Characteristics and mechanism of <i>Leuconostoc citreum</i> as a novel bioflocculant for starch granules in starch production

Xuan Wang; Pamela Owusu Osei; Lei Rao; Xiaomeng Wu; Xiaojun Liao; Xuan Wang; Pamela Owusu Osei; Lei Rao; Xiaomeng Wu; Xiaojun Liao

doi:10.48130/FIA-2023-0030

The Leuconostoc citreum SJ-57 strain isolated from the sweet potato starch production showed great potential as a microbiological flocculant, but its underlying flocculation mechanisms are yet unknown. In this study, infrared spectroscopy and thermodynamic analysis were performed to elucidate the short-range and long-range interactions between Leuc. citreum SJ-57 and starch granules, revealing that bacteria cells bond starch granules via metal-bridging ionic bonds. A high repulsive energy barrier of ~8 × 10⁻¹⁸ J must be overcome to initiate the flocculation process. Heat, protease, lipase, lysozyme, dextranase, and guanidine hydrochloride were used to treat the bacterial cell, confirming that its flocculation ability originated from surface proteins, including GW structural domain proteins, DnaK, GroEL, elongation factor Tu, and lysozyme M1. The primary flocculation mechanisms of Leuc. citreum was proposed to provide a deep understanding of microbiological flocculants and a foundation for future industrial applications in starch production.

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Introduction

Starch is the most important ingredient of human nutrition and also a critical raw material for various industries^[1]. During its production, the separation of starch is the most critical step as it determines its purity and quality. The two methods used most in the starch separation process are natural sedimentation and centrifugal separation. The natural sedimentation method has the advantages of lower production costs, lower energy consumption, and better end-product quality, but the process is often time-consuming^[2]. Therefore, in recent years, starch flocculant agents, both chemical and microbial flocculants, have been explored to accelerate starch sedimentation and improve production efficiency^[3].

Microbial flocculant (MBF) is a class of microorganisms or their metabolites displaying flocculating activity. It provides several advantages over chemical flocculants, such as being widely available, safe, easy to decompose, and free from secondary pollution^[4]. Many microorganisms and their metabolites have been studied and utilized as MBF, but their flocculation mechanisms are not yet clearly explained. Four primary mechanisms have been proposed: charge neutralization, adsorption and bridging, chemical reaction, and volume sweeping^[5]. In the charge neutralization mechanism, positively charged MBF can attract negatively charged colloids in solution by electrostatic forces. The neutralizing effect reduced the zeta potential and repulsive forces between the colloid particles, forming large flocs by van der Waals, followed by sedimentation due to gravity. The adsorption bridging mechanism often refers to establishing a bridge-like three-dimensional structure between colloids and MBF by hydrogen bonding and ionic bonding through MBF's carboxyl, hydroxyl, amino groups, et al. In contrast, the chemical reaction mechanism proposes that the MBF molecule contains some reactive groups that can react chemically with the colloidal particles in the medium to form larger flocs. Volume sweeping mechanism can be used to explain the continuous increase of the flocculation floc during sedimentation, in which flocs can sweep and capture the particles around them to form a large floc. Flocculation is a complicated process, and these mechanisms may take place at the same time. MBF is intensively researched and widely applied in many fields. One of the new trends for the application of MBF is in food production, as researchers have utilized MBF in clarifying sugar liquor and separating fermented products^[6].

Using MBF for starch production is green, energy-saving, and efficient. So far, the starch MBFs are mainly lactic acid bacteria (LAB) derived from naturally fermented starch emulsions, such as Streptococcus lactis^[7], Leuconostoc mesenteroides^[8], Acetobacter indonesiensis^[9], and Lactobacillus paracasei subsp. paracasei L1^[3]. Our previous research reported for the first time that a Leuconostoc citreum strain (SJ-57) could also serve as an efficient MBF in starch production. Using this strain could shorten the traditional production time of sweet potato starch from 6-8 h to 3 h with high purity^[10]. All these researches have demonstrated the great potential of MBF to improve the efficiency of starch production. However, the mechanism of starch flocculation by MBF is yet to be unveiled.

Zhang et al.^[3] suggested that the starch-flocculation properties of MBF could be the result of the bacterial cells' starch-binding ability. The bacterial starch-adhesive ability has been investigated in Vibrio cholerae, Bacteroides thetaiotaomicron, and other lactic acid bacteria, revealing that the starch-bind ability might be associated with bacterial surface proteins^[11−15]. For example, it was reported by Shipman et al.^[12] that outer membrane proteins, namely SusC, SusD, SusE, and SusF, were essential to starch-adhesive properties of Bacteroides thetaiotaomicron. However, these studies failed to specify the interactions between the cells and the starch granules with only partial evidence. It was found that the interaction of Bifidobacterium spp. with starch was independent of electrostatic interaction^[11]. Furthermore, Lactobacillus amylovorus's ability to utilize starch may serve as the fundamental to its ability to bind with starch^[13] . As starch granules adhere to Vibrio cholerae cells, non-specific hydrophobic interactions arose on their surfaces, along with some specific carbohydrate adhesion molecules^[14]. The mechanism behind starch flocculation can only be better understood if the interactions between the particles and bacteria are further elucidated.

Recently, we have identified and reported for the first time that the starch-flocculating activity of Leuc. citreum SJ-57 originated from their cell surface components^[10]. Critical questions remain unanswered: which cell surface components are the key contributor to its flocculating activity, and what interactions caused the flocculation? In this study, Fourier-infrared spectroscopy, zeta potential, binding inhibitors, and thermodynamic theory were introduced to systematically explore the short-range and long-range interactions between bacteria and starch. Thermal, enzymatic, and chemical treatments were used to isolate the effect of various cell surface components on the flocculation. Surface proteins involved in the cell-starch binding were also identified by mass spectrometry and SDS-PAGE. These results complement the theory of the flocculation mechanism of MBF and provide a foundation for the utilization of Leuc. citreum as a potential novel MBF.

Materials and methods

Bacterial strains, growth conditions, and harvesting

Leuc. citreum SJ-57 (CGMCC NO. 19201) was isolated from sweet potato sour liquid, as reported previously^[10]. Strains of bacteria were streaked on MRS agar plates (Aobox, China) and incubated at 37 °C for 16 h. MRS broth was inoculated with a colony from the agar plate to grow pre-cultures under the same conditions. A second culture was inoculated with pre-cultures and grown for 16 h before harvesting. The solution was centrifuged at 8,000 g for 10 min, rinsed twice with deionized (DI) water, and then suspended in sterile saline (~10⁹ CFU/mL) for future experiments.

Determination of flocculating rate (FR)

The FR of the Leuc. citreum SJ-57 was determined by measuring turbidities of the starch emulsion according to our previous method^[10]. Add 2 mL of testing culture to 25 mL of sweet potato starch solution (25 g/L) and then take an aliquot of 0.1 mL to measure the OD₅₀₀ after 20 min of reaction at room temperature. The FR was determined with sterile saline solution undergoing the same procedure as the control:

$ FR\left({\text%}\right)=\frac{{OD}_{550\;control}-{OD}_{550\;test}}{{OD}_{550\;control}}\times 100{\text%} $

Effect of thermal and enzymatic treatments on the flocculating activity of Leuc. citreum SJ-57

Cells (~10⁹ CFU/mL) were heated in the water bath at 25, 30, 35, 40, 45, 55, and 60 °C for 30 min. Cells were treated with 1 mg/mL of the following three enzymes at 37 °C for 30 min when pH = 7, respectively. 1) proteinase K from Tritirachium album, 2) β-dextranase from Chaetomium erraticum, and 3) lipase from Aspergillus. Cells were also treated with 400 μg/mL lysozyme for 15 min at 37 °C when pH = 6. After enzymatic treatments, the bacteria were rinsed three times with DI water and suspended in sterile saline (~10⁹ CFU/mL). The untreated cells were used as the control group.

Removal of surface proteins and exopolysaccharides (EPS)
Washed cells were incubated with 5 M guanidine hydrochloride (GHCl) in a shaking incubator (150 rpm) for 30 min at 37 °C to remove surface protein before being rinsed with sterile saline^[16]. The cells of the control group were untreated.

After washing, cells were treated with 1 M NaCl in a shaking incubator (150 rpm) for 0, 5, 10, 20, 40, 60, and 120 min at 37 °C before being centrifuged for 15 min at ×8,000 g. The centrifuged cells were resuspended in sterile saline. The supernatants of each treatment were lyophilized for the detection of the contents of carbohydrates in total and protein in supernatants by a phenol sulfuric acid method^[17] and the Bradford method^[18].

Isolation of starch-binding proteins
Surface proteins were extracted from bacterial cells according to a method by Malamud et al.^[16] with modification. Briefly, membranes with 0.45 μm pores were used to filter the supernatant after the bacteria were centrifuged (15 min at ×8,000 g) with 5 M GHCl. The protein-containing solutions were dialyzed at 4 °C using distilled water and then stored at −80 °C after freeze-drying. Sweet potato starch (10 mg) was added to 1 mL of surface proteins in PBS (1 mg/mL). The mixture was stirred for 30 min to allow full exposure before unbound proteins were removed by centrifugation (15 min at ×8,000 g). The Bradford method was applied to measure the protein concentration of the supernatant. Then, 40 μL of loading buffer was added to the centrifuged starch granules in 60 μL of PBS. In order to remove starch-binding proteins from the starch granules, samples were heated in boiling water for 10 min^[19]. The boiling solution was used for 10 min to resuspend whole surface proteins, unbound surface proteins, and starch-binding surface proteins for SDS-PAGE. Each sample was then run through 20 μL. After digestion with trypsin, the samples were examed with liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) by Q Exactive (Thermo Scientific, USA) and analyzed by a MaxQuant (1.6.2.10) protein identification program.

Transmission electron microscopy (TEM)
Fixation of cells in 0.05 M phosphate buffer (pH 7.2) with 2.5% glutaraldehyde was conducted. After washing with the phosphate buffer, the samples were fixed overnight at 4 °C with 1% osmium tetroxide in Kellenberger and Ryter's veronal-acetate buffer, followed by 0.5% uranyl acetate for 2 h. Epoxy resin was embedded in the specimens after dehydration through acetone. The samples were sliced by a Sorval Porter-Blum MT-1 ultramicrotome, stained with lead citrate, and observed in an 85-kV JEOL 12000EXII TEM (Jeol Ltd.)^[20].

Examination of the interactions between cells and starch granules
To investigate the hydrogen bond and ionic bonds between starch and bateria, the washed bacterial cells were suspended in KCl (10 mmmol/L) and CaCl₂ (10 mmmol/L), respectively, and then attached to starch granules by mixing with 25 g/L starch granules as described above. The supernatant was discarded after complete sedimentation for 20 min, and the starch sediment was pretreated with 2 mL of 5 M urea, 10 mmol/L HCl, and 10 mmol/L EDTA for 5 min at 20 °C, respectively, before being reconstituted into a starch emulsion (25 g/L, pH = 7) by adding KCl (10 mmmol/L) and CaCl₂ (10 mmmol/L), respectively. The FR of each treatment was determined as above.

Zeta potentials in various flocculation systems
The Zeta potential of the bacterial cells (~10⁸ CFU/mL) and starch granules (1 g/L) were measured in the presence of 0–10 mM of KCl, NaCl, CaCl₂, MgCl₂ at pH = 7 using a Malvern Zetasizer Nano System (Brookhaven Instruments Corporation, USA)^[21].

