Characterization of an extracellular thermophilic alkaline esterase produced by Bacillus subtilis DR8806

Asoodeh, Ahmad; Ghanbari, Tahereh

doi:10.1016/j.molcatb.2012.08.013

Cited by 21 publications

(12 citation statements)

References 46 publications

(45 reference statements)

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“…Similar results were also reported for esterases of Streptococcus thermophiles and Bacillus licheniformis S-86 [28,33]. respectively [34]. The K m values of enzymes range widely, but for most industrially used enzymes they lie in the range of 10 -1 to 10 -5 M when acting on biotechnologically important substrates, under normal reaction conditions.…”

Section: Effect Of Some Metal Ions On the Enzyme Activitysupporting

confidence: 80%

Purification and characterization of a novel thermostable esterase from Thermus sp. NCCB 100425T

Akatin

2015

Turk J Bioch

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Purification and characterization of a novel thermostable esterase from Thermus sp. NCCB 100425 T [Thermus sp. NCCB 100425 T ' den yeni bir ısıya dayanıklı esterazın saflaştırılması ve karakterizasyonu] ABSTRACT Objective: The purpose of the present study was to purify and characterize an esterase from a thermophilic bacterium Thermus sp. NCCB 100425 T and to check its suitability for industrial applications. Methods: Thermus sp. NCCB 100425 T esterase was purified by using ammonium sulphate precipitation and hydrophobic interaction chromatography and then characterized biochemically. Results: The purity of the enzyme was observed as a single band on native-and SDS-PAGE. In the presence of p-nitrophenyl acetate (pNPA) as a substrate, the optimum pH and temperature of the enzyme were found to be 7.5 and 60°C, respectively. K m and V max values are calculated as 18.32 mM and 96.15 U/mg protein, respectively, with pNPA. pH stability was investigated in the range of pH 4.0-9.0 at 4°C and 60°C. After 7 days incubation, activity of pure enzyme was retained 85-90% for all pH at 4°C and 59±5.2% for pH 8.0 at 60°C. It was determined that approximately 80% of enzyme activity was retained between 30-60°C after 7 days incubation. In the presence of 10% ethanol and DMSO, the enzyme activity was retained 96±2.7% and 78±2.5%, respectively. Additionally, it was detected that some metal ions affect the enzyme activity at different ratios. T esterazı amonyum sülfat çöktürmesi ve hidrofobik etkileşim kromatografisi kullanılarak saflaştırıldı ve biyokimyasal özellikleri incelendi. Bulgular: Doğal-ve SDS-PAGE'de tek bant şeklinde görülen saf enzimin, p-nitrofenil asetat (pNPA) varlığında optimum pH ve sıcaklık değerleri sırasıyla 7,5 ve 60°C olarak belirlendi. Yine pNPA bir substrat olarak kullanıldığında K m ve V max değerlerinin 18,32 mM ve 96,15 U/ mg protein olduğu tespit edildi. pH kararlılığı pH 4,0-9,0 aralığında 4°C ve 60°C'de incelendi. 7 günlük bir inkübasyondan sonra saf enzimin aktivitesinin 4°C'de bütün pH'larda yaklaşık %85-90 oranında korunduğu, bu oranın 60°C'de pH 8,0'de ise %59±5,2 olduğu görüldü. 30-60°C'ler arasında 7 gün inkübe edilen enzim, orijinal aktivitesini %80 oranında korudu. %10 nihai konsantrasyondaki etanol ve DMSO varlığında enzim aktivitesi sırasıyla %96±2,7 ve %78±2,5 oranlarında korundu. Ayrıca, bazı metal iyonlarının enzim aktivitesini farklı oranlarda etkilediği tespit edildi. Sonuç: Bütün bu sonuçlar değerlendirildiğinde Thermus sp. NCCB 100425 T esterazının özel-likle yüksek sıcaklık-ve pH-kararlılığı nedeniyle endüstriyel ve/veya klinik uygulamalar için avantajlara sahip olabileceği açıkça görülmektedir. Thus, this study can be considered as a step to obtain an industrially suitable esterase having excellent features. ) and solvents were purchased from Merck A.G. (Darmstadt, Germany). All chemicals were analytical and microbiological grade. Conclusion Materials and Methods Chemicals Bacterial strain and crude enzyme extractionThermus sp. NCCB 100425 T bacterial strain isolated from a geotherm...

