We discovered that the assembly dynamics of bone and cartilage progenitor cells follow the same physical laws as the compaction of a shaken granular material. In control conditions, the self-assembly is consistent with the dewetting of a thin liquid film, with exponential relaxation dynamics. By weakening the force generation of the cell using Rho kinase inhibitor, we were able to steer the material from exhibiting liquid-to glass-like behavior.

Studies on monolayer cultures and whole-animal models for the prediction of the response of native human tissue are associated with limitations. Therefore, more and more laboratories are tending towards multicellular spheroids grown in vitro as a model of native tissues. In addition, they are increasingly used in a wide range of biofabrication methodologies. These 3D microspheroids are generated through a self-assembly process that is still poorly characterised, called cellular aggregation. Here, a system is proposed for the automated, non-invasive and high throughput monitoring of the morphological changes during cell aggregation. Microwell patterned inserts were used for spheroid formation while an automated microscope with 4x bright-field objective captured the morphological changes during this process. Subsequently, the acquired time-lapse images were automatically segmented and several morphological features such as minor axis length, major axis length, roundness, area, perimeter and circularity were extracted for each spheroid. The method was quantitatively validated with respect to manual segmentation on four sets of ± 60 spheroids. The average sensitivities and precisions of the proposed segmentation method ranged from 96.67–97.84% and 96.77–97.73%, respectively. In addition, the different morphological features were validated, obtaining average relative errors between 0.78–4.50%. On average, a spheroid was processed 73 times faster than a human operator. As opposed to existing algorithms, our methodology was not only able to automatically monitor compact spheroids but also the aggregation process of individual spheroids, and this in an accurate and high-throughput manner. In total, the aggregation behaviour of more than 700 individual spheroids was monitored over a duration of 16 hours with a time interval of 5 minutes, and this could be increased up to 48,000 for the described culture format. In conclusion, the proposed system has the potential to be used for unravelling the mechanisms involved in spheroid formation and monitoring their formation during large-scale manufacturing protocols.

Spheroids are widely applied as building blocks for biofabrication of living tissues, where they exhibit spontaneous fusion toward an integrated structure upon contact. Tissue fusion is a fundamental biological process, but due to a lack of automated monitoring systems, the in-depth characterization of this process is still limited. Therefore, a quantitative high-throughput platform was developed to semi-automatically select doublet candidates and automatically monitor their fusion kinetics. Spheroids with varying degrees of chondrogenic maturation (days 1, 7, 14, and 21) were produced from two different cell pools, and their fusion kinetics were analyzed via the following steps: (1) by applying a novel spheroid seeding approach, the background noise was decreased due to the removal of cell debris while a sufficient number of doublets were still generated. (2) The doublet candidates were semi-automatically selected, thereby reducing the time and effort spent on manual selection. This was achieved by automatic detection of the microwells and building a random forest classifier, obtaining average accuracies, sensitivities, and precisions ranging from 95.0% to 97.4%, from 51.5% to 92.0%, and from 66.7% to 83.9%, respectively. (3) A software tool was developed to automatically extract morphological features such as the doublet area, roundness, contact length, and intersphere angle. For all data sets, the segmentation procedure obtained average sensitivities and precisions ranging from 96.8% to 98.1% and from 97.7% to 98.8%, respectively. Moreover, the average relative errors for the doublet area and contact length ranged from 1.23% to 2.26% and from 2.30% to 4.66%, respectively, while the average absolute errors for the doublet roundness and intersphere angle ranged from 0.0083 to 0.0135 and from 10.70 to 13.44°, respectively. (4) The data of both cell pools were analyzed, and an exponential model was used to extract kinetic parameters from the time-series data of the doublet roundness. For both cell pools, the technology was able to characterize the fusion rate and quality in an automated manner and allowed us to demonstrate that an increased chondrogenic maturity was linked with a decreased fusion rate. The platform is also applicable to other spheroid types, enabling an increased understanding of tissue fusion. Finally, our approach to study spheroid fusion over time will aid in the design of controlled fabrication of “assembloids” and bottom-up biofabrication of living tissues using spheroids.

Adherent cell cultures are often dissociated from their culture vessel (and each other) through enzymatic harvesting, where the detachment response is monitored by an operator. However, this approach is lacking standardisation and reproducibility, and prolonged exposure or too high concentrations can affect the cell’s viability and differentiation potential. Quantitative monitoring systems are required to characterise the cell detachment response and objectively determine the optimal time-point to inhibit the enzymatic reaction. State-of-the-art methodologies rely on bulky imaging systems and/or features (e.g. circularity) that lack robustness. In this study, lens-free imaging (LFI) technology was used to develop a novel cell detachment feature. Seven different donors were cultured and subsequently harvested with a (diluted) enzymatic harvesting solution after 3, 5 and 7 days of culture. Cell detachment was captured with the LFI set-up over a period of 20 min (every 20 s) and by optimising the reconstruction of the LFI intensity images, a new feature could be identified. Bright regions in the intensity image were identified as detaching cells and using image analysis, a method was developed to automatically extract this feature, defined as the percentage of detached cell regions. Next, the method was quantitatively and qualitatively validated on a diverse set of images. Average absolute error values of 1.49%, 1.34% and 1.97% were obtained for medium to high density and overconfluent cultures, respectively. The detachment response was quantified for all conditions and the optimal time for enzyme inhibition was reached when approximately 92.5% of the cells were detached. On average, inhibition times of 9.6–11.1 and 16.2–17.2 min were obtained for medium to high density and overconfluent cultures, respectively. In general, overconfluent cultures detached much slower, while their detachment rate was also decreased by the diluted harvesting solution. Moreover, several donors exhibited similar trends in cell detachment behaviour, with two clear outliers. Using the novel feature, measurements can be performed with an increased robustness, while the compact LFI design could pave the way for in situ monitoring in a variety of culture vessels, including bioreactors.

We study the self-assembly dynamics of human progenitor cells in agarose micro-wells that are used for production of chondrogenic organoids. Using image analysis on time-lapse microscopy, we estimate the aggregate area in function of time for a large number of aggregates. In control conditions, the aggregate radius follows an exponential relaxation that is consistent with the dewetting dynamics of a liquid film. Introducing Y-27632 Rho kinase inhibitor, the compatibility with the liquid model is lost, and slowed down relaxation dynamics are observed. We demonstrate that these aggregates behave as granular piles undergoing compaction, with a density relaxation that follows a stretched exponential. Using simulations with an individual cell-based model, we construct a phase diagram of cell aggregates that suggests that the aggregate in presence of Rho kinase inhibitor approaches the glass transition.