Phenotypic variation in growth and biofilm formation of Leuconostoc spp. from sugar beet factories

Leuconostoc bacteria are common colonizers of sugar crop processing environments, resulting in sucrose losses and the formation of exopolysaccharides (EPS) and biofilms that can lead to reduced product quality and higher operational costs. Although Leuconostoc species are present in abundance, strain-specific differences in biofilm formation, EPS production, and matrix structure are not well understood. In this study, nine sugar beet factory-derived Leuconostoc isolates were grown and evaluated using a combination of batch adherence and continuous flow biofilm bioreactor assays, cryo scanning electron microscopy (SEM), EPS quantification, viscosity testing, and growth rate analysis to determine which phenotypes correlate with biofilm formation. The results from the adherence batch-phase biofilms indicated significant phenotypic variation among isolates, with the highest bacterial proliferation by L. suionicum BSDF25-7 and BSDF48-3, exceeding 5 × 10⁸ colony-forming units/cm² on stainless steel coupons. In contrast, the highest biofilm biomass accumulated was BSDF2-3 and BSDF25-7, indicating differences in cell proliferation and biofilm matrix structure. CryoSEM imaging revealed diverse biofilm structures, such as silo-like aggregates and patchy surface colonization, indicating strain-specific extracellular matrix assembly strategies. Flow-through biofilm bioreactor assays further identified BSDF2-3 and BSDF5-1 as predominant biofilm formers with the highest CFU/cm² present at 4 × 10⁸ and 1 × 10⁹, respectively, while BSDF2-3 accumulated twice the biofilm biomass as BSDF5-1. Leuconostoc strains BSDF25-7 and BSDF48-3 produced high levels of dextran and EPS, while BSDF2-3 consistently formed dense, shear-resistant biofilms despite slow growth and low EPS levels, suggesting the possibility of alternative matrix composition or structural adaptations. Individual Leuconostoc strains adapt uniquely, adding to the functional diversity of biofilms that impact formation, matrix complexity, and resistance to environmental stressors. This study furthers our understanding of EPS and growth phenotypes involved in biofilm formation while providing a working model, enabling the development of future antimicrobial mitigation strategies.

1 Introduction

Sugar beet (Beta vulgaris ssp. vulgaris) is a vital crop, contributing significantly to global sugar production. The United States is among the top global producers contributing considerably to the sugar economy, with a projected 5.389 million short tons raw value (STRV) for the 2024/2025 campaign (Abadam, 2025). During post-harvest management of sugar beet processing, microbial contamination originating from sources, such as infected roots and associated soil, storage piles, juice (Bill et al., 2024; Bill et al., 2025), and factory biofilms (Qi et al., 2023; Qi et al., 2025), leads to sucrose losses and operational challenges (Soliman, 2007; Fugate and Campbell, 2009; Eggleston et al., 2011; Ernst et al., 2024). Microorganisms introduced from infected sugar beet roots, soil, and storage piles are carried into the processing streams, leading to sucrose deterioration and formation of EPS that interfere with clarification, clogging of filters, increased viscosity, and inhibition of sugar crystallization (Abdel-Rahman et al., 2008; Borji et al., 2019; Evageliou, 2020; Abdel-Rahman et al., 2023).

Leuconostoc spp., along with several other bacteria and fungi, such as Lactobacillus, Bacillus, Clostridium, Candida, Fusarium, and Penicillium, are frequently encountered in sugar beet processing environments (Kusstatscher et al., 2019; Kusstatscher et al., 2021; Bill et al., 2025; Qi et al., 2025). These microorganisms, especially lactic acid bacteria (LAB), metabolize sucrose into organic acids (Mendonça et al., 2022) and EPS, leading to pH shifts, reduced sucrose purity, and the accumulation of viscous byproducts in juice processing lines. EPS, such as dextran, levan, and heteropolysaccharides, can block filters, increase viscosity, and disrupt crystallization during downstream refining (Hector et al., 2016; Borji et al., 2019; Dolgopolova et al., 2021; Qi et al., 2023; Bruni et al., 2024). The resulting processing inefficiencies not only cause sugar losses but also necessitate costly interventions, such as frequent maintenance, enzyme treatments, and antimicrobial usage.

Although dextranase is routinely added during processing to target dextran, primarily produced by Leuconostoc and Lactobacillus, persistent processing issues suggest that other types of EPS may also be involved (Eggleston et al., 2009; Nel et al., 2019; Misra et al., 2022). Moreover, EPS, in addition to proteins, may facilitate adherence to factory surfaces during biofilm formation, further complicating cleaning and sanitation efforts. While there are several reports on EPS produced by Leuconostoc (Leathers and Côté, 2008; Côté and Leathers, 2009; Yan et al., 2016; Zikmanis et al., 2020), there are relatively few studies on biofilm formation in sugar crop factories or with factory-derived isolates, although some reports suggest that biofilms in sugarcane and sugar beet factories are polymicrobial in nature and encased in polysaccharides (Leathers and Côté, 2008; Qi et al., 2023; Qi et al., 2025). These studies also suggest the association of lactic acid bacteria and yeast in many biofilm samples (Qi et al., 2023; Qi et al., 2025).

The extracellular matrix of biofilms encases and shields the microbial community from external stresses such as heat and chemical treatments, making them more resistant to biocides and promoting persistent contamination (Liu et al., 2023; Liu et al., 2024). The combination of EPS-mediated viscosity issues and biofilm-related biofouling presents a multifaceted obstacle to efficient sucrose recovery in factories. Therefore, elucidating the phenotypic diversity in growth rate, EPS production, and biofilm biomass accumulation among Leuconostoc strains is central to understanding mechanisms of biofilm formation in sugar crop factories and developing effective control measures. This study sought to highlight the variation in biofilm production among nine Leuconostoc strains obtained from juice and biofilm niches within sugar beet factories (Qi et al., 2025). While earlier studies have modeled biofilm formation under high fluid shear with one strain at a time (Leathers and Côté, 2008; Côté and Leathers, 2009), this study utilized a biofilm bioreactor with low fluid shear and six growth chambers, enabling comparison of multiple strains and production of greater biofilm biomass for the study. Assessment of biofilm-related parameters indicates that varying phenotypic traits among Leuconostoc strains impact biofilm formation.

2 Materials and methods

2.1 Bacterial strains and growth media

Leuconostoc strains were isolated and identified from sugar beet factory juice and biofilm samples as described (Qi et al., 2025). The whole genome sequencing of these strains was previously reported (Joshi and Bruni, 2025). All strains were grown as precultures in MRS medium (De Man et al., 1960) at 28 °C, 250 rpm, unless specified otherwise. The strains used in this study are shown in Table 1.

Table 1

Table 1. Leuconostoc isolates used in this study were previously described (Joshi and Bruni, 2025; Qi et al., 2025).

