic and aromatic hydrocarbons (37.76%), alcohols (7.14%), and others. In contrast, the proportions of aldehydes, nitrogen-containing compounds, and other components were all less than 5% ( Fig. 3 A ). Furthermore, a compound waffle plot was used to visually characterize the abundance heterogeneity of volatile components between the two groups of samples. The number of colored squares indicated the relative abundance of each individual compound in RB12 and NZZ1, revealing significant differences in the abundance distribution patterns between the two groups. Specifically, the abundances of alkanes and alcohols in NZZ1 were significantly higher, and aldehydes were identified as specific components ( Fig. 3 B ). Simultaneously, analysis of the relative abundances of various compounds in RB12 and NZZ1 showed that the abundances of most categories, such as esters, phenols, and nitrogen-containing compounds, were significantly higher in NZZ1 than in RB12. In contrast, RB12 exhibited a higher abundance only in organic acid compounds ( Fig. 3 C ). Multivariate statistical analysis (OPLS-DA) demonstrated that the volatile component compositions of RB12 and NZZ1 samples had significant distinguishability ( Fig. 3 D ). Permutation tests indicated that both R² (goodness of fit) and Q² (predictive ability) were high, and the values decreased significantly after permutation, confirming the stability of the OPLS-DA model and the statistical reliability of intergroup differences ( Fig. 3 E ). Differential compounds were screened through VIP heatmap analysis, with a threshold of VIP > 1, and the top 10 characteristic substances were selected. The results showed that the abundances of 4-hydroxy-2-butanone, ethyl acetate, and other compounds were significantly increased in NZZ1, making substantial contributions to the intergroup differences ( Fig. 3 F ) . The gradient of VIP scores further defined the key differential compounds and their relative contributions, providing a basis for the subsequent screening of flavor markers. Analysis of metabolic mechanisms and enzymatic characteristics of key strains in milk fermentation To elucidate the metabolic pathways underlying flavor compound production in L. lactis , whole-genome sequencing was performed on the key strains NZZ1 and RB12 ( Fig. 4 A ) . CAZymes annotation results revealed significant differences in the number of genes belonging to the glycoside hydrolase (GHs) family between NZZ1 and RB12, with NZZ1 exhibiting a higher abundance of GHs-encoding genes ( Fig. 4 B ). For core functional enzymes including oxidoreductases (EC 1), transferases (EC 2), hydrolases (EC 3), and lyases (EC 4), the proportion of shared enzymes between the two strains exceeded 92%, indicating a high degree of conservation in the basic metabolic enzyme systems of L. lactis ( Fig. 4 D ). Meanwhile, COG annotation results showed that RB12 and NZZ1 had similar gene proportions in functional categories related to basic life activities, such as translation and ribosomal structure (Category J), and replication, recombination, and repair (Category L), demonstrating the conservation of core survival functions. In contrast, NZZ1 had a slightly higher gene proportion (7.4%) in carbohydrate transport and metabolism (Category G) compared to RB12 (7.2%) (Figure S1 A). This is consistent with the enrichment of genes involved in carbohydrate metabolic pathways, suggesting that NZZ1 may possess stronger functional potential in carbohydrate catabolism and utilization, which could further influence the synthesis efficiency of flavor compounds including 4-hydroxy-2-butanone. In addition, the gene distribution and core metabolic nodes of the glycolysis/gluconeogenesis pathway in NZZ1 were illustrated. Key genes such as K01835 (encoding glucokinase) and K01623 (encoding fructose-1,6-bisphosphate aldolase) were annotated ( Fig. 4 C & Figure S2) , confirming that NZZ1 harbors a complete genetic basis for the glycolytic pathway, enabling efficient conversion of glucose to pyruvate and facilitating flavor compound production. Additionally, KEGG pathway annotation results showed that NZZ1 contained the largest number of genes involved in carbon metabolism (67 genes), which constitutes the most core metabolic pathway, followed by purine metabolism (60 genes) and fatty acid metabolism (52 genes). This indicates that the strain has a relatively comprehensive genetic reserve for energy metabolism and substance synthesis. Notably, among carbohydrate metabolism-related pathways, genes involved in starch and sucrose metabolism (34 genes) and pyruvate metabolism (34 genes) were significantly enriched (Figure S1 B) , consistent with the core metabolic characteristics of lactic acid bacteria relying on carbohydrate fermentation. Based on the aforementioned gene annotation and pathway enrichment results, a schematic diagram of the potential metabolic pathway through which NZZ1 participates in the synthesis of butanone flavor compounds such as 4-hydroxy-2-butanone was constructed ( Fig. 4 E ). This provides a theoretical basis and pathway framework for the deduction of its flavor formation mechanism and subsequent functional verification. Comparative analysis of strain characterization and physicochemical and textural properties of fermented milk To explore the fermentation performance of NZZ1, we conducted a horizontal comparison of the physicochemical and textural properties of milk fermented by RB12, commercial starter cultures, and NZZ1. Colonies of NZZ1 on the plate were milky white, circular, convex, smooth, and translucent, with a diameter of 1–3 mm. Under an optical microscope, the bacterial cells were spherical or ovoid, approximately 0.5–1.5 µm in diameter, arranged as diplococci or short chains ( Fig. 5 A ). The growth curve showed that NZZ1 grew slowly in the initial stage (0–4 h), entered the logarithmic growth phase at 4–6 h with a rapid increase in cell count, and transitioned to the stationary growth phase after 6 h. With the consumption of nutrients and accumulation of metabolites, the total biomass decreased slightly ( Fig. 5 B ). Further acidification and curdling analysis revealed that NZZ1 exhibited excellent fermentation performance and unique pH regulation characteristics: fermentation was completed within 8 h, with earlier curd formation. Acidification was moderate during 0–2 h, and the pH rapidly decreased from 6.75 to 5.19 between 4–6 h, which was significantly superior to that of CLCS (commercial starter cultures) and RB12. This facilitates the inhibition of miscellaneous bacteria and ensures subsequent fermentation stability. During post-ripening, the pH remained stable, reaching 4.31 at 24 h, which was higher than that of CLCS and RB12, reflecting moderate acidification ( Fig. 5 C ). In terms of water holding capacity (WHC), NZZ1 performed the best, with the lowest syneresis rate (0.58 ± 0.00%) and the highest WHC (0.93 ± 0.02%) ( Fig. 5 D ). Milk fermented by NZZ1 also showed comprehensive advantages in textural parameters: hardness (139.79 ± 1.66 g) was significantly higher than that of CLCS (118.28 ± 3.89 g) and RB12 (72.33 ± 6.58 g), adhesiveness (165.35 ± 9.51 g·s) was approximately 3 times that of CLCS (55.64 ± 3.07 g·s) and 1.8 times that of RB12 (92.53 ± 0.93 g·s), chewiness (71.37 ± 3.35 g) was also significantly higher than that of CLCS (46.74 ± 1.59 g) and RB12 (40.20 ± 1.97 g), gumminess (82.63 ± 1.17) was slightly lower than that of CLCS (93.80 ± 2.94) but still significantly higher than that of RB12 (41.48 ± 2.07). These results indicate that NZZ1 contributes to the formation of superior textural properties ( Fig. 5 E ). Overall, NZZ1 not only possesses unique flavor characteristics but also significantly improves the water-holding capacity and textural properties of fermented milk, thereby optimizing the taste, texture, and storage stability of the product. This is conducive to enhancing product quality and consumer acceptance. The relationship between sensory evaluation and physicochemical properties of milk There was a high consistency between the textural parameters and sensory evaluation results—higher hardness, adhesiveness, and chewiness often corresponded to better mouthfeel richness and overall preference. Given this close correlation between textural properties and sensory performance, it was necessary to conduct further systematic sensory evaluation. Analysis based on a standardized sensory evaluation protocol ( Fig. 6 A ) showed that NZZ1 exhibited significant advantages in multiple sensory indicators. It achieved the highest score for overall liking degree (5.39 ± 1.46), which was significantly higher than that of the commercial starter culture (4.70 ± 1.63) and RB12 (4.22 ± 1.31). Meanwhile, the milk fermented by NZZ1 had the lowest sourness (2.76 ± 1.56) and bitterness (0.61 ± 1.24), along with the highest sweetness score (4.06 ± 2.11). These factors may have synergistically contributed to its high overall preference. In contrast, RB12 fermented milk showed the strongest sourness (4.22 ± 1.73), the lowest sweetness (3.17 ± 1.20), and a slightly higher fishy odor (0.83 ± 1.58), resulting in a lower overall preference score. To further verify the overall differences among strains, principal component analysis (PCA) was performed on the physicochemical and sensory indicators to characterize the distinctiveness of milk fermented by NZZ1, RB12, and CLCS. The PCA results ( Fig. 6 C ) indicated that the first principal component (PCA1) explained the majority of the data variance and served as the primary dimension distinguishing the three strains. The different strains were clearly separated along the PCA1 axis with good intra-group clustering, demonstrating significant inter-group differences among the fermented milk samples produced by NZZ1, RB12, and CLCS, which could be effectively discriminated. Regulatory effect of inter-strain interactions on the synthesis of flavor substances To investigate the synergistic effect of NZZ1 and commercial starter cultures on the synthesis of 4-hydroxy-2-butanone, this study compared the relative content of 4-hydroxy-2-butanone between the NZZ1 monoculture system and the NZZ1 + CLCS co-culture system. The results showed that the relative content of 4-hydroxy-2-butanone in the NZZ1 monoculture system was approximately 6×10⁸, while after co-cultivation of NZZ1 with CLCS, the relative content of this compound significantly increased to approximately 1.8×10⁹ ( p < 0.01) ( Fig. 6 D ) . This finding indicates that CLCS can significantly enhance the synthesis capacity of 4-hydroxy-2-butanone through metabolic interactions with NZZ1, further verifying the positive regulatory effect of strain combinations on the accumulation of flavor compounds in yogurt. Discussion In this study, naturally fermented cheeses were used as screening samples to isolate L. lactis strains with excellent fermentation performance and high yields of specific flavor compounds. The research team collected six types of dairy products from four provinces in China, with a total of 45 samples obtained. Geographically diverse sampling was adopted because geographical environments are key factors shaping the microbial characteristics of naturally fermented dairy products. Therefore, L. lactis strains isolated from a wide range of dairy products exhibited significant differences in their growth characteristics. Based on a systematic analysis of the fermentation traits of pure cultures, strains with outstanding fermentation performance were selected in this study. Their flavor-producing capacity was further determined, and whole-genome sequencing was performed to elucidate the key metabolic pathways involved. Finally, comparative studies were conducted between these selected strains and commercial starters in dairy product fermentation systems. Traditional naturally fermented dairy products represent a natural reservoir of microbial resources, and the differences in geographical environments and production techniques across different regions have fostered the diversity of microbial communities 18 , 19 . In this study, a total of 50 L. lactis strains were initially isolated and purified from 48 samples of 6 types of traditional dairy products collected from four major pastoral regions: Xinjiang, Yunnan, Inner Mongolia, and Tibet. Among these, the highest number of strains were isolated from Yunnan’s milk cake and Tibet’s qula, whereas only 3 strains were obtained from Xinjiang’s milk residue. This discrepancy may be closely associated with environmental factors such as fermentation temperature, raw material characteristics, and fermentation cycle of dairy products in each producing region 19 , and these differences in environmental factors have further contributed to the genetic and community diversity of the strains 20 . Traditional dairy products in Yunnan and Tibet mostly adopt a natural low-temperature slow-fermentation mode, which is more conducive to the proliferation and colonization of L. lactis 21 . Previous studies have demonstrated that lactic acid bacteria exhibit a certain degree of salt tolerance and can adapt to low-to-moderate salt environments by accumulating compatible solutes, but high salt concentrations inhibit their growth and metabolism 22 . Meanwhile, lactic acid bacteria are sensitive to water activity and require appropriate water activity levels to maintain normal physiological activities, excessively high or low water activity can disrupt their osmotic balance and proliferation 23 . The high-salt and dry characteristics of Xinjiang’s milk residue may impose selective pressure on the survival of strains. L. lactis exhibits excellent fermentation characteristics and plays a pivotal role in dairy product fermentation, with significant variations in milk fermentation capabilities observed among different strains 24 . The results of this study demonstrated that strains isolated from different pastoral regions showed differences and unbalanced distribution in acid production rate, generation time characteristics, and β-galactosidase activity. These findings fully confirmed the co-evolutionary relationship between strain phenotypes and geographical habitat adaptability reported in previous studies 25 , 26 . Excellent fermentation performance is a key factor determining the efficacy of strains in milk fermentation 27 . Overall, although some strains exhibited superior generation time characteristics, their acid-producing capacity and enzyme activity were suboptimal. Traditional strain screening relies primarily on manual experience combined with instrumental assistance 28 – 30 . For high-throughput strain screening—especially when evaluating a large number of indicators with high data dispersion—the interpretability of the empirical approach decreases significantly. The entropy weight method assigns weights based on the dispersion degree of objective data, which can be effectively applied to determine indicator weights 31 . In this study, a mathematical model was established for three indicators: acid production rate, generation time characteristics, and β-galactosidase activity. The results showed that strains NZZ1 and RB12 displayed outstanding overall fermentation performance. Furthermore, the model assigned higher weights to indicators with greater variability, which was consistent with the findings of previous studies 31 , 32 . This fully demonstrated that the established model had good interpretability and accuracy. Naturally fermented dairy products serve as important microbial reservoirs of lactic acid bacteria (LAB). LAB not only dominate the microbial communities of such fermented foods 33 , but also significantly shape the unique flavor profiles of the products by generating a variety of metabolites, including organic acids, esters, and aldehydes-ketones 27 , 33 . Previous studies have regarded fermented dairy products as controllable experimental ecosystems, and by analyzing the microbial communities of cheese rinds, these studies have facilitated the elucidation of the community assembly processes and functional mechanisms underlying LAB-mediated flavor formation 34 . Based on the two screened LAB strains with superior metabolic performance, this study revealed significant differences in their flavor compound profiles. Among these compounds, 4-hydroxy-2-butanone was identified as a signature differential metabolite, characterized by a distinctive creamy-sweet aroma with subtle notes of toasted bread and malt, which can remarkably enhance the flavor quality of fermented dairy products. As early as 1959, this compound was isolated and identified from four types of cheeses via paper chromatography 35 . However, the specific metabolic pathways and regulatory mechanisms of this substance in fermentation systems or living organisms have not yet been fully elucidated. Primary metabolism of this compound is presumably dominated by carbonyl reductases in L. lactis cells, particularly members of the short-chain dehydrogenase/reductase (SDR) family, which can reduce it to alcohols with completely different aromatic properties 35 , 36 . On the other hand, relevant kinetic characterization studies have demonstrated that carbonyl reductases tend to act as cofactors to catalyze the conversion to 1,3-butanediol 37 . In addition, 4-hydroxy-2-butanone may also serve as a substrate to enter esterification or cleavage pathways, and its acetyl moiety might be transformed through a mechanism analogous to ketone body metabolism 38 . These potential biotransformation pathways directly determine the final concentration of 4-hydroxy-2-butanone and the duration of its flavor expression in the system. Therefore, strain NZZ1, when used as a yogurt fermentation starter, can significantly improve product flavor, imparting a unique creamy and baked note to yogurt. Genetic analysis and annotation of the two strains revealed a high degree of conservation in their gene sequences and enzyme expression profiles, which is consistent with the findings of most relevant studies. Specifically, lactic acid bacteria with close genetic relationships exhibit high homology in core gene sequences and share similar genetic backgrounds 39 . Notably, although both strains RB12 and NZZ1 harbor the complete set of enzyme systems and gene sequences responsible for 4-hydroxy-2-butanone metabolism, substantial differences were observed in their expression levels. This phenomenon may be attributed to the following two reasons. First, L. lactis possesses an advantage in carbon source supply and stable central carbon metabolism 40 . Strain NZZ1 highly expresses β-galactosidases belonging to the GH2/GH42 families, which efficiently hydrolyze lactose in the yogurt matrix to produce glucose 41 . The generated glucose then enters the glycolysis pathway to provide sufficient precursors for pyruvate synthesis, thus forming a closed carbon supply loop of “lactose degradation – glycolysis – pyruvate accumulation” 42 . Second, the presence of genes without corresponding expression represents another critical factor contributing to metabolite differences. Although L. lactis generally harbors the complete key enzyme genes, including α-acetolactate synthase (ALS, EC 2.2.1.6) and α-acetolactate decarboxylase (ALDB, EC 4.1.1.5), these genes are usually inactive or expressed at low levels 38 . In contrast, strain NZZ1 not only maintains a complete metabolic pathway, but also exhibits active expression of key enzyme genes that participate in catalytic regulation, thereby acting as the core catalytic node for 4-hydroxy-2-butanone synthesis and ultimately achieving efficient production of the characteristic flavor of yogurt. Subsequently, a commercially available starter culture was incorporated as a control group in this study to comprehensively evaluate the performance of L. lactis in terms of physicochemical properties, texture characteristics, and sensory quality. The results of the relevant analyses indicated that the three yogurt samples showed good discriminability. When used as a monoculture starter, L. lactis NZZ1 exhibited significant advantages in milk fermentation. Its outstanding performance in physicochemical properties, texture, and sensory quality could be attributed to its unique metabolic regulatory network. Although the symbiotic system of traditional commercial starters ( Lactobacillus bulgaricus and Streptococcus thermophilus ) can synergistically produce acids and aroma compounds, their metabolic flux distribution is relatively fixed. In contrast, strain NZZ1 demonstrated a more sophisticated metabolic balance capability, presumably by regulating lactate dehydrogenase activity or sugar transport rate, thus achieving a gentler acid production kinetic process. This is conducive to the formation of a uniform and dense three-dimensional casein gel network, which macroscopically manifests as higher hardness and water-holding capacity, as well as lower whey syneresis rate 43 . Furthermore, this strain diverts a larger proportion of pyruvate toward the 4-hydroxy-2-butanone synthesis pathway, directly contributing to a rich creamy and cheesy aroma. More importantly, it exhibited high abundance and content of flavor compounds including alcohols, esters, and aromatic hydrocarbons. Together with taste-active substances such as amino acids, these compounds form a well-coordinated