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Levan

Levan is a polysaccharide produced by certain bacteria and fungi.
It is composed of fructose units linked by β-2,6 glycosidic bonds.
Levan has a variety of industrial and medical applications, including use as a prebiotic, a drug delivery agent, and a wound healing enhancer.
Reserach into the production, purification, and utilization of levan is an active area of study.
The platform PubCompare.ai leverages artificial intelligence to optimize levan research protocols, helping scientists identify the best methods and products to enhance reproducibilty and accuracy in their work.

Most cited protocols related to «Levan»

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Publication 2014
Cloning Vectors Gamma Rays levan Strains
Settled surface dust was collected from two different swine confinement facilities (housing 400–600 hogs), the storage facilities at two different grain elevators, and two different pet-free domestic homes as a control. The dust samples were obtained from surfaces approximately 3–5 feet above the floor to ensure the sampled dust had been airborne and potentially inhaled by a worker. Permission was granted by the owners of the swine confinement facilities, grain elevator facilities, and households to obtain samples in an anonymous manner. Total genomic DNA was isolated by bead beating following the manufacturer’s instructions (Mo Bio, PowerSoil Kit, Carlsbad, CA), then assayed using a Nanodrop ND-1000 UV spectrophotometer (NanoDrop Technologies, Wilmington, DE). Each DNA sample (3–5 µg) was used to prepare a shotgun pyrosequencing library using a kit for this purpose (Roche Applied Science, Indianapolis, IN) according to the manufacturer’s protocol. The multiple id, barcoded template DNAs were combined in equal amounts and titrated to obtain the optimal copies per bead (3 copies per bead). Emulsion PCR and pyrosequencing were performed with the Roche/454 Life Sciences’ Lib-L (LV) and XLR70 kits, respectively. Multiplexed shotgun metagenomic DNA pyrosequencing was performed by the Core for Applied Genomics and Ecology Laboratory at the University of Nebraska, Lincoln, using a Roche/454 Life Sciences’ GS FLX Titanium instrument (Branford, CT). GS FLX Off-Instrument Software was used to de-multiplex raw pyrosequencing reads into sample-specific bins. These six shotgun pyrosequencing metagenomic read datasets are publicly available at MG-RAST [DNAdustGrainTLV2011s (4465551.3), DNAdustGrainTLV2011e (4465547.3), DNAdustSwineTLV2011f (4465549.3), DNAdustSwineTLV2011n (4465550.3), DNAdustHouseTLV2011n (4465546.3), DNAdustHouseTLV2011p (4465548.3)].
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Publication 2014
Cereals DNA Library Emulsions Foot Genome Households Metagenome Pigs Radioallergosorbent Test Titanium Workers
Stool samples from 308 infants were extracted using a modified cetyltrimethylammonium bromide (CTAB) buffer based protocol13 (link). Briefly, 0.5 ml of modified CTAB extraction buffer were added to 25 mg of stool in a 2 ml Lysing Matrix E tube (MP Biomedicals, Santa Ana, CA) then incubated (65 °C, 15 min). Samples were bead–beaten (5.5 m s−1, 30 sec) in a Fastprep–24 (MP Biomedicals, Santa Ana, CA) followed by the addition of 0.5 ml of phenol:chloroform:isoamyl alcohol (25:24:1). Following centrifugation (14,000 rpm, 5 min), the supernatant was added to a heavy phase–lock gel tube (5 Prime, Gaithersburg, MD) and chloroform (v:v) was added. Samples were centrifuged (14,000 rpm, 5 min); resulting supernatants were added to fresh tubes, followed by addition of 1 μl of linear acrylamide prior to PEG–NaCl (2v:v). Samples were incubated (21 °C, 2 h), washed with 70% EtOH and resuspended in 10 mM Tris–Cl, pH 8.5.
Publication 2016
Acrylamide Buffers Centrifugation Cetrimonium Bromide Chloroform Ethanol Feces Infant isopentyl alcohol Phenols Sodium Chloride Tromethamine
For bacterial sequences, paired–end sequences were assembled using FLASH16 (link) v 1.2.7, demultiplexed by barcode, and low quality reads (Q–score < 30) were discarded in QIIME17 1.8. If three consecutive bases were < Q30, then the read was truncated and the resulting read retained in the data set only if it was at least 75% of the original length. Sequences were checked for chimeras using UCHIME18 (link) and filtered from the dataset prior to OTU picking at 97% sequence identification using UCLUST19 (link) against the Greengenes database20 (link) version 13_5. Those sequence reads that failed to cluster with a reference sequence were clustered de novo. Sequences were aligned using PyNAST21 (link), and taxonomy assigned using the RDP classifier and Greengenes reference database version20 (link) 13_5. To de–noise the OTU table, taxa with less than 5 total sequences across all samples were removed. A bacterial phylogenetic tree was built using FastTree22 (link) 2.1.3.
Fungal sequences were quality trimmed (Q–score < 25) and adapter sequences removed using cutadapt23 prior to assembling paired–end reads with FLASH16 (link). Sequences were de–multiplexed by barcode and truncated to 150 bp prior to clustering using USEARCH vers. 7 pipeline, specifically the UPARSE24 function, and chimera–checked using UCHIME. Taxonomy was assigned using UNITE25 (link) vers. 6.
To normalize variation in read depth across samples, data were rarefied to the minimum read depth of 202,367 sequences per sample for bacteria (n = 298) and 30,590 for fungi (n = 188). To ensure that a truly representative community was used for analysis for each sample, sequence sub–sampling at these defined depths was rarefied 100 times. The representative community composition for each sample was defined as that which exhibited the minimum average Euclidean distance to all other OTU vectors generated from all sub–samplings for that particular sample. Investigators at UCSF were blinded to sample identity until microbiota datasets underwent the aforementioned processing and were ready for statistical analyses.
Publication 2016
Bacteria Chimera Cloning Vectors Fungi Microbial Community Versed
Stool samples from 308 infants were extracted using a modified cetyltrimethylammonium bromide (CTAB) buffer based protocol13 (link). Briefly, 0.5 ml of modified CTAB extraction buffer were added to 25 mg of stool in a 2 ml Lysing Matrix E tube (MP Biomedicals, Santa Ana, CA) then incubated (65 °C, 15 min). Samples were bead–beaten (5.5 m s−1, 30 sec) in a Fastprep–24 (MP Biomedicals, Santa Ana, CA) followed by the addition of 0.5 ml of phenol:chloroform:isoamyl alcohol (25:24:1). Following centrifugation (14,000 rpm, 5 min), the supernatant was added to a heavy phase–lock gel tube (5 Prime, Gaithersburg, MD) and chloroform (v:v) was added. Samples were centrifuged (14,000 rpm, 5 min); resulting supernatants were added to fresh tubes, followed by addition of 1 μl of linear acrylamide prior to PEG–NaCl (2v:v). Samples were incubated (21 °C, 2 h), washed with 70% EtOH and resuspended in 10 mM Tris–Cl, pH 8.5.
Publication 2016
Acrylamide Buffers Centrifugation Cetrimonium Bromide Chloroform Ethanol Feces Infant isopentyl alcohol Phenols Sodium Chloride Tromethamine