2.2 Batch adherence phase

Biofilms were grown in a Drip-flow six-chamber biofilm reactor (Biosurface Technologies, Bozeman, MT, USA). Each strain was cultured overnight in 50 mL of MRS medium (De Man et al., 1960) in a 250-mL flask at 28 °C, with shaking at 250 rpm. Bacterial cells were normalized to approximately 5 × 10⁸ colony-forming units (CFU) per mL, expressed as CFU/mL in Tryptone Sucrose Yeast (TSY) medium, 120 g/L sucrose, adapted from Haynes et al. (1955), and inoculum cell counts were confirmed by plating for CFU/mL (see next section). 1 mL of normalized bacterial culture was inoculated into 15 mL of TSY medium in each growth chamber. The growth chambers were clamped at the effluent port to retain the growth medium during the batch adherence phase. Then 0.22-μm filter vents were attached to allow for aerobic growth. The inoculated biofilm reactor was incubated at 28 °C for 48 h during the batch phase to facilitate adherence to stainless steel coupons. Samples were then taken for quantification of microbial CFU/cm² recovered from stainless steel coupons and measurement of biofilm dextran (see below).

2.3 Flow-through bioreactor analysis

For flow-through bioreactor experiments, Leuconostoc spp. were processed similarly to the adherence phase experiment for 48 h. After 48 h, continuous flow was initiated at room temperature with a flow rate of 0.9 mL/min using TSY medium (120 g/L sucrose). The bioreactor was attached to a shaker platform with a speed setting of 8 rpm with front-to-back shaking (Fisherbrand, Waltham, MA, USA). The bioreactor was secured to the shaker platform with bungee cords. The continuous flow-through phase was maintained for 72 h. Then, samples were collected for the quantification of microbial CFU/cm² and biofilm biomass.

2.4 Quantification of microbial colonies

Samples for both adherence and continuous flow biofilm material were removed from the topside of stainless-steel coupons using a sterile cell scraper into 30 mL sterile ultrapure water. Biofilm biomass was then homogenized using an Ika T10 homogenizer (Ika Works, NC, USA) at 20,000 rpm for 30 s. Biofilm homogenates were serially diluted in sterile ultrapure water and plated onto MRS agar with an Eddy Jet 2 W Automatic Spiral Plater in triplicate in linear 100 mode (Neutec Group, Inc., NY, USA). Plates were incubated at 28 °C for 1–2 days until colonies appeared. Colonies were counted with the SphereFlash Automatic Colony Counter (Neutec Group, Inc., NY, USA) using the SphereFlash Colonies PRO software version 1.0.0.16. to measure CFU/mL.

CFU/mL from triplicate plates were averaged and divided by the area of the stainless-steel coupon, 18.75 cm², resulting in CFU/cm² metrics for each growth chamber. Each strain was run in side-by-side duplicate growth chambers. The resulting CFU/cm² from duplicate growth chambers was averaged for each strain. L. suionicum BSDF2-3 was used as a positive control for each experiment, allowing for additional experimental strains to be run in duplicate during each experiment since the bioreactor has a total of six side-by-side growth chambers. Each experiment was run at least twice.

2.5 Biofilm biomass

For both adherence and continuous flow experiments, biofilm biomass was precipitated with three volumes of absolute ethanol at 4 °C overnight. Samples were then centrifuged at 10,000×g at 4 °C for 30 min to pellet the biofilm biomass. The resulting pellet was lyophilized, weighed, and stored in a desiccator under vacuum.

2.6 Scanning electron microscopy (SEM) imaging

To examine the adherence phase biofilms formed by each isolate, a thin layer of biofilm sample was mounted on aluminum SEM stubs using a cryo-embedding compound (Pelco, Ted Pella, CA, USA). The prepared stubs were placed on a temperature-controlled stage (Coolstage, Deben, UK), which was maintained at −20 °C throughout imaging to minimize dehydration and preserve surface integrity. Then, the samples were analyzed with a Phenom G6 ProX SEM (Nanoscience Instruments, Phoenix, AZ, USA) operated under low-vacuum conditions to accommodate the partially hydrated state of the biofilms. SEM images were acquired at accelerating voltages of 5 kV and 10 kV, with magnifications of 2,000× and 5,000×, respectively.

2.7 Dextran assay

Biofilm samples harvested from adherence experiments were homogenized in 30 mL of sterile ultrapure water, serially diluted, and analyzed for dextran content using a dextran enzyme-linked immunosorbent assay (ELISA) kit (Beacon Analytical Systems, Saco, ME, USA). The calibration curve and sample data were processed according to the manufacturer’s recommendations. Data were analyzed using 4-parameter logistic (4PL) regression, and dilution factors were taken into consideration for each isolate.

2.8 Viscosity and exopolysaccharides measurements

Leuconostoc strains were grown, and the EPS was prepared as previously described (Bruni et al., 2024). Briefly, each strain was grown overnight as a preculture in MRS medium (De Man et al., 1960) and then inoculated into flask cultures at a starting OD of 0.05 in 50 mL TSY medium. Cultures were grown for 24 h at 28 °C with 250 rpm shaking. These flask cultures were used for both EPS and viscosity measurements.

After the 24-h incubation, OD₆₀₀ was measured with an Eppendorf Bio-Photometer (Hamburg, Germany), and flask culture viscosity was measured with a Brookfield model DV-11 + viscometer. Viscosity measurements were conducted using approximately 20 mL sample volume withdrawn from the flask culture, without dilution, using a UL spindle and small sample adapter at room temperature (Qi et al., 2025). Complete results from the viscosity analysis are given in the Supplementary material S1. One viscosity measurement was performed on three replicate culture flasks for each strain. For each sample, where possible, viscosity was measured at three different rotational speed instrument settings in the range of 5 to 50 RPM. Three samples, BSDF (5–1, 2–6, and 2–3), were substantially more viscous than other samples and required measurement at a rotational speed of 0.5 RPM (minimum instrument setting). For all other samples BSDF (48–3, 14–9, 47–1, 25–7, 62–9, 52–11), the recorded viscosity was taken as the measured viscosity at the lowest instrument speed setting, where the measured torque output exceeded a value of 10%; instrument manufacturer recommendation is to only use viscosity readings with associated torque values between 10 and 100%. Although shear thinning phenomena have been observed for some samples of this nature in a previous study (Qi et al., 2025), we assume Newtonian fluid behavior (Evageliou, 2020) here as a simplifying assumption in order to enable practical comparison between results and subsequent correlational analyses.

For EPS measurement, samples were centrifuged to remove bacterial cells, and supernatants containing soluble EPS were precipitated with three volumes of ethanol without DNase or proteinase treatment at 4 °C overnight. EPS was pelleted by centrifugation at 10,000 g for 30 min, and then lyophilized, weighed, and stored in a desiccator under vacuum (Bruni et al., 2024).

