Influence of Fiber Stiffness on Meniscal Cell Migration into Dense Fibrous Networks.
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ABSTRACT:
SUBMITTER: Song KH
PROVIDER: S-EPMC7274873 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Dense matrices impede interstitial cell migration and subsequent repair. We hypothesized that nuclear stiffness is a limiting factor in migration and posited that repair could be expedited by transiently decreasing nuclear stiffness. To test this, we interrogated the interstitial migratory capacity of adult meniscal cells through dense fibrous networks and adult tissue before and after nuclear softening via the application of a histone deacetylase inhibitor, Trichostatin A (TSA) or knockdown of the filamentous nuclear protein Lamin A/C. Our results show that transient softening of the nucleus improves migration through microporous membranes, electrospun fibrous matrices, and tissue sections and that nuclear properties and cell function recover after treatment. We also showed that biomaterial delivery of TSA promoted in vivo cellularization of scaffolds by endogenous cells. By addressing the inherent limitations to repair imposed by nuclear stiffness, this work defines a new strategy to promote the repair of damaged dense connective tissues.
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Project description:The peritumoral stroma is a complex 3D tissue that provides cells with myriad biophysical and biochemical cues. Histologic observations suggest that during metastatic spread of carcinomas, these cues influence transformed epithelial cells, prompting a diversity of migration modes spanning single cell and multicellular phenotypes. Purported consequences of these variations in tumor escape strategies include differential metastatic capability and therapy resistance. Therefore, understanding how cues from the peritumoral stromal microenvironment regulate migration mode has both prognostic and therapeutic value. Here, we utilize a synthetic stromal mimetic in which matrix fiber density and bulk hydrogel mechanics can be orthogonally tuned to investigate the contribution of these two key matrix attributes on MCF10A migration mode phenotypes, epithelial-mesenchymal transition (EMT), and invasive potential. We develop an automated computational image analysis framework to extract migratory phenotypes from fluorescent images and determine 3D migration metrics relevant to metastatic spread. Using this analysis, we find that matrix fiber density and bulk hydrogel mechanics distinctly contribute to a variety of MCF10A migration modes including amoeboid, single mesenchymal, clusters, and strands. We identify combinations of physical and soluble cues that induce a variety of migration modes originating from the same MCF10A spheroid and use these settings to examine a functional consequence of migration mode -resistance to apoptosis. We find that cells migrating as strands are more resistant to staurosporine-induced apoptosis than either disconnected clusters or individual invading cells. Improved models of the peritumoral stromal microenvironment and understanding of the relationships between matrix attributes and cell migration mode can aid ongoing efforts to identify effective cancer therapeutics that address cell plasticity-based therapy resistances. STATEMENT OF SIGNIFICANCE: Stromal extracellular matrix structure dictates both cell homeostasis and activation towards migratory phenotypes. However decoupling the effects of myriad biophysical cues has been difficult to achieve. Here, we encapsulate electrospun fiber segments within an amorphous hydrogel to create a fiber-reinforced hydrogel composite in which fiber density and hydrogel stiffness can be orthogonally tuned. Quantification of 3D cell migration reveal these two parameters uniquely contribute to a diversity of migration phenotypes spanning amoeboid, single mesenchymal, multicellular cluster, and collective strand. By tuning biophysical and biochemical cues to elicit heterogeneous migration phenotypes, we find that collective strands best resist apoptosis. This work establishes a composite approach to modulate fibrous topography and bulk hydrogel mechanics and identified biomaterial parameters to direct distinct 3D cell migration phenotypes.
| S-EPMC10043045 | biostudies-literature
Project description:The propagation of mechanical signals through nonlinear fibrous tissues is much more extensive than through continuous synthetic hydrogels. Results from recent studies indicate that increased mechanical propagation arises from the fibrous nature of the material rather than the strain-stiffening property. The relative importance of different parameters of the fibrous network structure to this propagation, however, remains unclear. In this work, we directly compared the mechanical response of substrates of varying thickness subjected to a constant cell traction force using either a nonfibrous strain-stiffening continuum-based model or a volume-averaged fiber network model consisting of two different types of fiber network structures: one with low fiber connectivity (growth networks) and one with high fiber connectivity (Delaunay networks). The growth network fiber models predicted a greater propagation of substrate displacements through the model and a greater sensitivity to gel thickness compared to the more connected Delaunay networks and the nonlinear continuum model. Detailed analysis of the results indicates that rotational freedom of the fibers in a network with low fiber connectivity is critically important for enhanced, long-range mechanosensing. Our findings demonstrate the utility of multiscale models in predicting cells mechanosensing on fibrous gels, and they provide a more complete understanding of how cell traction forces propagate through fibrous tissues, which has implications for the design of engineered tissues and the stem cell niche.
