کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6491444 | 43411 | 2014 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
In situ near infrared spectroscopy monitoring of cyprosin production by recombinant Saccharomyces cerevisiae strains
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بیو مهندسی (مهندسی زیستی)
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: In situ near infrared spectroscopy monitoring of cyprosin production by recombinant Saccharomyces cerevisiae strains In situ near infrared spectroscopy monitoring of cyprosin production by recombinant Saccharomyces cerevisiae strains](/preview/png/6491444.png)
چکیده انگلیسی
Near infrared (NIR) spectroscopy was used to in situ monitoring the cultivation of two recombinant Saccharomyces cerevisiae strains producing heterologous cyprosin B. NIR spectroscopy is a fast and non-destructive technique, that by being based on overtones and combinations of molecular vibrations requires chemometrics tools, such as partial least squares (PLS) regression models, to extract quantitative information concerning the variables of interest from the spectral data. In the present work, good PLS calibration models based on specific regions of the NIR spectral data were built for estimating the critical variables of the cyprosin production process: biomass concentration, cyprosin activity, cyprosin specific activity, the carbon sources glucose and galactose concentration and the by-products acetic acid and ethanol concentration. The PLS models developed are valid for both recombinant S. cerevisiae strains, presenting distinct cyprosin production capacities, and therefore can be used, not only for the real-time control of both processes, but also in optimization protocols. The PLS model for biomass yielded a R2 = 0.98 and a RMSEP = 0.46 g dcw lâ1, representing an error of 4% for a calibration range between 0.44 and 13.75 g dcw lâ1. A R2 = 0.94 and a RMSEP = 167 U mlâ1 were obtained for the cyprosin activity, corresponding to an error of 6.7% of the experimental data range (0-2509 U mlâ1), whereas a R2 = 0.93 and RMSEP = 672 U mgâ1 were obtained for the cyprosin specific activity, corresponding to an error of 7% of the experimental data range (0-11,690 U mgâ1). For the carbon sources glucose and galactose, a R2 = 0.96 and a RMSECV of 1.26 and 0.55 g lâ1, respectively, were obtained, showing high predictive capabilities within the range of 0-20 g lâ1. For the metabolites resulting from the cell growth, the PLS model for acetate was characterized by a R2 = 0.92 and a RMSEP = 0.06 g lâ1, which corresponds to a 6.1% error within the range of 0.41-1.23 g lâ1; for the ethanol, a high accuracy PLS model with a R2 = 0.97 and a RMSEP = 1.08 g lâ1 was obtained, representing an error of 9% within the range of 0.18-21.76 g lâ1. The present study shows that it is possible the in situ monitoring and prediction of the critical variables of the recombinant cyprosin B production process by NIR spectroscopy, which can be applied in process control in real-time and in optimization protocols. From the above, NIR spectroscopy appears as a valuable analytical tool for online monitoring of cultivation processes, in a fast, accurate and reproducible operation mode.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Biotechnology - Volume 188, 20 October 2014, Pages 148-157
Journal: Journal of Biotechnology - Volume 188, 20 October 2014, Pages 148-157
نویسندگان
Pedro N. Sampaio, Kevin C. Sales, Filipa O. Rosa, Marta B. Lopes, CecÃlia R. Calado,