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. 2017 Mar 6;12(3):e0173375.
doi: 10.1371/journal.pone.0173375. eCollection 2017.

Effects of diluents on cell culture viability measured by automated cell counter

Affiliations

Effects of diluents on cell culture viability measured by automated cell counter

Aaron Chen et al. PLoS One. .

Abstract

Commercially available automated cell counters based on trypan blue dye-exclusion are widely used in industrial cell culture process development and manufacturing to increase throughput and eliminate inherent variability in subjective interpretation associated with manual hemocytometers. When using these cell counters, sample dilution is often necessary to stay within the assay measurement range; however, the effect of time and diluents on cell culture is not well understood. This report presents the adverse effect of phosphate buffered saline as a diluent on cell viability when used in combination with an automated cell counter. The reduced cell viability was attributed to shear stress introduced by the automated cell counter. Furthermore, length of time samples were incubated in phosphate buffered saline also contributed to the observed drop in cell viability. Finally, as erroneous viability measurements can severely impact process decisions and product quality, this report identifies several alternative diluents that can maintain cell culture viability over time in order to ensure accurate representation of cell culture conditions.

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Conflict of interest statement

Competing Interests: The authors are employed by Seattle Genetics, Inc. This affiliation does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1
(A) Viability traces over time between the MBR (dashed lines) and 3 L bioreactor (solid lines) systems. Traces represent the means of replicates (n = 3 per experiment), and error bars represent standard deviations. (B) Daily standard deviations (STDEV, n = 11). Bars and the numbers above graphs represent the means of daily standard deviations, and comparison circles represent the results using Tukey-Kramer honest significant difference (Tukey) test. Raw data included in S1 Dataset.
Fig 2
Fig 2. Investigation of lower viability.
(A) Sample handling (manual, n = 17 and robot, n = 12). (B) Antifoam addition (no, n = 19 and yes, n = 18). (C) Diluent (Neat, n = 17 and PBS, n = 19). D) Additive effect of diluent and antifoam (neat, n = 12 and PBS, n = 18). Raw data included in S1 Dataset.
Fig 3
Fig 3
Effect of PBS is independent of A) cell line, B) operator and C) cell counter. p < 0.05 for all conditions. Raw data included in S1 Dataset.
Fig 4
Fig 4. Alternative diluents.
A) Data collected from automated cell counters. Neat (n = 114), fresh medium (n = 258) and PBS+Shear Protectant (n = 126) are not statistically different comparatively, but, are statistically different than both PBS (n = 229) and PBS+Buffer (n = 32). B) Data collected from manual cell counts (hemocytometer). All diluents are not statistically different (n = 7 for neat, fresh medium and PBS, and n = 10 for PBS+Shear Protectant). C) Viability difference between mixing cycles using PBS as the diluent (n = 18). D) Difference in LDH before (control) and after cell counting procedures (flow through) between PBS (n = 28) and PBS+Shear Protectant (n = 14). Raw data included in S1 Dataset.
Fig 5
Fig 5
Bivariate plots of viability differences vs. (A) incubation time and (B) TCC. (C) Increasing TCC by adjusting image captures (50 images, n = 25; 100 images, n = 21). Raw data included in S1 Dataset.

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