flavor profile, which mutually support and balance each other at their respective sensory thresholds, avoiding the predominance of a single odor, and ultimately yielding a flavor profile with rich layers and high acceptability 44 . These findings demonstrate that a single strain can also achieve or even surpass the comprehensive effects of traditional starters in texture construction and complex flavor generation by optimizing its own metabolic flux distribution. The composition and synergistic interactions of microbial communities play a crucial role in regulating flavor compounds and driving the formation of key flavor characteristics 45 . As traditional commercial starters, Lactobacillus bulgaricus and Streptococcus thermophilus can ferment lactose through pyruvate metabolism to produce lactic acid and certain carbonyl compounds, thereby influencing yogurt flavor 46 . The results of validation experiments showed that the yield of 4-hydroxy-2-butanone in the co-fermentation group was significantly higher than that in the monoculture group. We preliminarily inferred that the co-culture system formed by combining the commercial starter with L. lactis exhibits enhanced metabolic capacity, which strengthens the original pyruvate metabolism and its efficient accumulation 47 . The insufficient flux of pyruvate into the lactic acid synthesis pathway in a timely manner is one of the important reasons for the high-efficiency production of 4-hydroxy-2-butanone. Based on the findings of this study and advances in current research, it is evident that L. lactis has become a core functional microbial group in fermented milk production. However, its industrial application is still confronted with critical bottlenecks, including strain homogenization, monotonous product flavor profiles, and insufficient texture stability, with relatively few superior strains that simultaneously possess distinctive flavor and functional properties. Against this backdrop, this study isolated a L. lactis strain with both excellent fermentation performance and high 4-hydroxy-2-butanone-producing capacity from naturally fermented dairy products. Combined with genomic approaches, we preliminarily elucidated the metabolic pathways associated with 4-hydroxy-2-butanone synthesis in this strain, and further verified its application potential in flavor development and fermentation performance that surpasses commercial starter cultures in the yogurt fermentation system. In the future, the targeted breeding of flavor-specialized lactic acid bacteria is expected to rely on multi-omics technologies for in-depth exploration of microbial resources from distinctive habitats. Meanwhile, gene editing and metabolic engineering tools can be employed to enhance the synthesis and regulation of key flavor compounds. In addition, innovative application strategies such as “starter-enzyme composite formulations” should be explored; for instance, the synergistic application of L. lactis with Maillard reaction-related enzyme systems could degrade off-flavor substances while generating target characteristic aromas, thereby achieving the synergistic optimization of flavor, texture, and nutritional functions of fermented milk. Furthermore, to support these innovations, future research should elucidate key genes on a larger scale and establish correlations between strain genomes and flavor characteristics. Overall, this study provides an important strain foundation and theoretical reference for subsequent research on the targeted genetic modification of lactic acid bacteria to produce desired metabolites, as well as the development of novel biological flavors and personalized flavor starters. Methods Materials and chemicals In December 2024, samples were collected in pastoral areas of Xinjiang, Tibet, Inner Mongolia, and Yunnan in China, and were quickly placed in ice for transportation to the laboratory. M17 medium was purchased from Solebao Company (Beijing, China), lactose was purchased from Sinopharm Company (Beijing, China), and commercial starter cultures were purchased from Danisco (YO-MIX 300, Denmark), which included Streptococcus thermophilus and Lactobacillus bulgaricus. All other analytical grade chemicals were obtained from high-quality suppliers. Screening, strain identification and cultivation of L. lactis After preprocessing the sample with a homogenizer (D-600Pro, WIGGENS, Beijing, China) 0.5 mL of the well-mixed sample was pipetted into 4.5 mL of 0.9% physiological saline to obtain a 10⁻¹ dilution. Then, 0.5 mL of the 10⁻¹ dilution was pipetted into 4.5 mL of physiological saline to get a 10⁻² dilution. Following this procedure, 10⁻³, 10⁻⁴, 10⁻⁵, and 10⁻⁶ dilutions were obtained in sequence. 100 µL each of the 10⁻⁴, 10⁻⁵, and 10⁻⁶ dilutions was taken and plated on MRS solid medium using a spreader. The plates were incubated in an aerobic incubator at 37°C for 48 hours. Typical single colonies were picked and streaked onto MRS solid medium plates using the three-zone streaking method for purification, followed by incubation in an aerobic incubator at 37°C for 48 hours. The purified single colonies were transferred to MRS liquid medium and cultured in an aerobic medium at 37°C for 24 hours. The bacterial suspension was preserved with 30% glycerol to obtain lactic acid bacteria. The genome of the isolated lactic acid bacteria was extracted, and the 16S rDNA of the strain was amplified and sequenced (completed by Sangon Biotech Co., Ltd., Shanghai, China). The sequence was aligned in GenBank ( https://www.ncbi.nlm.nih.gov/genbank/ ), and finally, 50 strains with a homology of over 99% to L. lactis were identified as L. lactis . The aforementioned L. lactis was inoculated onto LM17 solid medium and cultured in an aerobic incubator at 30°C for 48 hours, and the colony morphology was observed and recorded. The strain was subjected to Gram staining and observed under a inverted light microscope (Nikon, T1-SAM, Tokyo, Japan). L. lactis was inoculated into LM17 liquid medium at an inoculum size of 2% ( v/v ) and placed in a microplate reader (Multiskan SkyHigh, Shanghai, China), followed by aerobic cultivation at 30°C for 24 hours. During the cultivation, the OD₆₀₀ value of the bacterial suspension was measured every 1 hour to plot the growth curve. The microbial growth curve detection system (CLARIOstar Plus, BMG LABTECH, UK) was used. Preparation of Reconstituted Milk Weigh 110 g of skimmed milk powder and added it to 890 mL of sterile water. Stir with a high-speed homogenizer for 5 min to 10 min. After hydrating overnight at 4 ℃, perform pasteurization (105 ℃, 10 min) using a fully automatic vertical steam sterilizer (BONOVO, CT65A, Shanghai, China). Cool to 30 ℃ in a clean bench (Thermo fisher, Protect-1FD, USA) for later use, and 1 L of reconstituted skimmed milk with a mass fraction of 11% can be obtained. Strain activation Inoculate L. lactis from the bacterial preservation tube into LM17 liquid medium at 2% ( v/v ), and culture it in a 30°C constant temperature incubator for 18 hours to obtain the activated first generation. Continue to inoculate the bacterial liquid of the first generation into LM17 liquid medium at 2% ( v/v ), and culture it in a 30°C constant temperature incubator for 18 hours to get the activated second generation. Repeat the above operation to obtain the activated third generation of L. lactis. Inoculate the commercial starter into LM17 liquid medium at 2% ( v/v ), and culture it in a 30°C constant temperature incubator for 24 hours to obtain the activated first generation. Continue to repeat the above operation to get the activated third generation. Determination of the generation time (G) of bacterial strains Generation time (G) refers to the time required for the number of bacterial cells to double during the logarithmic growth phase (a stage where cells proliferate at a constant exponential rate). Based on the previously plotted growth curve, in the logarithmic growth phase segment of the growth curve, selected two time points ( t 1 、t 2 ) and their corresponding cell concentrations ( N 1 、N 2 ), repeat the selection multiple times to take the average value to reduce errors. The conversion reference formula was Equation.1: $$\:\varvec{G}=\varvec{t}\times\:\varvec{l}\varvec{o}\varvec{g}2/({\varvec{l}\varvec{o}\varvec{g}\varvec{N}}_{\varvec{t}}-{\varvec{l}\varvec{o}\varvec{g}\varvec{N}}_{0})$$ 1 Where , Generation Time (G); Incubation time ( \(\:\varvec{t}\) ); Initial cell count ( \(\:{\varvec{N}}_{0}\) ); Start Formula Bold Italic Number of cells at time \(\:\varvec{t}\) ( \(\:{\varvec{N}}_{\varvec{t}}\) ). Determination of β-galactosidase Activity (GA) Use ONPG as the substrate. Inoculate the activated third-generation strain into LM17 medium at a ratio of 2% ( v/v ), and culture it at a constant temperature of 30°C until the mid-logarithmic phase; draw a certain amount of bacterial liquid (recorded as V), and measure the absorbance of the bacterial liquid at 600 nm (recorded as \(\:{OD}_{600}\) ), add 900 µL of Z buffer solution (60 mmol/L Na₂HPO₄, 40 mmol/L Na₂HPO₄, 10 mmol/L KCl, 1 mmol/L MgSO₄), add 10 µL of chloroform, and vortex thoroughly to obtain the crude enzyme solution, add 200 µL of substrate solution to the crude enzyme solution, place it at 30°C for constant temperature reaction and start timing, after 30 min, add 500 µL of 1 mol/L sodium carbonate solution to terminate the reaction; centrifuge the reaction solution at 10,000 r/min and 25°C for 5 min, take the supernatant to measure the absorbance at 420 nm (recorded as \(\:{OD}_{420}\) ). β-galactosidase Activity (GA) is defined as the amount of enzyme required to release unit 2-nitrophenol from the substrate solution per unit time, which was calculated according to the following Equation.2: $$\:\varvec{G}\varvec{A}={(\varvec{O}\varvec{D}}_{600}\times\:\varvec{V}\times\:30)/(1000\times\:{\varvec{O}\varvec{D}}_{420})$$ 2 Where: β-galactosidase Activity (GA) ; Absorbance at 600 nm and 420 nm ( \(\:{\varvec{O}\varvec{D}}_{600}\) , \(\:{\varvec{O}\varvec{D}}_{420}\) ). Determination of Acid Production Rate (APR) The rapid decrease in pH value was crucial during the fermentation process of fermented milk, as it was essential for coagulation and preventing or reducing the growth of harmful microorganisms 25 . The pH value at the fermentation endpoint of fermented milk was 4.5 ± 0.2. Let the pH value at the initial stage of fermentation be denoted as \(\:{\mathbf{p}\mathbf{H}}_{1}\) , the pH value at the fermentation endpoint as \(\:{\mathbf{p}\mathbf{H}}_{2}\) , and the fermentation time as \(\:\varvec{t}\) . The acid production rate ( \(\:\varvec{A}\varvec{P}\varvec{R}\) ) was calculated according to Equation. 3 : $$\:\varvec{A}\text{P}\text{R}={(\mathbf{p}\mathbf{H}}_{1}-{\mathbf{p}\mathbf{H}}_{2})/\text{t}$$ 3 Where : \(\:\varvec{A}\varvec{c}\varvec{i}\varvec{d}\:\varvec{P}\varvec{r}\varvec{o}\varvec{d}\varvec{u}\varvec{c}\varvec{t}\varvec{i}\varvec{o}\varvec{n}\:\varvec{R}\varvec{a}\varvec{t}\varvec{e}\) ( \(\:\varvec{A}\varvec{P}\varvec{R}\) ); The pH value at the initial stage of fermentation ( \(\:{\mathbf{p}\mathbf{H}}_{2}\) ); The pH value at the fermentation endpoint ( \(\:{\mathbf{p}\mathbf{H}}_{1}\) ). L. lactis activated for three generations was centrifuged at 6000 r/min and 4°C for 5 min. The supernatant was discarded, and the initial inoculum concentration in the fermentation system was controlled at 3×10⁶ CFU/mL. An equal volume of normal saline was added to the bacterial suspension, which was then centrifuged again at 6000 r/min and 4°C for 5 min. The supernatant was discarded, and this operation was repeated to obtain bacterial pellets washed with normal saline 2–3 times. An appropriate volume of reconstituted skim milk was added to resuspend the bacterial pellets, ensuring a homogeneous system. The resuspended L. lactis was inoculated into reconstituted skim milk and incubated in a constant-temperature incubator at 30°C. Samples were taken every 2 h to determine the pH value of the bacterial suspension, with the final sampling point at 12 h post-fermentation. TOPSIS entropy weight method screening Taking acid production rate, β-galactosidase activity, and metabolism as the core evaluation indicators, high-quality strain screening was performed by combining the entropy weight method and TOPSIS model using the entropy and TOPSIS packages in R software (Version 4.2.1). First, an \(\:n\times\:3\) dimensional strain evaluation matrix was constructed. The range standardization method was applied to eliminate the dimensional differences of indicators for positive and negative indicators using Equation. 4 and Equation. 5 , respectively: $$\:{\varvec{x}}_{\varvec{i}\varvec{j}}^{+}=\frac{{\varvec{x}}_{\varvec{i}\varvec{j}}-\varvec{m}\varvec{i}\varvec{n}\left({\varvec{x}}_{\varvec{j}}\right)}{\varvec{m}\varvec{a}\varvec{x}\left({\varvec{x}}_{\varvec{j}}\right)-\varvec{m}\varvec{i}\varvec{n}\left({\varvec{x}}_{\varvec{j}}\right)}$$ 4 $$\:{\varvec{x}}_{\varvec{i}\varvec{j}}^{-}=\frac{\varvec{m}\varvec{a}\varvec{x}\left({\varvec{x}}_{\varvec{j}}\right)-{\varvec{x}}_{\varvec{i}\varvec{j}}}{\varvec{m}\varvec{a}\varvec{x}\left({\varvec{x}}_{\varvec{j}}\right)-\varvec{m}\varvec{i}\varvec{n}\left({\varvec{x}}_{\varvec{j}}\right)}$$ 5 Where: \(\:{\varvec{x}}_{\varvec{i}\varvec{j}}\:\) represents the original value of the \(\:\varvec{j}\) indicator for the \(\:\varvec{i}\) strain; \(\:\varvec{m}\varvec{a}\varvec{x}\left({\varvec{x}}_{\varvec{j}}\right),\varvec{m}\varvec{i}\varvec{n}\left({\varvec{x}}_{\varvec{j}}\right)\) denote the maximum and minimum values of the \(\:\varvec{j}\) indicator, respectively. The weight of the \(\:\varvec{i}\) strain under the \(\:\varvec{j}\) indicator was calculated using Equation Equation. 6 . $$\:{\varvec{P}}_{\varvec{i}\varvec{j}}={\varvec{x}}_{\varvec{i}\varvec{j}}/\sum\:_{\varvec{i}=1}^{\varvec{n}}{\varvec{x}}_{\varvec{i}\varvec{j}}$$ 6 Where: The weight of the \(\:\varvec{i}\) strain under the \(\:\varvec{j}\) indicator ( \(\:{\varvec{P}}_{\varvec{i}\varvec{j}}\) ) The indicator entropy values and weights were calculated using Equation. 7 and Equation. 8 , respectively. The weight results reflect the objective contribution of each indicator to strain screening. $$\:{\varvec{e}}_{\varvec{j}}=-\varvec{k}\sum\:_{\varvec{i}=1}^{\varvec{n}}{\varvec{p}}_{\varvec{i}\varvec{j}}\varvec{l}\varvec{n}\left({\varvec{p}}_{\varvec{i}\varvec{j}}\right)\:(\varvec{k}=1/\varvec{l}\varvec{n}(\varvec{n}),\:\varvec{i}\varvec{f}\:{\varvec{p}}_{\varvec{i}\varvec{j}}=0,\:\varvec{t}\varvec{h}\varvec{e}\varvec{n}\:\varvec{l}\varvec{n}({\varvec{p}}_{\varvec{i}\varvec{j}}=0\left)\right)$$ 7 $$\:{\varvec{w}}_{\varvec{j}}=(1-{\varvec{e}}_{\varvec{j}})/\sum\:_{\varvec{i}=1}^{3}(1-{\varvec{e}}_{\varvec{j}})$$ 8 Where: The indicator entropy values ( \(\:{\varvec{e}}_{\varvec{j}}\) ); The indicator weights ( \(\:{\varvec{w}}_{\varvec{j}}\) ). Based on the weighted standardized matrix (standardized values×entropy weights), the positive ideal solution and negative ideal solution were determined using Equations Equation. 9 and Equation. 10 , and the Euclidean distances from each strain to the positive and negative ideal solutions were calculated. $$\:{\varvec{Z}}^{+}=\left(\varvec{m}\varvec{a}\varvec{x}\right({\varvec{w}}_{\varvec{j}}{\varvec{x}}_{\varvec{i}\varvec{j}}\left)\right)\:{\varvec{D}}_{\varvec{i}}^{+}=\sqrt{{\sum\:_{\varvec{i}=1}^{3}({\varvec{w}}_{\varvec{j}}{\varvec{x}}_{\varvec{i}\varvec{j}}-{\varvec{Z}}_{\varvec{j}}^{+})}^{2}}$$ 9 $$\:{\varvec{Z}}^{-}=\left(\varvec{m}\varvec{a}\varvec{x}\right({\varvec{w}}_{\varvec{j}}{\varvec{x}}_{\varvec{i}\varvec{j}}\left)\right)\:{\varvec{D}}_{\varvec{i}}^{-}=\sqrt{{\sum\:_{\varvec{i}=1}^{3}({\varvec{w}}_{\varvec{j}}{\varvec{x}}_{\varvec{i}\varvec{j}}-{\varvec{Z}}_{\varvec{j}}^{-})}^{2}}$$ 10 Where: Positive ideal solutions ( \(\:{\varvec{Z}}^{+}\) ); Negative ideal solutions ( \(\:{\varvec{Z}}^{-}\) ). Finally, the comprehensive closeness degree was calculated using Equation. 11 . The value of \(\:{\varvec{C}}_{\varvec{i}}\) ranges from 0 to 1, with values closer to 1 indicating superior comprehensive performance of the strain. Based on this, high-quality target strains were selected. $$\:{\varvec{C}}_{\varvec{i}}={\varvec{D}}_{\varvec{i}}^{-}/({\varvec{D}}_{\varvec{i}}^{-}+{\varvec{D}}_{\varvec{i}}^{+})$$ 11 Where: Comprehensive closeness degree ( \(\:{\varvec{C}}_{\varvec{i}}\) ). Analysis of volatile flavor compounds The volatile flavor compounds of the target strains were determined using a gas chromatography/mass spectrometry (GC/MS) system (Thermo Fisher Scientific, Trace 1300, USA). Briefly, 6 g of sample was placed in a 20 mL extraction vial, and 1 g of sodium chloride was added. The sample was equilibrated at 50°C for 30 min, after which the fiber probe was inserted into the sealed extraction vial and exposed to the headspace above the sample for 5 min. Chromatographic conditions: An RTX-Wax capillary column (30 m×0.25 mm, 0.25 µm) was used. The temperature program was as follows: initial temperature of 30°C held for 3 min, then increased to 225°C at a rate of 15°C/min and held for 5 min. The carrier gas was helium (He) with a flow rate of 1 mL/min. The injector temperature was set at 225°C, the injection volume was 1 µL, and the split ratio was 10:1.Mass spectrometric conditions: Electron ionization (EI) mode was employed with an ionization energy of 70 eV and an emission current of 200 µA. The detector voltage was set at 1.4 kV. The ion source temperature was maintained at 240°C, the interface temperature at 230°C, and the quadrupole temperature at 150°C. The mass spectral scanning range was m/z 30–500. Qualitative analysis was performed by comparing the results with the NIST2001 standard spectral library, and quantitative analysis was conducted via peak area normalization. All measurements were performed in triplicate. Strain sequencing The target strains were inoculated into LM17 liquid medium at an inoculum size of 2% ( v/v ) and cultured for 12–18 h. The bacterial cells were harvested by centrifugation at 6,000 r/min for 5 min, and genomic DNA was extracted using a DNA extraction kit. A genomic library was constructed from the bacterial DNA, and sequencing was performed on the Illumina NovaSeq PE150 platform (Beijing Novogene Bioinformatics Technology Co., Ltd., Beijing, China). Analysis of the physicochemical properties of fermented milk The pH and titratable acidity of yogurt were determined according to the method previously described by Liu et al. ¹⁹ . During milk fermentation, the pH was measured at predetermined time intervals using a pH meter (DZS-706F, Shanghai, China), and the stable pH value was recorded to analyze the acidification capacity. Titratable acidity was performed using a 0.1 mol/L standard sodium hydroxide solution. The procedure was as follows: 2 g of fermented milk was accurately weighed into a 50 mL Erlenmeyer flask at each predetermined time interval, and the mass m of the fermented milk was precisely recorded. An appropriate volume of distilled water was added, followed by two drops of 0.5% phenolphthalein solution as an indicator; the mixture was then shaken thoroughly. Titration was carried out with the 0.1 mol/L standard sodium hydroxide solution until a faint red color appeared in the solution and persisted for at least 30 seconds. The volume of the consumed standard NaOH solution was recorded. The results were expressed as titratable acidity AT (°T) using Equation. 12 , as follows: $$\:\varvec{T}\varvec{A}={(\varvec{V}}_{1}-{\varvec{V}}_{0})/(\varvec{m}\times\:0.1)\times\:\varvec{c}\times\:100$$ 12 Where: Titratable Acidity ( \(\:TA\) ); Molar concentration of NaOH standard solution (0.1022 mol/L) ( \(\:c\) ); The volume (mL) of NaOH standard solution consumed in titrating the sample ( \(\:{V}_{1}\) ); The volume (mL) of NaOH standard solution consumed in the titration blank ( \(\:{V}_{0}\) ); The quality (g) of fermented milk samples ( \(\:m\) ). Water holding capacity and syneresis of fermented milk The measurement was performed using set yogurt without stirring after ripening. An aliquot of 20.00 ± 0.02 g of yogurt sample was weighed into a 50.00 mL centrifuge tube and centrifuged at 640×g and 4°C for 10 min using a centrifuge (Eppendorf, Centrifuge 5424, Germany). The mass of the was weighed, and the syneresis (%) was calculated according to Equation. 13 : $$\:\varvec{s}\varvec{y}\varvec{n}\varvec{e}\varvec{r}\varvec{e}\varvec{s}\varvec{i}\varvec{s}={\varvec{M}}_{1}/{\varvec{m}}_{1}\times\:100\varvec{\%}$$ 13 Where: Yogurt quality ( \(\:{\varvec{m}}_{1}\) ); The quality of the supernatant whey ( \(\:{\varvec{M}}_{1}\) ). The water holding capacity (WHC) of yogurt was determined according to the method described in previous studies, with appropriate modifications following the protocol reported by D. Dhakal et al 43 . The set yogurt after ripening was centrifuged at 1250×g and 4°C for 10 min. The supernatant was discarded, and the centrifuge tube was inverted for 2 h to completely drain the whey. The precipitate was carefully collected and weighed, and the water holding capacity of the fermented milk was calculated according to Equation. 