The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in Nrxn2 deletion mice

Abstract

Background Of the many genetic mutations known to increase the risk of autism spectrum disorder, a large proportion cluster upon synaptic proteins. One such family of presynaptic proteins are the neurexins (NRXN), and recent genetic and mouse evidence has suggested a causative role for NRXN2 in generating altered social behaviours. Autism has been conceptualised as a disorder of atypical connectivity, yet how single-gene mutations affect such connectivity remains under-explored. To attempt to address this, we have developed a quantitative analysis of microstructure and structural connectivity leveraging diffusion tensor MRI (DTI) with high-resolution 3D imaging in optically cleared (CLARITY) brain tissue in the same mouse, applied here to the Nrxn2α knockout (KO) model. Methods Fixed brains of Nrxn2α KO mice underwent DTI using 9.4 T MRI, and diffusion properties of socially relevant brain regions were quantified. The same tissue was then subjected to CLARITY to immunolabel axons and cell bodies, which were also quantified. Results DTI revealed increases in fractional anisotropy in the amygdala (including the basolateral nuclei), the anterior cingulate cortex, the orbitofrontal cortex and the hippocampus. Axial diffusivity of the anterior cingulate cortex and orbitofrontal cortex was significantly increased in Nrxn2α KO mice, as were tracts between the amygdala and the orbitofrontal cortex. Using CLARITY, we find significantly altered axonal orientation in the amygdala, orbitofrontal cortex and the anterior cingulate cortex, which was unrelated to cell density. Conclusions Our findings demonstrate that deleting a single neurexin gene ( Nrxn2α ) induces atypical structural connectivity within socially relevant brain regions. More generally, our combined within-subject DTI and CLARITY approach presents a new, more sensitive method of revealing hitherto undetectable differences in the autistic brain. Electronic supplementary material The online version of this article (10.1186/s13229-019-0261-9) contains supplementary material, which is available to authorized users.

Insoluble Aβ overexpression in an App knock-in mouse model alters microstructure and gamma oscillations in the prefrontal cortex, affecting anxiety-related behaviours

“…Eight wild-type [four male (9.02±0.63 months), four female (9.43±0.30 months)] and eight App NL-G-F homozygotes [four male (8.88±0.22 months), four female (9.89±0.21 months)] were used in MRI. Image acquisition has been described elsewhere (Pervolaraki et al, 2017, 2019). MRI was performed on a vertical 9.4 Tesla spectrometer (Bruker AVANCE II NMR, Ettlingen, Germany).…”

“…Regions were extracted by manually segmenting OFC, ACC, hippocampal and whole-amygdalar regions using a mouse brain atlas (Franklin and Paxinos, 2008). We chose to focus on the aforementioned brain regions as these have been linked to social behaviour (Pervolaraki et al, 2019). Additionally, the hippocampus (Bannerman et al, 2004; McHugh et al, 2004), amygdala (Davis, 1992; Davis et al, 1994) and prefrontal cortical regions (including the ACC) (Davidson, 2002; Etkin et al, 2011) have all been linked to anxiety.…”

“…Extraction of FA, MD, AxD and RD was performed within selected segmented brain regions, with three 100 µm sections (one anterior and one posterior to the segmented section) extracted. A full atlas-based description of the segmentation can be found in Pervolaraki et al (2019).…”

Mapping the living mouse brain neural architecture: strain specific patterns of brain structural and functional connectivity

“…In the recent years, huge effort has been dedicated for the characterization of the mouse brain connectome -at micro and mesoscale (Bardella et al, 2016;Grandjean et al, 2017;Grange, 2018;Ingalhalikar et al, 2014;Knox et al, 2018;Oh et al, 2014;Pervolaraki et al, 2019), as this species remains the principal animal model used in neuroscience research. Most of these studies were carried-out in the C57BL/6 strain, which remains the primary "genetic background" for modelling of human disease.…”

Optimizing Diffusion Imaging Protocols for Structural Connectomics in Mouse Models of Neurological Conditions

“…While studies on diffusion imaging in the human brain have previously addressed the tradeoffs associated with spatial vs. angular resolution, the mouse brain provides insight into white matter connectivity at a vastly different scale and, thus, deserves special attention. We need to compare 2-mm linear dimension voxel sizes in humans (corresponding to 8-mm 3 voxel volumes), vs. 0.2-0.043-mm linear dimension voxel sizes (corresponding to ∼8 × 10 −2 -8 × 10 −5 -mm 3 voxel volumes) required to distinguish similar levels of anatomical detail in mouse brains [6][7][8][9][10][11]. This increased resolution enables the observation of brain architecture at the level of cellular layers, which, therefore, can help us gain insight into the mechanistic drivers behind the etiology and progression of disease, using animal models where axonal dimensions are relatively similar to humans [12,13].…”