Dataset Information

3D magnetically controlled spatiotemporal probing and actuation of collagen networks from a single cell perspective.

ABSTRACT: Cells continuously sense and react to mechanical cues from their surrounding matrix, which consists of a fibrous network of biopolymers that influences their fate and behavior. Several powerful methods employing magnetic control have been developed to assess the micromechanical properties within extracellular matrix (ECM) models hosting cells. However, many of these are limited to in-plane sensing and actuation, which does not allow the matrix to be probed within its full 3D context. Moreover, little attention has been given to factors specific to the model ECM systems that can profoundly influence the cells contained there. Here we present methods to spatiotemporally probe and manipulate extracellular matrix networks at the scale relevant to cells using magnetic microprobes (μRods). Our techniques leverage 3D magnetic field generation, physical modeling, and image analysis to examine and apply mechanical stimuli to fibrous collagen matrices. We determined shear moduli ranging between hundreds of Pa to tens of kPa and modeled the effects of proximity to rigid surfaces and local fiber densification. We analyzed the spatial extent and dynamics of matrix deformation produced in response to magnetic torques on the order of 10 pNm, deflecting fibers over an area spanning tens of micrometers. Finally, we demonstrate 3D actuation and pose extraction of fluorescently labelled μRods.

SUBMITTER: Asgeirsson DO

PROVIDER: S-EPMC8507888 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

3D magnetically controlled spatiotemporal probing and actuation of collagen networks from a single cell perspective.

Asgeirsson Daphne O DO Christiansen Michael G MG Valentin Thomas T Somm Luca L Mirkhani Nima N Nami Amin Hosseini AH Hosseini Vahid V Schuerle Simone S

Lab on a chip 20211012 20

Cells continuously sense and react to mechanical cues from their surrounding matrix, which consists of a fibrous network of biopolymers that influences their fate and behavior. Several powerful methods employing magnetic control have been developed to assess the micromechanical properties within extracellular matrix (ECM) models hosting cells. However, many of these are limited to in-plane sensing and actuation, which does not allow the matrix to be probed within its full 3D context. Moreover, l ...[more]

PMID: 34505607

Similar Datasets

Project description:While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo, functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a "bottom-up" 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

Project description:The predominant structural protein in vertebrates is collagen, which plays a key role in extracellular matrix and connective tissue mechanics. Despite its prevalence and physical importance in biology, the mechanical properties of molecular collagen are far from established. The flexibility of its triple helix is unresolved, with descriptions from different experimental techniques ranging from flexible to semirigid. Furthermore, it is unknown how collagen type (homo- versus heterotrimeric) and source (tissue derived versus recombinant) influence flexibility. Using SmarTrace, a chain-tracing algorithm we devised, we performed statistical analysis of collagen conformations collected with atomic force microscopy to determine the protein's mechanical properties. Our results show that types I, II, and III collagens-the key fibrillar varieties-exhibit similar molecular flexibilities. However, collagen conformations are strongly modulated by salt, transitioning from compact to extended as KCl concentration increases in both neutral and acidic pH. Although analysis with a standard worm-like chain model suggests that the persistence length of collagen can attain a wide range of values within the literature range, closer inspection reveals that this modulation of collagen's conformational behavior is not due to changes in flexibility but rather arises from the induction of curvature (either intrinsic or induced by interactions with the mica surface). By modifying standard polymer theory to include innate curvature, we show that collagen behaves as an equilibrated curved worm-like chain in two dimensions. Analysis within the curved worm-like chain model shows that collagen's curvature depends strongly on pH and salt, whereas its persistence length does not. Thus, we find that triple-helical collagen is well described as semiflexible irrespective of source, type, pH, and salt environment. These results demonstrate that collagen is more flexible than its conventional description as a rigid rod, which may have implications for its cellular processing and secretion.

Dataset Information

3D magnetically controlled spatiotemporal probing and actuation of collagen networks from a single cell perspective.

Publications

3D magnetically controlled spatiotemporal probing and actuation of collagen networks from a single cell perspective.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets