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High Resolution Dissection of Reactive Glial Nets in Alzheimer's Disease.

Bouvier DS, Jones EV, Quesseveur G, Davoli MA, A Ferreira T, Quirion R, Mechawar N, Murai KK - Sci Rep (2016)

Bottom Line: Applying the method to AD samples, we expose complex features of microglial cells and astrocytes in the disease.Through this methodology, we show that these cells form specialized 3D structures in AD that we refer to as reactive glial nets (RGNs).The method provided here will help reveal novel features of the healthy and diseased human brain, and aid experimental design in translational brain research.

View Article: PubMed Central - PubMed

Affiliation: Centre for Research in Neuroscience, Department of Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada.

ABSTRACT
Fixed human brain samples in tissue repositories hold great potential for unlocking complexities of the brain and its alteration with disease. However, current methodology for simultaneously resolving complex three-dimensional (3D) cellular anatomy and organization, as well as, intricate details of human brain cells in tissue has been limited due to weak labeling characteristics of the tissue and high background levels. To expose the potential of these samples, we developed a method to overcome these major limitations. This approach offers an unprecedented view of cytoarchitecture and subcellular detail of human brain cells, from cellular networks to individual synapses. Applying the method to AD samples, we expose complex features of microglial cells and astrocytes in the disease. Through this methodology, we show that these cells form specialized 3D structures in AD that we refer to as reactive glial nets (RGNs). RGNs are areas of concentrated neuronal injury, inflammation, and tauopathy and display unique features around β-amyloid plaque types. RGNs have conserved properties in an AD mouse model and display a developmental pattern coinciding with the progressive accumulation of neuropathology. The method provided here will help reveal novel features of the healthy and diseased human brain, and aid experimental design in translational brain research.

No MeSH data available.


Related in: MedlinePlus

Exposing macro- and microscopic AD pathology in post-mortem brain samples.(a) Maximum projection of a vertical column of cortical tissue (5.1 mm X 0.468 mm and 40 μm thick) from an AD patient brain samples (female, 85 years old) and labeled with an AT8 antibody (Phospho-PHF-tau pSer202+Thr205) and Thiazine-red (TR) that reveal Aβ plaques, PHF, and NFTs. (b,c) Individual maximum projections of image fields from panel (a). (d) Maximum projection showing a 4.6 mm2 (x: 2.35 mm, y: 1.95 mm) of temporal cortex from an AD sample (male, 87 years old) with a 30 μm imaging depth and labeled for Iba1 (microglia; magenta), GFAP (astrocytes; green), and Thiazine-Red (plaques, cyan). TR staining reveals the presence of subgroups of plaques/aggregates. The dense-core Aβ plaques (C, dashed white hexagons) are the most numerous while larger fibrillar amyloid plaques (F, dashed yellow squares) are found in older patients. PHF aggregates are also frequently observed (P, dashed orange triangles). Iba1+ cell clusters are detected around dense-core and fibrillar plaques but are absent around PHF aggregates. Coronas of reactive astrocytes are observed around the 3 types of plaques/aggregates. (e,f) General distribution of Iba1+ microglia in control and AD brain tissue (1 mm2). Topological density of Iba1-positive microglia before and after Voronoi segmentation, in which individual microglia territories are color-coded according to their surface area. The homogeneity of microglial cell distribution that we have measured in the healthy brain (left) is disrupted by the presence of plaques (right) in AD brain with individual microglial territories becoming smaller near plaques (darker areas) and larger in adjacent areas (lighter areas), suggest microglial cell aggregation near deposits and their depletion from adjacent areas. Scale bars: 200 µm (a) 20 µm (b,c).
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f2: Exposing macro- and microscopic AD pathology in post-mortem brain samples.(a) Maximum projection of a vertical column of cortical tissue (5.1 mm X 0.468 mm and 40 μm thick) from an AD patient brain samples (female, 85 years old) and labeled with an AT8 antibody (Phospho-PHF-tau pSer202+Thr205) and Thiazine-red (TR) that reveal Aβ plaques, PHF, and NFTs. (b,c) Individual maximum projections of image fields from panel (a). (d) Maximum projection showing a 4.6 mm2 (x: 2.35 mm, y: 1.95 mm) of temporal cortex from an AD sample (male, 87 years old) with a 30 μm imaging depth and labeled for Iba1 (microglia; magenta), GFAP (astrocytes; green), and Thiazine-Red (plaques, cyan). TR staining reveals the presence of subgroups of plaques/aggregates. The dense-core Aβ plaques (C, dashed white hexagons) are the most numerous while larger fibrillar amyloid plaques (F, dashed yellow squares) are found in older patients. PHF aggregates are also frequently observed (P, dashed orange triangles). Iba1+ cell clusters are detected around dense-core and fibrillar plaques but are absent around PHF aggregates. Coronas of reactive astrocytes are observed around the 3 types of plaques/aggregates. (e,f) General distribution of Iba1+ microglia in control and AD brain tissue (1 mm2). Topological density of Iba1-positive microglia before and after Voronoi segmentation, in which individual microglia territories are color-coded according to their surface area. The homogeneity of microglial cell distribution that we have measured in the healthy brain (left) is disrupted by the presence of plaques (right) in AD brain with individual microglial territories becoming smaller near plaques (darker areas) and larger in adjacent areas (lighter areas), suggest microglial cell aggregation near deposits and their depletion from adjacent areas. Scale bars: 200 µm (a) 20 µm (b,c).

