Tracing propionic acid infused to rat brain via deuterium tagging—further development of a novel rodent model of autism spectrum disorders

Abstract

MacFabe et al. have proposed a novel rat model of autism spectrum disorders (ASDs) with intraventricular infusions of propionic acid (PPA), a gut bacterial metabolic end product and common food preservative, which produces reversible behavioral and electrographic effects coupled with increased oxidative stress and innate neuroinflammatory changes consistent with findings in ASD patients. PPA appears to be a potential environmental trigger linking the disparate behavioral, dietary, gut, metabolic and immune factors implicated in ASD. These previous studies used traditional immunohistochemical and biochemical techniques to examine increased oxidative stress and visualize neurons, reactive astrocytes, and activated microglia in hippocampus and adjacent external capsule white matter from coronally sectioned rat brain. As PPA is also an important metabolic intermediate of fatty acid beta oxidation, we have repeated the experiments with deuterium-tagged PPA (DPPA) and employed ToF-SIMS to trace the deuterium decoration of comparable brain regions ipsilateral to the DPPA infusion. In the present case of revealing DPPA-induced changes in brain regions, ToF-SIMS imaging of deuterium confirms the effectiveness of the methodology and the imaging results support the PPA-triggered ASD rodent model.

Subcellular features revealed on unfixed rat brain sections by phase imaging

“…Coronal sections of dorsal hippocampal formation, adjacent neocortex and external capsule white matter were cut from the OCT-embedded brains in a cryostat operated at À20 C and were placed on glass slides. [18][19][20][21][22][23] The thickness of the rat sections was 5 mm. Fig.…”

“…Details about ToF-SIMS imaging of sectioned rat brains are published elsewhere. 18,20 The dynamic force mode of a Park Systems XE-100 AFM was used in this study. In this mode, a cantilever with a nominal spring constant of 40 N m À1 and a resonant frequency of 300 kHz (NSC15, Mikro Masch) was vibrated and its reduced amplitude A (e.g., 70% of A 0, the amplitude in free space, where there are no tip-sample interactions) was used as the feedback parameter to image the surface morphology.…”

“…14,17 There is a need to develop novel brain imaging techniques to complement traditional immunohistochemical and biochemical methods (using optical and electron microscopes) to localize multiple lipids and other biomolecules in clinical and basic neuroscience. Further to this, we are exploring the use of AFM coupled with time-of-flight secondary ion mass spectrometry (ToF-SIMS), [18][19][20] with the above traditional techniques to examine neuro-inflammatory, oxidative stress and altered lipid profiles from tissue samples in a rodent model of autism spectrum disorders, [21][22][23] where emerging evidence suggests autism as a systemic disorder of lipid metabolism resulting in altered membrane fluidity. [24][25][26][27] We have briefly reported the striking contrast observed in phase images, which reveals subcellular features on unfixed rat brain sections, reflecting totally different mechanical properties between the domains rich in fatty acids and the dried cytoplasm consisting of salts and proteins.…”

ToF-SIMS of tissues: “Lessons learned” from mice and women

“…Other ToF-SIMS studies have also used this approach of using large area scans for studying other tissues. 15,[45][46][47] A comparison of the ToF-SIMS stitched image to an H&E stained serial tissue slice (nearby slice from same tissue block) shows that some histologic features can be correlated between the two images. As shown in Fig.…”

Automated correlation and classification of secondary ion mass spectrometry images using a k-means cluster method

“…These secondary species are analyzed by mass-tocharge ratio, generally giving chemical information about the top few nanometers of the surface in 2D and 3D. Recent SIMS developments in the last year alone have led to the generation of multi-component chemical image sets from polymeric materials, 1-4 metals, 5 geological phenomena, 6 biological cells and tissue, [7][8][9][10][11][12][13][14][15][16][17][18][19][20] and biomedical sciences. [21][22][23] Time-of-flight (ToF)-SIMS imaging generates a hyperspectral dataset, where detected secondary ion counts are recorded versus mass-to-charge (m/z) in pixel-by-pixel images.…”