14 . $$\:\varvec{W}\varvec{H}\varvec{C}\left(\varvec{\%}\right)={\varvec{m}}_{2}/{\varvec{M}}_{2}\times\:100\varvec{\%}$$ 14 Where: Yogurt quality ( \(\:{\varvec{m}}_{2}\) ); The quality of precipitate ( \(\:{\varvec{M}}_{1}\) ). Texture determination of fermented milk The texture analysis was performed with appropriate modifications according to the method described by A. Abdelazez et al 48 . The set yogurt after ripening was removed from the refrigerator at 4°C and equilibrated at room temperature. When the temperature of the yogurt reached 10°C, the texture properties were determined using a Texture Analyzer (Stable Micro Systems Ltd, UK). The test sample was prepared by placing 50 g of yogurt into a 50 mL test container. The measured texture parameters included hardness, adhesiveness, gumminess, cohesiveness, and chewiness. The determination was carried out using a P/36R cylindrical probe under standardized conditions: a test speed of 1.0 mm/s, a penetration depth of 10 mm, and a sampling rate of 400 pps. Sensory evaluation of fermented milk Sensory evaluation of CSB was conducted according to Chinese standard GB/T 23776–2018, with modifications based on Yue and Zhou et al 49,50 . The sensory panel comprised 20 trained individuals (10 males and 10 females) aged between 22 and 30 years, all of whom are currently graduate students at Jiangnan University. All participants were non-smokers and had no known diseases, especially those related to the oral and olfactory organs. They were fully informed about the purpose of the study and provided written consent to participate in the experiment. The study protocol received approval from the Medical Ethics Committee of Jiangnan University (JNU202409RB0056), ensuring adherence to ethical standards in human research. Prior to the sensory assessment, training sessions were conducted for the panelists. These sessions facilitated the identification and refinement of the sensory attributes of the samples, occurring four times a week over a two week period, with each session lasting one hour 51 , 52 . Before starting, all volunteers received basic sensory training, were familiar with the 9-point hedonic scale, and were free from symptoms such as colds or respiratory infections that might impair taste and olfactory functions. Within 24 hours prior to the evaluation, volunteers were prohibited from consuming strong-flavored foods, and no food intake was allowed 1 hour before the test. The three groups of fermented milk samples were stored under refrigeration at 4°C. Prior to the test, the samples were equilibrated at room temperature (22 ± 2°C) for 30 minutes. Each sample, with a volume of 50 mL, was placed in a white plastic cup of uniform specifications and labeled with a random three-digit code. Sensory evaluation was conducted in a standardized sensory laboratory with adequate lighting, good ventilation, and free from extraneous odors. Each evaluation station was equipped with drinking water, soda crackers for palate cleansing, as well as score sheets and pens. The 9-point hedonic scale was adopted, where a score of 1 represented extremely poor and a score of 9 represented excellent. The evaluation indices included 11 dimensions: sourness, sweetness, astringency, bitterness, fishy odor, yogurt-like aroma, whey syneresis, hardness, consistency, viscosity and liking degree. Volunteers evaluated the three groups of samples sequentially; between each evaluation, they rinsed their mouths with warm water and waited for an interval of 3 min. The evaluation duration for each sample was no less than 2 min. After the completion of the evaluation, the score sheets from all 20 volunteers were collected for subsequent statistical analysis. Statistical analysis All experimental results were expressed as mean ± standard deviation (SD, n ≥ 3) . The corresponding significance analysis was performed via one-way analysis of variance (ANOVA) and Duncan’s multiple range test using SPSS 21.0. A value of p < 0.05 was considered statistically significant. Data visualization was conducted using Origin 2024 and GraphPad Prism 9.5.0. Multiple tools were employed for bioinformatics analysis, including filtering sequence reads from each dataset and performing de novo assembly of high-quality paired-end reads using SPAdes v.3.13 ( http://cab.spbu.ru/software/spades/ ). The genome of the target strain was visualized using Proksee software ( https://proksee.ca ). For gene annotation, prediction of gene functions, and characterization of enzyme systems related to carbohydrate metabolism, functional annotation of the genome was performed using EggNOG-mapper v2.1.3. The target protein sequences were aligned against the protein sequences in the EggNOG database via the DIAMOND blastp algorithm, with annotation completed using multi-threaded parallel computing. Online database annotations were carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG; https://www.genome.jp/kegg ) and Carbohydrate-Active enZYmes (CAZyme; http://www.cazy.org/ ). The related data graphs were plotted using R software (Version 4.2.1). Multivariate statistical analyses (OPLS-DA and PCA) were performed on the LC-Bio platform ( https://www.lc-bio.com ). Flow charts were constructed using Microsoft Visio 2025. Declarations Data availability No datasets were generated or analyzed during the course of this study. Competing interests The authors declare no competing interests. Author Contribution Writing–original draft: C.Z., H.Y.S. Writing–review and editing: C.Z., F.W.T., X.M.L., G.W., B.Y., S.M.C., W.W.L., Q.X.Z. Conceptualization and supervision: W.C. and Q.X.Z. Data analysis: C.Z., H.Y.S., Q.X.Z. Data acquisition, C.Z., H.Y.S., Q.X.Z. Acknowledgements This work was supported by the National Key Research and Development Project [No. 2022YFD2100703 and 2024YFD2100901]; the National Natural Science Foundation of China [No. U23A20259]; and the Fundamental Research Funds for the Central Universities JUSRP622013. References Abi Khalil, R. et al. Traditional fermented milk products of Eastern Mediterranean countries: A cultural heritage to preserve. International Dairy Journal 147, 105768 (2023). https://doi.org/10.1016/j.idairyj.2023.105768 Narvhus, J. A. & Abrahamsen, R. K. Traditional and modern Nordic fermented milk products: A review. International Dairy Journal 142, 105641 (2023). https://doi.org/10.1016/j.idairyj.2023.105641 Li, D. et al. Comparative study of yak and cow milk fermented with auxiliary cultures: Physicochemical, microstructural, and flavor profiles. Journal of Dairy Science 108, 10662–10676 (2025). https://doi.org/10.3168/jds.2025-26842 Marco, M. L. et al. The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on fermented foods. Nature Reviews Gastroenterology & Hepatology 18, 196–208 (2021). https://doi.org:10.1038/s41575-020-00390-5 Bai, Y. et al. Flavor profile of milks fermented with six starter cultures. Journal of Food Composition and Analysis 148, 108191 (2025). https://doi.org/10.1016/j.jfca.2025.108191 Bikheet, M. M. et al. Effects of clove (Syzygium aromaticum) extract on antibacterial activity, phytochemical properties, and storage quality of flavored milk beverages. Journal of Dairy Science 108, 3300–3313 (2025). https://doi.org/10.3168/jds.2024-26023 Gezginc, Y., Topcal, F., Comertpay, S. & Akyol, I. Quantitative analysis of the lactic acid and acetaldehyde produced by Streptococcus thermophilus and Lactobacillus bulgaricus strains isolated from traditional Turkish yogurts using HPLC. Journal of Dairy Science 98, 1426–1434 (2015). https://doi.org/10.3168/jds.2014-8447 Borges, T. J., Gutarra, M. L. E. & Melo, L. Importance of information on fermented dairy beverages on choices of specific consumers. Food Research International 217, 116728 (2025). https://doi.org/10.1016/j.foodres.2025.116728 Johansen, E., Øregaard, G., Sørensen, K. I. & Derkx, P. M. F. in Advances in Fermented Foods and Beverages (ed Wilhelm Holzapfel) 227–248 (Woodhead Publishing, 2015). Celik, O. F. & Temiz, H. Lactobacilli isolates as potential aroma producer starter cultures: Effects on the chemical, physical, microbial, and sensory properties of yogurt. Food Bioscience 48, 101802 (2022). https://doi.org/10.1016/j.fbio.2022.101802 Jingjing, E., Zhang, Y. & Yang, R. Impact of metabolite transformations on off-flavor profiles of pasteurized drinking yogurt in non-microbial conditions. LWT 217, 117359 (2025). https://doi.org/10.1016/j.lwt.2025.117359 Guan, Y., Cui, Y., Qu, X., Li, B. & Zhang, L. Post-acidification of fermented milk and its molecular regulatory mechanism. International Journal of Food Microbiology 426, 110920 (2025). https://doi.org/10.1016/j.ijfoodmicro.2024.110920 Bendig, T. et al. The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model. Journal of Biotechnology 374, 90–100 (2023). https://doi.org/10.1016/j.jbiotec.2023.08.001 Yu, X. et al. Effect of different isolation sources of Lactococcus lactis subsp. lactis on volatile metabolites in fermented milk. Food Chemistry: X 21, 101224 (2024). https://doi.org/10.1016/j.fochx.2024.101224 Zhao, Z., Zhang, Y., Simpson, D. J. & Gänzle, M. G. A phylogenetic perspective on the performance of Lactococcus lactis as starter culture in milk and plant milks. Food Research International 221, 117562 (2025). https://doi.org/10.1016/j.foodres.2025.117562 Ayad, E. H. E., Verheul, A., de Jong, C., Wouters, J. T. M. & Smit, G. Flavour forming abilities and amino acid requirements of Lactococcus lactis strains isolated from artisanal and non-dairy origin. International Dairy Journal 9, 725–735 (1999). https://doi.org/10.1016/S0958-6946(99)00140-5 Chen, C. et al. Characterization of metabolic pathways for biosynthesis of the flavor compound 3-methylbutanal by Lactococcus lactis. Journal of Dairy Science 105, 97–108 (2022). https://doi.org/10.3168/jds.2021-20779 Ercolini, D., Moschetti, G., Blaiotta, G. & Coppola, S. The potential of a polyphasic PCR-dGGE approach in evaluating microbial diversity of natural whey cultures for water-buffalo Mozzarella cheese production: bias of culture-dependent and culture-independent analyses. Syst Appl Microbiol 24, 610–617 (2001). https://doi.org:10.1078/0723-2020-00076 Sikombe, T. W., Moonga, H. B., Linnemann, A. R., Smid, E. J. & Schoustra, S. E. The effect of storage temperature on the physicochemical characteristics, volatile compounds and microbial community of a traditionally fermented dairy product. LWT 227, 118035 (2025). https://doi.org/10.1016/j.lwt.2025.118035 Song, Y. et al. Genetic diversity and population structure of Lactobacillus delbrueckii subspecies bulgaricus isolated from naturally fermented dairy foods. Sci Rep 6, 22704 (2016). https://doi.org:10.1038/srep22704 Oshiro, M., Zendo, T. & Nakayama, J. Diversity and dynamics of sourdough lactic acid bacteriota created by a slow food fermentation system. Journal of Bioscience and Bioengineering 131, 333–340 (2021). https://doi.org/10.1016/j.jbiosc.2020.11.007 Wang, H. et al. Analysis of biogenic amines in salt-reduced Harbin dry sausages: From the perspective of free amino acid profile and bacterial community composition. LWT 216, 117327 (2025). https://doi.org/10.1016/j.lwt.2025.117327 Martins, E. et al. Determination of ideal water activity and powder temperature after spray drying to reduce Lactococcus lactis cell viability loss. Journal of Dairy Science 102, 6013–6022 (2019). https://doi.org/10.3168/jds.2019-16297 Shen, X. et al. Metabolomics analysis reveals differences in milk metabolism and fermentation rate between individual Lactococcus lactis subsp. lactis strains. Food Research International 162, 111920 (2022). https://doi.org/10.1016/j.foodres.2022.111920 de Carvalho, C. F. & Planidin, N. P. in Encyclopedia of Evolutionary Biology (Second Edition) (eds Jason B. Wolf & Claudia Augusta De Moraes Russo) 110–126 (Academic Press, 2026). Li, W. et al. Global genomics of Lactococcus lactis: horizontal gene transfer and intergenic variation drive multiple domestication and dairy adaptation. Journal of Advanced Research (2025). https://doi.org/10.1016/j.jare.2025.07.053 Wusigale et al. Comparative genomics and untargeted metabolomics analysis of dairy-derived Lacticaseibacillus rhamnosus strains and their potential applications in dairy fermentation. Journal of Dairy Science 108, 6814–6827 (2025). https://doi.org/10.3168/jds.2025-26446 Hadef, S., Idoui, T., Sifour, M., Genay, M. & Dary-Mourot, A. Screening of Wild Lactic Acid Bacteria from Algerian Traditional Cheeses and Goat Butter to Develop a New Probiotic Starter Culture. Probiotics and Antimicrobial Proteins 15, 387–399 (2023). https://doi.org:10.1007/s12602-022-10000-2 Abushelaibi, A., Al-Mahadin, S., El-Tarabily, K., Shah, N. P. & Ayyash, M. Characterization of potential probiotic lactic acid bacteria isolated from camel milk. LWT - Food Science and Technology 79, 316–325 (2017). https://doi.org/10.1016/j.lwt.2017.01.041 Edalatian Dovom, M. R. et al. Screening of lactic acid bacteria strains isolated from Iranian traditional dairy products for GABA production and optimization by response surface methodology. Sci Rep 13, 440 (2023). https://doi.org:10.1038/s41598-023-27658-5 Han, Q. et al. Research on TOPSIS multi-indicator evaluation model based on entropy weight method for C2N site selection. Annals of Nuclear Energy 221, 111566 (2025). https://doi.org/10.1016/j.anucene.2025.111566 Zare Banadkouki, M. R. Selection of strategies to improve energy efficiency in industry: A hybrid approach using entropy weight method and fuzzy TOPSIS. Energy 279, 128070 (2023). https://doi.org/10.1016/j.energy.2023.128070 Tian, H., Xiong, J., Yu, H., Chen, C. & Lou, X. Flavor optimization in dairy fermentation: From strain screening and metabolic diversity to aroma regulation. Trends in Food Science & Technology 141, 104194 (2023). https://doi.org/10.1016/j.tifs.2023.104194 Frétin, M. et al. Bacterial community assembly from cow teat skin to ripened cheeses is influenced by grazing systems. Scientific Reports 8, 200 (2018). https://doi.org:10.1038/s41598-017-18447-y Li, K. et al. Sortase A-mediated crosslinked short-chain dehydrogenases/reductases as novel biocatalysts with improved thermostability and catalytic efficiency. Scientific Reports 7, 3081 (2017). https://doi.org:10.1038/s41598-017-03168-z Guo, X. et al. A short-chain carbonyl reductase mutant is an efficient catalyst in the production of (R)-1,3-butanediol. Microb Biotechnol 16, 1333–1343 (2023). https://doi.org:10.1111/1751-7915.14249 Zheng, R. C., Ge, Z., Qiu, Z. K., Wang, Y. S. & Zheng, Y. G. Asymmetric synthesis of (R)-1,3-butanediol from 4-hydroxy-2-butanone by a newly isolated strain Candida krusei ZJB-09162. Appl Microbiol Biotechnol 94, 969–976 (2012). https://doi.org:10.1007/s00253-012-3942-2 Bassett, E. W. & Harper, W. J. Isolation and Identification of Acidic and Neutral Carbonyl Compounds in Different Varieties of Cheese1, 2. Journal of Dairy Science 41, 1206–1217 (1958). https://doi.org/10.3168/jds.S0022-0302(58)91076-2 Morita, H. et al. Complete genome sequence and comparative analysis of the fish pathogen Lactococcus garvieae. PLoS One 6, e23184 (2011). https://doi.org:10.1371/journal.pone.0023184 Azizan, K. A., Ressom, H. W., Mendoza, E. R. & Baharum, S. N. (13)C based proteinogenic amino acid (PAA) and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP) pathway in response to agitation and temperature related stresses. PeerJ 5, e3451 (2017). https://doi.org:10.7717/peerj.3451 Galvão, L. C., Fernandes, M. I. & Sawamura, R. [Lactose content and beta-galactosidase activity in yogurt, cheeses and curdled milk made in Brazil]. Arq Gastroenterol 32, 8–14 (1995). Yang, M., Chen, R., Mu, T., Zhang, X. & Xing, J. Switch on a more efficient pyruvate synthesis pathway based on transcriptome analysis and metabolic evolution. Journal of Bioscience and Bioengineering 124, 523–527 (2017). https://doi.org/10.1016/j.jbiosc.2017.06.004 Dhakal, D., Kumar, G., Devkota, L., Subedi, D. & Dhital, S. The choice of probiotics affects the rheological, structural, and sensory attributes of lupin-oat-based yoghurt. Food Hydrocolloids 156, 110353 (2024). https://doi.org/10.1016/j.foodhyd.2024.110353 Han, X. Y., Sun, D. Q., Xiang, L., Huo, G. C. & Jiang, Y. J. [Gene regulation to lactic acid bacteria for increasing production of flavor metabolite]. Wei Sheng Wu Xue Bao 47, 1105–1109 (2007). Gopaulchan, D. et al. A defined microbial community reproduces attributes of fine flavour chocolate fermentation. Nat Microbiol 10, 2130–2152 (2025). https://doi.org:10.1038/s41564-025-02077-6 Gezginc, Y., Topcal, F., Comertpay, S. & Akyol, I. Quantitative analysis of the lactic acid and acetaldehyde produced by Streptococcus thermophilus and Lactobacillus bulgaricus strains isolated from traditional Turkish yogurts using HPLC. J Dairy Sci 98, 1426–1434 (2015). https://doi.org:10.3168/jds.2014-8447 Gao, C. H., Cao, H., Cai, P. & Sørensen, S. J. The initial inoculation ratio regulates bacterial coculture interactions and metabolic capacity. Isme j 15, 29–40 (2021). https://doi.org:10.1038/s41396-020-00751-7 Abdelazez, A. et al. Carob Pod Nanoparticles: enhancing physicochemical, antioxidant, and antibacterial properties of innovative functional frozen yogurt. npj Science of Food 9, 162 (2025). https://doi.org:10.1038/s41538-025-00529-1 Yue, Q., Liu, C., Li, L., Zheng, X. & Bian, K. Effects of fermentation on the rheological characteristics of dough and the quality of steamed bread. Journal of Food Processing and Preservation 43, e14115 (2019). https://doi.org/10.1111/jfpp.14115 Zhou, W. et al. Effects of the coculture of Pediococcus pentosaceus and Saccharomyces cerevisiae with different leavening ability on the quality and volatile organic compounds of Chinese steamed bread. Food Bioscience 59, 104216 (2024). https://doi.org/10.1016/j.fbio.2024.104216 Feng, X. et al. Exploration of the flavor diversity of oolong teas: A comprehensive analysis using metabolomics, quantification techniques, and sensory evaluation. Food Research International 195, 114868 (2024). https://doi.org/10.1016/j.foodres.2024.114868 Yao, W. et al. Flavor profile analysis of grilled lamb seasoned with classic salt, chili pepper, and cumin (Cuminum cyminum) through HS-SPME-GC-MS, HS-GC-IMS, E-nose techniques, and sensory evaluation on Sonit sheep. Food Chemistry 454, 139514 (2024). https://doi.org/10.1016/j.foodchem.2024.139514 Additional Declarations No competing interests reported. Supplementary Files Supplementary.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8656461","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":589576655,"identity":"c357e5c2-8bec-4801-8c81-b3819a925353","order_by":0,"name":"Chuan Zhang","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Chuan","middleName":"","lastName":"Zhang","suffix":""},{"id":589576663,"identity":"d4437b0a-48fc-4807-8d0b-b3f585cf2ae3","order_by":1,"name":"Haiyang Shi","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Haiyang","middleName":"","lastName":"Shi","suffix":""},{"id":589576669,"identity":"31b2d916-9907-440a-9dd0-0acfd49df5b1","order_by":2,"name":"Fengwei Tian","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Fengwei","middleName":"","lastName":"Tian","suffix":""},{"id":589576670,"identity":"57cf3342-f18b-4c96-b971-665d6d9f1356","order_by":3,"name":"Xiaomei Lyu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Xiaomei","middleName":"","lastName":"Lyu","suffix":""},{"id":589576673,"identity":"a4e614e5-93a1-42fb-9513-108772894ecf","order_by":4,"name":"Gang Wang","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Wang","suffix":""},{"id":589576675,"identity":"0b5387f4-8179-44ad-8d8a-ea9d4d409cd2","order_by":5,"name":"Bo Yang","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Yang","suffix":""},{"id":589576676,"identity":"dc133649-38b0-45ad-b8e1-75ae32e29d91","order_by":6,"name":"Shumao Cui","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Shumao","middleName":"","lastName":"Cui","suffix":""},{"id":589576677,"identity":"20458ce0-7b64-4fcf-820c-ed5d477c54e0","order_by":7,"name":"Wenwei Lu","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Wenwei","middleName":"","lastName":"Lu","suffix":""},{"id":589576680,"identity":"75e541d6-c9de-464e-9bee-7c6e765a1d2d","order_by":8,"name":"Wei Chen","email":"","orcid":"","institution":"Jiangnan University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Chen","suffix":""},{"id":589576681,"identity":"f435c0f4-c2de-4392-b05a-cad214303da2","order_by":9,"name":"Qixiao Zhai","email":"data:image/png;base64,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","orcid":"","institution":"Jiangnan University","correspondingAuthor":true,"prefix":"","firstName":"Qixiao","middleName":"","lastName":"Zhai","suffix":""}],"badges":[],"createdAt":"2026-01-21 07:27:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8656461/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8656461/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102513860,"identity":"32ea9a2f-bdda-40b1-9f13-e01dc6d080ea","added_by":"auto","created_at":"2026-02-12 13:11:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27052959,"visible":true,"origin":"","legend":"\u003cp\u003eScreening and fermentation characteristics of \u003cem\u003eL. lactis \u003c/em\u003e(n=3)\u003cem\u003e.\u003c/em\u003e Data are presented as means with SD. \u003cstrong\u003eA\u003c/strong\u003e Workflow for preliminary screening of \u003cem\u003eL. lactis.\u003c/em\u003e \u003cstrong\u003eB \u003c/strong\u003eGeographical source distribution of \u003cem\u003eL. lactis.\u003c/em\u003e \u003cstrong\u003eC\u003c/strong\u003e Generation time (h) characteristics of \u003cem\u003eL. lactis. \u003c/em\u003eThe redder the color, the longer the generation time; the bluer the color, the shorter the generation time. \u003cstrong\u003eD\u003c/strong\u003eAcid production rate of \u003cem\u003eL. lactis\u003c/em\u003e, where RE1, RE2, and RE3 respectively represent the three measured values, and AVG represents the average of the three measurements\u003cem\u003e. \u003c/em\u003eThe redder the color, the faster the acid production rate; the bluer the color, the slower the acid production rate. \u003cstrong\u003eE\u003c/strong\u003eβ-Galactosidase activity of \u003cem\u003eL. lactis \u003c/em\u003e(Yellow stars indicate samples with enzyme activity among the top ten).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/0b65a424599ea82453da61d3.png"},{"id":102513877,"identity":"f6aa93cc-f241-4227-9621-1c8678772f93","added_by":"auto","created_at":"2026-02-12 13:11:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2308926,"visible":true,"origin":"","legend":"\u003cp\u003eTOPSIS-Entropy weight method analysis. A Workflow of TOPSIS-Entropy weight method analysis. B Score results of TOPSIS-Entropy weight method (Ranked in Descending Order). In the Comprehensive Score column, a darker color indicates a higher score and better overall fermentation performance.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/c3ed9babfc0c4129915ac86e.png"},{"id":102513814,"identity":"20c1b955-f88d-4824-a67e-7b9f31458be9","added_by":"auto","created_at":"2026-02-12 13:10:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":446464,"visible":true,"origin":"","legend":"\u003cp\u003eVolatile compounds in fermented milk fermented by key strains. Data are presented as means with SD (n=3). \u003cstrong\u003eA\u003c/strong\u003e Proportional distribution of volatile flavor compound categories in fermented milk. \u003cstrong\u003eB\u003c/strong\u003eVolatile flavor compound profiles of fermented milk. Each square represents a volatile flavor substance. Different colors indicate different categories, and the same color represents the same category. \u003cstrong\u003eC \u003c/strong\u003eContent of volatile flavor compounds in fermented milk. \u003cstrong\u003eD, E\u003c/strong\u003e OPLS-DA score and correlation test plot derived from volatile compound data. Score chart shows the distribution of RB12 and NZZ1 samples on Principal Component 1 (t1, explaining 94.46% of the variance) and Principal Component 2 (t2, explaining 12.14% of the variance). The model diagnostic plot (R² \u0026amp; Q²) shows the trend of the model's goodness of fit (R², blue line) and predictive ability (Q², dark blue dots) as a function of the cumulative contribution rate of principal components (Cor) (R²=0.7628, Q² =-1.3639). \u003cstrong\u003eF\u003c/strong\u003e Heatmap visualization showing volatile compound relative abundances (row-normalized) in fermented milk samples, with bar chats representing VIP scores for each co-fermentation group (n=3). Here are the top ten flavor substances with the highest VIP values.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/e456cb9b7d496e6a68e2dcb1.png"},{"id":102513855,"identity":"6d068c2d-5c61-460f-a40a-1cfce53a3017","added_by":"auto","created_at":"2026-02-12 13:11:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1096957,"visible":true,"origin":"","legend":"\u003cp\u003eGenes and metabolic pathways of key strains. \u003cstrong\u003eA\u003c/strong\u003eCircular genome map of \u003cem\u003eL. lactis \u003c/em\u003eNZZ1 \u0026amp; RB12\u003cem\u003e.\u003c/em\u003e \u003cstrong\u003eB\u003c/strong\u003e Carbohydrate and GH family enzymes. \u003cstrong\u003eC\u003c/strong\u003e KO (KEGG Orthology) difference comparison analysis. D Venn diagrams of enzyme category distributions in \u003cem\u003eL. lactis\u003c/em\u003estrains NZZ1 and RB12. The closer the color is red, the greater the quantity; the closer the color is green, the smaller the quantity.\u003cstrong\u003e E\u003c/strong\u003e Metabolic pathway diagram of 4-hydroxy-2-butanone synthesis in\u003cem\u003e L. lactis\u003c/em\u003e during yogurt fermentation. We did not detect (N.D) 4-hydroxy-2-butanone in yogurt samples fermented by any others except NZZ1 and RB12 (The remaining 48 samples ranked from 3 to 50 in TOPSIS moedel comprehensive score，n=48).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/26d145f3adc871d5769a32b7.png"},{"id":102747245,"identity":"a6708908-b0ac-4de6-8c1b-d76d7e7a836a","added_by":"auto","created_at":"2026-02-16 09:04:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":835270,"visible":true,"origin":"","legend":"\u003cp\u003eBiological characterization of key strains and physicochemical \u0026amp; textural properties of fermented milk (n=3). \u003cstrong\u003eA\u003c/strong\u003eGram staining and streak plate assay of \u003cem\u003eL. lactis\u003c/em\u003e. \u003cstrong\u003eB\u003c/strong\u003e Growth curve of \u003cem\u003eL. lactis\u003c/em\u003e. \u003cstrong\u003eC\u003c/strong\u003e Titratable acidity and pH of fermented milk. Each sample was measured in triplicate.\u003cstrong\u003e D\u003c/strong\u003e Water-holding capacity and syneresis of fermented milk.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eE\u003c/strong\u003e Texture properties of fermented milk. The Statistical significance between different groups was analyzed using one-way ANOVA with Tukey Multiple Comparisons (* \u003cem\u003ep\u0026lt;\u003c/em\u003e0.05, * \u003cem\u003ep\u0026lt;\u003c/em\u003e0.01, *** \u003cem\u003ep\u0026lt;\u003c/em\u003e0.001 and **** \u003cem\u003ep\u0026lt;\u003c/em\u003e0.0001).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/8fe5c44c9dfde3a64432c3b6.png"},{"id":102513827,"identity":"83d38655-0247-49ce-b130-f4ad18035e62","added_by":"auto","created_at":"2026-02-12 13:10:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":897829,"visible":true,"origin":"","legend":"\u003cp\u003eSensory evaluation and co-fermentation of fermented milk. Data are presented as means with SD (n=3). \u003cstrong\u003eA\u003c/strong\u003e Sensory evaluation system and workflow. \u003cstrong\u003eB\u003c/strong\u003e Radar chart of sensory scores. \u003cstrong\u003eC\u003c/strong\u003e Principal component analysis (PCA) of sensory evaluation and physicochemical properties, Shows the distribution of RB12, NZZ1, and CLCS samples on Principal Component 1 (PCA1, explaining 95.99% of the variance) and Principal Component 2 (PCA2, explaining 3.18% of the variance). \u003cstrong\u003eD\u003c/strong\u003e Co-fermentation of \u003cem\u003eL. lactis\u003c/em\u003eand commercial starter culture. The Statistical significance between different groups was analyzed using one-way ANOVA with Tukey Multiple Comparisons (* \u003cem\u003ep\u0026lt;\u003c/em\u003e0.05, * \u003cem\u003ep\u0026lt;\u003c/em\u003e0.01, *** \u003cem\u003ep\u0026lt;\u003c/em\u003e0.001 and **** \u003cem\u003ep\u0026lt;\u003c/em\u003e0.0001).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/910825da8ea6c2400cffb170.png"},{"id":104782220,"identity":"28bc9372-0d0c-4a02-a200-7b7e3cc12d8d","added_by":"auto","created_at":"2026-03-17 07:56:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10715394,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/1afcaf47-6375-449b-898f-dc8acfa7e8f0.pdf"},{"id":102513868,"identity":"ee06694b-1f24-45d4-8e7f-f13a94161c4b","added_by":"auto","created_at":"2026-02-12 13:11:06","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":502417,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-8656461/v1/61e5c70c44b38fde2ce7ea5f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cem\u003eLactococcus lactis\u003c/em\u003e enhances the flavor of fermented milk by producing 4-hydroxy-2-butanone\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFermented dairy products have long been an integral part of the daily diet for people worldwide, serving as an excellent source of nutrients and beneficial microorganisms in modern life\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The unique flavors of these products not only enhance the dining experience but also significantly influence consumer choices\u003csup\u003e\u003cb\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. However, the enhancement of fermented dairy product flavors currently relies primarily on the addition of natural flavorings and flavor enhancers\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eResearch on enhancing the flavor of fermented dairy from a strain perspective is scarce and time-consuming, facing challenges such as a broad selection scope and numerous interfering factors\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. As the public places greater emphasis on healthy eating and the concept of \u0026ldquo;no-additive\u0026rdquo; foods\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Developing fermentation strains with superior flavor profiles not only reduces reliance on flavorings and enhancers while lowering production costs, but also enhances the sensory qualities of dairy products and ensures their quality, thereby promoting sustainable food production\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Naturally fermented dairy products are produced through the interaction between the microbial flora of raw dairy and indigenous microorganisms in the environment\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. To accelerate fermentation, inoculation technology was ultimately adopted, which involves using a small amount of the previous fermentation liquid as the \u0026ldquo;starter culture\u0026rdquo; for the next stage\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. This process employs natural selection to identify highly adaptable and productive microorganisms, thereby shortening fermentation time and enhancing fermentation quality, providing a robust system for the selection and breeding of superior strains for fermented dairy products\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTraditional dairy fermentation primarily relies on a mixed culture of \u003cem\u003eStreptococcus thermophilus\u003c/em\u003e and \u003cem\u003eLactobacillus bulgaricus\u003c/em\u003e\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. During fermentation, these two strains metabolize lactose to produce lactic acid\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. \u003cem\u003eLactobacillus bulgaricus\u003c/em\u003e, as a classic strain, rapidly lowers the pH of the fermentation system through its potent acid-producing capacity. This not only suppresses the growth of unwanted microorganisms and extends product shelf life, but also imparts the characteristic sweet-and-sour flavor profile to fermented dairy\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The combination of these classic strains forms the foundation of traditional fermented dairy's quality. Nevertheless, as consumer demand for diverse flavors rises, the traditional single-strain combination struggles to meet the market's pursuit of distinctive flavors. \u003cem\u003eLactococcus lactis\u003c/em\u003e is a commonly used starter culture in fermented dairy products. Unlike strains focused on acid production or probiotic functions, the core value of \u003cem\u003eLactococcus lactis\u003c/em\u003e lies in its precise shaping of fermented dairy flavor, making it highly valuable for application\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Specifically, it demonstrates outstanding application performance in the production of dairy products such as cheese and fermented dairy\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Research indicates that \u003cem\u003eLactococcus lactis\u003c/em\u003e can express α-keto acid decarboxylase and α-keto acid dehydrogenase to promote amino acid conversion into flavor compounds\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. During cheese fermentation, it significantly increases the content of 3-methylbutanal, enhancing the product's buttery flavor\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTherefore, this study aims to screen and identify superior \u003cem\u003eLactococcus lactis\u003c/em\u003e strains to enhance the flavor characteristics of fermented dairy products. Using Xinjiang milk curd and milk residue, Yunnan milk cake and milk fan, Inner Mongolia milk lump, and Tibet qula as research samples, \u003cem\u003eLactococcus lactis\u003c/em\u003e strains were isolated and purified. By measuring the strains' generation time characteristics, acid production rate, and β-galactosidase activity, combined with the TOPSIS entropy weight evaluation model, strains with excellent comprehensive fermentation performance were selected. Furthermore, solid-phase microextraction (SPME) was employed to characterize volatile compounds produced by superior strains in fermented dairy. Integrating whole-genome information with annotation from eggNOG, KEGG and CAZymes databases, specific flavor-compound biosynthetic pathways were elucidated to identify strains capable of synthesizing target flavor compounds. Differences in texture, water-holding capacity, acidity (titratable acidity, pH), and flavor were compared between commercially available composite starter cultures (\u003cem\u003eLactobacillus bulgaricus\u0026thinsp;+\u0026thinsp;Streptococcus thermophilus\u003c/em\u003e) and fermented dairy products. This clarified the application potential of superior strains and explored the impact of mixed fermentation on flavor compound changes.\u003c/p\u003e"},{"header":"Result","content":"\u003cp\u003e \u003cb\u003eScreening of\u003c/b\u003e \u003cb\u003eL. lactis\u003c/b\u003e \u003cb\u003eand determination of fermentation characteristics\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eL. lactis\u003c/em\u003e strains were isolated and purified using MRS medium from samples including Xinjiang milk tofu and milk resdue, Yunnan milk cake and milk fan, Inner Mongolia milk curd, and Tibet qula. A total of 50 target \u003cem\u003eL.\u003c/em\u003e lactis strains were obtained through identification by 16S rRNA gene sequencing \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e Notably, there was a significant variation in the capacity of different producing areas to yield \u003cem\u003eL. lactis\u003c/em\u003e. The highest number of \u003cem\u003eL. lactis\u003c/em\u003e strains were isolated from Tibet qula and Yunnan milk cake, with 15 and 17 strains respectively, while Xinjiang nazhaizi yielded the fewest, only 3 strains \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Furthermore, the generation times of the 50 \u003cem\u003eL. lactis\u003c/em\u003e strains were determined, revealing obvious differences among strains with an average generation time of 3.76 hours \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e Among them, strains such as RB8, NDF1, and RB16 exhibited generation times much lower than the average, indicating extremely rapid growth rates. In contrast, a small number of strains (e.g., NDF2) had generation times approaching 13 hours, which were significantly higher than the average.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnalysis of acid production rates showed significant differences among the 50 \u003cem\u003eL. lactis\u003c/em\u003e strains. High acid-producing strains were mainly derived from samples of Xinjiang, Inner Mongolia, and Tibet, while strains from Yunnan samples generally exhibited low acid production rates. Specifically, the average acid production rates of NDF3, NDF5, NGD2, NZZ6, and NZZ1 were all above 0.36, with the highest reaching 0.418 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e Determination of β-galactosidase activity indicated that among the top 10 strains with the highest enzyme activity (marked with yellow stars), 6 strains were isolated from Yunnan milk cake and milk fan, and 2 from Inner Mongolia milk curd. RB12 and NZZ1 showed the highest enzyme activities, at 991.51 U and 1108.83 U respectively. In contrast, \u003cem\u003eL. lactis\u003c/em\u003e strains from Tibet and Xinjiang generally had low enzyme activities, most of which were below 200 U \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eConstruction and Result Evaluation of Lactic Acid Bacteria Screening System Based on TOPSIS-Entropy Weight Method\u003c/h2\u003e \u003cp\u003eGiven the discrete distribution and low correlation of different \u003cem\u003eL. lactis\u003c/em\u003e strains across the three evaluation indicators, this study introduced the TOPSIS-entropy weight method into the multi-index comprehensive evaluation of strains to avoid excessive bias toward \"fermentation characteristics\" (a popular indicator) during subjective weighting and to enhance the objectivity and reliability of screening results \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e The ranking results of the TOPSIS-entropy weight method showed that strains NZZ1 and RB12 had significantly higher comprehensive scores than other strains, with 0.8476 and 0.7537 respectively. Although NZZ1 did not exhibit the optimal generation time, it achieved the highest comprehensive score for fermentation capacity through weighted calculation of the weight coefficients \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e\u0026amp;\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e This indicates that NZZ1 received the highest recognition in terms of overall fermentation potential, with the most excellent and balanced performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWeight information of each indicator in the TOPSIS entropy weight model\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicator\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInformation Entropy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoefficient of Variation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-Galactosidase activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.8534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1466\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.6724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneration time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.973\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.1236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcid production\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnalysis of flavor substances produced by key strains fermenting milk\u003c/h3\u003e\n\u003cp\u003eBased on the aforementioned comprehensive evaluation results of fermentation performance \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, strains NZZ1 and RB12 with excellent performance were selected. Solid-phase microextraction (SPME) was further employed to analyze the volatile flavor compounds of milk fermented by these two strains. The results showed that esters accounted for the highest proportion (52.46%) among the main components, followed by aliphatic and aromatic hydrocarbons (37.76%), alcohols (7.14%), and others. In contrast, the proportions of aldehydes, nitrogen-containing compounds, and other components were all less than 5% \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e Furthermore, a compound waffle plot was used to visually characterize the abundance heterogeneity of volatile components between the two groups of samples. The number of colored squares indicated the relative abundance of each individual compound in RB12 and NZZ1, revealing significant differences in the abundance distribution patterns between the two groups. Specifically, the abundances of alkanes and alcohols in NZZ1 were significantly higher, and aldehydes were identified as specific components \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSimultaneously, analysis of the relative abundances of various compounds in RB12 and NZZ1 showed that the abundances of most categories, such as esters, phenols, and nitrogen-containing compounds, were significantly higher in NZZ1 than in RB12. In contrast, RB12 exhibited a higher abundance only in organic acid compounds \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e Multivariate statistical analysis (OPLS-DA) demonstrated that the volatile component compositions of RB12 and NZZ1 samples had significant distinguishability \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e Permutation tests indicated that both R\u0026sup2; (goodness of fit) and Q\u0026sup2; (predictive ability) were high, and the values decreased significantly after permutation, confirming the stability of the OPLS-DA model and the statistical reliability of intergroup differences \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e Differential compounds were screened through VIP heatmap analysis, with a threshold of VIP\u0026thinsp;\u0026gt;\u0026thinsp;1, and the top 10 characteristic substances were selected. The results showed that the abundances of 4-hydroxy-2-butanone, ethyl acetate, and other compounds were significantly increased in NZZ1, making substantial contributions to the intergroup differences \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. The gradient of VIP scores further defined the key differential compounds and their relative contributions, providing a basis for the subsequent screening of flavor markers.