Rapid analysis of the expression of heterologous proteins in Escherichia coli using pyrolysis mass spectrometry and Fourier transform infrared spectroscopy with chemometrics:: application to α2-interferon production

被引:32
作者
McGovern, AC
Ernill, R
Kara, BV
Kell, DB
Goodacre, R
机构
[1] Univ Wales, Inst Biol Sci, Aberystwyth SY23 3DD, Dyfed, Wales
[2] Zeneca Pharmaceut, Macclesfield SK10 4TG, Cheshire, England
基金
英国生物技术与生命科学研究理事会; 英国惠康基金;
关键词
PyMS; FT-IR; bioprocess; interferon; heterologous proteins; chemometrics;
D O I
10.1016/S0168-1656(99)00128-5
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
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. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:157 / 167
页数:11
相关论文
共 40 条
[1]   ENHANCEMENT AND COMPRESSION TECHNIQUES FOR HYPERSPECTRAL DATA [J].
ABOUSLEMAN, GP ;
GIFFORD, E ;
HUNT, BR .
OPTICAL ENGINEERING, 1994, 33 (08) :2562-2571
[2]   MULTIVARIATE DETERMINATION OF GLUCOSE IN WHOLE-BLOOD USING PARTIAL LEAST-SQUARES AND ARTIFICIAL NEURAL NETWORKS BASED ON MIDINFRARED SPECTROSCOPY [J].
BHANDARE, P ;
MENDELSON, Y ;
PEURA, RA ;
JANATSCH, G ;
KRUSEJARRES, JD ;
MARBACH, R ;
HEISE, HM .
APPLIED SPECTROSCOPY, 1993, 47 (08) :1214-1221
[3]  
Bishop C. M., 1995, NEURAL NETWORKS PATT
[4]  
Brown SD, 1996, ANAL CHEM, V68, pR21, DOI 10.1021/a1960005x
[5]  
CAUSTON DR, 1987, BIOL ADV MATH
[6]   EMPIRICISM STRIKES BACK - NEURAL NETWORKS IN BIOTECHNOLOGY [J].
COLLINS, M .
BIO-TECHNOLOGY, 1993, 11 (02) :163-166
[7]  
Everitt B., 1993, CLUSTER ANAL
[8]   IMAGING SPECTROMETRY FOR EARTH REMOTE-SENSING [J].
GOETZ, AFH ;
VANE, G ;
SOLOMON, JE ;
ROCK, BN .
SCIENCE, 1985, 228 (4704) :1147-1153
[9]   RAPID SCREENING FOR METABOLITE OVERPRODUCTION IN FERMENTOR BROTHS, USING PYROLYSIS MASS-SPECTROMETRY WITH MULTIVARIATE CALIBRATION AND ARTIFICIAL NEURAL NETWORKS [J].
GOODACRE, R ;
TREW, S ;
WRIGLEYJONES, C ;
NEAL, MJ ;
MADDOCK, J ;
OTTLEY, TW ;
PORTER, N ;
KELL, DB .
BIOTECHNOLOGY AND BIOENGINEERING, 1994, 44 (10) :1205-1216
[10]   Pyrolysis mass spectrometry and its applications in biotechnology [J].
Goodacre, R ;
Kell, DB .
CURRENT OPINION IN BIOTECHNOLOGY, 1996, 7 (01) :20-28