| S-EPMC5018119 | biostudies-literature
Project description:It has been shown that cellular migration, persistence, and associated cytoskeletal arrangement are highly dependent on substrate stiffness (modulus: N/m(2) and independent of geometry), but little is known on how cells respond to subtle changes in local geometry and structural stiffness (N/m). Here, using fibers of varying diameter (400, 700, and 1200 nm) and length (1 and 2 mm) deposited over hollow substrates, we demonstrate that single mouse C2C12 cells attached to single suspended fibers form spindle morphologies that are sensitive to fiber mechanical properties. Over a wide range of increasing structural stiffness (2 to 100+ mN/m), cells exhibited decreases in migration speed and average nucleus shape index of ∼57% (from 58 to 25 μm/h) and ∼26% (from 0.78 to 0.58), respectively, whereas the average paxillin focal-adhesion-cluster (FAC, formed at poles) length increased by ∼38% (from 8 to 11 μm). Furthermore, the increase in structural stiffness directly correlates with cellular persistence, with 60% of cells moving in the direction of increasing structural stiffness. At similar average structural stiffness (25 ± 5 mN/m), cells put out longer FAC lengths on smaller diameters, suggesting a conservation of FAC area, and also exhibited higher nucleus shape index and migration speeds on larger-diameter fibers. Interestingly, cells were observed to deform fibers locally or globally through forces applied through the FAC sites and cells undergoing mitosis were found to be attached to the FAC sites by single filamentous tethers. These varied reactions have implications in developmental and disease biology models as they describe a strong dependence of cellular behavior on the cell's immediate mechanistic environment arising from alignment and geometry of fibers.
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Project description:Cell migration, which is central to many biological processes including wound healing and cancer progression, is sensitive to environmental stiffness, and many cell types exhibit a stiffness optimum, at which migration is maximal. Here we present a cell migration simulator that predicts a stiffness optimum that can be shifted by altering the number of active molecular motors and clutches. This prediction is verified experimentally by comparing cell traction and F-actin retrograde flow for two cell types with differing amounts of active motors and clutches: embryonic chick forebrain neurons (ECFNs; optimum ∼1 kPa) and U251 glioma cells (optimum ∼100 kPa). In addition, the model predicts, and experiments confirm, that the stiffness optimum of U251 glioma cell migration, morphology and F-actin retrograde flow rate can be shifted to lower stiffness by simultaneous drug inhibition of myosin II motors and integrin-mediated adhesions.
| S-EPMC5458120 | biostudies-literature
Project description:Cell migration is central to many biological processes including embryonic development, wound healing, and cancer progression. Cell migration is sensitive to environmental stiffness, and many cell types exhibit a stiffness optimum at which migration is maximal. Here we present a cell migration simulator that predicts a stiffness optimum that can be shifted by altering the number of active molecular motors and clutches. This prediction is verified experimentally by comparing cell traction and F-actin retrograde flow for two cell types with differing amounts of active motors and clutches: embryonic chick forebrain neurons (ECFNs; optimum ~1 kPa) and U251 glioma cells (optimum ~100 kPa). In addition, the model predicts, and experiments confirm, that the stiffness optimum of U251 glioma cell migration, morphology, and F-actin retrograde flow rate can be shifted to lower stiffness by simultaneous drug inhibition of myosin II motors and integrin-mediated adhesions.