\u003c/p\u003e\n\u003ch3\u003eAnalysis of metabolic mechanisms and enzymatic characteristics of key strains in milk fermentation\u003c/h3\u003e\n\u003cp\u003eTo elucidate the metabolic pathways underlying flavor compound production in \u003cem\u003eL. lactis\u003c/em\u003e, whole-genome sequencing was performed on the key strains NZZ1 and RB12 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. CAZymes annotation results revealed significant differences in the number of genes belonging to the glycoside hydrolase (GHs) family between NZZ1 and RB12, with NZZ1 exhibiting a higher abundance of GHs-encoding genes \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e For core functional enzymes including oxidoreductases (EC 1), transferases (EC 2), hydrolases (EC 3), and lyases (EC 4), the proportion of shared enzymes between the two strains exceeded 92%, indicating a high degree of conservation in the basic metabolic enzyme systems of \u003cem\u003eL. lactis\u003c/em\u003e \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e Meanwhile, COG annotation results showed that RB12 and NZZ1 had similar gene proportions in functional categories related to basic life activities, such as translation and ribosomal structure (Category J), and replication, recombination, and repair (Category L), demonstrating the conservation of core survival functions. In contrast, NZZ1 had a slightly higher gene proportion (7.4%) in carbohydrate transport and metabolism (Category G) compared to RB12 (7.2%) \u003cb\u003e(Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA).\u003c/b\u003e This is consistent with the enrichment of genes involved in carbohydrate metabolic pathways, suggesting that NZZ1 may possess stronger functional potential in carbohydrate catabolism and utilization, which could further influence the synthesis efficiency of flavor compounds including 4-hydroxy-2-butanone.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition, the gene distribution and core metabolic nodes of the glycolysis/gluconeogenesis pathway in NZZ1 were illustrated. Key genes such as K01835 (encoding glucokinase) and K01623 (encoding fructose-1,6-bisphosphate aldolase) were annotated \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC \u003cb\u003e\u0026amp; Figure S2)\u003c/b\u003e, confirming that NZZ1 harbors a complete genetic basis for the glycolytic pathway, enabling efficient conversion of glucose to pyruvate and facilitating flavor compound production. Additionally, KEGG pathway annotation results showed that NZZ1 contained the largest number of genes involved in carbon metabolism (67 genes), which constitutes the most core metabolic pathway, followed by purine metabolism (60 genes) and fatty acid metabolism (52 genes). This indicates that the strain has a relatively comprehensive genetic reserve for energy metabolism and substance synthesis. Notably, among carbohydrate metabolism-related pathways, genes involved in starch and sucrose metabolism (34 genes) and pyruvate metabolism (34 genes) were significantly enriched \u003cb\u003e(Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB)\u003c/b\u003e, consistent with the core metabolic characteristics of lactic acid bacteria relying on carbohydrate fermentation. Based on the aforementioned gene annotation and pathway enrichment results, a schematic diagram of the potential metabolic pathway through which NZZ1 participates in the synthesis of butanone flavor compounds such as 4-hydroxy-2-butanone was constructed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e This provides a theoretical basis and pathway framework for the deduction of its flavor formation mechanism and subsequent functional verification.\u003c/p\u003e\n\u003ch3\u003eComparative analysis of strain characterization and physicochemical and textural properties of fermented milk\u003c/h3\u003e\n\u003cp\u003eTo explore the fermentation performance of NZZ1, we conducted a horizontal comparison of the physicochemical and textural properties of milk fermented by RB12, commercial starter cultures, and NZZ1. Colonies of NZZ1 on the plate were milky white, circular, convex, smooth, and translucent, with a diameter of 1\u0026ndash;3 mm. Under an optical microscope, the bacterial cells were spherical or ovoid, approximately 0.5\u0026ndash;1.5 \u0026micro;m in diameter, arranged as diplococci or short chains \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e).\u003c/b\u003e The growth curve showed that NZZ1 grew slowly in the initial stage (0\u0026ndash;4 h), entered the logarithmic growth phase at 4\u0026ndash;6 h with a rapid increase in cell count, and transitioned to the stationary growth phase after 6 h. With the consumption of nutrients and accumulation of metabolites, the total biomass decreased slightly \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e).\u003c/b\u003e Further acidification and curdling analysis revealed that NZZ1 exhibited excellent fermentation performance and unique pH regulation characteristics: fermentation was completed within 8 h, with earlier curd formation. Acidification was moderate during 0\u0026ndash;2 h, and the pH rapidly decreased from 6.75 to 5.19 between 4\u0026ndash;6 h, which was significantly superior to that of CLCS (commercial starter cultures) and RB12. This facilitates the inhibition of miscellaneous bacteria and ensures subsequent fermentation stability. During post-ripening, the pH remained stable, reaching 4.31 at 24 h, which was higher than that of CLCS and RB12, reflecting moderate acidification \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn terms of water holding capacity (WHC), NZZ1 performed the best, with the lowest syneresis rate (0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00%) and the highest WHC (0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02%) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD\u003cb\u003e).\u003c/b\u003e Milk fermented by NZZ1 also showed comprehensive advantages in textural parameters: hardness (139.79\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66 g) was significantly higher than that of CLCS (118.28\u0026thinsp;\u0026plusmn;\u0026thinsp;3.89 g) and RB12 (72.33\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58 g), adhesiveness (165.35\u0026thinsp;\u0026plusmn;\u0026thinsp;9.51 g\u0026middot;s) was approximately 3 times that of CLCS (55.64\u0026thinsp;\u0026plusmn;\u0026thinsp;3.07 g\u0026middot;s) and 1.8 times that of RB12 (92.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93 g\u0026middot;s), chewiness (71.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.35 g) was also significantly higher than that of CLCS (46.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59 g) and RB12 (40.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.97 g), gumminess (82.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17) was slightly lower than that of CLCS (93.80\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94) but still significantly higher than that of RB12 (41.48\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07). These results indicate that NZZ1 contributes to the formation of superior textural properties \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE\u003cb\u003e).\u003c/b\u003e Overall, NZZ1 not only possesses unique flavor characteristics but also significantly improves the water-holding capacity and textural properties of fermented milk, thereby optimizing the taste, texture, and storage stability of the product. This is conducive to enhancing product quality and consumer acceptance.\u003c/p\u003e\n\u003ch3\u003eThe relationship between sensory evaluation and physicochemical properties of milk\u003c/h3\u003e\n\u003cp\u003eThere was a high consistency between the textural parameters and sensory evaluation results\u0026mdash;higher hardness, adhesiveness, and chewiness often corresponded to better mouthfeel richness and overall preference. Given this close correlation between textural properties and sensory performance, it was necessary to conduct further systematic sensory evaluation. Analysis based on a standardized sensory evaluation protocol \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e showed that NZZ1 exhibited significant advantages in multiple sensory indicators. It achieved the highest score for overall liking degree (5.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46), which was significantly higher than that of the commercial starter culture (4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63) and RB12 (4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.31). Meanwhile, the milk fermented by NZZ1 had the lowest sourness (2.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56) and bitterness (0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24), along with the highest sweetness score (4.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11). These factors may have synergistically contributed to its high overall preference. In contrast, RB12 fermented milk showed the strongest sourness (4.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73), the lowest sweetness (3.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20), and a slightly higher fishy odor (0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58), resulting in a lower overall preference score.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further verify the overall differences among strains, principal component analysis (PCA) was performed on the physicochemical and sensory indicators to characterize the distinctiveness of milk fermented by NZZ1, RB12, and CLCS. The PCA results \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e indicated that the first principal component (PCA1) explained the majority of the data variance and served as the primary dimension distinguishing the three strains. The different strains were clearly separated along the PCA1 axis with good intra-group clustering, demonstrating significant inter-group differences among the fermented milk samples produced by NZZ1, RB12, and CLCS, which could be effectively discriminated.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRegulatory effect of inter-strain interactions on the synthesis of flavor substances\u003c/h2\u003e \u003cp\u003e To investigate the synergistic effect of NZZ1 and commercial starter cultures on the synthesis of 4-hydroxy-2-butanone, this study compared the relative content of 4-hydroxy-2-butanone between the NZZ1 monoculture system and the NZZ1\u0026thinsp;+\u0026thinsp;CLCS co-culture system. The results showed that the relative content of 4-hydroxy-2-butanone in the NZZ1 monoculture system was approximately 6\u0026times;10⁸, while after co-cultivation of NZZ1 with CLCS, the relative content of this compound significantly increased to approximately 1.8\u0026times;10⁹ (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. This finding indicates that CLCS can significantly enhance the synthesis capacity of 4-hydroxy-2-butanone through metabolic interactions with NZZ1, further verifying the positive regulatory effect of strain combinations on the accumulation of flavor compounds in yogurt.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, naturally fermented cheeses were used as screening samples to isolate \u003cem\u003eL. lactis\u003c/em\u003e strains with excellent fermentation performance and high yields of specific flavor compounds. The research team collected six types of dairy products from four provinces in China, with a total of 45 samples obtained. Geographically diverse sampling was adopted because geographical environments are key factors shaping the microbial characteristics of naturally fermented dairy products. Therefore, \u003cem\u003eL. lactis\u003c/em\u003e strains isolated from a wide range of dairy products exhibited significant differences in their growth characteristics. Based on a systematic analysis of the fermentation traits of pure cultures, strains with outstanding fermentation performance were selected in this study. Their flavor-producing capacity was further determined, and whole-genome sequencing was performed to elucidate the key metabolic pathways involved. Finally, comparative studies were conducted between these selected strains and commercial starters in dairy product fermentation systems.\u003c/p\u003e \u003cp\u003eTraditional naturally fermented dairy products represent a natural reservoir of microbial resources, and the differences in geographical environments and production techniques across different regions have fostered the diversity of microbial communities\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. In this study, a total of 50 \u003cem\u003eL. lactis\u003c/em\u003e strains were initially isolated and purified from 48 samples of 6 types of traditional dairy products collected from four major pastoral regions: Xinjiang, Yunnan, Inner Mongolia, and Tibet. Among these, the highest number of strains were isolated from Yunnan\u0026rsquo;s milk cake and Tibet\u0026rsquo;s qula, whereas only 3 strains were obtained from Xinjiang\u0026rsquo;s milk residue. This discrepancy may be closely associated with environmental factors such as fermentation temperature, raw material characteristics, and fermentation cycle of dairy products in each producing region\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e, and these differences in environmental factors have further contributed to the genetic and community diversity of the strains \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Traditional dairy products in Yunnan and Tibet mostly adopt a natural low-temperature slow-fermentation mode, which is more conducive to the proliferation and colonization of \u003cem\u003eL. lactis\u003c/em\u003e \u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Previous studies have demonstrated that lactic acid bacteria exhibit a certain degree of salt tolerance and can adapt to low-to-moderate salt environments by accumulating compatible solutes, but high salt concentrations inhibit their growth and metabolism\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Meanwhile, lactic acid bacteria are sensitive to water activity and require appropriate water activity levels to maintain normal physiological activities, excessively high or low water activity can disrupt their osmotic balance and proliferation\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The high-salt and dry characteristics of Xinjiang\u0026rsquo;s milk residue may impose selective pressure on the survival of strains.\u003c/p\u003e \u003cp\u003e \u003cem\u003eL. lactis\u003c/em\u003e exhibits excellent fermentation characteristics and plays a pivotal role in dairy product fermentation, with significant variations in milk fermentation capabilities observed among different strains\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The results of this study demonstrated that strains isolated from different pastoral regions showed differences and unbalanced distribution in acid production rate, generation time characteristics, and β-galactosidase activity. These findings fully confirmed the co-evolutionary relationship between strain phenotypes and geographical habitat adaptability reported in previous studies\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eExcellent fermentation performance is a key factor determining the efficacy of strains in milk fermentation\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Overall, although some strains exhibited superior generation time characteristics, their acid-producing capacity and enzyme activity were suboptimal. Traditional strain screening relies primarily on manual experience combined with instrumental assistance\u003csup\u003e\u003cb\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. For high-throughput strain screening\u0026mdash;especially when evaluating a large number of indicators with high data dispersion\u0026mdash;the interpretability of the empirical approach decreases significantly. The entropy weight method assigns weights based on the dispersion degree of objective data, which can be effectively applied to determine indicator weights\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. In this study, a mathematical model was established for three indicators: acid production rate, generation time characteristics, and β-galactosidase activity. The results showed that strains NZZ1 and RB12 displayed outstanding overall fermentation performance. Furthermore, the model assigned higher weights to indicators with greater variability, which was consistent with the findings of previous studies\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. This fully demonstrated that the established model had good interpretability and accuracy.\u003c/p\u003e \u003cp\u003eNaturally fermented dairy products serve as important microbial reservoirs of lactic acid bacteria (LAB). LAB not only dominate the microbial communities of such fermented foods\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e, but also significantly shape the unique flavor profiles of the products by generating a variety of metabolites, including organic acids, esters, and aldehydes-ketones\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Previous studies have regarded fermented dairy products as controllable experimental ecosystems, and by analyzing the microbial communities of cheese rinds, these studies have facilitated the elucidation of the community assembly processes and functional mechanisms underlying LAB-mediated flavor formation\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Based on the two screened LAB strains with superior metabolic performance, this study revealed significant differences in their flavor compound profiles. Among these compounds, 4-hydroxy-2-butanone was identified as a signature differential metabolite, characterized by a distinctive creamy-sweet aroma with subtle notes of toasted bread and malt, which can remarkably enhance the flavor quality of fermented dairy products. As early as 1959, this compound was isolated and identified from four types of cheeses via paper chromatography\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. However, the specific metabolic pathways and regulatory mechanisms of this substance in fermentation systems or living organisms have not yet been fully elucidated. Primary metabolism of this compound is presumably dominated by carbonyl reductases in \u003cem\u003eL. lactis\u003c/em\u003e cells, particularly members of the short-chain dehydrogenase/reductase (SDR) family, which can reduce it to alcohols with completely different aromatic properties\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. On the other hand, relevant kinetic characterization studies have demonstrated that carbonyl reductases tend to act as cofactors to catalyze the conversion to 1,3-butanediol\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. In addition, 4-hydroxy-2-butanone may also serve as a substrate to enter esterification or cleavage pathways, and its acetyl moiety might be transformed through a mechanism analogous to ketone body metabolism\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. These potential biotransformation pathways directly determine the final concentration of 4-hydroxy-2-butanone and the duration of its flavor expression in the system. Therefore, strain NZZ1, when used as a yogurt fermentation starter, can significantly improve product flavor, imparting a unique creamy and baked note to yogurt.\u003c/p\u003e \u003cp\u003eGenetic analysis and annotation of the two strains revealed a high degree of conservation in their gene sequences and enzyme expression profiles, which is consistent with the findings of most relevant studies. Specifically, lactic acid bacteria with close genetic relationships exhibit high homology in core gene sequences and share similar genetic backgrounds\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Notably, although both strains RB12 and NZZ1 harbor the complete set of enzyme systems and gene sequences responsible for 4-hydroxy-2-butanone metabolism, substantial differences were observed in their expression levels. This phenomenon may be attributed to the following two reasons. First, \u003cem\u003eL. lactis\u003c/em\u003e possesses an advantage in carbon source supply and stable central carbon metabolism\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Strain NZZ1 highly expresses β-galactosidases belonging to the GH2/GH42 families, which efficiently hydrolyze lactose in the yogurt matrix to produce glucose\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The generated glucose then enters the glycolysis pathway to provide sufficient precursors for pyruvate synthesis, thus forming a closed carbon supply loop of \u0026ldquo;lactose degradation \u0026ndash; glycolysis \u0026ndash; pyruvate accumulation\u0026rdquo;\u003csup\u003e\u003cb\u003e42\u003c/b\u003e\u003c/sup\u003e. Second, the presence of genes without corresponding expression represents another critical factor contributing to metabolite differences. Although \u003cem\u003eL. lactis\u003c/em\u003e generally harbors the complete key enzyme genes, including α-acetolactate synthase (ALS, EC 2.2.1.6) and α-acetolactate decarboxylase (ALDB, EC 4.1.1.5), these genes are usually inactive or expressed at low levels\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. In contrast, strain NZZ1 not only maintains a complete metabolic pathway, but also exhibits active expression of key enzyme genes that participate in catalytic regulation, thereby acting as the core catalytic node for 4-hydroxy-2-butanone synthesis and ultimately achieving efficient production of the characteristic flavor of yogurt.