Magnetic resonance measurements of cellular and sub-cellular membrane structures in live and fixed neural tissue

Abstract

We develop magnetic resonance (MR) methods for real-time measurement of tissue microstructure and membrane permeability of live and fixed excised neonatal mouse spinal cords. Diffusion and exchange MR measurements are performed using the strong static gradient produced by a single-sided permanent magnet. Using tissue delipidation methods, we show that water diffusion is restricted solely by lipid membranes. Most of the diffusion signal can be assigned to water in tissue which is far from membranes. The remaining 25% can be assigned to water restricted on length scales of roughly a micron or less, near or within membrane structures at the cellular, organelle, and vesicle levels. Diffusion exchange spectroscopy measures water exchanging between membrane structures and free environments at 100 s-1.

Attempts at the Characterization of In-Cell Biophysical Processes Non-Invasively—Quantitative NMR Diffusometry of a Model Cellular System

“…As shown in the Results section, three compartments cannot be characterized in the full range of b -values by using model 1, because the observations show that the 2% drop of signal coming from an organelle with a molar fraction of several percent is already visible in the experiment with high SNR (in this work—128 scans). The intercept values in model 1 were equal to 10% of the total signal, which is a significant amount considering the capabilities of a NMR-MoUSE system to detect very slow ( D ~10 −15 m 2 s −1 ), low-populated components (even 1% of the total population according to Williamson [ 41 ]). Model 2, which delivers smooth TDDC, but biased parameters, can be applied only for the determination of approximate values of parameters.…”

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

“…7). Applying these concepts to our findings, we suggest the following partial biological interpretation: SC 1 can be assigned to "immobile" water, e.g., trapped in glial cells or water bound to membranes (Stanisz et al, 1997;Alexander et al, 2010;Williamson et al, 2019); SC 5 has the diffusive characteristics of the so-called "stick" (Kroenke et al, 2004), which is most commonly assigned to intra-axonal water; and SC 4 can be thought to originate from extra-axonal water that reside between the aligned spinal cord fibers. These components have been previously formalized within the "standard model" .…”

“…There may be two reasons for non-Gaussianity in biological tissue: (1) multiple water pools that can each be Gaussian, (2) and the restricted diffusion non-Gaussianity, which leads to time-dependency (Fieremans et al, 2016;Lee et al, 2018). Nevertheless, although it is well known that Gaussian diffusion is not universally applicable to biological tissue, this method provided a phenomenological description of the range of water mobilities in such systems (Pfeuffer et al, 1999;Topgaard and Söderman, 2002;Yablonskiy et al, 2003;Ronen et al, 2006;Zong et al, 2017;Kim et al, 2017;Slator et al, 2019;Benjamini and Basser, 2019;Williamson et al, 2019). This approach inspired the tensor distribution model (Tuch et al, 2002), which is a generalization of the 1D multiexponential distribution.…”

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

“…7 ). Applying these concepts to our findings, we suggest the following partial biological interpretation: SC 1 can be assigned to “immobile” water, e.g., trapped in glial cells or water bound to membranes ( Alexander et al, 2010 ; Palombo et al, 2019 ; Stanisz et al, 1997 ; Williamson et al, 2019 ); SC 5 has the diffusive characteristics of the so-called “stick” ( Kroenke et al, 2004 ; Panagiotaki et al, 2012 ), which is most commonly assigned to intra-axonal water; and SC 4 can be thought to originate from extra-axonal water that reside between the aligned spinal cord fibers. These components have been previously formalized within the “standard model” ( Novikov et al, 2018 ).…”

“…There may be two reasons for non-Gaussianity in biological tissue: (1) multiple water pools that can each be Gaussian, (2) and the restricted diffusion non-Gaussianity, which leads to time-dependency ( Fieremans et al, 2016 ; Lee et al, 2018 ). Nevertheless, although it is well known that Gaussian diffusion is not universally applicable to biological tissue, this method provided a phenomenological description of the range of water mobilities in such systems ( Benjamini and Basser, 2019 ; Benjamini et al, 2017 ; Kim et al, 2017 ; Pfeuffer et al, 1999 ; Ronen et al, 2006 ; Slator et al, 2019 ; Topgaard and Söderman, 2002 ; Williamson et al, 2019 ; Yablonskiy et al, 2003 ; Zong et al, 2017 ). This approach inspired the tensor distribution model ( Tuch et al, 2002 ), which is a generalization of the 1D multiexponential distribution.…”