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Studies On Griseofulvin Production From Penicillium Patulinum HHB1-31

Posted on:2021-04-07Degree:MasterType:Thesis
Country:ChinaCandidate:Y LeiFull Text:PDF
GTID:2481306515493444Subject:Microbiology
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Since 1958,griseofulvin has been used in clinical applications,and has a good effect on superficial filamentous fungal infections.Griseofulvin has been applied in animal husbandry,aquatic products and plant fungal diseases.Nowadays,China is the largest producer of Griseofulvin and the only country that exports Griseofulvin.Griseofulvin is now mainly produced by fermentation.Prior art has the disadvantages of high fermentation cost,low yield,and long cycle time,it cannot be widely used in agriculture..This study intends to increase the griseofulvin yield through response surface optimization,and construct a kinetic equation for griseofulvin fermentation to provide a scientific data for industrial production.The key enzyme gene of griseofulvin synthesis in fermentation was studied.And it purpose was to discuss the synthesis mechanism of griseofulvin.Optimization of fermentation technology for producing griseofulvin from penicillium Penicillium patulum HHB1-31.The single-factor experiment and BOX-Behnken response surface design optimization were used to determine the optimal medium composition for the fermentation of strain HHB 1-31:the proportion of rice flour was 18%,the concentration of inorganic nitrogen source was NaNO3+NH4SO4 and the proportion of each was 0.04%?NaH2PO4 0.1%?FeSO4 0.1%?MgSO4 0.1%?CaCO31.0%?KCl 1.528%,The best culture conditions were:the incubation time of seed solutionwas 48 h inoculation volume was 4%,activation time was 48 h,and the loading volume of triangle bottle was 20 ml/250 ml.The yield of griseofulvin could be up to 11811 g/mLUsing two methods to establish a fermentation model of patulin.The first method based on the classical theory of fermentation dynamics used the Logisit model and the Luedeking-Piret equation to establish a bacterial Kinetic model of griseofulvin fermentation,a product generation dynamic model,and a matrix consumption dynamic model in the fermentation process.The second method used Origin 8.6 software to perform nonlinear fitting using screened multiple equations,and compared several different models.Therefore,The best model was selected to establish a bacterial cell dynamic model,a product generation dynamic model,and a matrix consumption dynamic model.(1)Based on the classic fermentation kinetics,the fermentation kinetics model of griseofulvin was established:abacterial cell dynamic model:X=0.174×e0.73t/1.478+0.110 e0.73t R2=0.994 a product generation dynamic model:P=-270.13×e0.73t/1.478+0.110e0.73t+1753.36ln(48+0.110e0.73t/1.587))R2=0.982 a matrix consumption dynamic model:S=150.010-0.017e0.73y/1.470+0.110e0.73t-24.174/1.480+0.110e0.73t-156.900ln(1.480+0.110e0.73t/1.587)+181.7ln(1.480+0.110e0.73t/1.578)R2=0.933?(2)Based on origin8.6 to screen the optimal mathematical model cell dynamic model:y=1.605-1.775/1+e(x-3.205/1.613 R2=0.994 a product generation dynamic model:y=13948.285-1.4837.289/1+e(x-6.800)/2.147 R2=0.990 a matrix consumption dynamic model:y=179/1+e(x-1.357)/1.277+16 R2=0.996 According to the LC-MS test results,from the fourth day to the eight day of fermentation,the yield of griseofulvin and chlorhexidomycin both showed an increasing trend,but the increment of griseofulvin was higher than chlorhexidomycin.Fluorescence quantitative PCR was used to study the expression of key genes of penicillium HHB1-31 in griseofulvin fermentation.It was showed that expression level of gsfA and gsfI with concentrations of 0.8%NaCl and 0.7%KCl were significantly higher than those without addition of chloride ions.However,excessive addition of chloride ions(the concentration of chloride ion was 1.6%NaCl and 1.4%KCI)cloud affect he expression level.Therefore,chloride ion control is very important in fermentation.The research showed that the addition of Al3+,Cu2+,Zn2+,Mn2+,Cl-had effect on the expression of key genes gsfA and gsfI during fermentation.
Keywords/Search Tags:Penicillium patulu, griseofulvin, fermentation optimization, fermentation dynamics, qPCR
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