Ying Liu1,2, Lei Wei1,2, and Xiaoyong Zhang1,2
1Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, 2Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
Synopsis
Shank3 plays an important role in the functioning of glutamatergic synapses. In this work, we
investigated whether Shank3 deficiency could
induce neuroimaging changes in a transgenic autism mouse model using structural MRI and
MRS at 11.7T. Our data showed that the neurochemical metabolites in medial prefrontal cortex (mPFC) are significantly changed in Shank3 deficiency models of heterozygous and homozygous genotypes, relative to wildtype controls.
However, the volume of mPFC does not
show significant alteration among three groups. We concluded that metabolic abnormalities
are closely related to different phenotypes of Shank3 deficiency in mice.
Introduction
The SH3
and multiple ankyrin repeat domains 3 (Shank3) is a synaptic scaffolding
protein, which interacts with various synaptic molecules and influence glutamatergic
metabolism in mammalian brain. Deletions of the Shank3 have been found associated
with neuropathology of autism spectrum disorder (ASD), which is a
neurodevelopmental disorder with phenotypic heterogeneity in its etiopathogenesis1–3 . Recent neuroimaging studies
have revealed the critical role of Shank3 in ASD development using structural
and functional magnetic resonance imaging (MRI) modalities4. Abnormalities
in neurotransmitters have also been hypothesized to underlie ASD symptoms in the human5,6, but it remains unclear whether these metabolic abnormalities
are associated with different genotypes of rodent Shank3 models of ASD. In the present work, using magnetic
resonance spectroscopy (MRS), a powerful noninvasive tool
for measurement of neurochemical information, we aimed to identify Shank3 deficiency ASD genotypes by measuring metabolic
levels in the medial
prefrontal cortex (mPFC) in mice at 11.7T.Materials and Methods
Animal model: All
experimental protocols were approved by the Animal Ethics Committee of Fudan
University. A total of 21 C57BL/6J Shank3 deficiency mice (male, 8 weeks
old) and 8 age-control wildtype (WT)
C57BL/6J mice were obtained from Slac Laboratory (Shanghai, China). Animals
were divided into three groups: n = 8 for WT, n = 11 for heterozygous (HET) and
n = 10 for homozygous (HOMO). To establish Shank3 deficiency rodent models, mice
were injected with the SAD_G-mCherry-RV virus in mouse brain with a Nanofil
syringe mounted on an UltraMicroPump UMP3 with a four channel Micro4 controller
(World Precision Instruments, FL, USA). MRI was performed 4 weeks after virus
injection.
Data Acquisition: MRI
experiments were performed at a 11.7T BioSpec 117/16 USR MRI system equipped
with a CryoProbe (Bruker BioSpin, Ettlingen, Germany). T2-weighted images of the whole brain
were acquired using a Rapid Acquisition with Relaxation Enhancement (RARE)
sequence with the following parameters: TR/TE, 4000/30 ms; RARE factor, 8;
spatial resolution, 80 × 80 × 400 μm3. 1H-MRS data was
acquired using a stimulated echo acquisition Mode (STEAM) sequence with the
following parameters: TR/TM/TE, 2000/10/3 ms; number of averages, 256; voxel
size, 2 × 2 × 1 mm3 located in the medial prefrontal cortex (mPFC).
An isoflurane dose, ranging from 1% to 1.5 %, was used for anesthesia in all
imaging runs.
Data
analysis: The T2-weighted images were used to generate the specific template and
the prior tissue probability maps. Then a voxel-based morphometry (VBM) method was used to measure the volume of brain regions based on a mouse atlas7. 1H-MRS spectra were analyzed using LCModel software
(Version 6.3-1L; http://s-provencher.com/pages/lcmodel.shtml). Only metabolites with Cramér–Rao bounds < 15% were
considered for statistical analysis. One-way ANOVA with a Fisher's Least
Significant Difference (LSD) post-hoc test was performed using SPSS 22.0 for
Windows (SPSS Inc., USA) with p<0.05 as the significance criterion. Results and Discussion
Figure 1 shows a voxel located in mPFC superimposed
on the T2-weighted images, a representative LCModel fit and a subtracted
residual, which reveal that the gamma-aminobutyric acid (GABA) peak at 2.28 ppm was resolved well. As
shown in Figure 2, compared with WT group, the glutamine (Gln) exhibits a significant increase in
both HET (p=0.019) and HOMO group (p=0.002); the glutamate (Glu) shows a significant increase only in HOMO
group (p=0.036), while the GABA signal does not show any significant difference between groups. We further
measured the balance of GABA/GLx and found significant decreases
of GABA /Gln ratio (p=0.007) , GABA/Glu ratio (p=0.046) and
GABA/Glx ratio (p=0.021) in HET group (Figure 3), which may reflect inhibition/excitation imbalance in cortex, or a disruption in synaptic mechanisms that contribute to
ASD psychopathology6,8. Moreover, relative to the HOMO and
WT group, the concentrations of myo-Inositol (Ins) and choline are significantly lower in HET group, p<0.05 and p<0.0001
respectively, indicating abnormalities in cellular membrane metabolism and
reduction in cell signaling in heterozygous mice6,9. To further investigate the
relationship between morphometric change and metabolic activities,
we measured the volume of mPFC using VBM. Our data show
that compared with the WT group, no
significant changes were observed in mPFC either in the HET or HOMO group (Figure 4).
Conclusion
With MRS, our data showed that neurochemical profile of mPFC is significantly changed in different phenotypes of SHANK3 deficiency ASD. Moreover, the heterozygous genotype shows significant abnormalities in excitation/inhibition
neurotransmitter cycle, as well as lower levels of Ins and tCho. However,
the volume of mPFC does not show significant alteration between different groups. We
concluded that metabolic abnormalities are closely related to different phenotypes
of SHANK3 deficiency in mice. Acknowledgements
This work was
supported by grants from the National Natural Science Foundation of China
(81873893), the key project of Shanghai Science & Technology (16JC1420402),
and Shanghai Municipal Science and Technology Major Project (2018SHZDZX01) and ZJlab. References
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