2.9 Doubling time determination

Precultures of each isolate were grown in MRS medium (De Man et al., 1960) to minimize EPS production and allow for pipetting non-viscous precultures. Optical densities (OD₆₀₀, hereafter OD) of precultures were measured in an Eppendorf Bio-Photometer (Hamburg, Germany) and normalized to 0.2 in TSY medium (50 g/L sucrose) (Haynes et al., 1955). Normalized precultures were pipetted into a 96-well plate in triplicate. A block design was employed to arrange the microbial isolates within the plates, and each block included triplicate blank wells without inoculum to serve as a reference. Plates were incubated at 28 °C with shaking at 250 rpm for 24 h in a TECAN plate reader (TECAN, Männedorf, Switzerland), which recorded OD values every 10 min using Magellan Standard software, version 7.5.

The Richards growth model was fitted to modified curves of the samples (inoculated wells). First, OD values from blank wells were subtracted from those of inoculated wells to generate adjusted OD values. To ensure accurate modeling of the exponential growth phase, data points occurring after the first instance of 99% of the maximum OD value for each curve were excluded, preventing the Richards growth model from overfitting the stationary phase. All model fitting was performed in R version 4.4.1 (Team R.C., 2016). The Richards growth model was fitted to these modified growth curves using the Richards growth function from the R package growth rates version 0.8.4 (Petzoldt, 2022). Visual inspection of the fits was conducted using the ggplot2 R package (Gómez-Rubio, 2017).

The maximum growth rate (mumax) was extracted from the fitted Richards growth equations (Richards, 1959). This value was then used to calculate the doubling time (t) using the exponential growth equation, N(t) = N(0)e^(rt), where N(t) is the final abundance, N(0) is the initial abundance, and ‘e’ is Euler’s number. The doubling time for each isolate was determined by setting N(t) = 2, N(0) = 1, and r = mumax, and solving for t. The doubling times derived for triplicate samples of each isolate were subsequently averaged.

2.10 Statistical analysis

Statistical analysis was conducted using GraphPad Prism Software (version 10.4.2, GraphPad Software, United States). The data represent at least two independent trials and are shown as the mean ± standard error. To compare multiple groups, a one-way ANOVA test was used, followed by a Tukey post hoc test. Significant differences were considered at p-values less than 0.05. Similarly, correlation analysis was performed using the Pearson R correlation test.

3 Results

3.1 Variation in adhesion, proliferation, and biomass accumulation among Leuconostoc isolates

Leuconostoc strains isolated from juice and biofilm samples in sugar beet factories were examined for the ability to adhere, proliferate on abiotic surfaces, and form biofilms. This was assessed through quantification of viable cell counts and biofilm biomass after 48 h of the batch phase (Figures 1A,B and Supplementary material S2). All nine strains exhibited the capacity to adhere and proliferate on the abiotic surface, but with significant variation in CFU density and biomass accumulation across isolates. In Figure 1A, average CFU/cm² measurements indicated that strains L. suionicum BSDF25-7 and BSDF48-3 exhibited significantly higher adhesion and proliferation, each exceeding 5 × 10⁸ CFU/cm², while strains such as L. suionicum BSDF2-3, BSDF2-6, L. mesenteroides BSDF62-9, and L. citreum BSDF5-1 showed markedly lower CFU levels at 10⁷ CFU/cm². However, biofilm biomass quantification (Figure 1B) revealed that BSDF2-3 formed significantly denser biofilm matrices compared to other strains. Notably, strains such as L. suionicum BSDF25-7 and BSDF48-3 displayed comparatively low biomass, indicating potential differences in extracellular matrix production relative to cell density. Statistical analysis using one-way ANOVA followed by Tukey’s post hoc test confirmed significant differences among strains in both CFU and biomass measures. These findings highlight substantial strain-specific heterogeneity in biofilm-forming phenotypes, suggesting possible differences in cell surface properties, EPS production, or regulatory mechanisms underlying biofilm development in Leuconostoc isolates.

Figure 1

Figure 1. Biofilm formation by Leuconostoc isolates in a 48 h batch phase to measure adhesion and proliferation on stainless steel coupons was measured as (A) the average CFU/cm² and (B) average dry biomass (g) of biofilm. Values are based on at least two independent experiments with two coupons per experiment. Significant differences between isolates (p < 0.05) were determined by ANOVA followed by Tukey post-hoc analysis as indicated by distinct letters.

3.2 Biofilm formation in a flow-through bioreactor reveals strain-dependent variation

The ability of Leuconostoc strains to proliferate and form biofilms in a continuous flow bioreactor was evaluated in a flow-through bioreactor system for 72 h. Quantification of surface-associated viable cells (CFU/cm²) and total biofilm biomass showed clear strain-level differences in biofilm formation (Figures 2A,B).

Figure 2

Figure 2. Biofilm formation by Leuconostoc isolates in a 72 h continuous flow phase to measure proliferation and biomass accumulation on stainless steel coupons, measured as (A) the average CFU/cm² and (B) average dry biomass (g) of biofilm. Values are based on at least two independent experiments, with two coupons per experiment. Significant differences between isolates (p < 0.05) were determined by ANOVA followed by Tukey post-hoc analysis as indicated by distinct letters.

L. citreum BSDF5-1 had the highest 1.14 × 10⁹ CFU/cm² in contrast to L. mesenteroides BSDF62-9, which was the lowest biofilm-forming strain with 1.33 × 10⁶ CFU/cm² (p value <0.0001), as shown in Figure 2A. Among L. suionicum, BSDF2-3 showed the highest count of 3.73 × 10⁸ CFU/cm², followed by BSDF2-6 with 2.55 × 10⁸ CFU/cm². These data suggest bacterial proliferation leading to increased CFU counts in 72 h. Biofilm biomass accumulation during the continuous flow-through phase showed trends similar to the batch phase biofilm biomass phenotypes. The highest average biofilm biomass was produced by L. suionicum BSDF2-3 compared to all other strains. However, L. suionicum BSDF47-1 maintained low CFU/cm² levels but produced moderate biomass. The minimal biofilm biomass produced by L. mesenteroides BSDF62-9 also corresponded with the low CFU/cm² values (Figure 2B).

3.3 Topological variation in Leuconostoc biofilm shows aggregation and pillar-like architectures

SEM images revealed significant topological diversity in 48-h cultivated biofilm structures (Figures 3A,B and Supplementary material S3). At 2,000× magnification (Figure 3A), L. suionicum strains BSDF2-3, BSDF2-6, and BSDF47-1 formed dense, mat-like biofilms with relatively uniform surface coverage. In contrast, L. suionicum BSDF48-3 and L. citreum BSDF5-1 formed distinct, silo- or dome-like protrusions emerging from a sparsely colonized background. BSDF62-9 showed weak biofilm formation, presenting a loose, watery structure. Notably, BSDF48-3 exhibited a large, centrally aggregated pillar structure, suggesting vertical stratification and localized microcolony development. These elevated morphologies resemble the “mushroom” or “silo” structures commonly seen in mature biofilms of Pseudomonas and Staphylococcus, which are linked to nutrient gradients and protective EPS layers (Coraça-Huber et al., 2020; Wang et al., 2023).

