In situ microscopy for on-line determination of biomass.

A sensor is presented, which allows on-line microscopic observation of microorganisms during fermentations in bioreactors. This sensor, an In Situ Microscope (ISM) consists of a direct-light microscope with a measuring chamber, integrated in a 25 mm stainless steel tube, two CCD-cameras, and two frame-grabbers. The data obtained are processed by an automatic image analysis system. The ISM is connected with the bioreactor via a standard port, and it is immersed directly in the culture liquid-in our case Saccharomyces cerevisiae in a synthetic medium. The microscopic examination of the liquid is performed in the measuring chamber, which is situated near the front end of the sensor head. The measuring chamber is opened and closed periodically. In the open state, the liquid in the bioreactor flows unrestricted through the chamber. In closing, a defined volume of 2,2. 10(-8) mL of the liquid becomes enclosed. After a few seconds, when the movement of the cells in the enclosed culture has stopped, they are examined with the microscope. The microscopic images of the cells are registered with the CCD-cameras and are visualized on a monitor, allowing a direct view of the cell population. After detection, the measuring chamber reopens, and the enclosed liquid is released. The images obtained are evaluated as to cell concentration, cell size, cell volume, biomass, and other relevant parameters simultaneously by automatic image analysis. With a PC (486/33 MHz), image processing takes about 15 s per image. The detection range tested when measuring cells of S. cerevisiae is about 10(6) to 10(9) cells/mL (equivalent to a biomass of 0.01 g/L to 12 g/L). The calculated biomass values correlate very well with those obtained using dry weight analysis. Furthermore, histograms can be calculated, which are comparable to those obtained by flow cytometry.

[1]  Herbert Schatzmann,et al.  Anaerobes Wachstum von Saccharomyces cerevisiae , 1975 .

[2]  D B Kell,et al.  The estimation of microbial biomass. , 1985, Biosensors.

[3]  David J. Clarke,et al.  Monitoring reactor biomass , 1986 .

[4]  P. K. Bjørnsen Automatic Determination of Bacterioplankton Biomass by Image Analysis , 1986, Applied and environmental microbiology.

[5]  K. Schügerl,et al.  Flow cytometric studies during culture of Saccharomyces cerevisiae , 1987 .

[6]  K. K. Frame,et al.  Cell volume measurement as an estimation of mammalian cell biomass , 1990, Biotechnology and bioengineering.

[7]  E Keshavarz-Moore,et al.  Estimation of cell volume and biomass of penicillium chrysogenum using image analysis , 1992, Biotechnology and bioengineering.

[8]  J. A. Valkenburg,et al.  A computer‐aided measuring system for the characterization of yeast populations combining 2D‐image analysis, electronic particle counter, and flow cytometry , 1992, Biotechnology and bioengineering.

[9]  S E Vecht-Lifshitz,et al.  Biotechnological applications of image analysis: present and future prospects. , 1992, Journal of biotechnology.

[10]  J. Dodds,et al.  Morphological characterization of yeast by image analysis , 1993, Biotechnology and bioengineering.

[11]  B. Jähne,et al.  In situ microscopy for on‐line characterization of cell‐populations in bioreactors, including cell‐concentration measurements by depth from focus , 1995, Biotechnology and bioengineering.

[12]  Thomas,et al.  Applications of image analysis in cell technology. , 1996, Current opinion in biotechnology.

[13]  J. Teixeira,et al.  Sizing and counting of saccharomyces cerevisiae floc populations by image analysis, using an automatically calculated threshold. , 2010, Biotechnology and bioengineering.