Expert systems in the control of animal cell culture processes: potentials, functions, and perspectives

Label-free morphology-based prediction of multiple differentiation potentials of human mesenchymal stem cells for early evaluation of intact cells

Precise quantification of cellular potential of stem cells, such as human bone marrow-derived mesenchymal stem cells (hBMSCs), is important for achieving stable and effective outcomes in clinical stem cell therapy. Here, we report a method for image-based prediction of the multiple differentiation potentials of hBMSCs. This method has four major advantages: (1) the cells used for potential prediction are fully intact, and therefore directly usable for clinical applications; (2) predictions of potentials are generated before differentiation cultures are initiated; (3) prediction of multiple potentials can be provided simultaneously for each sample; and (4) predictions of potentials yield quantitative values that correlate strongly with the experimental data. Our results show that the collapse of hBMSC differentiation potentials, triggered by in vitro expansion, can be quantitatively predicted far in advance by predicting multiple potentials, multi-lineage differentiation potentials (osteogenic, adipogenic, and chondrogenic) and population doubling potential using morphological features apparent during the first 4 days of expansion culture. In order to understand how such morphological features can be effective for advance predictions, we measured gene-expression profiles of the same early undifferentiated cells. Both senescence-related genes (p16 and p21) and cytoskeleton-related genes (PTK2, CD146, and CD49) already correlated to the decrease of potentials at this stage. To objectively compare the performance of morphology and gene expression for such early prediction, we tested a range of models using various combinations of features. Such comparison of predictive performances revealed that morphological features performed better overall than gene-expression profiles, balancing the predictive accuracy with the effort required for model construction. This benchmark list of various prediction models not only identifies the best morphological feature conversion method for objective potential prediction, but should also allow clinicians to choose the most practical morphology-based prediction method for their own purposes.

High viable cell concentration fed-batch cultures of hybridoma cells through on-line nutrient feeding

A hybridoma cell line was cultivated in fed-batch cultures using a low-protein, serum-free medium. On-line oxygen uptake rate (OUR) measurement was used to adjust the nutrient feeding rate based on glucose consumption, which was estimated on-line using the stoichiometric relations between glucose and oxygen consumption. Through on-line control of the nutrient feeding rate, not only sufficient were supplied for cell growth and antibody production, but also the concentrations of glucose and other important nutrients such as amino acids were maintained at low levels during the cell growth phase. During the cultivation, cell metabolism changed from high lactate production and low oxygen consumption to low lactate production and high oxygen consumption. As a result the accumulation of lactate was reduced and the growth phase was extended. In comparison with the batch cultures, in which cells reached a concentration of approximately 2 x 10(6) cells/mL, a very high concentration of 1.36 x 10(7) cells/mL with a high cell viability (>90%) was achieved in the fed-batch culture. By considering the consumption of glucose and amino acids, as well as the production of cell mass, metabolites, and antibodies, a well-closed material balance was established. Our results demonstrate the value of coupling on-line OUR measurement and the stoichiometric relations for dynamic nutrient feeding in high cell concentration fed batch cultures.

Instantaneous evaluation of mammalian cell culture growth rates through analysis of the mitotic index

Since a culture increases in cell number when dividing cells separate into two newborn cells, the fraction of mitotic cells in a growing cell population directly reflects the overall growth behavior of a cell culture. To rapidly assess the effects of growth conditions on the fraction of mitotic cells we have employed an antibody specific for the phosphorylated form of histone H3 for the identification of mitotic cells using flow cytometry. The phosphorylation of histone H3 closely correlates with the chromosomal condensation that accompanies the onset of mitosis, and, therefore, it represents a convenient marker for dividing cells. We have optimized the protocol for the staining of mitotic cells for both Chinese hamster ovary and hybridoma cell cultures. Fluorescence micrographs taken of stained cells show that cells in the various stages of mitosis can be detected based on the morphological characteristics of the chromosomes. The variation in the mitotic cell fraction has been determined throughout the batch growth phases of cultures under different growth conditions. The dynamics of the mitotic index show that balanced growth was never truly reached and that the growth rate is in fact quite variable for these cultures since large variations in the mitotic index are observed. In addition, a large increase in the fraction of mitotic cells just prior to the exponential growth phase for all cultures indicates that they are partially synchronized at the exit from the lag phase. According to a two-staged, age structured population balance model, the mitotic index is directly proportional to the growth rate of a culture. The proportionality constant for this case is shown to be the time required for cells to progress through mitosis. This time is believed to be constant for a particular cell line, as shown by experimental data. Thus, growth rates can be determined solely by measurement of the fraction of cells in mitosis. The mitotic index measurements were then used to calculate the growth in cell number of the cultures, and these simulations accurately reflect observed cell counts. Other simulations also show that changes in cell growth can be predicted before they are reflected in the cell count data. This technique can be used as a sensitive indicator of cell growth and could be useful as a process monitoring technique and for developing better feeding strategies for animal cell cultures.

Physiological state-specific models in estimation of recombinant Escherichia coli fermentation performance

Implementation of advanced control strategies in bioprocesses is often hindered by the lack of on-line measurements reflecting the physiological state of the culture. Although a number of techniques have been used to estimate key variables from data monitored on-line, these often do not explicitly take into account changes in physiological state and information on many aspects of physiological state that may not be present in on-line data. Here we demonstrate that data obtained from chemical fingerprinting methods, such as pyrolysis mass spectrometry, can be used to identify changes in the physiological state during cultivation. This information can be utilized for the estimation of the physiological state and can enable physiological state-specific-model development for on-line bioprocess control.

Issues in the development of an industrial bioprocess advisory system

The background and motivation for the construction of a fault detection and advisory system for an industrial fermentation process plant are described. Here, the knowledge extracted from the operators (implemented in the form of production rules) is integrated with multivariate data-based methods for fault detection. The industrial benefits arising from this integrated system include: (1) reduced variability, (2) increased mean performance levels, (3) reduced operator-training time and (4) knowledge management in the broader organization.