Most recents protocols related to «Levan»

The following ingredients make up the basal broth medium (BM) for the yield of levan: sucrose (80), yeast extract (1.0), K2HPO4 (1.0), and MgSO4 (0.2)21 . The chosen isolates were each given a freshly made culture that was placed separately into a 250 mL Erlenmeyer flask. Each flask held 50 mL of the sample (BM).
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Publication 2024
Scanning electron microscopy (SEM) of synthesized levan CSPs was carried out using a JOEL JSM-7000F field-emission scanning electron microscope.
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Publication 2024
The appropriate levan derivative was dissolved in dichloromethane. The solution was added to depolarized silica gel (3.00 g), and the mixture was sonicated for a few minutes. The solvent was removed with a rotary evaporator. The resulting chiral stationary phase was suspended in 2-propanol and passed through a sieve. The suspension was then filtered, and the separated chiral stationary phase was dried overnight in an electric dryer. After drying, the stationary phase was packed into the stainless-steel column (250 mm × 4.6 mm I.D.), using a conventional high-pressure slurry packing technique with a Knauer pneumatic HPLC pump (Knauer GmbH, Berlin, Germany).
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Publication 2024
Following PBD’s estimation of the most important elements for levan production, CCD is used to identify the best concentration of these three factors (sucrose, incubation time, and sugarcane bagasse) that scored the highest positive effect.
The five coded levels (− 2, − 1, 0, + 1, + 2) for the study’s variables led to a total of 20 experimental trials, including 8 factorial design trials, 6 axial point trials, and 6 replications of the central point trials (Table 2). The optimal setting established in the prior studies was maintained for all other factors. Using a multiple regression technique, the following second-order polynomial was used to represent the results of CCD: Y=β0+Σβi Xi+Σβii X2i+Σβij Xi Xj.

CCD for levan production.

