RAPID AND QUANTITATIVE-ANALYSIS OF BIOPROCESSES USING PYROLYSIS MASS-SPECTROMETRY AND NEURAL NETWORKS - APPLICATION TO INDOLE PRODUCTION

In pure form indole, when subjected to pyrolysis mass spectrometry (Py MS), gave a pattern of peaks at m/z 117, 90, 89 and a murmur at 63. Si gnificant differences in the magnitudes of these peaks were observed b etween strains of Escherichia coli which were grown on nutrient agar a nd which differed solely in whether a transposon had been inserted int o the tryptophanase gene or elsewhere within the genome. We applied ar tificial neural networks (ANNs) to the deconvolution of pyrolysis mass spectra. The combination of ANNs and PyMS was able quantitatively to detect the component indole when a single strain of E. coli, containin g the tryptophanase gene, was grown on a minimal supplemented salts me dium incorporating various amount of tryptophan, in the range 0-253 mg /l. This approach constitutes a novel, powerful and interesting techno logy for the analysis of the concentrations of appropriate substrates, metabolites and products in chemical and bioprocesses generally.