RESUMEN
Three-dimensional (3D) cell models that mimic the structure and function of native tissues are enabling more detailed study of physiological and pathological mechanisms in vitro. We have previously demonstrated the ability to build and manipulate 3D multicellular microscopic structures using holographic optical tweezers (HOTs). Here, we show the construction of a precisely patterned 3D microenvironment and biochemical gradient model consisting of mouse embryoid bodies (mEBs) and polymer microparticles loaded with retinoic acid (RA), embedded in a hydrogel. We demonstrate discrete, zonal expression of the RA-inducible protein Stra8 within mEBs in response to release of RA from polymer microparticles, corresponding directly to the defined 3D positioning of the microparticles using HOTs. These results demonstrate the ability of this technology to create chemical microgradients at definable length scales and to elicit, with fidelity and precision, specific biological responses. This technique can be used in the study of in vitro microenvironments to enable new insights on 3D cell models, their cellular assembly, and the delivery of drug or biochemical molecules for engineering and interrogation of functional and morphogenic responses. Graphical abstract.
RESUMEN
BACKGROUND: To investigate how patterns of cell differentiation are related to underlying intra- and inter-cellular signalling pathways, we use a stochastic individual-based model to simulate pattern formation when stem cells and their progeny are cultured as a monolayer. We assume that the fate of an individual cell is regulated by the signals it receives from neighbouring cells via either diffusive or juxtacrine signalling. We analyse simulated patterns using two different spatial statistical measures that are suited to planar multicellular systems: pair correlation functions (PCFs) and quadrat histograms (QHs). RESULTS: With a diffusive signalling mechanism, pattern size (revealed by PCFs) is determined by both morphogen decay rate and a sensitivity parameter that determines the degree to which morphogen biases differentiation; high sensitivity and slow decay give rise to large-scale patterns. In contrast, with juxtacrine signalling, high sensitivity produces well-defined patterns over shorter lengthscales. QHs are simpler to compute than PCFs and allow us to distinguish between random differentiation at low sensitivities and patterned states generated at higher sensitivities. CONCLUSIONS: PCFs and QHs together provide an effective means of characterising emergent patterns of differentiation in planar multicellular aggregates.
