Evaluation of commercial soy sauce koji strains of Aspergillus oryzae for γ-aminobutyric acid (GABA) production

In this study, four selected commercial strains of Aspergillus oryzae were collected from soy sauce koji. These A. oryzae strains designated as NSK, NSZ, NSJ and NST shared similar morphological characteristics with the reference strain (A. oryzae FRR 1675) which confirmed them as A. oryzae species. They were further evaluated for their ability to produce γ-aminobutyric acid (GABA) by cultivating the spore suspension in a broth medium containing 0.4 % (w/v) of glutamic acid as a substrate for GABA production. The results showed that these strains were capable of producing GABA; however, the concentrations differed significantly (P < 0.05) among themselves. Based on the A. oryzae strains, highest GABA concentration was obtained from NSK (194 mg/L) followed by NSZ (63 mg/L), NSJ (51.53 mg/L) and NST (31.66 mg/L). Therefore, A. oryzae NSK was characterized and the sequence was found to be similar to A. oryzae and A. flavus with 99 % similarity. The evolutionary distance (K nuc) between sequences of identical fungal species was calculated and a phylogenetic tree prepared from the K nuc data showed that the isolate belonged to the A. oryzae species. This finding may allow the development of GABA-rich ingredients using A. oryzae NSK as a starter culture for soy sauce production

Towards better understanding of an industrial cell factory : investigating the feasibility of real-time metabolic flux analysis in Pichia pastoris

Background: Novel analytical tools, which shorten the long and costly development cycles of biopharmaceuticals are essential. Metabolic flux analysis (MFA) shows great promise in improving our understanding of the metabolism of cell factories in bioreactors, but currently only provides information post-process using conventional off-line methods. MFA combined with real time multianalyte process monitoring techniques provides a valuable platform technology allowing real time insights into metabolic responses of cell factories in bioreactors. This could have a major impact in the bioprocessing industry, ultimately improving product consistency, productivity and shortening development cycles. Results: This is the first investigation using Near Infrared Spectroscopy (NIRS) in situ combined with metabolic flux modelling which is both a significant challenge and considerable extension of these techniques. We investigated the feasibility of our approach using the industrial workhorse Pichia pastoris in a simplified model system. A parental P. pastoris strain (i.e. which does not synthesize recombinant protein) was used to allow definition of distinct metabolic states focusing solely upon the prediction of intracellular fluxes in central carbon metabolism. Extracellular fluxes were determined using off-line conventional reference methods and on-line NIR predictions (calculated by multivariate analysis using the partial least squares algorithm, PLS). The results showed that the PLS-NIRS models for biomass and glycerol were accurate: correlation coefficients, R2, above 0.90 and the root mean square error of prediction, RMSEP, of 1.17 and 2.90 g/L, respectively. The analytical quality of the NIR models was demonstrated by direct comparison with the standard error of the laboratory (SEL), which showed that performance of the NIR models was suitable for quantifying biomass and glycerol for calculating extracellular metabolite rates and used as independent inputs for the MFA (RMSEP lower than 1.5 × SEL). Furthermore, the results for the MFA from both datasets passed consistency tests performed for each steady state, showing that the precision of on-line NIRS is equivalent to that obtained by the off-line measurements. Conclusions: The findings of this study show for the first time the potential of NIRS as an input generating for MFA models, contributing to the optimization of cell factory metabolism in real-time

How lean principles can be applied to the development process of educational programs?

This document outlines the scope of the proposal which will investigate the application of Lean production theory to service-based industries such as educational bodies with the view of eliminating waste i.e. eliminating redundant processes, waiting times, rework, etc whilst increasing the efficiency of the new programme development processes (e.g. MSc programmes). Lean is an approach to managing business processes, such as production processes, based on the overall objective of increasing value through waste reduction. Lean principles have been successfully applied within Toyota’s development and production processes since the 1950s. The benefits derived from the application of these principles have been investigated by academia and practitioners. It has been proven from time to time that the application of Lean principles significantly impacts on the quality of the outcome. Due to its successful results, the knowledge gathered is gradually being applied in many different industries and processes, such as construction, healthcare and education. The name LEAN, in this proposal, is an acronym for Lean Educational and Academic Nucleus. It is envisaged that the proposed 'nucleus' will be instrumental in promoting efficiency and improving management of new programme development processes by providing informed guidance on the 'know-how, -why, -when and -who', thus equipping the programme development team with the correct ammunition to seamlessly manage the development processes. Thus, it is envisioned that this novel application of Lean principles to the module development programme and the guidance notes thus developed will benefit both, staff and students alike