RunSucrose conc. (g/L)Incubation time (hours)Sugar cane (g/f)Levan weight (g/L)Levan predicted value
195364.2526.0027.28
2130246.0081.5066.41
3130242.5026.0025.96
495364.2523.7027.28
536.15364.2510.306.35
695364.2526.3027.28
760486.0015.209.21
89556.184.2527.2024.49
9153.86364.2540.3048.20
1095361.3123.0017.65
1160246.0016.5015.88
1295367.1929.0036.90
13130482.5031.4026.00
14130486.0042.0040.50
1560482.5017.7026.76
1695364.2525.1027.28
1795364.2522.3027.28
189515.824.2523.0030.06
1995364.2527.0027.28
2060242.5012.007.48
Y and β0 are the predicted response and the intercept term, respectively. βi means the linear coefficients, and βii is the quadratic coefficients. βij means the interactive coefficients, and xi and xj represent independent variables coded.
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Publication 2024
This study has been concerned with identifying the factors affecting levan production in a parallel way using PBD25 (link). Also, this study used the statistical design to apply the coculture technique by studying it as a factor and determining the most suitable isolates to act together synergistically for levan production.
Eleven components (sucrose, yeast, K2HPO4, MgSO4, isolates; I1, K2, V2, G1, sugarcane bagasse, banana peel, and incubation time) were selected for the study (Table 1). Each variable has two levels: high value (+ 1) and low value (− 1). A 12-run experiment was generated using the formula R = n + 1, where n is the number of variables and R is the run number.

PBD for levan production.

RunA: sucrose (g/L)B: yeast (g/L)C: K2HPO4 (g/L)D: MgSO4 (g/L)E:I1 (ml/f)F: K2 (ml/f)G: V2 (ml/f)H: G1 (ml/f)J: sugarcane (g/f)K: banana peel (g/f)L: incubation time (hours)Levan weight (g/L)Levan predicted value
10110.144412.51488.58.83
21200.510.2400151483736.67
300.50.250.100012.51244040.27
412010.250.244012.522428.328.63
5120110.1004152242120.67
612010.250.1040451485251.73
71200.50.250.140442.524827.327.57
800.510.144045224109.73
91200.510.204442.512421.421.73
100110.200042.524844.27
11010.250.2404451242.21.87
1200.50.250.20441524810.910.63

N.B. I1, K2, V2, and G4 are bacterial honey isolates.

The PB experimental design is built on the first-order model shown below. Y=β0+i=0kBiXi, where Xi is the level of the independent variable, Y is the response (levan production), B0 is the model intercept, Bi is the linear coefficient, and k is the total number of variables involved.
The response variable for each experiment was the average production, and trials were conducted in triplicate. Standard mistakes in a balanced design should be comparable to one another. Reduced standard errors are preferable. VIF and Ri2 should both be set to 1.0. A high Ri2 suggests that sentences are interconnected.
Further optimization trials evaluated the factors that, according to regression analysis, showed a significant impact on production (95% confidence level, Prob > F 0.05).
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Publication 2024

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Levan is a microbial polysaccharide produced by certain strains of bacteria. It functions as a non-digestible carbohydrate with prebiotic properties, supporting the growth of beneficial gut microbiota.
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Inulin is a type of carbohydrate that is commonly used in laboratory settings. It is a soluble dietary fiber that is extracted from various plant sources, such as chicory root. Inulin serves as a prebiotic, supporting the growth of beneficial gut bacteria.

More about "Levan"

Levan is a versatile polysaccharide produced by certain bacteria and fungi.
This fructose-based biopolymer, composed of β-2,6 glycosidic bonds, has garnered significant interest in the scientific community due to its diverse industrial and medical applications.
As a prebiotic, levan has the potential to promote the growth of beneficial gut microbiota, making it a promising candidate for gut health applications.
Additionally, its unique properties as a drug delivery agent and wound healing enhancer have fueled ongoing research into its utilization in pharmaceutical and biomedical fields.
The study of levan production, purification, and optimization is an active area of investigation.
Researchers leverage advanced analytical tools, such as the Image-Pro Plus 4.5 software and BX50, BX51, and BX53 microscopes, to characterize and analyze levan samples.
The MirVana miRNA Isolation Kit and ChemiDoc Touch Imaging System may also be employed to facilitate the extraction and characterization of levan.
Beyond levan, related polysaccharides like inulin, a fructan with structural similarities, are also explored for their potential applications.
The insights gained from levan research can potentially be applied to the study and utilization of other biopolymers, expanding the horizons of biomaterial science and biotechnology.
By harnessing the power of artificial intelligence, platforms like PubCompare.ai are revolutionizing the way scientists approach levan research.
These AI-driven tools enable researchers to optimize their protocols, identify the most effective methods and products, and enhance the reproducibility and accuracy of their work, ultimately accelerating advancements in this dynamic field of study.