Anan Tongta

Gamma-linolenic acid production of Mucor rouxii by solid-state fermentation using agricultural by-products

Aims:  This study aims to maximize the yield of gamma‐linolenic acid by a filamentous fungus, Mucor rouxii, using low cost production by solid‐state fermentation.

Enhancing the production of gamma-linolenic acid in Hansenula polymorpha by fed-batch fermentation using response surface methodology

Gamma-linolenic acid (GLA, C18:3Δ6,9,12) is an n-6 polyunsaturated fatty acid (PUFA) that has been used for the alleviation and treatment of a number of symptoms and diseases. Increasing GLA demand has led to a search for alternative producers and potential strategies for GLA production. Based on the successful performance of Hansenula polymorpha, a methylotrophic yeast, as a “cell factory” for the production of valuable bioproducts, a bioprocess development approach was implemented for GLA production in the recombinant yeast carrying the mutated Δ6-desaturase gene of Mucor rouxii. Using a substrate-feeding strategy under glycerol-limited conditions, the physical-chemical variables during the fed-batch fermentation of the recombinant H. polymorpha were optimised for GLA production through response surface methodology using a Box-Behnken design. The medium composition, including yeast extract and trace elements, and dissolved oxygen tension (DOT) were targeted. We found that DOT was the most effective variable for enhancing GLA yield. These results also suggest that the optimum conditions for GLA production are 28 % saturation of DOT, 1 g L−1 of yeast extract and 3.6 mL L−1 of the Pichia trace metals 1 (PTM1).

Mathematical Modeling of Biomass and Enzyme Production Kinetics by Aspergillus niger in Solid-State Fermentation at Various Temperatures and Moisture Contents

The effect of temperature and substrate moisture content on the growth and production of amylase, protease and phytase by Aspergillus niger during solid-state fermentation was investigated. A mathematical model regarding the kinetics of growth and enzyme production was performed to calculate the parameters at different temperatures and substrate moisture contents. The growth kinetics of A. niger could be described by the logistic growth model; the mathematical modeling parameters regarding maximum specific growth rate (μmax) and maximum biomass concentration (Xmax) were obtained by fitting the experimental data to the logistic model. The enzyme production kinetics could be described by the Luedeking-Piret model. The mathematical modeling parameters which included the growth-associated formation constant of the product i (αi) and the non-growth-associated formation constant of the product i (βi) were calculated. The production of amylase, protease and phytase was shown to be exclusively growth-associated. The effect of temperature on μmax, Xmax and αi could be described by the cardinal temperature model with inflection (CTMI). Both growth and enzyme formation were clearly influenced by temperature and the optimum culture conditions for growth and enzyme production by A. niger were determined to be approximately 34°C with a substrate moisture content ranging from 40 to 60%.

On-line methanol sensor system development for recombinant human serum albumin production by Pichia pastoris

An on-line methanol sensor system was developed using a methanol probe, methanol sensor unit and peristaltic pump. The system was commanded using data acquisition (DAQ) and LabVIEW software. Calibration of the methanol sensor system was done in a medium environment with yeast cells during cells adaptation to methanol metabolism after glycerol feeding was stopped. The correlation equations between voltage output signal from the methanol sensor unit and residual methanol in culture broth were created with third order polynomial regression. This developed system was implemented for online methanol control in recombinant human serum albumin (rHSA) protein production by P. pastoris KM71 at methanol levels of 4 and 10 g/l with controlled fluctuations at 13.0 and 11.3% of oscillation, respectively. The accumulated amounts of recombinant protein from two levels of methanol concentration controls (4 and 10 g/l) were similar but the proteins were produced at a different rate related with methanol concentration in the broth. Therefore, the control at 10 g/l methanol had a higher production rate (0.53 mg-protein/g dry-cell-h) than 4 g/l methanol control (0.38 mg-protein/g dry-cell-h) as it reached the maximum protein concentration in a shorter time, even though its cell yield was less than that of 4 g/l methanol control. At the end of the experiments, the high cell density environment caused both cell and protein reduction by cell autolysis and protease degradation. However, the protein decrease could be prevented by taking protein induction at a low temperature and a pH where protease does not function. Key words : Methanol monitoring, methanol sensor, on-line methanol, Pichia pastoris, recombinant human serum albumin.