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There is increasing consumer demand for alternative animal protein products that are delicious and sustainably produced to address concerns about the impacts of mass-produced meat on human and planetary health. Cultured meat has the potential to provide a source of nutritious dietary protein that both is palatable and has reduced environmental impact. However, strategies to support the production of cultured meats at the scale required for food consumption will be critical. In this review, we discuss the current challenges and opportunities of using edible scaffolds for scaling up the production of cultured meat. We provide an overview of different types of edible scaffolds, scaffold fabrication techniques, and common scaffold materials. Finally, we highlight potential advantages of using edible scaffolds to advance cultured meat production by accelerating cell growth and differentiation, providing structure to build complex 3D tissues, and enhancing the nutritional and sensory properties of cultured meat. 

Epithelial mechanics and mechanobiology have become 2 important research fields in life sciences and bioengineering. These fields investigate how physical factors induced by cell adhesion and collective behaviors can directly regulate biologic processes, such as organ development and disease progression. Cell mechanics and mechanobiology thus make exciting biophysics education topics to illustrate how fundamental physics principles play a role in regulating cell biology. However, the field currently lacks hands-on activities that engage students in learning science and outreach programs in these topics. One such area is the development of robust hands-on modules that allow students to observe features of cell shape and mechanics and connect them to fundamental physics principles. Here, we demonstrate a workflow that engages students in studying epithelial cell mechanics by using commercial histology slides of frog skin. We show that by using recently developed artificial intelligence–based image-segmentation tools, students can easily quantify different cell morphologic features in a high-throughput manner. Using our workflow, students can reproduce 2 essential findings in cell mechanics: the common gamma distribution of normalized cell aspect ratio in jammed epithelia and the constant ratio between the nuclear and cellular area. Importantly, because the only required instrument for this active learning module is a readily available light microscope and a computer, our module is relatively low cost, as well as portable. These features make the module scalable for students at various education levels and outreach programs. This highly accessible education module provides a fun and engaging way to introduce students to the world of epithelial tissue mechanics. 

Abstract The recurrence of cancer following chemotherapy treatment is a major cause of death across solid and hematologic cancers. In B-cell acute lymphoblastic leukemia (B-ALL), relapse after initial chemotherapy treatment leads to poor patient outcomes. Here we test the hypothesis that chemotherapy-treated versus control B-ALL cells can be characterized based on cellular physical phenotypes. To quantify physical phenotypes of chemotherapy-treated leukemia cells, we use cells derived from B-ALL patients that are treated for 7 days with a standard multidrug chemotherapy regimen of vincristine, dexamethasone, and L-asparaginase (VDL). We conduct physical phenotyping of VDL-treated versus control cells by tracking the sequential deformations of single cells as they flow through a series of micron-scale constrictions in a microfluidic device; we call this method Quantitative Cyclical Deformability Cytometry. Using automated image analysis, we extract time-dependent features of deforming cells including cell size and transit time (TT) with single-cell resolution. Our findings show that VDL-treated B-ALL cells have faster TTs and transit velocity than control cells, indicating that VDL-treated cells are more deformable. We then test how effectively physical phenotypes can predict the presence of VDL-treated cells in mixed populations of VDL-treated and control cells using machine learning approaches. We find that TT measurements across a series of sequential constrictions can enhance the classification accuracy of VDL-treated cells in mixed populations using a variety of classifiers. Our findings suggest the predictive power of cell physical phenotyping as a complementary prognostic tool to detect the presence of cells that survive chemotherapy treatment. Ultimately such complementary physical phenotyping approaches could guide treatment strategies and therapeutic interventions. Insight box Cancer cells that survive chemotherapy treatment are major contributors to patient relapse, but the ability to predict recurrence remains a challenge. Here we investigate the physical properties of leukemia cells that survive treatment with chemotherapy drugs by deforming individual cells through a series of micron-scale constrictions in a microfluidic channel. Our findings reveal that leukemia cells that survive chemotherapy treatment are more deformable than control cells. We further show that machine learning algorithms applied to physical phenotyping data can predict the presence of cells that survive chemotherapy treatment in a mixed population. Such an integrated approach using physical phenotyping and machine learning could be valuable to guide patient treatments. 

Abstract Tuning of genome structure and function is accomplished by chromatin-binding proteins, which determine the transcriptome and phenotype of the cell. Here we investigate how communication between extracellular stress and chromatin structure may regulate cellular mechanical behaviors. We demonstrate that histone H1.0, which compacts nucleosomes into higher-order chromatin fibers, controls genome organization and cellular stress response. We show that histone H1.0 has privileged expression in fibroblasts across tissue types and that its expression is necessary and sufficient to induce myofibroblast activation. Depletion of histone H1.0 prevents cytokine-induced fibroblast contraction, proliferation and migration via inhibition of a transcriptome comprising extracellular matrix, cytoskeletal and contractile genes, through a process that involves locus-specific H3K27 acetylation. Transient depletion of histone H1.0 in vivo prevents fibrosis in cardiac muscle. These findings identify an unexpected role of linker histones to orchestrate cellular mechanical behaviors, directly coupling force generation, nuclear organization and gene transcription. 

Cellular traction forces that are dependent on actin-myosin activity are necessary for numerous developmental and physiological processes. As traction force emerges as a promising cancer biomarker there is a growing need to understand force generation in response to chemical and mechanical cues. Our goal is to present a unified modeling framework that integrates actin-myosin activity, substrate stiffness, integrin bond type, and adhesion complex dynamics to explain how force develops under specific conditions. Our simulation results show that substrate stiffness and number of myosin motors contribute to the maximum actin-myosin forces that can be generated but do not solely control the force transmitted by the cells to the surface, i.e., the traction force. The kinetics of the bonds between the cell and the substrate plays an equally important role. Overall, we find that while the cell can generate large actin-myosin forces in individual stress fibers ( > 300 pN), the maximum force transmitted to the surface per cell-substrate attachment only reaches a fraction of these values (approx. 50 pN). Traction stress, the sum of forces transferred by all cell-substrate attachments in a unit area, is biphasic or sigmoidal with increasing substrate stiffness depending on the number of active myosin motors generating forces. Finally, we conclude that adhesions < 1  μm 2 generate widely variable traction forces and that impulse, the magnitude and duration of a force generating event, is a key limiting factor in traction stress.