CELL CONTRACTILITY AND AN ACTIN GRADIENT DRIVE POLAR ALIGNMENT OF FIBROBLASTS IN CONSTRAINED GEOMETRIES
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE148155 | GEO | 2020/04/07
REPOSITORIES: GEO
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Project description:CELL CONTRACTILITY AND AN ACTIN GRADIENT DRIVE POLAR ALIGNMENT OF FIBROBLASTS IN CONSTRAINED GEOMETRIES
| PRJNA623348 | ENA
Project description:Asymmetrical delivery of stimuli to moving cells for perturbing spatially-heterogeneous intracellular signaling is an experimental challenge not adequately met by existing technologies. Here, we report a robust microfluidic platform allowing localized treatment of the front and/or back of moving cells which crawl through narrow channels that they completely occlude. The enabling technical element for this study is a novel design for precise, passive balancing of flow inside the microfluidic device by contacting two fluid streams before splitting them again. The microchannels constrain cell morphology and induce qualitative and quantitative changes in neutrophil chemotaxis that mimic cells crawling through tissues.
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Project description:During animal development and homeostasis, the structure of tissues, including muscles, blood vessels, and connective tissues, adapts to mechanical strains in the extracellular matrix (ECM). These strains originate from the differential growth of tissues or forces due to muscle contraction or gravity. Here we show using a computational model that by amplifying local strain cues, active cell contractility can facilitate and accelerate the reorientation of single cells to static strains. At the collective cell level, the model simulations show that active cell contractility can facilitate the formation of strings along the orientation of stretch. The computational model is based on a hybrid cellular Potts and finite-element simulation framework describing a mechanical cell-substrate feedback, where: 1) cells apply forces on the ECM, such that 2) local strains are generated in the ECM and 3) cells preferentially extend protrusions along the strain orientation. In accordance with experimental observations, simulated cells align and form stringlike structures parallel to static uniaxial stretch. Our model simulations predict that the magnitude of the uniaxial stretch and the strength of the contractile forces regulate a gradual transition between stringlike patterns and vascular networklike patterns. Our simulations also suggest that at high population densities, less cell cohesion promotes string formation.
| S-EPMC5340096 | biostudies-literature
Project description:Whole cell cryo-electron tomography emerges as an important component for structural system biology approaches. It allows the localization and structural characterization of macromolecular complexes in near living conditions. However, the method is hampered by low resolution, missing data and low signal-to-noise ratio (SNR). To overcome some of these difficulties one can align and average a large set of subtomograms. Existing alignment methods are mostly based on an exhaustive scanning and sampling of all but discrete relative rotations and translations of one subtomogram with respect to the other. In this paper, we propose a gradient-guided alignment method based on two subtomogram similarity measures. We also propose a stochastic parallel optimization that increases significantly the efficiency for the simultaneous refinement of a set of alignment candidates. Results on simulated data of model complexes and experimental structures of protein complexes show that even for highly distorted subtomograms and with only a small number of very sparsely distributed initial alignment seeds, our method can accurately recover true transformations with a significantly higher precision than scanning based alignment methods.
| S-EPMC4108348 | biostudies-literature
Project description:Highly constrained bicyclic scaffolds are ubiquitous and attracting increasing interest in pharmaceutical and biotechnology discoveries owing to the enhanced activities. Herein, we report a protocol to access highly substituted constrained bicycloalkanes from readily accessible α-silyl alcohols and olefins through a bibase-promoted Brook rearrangement/radical-polar crossover cyclization (RPCC) process. Of note, the practical procedure features broad substrate scope and good group tolerance under mild and operationally simple conditions, using an inexpensive organic photocatalyst. Gram-scale preparation and diverse synthetic transformations demonstrate opportunities to rapidly construct molecular complexity. Mechanistic studies have indicated that the transformation involves a bibase-promoted radical transfer rearrangement addition/radical-polar crossover cyclization relay sequence, which differs from traditional solitary RPCC reactions.
| S-EPMC11253123 | biostudies-literature
Project description:Tissue elongation and its control by spatiotemporal signals is a major developmental question. Currently, it is thought that Drosophila ovarian follicular epithelium elongation requires the planar polarization of the basal domain cytoskeleton and of the extra-cellular matrix, associated with a dynamic process of rotation around the anteroposterior axis. Here we show, by careful kinetic analysis of fat2 mutants, that neither basal planar polarization nor rotation is required during a first phase of follicle elongation. Conversely, a JAK-STAT signaling gradient from each follicle pole orients early elongation. JAK-STAT controls apical pulsatile contractions, and Myosin II activity inhibition affects both pulses and early elongation. Early elongation is associated with apical constriction at the poles and with oriented cell rearrangements, but without any visible planar cell polarization of the apical domain. Thus, a morphogen gradient can trigger tissue elongation through a control of cell pulsing and without a planar cell polarity requirement.
| S-EPMC5805408 | biostudies-literature
Project description:Cryo-electron tomography allows the visualization of macromolecular complexes in their cellular environments in close-to-live conditions. The nominal resolution of subtomograms can be significantly increased when individual subtomograms of the same kind are aligned and averaged. A vital step for such a procedure are algorithms that speedup subtomogram alignment and improve its accuracy to allow reference-free subtomogram classifications. Such methods will facilitate automation of tomography analysis and overall high throughput in the data processing. Building on previous work, here we propose a fast rotational alignment method that uses the Fourier equivalent form of a popular constrained correlation measure that considers missing wedge corrections and density variances in the subtomograms. The fast rotational search is based on 3D volumetric matching, which improves the rotational alignment accuracy in particular for highly distorted subtomograms with low SNR and tilt angle ranges in comparison to fast rotational matching of projected 2D spherical images. We further integrate our fast rotational alignment method in a reference-free iterative subtomogram classification scheme, and propose a local feature enhancement strategy in the classification process. As a proof of principle, we can demonstrate that the automatic method can successfully classify a large number of experimental subtomograms without the need of a reference structure.
| S-EPMC3821800 | biostudies-literature
Project description:PurposeDiffusion-weighted MRI is sensitive to incoherent tissue motion, which may confound the measured signal and subsequent analysis. We propose a "motion-compensated" gradient waveform design for tensor-valued diffusion encoding that negates the effects bulk motion and incoherent motion in the ballistic regime.MethodsMotion compensation was achieved by constraining the magnitude of gradient waveform moment vectors. The constraint was incorporated into a numerical optimization framework, along with existing constraints that account for b-tensor shape, hardware restrictions, and concomitant field gradients. We evaluated the efficacy of encoding and motion compensation in simulations, and we demonstrated the approach by linear and planar b-tensor encoding in a healthy heart in vivo.ResultsThe optimization framework produced asymmetric motion-compensated waveforms that yielded b-tensors of arbitrary shape with improved efficiency compared with previous designs for tensor-valued encoding, and equivalent efficiency to previous designs for linear (conventional) encoding. Technical feasibility was demonstrated in the heart in vivo, showing vastly improved data quality when using motion compensation. The optimization framework is available online in open source.ConclusionOur gradient waveform design is both more flexible and efficient than previous methods, facilitating tensor-valued diffusion encoding in tissues in which motion would otherwise confound the signal. The proposed design exploits asymmetric encoding times, a single refocusing pulse or multiple refocusing pulses, and integrates compensation for concomitant gradient effects throughout the imaging volume.
| S-EPMC7821235 | biostudies-literature
Project description:Sample groupings for this project are as follows: Cauline leaf vs Cultured Cell : - Cauline leaf, p1; Exp:Red; Ref: Green (Cy5:Cy3) - Cauline leaf, p2; Exp:Red; Ref: Green (Cy5:Cy3) - Cauline leaf, p3; Exp:Red; Ref: Green (Cy5:Cy3) Cotyledon light vs Cotyledon dark : - Cotyledon, CP1; Exp:Red; Ref: Green (Cy5:Cy3) - Cotyledon, CP2; Exp:Red; Ref: Green (Cy5:Cy3) Cotyledon light vs Cultured cell : - Cotyledon, cn1; Exp:Green; Ref: Red (Cy3:Cy5) - Cotyledon, cn2; Exp:Green; Ref: Red (Cy3:Cy5) Cotyledon dark vs Cultured cell : - Cotyledon dark, n1; Exp:Green; Ref: Red (Cy3:Cy5) - Cotyledon dark, n2; Exp:Green; Ref: Red (Cy3:Cy5) - Cotyledon dark, n3; Exp:Green; Ref: Red (Cy3:Cy5) Germinating seed vs Cultured cell : - Germinating seed, gn1; Exp:Green; Ref: Red (Cy3:Cy5) - Germinating seed, gn2; Exp:Green; Ref: Red (Cy3:Cy5) - Germinating seed, gn3; Exp:Green; Ref: Red (Cy3:Cy5) Hypocotyl light vs Hypocotyl dark : - Hypocotyl, hldn1; Exp:Red; Ref: Green (Cy5:Cy3) - Hypocotyl, hldn2; Exp:Red; Ref: Green (Cy5:Cy3) Hypocotyl light vs Cultured cell : - Hypocotyl light, hln1; Exp:Green; Ref: Red (Cy3:Cy5) - Hypocotyl light, hln2; Exp:Green; Ref: Red (Cy3:Cy5) Petal vs Cultured cell : - Petal, pn1; Exp:Green; Ref: Red (Cy3:Cy5) - Petal, pn2; Exp:Green; Ref: Red (Cy3:Cy5) - Petal, pn3; Exp:Green; Ref: Red (Cy3:Cy5) 1DBP vs Cultured cell : - Pistil 1DBP, pin1; Exp:Green; Ref: Red (Cy3:Cy5) - Pistil 1DBP, pin2; Exp:Green; Ref: Red (Cy3:Cy5) - Pistil 1DBP, pin3; Exp:Green; Ref: Red (Cy3:Cy5) Pistil 1DPP vs Cultured cell : - Pistil 1DPP, psn1; Exp:Green; Ref: Red (Cy3:Cy5) - Pistil 1DPP, psn2; Exp:Green; Ref: Red (Cy3:Cy5) - Pistil 1DPP, psn3; Exp:Green; Ref: Red (Cy3:Cy5) - Pistil 1DPP, psn4; Exp:Green; Ref: Red (Cy3:Cy5) Root dark vs Cultured cell : - Root dark, rdn1; Exp:Green; Ref: Red (Cy3:Cy5) - Root dark, rdn2; Exp:Green; Ref: Red (Cy3:Cy5) Root light vs Cultured cell : - Root light, rln1; Exp:Green; Ref: Red (Cy3:Cy5) - Root light, rlp1; Exp:Red; Ref: Green (Cy5:Cy3) Root light vs Root dark : - Root light vs dark, rldp1; Exp:Red; Ref: Green (Cy5:Cy3) - Root light vs dark, rldp2; Exp:Red; Ref: Green (Cy5:Cy3) Rosette leaf vs Cultured cell : - Rosette leaf, rfp1; Exp:Red; Ref: Green (Cy5:Cy3) - Rosette leaf, rfp2; Exp:Red; Ref: Green (Cy5:Cy3) - Rosette leaf, rfp3; Exp:Red; Ref: Green (Cy5:Cy3) Sepal vs Cultured cell : - Sepal, sn1; Exp:Green; Ref: Red (Cy3:Cy5) - Sepal, sn2; Exp:Green; Ref: Red (Cy3:Cy5) Silique 3DPP vs Cultured cell : - Silique 3DPP, s3n1; Exp:Green; Ref: Red (Cy3:Cy5) - Silique 3DPP, s3n2; Exp:Green; Ref: Red (Cy3:Cy5) - Silique 3DPP, s3n3; Exp:Green; Ref: Red (Cy3:Cy5) Silique 8DPP vs Cultured cell : - Silique 8DPP, s8n1; Exp:Green; Ref: Red (Cy3:Cy5) - Silique 8DPP, s8n2; Exp:Green; Ref: Red (Cy3:Cy5) - Silique 8DPP, s8n3; Exp:Green; Ref: Red (Cy3:Cy5) Stamen vs Cultured cell : - Stamen, smn1; Exp:Green; Ref: Red (Cy3:Cy5) - Stamen, smn2; Exp:Green; Ref: Red (Cy3:Cy5) - Stamen, smn3; Exp:Green; Ref: Red (Cy3:Cy5) Hypocotyl dark vs Cultured cell : - Hypocotyl dark, hn1; Exp:Green; Ref: Red (Cy3:Cy5) - Hypocotyl dark, hn2; Exp:Green; Ref: Red (Cy3:Cy5) Stem vs Cultured cell : - Stem, stp1; Exp:Red; Ref: Green (Cy5:Cy3) - Stem, stp2; Exp:Red; Ref: Green (Cy5:Cy3) - Stem, stp3; Exp:Red; Ref: Green (Cy5:Cy3) Keywords: other
2004-10-24 | GSE1599 | GEO
Project description:MotivationGiven a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism.ResultsWe consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms.AvailabilityOpen source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC3694646 | biostudies-literature