Dataset Information

Observations of Membrane Domain Reorganization in Mechanically Compressed Artificial Cells.

ABSTRACT: Giant unilamellar vesicles (GUVs) are considered to be the gold standard for assembling artificial cells from the bottom up. In this study, we investigated the behavior of such biomimetic vesicles as they were subjected to mechanical compression. A microfluidic device is presented that comprises a trap to capture GUVs and a microstamp that is deflected downwards to mechanically compress the trapped vesicle. After characterization of the device, we show that single-phase GUVs can be controllably compressed to a high degree of deformation (D=0.40) depending on the pressure applied to the microstamp. A permeation assay was implemented to show that vesicle bursting is prevented by water efflux. Next, we mechanically compressed GUVs with co-existing liquid-ordered and liquid-disordered membrane phases. Upon compression, we observed that the normally stable lipid domains reorganized themselves across the surface and fused into larger domains. This phenomenon, observed here in a model membrane system, not only gives us insights into how the multicomponent membranes of artificial cells behave, but might also have interesting consequences for the role of lipid rafts in biological cells that are subjected to compressive forces in a natural environment.

SUBMITTER: Robinson T

PROVIDER: S-EPMC7612542 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Observations of Membrane Domain Reorganization in Mechanically Compressed Artificial Cells.

Robinson Tom T Dittrich Petra S PS

Chembiochem : a European journal of chemical biology 20191001 20

Giant unilamellar vesicles (GUVs) are considered to be the gold standard for assembling artificial cells from the bottom up. In this study, we investigated the behavior of such biomimetic vesicles as they were subjected to mechanical compression. A microfluidic device is presented that comprises a trap to capture GUVs and a microstamp that is deflected downwards to mechanically compress the trapped vesicle. After characterization of the device, we show that single-phase GUVs can be controllably ...[more]

PMID: 31087814

Similar Datasets

Project description:BackgroundLocalization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method.ResultsHere we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality.ConclusionsOur deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.

Project description:Classical in vitro fertilization (IVF) is still poorly successful in horses. This lack of success is thought to be due primarily to inadequate capacitation of stallion spermatozoa under in vitro conditions. In species in which IVF is successful, bicarbonate, calcium, and albumin are considered the key components that enable a gradual reorganization of the sperm plasma membrane that allows the spermatozoa to undergo an acrosome reaction and fertilize the oocyte. The aim of this work was to comprehensively examine contributors to stallion sperm capacitation by investigating bicarbonate-induced membrane remodelling steps, and elucidating the contribution of cAMP signalling to these events. In the presence of capacitating media containing bicarbonate, a significant increase in plasma membrane fluidity was readily detected using merocyanine 540 staining in the majority of viable spermatozoa within 15 min of bicarbonate exposure. Specific inhibition of soluble adenylyl cyclase (sAC) in the presence of bicarbonate by LRE1 significantly reduced the number of viable sperm with high membrane fluidity. This suggests a vital role for sAC-mediated cAMP production in the regulation of membrane fluidity. Cryo-electron tomography of viable cells with high membrane fluidity revealed a range of membrane remodelling intermediates, including destabilized membranes and zones with close apposition of the plasma membrane and the outer acrosomal membrane. However, lipidomic analysis of equivalent viable spermatozoa with high membrane fluidity demonstrated that this phenomenon was neither accompanied by a gross change in the phospholipid composition of stallion sperm membranes nor detectable sterol efflux (p > 0.05). After an early increase in membrane fluidity, a significant and cAMP-dependent increase in viable sperm with phosphatidylserine (PS), but not phosphatidylethanolamine (PE) exposure was noted. While the events observed partly resemble findings from the in vitro capacitation of sperm from other mammalian species, the lack of cholesterol removal appears to be an equine-specific phenomenon. This research will assist in the development of a defined medium for the capacitation of stallion sperm and will facilitate progress toward a functional IVF protocol for horse gametes.

Dataset Information

Observations of Membrane Domain Reorganization in Mechanically Compressed Artificial Cells.

Publications

Observations of Membrane Domain Reorganization in Mechanically Compressed Artificial Cells.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets