Motility-limited aggregation of mammary epithelial cells into fractal-like clusters.

Migratory cells transition between dispersed individuals and multicellular collectives during development, wound healing, and cancer. These transitions are associated with coordinated behaviors as well as arrested motility at high cell densities, but remain poorly understood at lower cell densities. Here, we show that dispersed mammary epithelial cells organize into arrested, fractal-like clusters at low density in reduced epidermal growth factor (EGF). These clusters exhibit a branched architecture with a fractal dimension of [Formula: see text], reminiscent of diffusion-limited aggregation of nonliving colloidal particles. First, cells display diminished motility in reduced EGF, which permits irreversible adhesion upon cell-cell contact. Subsequently, leader cells emerge that guide collectively migrating strands and connect clusters into space-filling networks. Thus, this living system exhibits gelation-like arrest at low cell densities, analogous to the glass-like arrest of epithelial monolayers at high cell densities. We quantitatively capture these behaviors with a jamming-like phase diagram based on local cell density and EGF. These individual to collective transitions represent an intriguing link between living and nonliving systems, with potential relevance for epithelial morphogenesis into branched architectures.

Stereolithographic printing of ionically-crosslinked alginate hydrogels for degradable biomaterials and microfluidics.

3D printed biomaterials with spatial and temporal functionality could enable interfacial manipulation of fluid flows and motile cells. However, such dynamic biomaterials are challenging to implement since they must be responsive to multiple, biocompatible stimuli. Here, we show stereolithographic printing of hydrogels using noncovalent (ionic) crosslinking, which enables reversible patterning with controlled degradation. We demonstrate this approach using sodium alginate, photoacid generators and various combinations of divalent cation salts, which can be used to tune the hydrogel degradation kinetics, pattern fidelity, and mechanical properties. This approach is first utilized to template perfusable microfluidic channels within a second encapsulating hydrogel for T-junction and gradient devices. The presence and degradation of printed alginate microstructures were further verified to have minimal toxicity on epithelial cells. Degradable alginate barriers were used to direct collective cell migration from different initial geometries, revealing differences in front speed and leader cell formation. Overall, this demonstration of light-based 3D printing using non-covalent crosslinking may enable adaptive and stimuli-responsive biomaterials, which could be utilized for bio-inspired sensing, actuation, drug delivery, and tissue engineering.

Morphological single cell profiling of the epithelial-mesenchymal transition.

Single cells respond heterogeneously to biochemical treatments, which can complicate the analysis of in vitro and in vivo experiments. In particular, stressful perturbations may induce the epithelial-mesenchymal transition (EMT), a transformation through which compact, sensitive cells adopt an elongated, resistant phenotype. However, classical biochemical measurements based on population averages over large numbers cannot resolve single cell heterogeneity and plasticity. Here, we use high content imaging of single cell morphology to classify distinct phenotypic subpopulations after EMT. We first characterize a well-defined EMT induction through the master regulator Snail in mammary epithelial cells over 72 h. We find that EMT is associated with increased vimentin area as well as elongation of the nucleus and cytoplasm. These morphological features were integrated into a Gaussian mixture model that classified epithelial and mesenchymal phenotypes with >92% accuracy. We then applied this analysis to heterogeneous populations generated from less controlled EMT-inducing stimuli, including growth factors (TGF-ß1), cell density, and chemotherapeutics (Taxol). Our quantitative, single cell approach has the potential to screen large heterogeneous cell populations for many types of phenotypic variability, and may thus provide a predictive assay for the preclinical assessment of targeted therapeutics.