Figure 3

Figure 3. Scanning electron microscopy images of a 48-h biofilm from the adhesion batch phase experiment. Images were taken on a Phenom G6 ProX SEM with (A) 2,000× and (B) 5,000× magnifications.

At higher magnification (5,000×, Figure 3B), finer structural details became evident. Leuconostoc strains, such as BSDF62-9 and BSDF14-9, showed coarse, corrugated, net-like surfaces with loosely aggregated cells. In contrast, strains BSDF2-6 and BSDF52-11 exhibited sparse cell clusters interspersed with voids, indicating limited matrix formation and weaker cohesion. The strain BSDF48-3 showed a compact, elevated central mass, composed of tightly packed cells arranged radially, possibly indicating increased localized EPS deposition. Notably, strains L. citreum BSDF5-1 and L. suionicum BSDF2-3 demonstrated a mucinous, spiky monolayer-like conformation with vertical growth, suggesting a biofilm adapted for surface adhesion rather than volume expansion.

3.4 Strain-specific variation in the growth rate of Leuconostoc isolates

Next, in order to determine whether bacterial proliferation rate may impact biofilm formation, the doubling time of each Leuconostoc strain was determined under standard growth conditions to establish if biofilm formation phenotypes may be attributable to inherent growth rates (Figure 4). Substantial variation in growth rates was observed across all Leuconostoc strains, with doubling times ranging from approximately 24–53 min. L. suionicum strains BSDF52-11 and BSDF48-3 exhibited the fastest growth rates, with doubling times under 30 min, while L. suionicum strains BSDF2-3 and BSDF2-6 showed slower growth, with doubling times exceeding 50 min.

Figure 4

Figure 4. Average doubling time of Leuconostoc sp. isolates arranged from fastest (top) to slowest (bottom). Doubling times were calculated from growth curves inoculated at 0.2 OD₆₀₀, using growth rate r from fitted Richards growth models. Sample size n = 3. Error bars are the sample standard error.

3.5 Strain-dependent production of dextran in batch phase biofilms

To evaluate the EPS production capacity among Leuconostoc strains, dextran levels were quantified from batch-phase biofilm samples using a dextran ELISA kit and analyzed using a 4-parameter logistic regression model (R² = 0.99; Figure 5). Substantial differences in dextran concentrations were observed among the nine Leuconostoc strains, with values ranging from approximately 31 to over 548 ppm. In particular, L. suionicum strains BSDF25-7 and BSDF48-3 exhibited the highest dextran production, consistent with high CFU/cm² densities and biomass accumulation observed in the batch-phase experiments. In contrast, strains such as L. suionicum BSDF2-6 and L. mesenteroides BSDF62-9 produced significantly lower levels of dextran. These results highlight extensive heterogeneity in dextran synthesis among Leuconostoc strains and underscore the potential contribution of dextran production to the robustness of biofilms.

Figure 5

Figure 5. Concentration of dextran (ppm) from the adhesion batch phase biofilm. Dextran ELISA was performed with standard calibrations, and samples were run in triplicate. Dextran ELISA kit 4-parameter logistic regression curve showed R² = 0.99.

3.6 Quantification of EPS and viscosity reveals variability in the extracellular matrix yield

EPS and viscosity were measured from 24-h Leuconostoc flask cultures to gain a comprehensive understanding of Leuconostoc strain EPS production capacity under planktonic conditions (Figure 6 and Table 2). Substantial variation was observed in EPS yield dry weight extracted from the flask cultures among the strains, with values ranging from less than 0.5 g to over 4 g per culture. Strains BSDF25-7 and BSDF48-3 produced the highest amounts of EPS, indicating strong extracellular matrix production under planktonic batch growth conditions. In contrast, strains BSDF2-3 and BSDF2-6 exhibited markedly lower EPS levels, which may be attributed to variations in EPS solubility when preparing EPS samples from cultures. Notably, others have reported that some Leuconostoc isolates produce insoluble EPS fractions that remain cell-associated (Padmanabhan and Kim, 2002; Côté and Leathers, 2009). This possibility and the impact of EPS structure on solubility warrant further investigation. The differences in EPS yield broadly align with trends observed in the dextran ELISA results and biofilm biomass accumulation, supporting the notion that EPS production is a key factor in strain-specific biofilm phenotypes.

Figure 6

Figure 6. Dry weight (g) of EPS from Leuconostoc isolates. EPS was extracted from 24 h flask cultures. Sample flasks were run in duplicates and pooled.

Table 2

Table 2. Average viscosity and measured OD₆₀₀ of Leuconostoc 24-h flask cultures.

Furthermore, viscosity measurements demonstrated that strains exhibited varying levels of viscosity in the respective flask culture broths (Table 2). Since measured viscosities span orders of magnitude, values are reported both as—is and as log₁₀—transformed. Due to the wide variation in culture viscosity, culture samples were read at different rpm in order to obtain viscosity measurements with a torque greater than 10. L. suionicum BSDF2-3 and BSDF2-6 strains produced the highest average viscosity, measured at 3.04 ± 0.01 log₁₀ and 3.08 ± 0.01 log₁₀ cP, respectively. L. citreum BSDF5-1 exhibited the next highest viscosity of 2.79 ± 0.07 log₁₀ cP (Table 2). The remaining Leuconostoc isolates had lower viscosities ranging between 0.48 and 1 cP. Taken together, the results indicate that Leuconostoc strains possess diverse capabilities in modifying the viscosity of the growth environment through the production of various EPS.

3.7 Dry-weight EPS is positively correlated with dextran concentration

Finally, the functional contribution of the EPS production capacity of the respective Leuconostoc strains was assessed. Pearson correlation was performed between the dextran levels measured in batch phase biofilms and the extracted EPS dry weight of flask cultures (Figure 7A) since the biofilm biomass from the adherence phase was very low for some strains. A significant positive correlation (R² = 0.85, p = 0.00037) was observed between the EPS weight and the dextran concentration, indicating that strains with greater EPS yields also produced higher quantities of dextran (Figure 7A).

Figure 7

Figure 7. Scatter plot showing the correlation between (A) EPS and dextran and (B) viscosity and OD₆₀₀ by Pearson correlation from 24-h Leuconostoc flask cultures.

Next, Pearson correlation was performed for the viscosity of the 24-h flask cultures and OD₆₀₀ (Figure 7B). Similarly, a significant positive correlation was found (R² = 0.94, p = 0.000013), suggesting that OD₆₀₀ contributes to the rheological properties of the culture medium (Figure 7B). Interestingly, the observed viscosities showed poor correlation with EPS yield (Figure 6), suggesting additional variables such as OD₆₀₀, EPS structure, and solubility may also impact viscosity. These findings highlight the central role of strain-specific EPS biosynthesis in modulating both biochemical (dextran content) and biophysical (viscosity) characteristics of Leuconostoc cultures.

