Developing a scalable model of recombinant protein yield from Pichia pastoris:the influence of culture conditions, biomass and induction regime

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

Altering the ribosomal subunit ratio in yeast maximizes recombinant protein yield

Background The production of high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences that has yet to be addressed in a truly rational manner. Typically eukaryotic protein production experiments have relied on varying expression construct cassettes such as promoters and tags, or culture process parameters such as pH, temperature and aeration to enhance yields. These approaches require repeated rounds of trial-and-error optimization and cannot provide a mechanistic insight into the biology of recombinant protein production. We published an early transcriptome analysis that identified genes implicated in successful membrane protein production experiments in yeast. While there has been a subsequent explosion in such analyses in a range of production organisms, no one has yet exploited the genes identified. The aim of this study was to use the results of our previous comparative transcriptome analysis to engineer improved yeast strains and thereby gain an understanding of the mechanisms involved in high-yielding protein production hosts. Results We show that tuning BMS1 transcript levels in a doxycycline-dependent manner resulted in optimized yields of functional membrane and soluble protein targets. Online flow microcalorimetry demonstrated that there had been a substantial metabolic change to cells cultured under high-yielding conditions, and in particular that high yielding cells were more metabolically efficient. Polysome profiling showed that the key molecular event contributing to this metabolically efficient, high-yielding phenotype is a perturbation of the ratio of 60S to 40S ribosomal subunits from approximately 1:1 to 2:1, and correspondingly of 25S:18S ratios from 2:1 to 3:1. This result is consistent with the role of the gene product of BMS1 in ribosome biogenesis. Conclusion This work demonstrates the power of a rational approach to recombinant protein production by using the results of transcriptome analysis to engineer improved strains, thereby revealing the underlying biological events involved.

A two-factor model of the U.K. yield curve

I model the forward premium in the U.K. gilt-edged market over the period 1982–96 using a two-factor general equilibrium model of the term structure of interest rates. The model permits the decomposition of the forward premium into separate components representing interest rate expectations, the risk premia associated with each of the underlying factors, and terms capturing the direct impact of the variances of the factors on the shape of the forward curve.

Thermochemical characterisation of straws and high yielding perennial grasses

The research is concerned with thermochemical characterisation of straws and high yielding perennial grasses. Crops selected for this study include wheat straw (Triticum aestivum), rape straw (Brassica napus), reed canary grass (Phalaris arundinacea) and switch grass (Panicum virgatum). Thermogravimetric analysis (TGA) was used to examine the distribution of char and volatiles during pyrolysis up to 900 °C. Utilising multi-heating rate thermogravimetric data, the Friedman iso-conversional kinetic method was used to determine pyrolysis kinetic parameters. Light and medium volatile decomposition products were investigated using pyrolysis–gas chromatography–mass spectrometry (Py–GC–MS) up to 520 °C. The 22 highest yielding identifiable cellulose, hemicellulose and lignin biomass markers were semi-quantified taking into consideration peak areas from GC chromatograms. Notable differences can be seen in butanedioic acid, dimethyl ester (hemicelluloses decomposition products), 2-methoxy-4-vinylphenol (lignin marker) and levoglucosan (intermediate pyrolytic decomposition product of cellulose) content when comparing perennial grasses with straw. From results presented in this study, perennial grasses such as switch grass, have the most attractive properties for fast pyrolysis processing. This is because of the observed high volatile yield content of 82.23%, heating value of 19.64 MJ/kg and the relatively low inorganic content.

Characterization of viscoplastic yielding of asphalt concrete

A temperature and strain rate dependent yield surface model was proposed to characterize the viscoplastic yielding of asphalt concrete. Laboratory tests were conducted on specimens that have two binders, two air void contents, and three aging periods. Strain decomposition was performed to obtain viscoplastic strain and stress-pseudostrain curves were constructed to determine the model parameters accurately and efficiently. Results indicate that a stiffer asphalt concrete has greater cohesion and strain hardening amplitude, both of which decline as temperature increases or strain rate decreases. The temperature and strain rate factors of the yield surface can be accurately determined solely by the peak stress of the strength tests. © 2013 Elsevier Ltd. All rights reserved.