Rapid analysis of the expression of heterologous proteins in Escherichia coli using pyrolysis mass spectrometry and Fourier transform infrared spectroscopy with chemometrics: application to alpha 2-interferon production.

Cell pastes and supernatant Escherichia coli samples, taken from an industrial bioprocess overproducing recombinant alpha 2 IFN were analysed using pyrolysis mass spectrometry (PyMS) and diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR). PyMS and FT-IR are physico-chemical methods which measure predominantly the bond strengths of molecules and the vibrations of bonds within functional groups, respectively. They therefore give quantitative information about the total biochemical composition of the bioprocess sample. The interpretation of these hyperspectral data, in terms of the quantity of alpha 2 IFN in the cell pastes and supernatant samples was possible only after the application of the 'supervised learning' methods of artificial neural networks (ANNs) and partial least squares (PLS) regression. Both PyMS and FT-IR are novel, rapid and economical methods for the screening and the quantitative analysis of complex biological bioprocess over producing recombinant proteins. Models established using either spectral data set had a similarly satisfactory predictive ability. This shows that whole-reaction mixture spectral methods, which measure all molecules simultaneously, do contain enough information to allow their quantification when the entire spectra are used as the inputs to methods based on supervised learning. Moreover, this is the first study where FT-IR in the mid-IR range has been used to quantify the expression of a heterologous protein directly from fermentation broths and the first study to compare the abilities of PyMS and FT-IR for the quantitative analyses of an industrial bioprocess.

Structure of a specific peptide complex of the carboxy-terminal SH2 domain from the p85 alpha subunit of phosphatidylinositol 3-kinase.

We have determined the solution structure of the C-terminal SH2 domain of the p85 alpha subunit of human phosphatidylinositol (PI) 3-kinase (EC 2.7.1.137) in complex with a phosphorylated tyrosine pentapeptide sequence from the platelet-derived growth factor receptor using heteronuclear nuclear magnetic resonance spectroscopy. Overall, the structure is similar to other SH2 domain complexes, but displays different detail interactions within the phosphotyrosine binding site and in the recognition site for the +3 methionine residue of the peptide, the side chain of which inserts into a particularly deep and narrow pocket which is displaced relative to that of other SH2 domains. The contacts made within this +3 pocket provide the structural basis for the strong selection for methionine at this position which characterizes the SH2 domains of PI3-kinase. Comparison with spectral and structural features of the uncomplexed domain shows that the long BG loop becomes less mobile in the presence of the bound peptide. In contrast, extreme resonance broadening encountered for most residues in the beta D', beta E and beta F strands and associated connecting loops of the domain in the absence of peptide persists in the complex, implying conformational averaging in this part of the molecule on a microsecond-to-millisecond time scale.

Artificial neural network based experimental design procedure for enhancing fermentation development.

Conventional experimental design techniques are available to assist in the optimization of fermentation processes, but due to the nonlinearities in the bioprocess, they are limited in their effectiveness. This problem is further complicated with recombinant systems as a result of the additional complexities of the process. This article describes a general strategy using artificial neural networks as an alternative approach to fermentation process development laboratory are presented for the neural network based procedures. (c) 1994 John Wiley & Sons, Inc.