Junichi Hata1,2,3, Takayuki Obata4, Yasuhiko Tachibana4, Yawara Haga1, Mai Mizumura1, Daisuke Nakashima2, Yasushi Sera2, Masaya Nakamura2, and Hideyuki Okano1,2
1Center for Brain Science, RIKEN, Wako, Japan, 2Keio University, Tokyo, Japan, 3Central Institute for Experimental Animals, Kanagawa, Japan, 4National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
Synopsis
We
focused on aquaporin 4 in skeletal muscle and attempted to visualize its
function using time-dependent diffusion magnetic resonance imaging (MRI). In
addition, the validity of the muscle cell type characteristics was evaluated by
immunostaining. The diffusion time was adjusted with the PG-STE method using a 9.4-T
MRI scanner. Diffusivity associated with a difference in the diffusion time was
found to differ depending on the skeletal muscle type. Thus, it was possible to
visualize the water molecule exchange rate of skeletal muscle cell membranes.
Introduction
Aquaporin (AQP) is a protein
expressed on the cell membrane, and it plays a specific role in water molecule permeability(1).
AQP4 is strongly expressed in the fibrous membranes
of glycolytic fast muscle fibers (type 2a) and
oxidized-thawed fast muscle fibers (type 2b), and it promotes water molecule inflow into cells(2).
However, there are very few research reports on AQP4. Diffusion-weighted magnetic resonance imaging (dMRI) may be able to provide functional measurements for
AQP4. Macroscopic diffusion metrics obtained with dMRI(3)
are sensitive to nominally invisible micron-level sample architecture owing to the diffusion length, i.e., the rms molecular displacement L(t) = (δx2(t))1/2, providing the mesoscopic length scale. The
dynamical exponent associated
with the time dependence of the diffusion
coefficient can distinguish mesoscopic structural complexity.Methods
The measurement objects were the lower
legs of mice (C57BL/6, 12 weeks, n = 6) and phantoms with known pore diameters
(6, 25, 50, and 100 µm; Hamamatsu Photonics K.K., Japan). The imaging range was
the area around the greatest diameter of the lower leg. MRI was performed using
a 9.4-T MRI scanner (BioSpec 94/30; Bruker
BioSpin, Ettlingen, Germany) and a cryogenic four-channel surface probe (Bruker BioSpin). We used the pulsed gradient stimulated-echo pulse
sequence. The imaging parameters were as follows: repetition time/echo time, 4,000/12.6 ms; Δ/δ, 101.2–1001.2/3.6 ms (six steps); output b-values, 1,000 and 2,000 s/mm2; field of view, 100 × 100 µm2; pixel resolution, 300 × 300 µm; slice thickness, 1 mm; motion probing gradient moment, six axes. To
determine the anatomical locations of the skeletal muscles, fast spin-echo T2-weighted
imaging was performed. Mrtrix3 open-source software (http://www.mrtrix.org/) was used for diffusion tensor analysis. For water permeability evaluation(4,5), linear function
f(x) = b / (x^a) + c was applied to
the acquisition mean values at each diffusion time to determine the best-fitting curves(6).
For histological/immunological
analysis, the lower legs of the mice were stained with several stains (BA-D5, SC-71, BF-F3, and AQP4) to observe muscle cell type, using the frozen-section method.
This study was approved by the local animal experiment committee and was conducted in accordance with the Guidelines for Conducting
Animal Experiments of the Riken Center for Brain Science.Results
The AQP4 expression on immunostaining differed among the muscle types. It was only expressed in fast muscles (types 2a and 2b) and was not expressed in slow muscles (type 1) (Figure 1).
On MRI under several conditions, the apparent diffusion coefficient attenuated exponentially with
prolongation of the diffusion time. Signal change was not observed in the axial direction, but in the radial direction, the characteristics of the attenuation were captured. In addition, the characteristics differed between the
tibialis anterior muscle (TA) and soleus muscle (SOL) (Figures 2 and 4). With the capillary phantom, which is a perfectly restricted structure, the characteristics of ADC attenuation associated with cell diameter differences were obtained (Figures 3 and 4).Discussion
In animal experiments, the relation between
each muscle group and AQP4 expression could
be confirmed with immunostaining. Additionally, the diffusion time-dependent dMRI
measurement showed a different transitional ADC change depending on the diffusion time among skeletal muscle groups. In the
comparative experiment, on measuring the phantom
with pore sizes equivalent to those of the skeletal
muscle(3) (i.e., 15–50 µm) and no water
exchange at the pore wall, we identified the functional
characteristics of the closed cell system model. With regard to the transition of the diffusion coefficient owing to the difference in the diffusion time, the gastrocnemius muscle and TA had strong AQP4 expression, while the SOL had abundant type 1 fibers with no AQP4 expression, resulting in low diffusion time dependence and gradually causing a relatively low diffusion coefficient. In numerical analysis by curve fitting, the coefficients assumed to
represent the water molecule transfer exchange amount showed the same tendency
inside and outside the TA. The cell diameter was largely different between type 2a and 2b fibers, although
they represented the same type 2 fiber(7). However, there was no difference in Figure 5, and it was suggested that the AQP4 function
difference could be measured. Moreover, it was
suggested that this method could dynamically assess mesoscopic information with or without skeletal muscle
AQP4 function (i.e., cell membrane water permeability).Conclusion
We obtained images reflecting the
difference in the function of cell membrane permeability of water
molecules associated with AQP4, independent of
muscle cell size. Our approach might help
in the identification of novel medical findings
after its development for the assessment of many skeletal muscle
diseases and the evaluation of motor function.Acknowledgements
This research is partially supported by the program for Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) from Japan Agency for Medical Research and development, AMEDReferences
-
Agre P. et
al. Science. 1992 Apr 17;256(5055):385-7.
- Schiaffino
S. et al. Physiol Rev. 2011 Oct;91(4):1447-531.
- Callaghan
PT, 1991, Clarendon, Oxford
- Novikov
DS. et al. Proc Natl Acad Sci U S A. 2014 Apr 8;111(14):5088-93.
- Takayuki
O, et al. ISMRM 2016 Volume: 24 (No.2010)
- Nilsson M.
et al. Magn Reson Med. 2013 Jun;69(6):1573-81.
- Junichi H,
et al. ISMRM 2017 Volume: 25 (No.4998)