Fourier Transform-Infrared (FT-IR) spectroscopy
The chemical compositions of Leuc. citreum SJ-57 surface, starch granules, and bacteraia-adhered starch granules were examined using a Bio-Rad FTS 135 spectrometer (Hercules, CA, USA) in the reflectance mode, ranging 400 to 4,000 cm⁻¹.

Contact angle measurement and surface energy estimation

The contact angles of bacteria and starch were analyzed using the sessile drop method. Briefly, rinsed cells were kept in 10 mM KCl at pH = 7 for 4 h and then harvested by filtration through cellulose acetate membranes with 0.45 mm pore sizes (Beijing Solarbio Science & Technology Co., Ltd., China) to create a cell layer and air-dried at room temperature. Starch granules were also kept in 10 mM KCl at pH = 7 for 4 h and then lyophilized for detection. The probe liquids used and their properties are summarized in Table 1.

Table 1. Surface tension parameters of probe liquids used for contact angle measurements for Leuc. citreum SJ-57 and starch granules.

Surface tension parameters (mJ/m²)
	γ^LW	γ⁺	γ⁻	γ^Tot
H₂O	21.8	25.5	25.5	72.8
C₃H₈O₃	34.0	3.9	57.4	64.0
CH₂I₂	50.8	0.0	0.0	50.8
Note: γ^LW represents the LW component of the surface tension. γ⁺ and γ^- are the electron-acceptor and electron-donor parameters of the surface tension, respectively.

The hydrophobicity of bacteria and starch was expressed in ΔG_iwi, with i representing particles and w representing water^[22].

$ {\Delta G}_{iwi}={-2\left(\sqrt{{\mathrm{\gamma }}_{i}^{LW}}-\sqrt{{\mathrm{\gamma }}_{w}^{Lw}}\right)}^{2}-4\left(\sqrt{{\mathrm{\gamma }}_{i}^+}-\sqrt{{\mathrm{\gamma }}_{w}^-}\right)\left(\sqrt{{\mathrm{\gamma }}_{i}^+}-\sqrt{{\mathrm{\gamma }}_{w}^-}\right) $

(1)

Where γ^LW is the Lifshitz–van der Waals (LW) parameter of the surface tension (mJ/m²), and γ⁺ and γ⁻ are the electron-acceptor and electron-donor parameter (mJ/m²), respectively.

Contact angles were measured with three different probe liquids (one non-polar and two polar), and Young's Equation was applied to determine the three unknown entities $\gamma_i^{LW} $, $\gamma_i^+ $ and $\gamma_i^- $, in Eqn (2)^[23].

$ {\mathrm{\gamma }}_{l}^+(1+\mathrm{cos}{\theta }_{li})=2\left(\sqrt{{\mathrm{\gamma }}_{l}^{Lw}{\mathrm{\gamma }}_{i}^{LW}}+\sqrt{{\mathrm{\gamma }}_{l}^+{\mathrm{\gamma }}_{i}^-}+\sqrt{{\mathrm{\gamma }}_{l}^-{\mathrm{\gamma }}_{i}^+}\right) $

(2)

where θ is the contact angle, and the indices l and i denote solids and liquids.

Interaction energy calculations

Calculation of Leuc. citreum SJ-57–starch interaction energy profiles

The Derjaguin, Landau, Verwey, and Overbeek (DLVO) theory was applied to calculate the interaction energies between the bacteria and starch^[22]. By considering the system using the sphere-slab model, total interaction energies were calculated as the sum of three interactions^[24].

$ {G}_{}^{Tot}\left(d\right)={G}_{}^{LW}\left(d\right)+{G}_{}^{EL}\left(d\right)+{G}_{}^{AB}\left(d\right) $

(3)

Where LW, EL, and AB denote van der Waals, electrostatic interactions, and Lewis acid/base interactions, respectively.

