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Sutherland, B. A.

Publications and source records attributed to Sutherland, B. A..

2 recordsLinked to original sources

Microglia associations with brain pericytes and the vasculature are reduced in Alzheimer's disease

Cerebral blood flow is important for the maintenance of brain function and its dysregulation has been implicated in Alzheimers disease (AD). Subpopulations of microglia have well-characterised associations with the vasculature in the central nervous system but the precise relationship between microglia and cells which exist on the vasculature is not yet clear. In this study we explored the relationship between microglia and pericytes, a vessel-resident cell type that has a major role in the regulation of cerebral blood flow and maintenance of the blood brain barrier. Using fixed tissue sections and in vivo live imaging, we discovered a subset of microglia that closely associated with pericytes, termed PEricyte-associated Microglia (PEM). PEM are present throughout all regions of the brain and spinal cord in NG2DsRed x CX3CR1+/GFP mice, and in the human frontal cortex. They reside adjacent to pericytes at all levels of the capillary tree and can maintain their position for at least 28 days. PEM associate with pericytes lacking astroglial endfeet coverage but are segregated from pericytes by capillary basement membranes and capillary vessel width is similarly increased beneath pericytes with or without an associated PEM. Deletion of the microglia fractalkine receptor (CX3CR1) did not disrupt the association between pericytes and PEM, suggesting the association is not reliant on fractalkine signalling. Finally, we found that the proportion of microglia that are capillary-associated and PEM declines in the superior frontal gyrus (SFG) in AD, which is exacerbated by the APOE {varepsilon}3/{varepsilon}4 genotype. In summary, we identify and characterise a subpopulation of microglia that specifically associate with pericytes and find this population is reduced in the SFG in AD. This reduction may be a novel mechanism contributing to vascular dysfunction in diseases such as AD.

neuroscience↗

An automated approach to improve the speed and accuracy of pericyte and microglia quantification in whole mouse brain sections

Whole slide scanning technology has enabled the generation of high-resolution images of complete tissue sections. However, commonly used analysis software is often unable to handle the large data files produced. Here we present a method using the open-source software QuPath to detect, classify and quantify fluorescently-labelled cells (microglia and pericytes) in whole coronal brain tissue sections. Whole brain sections from both male and female NG2DsRed x CX3CR1+/GFP mice were analysed. Small regions of interest were selected and manual counts were compared to counts generated from an automated approach, across a range of detection parameters. The optimal parameters for detecting cells and classifying them as microglia or pericytes in each brain region were determined and applied to annotations corresponding to the entire cortex, hippocampus, thalamus and hypothalamus in each section. 3.71% of all detected cells were classified as pericytes, however this proportion was significantly higher in the thalamus (6.39%) than in other regions. In contrast, microglia (4.45% of total cells) were more abundant in the cortex (5.54%). No differences were detected between male and female mice. In conclusion, QuPath offers a user-friendly, rapid and accurate solution to whole-slide image analysis which could lead to important new discoveries in both health and disease. Significance StatementRapid and accurate quantification of cell numbers and distributions from whole tissue sections represents a difficult challenge in biomedical research. Slide scanning microscopes generate high-resolution images of complete tissue sections but most common image analysis software packages struggle to cope with the large data files they produce. We provide a method for rapidly and accurately quantifying pericyte and microglia cell numbers in whole brain tissue sections using QuPath, a new open-source software designed specifically to overcome this challenging roadblock.

neuroscience↗