Bakhtina, N. | Search bioRxiv

bioRxiv2020

3D synthetic microscaffolds promote homogenous expression of NANOG in mouse embryonic stem cells

The development of in vitro models, which accurately recapitulate early embryonic development, is one of the fundamental challenges in stem cell research. Most of the currently employed approaches involve the culture of embryonic stem cells (ESCs) on two-dimensional (2D) surfaces. However, the monolayer nature of these cultures does not permit cells to grow and proliferate in realistic three-dimensional (3D) microenvironments, as in an early embryo. In this paper, novel 3D synthetic scaffold arrays, fabricated by two-photon polymerization photolithography, are utilized to mimic tissue-specific architecture, enabling cell-to-matrix interaction and cell-to-cell communication in vitro. Mouse ESCs (mESCs) are able to grow and proliferate on these structures and maintain their pluripotent state. Furthermore, the 3D microscaffold arrays are integrated into a microscopy slide allowing the evaluation of the expression of key pluripotency factors at the single-cell level. Comparing 2D and 3D surfaces, mESCs grown in serum+LIF on 3D microscaffolds exhibit a stronger and more homogenous expression of NANOG and OCT4 pluripotency factors, than cells cultivated in 2i media, demonstrating that 3D microscaffolds capture naive pluripotency in vitro. Thus, the slide affords a novel and unique tool to model and study mammalian early development with greater physiological relevance than conventional 2D cultures.

bioengineering↗

bioRxiv2019

Motion prediction enables simulated MR-imaging of freely moving model organisms

AbstractMagnetic resonance tomography typically applies the Fourier transform to k-space signals repeatedly acquired from a frequency encoded spatial region of interest, therefore requiring a stationary object during scanning. Any movement of the object results in phase errors in the recorded signal, leading to deformed images, phantoms, and artifacts, since the encoded information does not originate from the intended region of the object. However, if the type and magnitude of movement is known instantaneously, the scanner or the reconstruction algorithm could be adjusted to compensate for the movement, directly allowing high quality imaging with non-stationary objects. This would be an enormous boon to studies that tie cell metabolomics to spontaneous organism behaviour, eliminating the stress otherwise necessitated by restraining measures such as anesthesia or clamping.\n\nIn the present theoretical study, we use a phantom of the animal model C. elegans to examine the feasibility to automatically predict its movement and position, and to evaluate the impact of movement prediction, within a sufficiently long time horizon, on image reconstruction. For this purpose, we use automated image processing to annotate body parts in freely moving C. elegans, and predict their path of movement. We further introduce an MRI simulation platform based on brightfield-videos of the moving worm, combined with a stack of high resolution transmission electron microscope (TEM) slice images as virtual high resolution phantoms. A phantom provides an indication of the spatial distribution of signal-generating nuclei on a particular imaging slice. We show that adjustment of the scanning to the predicted movements strongly reduces distortions in the resulting image, opening the door for implementation in a high-resolution NMR scanner.

systems biology↗