Application of an Online-Biomass Sensor in an Optical Multisensory Platform Prototype for Growth Monitoring of Biotechnical Relevant Microorganism and Cell Lines in Single-Use Shake Flasks

Abstract

In the context of this work we evaluated a multisensory, noninvasive prototype platform for shake flask cultivations by monitoring three basic parameters (pH, pO2 and biomass). The focus lies on the evaluation of the biomass sensor based on backward light scattering. The application spectrum was expanded to four new organisms in addition to E. coli K12 and S. cerevisiae [1]. It could be shown that the sensor is appropriate for a wide range of standard microorganisms, e.g., L. zeae, K. pastoris, A. niger and CHO-K1. The biomass sensor signal could successfully be correlated and calibrated with well-known measurement methods like OD600, cell dry weight (CDW) and cell concentration. Logarithmic and Bleasdale-Nelder derived functions were adequate for data fitting. Measurements at low cell concentrations proved to be critical in terms of a high signal to noise ratio, but the integration of a custom made light shade in the shake flask improved these measurements significantly. This sensor based measurement method has a high potential to initiate a new generation of online bioprocess monitoring. Metabolic studies will particularly benefit from the multisensory data acquisition. The sensor is already used in labscale experiments for shake flask cultivations.

Parallelised online biomass monitoring in shake flasks enables efficient strain and carbon source dependent growth characterisation of Saccharomyces cerevisiae

“…Especially in the lower and intermediate biomass concentration range, the assumption of a purely linear correlation appears to be too imprecise. Ude et al [ 54 ] as well as Schmidt-Hager et al [ 8 ] proposed several different nonlinear model functions for correlation of backscatter intensities and offline biomass measures, such as polynomial, exponential and Bleasdale-Nelder functions. However, each organism under investigation required a different model type for optimal correlation description.…”

Case study: The characterization and implementation of dielectric spectroscopy (biocapacitance) for process control in a commercial GMP CHO manufacturing process

“…Additionally, Raman spectroscopy has been effectively applied to the monitoring and control of individual process metabolites and for overall batch status monitoring . Techniques for real time biomass measurement include optical methods such as fluorescence and backward light scattering, auto‐sampler technology used in conjunction with an off‐line optical cell counting instrument, and dielectric spectroscopy (biocapacitance) . Currently, the commercial availability and simplicity of dielectric spectroscopy probes make biocapacitance a desirable biomass monitoring solution for high‐density processes.…”

A novel nicotinamide adenine dinucleotide control strategy for increasing the cell density of Haemophilus parasuis

“…Previously, a correlation between capacitance and biomass concentration was clearly established in regard to flocculating yeast . Moreover, online quantification of biomass during lactate production by Bacillus coagulans was monitored using an innovative scattered light sensor, and the results were consistently and reproducibly more accurate than offline measurements of optical density (OD) and dry cell weight (DCW), resulting in a controlled cell growth rate and an increased yield of lactate . As such, real‐time estimation of biomass during the cultivation of H. parasuis could aid in substantially increasing the cell density of the culture.…”