Ordered materials meet living cells: Engineering alignment and programming force actuation

Highly regulated cellular anisotropy is widely observed in vivo. Yet, reproducing tissue anisotropy in vitro is an open challenge. While considerable literature exists on engineering cell alignment, inferring or mimicking cell reorientation, proliferation, and force generation in a tightly coupled process presents unique challenges from fabrication to characterization and modeling. Advances in miniaturization, synthetic fibrous materials, and bioprinting have enabled oriented cell assembly and force generation, making engineered macroscopic shape transformation a reality. Alternatively, bottom-up strategies build complexity from simple, self-organizing components. Steric interactions among cells confer liquid crystal (LC)-like properties, suggesting that tools from LC processing can be leveraged to engineer cell alignment. These tools are also broadly accessible, as they do not require specialized synthesis or instrumentation typically unavailable in standard biological laboratories. Meanwhile, theoretical frameworks for nematic alignment and topological defects are well established. The active nematic model has proven increasingly effective in explaining collective cell behaviors, and an expanding array of active nematic structures is being identified in biological systems. In this Review, we will outline recent progress on tapping into the active nematic nature of cells to organize supracellular, millimeter-scale structures in both 2D and 3D. We will introduce advances in recreating complex cellular order through substrate guidance and in vitro scaffolding. The experimental progress stimulates bottom-up modeling of collective behaviors, activity-enriched description of nematic alignment and topological defects, and machine learning approaches for predictions and uncertainty quantification. These efforts are increasingly complemented by developments in high-throughput imaging for materials characterization, statistical learning approaches for model construction, and generative models for data inversion. Together, a combination of experimental, computational, and data-driven approaches paves the way for the ultimate realization of in vitro, tissue-like morphogenesis.