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Section: Effect Of Some Metal Ions On the Enzyme Activitysupporting

confidence: 80%

Purification and characterization of a novel thermostable esterase from Thermus sp. NCCB 100425T

Akatin

2015

Turk J Bioch

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“…T1 [3]. An esterase from Bacillus subtilis DR8806 showed an optimal temperature at 50 • C as a mesophilic enzyme [19]. The recombinant enzyme retained 90% and 87.5% of its initial activity after incubation at 75 • C and 80 • C for 1 h, respectively.…”

Section: Effect Of Temperature On Enzyme Activity and Stabilitymentioning

confidence: 99%

“…The optimum pH of B. subtilis DR8806 lipase was identical to that of other thermophilic lipases from B. subtilis EH 37 [16], Bacillus sphaericus 205y [17], Bacillus sp. L2 [18] and a lipolytic enzyme from B. subtilis DR8806 [19]. The pH stability of enzyme showed that it was stable (>90% of lipase activity) at pH values ranging from 8.0 to 10.0 upon a 60-min treatment at 50 • C in Tris-HCl buffer.…”

Section: Ph Profile and Stabilitymentioning

confidence: 99%

Molecular cloning of a thermo-alkaliphilic lipase from Bacillus subtilis DR8806: Expression and biochemical characterization

Emtenani

Asoodeh

Emtenani

2013

Process Biochemistry

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“…Many chemical reagents, in particular metal ions, can either promote or inhibit the activity of proteases (Torres‐Fuentes et al . ; Asoodeh and Ghanbari ). So if proteases of A. oryzae are treated using different chemical reagents, the proteases activity will be altered to obtain various ratios of protease components.…”

Section: Introductionmentioning

confidence: 98%

“…The ratio of protease components of A. oryzae is influenced by multiple interrelated factors, such as fermentation time, temperature, pH and chemical reagent (Belmessikh et al 2013). Many chemical reagents, in particular metal ions, can either promote or inhibit the activity of proteases (Torres-Fuentes et al 2012;Asoodeh and Ghanbari 2013). So if proteases of A. oryzae are treated using different chemical reagents, the proteases activity will be altered to obtain various ratios of protease components.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Hydrolytic Capacities of Aspergillus oryzae Proteases on Soybean Protein Using Artificial Neural Networks

Hong

et al. 2015

Journal of Food Processing and Preservation

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An artificial neural network (ANN) model was established to predict the hydrolytic capacities of Aspergillus oryzae proteases on soybean protein. The available training data were split in two subsets: training and testing data, which comprised 25 and six groups of proteases, respectively. These data served as the inputs of ANN to predict small peptide content, degree of hydrolysis and free amino nitrogen content. This network included three neurons in the single hidden layer with a low mean squared error. The predicted results were similar to the actual values (R 2 > 0.92) and were superior to those of multiple linear regression. Sensitivity analysis revealed that there is a correlation between protease and soy protein hydrolysates. It was also verified that protease and soy protein hydrolysates could serve as inputs and outputs in the ANN. Among the tested proteases, aminopeptidase showed the highest hydrolytic capacity for soybean protein with sensitivity analysis. PRACTICAL APPLICATIONSThe artificial neural network model is a powerful technique to predict the hydrolytic capacities of Aspergillus oryzae proteases for soybean protein. The results of this study could be used to test the amount of yielded hydrolysates of soybean protein under one combination protease, and also explained the mechanism underlying the protease-catalyzed hydrolysis of soybean.

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Characterization of an extracellular thermophilic alkaline esterase produced by Bacillus subtilis DR8806

Cited by 21 publications

References 46 publications

Purification and characterization of a novel thermostable esterase from Thermus sp. NCCB 100425T

Purification and characterization of a novel thermostable esterase from Thermus sp. NCCB 100425T

Molecular cloning of a thermo-alkaliphilic lipase from Bacillus subtilis DR8806: Expression and biochemical characterization

Analysis of the Hydrolytic Capacities of Aspergillus oryzae Proteases on Soybean Protein Using Artificial Neural Networks

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