Monitoring and control of the physiological state of cell cultures

Abstract

Advances in bioprocess engineering depends ultimately on the level of understanding and control of the physiological state of the cell population. Process efficiency is strongly influenced by changes in the cellular state which should be monitored, interpreted, and, if possible, properly manipulated. In most control systems this function is not explicitly considered, which hampers process development and optimization. Conventional control logic is based on direct mapping of the growth environment into process efficiency, thereby bypassing the cell state as an intermediate control objective. Today, this limitation is well realized, and explicit monitoring and control of cellular physiology are considered to be among the most challenging tasks of modern bioprocess engineering. We present here a generic methodology for the design of systems capable of performing these advanced monitoring and control functions.The term "physiological state" is quantified by a vector composed of several process variables that convey significant information about cellular state. These variables can be selected among different classes, including specific metabolic rates, metabolic rate ratios, degees of limitation, and others. The real-time monitoring of many of these is possible using commercial sensors. The definition and calculation of representative sets of physiological state variables is demonstrated with examples from several fermentor cultures: recombinant Escherichia coli for phenylalanine production, bioluminescent E. coli (harboring lux genes driven by a heat shock protein promoter) for detection of environmental pollutants, plant cell culture of Perilla frutescensfor anthocyanin production, and perfusion cultures of recombinant mammalian cells (NS0 and CHO) for therapeutic protein production.If the physiological state vector is on-line calculated, the fermentation process can be described by its trajectory in a space defined by the vector components. Then, the goal of the control system is to maintain the physiological state of the cell as close as possible to the trajectory, providing maximum efficiency. A control structure meant to perform this function is proposed, along with the mechanism for its design. In contrast to conventional systems which work in a closed loop in respect to the cell environment, this scheme operates in a closed loop in respect to the cell state. The discussed control concept has been successfully applied to the recombinant phenylalanine production, resulting in physiologically consistent operation, total computer control, and high process efficiency. Initial results from the application of the method to perfusion mammalian cell cultures are also presented.

Soft sensor control of metabolic fluxes in a recombinant Escherichia coli fed-batch cultivation producing green fluorescence protein

“…The control strategy used in this study was based on the idea that the accumulation of metabolites from glucose overflow and MAF metabolism in E. coli should be maintained at a It has previously been suggested [30] that fed-batch cultivations should benefit from been controlled in such a way that the metabolic fluxes in the individual cell are constant and low.…”

“…This has been referred to as physiological control [30]. It requires that the cell concentration of the culture is monitored on-line and that the key metabolites involved are monitored simultaneously.…”

Multifrequency permittivity measurements enable on‐line monitoring of changes in intracellular conductivity due to nutrient limitations during batch cultivations of CHO cells

“…This term is defined by several variables that impart significant information about the cellular state. 25 These variables include growth and metabolic rates (including their ratios), degrees of nutrient limitations, cellular morphology (cell size, membrane state), dielectric properties (intracellular conductivity, membrane conductivity), and the distribution of these variables. Although qualitatively intuitively clear, the quantitative description of the physiological state is, due to the complexity of the variables, rather elusive.…”

“…It is therefore difficult to monitor, causing a complex situation when it should be used to control a bioprocess. 25,26 Advances in bioprocess engineering will consequently ultimately depend on the level of understanding and control of the physiological state of a cell population. 25 Concerning the measurement of the physiological state, current sensor technology suffers from critical limitations.…”

“…25,26 Advances in bioprocess engineering will consequently ultimately depend on the level of understanding and control of the physiological state of a cell population. 25 Concerning the measurement of the physiological state, current sensor technology suffers from critical limitations. It is consequently impossible to uncover all aspects of the cellular state at an intracellular level.…”