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Statistical optimization of single-cell production from Taxus cuspidata plant cell aggregates
Vishal Gaurav1, Susan C Roberts
1Department of Chemical Engineering, University of Massachusetts Amherst, USA.
Abstract:
Flow-cytometric characterization of plant cell culture growth and metabolism at the single-cell level is a method superior to traditional culture average measurements for collecting population information. Investigation of culture heterogeneity and production variability by obtaining information about different culture subpopulations is crucial for optimizing bio-processes for enhanced productivity. Obtaining high yields of intact and viable single cells from aggregated plant cell cultures is an enabling criterion for their analysis and isolation using high-throughput flow cytometric methods. The critical parameters affecting the enzymatic isolation of single cells from aggregated Taxus cuspidata plant cell suspensions were optimized using response-surface methodology and factorial central composite design. Using a design of experiments approach, the output response single-cell yield (SCY, percentage of cell clusters containing only a single cell) was optimized. Optimal conditions were defined for the independent parameters cellulase concentration, pectolyase Y-23 concentration, and centrifugation speed to be 0.045% (w/v), 0.7% (w/v), and 1200 × g, respectively. At these optimal conditions, the model predicted a maximum SCY of 48%. The experimental data exhibited a 72% increase over previously attained values and additionally validated the model predictions. More than 99% of the isolated cells were viable and suitable for rapid analysis through flow cytometry, thus enabling the collection of population information from cells that accurately represent aggregated suspensions. These isolated cells can be further studied to gain insight into both growth and secondary metabolite production, which can be used for bio-process optimization.
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