The Use of Multidimensional Image-Based Analysis to Accurately Monitor Cell Growth in 3D Bioreactor Culture

Abstract

The transition from traditional culture methods towards bioreactor based bioprocessing to produce cells in commercially viable quantities for cell therapy applications requires the development of robust methods to ensure the quality of the cells produced. Standard methods for measuring cell quality parameters such as viability provide only limited information making process monitoring and optimisation difficult. Here we describe a 3D image-based approach to develop cell distribution maps which can be used to simultaneously measure the number, confluency and morphology of cells attached to microcarriers in a stirred tank bioreactor. The accuracy of the cell distribution measurements is validated using in silico modelling of synthetic image datasets and is shown to have an accuracy >90%. Using the cell distribution mapping process and principal component analysis we show how cell growth can be quantitatively monitored over a 13 day bioreactor culture period and how changes to manufacture processes such as initial cell seeding density can significantly influence cell morphology and the rate at which cells are produced. Taken together, these results demonstrate how image-based analysis can be incorporated in cell quality control processes facilitating the transition towards bioreactor based manufacture for clinical grade cells.

A novel scale‐down cell culture and imaging design for the mechanistic insight of cell colonisation within porous substrate

“…, ; Nuernberger et al. , ), the limited focus depth and resolution of commonly used optical microscopes (Baradez & Marshall, ; Sun et al. , ).…”

“…, ; Lowenthal & Gerecht, ). Monitoring cells infiltrated deep inside 3D scaffolds using conventional optical microscopes is also hardly achievable simply due to their limited focus depth compared with the size of most scaffolds (from mm to cm) (Baradez & Marshall, ; Sun et al. , ).…”

“…First of all, it is almost impossible to distinguish the regulatory functions of each individual architectural and topographic features at nano-, microand macroscales, as well as other biochemical and biomechanical properties because of their coexistence in 3D biomatrices (Lin et al, 2014;Yang et al, 2014;Lowenthal & Gerecht, 2016). Monitoring cells infiltrated deep inside 3D scaffolds using conventional optical microscopes is also hardly achievable simply due to their limited focus depth compared with the size of most scaffolds (from mm to cm) (Baradez & Marshall, 2011;Sun et al, 2011). In addressing these problematic issues, an alternative novel scaled-down study design has been developed in our research group.…”

Enabling stem cell therapies for tissue repair: Current and future challenges

“…For example, fluorescent cell markers have been used to assess neuronal morphology in two versus three dimensional culture conditions, demonstrating important quantitative differences in differentiation (Arien-Zakay et al , 2009). Novel techniques to monitor cell growth and quality have also been developed using multidimensional image analysis (Baradez and Marshall, 2011). As stem cell research moves from the laboratory into the clinics, more efficient and precise systems will be needed for large-scale manufacturing of high-grade therapeutic stem cells.…”

Uncertainty in cell confluency measurements

“…Cell confluency is measured in cell cultures to monitor the cell growth during a treatment and to modulate the subculture in 2D and 3D cell culture [16,17,18,19], to perform toxicity tests with chemical or drug treatment at a certain cell confluency % [20,21], to measure tumor cell proliferation in vitro [22], in drug development to find cytoplasm abnormalities discriminating between areas with cells (occupied by cells) and areas no cells (background) [3]. Cell confluency has been found to affect the expression of cell surface markers in studies on murine stem cells [23], to have effect on the cell stiffness [24], intracellular forces [25] and on the cell cycle [26], to have a critical impact in gene expression in adipose stromal cells [27].…”