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Casein whey permeate (CWP), a lactose-enriched dairy waste effluent, is a viable feed stock for the production of value-added products. Two lactic acid bacteria were cultivated in a synthetic casein whey permeate medium with or without pH control. Lactobacillus lactis ATCC 4797 produced D-lactic acid (DLA) at 12.5 g l(-1) in a bioreactor. The values of Leudking-Piret model parameters suggested that lactate was a growth-associated product. Batch fermentation was also performed employing CWP (35 g lactose l(-1)) with casein hydrolysate as a nitrogen supplement in a bioreactor. After 40 h, L. lactis produced 24.3 g lactic acid l(-1) with an optical purity >98 %. Thus CWP may be regarded as a potential feed-stock for DLA production.

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BACKGROUND Process variability in bioprocess systems involving genetically engineered strains is a common bottleneck and a real‐time insight of the on‐going process is crucial to achieve the desired product and its quality. In this study, a process analytical technology (PAT) platform was developed for the monitoring and control of specific growth rate during methanol induction phase (μmet) of glycoengineered Pichia pastoris fermentation for human interferon alpha 2b (huIFNα2b) production. RESULTS The PAT guided approach involves real‐time monitoring of capacitance (ΔC) facilitating online estimation of specific growth rate (μest), which serves as a process input during controller application. Fed‐batch experiments using pulsed‐feeding of methanol at different dosage (20 g and 30 g) did not significantly influence μmet. Exponential methanol feeding was achieved using a modified proportional, integral and derivative (PID) controller for different predefined specific growth rate set point (μsp) values, namely 0.015, 0.03, 0.04 and 0.06 h−1. Exponential feeding strategy during the induction phase resulted in two crucial outcomes: (i) controlled methanol feeding rate (regulated by the developed PID controller) balanced the methanol consumption rate (qs, met) of the P. pastoris; (ii) significant improvement in huIFNα2b titer (1483 mg L−1) and specific productivity(>0.4 mg g−1. h) was achieved by the robust control of μmet at optimal (0.04 h−1) value. The purified huIFNα2b was found to exhibit antiproliferative effect against human breast cancer cell lines. CONCLUSIONS Efficient control of μmet at a very low narrow range was achieved with a long‐term controller stability (>10 h) and the highest titer reported to date for huIFNα2b (at optimal μmet) in the yeast expression platform. © 2019 Society of Chemical Industry

Aims The present study was aimed at design of experiments (DoE)‐ and artificial intelligence‐based culture medium optimization for high level extracellular production of a novel recombinant human interferon alpha 2b (huIFNα2b) in glycoengineered Pichia pastoris and its characterization. Methods and Results The artificial neural network—genetic algorithm model exhibited improved huIFNα2b production and better predictability compared to response surface methodology. The optimized medium exhibited a fivefold increase in huIFNα2b titre compared to the complex medium. A maximum titre of huIFNα2b (436 mg l−1) was achieved using the optimized medium in the bioreactor. Real‐time capacitance data from dielectric spectroscopy were utilized to model the growth kinetics with unstructured models. Biological characterization by antiproliferative assay proved that the purified recombinant huIFNα2b was biologically active, exhibiting growth inhibition on breast cancer cell line. Conclusions Culture medium optimization resulted in enhanced production of huIFNα2b in glycoengineered P. pastoris at both shake flask and bioreactor level. The purified huIFNα2b was found to be N‐glycosylated and biologically active. Significance and Impact of the Study DoE‐based medium optimization strategy significantly improved huIFNα2b production. The antiproliferative activity of huIFNα2b substantiates its potential scope for application in cancer therapy.