4 Discussion

Leuconostoc species are key microbial contaminants of post-harvest sugar beet processing streams, often originating from rotting sugar beet roots and subsequently contaminating the factory (Bill et al., 2024; Qi et al., 2025). These microbes pose significant issues for raw sugar production, such as sucrose losses and operational disruptions during processing (Qi et al., 2023; Bill et al., 2025; Qi et al., 2025). An examination of the phenotypic variability in growth, EPS, and biofilm-forming capacity of these Leuconostoc strains originating from the sugar beet factory environment is presented in this study. Notably, Leuconostoc strains BSDF2-3, BSDF2-6, BSDF14-9, and BSDF5-1 were originally isolated from sugar beet factory biofilm samples, while Leuconostoc strains BSDF48-3, BSDF62-9, BSDF52-11, and BSDF47-1 were isolated from sugar beet factory juice samples (Qi et al., 2025). Additionally, the genome sequences of the nine Leuconostoc isolates are reported (Joshi and Bruni, 2025).

Our study found significant heterogeneity in biofilm-forming capabilities, EPS production, and growth kinetics among Leuconostoc isolates from industrial sugar beet factories. Under both static and dynamic culture conditions, the isolates varied greatly in adhesion, CFU density, and total biomass during both the batch phase and the continuous flow through phase. Notably, strains BSDF25-7 and BSDF48-3 showed strong planktonic growth and surface colonization under batch conditions. At the same time, BSDF2-3 formed dense biofilm matrices despite lower CFU counts during the batch phase, suggesting that biomass accumulation is not solely reliant on cell proliferation (Figure 1). This decoupling likely reflects different regulatory strategies controlling the biofilm matrix and cellular division, as seen in other bacterial systems (Flemming and Wingender, 2010; Flemming et al., 2016; Karygianni et al., 2020). In flow-through assays simulating industrial shear stress, BSDF5-1 and BSDF2-3 maintained high biomass and CFU, indicating biofilm resilience under hydrodynamic stress (Figure 2).

Similar phenomena have been observed in Pseudomonas spp., where shear exposure induces biofilms with higher carbohydrate content and better structural stability, increasing resistance to detachment (Dingemans et al., 2016; Palalay et al., 2023). BSDF2-3 proved to be a strong biofilm former in both models, despite slower growth and lower EPS yield by mass. Conversely, BSDF25-7, despite its strong adhesion during the batch phase, showed poor adherence under fluid shear, highlighting the importance of testing biofilms in conditions that resemble those in industrial pipelines for evaluating persistence. Substantial variability in the composition and structure of EPS may be partially attributable to various factors, such as additional extracellular components, for example, DNA and protein, as well as other microbes in the community, the ambient shear forces, nutrient and substrate availability, and the characteristics of the host environment (Lebeaux et al., 2014; Flemming et al., 2016).

Scanning electron microscopy of biofilm samples revealed considerable phenotypic variability in the three-dimensional architecture (Figure 3). The diverse topographical features of Leuconostoc biofilms pose significant challenges during sugar beet processing by decreasing sanitation efficiency. Filter blockages in processing streams are also a significant operational challenge (Qi et al., 2023; Qi et al., 2025). Strains such as BSDF48-3 and BSDF5-1 exhibited distinct, silo-like structures, while strain BSDF62-9 displayed irregular, loosely aggregated matrices. Notably, the elevated, EPS-rich structures formed by some Leuconostoc strains like BSDF48-3 and BSDF5-1 resemble mature biofilms seen in other LAB and pathogens, promoting long-term persistence and antimicrobial tolerance (Costerton et al., 1995). Conversely, flattened, fragmented biofilms likely indicate weaker matrix formation or impaired adhesion, reducing survival under shear stress and posing less threat in dynamic systems (Simões et al., 2010; Paul et al., 2012; Simões and Simões, 2023).

This structural diversity likely reflects differences in EPS structural composition as well as any accompanying extracellular DNA and proteins that may affect adhesion dynamics. These features may affect strain-specific biofilm resilience, nutrient diffusion, and persistence in industrial settings.

Growth rate analysis provided further insight into the phenotypic divergence among strains. Fast-growing strains, such as BSDF48-3 and BSDF52-11, exhibited shorter doubling times and higher CFU levels during the batch phase, whereas slow-growing strains, like BSDF2-3 and BSDF2-6, showed increased biofilm biomass during the continuous flow phase and increased viscosity during planktonic culture, indicative of a biofilm-specialized phenotype (Figure 4 and Table 2). This tradeoff between rapid proliferation and matrix investment supports patterns observed in LAB and other gram-positive bacteria, where biofilm specialization involves resource allocation toward structural polymer synthesis rather than cell division (Niederdorfer et al., 2017; Reichhardt et al., 2025). In contrast, BSDF2-3 forms higher-biomass biofilms during the continuous flow phase with modest EPS recovery, indicating a more compact, cross-linked matrix likely enriched in insoluble or branched polysaccharides (Leathers and Côté, 2008; Côté and Leathers, 2009).

Additionally, the divergence in observed strain-specific biofilm phenotypes may reflect ecological adaptation to niches within the sugar-processing environment, where selection pressures such as flow, surface contact, and nutrient flux drive EPS diversity (Hector et al., 2016; Henriksen et al., 2022). Notably, strains with faster doubling times also tended to form more viable cells during the adherence batch phase when nutrients are limited, while slower-growing strains, such as L. suionicum BSDF2-3 and L. citreum BSDF5-1, tended to be robust biofilm producers during the continuous-flow phase with unlimited sucrose. These findings indicate that growth kinetics may partially underpin the observed strain-specific variation in biofilm phenotypes.

Quantitative analyses revealed considerable variation in total EPS and dextran production across all strains (Figures 5, 6). High-EPS producers, such as BSDF25-7 and BSDF48-3, yielded abundant dextran, correlating with elevated CFU counts but not necessarily total biomass, suggesting a loosely bound or soluble extracellular matrix. In contrast, BSDF2-3 produced modest EPS mass but high viscosity and biofilm biomass, implying a denser, possibly branched or insoluble polymeric network. Previous studies emphasize that EPS in LAB, such as Leuconostoc, include diverse glucans, often mixtures of dextran and levan, each influencing viscosity, adhesion, and texture differently (Jurášková et al., 2022; Du et al., 2023). The strong positive correlations observed between EPS quantity and dextran concentration confirm that dextran is a key contributor to the matrix, though not the sole determinant (Figure 7). Notably, one report in the literature indicates that L. citreum biofilms have relatively low protein content relative to carbohydrate (Labadie et al., 2021). Further, another report suggests that both dextran and nucleic acid are involved in Leuconostoc biofilm formation (Badel et al., 2008). These results suggest compositional complexity, potentially involving other glucans, proteins, or extracellular DNA, all of which may modulate biofilm structure and resistance traits (Flemming and Wingender, 2010; Torres-Rodríguez et al., 2014).