\u003c/p\u003e \u003cp\u003eSubsequently, a commercially available starter culture was incorporated as a control group in this study to comprehensively evaluate the performance of \u003cem\u003eL. lactis\u003c/em\u003e in terms of physicochemical properties, texture characteristics, and sensory quality. The results of the relevant analyses indicated that the three yogurt samples showed good discriminability. When used as a monoculture starter, \u003cem\u003eL. lactis\u003c/em\u003e NZZ1 exhibited significant advantages in milk fermentation. Its outstanding performance in physicochemical properties, texture, and sensory quality could be attributed to its unique metabolic regulatory network. Although the symbiotic system of traditional commercial starters (\u003cem\u003eLactobacillus bulgaricus\u003c/em\u003e and \u003cem\u003eStreptococcus thermophilus\u003c/em\u003e) can synergistically produce acids and aroma compounds, their metabolic flux distribution is relatively fixed. In contrast, strain NZZ1 demonstrated a more sophisticated metabolic balance capability, presumably by regulating lactate dehydrogenase activity or sugar transport rate, thus achieving a gentler acid production kinetic process. This is conducive to the formation of a uniform and dense three-dimensional casein gel network, which macroscopically manifests as higher hardness and water-holding capacity, as well as lower whey syneresis rate\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. Furthermore, this strain diverts a larger proportion of pyruvate toward the 4-hydroxy-2-butanone synthesis pathway, directly contributing to a rich creamy and cheesy aroma. More importantly, it exhibited high abundance and content of flavor compounds including alcohols, esters, and aromatic hydrocarbons. Together with taste-active substances such as amino acids, these compounds form a well-coordinated flavor profile, which mutually support and balance each other at their respective sensory thresholds, avoiding the predominance of a single odor, and ultimately yielding a flavor profile with rich layers and high acceptability\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. These findings demonstrate that a single strain can also achieve or even surpass the comprehensive effects of traditional starters in texture construction and complex flavor generation by optimizing its own metabolic flux distribution.\u003c/p\u003e \u003cp\u003eThe composition and synergistic interactions of microbial communities play a crucial role in regulating flavor compounds and driving the formation of key flavor characteristics\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. As traditional commercial starters, \u003cem\u003eLactobacillus bulgaricus\u003c/em\u003e and \u003cem\u003eStreptococcus thermophilus\u003c/em\u003e can ferment lactose through pyruvate metabolism to produce lactic acid and certain carbonyl compounds, thereby influencing yogurt flavor\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The results of validation experiments showed that the yield of 4-hydroxy-2-butanone in the co-fermentation group was significantly higher than that in the monoculture group. We preliminarily inferred that the co-culture system formed by combining the commercial starter with \u003cem\u003eL. lactis\u003c/em\u003e exhibits enhanced metabolic capacity, which strengthens the original pyruvate metabolism and its efficient accumulation\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The insufficient flux of pyruvate into the lactic acid synthesis pathway in a timely manner is one of the important reasons for the high-efficiency production of 4-hydroxy-2-butanone.\u003c/p\u003e \u003cp\u003eBased on the findings of this study and advances in current research, it is evident that \u003cem\u003eL. lactis\u003c/em\u003e has become a core functional microbial group in fermented milk production. However, its industrial application is still confronted with critical bottlenecks, including strain homogenization, monotonous product flavor profiles, and insufficient texture stability, with relatively few superior strains that simultaneously possess distinctive flavor and functional properties. Against this backdrop, this study isolated a \u003cem\u003eL. lactis\u003c/em\u003e strain with both excellent fermentation performance and high 4-hydroxy-2-butanone-producing capacity from naturally fermented dairy products. Combined with genomic approaches, we preliminarily elucidated the metabolic pathways associated with 4-hydroxy-2-butanone synthesis in this strain, and further verified its application potential in flavor development and fermentation performance that surpasses commercial starter cultures in the yogurt fermentation system.\u003c/p\u003e \u003cp\u003eIn the future, the targeted breeding of flavor-specialized lactic acid bacteria is expected to rely on multi-omics technologies for in-depth exploration of microbial resources from distinctive habitats. Meanwhile, gene editing and metabolic engineering tools can be employed to enhance the synthesis and regulation of key flavor compounds. In addition, innovative application strategies such as \u0026ldquo;starter-enzyme composite formulations\u0026rdquo; should be explored; for instance, the synergistic application of \u003cem\u003eL. lactis\u003c/em\u003e with Maillard reaction-related enzyme systems could degrade off-flavor substances while generating target characteristic aromas, thereby achieving the synergistic optimization of flavor, texture, and nutritional functions of fermented milk. Furthermore, to support these innovations, future research should elucidate key genes on a larger scale and establish correlations between strain genomes and flavor characteristics. Overall, this study provides an important strain foundation and theoretical reference for subsequent research on the targeted genetic modification of lactic acid bacteria to produce desired metabolites, as well as the development of novel biological flavors and personalized flavor starters.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMaterials and chemicals\u003c/h2\u003e \u003cp\u003eIn December 2024, samples were collected in pastoral areas of Xinjiang, Tibet, Inner Mongolia, and Yunnan in China, and were quickly placed in ice for transportation to the laboratory. M17 medium was purchased from Solebao Company (Beijing, China), lactose was purchased from Sinopharm Company (Beijing, China), and commercial starter cultures were purchased from Danisco (YO-MIX 300, Denmark), which included Streptococcus thermophilus and Lactobacillus bulgaricus. All other analytical grade chemicals were obtained from high-quality suppliers.\u003c/p\u003e \u003cp\u003e \u003cb\u003eScreening, strain identification and cultivation of\u003c/b\u003e \u003cb\u003eL.\u003c/b\u003e \u003cb\u003elactis\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAfter preprocessing the sample with a homogenizer (D-600Pro, WIGGENS, Beijing, China) 0.5 mL of the well-mixed sample was pipetted into 4.5 mL of 0.9% physiological saline to obtain a 10⁻\u0026sup1; dilution. Then, 0.5 mL of the 10⁻\u0026sup1; dilution was pipetted into 4.5 mL of physiological saline to get a 10⁻\u0026sup2; dilution. Following this procedure, 10⁻\u0026sup3;, 10⁻⁴, 10⁻⁵, and 10⁻⁶ dilutions were obtained in sequence. 100 \u0026micro;L each of the 10⁻⁴, 10⁻⁵, and 10⁻⁶ dilutions was taken and plated on MRS solid medium using a spreader. The plates were incubated in an aerobic incubator at 37\u0026deg;C for 48 hours. Typical single colonies were picked and streaked onto MRS solid medium plates using the three-zone streaking method for purification, followed by incubation in an aerobic incubator at 37\u0026deg;C for 48 hours. The purified single colonies were transferred to MRS liquid medium and cultured in an aerobic medium at 37\u0026deg;C for 24 hours. The bacterial suspension was preserved with 30% glycerol to obtain lactic acid bacteria. The genome of the isolated lactic acid bacteria was extracted, and the 16S rDNA of the strain was amplified and sequenced (completed by Sangon Biotech Co., Ltd., Shanghai, China). The sequence was aligned in GenBank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/genbank/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/genbank/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and finally, 50 strains with a homology of over 99% to \u003cem\u003eL. lactis\u003c/em\u003e were identified as \u003cem\u003eL. lactis\u003c/em\u003e. The aforementioned \u003cem\u003eL. lactis\u003c/em\u003e was inoculated onto LM17 solid medium and cultured in an aerobic incubator at 30\u0026deg;C for 48 hours, and the colony morphology was observed and recorded. The strain was subjected to Gram staining and observed under a inverted light microscope (Nikon, T1-SAM, Tokyo, Japan). \u003cem\u003eL. lactis\u003c/em\u003e was inoculated into LM17 liquid medium at an inoculum size of 2% (\u003cem\u003ev/v\u003c/em\u003e) and placed in a microplate reader (Multiskan SkyHigh, Shanghai, China), followed by aerobic cultivation at 30\u0026deg;C for 24 hours. During the cultivation, the OD₆₀₀ value of the bacterial suspension was measured every 1 hour to plot the growth curve. The microbial growth curve detection system (CLARIOstar Plus, BMG LABTECH, UK) was used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePreparation of Reconstituted Milk\u003c/h2\u003e \u003cp\u003eWeigh 110 g of skimmed milk powder and added it to 890 mL of sterile water. Stir with a high-speed homogenizer for 5 min to 10 min. After hydrating overnight at 4 ℃, perform pasteurization (105 ℃, 10 min) using a fully automatic vertical steam sterilizer (BONOVO, CT65A, Shanghai, China). Cool to 30 ℃ in a clean bench (Thermo fisher, Protect-1FD, USA) for later use, and 1 L of reconstituted skimmed milk with a mass fraction of 11% can be obtained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrain activation\u003c/h2\u003e \u003cp\u003eInoculate \u003cem\u003eL. lactis\u003c/em\u003e from the bacterial preservation tube into LM17 liquid medium at 2% (\u003cem\u003ev/v\u003c/em\u003e), and culture it in a 30\u0026deg;C constant temperature incubator for 18 hours to obtain the activated first generation. Continue to inoculate the bacterial liquid of the first generation into LM17 liquid medium at 2% (\u003cem\u003ev/v\u003c/em\u003e), and culture it in a 30\u0026deg;C constant temperature incubator for 18 hours to get the activated second generation. Repeat the above operation to obtain the activated third generation of \u003cem\u003eL. lactis.\u003c/em\u003e Inoculate the commercial starter into LM17 liquid medium at 2% (\u003cem\u003ev/v\u003c/em\u003e), and culture it in a 30\u0026deg;C constant temperature incubator for 24 hours to obtain the activated first generation. Continue to repeat the above operation to get the activated third generation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of the generation time (G) of bacterial strains\u003c/h2\u003e \u003cp\u003eGeneration time (G) refers to the time required for the number of bacterial cells to double during the logarithmic growth phase (a stage where cells proliferate at a constant exponential rate). Based on the previously plotted growth curve, in the logarithmic growth phase segment of the growth curve, selected two time points (\u003cb\u003et\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e、t\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e) and their corresponding cell concentrations (\u003cb\u003eN\u003c/b\u003e\u003csub\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e、N\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e), repeat the selection multiple times to take the average value to reduce errors. The conversion reference formula was Equation.1:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{G}=\\varvec{t}\\times\\:\\varvec{l}\\varvec{o}\\varvec{g}2/({\\varvec{l}\\varvec{o}\\varvec{g}\\varvec{N}}_{\\varvec{t}}-{\\varvec{l}\\varvec{o}\\varvec{g}\\varvec{N}}_{0})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eWhere\u003c/b\u003e, Generation Time (G); Incubation time (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{t}\\)\u003c/span\u003e\u003c/span\u003e); Initial cell count (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{N}}_{0}\\)\u003c/span\u003e\u003c/span\u003e); Start Formula Bold Italic Number of cells at time \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{t}\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{N}}_{\\varvec{t}}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of β-galactosidase Activity (GA)\u003c/h2\u003e \u003cp\u003eUse ONPG as the substrate. Inoculate the activated third-generation strain into LM17 medium at a ratio of 2% (\u003cem\u003ev/v\u003c/em\u003e), and culture it at a constant temperature of 30\u0026deg;C until the mid-logarithmic phase; draw a certain amount of bacterial liquid (recorded as V), and measure the absorbance of the bacterial liquid at 600 nm (recorded as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{OD}_{600}\\)\u003c/span\u003e\u003c/span\u003e), add 900 \u0026micro;L of Z buffer solution (60 mmol/L Na₂HPO₄, 40 mmol/L Na₂HPO₄, 10 mmol/L KCl, 1 mmol/L MgSO₄), add 10 \u0026micro;L of chloroform, and vortex thoroughly to obtain the crude enzyme solution, add 200 \u0026micro;L of substrate solution to the crude enzyme solution, place it at 30\u0026deg;C for constant temperature reaction and start timing, after 30 min, add 500 \u0026micro;L of 1 mol/L sodium carbonate solution to terminate the reaction; centrifuge the reaction solution at 10,000 r/min and 25\u0026deg;C for 5 min, take the supernatant to measure the absorbance at 420 nm (recorded as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{OD}_{420}\\)\u003c/span\u003e\u003c/span\u003e). β-galactosidase Activity (GA) is defined as the amount of enzyme required to release unit 2-nitrophenol from the substrate solution per unit time, which was calculated according to the following Equation.2:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{G}\\varvec{A}={(\\varvec{O}\\varvec{D}}_{600}\\times\\:\\varvec{V}\\times\\:30)/(1000\\times\\:{\\varvec{O}\\varvec{D}}_{420})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: β-galactosidase Activity \u003cb\u003e(GA)\u003c/b\u003e; Absorbance at 600 nm and 420 nm \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{O}\\varvec{D}}_{600}\\)\u003c/span\u003e\u003c/span\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{O}\\varvec{D}}_{420}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDetermination of Acid Production Rate (APR)\u003c/h2\u003e \u003cp\u003eThe rapid decrease in pH value was crucial during the fermentation process of fermented milk, as it was essential for coagulation and preventing or reducing the growth of harmful microorganisms\u003csup\u003e\u003cb\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/b\u003e\u003c/sup\u003e. The pH value at the fermentation endpoint of fermented milk was 4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2. Let the pH value at the initial stage of fermentation be denoted as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\mathbf{p}\\mathbf{H}}_{1}\\)\u003c/span\u003e\u003c/span\u003e, the pH value at the fermentation endpoint as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\mathbf{p}\\mathbf{H}}_{2}\\)\u003c/span\u003e\u003c/span\u003e, and the fermentation time as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{t}\\)\u003c/span\u003e\u003c/span\u003e. The acid production rate (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{A}\\varvec{P}\\varvec{R}\\)\u003c/span\u003e\u003c/span\u003e) was calculated according to Equation. \u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{A}\\text{P}\\text{R}={(\\mathbf{p}\\mathbf{H}}_{1}-{\\mathbf{p}\\mathbf{H}}_{2})/\\text{t}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eWhere\u003c/b\u003e: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{A}\\varvec{c}\\varvec{i}\\varvec{d}\\:\\varvec{P}\\varvec{r}\\varvec{o}\\varvec{d}\\varvec{u}\\varvec{c}\\varvec{t}\\varvec{i}\\varvec{o}\\varvec{n}\\:\\varvec{R}\\varvec{a}\\varvec{t}\\varvec{e}\\)\u003c/span\u003e\u003c/span\u003e \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{A}\\varvec{P}\\varvec{R}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e);\u003c/b\u003e The pH value at the initial stage of fermentation \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\mathbf{p}\\mathbf{H}}_{2}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e);\u003c/b\u003e The pH value at the fermentation endpoint \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\mathbf{p}\\mathbf{H}}_{1}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eL. lactis\u003c/em\u003e activated for three generations was centrifuged at 6000 r/min and 4\u0026deg;C for 5 min. The supernatant was discarded, and the initial inoculum concentration in the fermentation system was controlled at 3\u0026times;10⁶ CFU/mL. An equal volume of normal saline was added to the bacterial suspension, which was then centrifuged again at 6000 r/min and 4\u0026deg;C for 5 min. The supernatant was discarded, and this operation was repeated to obtain bacterial pellets washed with normal saline 2\u0026ndash;3 times. An appropriate volume of reconstituted skim milk was added to resuspend the bacterial pellets, ensuring a homogeneous system. The resuspended \u003cem\u003eL. lactis\u003c/em\u003e was inoculated into reconstituted skim milk and incubated in a constant-temperature incubator at 30\u0026deg;C. Samples were taken every 2 h to determine the pH value of the bacterial suspension, with the final sampling point at 12 h post-fermentation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eTOPSIS entropy weight method screening\u003c/h2\u003e \u003cp\u003eTaking acid production rate, β-galactosidase activity, and metabolism as the core evaluation indicators, high-quality strain screening was performed by combining the entropy weight method and TOPSIS model using the entropy and TOPSIS packages in R software (Version 4.2.1).\u003c/p\u003e \u003cp\u003eFirst, an \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:n\\times\\:3\\)\u003c/span\u003e\u003c/span\u003e dimensional strain evaluation matrix was constructed. The range standardization method was applied to eliminate the dimensional differences of indicators for positive and negative indicators using Equation. \u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Equation. \u003cspan refid=\"Equ5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, respectively:\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{x}}_{\\varvec{i}\\varvec{j}}^{+}=\\frac{{\\varvec{x}}_{\\varvec{i}\\varvec{j}}-\\varvec{m}\\varvec{i}\\varvec{n}\\left({\\varvec{x}}_{\\varvec{j}}\\right)}{\\varvec{m}\\varvec{a}\\varvec{x}\\left({\\varvec{x}}_{\\varvec{j}}\\right)-\\varvec{m}\\varvec{i}\\varvec{n}\\left({\\varvec{x}}_{\\varvec{j}}\\right)}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{x}}_{\\varvec{i}\\varvec{j}}^{-}=\\frac{\\varvec{m}\\varvec{a}\\varvec{x}\\left({\\varvec{x}}_{\\varvec{j}}\\right)-{\\varvec{x}}_{\\varvec{i}\\varvec{j}}}{\\varvec{m}\\varvec{a}\\varvec{x}\\left({\\varvec{x}}_{\\varvec{j}}\\right)-\\varvec{m}\\varvec{i}\\varvec{n}\\left({\\varvec{x}}_{\\varvec{j}}\\right)}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{x}}_{\\varvec{i}\\varvec{j}}\\:\\)\u003c/span\u003e\u003c/span\u003erepresents the original value of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{j}\\)\u003c/span\u003e\u003c/span\u003e indicator for the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{i}\\)\u003c/span\u003e\u003c/span\u003e strain; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{m}\\varvec{a}\\varvec{x}\\left({\\varvec{x}}_{\\varvec{j}}\\right),\\varvec{m}\\varvec{i}\\varvec{n}\\left({\\varvec{x}}_{\\varvec{j}}\\right)\\)\u003c/span\u003e\u003c/span\u003e denote the maximum and minimum values of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{j}\\)\u003c/span\u003e\u003c/span\u003e indicator, respectively.\u003c/p\u003e \u003cp\u003eThe weight of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{i}\\)\u003c/span\u003e\u003c/span\u003e strain under the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{j}\\)\u003c/span\u003e\u003c/span\u003e indicator was calculated using Equation Equation. \u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{P}}_{\\varvec{i}\\varvec{j}}={\\varvec{x}}_{\\varvec{i}\\varvec{j}}/\\sum\\:_{\\varvec{i}=1}^{\\varvec{n}}{\\varvec{x}}_{\\varvec{i}\\varvec{j}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: The weight of the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{i}\\)\u003c/span\u003e\u003c/span\u003e strain under the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\varvec{j}\\)\u003c/span\u003e\u003c/span\u003e indicator (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{P}}_{\\varvec{i}\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe indicator entropy values and weights were calculated using Equation. \u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and Equation. \u003cspan refid=\"Equ8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, respectively. The weight results reflect the objective contribution of each indicator to strain screening.\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{e}}_{\\varvec{j}}=-\\varvec{k}\\sum\\:_{\\varvec{i}=1}^{\\varvec{n}}{\\varvec{p}}_{\\varvec{i}\\varvec{j}}\\varvec{l}\\varvec{n}\\left({\\varvec{p}}_{\\varvec{i}\\varvec{j}}\\right)\\:(\\varvec{k}=1/\\varvec{l}\\varvec{n}(\\varvec{n}),\\:\\varvec{i}\\varvec{f}\\:{\\varvec{p}}_{\\varvec{i}\\varvec{j}}=0,\\:\\varvec{t}\\varvec{h}\\varvec{e}\\varvec{n}\\:\\varvec{l}\\varvec{n}({\\varvec{p}}_{\\varvec{i}\\varvec{j}}=0\\left)\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ8\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ8\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{w}}_{\\varvec{j}}=(1-{\\varvec{e}}_{\\varvec{j}})/\\sum\\:_{\\varvec{i}=1}^{3}(1-{\\varvec{e}}_{\\varvec{j}})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: The indicator entropy values (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{e}}_{\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e); The indicator weights (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{w}}_{\\varvec{j}}\\)\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the weighted standardized matrix (standardized values\u0026times;entropy weights), the positive ideal solution and negative ideal solution were determined using Equations Equation. \u003cspan refid=\"Equ9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and Equation. \u003cspan refid=\"Equ10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, and the Euclidean distances from each strain to the positive and negative ideal solutions were calculated.\u003cdiv id=\"Equ9\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ9\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{Z}}^{+}=\\left(\\varvec{m}\\varvec{a}\\varvec{x}\\right({\\varvec{w}}_{\\varvec{j}}{\\varvec{x}}_{\\varvec{i}\\varvec{j}}\\left)\\right)\\:{\\varvec{D}}_{\\varvec{i}}^{+}=\\sqrt{{\\sum\\:_{\\varvec{i}=1}^{3}({\\varvec{w}}_{\\varvec{j}}{\\varvec{x}}_{\\varvec{i}\\varvec{j}}-{\\varvec{Z}}_{\\varvec{j}}^{+})}^{2}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ10\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ10\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{Z}}^{-}=\\left(\\varvec{m}\\varvec{a}\\varvec{x}\\right({\\varvec{w}}_{\\varvec{j}}{\\varvec{x}}_{\\varvec{i}\\varvec{j}}\\left)\\right)\\:{\\varvec{D}}_{\\varvec{i}}^{-}=\\sqrt{{\\sum\\:_{\\varvec{i}=1}^{3}({\\varvec{w}}_{\\varvec{j}}{\\varvec{x}}_{\\varvec{i}\\varvec{j}}-{\\varvec{Z}}_{\\varvec{j}}^{-})}^{2}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Positive ideal solutions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{Z}}^{+}\\)\u003c/span\u003e\u003c/span\u003e); Negative ideal solutions (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{Z}}^{-}\\)\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, the comprehensive closeness degree was calculated using Equation. \u003cspan refid=\"Equ11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. The value of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{C}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e ranges from 0 to 1, with values closer to 1 indicating superior comprehensive performance of the strain. Based on this, high-quality target strains were selected.\u003cdiv id=\"Equ11\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ11\" name=\"EquationSource\"\u003e\n$$\\:{\\varvec{C}}_{\\varvec{i}}={\\varvec{D}}_{\\varvec{i}}^{-}/({\\varvec{D}}_{\\varvec{i}}^{-}+{\\varvec{D}}_{\\varvec{i}}^{+})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Comprehensive closeness degree (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{C}}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of volatile flavor compounds\u003c/h2\u003e \u003cp\u003eThe volatile flavor compounds of the target strains were determined using a gas chromatography/mass spectrometry (GC/MS) system (Thermo Fisher Scientific, Trace 1300, USA). Briefly, 6 g of sample was placed in a 20 mL extraction vial, and 1 g of sodium chloride was added. The sample was equilibrated at 50\u0026deg;C for 30 min, after which the fiber probe was inserted into the sealed extraction vial and exposed to the headspace above the sample for 5 min.\u003c/p\u003e \u003cp\u003eChromatographic conditions: An RTX-Wax capillary column (30 m\u0026times;0.25 mm, 0.25 \u0026micro;m) was used. The temperature program was as follows: initial temperature of 30\u0026deg;C held for 3 min, then increased to 225\u0026deg;C at a rate of 15\u0026deg;C/min and held for 5 min. The carrier gas was helium (He) with a flow rate of 1 mL/min. The injector temperature was set at 225\u0026deg;C, the injection volume was 1 \u0026micro;L, and the split ratio was 10:1.Mass spectrometric conditions: Electron ionization (EI) mode was employed with an ionization energy of 70 eV and an emission current of 200 \u0026micro;A. The detector voltage was set at 1.4 kV. The ion source temperature was maintained at 240\u0026deg;C, the interface temperature at 230\u0026deg;C, and the quadrupole temperature at 150\u0026deg;C. The mass spectral scanning range was m/z 30\u0026ndash;500.\u003c/p\u003e \u003cp\u003eQualitative analysis was performed by comparing the results with the NIST2001 standard spectral library, and quantitative analysis was conducted via peak area normalization. All measurements were performed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eStrain sequencing\u003c/h2\u003e \u003cp\u003eThe target strains were inoculated into LM17 liquid medium at an inoculum size of 2% (\u003cem\u003ev/v\u003c/em\u003e) and cultured for 12\u0026ndash;18 h. The bacterial cells were harvested by centrifugation at 6,000 r/min for 5 min, and genomic DNA was extracted using a DNA extraction kit. A genomic library was constructed from the bacterial DNA, and sequencing was performed on the Illumina NovaSeq PE150 platform (Beijing Novogene Bioinformatics Technology Co., Ltd., Beijing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of the physicochemical properties of fermented milk\u003c/h2\u003e \u003cp\u003eThe pH and titratable acidity of yogurt were determined according to the method previously described by Liu et al.\u003cb\u003e\u0026sup1;⁹\u003c/b\u003e. During milk fermentation, the pH was measured at predetermined time intervals using a pH meter (DZS-706F, Shanghai, China), and the stable pH value was recorded to analyze the acidification capacity.\u003c/p\u003e \u003cp\u003eTitratable acidity was performed using a 0.1 mol/L standard sodium hydroxide solution. The procedure was as follows: 2 g of fermented milk was accurately weighed into a 50 mL Erlenmeyer flask at each predetermined time interval, and the mass m of the fermented milk was precisely recorded. An appropriate volume of distilled water was added, followed by two drops of 0.5% phenolphthalein solution as an indicator; the mixture was then shaken thoroughly. Titration was carried out with the 0.1 mol/L standard sodium hydroxide solution until a faint red color appeared in the solution and persisted for at least 30 seconds. The volume of the consumed standard NaOH solution was recorded. The results were expressed as titratable acidity AT (\u0026deg;T) using Equation. \u003cspan refid=\"Equ12\" class=\"InternalRef\"\u003e12\u003c/span\u003e, as follows:\u003cdiv id=\"Equ12\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ12\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{T}\\varvec{A}={(\\varvec{V}}_{1}-{\\varvec{V}}_{0})/(\\varvec{m}\\times\\:0.1)\\times\\:\\varvec{c}\\times\\:100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e12\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Titratable Acidity (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:TA\\)\u003c/span\u003e\u003c/span\u003e); Molar concentration of NaOH standard solution (0.1022 mol/L) (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:c\\)\u003c/span\u003e\u003c/span\u003e); The volume (mL) of NaOH standard solution consumed in titrating the sample (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{1}\\)\u003c/span\u003e\u003c/span\u003e); The volume (mL) of NaOH standard solution consumed in the titration blank (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{V}_{0}\\)\u003c/span\u003e\u003c/span\u003e); The quality (g) of fermented milk samples (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:m\\)\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eWater holding capacity and syneresis of fermented milk\u003c/h2\u003e \u003cp\u003eThe measurement was performed using set yogurt without stirring after ripening. An aliquot of 20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 g of yogurt sample was weighed into a 50.00 mL centrifuge tube and centrifuged at 640\u0026times;g and 4\u0026deg;C for 10 min using a centrifuge (Eppendorf, Centrifuge 5424, Germany). The mass of the was weighed, and the syneresis (%) was calculated according to Equation. \u003cspan refid=\"Equ13\" class=\"InternalRef\"\u003e13\u003c/span\u003e:\u003cdiv id=\"Equ13\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ13\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{s}\\varvec{y}\\varvec{n}\\varvec{e}\\varvec{r}\\varvec{e}\\varvec{s}\\varvec{i}\\varvec{s}={\\varvec{M}}_{1}/{\\varvec{m}}_{1}\\times\\:100\\varvec{\\%}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e13\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Yogurt quality \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{m}}_{1}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e);\u003c/b\u003e The quality of the supernatant whey \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{M}}_{1}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe water holding capacity (WHC) of yogurt was determined according to the method described in previous studies, with appropriate modifications following the protocol reported by D. Dhakal et al\u003csup\u003e\u003cb\u003e43\u003c/b\u003e\u003c/sup\u003e. The set yogurt after ripening was centrifuged at 1250\u0026times;g and 4\u0026deg;C for 10 min. The supernatant was discarded, and the centrifuge tube was inverted for 2 h to completely drain the whey. The precipitate was carefully collected and weighed, and the water holding capacity of the fermented milk was calculated according to Equation. \u003cspan refid=\"Equ14\" class=\"InternalRef\"\u003e14\u003c/span\u003e.\u003cdiv id=\"Equ14\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ14\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{W}\\varvec{H}\\varvec{C}\\left(\\varvec{\\%}\\right)={\\varvec{m}}_{2}/{\\varvec{M}}_{2}\\times\\:100\\varvec{\\%}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e14\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere: Yogurt quality \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{m}}_{2}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e);\u003c/b\u003e The quality of precipitate \u003cb\u003e(\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\varvec{M}}_{1}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eTexture determination of fermented milk\u003c/h2\u003e \u003cp\u003eThe texture analysis was performed with appropriate modifications according to the method described by A. Abdelazez et al\u003csup\u003e\u003cb\u003e48\u003c/b\u003e\u003c/sup\u003e. The set yogurt after ripening was removed from the refrigerator at 4\u0026deg;C and equilibrated at room temperature. When the temperature of the yogurt reached 10\u0026deg;C, the texture properties were determined using a Texture Analyzer (Stable Micro Systems Ltd, UK). The test sample was prepared by placing 50 g of yogurt into a 50 mL test container. The measured texture parameters included hardness, adhesiveness, gumminess, cohesiveness, and chewiness. The determination was carried out using a P/36R cylindrical probe under standardized conditions: a test speed of 1.0 mm/s, a penetration depth of 10 mm, and a sampling rate of 400 pps.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eSensory evaluation of fermented milk\u003c/h2\u003e \u003cp\u003eSensory evaluation of CSB was conducted according to Chinese standard GB/T 23776\u0026ndash;2018, with modifications based on Yue and Zhou et al\u003csup\u003e49,50\u003c/sup\u003e. The sensory panel comprised 20 trained individuals (10 males and 10 females) aged between 22 and 30 years, all of whom are currently graduate students at Jiangnan University. All participants were non-smokers and had no known diseases, especially those related to the oral and olfactory organs. They were fully informed about the purpose of the study and provided written consent to participate in the experiment. The study protocol received approval from the Medical Ethics Committee of Jiangnan University (JNU202409RB0056), ensuring adherence to ethical standards in human research. Prior to the sensory assessment, training sessions were conducted for the panelists. These sessions facilitated the identification and refinement of the sensory attributes of the samples, occurring four times a week over a two week period, with each session lasting one hour\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Before starting, all volunteers received basic sensory training, were familiar with the 9-point hedonic scale, and were free from symptoms such as colds or respiratory infections that might impair taste and olfactory functions. Within 24 hours prior to the evaluation, volunteers were prohibited from consuming strong-flavored foods, and no food intake was allowed 1 hour before the test.\u003c/p\u003e \u003cp\u003eThe three groups of fermented milk samples were stored under refrigeration at 4\u0026deg;C. Prior to the test, the samples were equilibrated at room temperature (22\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C) for 30 minutes. Each sample, with a volume of 50 mL, was placed in a white plastic cup of uniform specifications and labeled with a random three-digit code. Sensory evaluation was conducted in a standardized sensory laboratory with adequate lighting, good ventilation, and free from extraneous odors. Each evaluation station was equipped with drinking water, soda crackers for palate cleansing, as well as score sheets and pens. The 9-point hedonic scale was adopted, where a score of 1 represented extremely poor and a score of 9 represented excellent. The evaluation indices included 11 dimensions: sourness, sweetness, astringency, bitterness, fishy odor, yogurt-like aroma, whey syneresis, hardness, consistency, viscosity and liking degree. Volunteers evaluated the three groups of samples sequentially; between each evaluation, they rinsed their mouths with warm water and waited for an interval of 3 min. The evaluation duration for each sample was no less than 2 min. After the completion of the evaluation, the score sheets from all 20 volunteers were collected for subsequent statistical analysis.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll experimental results were expressed as \u003cb\u003emean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD, n\u0026thinsp;\u0026ge;\u0026thinsp;3)\u003c/b\u003e. The corresponding significance analysis was performed via one-way analysis of variance (ANOVA) and Duncan\u0026rsquo;s multiple range test using SPSS 21.0. A value of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Data visualization was conducted using Origin 2024 and GraphPad Prism 9.5.0. Multiple tools were employed for bioinformatics analysis, including filtering sequence reads from each dataset and performing de novo assembly of high-quality paired-end reads using SPAdes v.3.13 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cab.spbu.ru/software/spades/\u003c/span\u003e\u003cspan address=\"http://cab.spbu.ru/software/spades/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The genome of the target strain was visualized using Proksee software (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://proksee.ca\u003c/span\u003e\u003cspan address=\"https://proksee.ca\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). For gene annotation, prediction of gene functions, and characterization of enzyme systems related to carbohydrate metabolism, functional annotation of the genome was performed using EggNOG-mapper v2.1.3. The target protein sequences were aligned against the protein sequences in the EggNOG database via the DIAMOND blastp algorithm, with annotation completed using multi-threaded parallel computing. Online database annotations were carried out using the Kyoto Encyclopedia of Genes and Genomes (KEGG; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Carbohydrate-Active enZYmes (CAZyme; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.cazy.org/\u003c/span\u003e\u003cspan address=\"http://www.cazy.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The related data graphs were plotted using R software (Version 4.2.1). Multivariate statistical analyses (OPLS-DA and PCA) were performed on the LC-Bio platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.lc-bio.com\u003c/span\u003e\u003cspan address=\"https://www.lc-bio.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Flow charts were constructed using Microsoft Visio 2025.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eNo datasets were generated or analyzed during the course of this study.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWriting\u0026ndash;original draft: C.Z., H.Y.S. Writing\u0026ndash;review and editing: C.Z., F.W.T., X.M.L., G.W., B.Y., S.M.C., W.W.L., Q.X.Z. Conceptualization and supervision: W.C. and Q.X.Z. Data analysis: C.Z., H.Y.S., Q.X.Z. Data acquisition, C.Z., H.Y.S., Q.X.Z.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Key Research and Development Project [No. 2022YFD2100703 and 2024YFD2100901]; the National Natural Science Foundation of China [No. U23A20259]; and the Fundamental Research Funds for the Central Universities JUSRP622013.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbi Khalil, R. \u003cem\u003eet al.\u003c/em\u003e Traditional fermented milk products of Eastern Mediterranean countries: A cultural heritage to preserve. \u003cem\u003eInternational Dairy Journal\u003c/em\u003e 147, 105768 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.idairyj.2023.105768\u003c/span\u003e\u003cspan address=\"10.1016/j.idairyj.2023.105768\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNarvhus, J. A. \u0026amp; Abrahamsen, R. K. Traditional and modern Nordic fermented milk products: A review. \u003cem\u003eInternational Dairy Journal\u003c/em\u003e 142, 105641 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.idairyj.2023.105641\u003c/span\u003e\u003cspan address=\"10.1016/j.idairyj.2023.105641\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, D. \u003cem\u003eet al.\u003c/em\u003e Comparative study of yak and cow milk fermented with auxiliary cultures: Physicochemical, microstructural, and flavor profiles. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 108, 10662\u0026ndash;10676 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2025-26842\u003c/span\u003e\u003cspan address=\"10.3168/jds.2025-26842\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarco, M. L. \u003cem\u003eet al.\u003c/em\u003e The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on fermented foods. \u003cem\u003eNature Reviews Gastroenterology \u0026amp; Hepatology\u003c/em\u003e 18, 196\u0026ndash;208 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41575-020-00390-5\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41575-020-00390-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBai, Y. \u003cem\u003eet al.\u003c/em\u003e Flavor profile of milks fermented with six starter cultures. \u003cem\u003eJournal of Food Composition and Analysis\u003c/em\u003e 148, 108191 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jfca.2025.108191\u003c/span\u003e\u003cspan address=\"10.1016/j.jfca.2025.108191\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBikheet, M. M. \u003cem\u003eet al.\u003c/em\u003e Effects of clove (Syzygium aromaticum) extract on antibacterial activity, phytochemical properties, and storage quality of flavored milk beverages. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 108, 3300\u0026ndash;3313 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2024-26023\u003c/span\u003e\u003cspan address=\"10.3168/jds.2024-26023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGezginc, Y., Topcal, F., Comertpay, S. \u0026amp; Akyol, I. Quantitative analysis of the lactic acid and acetaldehyde produced by Streptococcus thermophilus and Lactobacillus bulgaricus strains isolated from traditional Turkish yogurts using HPLC. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 98, 1426\u0026ndash;1434 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2014-8447\u003c/span\u003e\u003cspan address=\"10.3168/jds.2014-8447\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorges, T. J., Gutarra, M. L. E. \u0026amp; Melo, L. Importance of information on fermented dairy beverages on choices of specific consumers. \u003cem\u003eFood Research International\u003c/em\u003e 217, 116728 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodres.2025.116728\u003c/span\u003e\u003cspan address=\"10.1016/j.foodres.2025.116728\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohansen, E., \u0026Oslash;regaard, G., S\u0026oslash;rensen, K. I. \u0026amp; Derkx, P. M. F. in \u003cem\u003eAdvances in Fermented Foods and Beverages\u003c/em\u003e (ed Wilhelm Holzapfel) 227\u0026ndash;248 (Woodhead Publishing, 2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCelik, O. F. \u0026amp; Temiz, H. Lactobacilli isolates as potential aroma producer starter cultures: Effects on the chemical, physical, microbial, and sensory properties of yogurt. \u003cem\u003eFood Bioscience\u003c/em\u003e 48, 101802 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fbio.2022.101802\u003c/span\u003e\u003cspan address=\"10.1016/j.fbio.2022.101802\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJingjing, E., Zhang, Y. \u0026amp; Yang, R. Impact of metabolite transformations on off-flavor profiles of pasteurized drinking yogurt in non-microbial conditions. \u003cem\u003eLWT\u003c/em\u003e 217, 117359 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lwt.2025.117359\u003c/span\u003e\u003cspan address=\"10.1016/j.lwt.2025.117359\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuan, Y., Cui, Y., Qu, X., Li, B. \u0026amp; Zhang, L. Post-acidification of fermented milk and its molecular regulatory mechanism. \u003cem\u003eInternational Journal of Food Microbiology\u003c/em\u003e 426, 110920 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ijfoodmicro.2024.110920\u003c/span\u003e\u003cspan address=\"10.1016/j.ijfoodmicro.2024.110920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBendig, T. \u003cem\u003eet al.\u003c/em\u003e The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model. \u003cem\u003eJournal of Biotechnology\u003c/em\u003e 374, 90\u0026ndash;100 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbiotec.2023.08.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jbiotec.2023.08.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu, X. \u003cem\u003eet al.\u003c/em\u003e Effect of different isolation sources of Lactococcus lactis subsp. lactis on volatile metabolites in fermented milk. \u003cem\u003eFood Chemistry: X\u003c/em\u003e 21, 101224 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fochx.2024.101224\u003c/span\u003e\u003cspan address=\"10.1016/j.fochx.2024.101224\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, Z., Zhang, Y., Simpson, D. J. \u0026amp; G\u0026auml;nzle, M. G. A phylogenetic perspective on the performance of Lactococcus lactis as starter culture in milk and plant milks. \u003cem\u003eFood Research International\u003c/em\u003e 221, 117562 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodres.2025.117562\u003c/span\u003e\u003cspan address=\"10.1016/j.foodres.2025.117562\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyad, E. H. E., Verheul, A., de Jong, C., Wouters, J. T. M. \u0026amp; Smit, G. Flavour forming abilities and amino acid requirements of Lactococcus lactis strains isolated from artisanal and non-dairy origin. \u003cem\u003eInternational Dairy Journal\u003c/em\u003e 9, 725\u0026ndash;735 (1999). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0958-6946(99)00140-5\u003c/span\u003e\u003cspan address=\"10.1016/S0958-6946(99)00140-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, C. \u003cem\u003eet al.\u003c/em\u003e Characterization of metabolic pathways for biosynthesis of the flavor compound 3-methylbutanal by Lactococcus lactis. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 105, 97\u0026ndash;108 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2021-20779\u003c/span\u003e\u003cspan address=\"10.3168/jds.2021-20779\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErcolini, D., Moschetti, G., Blaiotta, G. \u0026amp; Coppola, S. The potential of a polyphasic PCR-dGGE approach in evaluating microbial diversity of natural whey cultures for water-buffalo Mozzarella cheese production: bias of culture-dependent and culture-independent analyses. \u003cem\u003eSyst Appl Microbiol\u003c/em\u003e 24, 610\u0026ndash;617 (2001). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1078/0723-2020-00076\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1078/0723-2020-00076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSikombe, T. W., Moonga, H. B., Linnemann, A. R., Smid, E. J. \u0026amp; Schoustra, S. E. The effect of storage temperature on the physicochemical characteristics, volatile compounds and microbial community of a traditionally fermented dairy product. \u003cem\u003eLWT\u003c/em\u003e 227, 118035 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lwt.2025.118035\u003c/span\u003e\u003cspan address=\"10.1016/j.lwt.2025.118035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong, Y. \u003cem\u003eet al.\u003c/em\u003e Genetic diversity and population structure of Lactobacillus delbrueckii subspecies bulgaricus isolated from naturally fermented dairy foods. \u003cem\u003eSci Rep\u003c/em\u003e 6, 22704 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/srep22704\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/srep22704\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOshiro, M., Zendo, T. \u0026amp; Nakayama, J. Diversity and dynamics of sourdough lactic acid bacteriota created by a slow food fermentation system. \u003cem\u003eJournal of Bioscience and Bioengineering\u003c/em\u003e 131, 333\u0026ndash;340 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbiosc.2020.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.jbiosc.2020.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, H. \u003cem\u003eet al.\u003c/em\u003e Analysis of biogenic amines in salt-reduced Harbin dry sausages: From the perspective of free amino acid profile and bacterial community composition. \u003cem\u003eLWT\u003c/em\u003e 216, 117327 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lwt.2025.117327\u003c/span\u003e\u003cspan address=\"10.1016/j.lwt.2025.117327\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartins, E. \u003cem\u003eet al.\u003c/em\u003e Determination of ideal water activity and powder temperature after spray drying to reduce Lactococcus lactis cell viability loss. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 102, 6013\u0026ndash;6022 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2019-16297\u003c/span\u003e\u003cspan address=\"10.3168/jds.2019-16297\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShen, X. \u003cem\u003eet al.\u003c/em\u003e Metabolomics analysis reveals differences in milk metabolism and fermentation rate between individual Lactococcus lactis subsp. lactis strains. \u003cem\u003eFood Research International\u003c/em\u003e 162, 111920 (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodres.2022.111920\u003c/span\u003e\u003cspan address=\"10.1016/j.foodres.2022.111920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Carvalho, C. F. \u0026amp; Planidin, N. P. in \u003cem\u003eEncyclopedia of Evolutionary Biology (Second Edition)\u003c/em\u003e (eds Jason B. Wolf \u0026amp; Claudia Augusta De Moraes Russo) 110\u0026ndash;126 (Academic Press, 2026).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, W. \u003cem\u003eet al.\u003c/em\u003e Global genomics of Lactococcus lactis: horizontal gene transfer and intergenic variation drive multiple domestication and dairy adaptation. \u003cem\u003eJournal of Advanced Research\u003c/em\u003e (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jare.2025.07.053\u003c/span\u003e\u003cspan address=\"10.1016/j.jare.2025.07.053\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWusigale \u003cem\u003eet al.\u003c/em\u003e Comparative genomics and untargeted metabolomics analysis of dairy-derived Lacticaseibacillus rhamnosus strains and their potential applications in dairy fermentation. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 108, 6814\u0026ndash;6827 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.2025-26446\u003c/span\u003e\u003cspan address=\"10.3168/jds.2025-26446\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHadef, S., Idoui, T., Sifour, M., Genay, M. \u0026amp; Dary-Mourot, A. Screening of Wild Lactic Acid Bacteria from Algerian Traditional Cheeses and Goat Butter to Develop a New Probiotic Starter Culture. \u003cem\u003eProbiotics and Antimicrobial Proteins\u003c/em\u003e 15, 387\u0026ndash;399 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1007/s12602-022-10000-2\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1007/s12602-022-10000-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbushelaibi, A., Al-Mahadin, S., El-Tarabily, K., Shah, N. P. \u0026amp; Ayyash, M. Characterization of potential probiotic lactic acid bacteria isolated from camel milk. \u003cem\u003eLWT - Food Science and Technology\u003c/em\u003e 79, 316\u0026ndash;325 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.lwt.2017.01.041\u003c/span\u003e\u003cspan address=\"10.1016/j.lwt.2017.01.041\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdalatian Dovom, M. R. \u003cem\u003eet al.\u003c/em\u003e Screening of lactic acid bacteria strains isolated from Iranian traditional dairy products for GABA production and optimization by response surface methodology. \u003cem\u003eSci Rep\u003c/em\u003e 13, 440 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41598-023-27658-5\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41598-023-27658-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan, Q. \u003cem\u003eet al.\u003c/em\u003e Research on TOPSIS multi-indicator evaluation model based on entropy weight method for C2N site selection. \u003cem\u003eAnnals of Nuclear Energy\u003c/em\u003e 221, 111566 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anucene.2025.111566\u003c/span\u003e\u003cspan address=\"10.1016/j.anucene.2025.111566\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZare Banadkouki, M. R. Selection of strategies to improve energy efficiency in industry: A hybrid approach using entropy weight method and fuzzy TOPSIS. \u003cem\u003eEnergy\u003c/em\u003e 279, 128070 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.energy.2023.128070\u003c/span\u003e\u003cspan address=\"10.1016/j.energy.2023.128070\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian, H., Xiong, J., Yu, H., Chen, C. \u0026amp; Lou, X. Flavor optimization in dairy fermentation: From strain screening and metabolic diversity to aroma regulation. \u003cem\u003eTrends in Food Science \u0026amp; Technology\u003c/em\u003e 141, 104194 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tifs.2023.104194\u003c/span\u003e\u003cspan address=\"10.1016/j.tifs.2023.104194\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFr\u0026eacute;tin, M. \u003cem\u003eet al.\u003c/em\u003e Bacterial community assembly from cow teat skin to ripened cheeses is influenced by grazing systems. \u003cem\u003eScientific Reports\u003c/em\u003e 8, 200 (2018). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41598-017-18447-y\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41598-017-18447-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi, K. \u003cem\u003eet al.\u003c/em\u003e Sortase A-mediated crosslinked short-chain dehydrogenases/reductases as novel biocatalysts with improved thermostability and catalytic efficiency. \u003cem\u003eScientific Reports\u003c/em\u003e 7, 3081 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41598-017-03168-z\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41598-017-03168-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo, X. \u003cem\u003eet al.\u003c/em\u003e A short-chain carbonyl reductase mutant is an efficient catalyst in the production of (R)-1,3-butanediol. \u003cem\u003eMicrob Biotechnol\u003c/em\u003e 16, 1333\u0026ndash;1343 (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1111/1751-7915.14249\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1111/1751-7915.14249\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng, R. C., Ge, Z., Qiu, Z. K., Wang, Y. S. \u0026amp; Zheng, Y. G. Asymmetric synthesis of (R)-1,3-butanediol from 4-hydroxy-2-butanone by a newly isolated strain Candida krusei ZJB-09162. \u003cem\u003eAppl Microbiol Biotechnol\u003c/em\u003e 94, 969\u0026ndash;976 (2012). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1007/s00253-012-3942-2\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1007/s00253-012-3942-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBassett, E. W. \u0026amp; Harper, W. J. Isolation and Identification of Acidic and Neutral Carbonyl Compounds in Different Varieties of Cheese1, 2. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e 41, 1206\u0026ndash;1217 (1958). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3168/jds.S0022-0302(58)91076-2\u003c/span\u003e\u003cspan address=\"10.3168/jds.S0022-0302(58)91076-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorita, H. \u003cem\u003eet al.\u003c/em\u003e Complete genome sequence and comparative analysis of the fish pathogen Lactococcus garvieae. \u003cem\u003ePLoS One\u003c/em\u003e 6, e23184 (2011). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1371/journal.pone.0023184\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1371/journal.pone.0023184\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzizan, K. A., Ressom, H. W., Mendoza, E. R. \u0026amp; Baharum, S. N. (13)C based proteinogenic amino acid (PAA) and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP) pathway in response to agitation and temperature related stresses. \u003cem\u003ePeerJ\u003c/em\u003e 5, e3451 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.7717/peerj.3451\u003c/span\u003e\u003cspan address=\"https://doi.org:10.7717/peerj.3451\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGalv\u0026atilde;o, L. C., Fernandes, M. I. \u0026amp; Sawamura, R. [Lactose content and beta-galactosidase activity in yogurt, cheeses and curdled milk made in Brazil]. \u003cem\u003eArq Gastroenterol\u003c/em\u003e 32, 8\u0026ndash;14 (1995).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang, M., Chen, R., Mu, T., Zhang, X. \u0026amp; Xing, J. Switch on a more efficient pyruvate synthesis pathway based on transcriptome analysis and metabolic evolution. \u003cem\u003eJournal of Bioscience and Bioengineering\u003c/em\u003e 124, 523\u0026ndash;527 (2017). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jbiosc.2017.06.004\u003c/span\u003e\u003cspan address=\"10.1016/j.jbiosc.2017.06.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhakal, D., Kumar, G., Devkota, L., Subedi, D. \u0026amp; Dhital, S. The choice of probiotics affects the rheological, structural, and sensory attributes of lupin-oat-based yoghurt. \u003cem\u003eFood Hydrocolloids\u003c/em\u003e 156, 110353 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodhyd.2024.110353\u003c/span\u003e\u003cspan address=\"10.1016/j.foodhyd.2024.110353\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan, X. Y., Sun, D. Q., Xiang, L., Huo, G. C. \u0026amp; Jiang, Y. J. [Gene regulation to lactic acid bacteria for increasing production of flavor metabolite]. \u003cem\u003eWei Sheng Wu Xue Bao\u003c/em\u003e 47, 1105\u0026ndash;1109 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGopaulchan, D. \u003cem\u003eet al.\u003c/em\u003e A defined microbial community reproduces attributes of fine flavour chocolate fermentation. \u003cem\u003eNat Microbiol\u003c/em\u003e 10, 2130\u0026ndash;2152 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41564-025-02077-6\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41564-025-02077-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGezginc, Y., Topcal, F., Comertpay, S. \u0026amp; Akyol, I. Quantitative analysis of the lactic acid and acetaldehyde produced by Streptococcus thermophilus and Lactobacillus bulgaricus strains isolated from traditional Turkish yogurts using HPLC. \u003cem\u003eJ Dairy Sci\u003c/em\u003e 98, 1426\u0026ndash;1434 (2015). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.3168/jds.2014-8447\u003c/span\u003e\u003cspan address=\"https://doi.org:10.3168/jds.2014-8447\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao, C. H., Cao, H., Cai, P. \u0026amp; S\u0026oslash;rensen, S. J. The initial inoculation ratio regulates bacterial coculture interactions and metabolic capacity. \u003cem\u003eIsme j\u003c/em\u003e 15, 29\u0026ndash;40 (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41396-020-00751-7\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41396-020-00751-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdelazez, A. \u003cem\u003eet al.\u003c/em\u003e Carob Pod Nanoparticles: enhancing physicochemical, antioxidant, and antibacterial properties of innovative functional frozen yogurt. \u003cem\u003enpj Science of Food\u003c/em\u003e 9, 162 (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org:10.1038/s41538-025-00529-1\u003c/span\u003e\u003cspan address=\"https://doi.org:10.1038/s41538-025-00529-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYue, Q., Liu, C., Li, L., Zheng, X. \u0026amp; Bian, K. Effects of fermentation on the rheological characteristics of dough and the quality of steamed bread. \u003cem\u003eJournal of Food Processing and Preservation\u003c/em\u003e 43, e14115 (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jfpp.14115\u003c/span\u003e\u003cspan address=\"10.1111/jfpp.14115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou, W. \u003cem\u003eet al.\u003c/em\u003e Effects of the coculture of Pediococcus pentosaceus and Saccharomyces cerevisiae with different leavening ability on the quality and volatile organic compounds of Chinese steamed bread. \u003cem\u003eFood Bioscience\u003c/em\u003e 59, 104216 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.fbio.2024.104216\u003c/span\u003e\u003cspan address=\"10.1016/j.fbio.2024.104216\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng, X. \u003cem\u003eet al.\u003c/em\u003e Exploration of the flavor diversity of oolong teas: A comprehensive analysis using metabolomics, quantification techniques, and sensory evaluation. \u003cem\u003eFood Research International\u003c/em\u003e 195, 114868 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodres.2024.114868\u003c/span\u003e\u003cspan address=\"10.1016/j.foodres.2024.114868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYao, W. \u003cem\u003eet al.\u003c/em\u003e Flavor profile analysis of grilled lamb seasoned with classic salt, chili pepper, and cumin (Cuminum cyminum) through HS-SPME-GC-MS, HS-GC-IMS, E-nose techniques, and sensory evaluation on Sonit sheep. \u003cem\u003eFood Chemistry\u003c/em\u003e 454, 139514 (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.foodchem.2024.139514\u003c/span\u003e\u003cspan address=\"10.1016/j.foodchem.2024.139514\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Starter cultures, Lactococcus lactis, Flavor, 4-hydroxy-2-butanone, Fermented milk","lastPublishedDoi":"10.21203/rs.3.rs-8656461/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8656461/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe fermentation of dairy products is a complex biotransformation process, with flavor characteristics linked to the metabolic activities of specific strains, highlighting the necessity of identifying unique strains to enhance product quality. Here, 50 \u003cem\u003eLactococcus lactis\u003c/em\u003e (\u003cem\u003eL. lactis\u003c/em\u003e) strains were isolated from traditional dairy products collected from four major pastoral regions in China, namely Xinjiang, Yunnan, Inner Mongolia, and Tibet. Based on the physiological characteristic indices of the strains, combined with the TOPSIS-entropy weight method, NZZ1 and RB12 with excellent fermentation performance were screened out. Among these, strain NZZ1 was identified as a significant producer of 4-hydroxy-2-butanone, the key volatile compound with the highest variable importance in projection, due to its complete coding genes for acetolactate synthase and acetolactate decarboxylase, enabling the biosynthesis of this compound. Comparative analysis with commercial starter cultures demonstrated that NZZ1 exhibits a shorter milk coagulation time (6 h), a faster fermentation rate (8 h), strong water holding capacity, and no excessive post-acidification (90.16 \u0026deg;T), along with outstanding sensory preference scores. Furthermore, co-fermentation with commercial starters significantly increased the yield of 4-hydroxy-2-butanone by more than threefold. These findings highlight the potential of NZZ1 as a distinctive starter culture, offering innovative strategies for enhancing dairy product quality.\u003c/p\u003e","manuscriptTitle":"Lactococcus lactis enhances the flavor of fermented milk by producing 4-hydroxy-2-butanone","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 13:09:42","doi":"10.21203/rs.3.rs-8656461/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e2fe4b41-d4b8-4f0c-be60-71817b8fdc63","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":62813269,"name":"Biological sciences/Biochemistry"},{"id":62813270,"name":"Biological sciences/Biotechnology"},{"id":62813271,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-03-14T10:09:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 13:09:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8656461","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8656461","identity":"rs-8656461","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}