Abstract
With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.
Highlights
Since Nature published the initial sequence of the (Mouse Genome Sequencing Consortium et al, 2002), there has been a marked increase in the number of transgenic and gene-targeted mice that have been engineered to deepen our understanding of the function of genes in human biology
The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements are representative results from practical scan times achievable for the in vivo and ex vivo imaging protocols (Table 2). This was 1.5 h in vivo, which permitted the acquisition of other complementary functional scans within a feasible in vivo imaging time (Holmes et al, 2016), and 12 h to image 3 ex vivo brains simultaneously (4 h per ex vivo specimen), which maximized the utility of the Magnetic resonance imaging (MRI) scanner by imaging overnight
We observed an increase in SNR of the in vivo images compared to the ex vivo images in 7 of the 9 regions investigated: the caudate putamen (55%), corpus callosum (271%), cortex (42%), hippocampus (79%), olfactory bulb (36%), midbrain (61%), and thalamus (59%)
Summary
Since Nature published the initial sequence of the (Mouse Genome Sequencing Consortium et al, 2002), there has been a marked increase in the number of transgenic and gene-targeted mice that have been engineered to deepen our understanding of the function of genes in human biology. It has been estimated that to create a knock-out mouse for each of the 20,000 genes in the mouse genome, over 7 million animals will be required in order to fully characterize the subsequent loss of gene activity (Qiu, 2006). This figure does not include knock-in and transgenic mice, all of which will require characterization in order to fully comprehend gene function. Phenotyping, at the macroscopic and microscopic level, is traditionally carried out using histological methods, which are useful for validating hypotheses and uncovering unexpected biochemical changes that accompany altered gene function. Techniques for structural phenotyping have moved beyond the use of histology to embrace whole-organ or organism, high resolution imaging methods (Turnbull and Mori, 2007; Lau et al, 2008; Carroll et al, 2011; Cleary et al, 2011a,b; Lerch et al, 2011a; Yu et al, 2011; Badhwar et al, 2013; Ellegood et al, 2013; Norris et al.)
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