Enhancement Of Rapamycin Production In Streptomyces Hygroscopicus Based On Genome-scale Metabolic Network Model

Rapamycin,as a macrocyclic polyketide with immunosuppressive,antifungal,and anti-tumor activity produced by streptomyces hygroscopicus,is receiving considerable popularity for its significant contribution in medical field.especially in the role of organ transplantation.However,the production capacity of the wild strain is very low,which limits its industrialization and industrialization.Hereby,a computational guided engineering approach was proposed in order to improve the capability of rapamycin production.First,we collect annotated genomic and biochemical information of streptomyces hygroscopicus ATCC 29253 from KEGG metabolic pathway database in order to obtain an initial gene-protein-response list.Then,after manually refined and added transport reaction and exchange reaction,a genome-scale metabolic model?GSMM?of streptomyces hygroscopicus ATCC 29253 was constructed.The model consists of1,003 reactions,711 metabolites.Then,the fermentation characteristic curves including growth curve,residual sugar curve and rapamycin synthetic curve were determined.The specific glucose uptake rate and the rapamycin synthesis rate were obtained.With the specific glucose uptake rate and the rapamycin synthesis rate as constraints,with biomass as the objective function,maximum specific growth rate was calculated by flux balance analysis?FBA?algorithm and the result was 0.0535 h^-1.Compared with the experimental result 0.0512 h^-1,error is in the range of 5%which verifies the high credibility of the model.Subsequently,several potential genetic targets that likely guaranteed an improved yield of rapamycin were identified by flux balance analysis?FBA?and minimization of metabolic adjustment?MOMA?algorithm.Furthermore,according to the results of model prediction and sort analysis,gene pfk?encoding6-phosphofructokinase?was selected as knockout target and genes dahP?encoding DAHP synthase?and rapK?encoding chorismatase?were selected as overexpression targets.At last,gene pfk was knocked out and genes dahP and rapK were overexpressed in the parent strain ATCC 29253,respectively.The yield of rapamycin increased by30.8%,36.2%and 44.8%by knockout pfk,overexpression of rapK and dahP respectively,compared with parent strain.The titer of rapamycin reached 250.8mg/l by co-expression the gene dahP and rapK,knockout pfk simultaneously,corresponding to 142.3%increase relative to that for parent strain.The relationship between model prediction and experimental results demonstrates the validity and rationality of this approach for targets identification and rapamycin production improvement.