Strains such as L. suionicum BSDF2-3 and L. citreum BSDF5-1, which form resilient biofilms, pose significant challenges for cleaning protocols and may promote biofilm-associated clogging or contamination. Conversely, dextran-rich but weakly adherent strains, such as BSDF25-7, may still clog filters during sugar beet processing despite weaker adherence. Further, these types of Leuonostoc isolates are advantageous for controlled EPS production for food applications, such as texture enhancement, provided conditions are optimized for yield and polymer quality.

Understanding the unique biochemical traits attributable to each bacterial EPS is crucial, as this knowledge can inform utilization in biotechnology or removal in industrial settings. Gaining deeper insights into the various aspects of the biofilm matrix is vital for developing better methods to prevent and address biofilm-related problems in sugar processing facilities. To further understand the structural aspects of biofilm formation, the role of EPS structure, as well as the contributions of additional extracellular matrix components such as DNA and proteins, ought to be explored in future research. Additionally, the complex dynamics of matrix formation, structural organization, and remodeling in interspecies and interkingdom interactions in industrial biofilms must be considered (Qi et al., 2023).

This investigation underscored the critical role of EPS in Leuconostoc biofilm formation. However, the results also demonstrate that EPS quantity alone does not fully predict biofilm performance; rather, the growth rate, architecture, composition, and viscoelastic properties of the matrix contribute to persistence and function. While the various Leuconostoc strains exhibited phenotypic variation in CFUs and biofilm accumulation over time during the batch phase and continuous flow phase, future studies are needed to further investigate, more specifically, the time-dependent dynamics of biofilm formation and biomass accumulation. These dynamics are likely strain-specific adaptive mechanisms that regulate biofilm formation in Leuconostoc species.

5 Conclusion

This study demonstrates marked strain-specific variation in biofilm formation, EPS production, and growth kinetics among nine Leuconostoc isolates from sugar beet processing environments. Notably, matrix accumulation and biofilm resilience were not always linked to CFU counts or EPS yield, indicating functional diversity in biofilm architecture. The unique combination of high culture viscosity and low EPS production in strains, such as BSDF2-3, points to novel extracellular matrix compositions, with significant ramifications for sanitation procedures and the management of biofouling in industrial settings. Conversely, strains with high dextran output may have potential in biotechnological applications, such as food texturization. These findings highlight the importance of evaluating both structural and compositional attributes of biofilms and underscore the need for further studies on EPS diversity and regulation to guide targeted control or exploitation of Leuconostoc species.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

SJ: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing, Validation, Visualization. GB: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing, Funding acquisition, Project administration, Resources, Supervision. TZ: Investigation, Methodology, Visualization, Writing – review & editing. ET: Investigation, Methodology, Writing – review & editing, Data curation, Formal analysis, Validation, Visualization, Writing – original draft. JS: Investigation, Methodology, Writing – review & editing. MK: Formal analysis, Investigation, Methodology, Visualization, Writing – review & editing. SN: Investigation, Methodology, Resources, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This study was supported by the U.S. Department of Agriculture (USDA), Agricultural Research Service (ARS), under project number 6054-30600-003-000D. This study was also supported in part by the ARS-Sugar Beet Research Initiative to GB, which supports SJ.

Acknowledgments

The authors thank Dr. K. Thomas Klasson (USDA ARS, retired) for initial technical assistance with the biofilm reactor.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Author disclaimer

Mention of trade names or commercial products in this publication is solely to provide specific information and does not imply recommendation or endorsement by USDA.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2025.1745936/full#supplementary-material

References

Abadam, V. (2025). Sugar and sweeteners outlook: March 2025. Washington DC: USDA Economic Research Service.

Google Scholar

Abdel-Rahman, E. A., Frankenfeld, T., Saleh, A. S. M., and Floter, E. (2023). Reduction of the microbiological action during sugar beet extraction with focus on nitrite contamination. Assiut J. Agric. Sci. 54, 108–126. doi: 10.21608/ajas.2023.196364.1236

Crossref Full Text | Google Scholar

Abdel-Rahman, E. A., Smejkal, Q., Schick, R., El-Syiad, S., and Kurz, T. (2008). Influence of dextran concentrations and molecular fractions on the rate of sucrose crystallization in pure sucrose solutions. J. Food Eng. 84, 501–508. doi: 10.1016/j.jfoodeng.2007.06.014

Crossref Full Text | Google Scholar

Badel, S., Laroche, C., Gardarin, C., Bernardi, T., and Michaud, P. (2008). New method showing the influence of matrix components in Leuconostoc mesenteroides biofilm formation. Appl. Biochem. Biotechnol. 151, 364–370. doi: 10.1007/s12010-008-8199-y,

PubMed Abstract | Crossref Full Text | Google Scholar

Bill, M., Adhikari, S., Bruni, G. O., Fugate, K. K., Qi, Y., Khan, M. F., et al. (2025). Fungal and bacterial species associated with storage diseases in sugar beet from the Red River Valley of Minnesota and North Dakota. Plant Dis. 109, 1702–1712. doi: 10.1094/PDIS-10-24-2188-RE,

PubMed Abstract | Crossref Full Text | Google Scholar

Bill, M., Eide, J. D., Fugate, K. K., Bolton, M. D., Kandel, H. P., and Kandel, S. L. (2024). Continental-scale insights into the sugarbeet diffusion juice microbiomes. Micro. Spec. 12:e0101024. doi: 10.1128/spectrum.01093-24,

PubMed Abstract | Crossref Full Text | Google Scholar

Borji, A., Borji, F.-E., and Jourani, A. (2019). Sugar industry: effect of dextran concentrations on the sucrose crystallization in aqueous solutions. J. Eng. 2019, 1–6. doi: 10.1155/2019/7987369,

PubMed Abstract | Crossref Full Text | Google Scholar

Bruni, G. O., Qi, Y., Terrell, E., Dupre, R. A., and Mattison, C. P. (2024). Characterization of Levan fructan produced by a Gluconobacter japonicus strain isolated from a sugarcane processing facility. Microorganisms 12:107. doi: 10.3390/microorganisms12010107,

PubMed Abstract | Crossref Full Text | Google Scholar

Coraça-Huber, D. C., Kreidl, L., Steixner, S., Hinz, M., Dammerer, D., and Fille, M. (2020). Identification and morphological characterization of biofilms formed by strains causing infection in orthopedic implants. Pathogens 9:649. doi: 10.3390/pathogens9080649,

PubMed Abstract | Crossref Full Text | Google Scholar

Costerton, J. W., Lewandowski, Z., Caldwell, D. E., Korber, D. R., and Lappin-Scott, H. M. (1995). Microbial biofilms. Ann. Rev. Microbiol. 49, 711–745. doi: 10.1146/annurev.mi.49.100195.003431,

PubMed Abstract | Crossref Full Text | Google Scholar

Côté, G. L., and Leathers, T. D. (2009). Insoluble glucans from planktonic and biofilm cultures of mutants of Leuconostoc mesenteroides NRRL B-1355. Appl. Microbiol. Biotechnol. 82, 149–154. doi: 10.1007/s00253-008-1767-9,