G^LW(d) was calculated using the following expression:

$ {G}_{1W2}^{LW}\left(d\right)=\frac{-{A}_{1W2}{r}_{1}}{6d}\left[1+\frac{d}{2{r}_{1}+d}+\frac{d}{r}\mathrm{l}\mathrm{n}\left(\frac{d}{2{r}_{1}+d}\right)\right] $

(4)

Where r₁ is the equivalent bacterial radius (m). A_1w2 is the Hamaker constant (J), a combination of bacteria (1) and starch (2) in water (w), calculated via Eqn (5):

$ {A}_{1w2}=-24\pi {d}_{0}^{2}\left(\sqrt{{\gamma }_{1}^{LW}}-\sqrt{{\gamma }_{W}^{LW}}\right)\left(\sqrt{{\gamma }_{2}^{LW}}-\sqrt{{\gamma }_{W}^{LW}}\right) $

(5)

G^EL(d) was formulated as^[23]:

$ \begin{aligned}{G}_{1w2}^{EL}\left(d\right)=&\;\pi \epsilon {r}_{1}\Bigg\{2{\psi }_{1}{\psi }_{1}ln\left[\frac{1+\mathrm{e}\mathrm{x}\mathrm{p}(-\kappa d)}{1-\mathrm{e}\mathrm{x}\mathrm{p}(-\kappa d)}\right]\\&+\;\left({\psi }_{1}^{2}+{\psi }_{1}^{2}\right)ln\left[1-\mathrm{e}\mathrm{x}\mathrm{p}(-2\kappa d)\right]\Bigg\} \end{aligned}$

(6)

Where ε is the dielectric constant of water; ψ₁ and ψ₂ are the surface potential of the starch and bacterium, respectively, which are assessed from zeta potentials based on ψ = zeζ/κT; z represents the ion valence.

As shown in Van Oss^[23], κ is the reverse of the Debye length (m⁻¹):

$ \mathrm{\kappa }=\sqrt{\frac{2{e}^{2}{N}_{A}I}{\mathrm{\epsilon }{K}_{B}T}} $

(7)

Where e represents the elementary charge; N_A denotes Avogadro's number; k_B is Boltzmann's constant; T is the absolute temperature; I denotes the solution ionic strength.

This equation was used to calculate G^AB(d):

$ {G}_{1W2}^{AB}\left(d\right)=2\pi {r}_{1}\lambda \Delta {G}_{d0}^{AB}\mathrm{e}\mathrm{x}\mathrm{p}\left(\frac{{d}_{0}-d}{\lambda }\right) $

(8)

Where λ is the decay length of AB interactions. d₀ is the minimum equilibrium distance. From the surface tension parameters, ΔGAB d0 can be determined as the Lewis acid/base free energy of the bacterium-starch interaction at a minimum separation distance (d₀).

$\begin{aligned} {\Delta G}_{d0}^{AB}=\;&\;2\left(\sqrt{{\gamma }_{1}^+}-\sqrt{{\gamma }_{2}^+}\right)\left(\sqrt{{\gamma }_{2}^-}-\sqrt{{\gamma }_{2}^-}\right)\\&-\;2\left(\sqrt{{\gamma }_{1}^+}-\sqrt{{\gamma }_{w}^+}\right)\left(\sqrt{{\gamma }_{1}^-}-\sqrt{{\gamma }_{w}^-}\right) \\&-\;2\left(\sqrt{{\gamma }_{2}^+}-\sqrt{{\gamma }_{w}^+}\right)\left(\sqrt{{\gamma }_{2}^-}-\sqrt{{\gamma }_{w}^-}\right)\end{aligned} $

(9)

Calculation of bacteria-bacteria and starch-starch interaction energy profiles

The DLVO theory was used to obtain the interaction energy between cell-cell and starch-starch. The interaction energies were calculated with the sphere–sphere model as follows^[23]:

$ {G}_{1w2}^{LW}\left(d\right)=\frac{-{A}_{1w2}{r}_{1}{r}_{2}}{6d({r}_{1}+{r}_{2})} $

(10)

$\begin{aligned} {G}_{1w2}^{EL}=\;&\;\pi \epsilon \frac{{r}_{1}{r}_{2}({\psi }_{1}^{2}+{\psi }_{2}^{2})}{({r}_{1}+{r}_{2})}\Bigg\{\frac{2{\psi }_{1}{\psi }_{2}}{{\psi }_{1}^{2}+{\psi }_{2}^{2}}ln\left[\frac{1+\mathrm{e}\mathrm{x}\mathrm{p}(-\kappa d)}{1-\mathrm{e}\mathrm{x}\mathrm{p}(-\kappa d)}\right]\\&+\;ln\left[1-\mathrm{e}\mathrm{x}\mathrm{p}(-2\kappa d)\right]\Bigg\} \end{aligned}$

(11)

$ {G}_{1w2}^{AB}\left(d\right)=\pi \lambda \frac{{r}_{1}{r}_{2}}{({r}_{1}+{r}_{2})}\Delta {G}_{d0}^{AB}\mathrm{e}\mathrm{x}\mathrm{p}\left(\frac{{d}_{0}-d}{\lambda }\right) $

(12)

Where r₁ and r₂ are the equivalent bacterial radius (m) and starch radius (m), respectively, and the remaining parameters were the same as above.

Statistical analysis

All experiments were conducted in triplicate, and the results were reported as mean ± standard deviation. One-way analysis of variance with Duncan's test was performed with IBM SPSS Statistics 25 (SPSS Inc., Chicago, IL, USA) with α = 0.05.

Conclusions

In this study, the primary mechanism of how Leuc. citreum SJ-57 flocculate starch was proposed after thoroughly investigating the short-range and long-range interactions between bacteria and starch granules. Essential bacteria surface proteins interacting with starch through simultaneous ionic bonds with metal cations were identified, i.e., GW structural domain proteins, DnaK, GroEL, elongation factor Tu, and lysozyme M1. The negative effect of EPS and the positive effect of the intact bacterial cell on the flocculation rate were explained. This study provided a deeper understanding of the mechanism of microbiological flocculants and a foundation for their future industrial application in starch production.

Author contributions

The authors confirm contribution to the paper as follows: study conception and design: Liao X, Wu X, Rao L, Wang X; data collection: Wang X; analysis and interpretation of results: Wang X; draft manuscript preparation: Wang X, Osei P. All authors reviewed the results and approved the final version of the manuscript.

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	Contact angles (degree)			Surface tension parameters (mJ/m²)			ΔG_iwi (mJ/m²)
	H₂O	C₃H₈O₃	CH₂I₂	γ^LW	γ⁺	γ⁻	ΔG_iwi (mJ/m²)
Leuc. citreum SJ-57	53.5 ± 4.3	49.2 ± 2.0	24.5 ± 2.9	46.3	0.3	21.9	−15.8
Starch	26.8 ± 2.8	31.3 ± 7.5	18.5 ± 2.7	48.2	41.6	0.6	13.7
The contact angles are presented as the means ± standard error. Parameters γ^LW, γ^+, and γ⁻ are the surface tension components. Hydrophobicity was evaluated by ΔG_iwi, which was calculated using the surface tension parameters according to Eqn (2).

