High‐throughput analysis of the plasmid bioproduction process in Escherichia coli by FTIR spectroscopy

• Autor(a) principal: Scholz, Teresa
• Data de Publicação: 2012
• Outros Autores: Lopes, Vítor V., Calado, Cecília
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.21/12240
• topic: FTIR spectroscopy; Bioprocess development; PLS regression; Escherichia coli; Plasmid production

Monitoring plasmid production systems is a lab intensive task. This article proposes a methodology based on FTIR spectroscopy and the use of chemometrics for the high‐throughput analysis of the plasmid bioproduction process in E. coli. For this study, five batch cultures with different initial medium compositions are designed to represent different biomass and plasmid production behavior, with the maximum plasmid and biomass concentrations varying from 11 to 95 mg L−1 and 6.8 to 12.8 g L−1, respectively, and the plasmid production per biomass varying from 0.4 to 5.1 mg g−1. After a short sample processing consisting of centrifugation and dehydration, the FTIR spectra are recorded from the collected cellular biomass using microtiter plates with 96 wells. After spectral pre‐processing, the predictive FTIR spectra models are derived by using partial least squares (PLS) regression with the wavenumber selection performed by a Monte‐Carlo strategy. Results show that it is possible to improve the PLS models by selecting specific spectral ranges. For the plasmid model, the spectral regions between 590–1,130, 1,670–2,025, and 2,565–3,280 cm−1 are found to be highly relevant. Whereas for the biomass, the best wavenumber selections are between 900–1,200, 1,500–1,800, and 2,850–3,200 cm−1. The optimized PLS models show a high coefficient of determination of 0.91 and 0.89 for the plasmid and biomass concentration, respectively. Additional PLS models for the prediction of the carbon sources glucose and glycerol and the by‐product acetic acid, based on metabolism‐induced correlations between the nutrients and the cellular biomass are also established.