Premium
Biocalorimetric monitoring of glycoengineered P . pastoris cultivation for the production of recombinant huIFNα2b: A quantitative study based on mixed feeding strategies
Author(s) -
Katla Srikanth,
Pavan Satya Sai,
Mohan Naresh,
Sivaprakasam Senthilkumar
Publication year - 2020
Publication title -
biotechnology progress
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.572
H-Index - 129
eISSN - 1520-6033
pISSN - 8756-7938
DOI - 10.1002/btpr.2971
Subject(s) - pichia pastoris , sorbitol , methanol , chemistry , glycerol , fermentation , pichia , carbon fibers , titer , biomass (ecology) , yield (engineering) , recombinant dna , biochemistry , chromatography , biology , organic chemistry , materials science , composite number , metallurgy , antibody , agronomy , immunology , composite material , gene
Real‐time monitoring of glycoengineered Pichia pastoris by employing process analytical technology (PAT) tools is vital for gaining deeper insights into the therapeutic protein production process. The present study focuses on influence of mixed feed carbon substrates during the induction phases of glycoengineered P . pastoris cultivation, for recombinant human interferon α2b (huIFNα2b) production by employing calorimetric (biological heat rate, q B ) and respirometric (oxygen uptake rate and carbon dioxide evolution rate) measurements. Mixed feed stream of carbon substrates (methanol + glycerol, methanol + sorbitol) at a predetermined “C‐molar ratios” were added during the induction phases. Methanol‐ and sorbitol‐based mixed feeding approach resulted in an improved huIFNα2b titer of 288 mg/L by channeling of methanol predominantly towards an optimal functioning of AOX expression system. A stand‐off between biomass yieldY X Sand biomass heat yieldY Q Xcoefficient, degree of reduction of methanol and its cosubstrate (glycerol and sorbitol) determines the fraction of carbon energy channeled toward biomass and protein production, under strict aerobic conditions. Calorespirometric monitoring and assessment of thermal yields enables a reliable prediction of process variables, leading to futuristic efficient PAT‐based feed rate control.