PubMed Abstract | Crossref Full Text | Google Scholar

De Man, J., Rogosa, d., and Sharpe, M. E. (1960). A medium for the cultivation of lactobacilli. J. Appl. Bacteriol. 23, 130–135. doi: 10.1111/j.1365-2672.1960.tb00188.x

Crossref Full Text | Google Scholar

Dingemans, J., Monsieurs, P., Yu, S. H., Crabbé, A., Förstner, K. U., Malfroot, A., et al. (2016). Effect of shear stress on Pseudomonas aeruginosa isolated from the cystic fibrosis lung. mBio 7, 10–128. doi: 10.1128/mBio.00813-16,

PubMed Abstract | Crossref Full Text | Google Scholar

Dolgopolova, N., Kaluzhskikh, A., and Kotelnikova, M. (2021). “State-of-the-art methods for eradication of pathogenic microflora in sugar production” in IOP conference series: Earth and environmental science. (Vladivostok, Russian Federation: IOP Publishing).

Google Scholar

Du, R., Yu, L., Sun, M., Ye, G., Yang, Y., Zhou, B., et al. (2023). Characterization of dextran biosynthesized by glucansucrase from Leuconostoc pseudomesenteroides and their potential biotechnological applications. Antioxidants (Basel) 12:275. doi: 10.3390/antiox12020275,

PubMed Abstract | Crossref Full Text | Google Scholar

Eggleston, G., Dilka, A., Blowers, M., and Winters, K. (2011). “Successful application of dextranase in sugar beet factories” in Proceedings of the American Society of Sugarbeet Technologists meeting, 1–16.

Google Scholar

Eggleston, G., Monge, A., Montes, B., and Stewart, D. (2009). Application of dextranases in sugarcane factory: overcoming practical problems. Sugar Tech 11, 135–141. doi: 10.1007/s12355-009-0020-x

Crossref Full Text | Google Scholar

Ernst, L., Offermann, H., Werner, A., and Wefers, D. (2024). Comprehensive structural characterization of water-soluble and water-insoluble homoexopolysaccharides from seven lactic acid bacteria. Carbohydr. Polym. 323:121417. doi: 10.1016/j.carbpol.2023.121417,

PubMed Abstract | Crossref Full Text | Google Scholar

Evageliou, V. (2020). Shear and extensional rheology of selected polysaccharides. Int. J. Food Sci. Technol. 55, 1853–1861. doi: 10.1111/ijfs.14545

Crossref Full Text | Google Scholar

Flemming, H.-C., and Wingender, J. (2010). The biofilm matrix. Nat. Rev. Microbiol. 8, 623–633. doi: 10.1038/nrmicro2415,

PubMed Abstract | Crossref Full Text | Google Scholar

Flemming, H. C., Wingender, J., Szewzyk, U., Steinberg, P., Rice, S. A., and Kjelleberg, S. (2016). Biofilms: an emergent form of bacterial life. Nat. Rev. Microbiol. 14, 563–575. doi: 10.1038/nrmicro.2016.94,

PubMed Abstract | Crossref Full Text | Google Scholar

Fugate, K., and Campbell, L. (2009). “Postharvest deterioration of sugar beet” in Compendium of beet diseases and pests. eds. R. M. Harveson, L. E. Hanson, and G. L. Hein.

Google Scholar

Gómez-Rubio, V. (2017). Ggplot2-elegant graphics for data analysis. J. Stat. Softw. 77, 1–3. doi: 10.1080/15366367.2019.1565254

Crossref Full Text | Google Scholar

Haynes, W. C., Wickerham, L. J., and Hesseltine, C. W. (1955). Maintenance of cultures of industrially important microorganisms. Appl. Environ. Microbiol. 3, 361–368. doi: 10.1128/am.3.6.361-368.1955,

PubMed Abstract | Crossref Full Text | Google Scholar

Hector, S., Willard, K., Bauer, R., Mulako, I., Slabbert, E., Kossmann, J., et al. (2016). Diverse exopolysaccharide producing bacteria isolated from milled sugarcane: implications for cane spoilage and sucrose yield. PLoS One 10:e0145487. doi: 10.1371/journal.pone.0145487,

PubMed Abstract | Crossref Full Text | Google Scholar

Henriksen, N. N. S. E., Hansen, M. F., Kiesewalter, H. T., Russel, J., Nesme, J., Foster, K. R., et al. (2022). Biofilm cultivation facilitates coexistence and adaptive evolution in an industrial bacterial community. npj Biofilms Microb. 8:59. doi: 10.1038/s41522-022-00323-x,

PubMed Abstract | Crossref Full Text | Google Scholar

Joshi, S., and Bruni, G. O. (2025). Whole genome sequencing of Leuconostoc suionicum, L. mesenteroides, and L. citreum isolates from sugar beet factory juice and biofilms. Micro. Res. Announ. 14:e00353-25. doi: 10.1128/mra.00353-25,

PubMed Abstract | Crossref Full Text | Google Scholar

Jurášková, D., Ribeiro, S. C., and Silva, C. C. G. (2022). Exopolysaccharides produced by lactic acid Bacteria: from biosynthesis to health-promoting properties. Foods 11:156. doi: 10.3390/foods11020156,

PubMed Abstract | Crossref Full Text | Google Scholar

Karygianni, L., Ren, Z., Koo, H., and Thurnheer, T. (2020). Biofilm matrixome: extracellular components in structured microbial communities. Trends Microbiol. 28, 668–681. doi: 10.1016/j.tim.2020.03.016,

PubMed Abstract | Crossref Full Text | Google Scholar

Kusstatscher, P., Cernava, T., Harms, K., Maier, J., Eigner, H., Berg, G., et al. (2021). “On-field microbial community influences postharvest root rot in sugar beets” in Acta Horticulturae (Leuven, Belgium: International Society for Horticultural Science (ISHS)).

