Abstract

The use of organ-on-a-chip technologies is gaining importance, particularly in neuroscience, as they can replicate features of the complex neural networks seen in vivo [1]. This comes with a requirement to accurately position spheroids and microtissues, as well as single cells, within experimental microstructures in order to create well-defined, heterogeneous systems resembling physiological conditions. Fluidic force microscopy (FluidFM) comprises an atomic force microscopy (AFM) cantilever, containing a hollow microfluidic channel [2]. Thus, the system merges the force-sensing abilities of AFM with the aspiration and dispensing abilities of a micropipette and can be used for the pick and place of objects of interest. Because of its gentleness, accuracy and optical access, FluidFM is ideal for the precise pick and place of single cells [3], in particular, neurons, to build functioning neuronal networks. The FluidFM OMNIUM can be used to build neuronal networks using one of two methods; picking and placing single neurons on flat, patterned surfaces, or picking and placing neuronal spheroids in polydimethylsiloxane microstructures. Both single cells and spheroids can also be placed on microelectrode arrays. The required number of neuronal spheroids or single cells are selected manually from a cell-repellent substrate. The cantilever is lowered until contact is made with the selected spheroid or cell, detected using its AFM capabilities. A negative pressure is applied in the cantilever, and the object of interest is aspirated onto the cantilever’s aperture. The spheroid or cell is then transferred to the location of interest, before depositing it there. Process flows have now been defined for picking both spheroids and cells using the FluidFM OMNIUM and placing on a variety of surface structures. FluidFM is useful in a variety of applications such as lab- or organ-on-a-chip technologies where the precise placing of cells and spheroids is required for experimental accuracy, with no adverse effects on the cells. It is also useful where the viability of such cells is required for experimental applications. Current projects are developing a system for automated pick and place of single cells, leveraging imaging recognition and automation. This will also allow for better prediction of viable cells in induced pluripotent stem cell populations where cell viability has already been compromised by the process of freezing and thawing.

References

[1] E. Vuille-dit-Bille et al., (2022) Lab Chip, 22:4043-66.

[2] A. Meister et al., (2009) Nano Lett. 9(6):2501-07.

[3] V. Martinez et al., (2016) Lab Chip 16:1663-74.