Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, ul. Reymonta 19, 30-059 Cracow, Poland.
Faculty of Geology, Geophysics and Environmental Protection, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland.
Cells. 2020 Sep 19;9(9):2124. doi: 10.3390/cells9092124.
In the literature, diffusion studies of cell systems are usually limited to two water pools that are associated with the extracellular space and the entire interior of the cell. Therefore, the time-dependent diffusion coefficient contains information about the geometry of these two water regions and the water exchange through their boundary. This approach is due to the fact that most of these studies use pulse techniques and relatively low gradients, which prevents the achievement of high -values. As a consequence, it is not possible to register the signal coming from proton populations with a very low bulk or apparent self-diffusion coefficient, such as cell organelles. The purpose of this work was to obtain information on the geometry and dynamics of water at a level lower than the cell size, i.e., in cellular structures, using the time-dependent diffusion coefficient method. The model of the cell system was made of baker's yeast () since that is commonly available and well-characterized. We measured characteristic fresh yeast properties with the application of a compact Nuclear Magnetic Resonance (NMR)-Magritek Mobile Universal Surface Explorer (MoUSE) device with a very high, constant gradient (~24 T/m), which enabled us to obtain a sufficient stimulated echo attenuation even for very short diffusion times (0.2-40 ms) and to apply very short diffusion encoding times. In this work, due to a very large diffusion weighting (-values), splitting the signal into three components was possible, among which one was associated only with cellular structures. Time-dependent diffusion coefficient analysis allowed us to determine the self-diffusion coefficients of extracellular fluid, cytoplasm and cellular organelles, as well as compartment sizes. Cellular organelles contributing to each compartment were identified based on the random walk simulations and approximate volumes of water pools calculated using theoretical sizes or molar fractions. Information about different cell structures is contained in different compartments depending on the diffusion regime, which is inherent in studies applying extremely high gradients.
在文献中，细胞系统的扩散研究通常仅限于与细胞外空间和整个细胞内部相关的两个水池。因此，随时间变化的扩散系数包含有关这两个水区域的几何形状以及通过其边界进行水交换的信息。这种方法是由于大多数这些研究使用脉冲技术和相对较低的梯度，这阻止了实现高值。因此，不可能记录来自质子群体的信号，这些质子群体具有非常低的体相或表观自扩散系数，例如细胞细胞器。这项工作的目的是使用随时间变化的扩散系数方法获取低于细胞大小的水平（即细胞结构中）的水的几何形状和动态信息。细胞系统的模型由面包酵母（）制成，因为它是常见的且特征良好的。我们使用具有非常高且恒定梯度（~24 T/m）的紧凑型核磁共振（NMR）-Magritek 移动通用表面探测器（MoUSE）设备测量了新鲜酵母的特性，这使我们即使在非常短的扩散时间（0.2-40 ms）也能获得足够的激发回波衰减，并且能够应用非常短的扩散编码时间。在这项工作中，由于非常大的扩散加权（-值），可以将信号分成三个分量，其中一个仅与细胞结构相关。随时间变化的扩散系数分析使我们能够确定细胞外液、细胞质和细胞器的自扩散系数，以及隔室的大小。基于随机游走模拟和使用理论尺寸或摩尔分数计算的水池近似体积，确定了对每个隔室有贡献的细胞器。不同的细胞结构信息包含在不同的隔室中，具体取决于扩散状态，这是应用极高梯度的研究所固有的。
