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Abstract Structural and mechanical cues from the extracellular matrix (ECM) regulate tissue morphogenesis. Tissue development has conventionally been studied withex vivosystems where mechanical properties of the extracellular environment are either poorly controlled in space and time, lack tunability, or do not mimic ECM mechanics. For these reasons, it remains unknown how matrix stress relaxation rate, a time-dependent mechanical property that influences several cellular processes, regulates mammary branching morphogenesis. Here, we systematically investigated the influence of matrix stress relaxation on mammary branching morphogenesis using 3D alginate-collagen matrices and spheroids of human mammary epithelial cells. Slow stress relaxing matrices promoted significantly greater branch formation compared to fast stress relaxing matrices. Branching in slow stress relaxing matrices was accompanied by local collagen fiber alignment, while collagen fibers remained randomly oriented in fast stress relaxing matrices. In slow stress relaxing matrices, branch formation was driven by intermittent pulling contractions applied to the local ECM at the tips of elongating branches, which was accompanied by an abundance of phosphorylated focal adhesion kinase (phospho-FAK) and β1 integrin at the tips of branches. On the contrary, we observed that growing spheroids in fast stress relaxing matrices applied isotropic pushing forces to the ECM. Pharmacological inhibition of both Rac1 and non-muscle myosin II prevented epithelial branch formation, regardless of matrix stress relaxation rate. Interestingly, restricting cellular expansion via increased osmotic pressure was sufficient to impede epithelial branching in slow stress relaxing matrices. This work highlights the importance of stress relaxation in regulating and directing mammary branch elongation. 

Abstract Breast cancer progression is marked by extracellular matrix (ECM) remodeling, including increased stiffness, faster stress relaxation, and elevated collagen levels. In vitro experiments have revealed a role for each of these factors to individually promote malignant behavior, but their combined effects remain unclear. To address this, we developed alginate-collagen hydrogels with independently tunable stiffness, stress relaxation, and collagen density. We show that these combined tumor-mimicking ECM cues reinforced invasive morphologies and promoted spheroid invasion in breast cancer and mammary epithelial cells. High stiffness and low collagen density in slow-relaxing matrices led to the greatest cell migration speed and displacement. RNA-seq revealed Sp1 target gene enrichment in response to both individual and combined ECM cues, with a greater enrichment observed under multiple cues. Notably, high expression of Sp1 target genes upregulated by fast stress relaxation correlated with poor patient survival. Mechanistically, we found that phosphorylated-Sp1 (T453) was increasingly located in the nucleus in stiff and/or fast relaxing matrices, which was regulated by PI3K and ERK1/2 signaling, as well as actomyosin contractility. This study emphasizes how multiple ECM cues in complex microenvironments reinforce malignant traits and supports an emerging role for Sp1 as a mechanoresponsive transcription factor. 

Abstract Reconstituted basement membrane (rBM) products like Matrigel are widely used in 3D culture models of epithelial tissues and cancer. However, their utility is hindered by key limitations, including batch variability, xenogenic contaminants, and a lack of tunability. To address these challenges, we engineered a 3D basement membrane (eBM) matrix by conjugating defined extracellular matrix (ECM) adhesion peptides (IKVAV, YIGSR, RGD) to an alginate hydrogel network with precisely tunable stiffness and viscoelasticity. We optimized the mechanical and biochemical properties of the engineered basement membranes (eBMs) to support mammary acinar morphogenesis in MCF10A cells, similar to rBM. We found that IKVAV-modified, fast-relaxing (τ_1/2= 30-150 s), and soft (E = 200 Pa) eBMs best promoted polarized acinar structures. Clusters became invasive and lost polarity only when the IKVAV-modified eBM exhibited both similar stiffness to a malignant breast tumor (E = 4000 Pa) and slow stress relaxation (τ_1/2= 600-1100 s). Notably, tumor-like stiffness alone was not sufficient to drive invasion in fast stress relaxing matrices modified with IKVAV. In contrast, RGD-modified matrices promoted a malignant phenotype regardless of mechanical properties. We also utilized this system to interrogate the mechanism driving acinar and tumorigenic phenotypes in response to microenvironmental parameters. A balance in activity between β1- and β4-integrins was observed in the context of IKVAV-modified eBMs, prompting further investigation into the downstream mechanisms. We found differences in hemidesmosome formation and production of endogenous laminin in response to peptide type, stress relaxation, and stiffness. We also saw that inhibiting either focal adhesion kinase or hemidesmosome signaling in IKVAV eBMs prevented acinus formation. This eBM matrix is a powerful, reductionist, xenogenic-free system, offering a robust platform for both fundamental research and translational applications in tissue engineering and disease modeling. 

We introduce the shape module of the Python package Geomstats to analyze shapes of objects represented as landmarks, curves and surfaces across fields of natural sciences and engineering. The shape module first implements widely used shape spaces, such as the Kendall shape space, as well as elastic spaces of discrete curves and surfaces. The shape module further implements the abstract mathematical structures of group actions, fiber bundles, quotient spaces and associated Riemannian metrics which allow users to build their own shape spaces. The Riemannian geometry tools enable users to compare, average, interpolate between shapes inside a given shape space. These essential operations can then be leveraged to perform statistics and machine learning on shape data. We present the object-oriented implementation of the shape module along with illustrative examples and show how it can be used to perform statistics and machine learning on shape spaces. 

Abstract This paper presents a method for time-lapse 3D cell analysis. Specifically, we consider the problem of accurately localizing and quantitatively analyzing sub-cellular features, and for tracking individual cells from time-lapse 3D confocal cell image stacks. The heterogeneity of cells and the volume of multi-dimensional images presents a major challenge for fully automated analysis of morphogenesis and development of cells. This paper is motivated by the pavement cell growth process, and building a quantitative morphogenesis model. We propose a deep feature based segmentation method to accurately detect and label each cell region. An adjacency graph based method is used to extract sub-cellular features of the segmented cells. Finally, the robust graph based tracking algorithm using multiple cell features is proposed for associating cells at different time instances. We also demonstrate the generality of our tracking method on C. elegans fluorescent nuclei imagery. Extensive experiment results are provided and demonstrate the robustness of the proposed method. The code is available on and the method is available as a service through the BisQue portal. 

Septins self-assemble into polymers that bind and deform membranes in vitro and regulate diverse cell behaviors in vivo. How their in vitro properties relate to their in vivo functions is under active investigation. Here, we uncover requirements for septins in detachment and motility of border cell clusters in the Drosophila ovary. Septins and myosin colocalize dynamically at the cluster periphery and share phenotypes but, surprisingly, do not impact each other. Instead, Rho independently regulates myosin activity and septin localization. Active Rho recruits septins to membranes, whereas inactive Rho sequesters septins in the cytoplasm. Mathematical analyses identify how manipulating septin expression levels alters cluster surface texture and shape. This study shows that the level of septin expression differentially regulates surface properties at different scales. This work suggests that downstream of Rho, septins tune surface deformability while myosin controls contractility, the combination of which governs cluster shape and movement.