Band	Protein	Accession number	Number of matches	Score	Isoelectric point	Molecular weight (KD)
1	GW (glycine-tryptophan)) dipeptide domain-containing	WP_146992371.1	154	3546	5.26	230
2	GW (glycine-tryptophan)) dipeptide domain-containing	WP_146992371.1	867	22986	5.26	230
3	GW (glycine-tryptophan)) dipeptide domain-containing	WP_146992371.1	761	18792	5.26	230
4	molecular chaperone DnaK	WP_040177072.1	281	6808	4.60	65
5	Chaperonin GroEL	WP_004901547.1	1085	28391	4.60	57
6	Elongation factor Tu	WP_004900335.1	297	6485	4.82	43
7	Lysozyme M1	WP_004901157.1	974	26689	5.08	36
8	Lysozyme M1	WP_004901157.1	110	2473	5.08	36

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Characteristics and mechanism of Leuconostoc citreum as a novel bioflocculant for starch granules in starch production

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Characteristics and mechanism of Leuconostoc citreum as a novel bioflocculant for starch granules in starch production

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Bacterial strains, growth conditions, and harvesting

Determination of flocculating rate (FR)

Effect of thermal and enzymatic treatments on the flocculating activity of Leuc. citreum SJ-57

Removal of surface proteins and exopolysaccharides (EPS)

Isolation of starch-binding proteins

Transmission electron microscopy (TEM)

Examination of the interactions between cells and starch granules

Zeta potentials in various flocculation systems

Fourier Transform-Infrared (FT-IR) spectroscopy

Contact angle measurement and surface energy estimation

Interaction energy calculations

Calculation of Leuc. citreum SJ-57–starch interaction energy profiles

Calculation of bacteria-bacteria and starch-starch interaction energy profiles

Statistical analysis

The short-range interactions between cells and starch granules

FT-IR analysis

FR and zeta potential of cells and starch granules in different ionic strength

Disruption of the interactions between cells and starch

Long-range interaction between cells and starch granules

Cell-cell and starch-starch interaction

Starch-flocculating ability of Leuc. citreum SJ-57's cell surface components

The effect of thermal and enzymatic treatments on the starch-flocculating ability of Leuc. citreum SJ-57

Cell surface proteins' starch binding capacity

Contribution of EPS and cell wall to flocculation capacity

Contribution of the cell wall to starch flocculation capacity

Catalog

Supplemental Fig. S1 Effect of different pH on the FR of Leuconostoc citreum SJ 57.
Supplemental Fig. S2 SDS-PAGE analysis of whole cell surface proteins (lane 1) and proteins in the eluent (lane 2). The molecular masses (in kDa) of the standard proteins (lane M) were indicated on the left.

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Characteristics and mechanism of Leuconostoc citreum as a novel bioflocculant for starch granules in starch production

Abstract

Supplementary Information

Rights and permissions

References

About this article

Cite this article

Article Metrics

Access History

Other Articles By Authors

Characteristics and mechanism of Leuconostoc citreum as a novel bioflocculant for starch granules in starch production

HTML

Bacterial strains, growth conditions, and harvesting

Determination of flocculating rate (FR)

Effect of thermal and enzymatic treatments on the flocculating activity of Leuc. citreum SJ-57

Removal of surface proteins and exopolysaccharides (EPS)

Isolation of starch-binding proteins

Transmission electron microscopy (TEM)

Examination of the interactions between cells and starch granules

Zeta potentials in various flocculation systems

Fourier Transform-Infrared (FT-IR) spectroscopy

Contact angle measurement and surface energy estimation

Interaction energy calculations

Calculation of Leuc. citreum SJ-57–starch interaction energy profiles

Calculation of bacteria-bacteria and starch-starch interaction energy profiles

Statistical analysis

The short-range interactions between cells and starch granules

FT-IR analysis

FR and zeta potential of cells and starch granules in different ionic strength

Disruption of the interactions between cells and starch

Long-range interaction between cells and starch granules

Cell-cell and starch-starch interaction

Starch-flocculating ability of Leuc. citreum SJ-57's cell surface components

The effect of thermal and enzymatic treatments on the starch-flocculating ability of Leuc. citreum SJ-57

Cell surface proteins' starch binding capacity

Contribution of EPS and cell wall to flocculation capacity

Contribution of the cell wall to starch flocculation capacity

Catalog

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