2017-05-23 | GSE95680 | GEO
Project description:Cells contracting in extracellular matrix (ECM) can transmit stress over long distances, communicating their position and orientation to cells many tens of micrometres away. Such phenomena are not observed when cells are seeded on substrates with linear elastic properties, such as polyacrylamide (PA) gel. The ability for fibrous substrates to support far reaching stress and strain fields has implications for many physiological processes, while the mechanical properties of ECM are central to several pathological processes, including tumour invasion and fibrosis. Theoretical models have investigated the properties of ECM in a variety of network geometries. However, the effects of network architecture on mechanical cell-cell communication have received little attention. This work investigates the effects of geometry on network mechanics, and thus the ability for cells to communicate mechanically through different networks. Cell-derived displacement fields are quantified for various network geometries while controlling for network topology, cross-link density and micromechanical properties. We find that the heterogeneity of response, fibre alignment, and substrate displacement fields are sensitive to network choice. Further, we show that certain geometries support mechanical communication over longer distances than others. As such, we predict that the choice of network geometry is important in fundamental modelling of cell-cell interactions in fibrous substrates, as well as in experimental settings, where mechanical signalling at the cellular scale plays an important role. This work thus informs the construction of theoretical models for substrate mechanics and experimental explorations of mechanical cell-cell communication.
| S-EPMC5331102 | biostudies-literature
Project description:Seeking new insights into the homeostasis, modulation and plasticity of cortical synaptic networks, we have analyzed results from a single-cell RNA-seq study of 22,439 mouse neocortical neurons. Our analysis exposes transcriptomic evidence for dozens of molecularly distinct neuropeptidergic modulatory networks that directly interconnect all cortical neurons. This evidence begins with a discovery that transcripts of one or more neuropeptide precursor (NPP) and one or more neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes are highly abundant in all, or very nearly all, cortical neurons. Individual neurons express diverse subsets of NP signaling genes from palettes encoding 18 NPPs and 29 NP-GPCRs. These 47 genes comprise 37 cognate NPP/NP-GPCR pairs, implying the likelihood of local neuropeptide signaling. Here, we use neuron-type-specific patterns of NP gene expression to offer specific, testable predictions regarding 37 peptidergic neuromodulatory networks that may play prominent roles in cortical homeostasis and plasticity.
| S-EPMC6881117 | biostudies-literature
Project description:MotivationIn single-cell transcriptomics applications, effective identification of cell types in multicellular organisms and in-depth study of the relationships between genes has become one of the main goals of bioinformatics research. However, data heterogeneity and random noise pose significant difficulties for scRNA-seq data analysis.ResultsWe have proposed an adversarial dense graph convolutional network architecture for single-cell classification. Specifically, to enhance the representation of higher-order features and the organic combination between features, dense connectivity mechanism and attention-based feature aggregation are introduced for feature learning in convolutional neural networks. To preserve the features of the original data, we use a feature reconstruction module to assist the goal of single-cell classification. In addition, HNNVAT uses virtual adversarial training to improve the generalization and robustness. Experimental results show that our model outperforms the existing classical methods in terms of classification accuracy on benchmark datasets.Availability and implementationThe source code of HNNVAT is available at https://github.com/DisscLab/HNNVAT.Supplementary informationSupplementary data are available at Bioinformatics online.
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Project description:Cell migration is associated with the establishment of defined leading and trailing edges, which in turn requires polarization of contractile forces. While the actomyosin stress fiber (SF) network plays a critical role in enforcing this polarity, precisely how this asymmetry is established remains unclear. Here, we provide evidence for a model in which the actin-severing protein cofilin (specifically cofilin-1) participates in symmetry breakage by removing low-tension actomyosin filaments during transverse arc assembly. Cofilin knockdown (KD) produces a non-polarized SF architecture that cannot be rescued with chemokines or asymmetric matrix patterns. Whereas cofilin KD increases whole-cell prestress, it decreases prestress within single SFs, implying an accumulation of low-tension SFs. This notion is supported by time-lapse imaging, which reveals weakly contractile and incompletely fused transverse arcs. Confocal and super-resolution imaging further associate this failed fusion with the presence of crosslinker-rich, tropomyosin-devoid nodes at the junctions of multiple transverse arc fragments and dorsal SFs. These results support a model in which cofilin facilitates the formation of high-tension transverse arcs, thereby promoting mechanical asymmetry.
| S-EPMC7358140 | biostudies-literature