Google Scholar

Kusstatscher, P., Zachow, C., Harms, K., Maier, J., Eigner, H., Berg, G., et al. (2019). Microbiome-driven identification of microbial indicators for postharvest diseases of sugar beets. Microbiome 7:112. doi: 10.1186/s40168-019-0728-0,

PubMed Abstract | Crossref Full Text | Google Scholar

Labadie, M., Marchal, F., Merbahi, N., Girbal-Neuhauser, E., Fontagné-Faucher, C., and Marcato-Romain, C.-E. (2021). Response of controlled cell load biofilms to cold atmospheric plasma jet: evidence of extracellular matrix contribution. Life 11:694. doi: 10.3390/life11070694,

PubMed Abstract | Crossref Full Text | Google Scholar

Leathers, T. D., and Côté, G. L. (2008). Biofilm formation by exopolysaccharide mutants of Leuconostoc mesenteroides strain NRRL B-1355. Appl. Microbiol. Biotechnol. 78, 1025–1031. doi: 10.1007/s00253-008-1384-7,

PubMed Abstract | Crossref Full Text | Google Scholar

Lebeaux, D., Ghigo, J.-M., and Beloin, C. (2014). Biofilm-related infections: bridging the gap between clinical management and fundamental aspects of recalcitrance toward antibiotics. Microbiol. Mol. Biol. Rev. 78, 510–543. doi: 10.1128/mmbr.00013-14,

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, H. Y., Prentice, E. L., and Webber, M. A. (2024). Mechanisms of antimicrobial resistance in biofilms. npj Antimicro. Resist. 2:27. doi: 10.1038/s44259-024-00046-3,

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, X., Yao, H., Zhao, X., and Ge, C. (2023). Biofilm formation and control of foodborne pathogenic bacteria. Molecules 28:2432. doi: 10.3390/molecules28062432,

PubMed Abstract | Crossref Full Text | Google Scholar

Mendonça, A. A., Pinto-Neto, W. P., da Paixão, G. A., Santos, D. D. S., De Morais, M. A. Jr., and De Souza, R. B. (2022). Journey of the probiotic bacteria: survival of the fittest. Microorganisms 11:95. doi: 10.3390/microorganisms11010095,

PubMed Abstract | Crossref Full Text | Google Scholar

Misra, V., Mall, A. K., Solomon, S., and Ansari, M. I. (2022). Post-harvest biology and recent advances of storage technologies in sugarcane. Biotechnol. Rep. (Amst.) 33:e00705. doi: 10.1016/j.btre.2022.e00705,

PubMed Abstract | Crossref Full Text | Google Scholar

Nel, S., Davis, S. B., Endo, A., and Dicks, L. M. T. (2019). Microbial diversity profiling of polysaccharide (gum)-producing Bacteria isolated from a South African sugarcane processing factory. Curr. Microbiol. 76, 527–535. doi: 10.1007/s00284-018-01625-0,

PubMed Abstract | Crossref Full Text | Google Scholar

Niederdorfer, R., Besemer, K., Battin, T. J., and Peter, H. (2017). Ecological strategies and metabolic trade-offs of complex environmental biofilms. NPJ Bio. Micro. 3:21. doi: 10.1038/s41522-017-0029-y,

PubMed Abstract | Crossref Full Text | Google Scholar

Padmanabhan, P. A., and Kim, D.-S. (2002). Production of insoluble dextran using cell-bound dextransucrase of Leuconostoc mesenteroides NRRL B-523. Carbohydr. Res. 337, 1529–1533. doi: 10.1016/S0008-6215(02)00214-8,

PubMed Abstract | Crossref Full Text | Google Scholar

Palalay, J. S., Simsek, A. N., Reed, J. L., Koch, M. D., Sabass, B., and Sanfilippo, J. E. (2023). Shear force enhances adhesion of Pseudomonas aeruginosa by counteracting pilus-driven surface departure. Proc. Natl. Acad. Sci. USA 120:e2307718120. doi: 10.1073/pnas.2307718120,

PubMed Abstract | Crossref Full Text | Google Scholar

Paul, E., Ochoa, J. C., Pechaud, Y., Liu, Y., and Liné, A. (2012). Effect of shear stress and growth conditions on detachment and physical properties of biofilms. Water Res. 46, 5499–5508. doi: 10.1016/j.watres.2012.07.029,

PubMed Abstract | Crossref Full Text | Google Scholar

Petzoldt, T. (2022). Growthrates: estimate growth rates from experimental data. R Packag. Available online at: https://cran.r-project.org/package=growthrates (Accessed on April 20, 2020).

Google Scholar

Qi, Y., Bruni, G. O., and Klasson, K. T. (2023). Microbiome analysis of sugarcane juices and biofilms from Louisiana raw sugar factories. Micro. Spec. 11:e04322. doi: 10.1128/spectrum.04345-22,

PubMed Abstract | Crossref Full Text | Google Scholar

Qi, Y., Terrell, E., Bruni, G. O., Yassin, Z., and Kandel, S. L. (2025). Microbial isolates from north American sugar beet factory juices and biofilms. J. Sugar Beet Res. 62.

Google Scholar

Reichhardt, C., Matwichuk, M. L., Lewerke, L. T., Jacobs, H. M., Yan, J., and Parsek, M. R. (2025). Non-disruptive matrix turnover is a conserved feature of biofilm aggregate growth in paradigm pathogenic species. MBio 16:e0393524. doi: 10.1128/mbio.03935-24,

PubMed Abstract | Crossref Full Text | Google Scholar

Richards, F. J. (1959). A flexible growth function for empirical use. J. Exp. Bot. 10, 290–301. doi: 10.1093/jxb/10.2.290

Crossref Full Text | Google Scholar

Simões, L. C., and Simões, M. (2023). Contribution to understanding the mechanisms involved in biofilm formation, tolerance and control. Int. J. Mol. Sci. 24:9475. doi: 10.3390/ijms24119475,

PubMed Abstract | Crossref Full Text | Google Scholar

Simões, M., Simões, L. C., and Vieira, M. J. (2010). A review of current and emergent biofilm control strategies. LWT Food Sci. Technol. 43, 573–583. doi: 10.1016/j.lwt.2009.12.008

Crossref Full Text | Google Scholar

Soliman, E. A. A. (2007). Investigations on the influence of dextran during beet sugar production with special focus on crystal growth and morphology. (Ph.D): Technical University of Berlin.

Google Scholar

Team, R. C. (2016). R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

Google Scholar

Torres-Rodríguez, I., Rodríguez-Alegría, M. E., Miranda-Molina, A., Giles-Gómez, M., Conca Morales, R., López-Munguía, A., et al. (2014). Screening and characterization of extracellular polysaccharides produced by Leuconostoc kimchii isolated from traditional fermented pulque beverage. Springerplus 3:583. doi: 10.1186/2193-1801-3-583,

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, X., Liu, M., Yu, C., Li, J., and Zhou, X. (2023). Biofilm formation: mechanistic insights and therapeutic targets. Mol. Biomed. 4:49. doi: 10.1186/s43556-023-00164-w,

PubMed Abstract | Crossref Full Text | Google Scholar

Yan, M., Han, J., Xu, X., Liu, L., Gao, C., Zheng, H., et al. (2016). Gsy, a novel glucansucrase from Leuconostoc mesenteroides, mediates the formation of cell aggregates in response to oxidative stress. Sci. Rep. 6:38122. doi: 10.1038/srep38122,

PubMed Abstract | Crossref Full Text | Google Scholar

Zikmanis, P., Brants, K., Kolesovs, S., and Semjonovs, P. (2020). Extracellular polysaccharides produced by bacteria of the Leuconostoc genus. World J. Microbiol. Biotechnol. 36:161. doi: 10.1007/s11274-020-02937-9,

PubMed Abstract | Crossref Full Text | Google Scholar