Extracellular expression of Saccharomyces cerevisiae 's L-asparaginase II in Pichia pastoris results in novel enzyme with better parameters.
Henrique P BiasotoCristina B HebedaSandra H P FarskyAdalberto PessoaTales A Costa-SilvaGisele MonteiroPublished in: Preparative biochemistry & biotechnology (2022)
L-asparaginase (ASNase) is an efficient inhibitor of tumor development, used in chemotherapy sessions against acute lymphoblastic leukemia (ALL) tumor cells; its use results in 80% complete remission of the disease in treated patients. Saccharomyces cerevisiae 's L-asparaginase II (ScASNaseII) has a high potential to substitute bacteria ASNase in patients that developed hypersensitivity, but the endogenous production of it results in hypermannosylated immunogenic enzyme. Here we describe the genetic process to acquire the ScASNaseII expressed in the extracellular medium. Our strategy involved a fusion of mature sequence of protein codified by ASP3 (amino acids 26-362) with the secretion signal sequence of Pichia pastoris acid phosphatase enzyme; in addition, this DNA construction was integrated in P. pastoris Glycoswitch ® strain genome, which has the cellular machinery to express and secrete high quantity of enzymes with humanized glycosylation. Our data show that the DNA construction and strain employed can express extracellular asparaginase with specific activity of 218.2 IU mg -1 . The resultant enzyme is 40% more stable than commercially available Escherichia coli's ASNase (EcASNaseII) when incubated with human serum. In addition, ScASNaseII presents 50% lower cross-reaction with anti-ASNase antibody produced against EcASNaseII when compared with ASNase from Dickeya chrysanthemi .
Keyphrases
- saccharomyces cerevisiae
- end stage renal disease
- acute lymphoblastic leukemia
- newly diagnosed
- ejection fraction
- amino acid
- chronic kidney disease
- prognostic factors
- recombinant human
- peritoneal dialysis
- squamous cell carcinoma
- genome wide
- circulating tumor
- poor prognosis
- rheumatoid arthritis
- single molecule
- systemic lupus erythematosus
- binding protein
- big data
- disease activity
- protein protein
- deep learning
- nucleic acid