No abstract

The COVID-19 pandemic continues to present enormous challenges for colleges and universities and strategies for save reopening remain a topic of ongoing debate. Many institutions that reopened cautiously in the fall experienced a massive wave of infections and colleges were soon declared as the new hotspots of the pandemic. However, the precise effects of college outbreaks on their immediate neighborhood remain largely unknown. Here we show that the first two weeks of instruction present a high-risk period for campus outbreaks and that these outbreaks tend to spread into the neighboring communities. By integrating a classical mathematical epidemiology model and Bayesian learning, we learned the dynamic reproduction number for 30 colleges from their daily case reports. Of these 30 institutions, 14 displayed a spike of infections within the first two weeks of class, with peak seven-day incidences well above 1,000 per 100,000, an order of magnitude larger than the nationwide peaks of 70 and 150 during the first and second waves of the pandemic. While most colleges were able to rapidly reduce the number of new infections, many failed to control the spread of the virus beyond their own campus: Within only two weeks, 17 campus outbreaks translated directly into peaks of infection within their home counties. These findings suggests that college campuses are at risk to develop an extreme incidence of COVID-19 and become superspreaders for neighboring communities. We anticipate that tight test-trace-quarantine strategies, flexible transition to online instruction, and-most importantly-compliance with local regulations will be critical to ensure a safe campus reopening after the winter break.

Organoids are lumen‐containing multicellular structures that recapitulate key features of the organs, and are increasingly used in models of disease, drug testing, and regenerative medicine. Recent work has used 3D culture models to form organoids from human induced pluripotent stem cells (hiPSCs) in reconstituted basement membrane (rBM) matrices. However, rBM matrices offer little control over the microenvironment. More generally, the role of matrix viscoelasticity in directing lumen formation remains unknown. Here, viscoelastic alginate hydrogels with independently tunable stress relaxation (viscoelasticity), stiffness, and arginine–glycine–aspartate (RGD) ligand density are used to study hiPSC morphogenesis in 3D culture. A phase diagram that shows how these properties control hiPSC morphogenesis is reported. Higher RGD density and fast stress relaxation promote hiPSC viability, proliferation, apicobasal polarization, and lumen formation, while slow stress relaxation at low RGD densities triggers hiPSC apoptosis. Notably, hiPSCs maintain pluripotency in alginate hydrogels for much longer times than is reported in rBM matrices. Lumen formation is regulated by actomyosin contractility and is accompanied by translocation of Yes‐associated protein (YAP) from the nucleus to the cytoplasm. The results reveal matrix viscoelasticity as a potent factor regulating stem cell morphogenesis and provide new insights into how engineered biomaterials may be leveraged to build organoids.

Physical properties of the extracellular matrix (ECM) affect cell behaviors ranging from cell adhesion and migration to differentiation and gene expression, a process known as mechanotransduction. While most studies have focused on the impact of ECM stiffness, using linearly elastic materials such as polyacrylamide gels as cell culture substrates, biological tissues and ECMs are viscoelastic, which means they exhibit time-dependent mechanical responses and dissipate mechanical energy. Recent studies have revealed ECM viscoelasticity, independent of stiffness, as a critical physical parameter regulating cellular processes. These studies have used biomaterials with tunable viscoelasticity as cell-culture substrates, with alginate hydrogels being one of the most commonly used systems. Here, we detail the protocols for three approaches to modulating viscoelasticity in alginate hydrogels for 2D and 3D cell culture studies, as well as the testing of their mechanical properties. Viscoelasticity in alginate hydrogels can be tuned by varying the molecular weight of the alginate polymer, changing the type of crosslinker-ionic versus covalent-or by grafting short poly(ethylene-glycol) (PEG) chains to the alginate polymer. As these approaches are based on commercially available products and simple chemistries, these protocols should be accessible for scientists in the cell biology and bioengineering communities.

The basement membrane (BM) provides a physical barrier to invasion in epithelial tumors, and alterations in the molecular makeup and structural integrity of the BM have been implicated in cancer progression. Invadopodia are the invasive protrusions that enable cancer cells to breach the nanoporous basement membrane, through matrix degradation and generation of force. However, the impact of covalent cross-linking on invadopodia extension into the BM remains unclear. Here, we examine the impact of covalent cross-linking of extracellular matrix on invasive protrusions using biomaterials that present ligands relevant to the basement membrane and provide a nanoporous, confining microenvironment. We find that increased covalent cross-linking of reconstituted basement membrane (rBM) matrix diminishes matrix mechanical plasticity, or the ability of the matrix to permanently retain deformation due to force. Covalently cross-linked rBM matrices, and rBM-alginate interpenetrating networks (IPNs) with covalent cross-links and low plasticity, restrict cell spreading and protrusivity. The reduced spreading and reduced protrusivity in response to low mechanical plasticity occurred independent of proteases. Mechanistically, our computational model reveals that the reduction in mechanical plasticity due to covalent crosslinking is sufficient to mechanically prevent cell protrusions from extending, independent of the impact of covalent cross-linking or matrix mechanical plasticity on cell signaling pathways. These