Real-time monitoring of a fermentation process: linking yeast morphology to insulin production by image analysis

  • Katrin Pontius (Guest lecturer)

Activity: Talks and presentationsConference presentations


Fermentation production processes are often the most complex step within bio-manufacturing. Nevertheless, due to a highly challenging environment inside the bioreactor, industrial fermentation processes are presently rather limited regarding analytical tools for process control. There is a deficit in suitable monitoring devices that can cope with the complexity of the dynamic fermentation environment without compromising the integral success of the process. Therefore, we want to take advantage of the recent advances in microscopy image analysis and evaluate its potential for on-/ at-line monitoring of yeast physiology. In yeast cultures, cell size (distribution) has been shown to be correlated with cell viability (dead/alive1, osmotically stressed2) and growth rate3. Furthermore, the cell size was recently correlated to the accumulation of an internal product (fatty acids) in microalgae4. Consequently, image analysis seems to be a promising tool for getting a snapshot of the physiological state of a yeast culture during a production process. The lately developed oCelloScope instrument5 enables rapid imaging and image analysis of a growing yeast culture. By analyzing images over the cultivation time we investigate the distribution dynamics of single cells, budding cells and cell aggregates, aiming at correlations between morphological features and process performance. Ideally, we want to develop a real-time monitoring tool that may be used in industrial bioprocess setups. Within this approach, methodologies for automatic distinction between image objects (single cells, budding cells, cell aggregates) are developed and first time trends of the morphology dynamics of an insulin production process are discussed. 1. Tibayrenc, P., Preziosi-Belloy, L., Roger, J. M. & Ghommidh, C. Assessing yeast viability from cell size measurements? J. Biotechnol. (2010). doi:10.1016/j.jbiotec.2010.06.019 2. Camisard, V., Brienne, J. P., Baussart, H., Hammann, J. & Suhr, H. Inline characterization of cell concentration and cell volume in agitated bioreactors using in situ microscopy: Application to volume variation induced by osmotic stress. Biotechnol. Bioeng. (2002). doi:10.1002/bit.10178 3. Tyson, C. B., Lord, P. G. & Wheals, A. E. Dependency of Size of Saccharomyces cerevisiae Cells on Growth Rate. J. Bacteriol. 138, 92–98 (1979). 4. Marbà-Ardébol, A.-M., Emmerich, J., Neubauer, P. & Junne, S. Single-cell-based monitoring of fatty acid accumulation in Crypthecodinium cohnii with three-dimensional holographic and in situ microscopy. Process Biochem. 52, 223–232 (2017). 5. Fredborg, M. et al. Real-time optical antimicrobial susceptibility testing. J. Clin. Microbiol. 51, 2047–2053 (2013).
Period1 Nov 2017
Event title12th Recent Advances in Fermentation Technology
Event typeConference
Conference number12
LocationBonita Springs, United States, FloridaShow on map