Mentions: The anatomical distribution of Aβ plaques and neurofibrillary tangles (NFTs) through the course of AD has been characterized in human AD post-mortem samples two decades ago2223. Aβ plaques are commonly categorized according their morphology and the presence of surrounding abnormal neuronal structures24. Thus, Aβ plaques are commonly divided into two sub-groups, dense-core and diffuse plaques, with dense-core plaques commonly associated with surrounding dysmorphic glial cells and neurons/neurites24. However there is a need to update these classifications that were originally based upon traditional immunohistochemistry techniques that do not provide sufficient resolution to detect more subtle alterations in the spatial organisation of neuronal and glial cells in AD brain. Although the mechanisms underlying the neurodegenerative events in AD remain to be fully understood, the disease is recognized as a multifactorial disorder4. Aβ plaques, NFTs, glial reactivity, and inflammation are all signatures of the disease. However, exactly how these pathological features are spatially coordinated in the AD brain requires further investigation. With a cohort of AD samples (Table 1), we applied the labeling/imaging method to resolve cellular and subcellular changes in AD. We applied Thiazine Red (TR) labelling which is commonly used on post-mortem samples for diagnostic purposes25 to reliably mark dense-core Aβ plaques and tangles. Importantly, TR is also compatible with multi-antibody labeling procedures, penetrating deep into thick brain tissue (Suppl. Figs 1 and 2). While large 3D image landscapes showed the overall organization Aβ plaques, aggregates of paired-helical filaments (PHFs), and NFTs2324 (Fig. 2a), individual image stacks embedded within these landscapes unveiled the detailed 3D pathology of degenerating neurons (Fig. 2b,c). To understand microglial-astrocyte relationships with pathological hallmarks of AD, we labeled for Iba1+ microglia and GFAP+ astrocytes and performed 3D imaging of millimeter-size territories of frontal cortex. This revealed a striking arrangement of astrocytes and microglia near large Aβ deposits and arrays of PHFs (Fig. 2d). GFAP+ astrocytes densely populated areas of high Aβ plaque load and NFT density. Iba1+ microglia also showed an altered distribution, albeit in a different manner, than astrocytes. Maximum projections of image stacks enabled Voronoi tessellation and nearest-neighbor distance analysis of microglia, revealing their irregular distribution in AD with microglial aggregation near plaques and depletion in adjacent zones (Fig. 2e,f; Suppl. Fig. 3d,e).


High Resolution Dissection of Reactive Glial Nets in Alzheimer's Disease.

Bouvier DS, Jones EV, Quesseveur G, Davoli MA, A Ferreira T, Quirion R, Mechawar N, Murai KK - Sci Rep (2016)

Exposing macro- and microscopic AD pathology in post-mortem brain samples.(a) Maximum projection of a vertical column of cortical tissue (5.1 mm X 0.468 mm and 40 μm thick) from an AD patient brain samples (female, 85 years old) and labeled with an AT8 antibody (Phospho-PHF-tau pSer202+Thr205) and Thiazine-red (TR) that reveal Aβ plaques, PHF, and NFTs. (b,c) Individual maximum projections of image fields from panel (a). (d) Maximum projection showing a 4.6 mm2 (x: 2.35 mm, y: 1.95 mm) of temporal cortex from an AD sample (male, 87 years old) with a 30 μm imaging depth and labeled for Iba1 (microglia; magenta), GFAP (astrocytes; green), and Thiazine-Red (plaques, cyan). TR staining reveals the presence of subgroups of plaques/aggregates. The dense-core Aβ plaques (C, dashed white hexagons) are the most numerous while larger fibrillar amyloid plaques (F, dashed yellow squares) are found in older patients. PHF aggregates are also frequently observed (P, dashed orange triangles). Iba1+ cell clusters are detected around dense-core and fibrillar plaques but are absent around PHF aggregates. Coronas of reactive astrocytes are observed around the 3 types of plaques/aggregates. (e,f) General distribution of Iba1+ microglia in control and AD brain tissue (1 mm2). Topological density of Iba1-positive microglia before and after Voronoi segmentation, in which individual microglia territories are color-coded according to their surface area. The homogeneity of microglial cell distribution that we have measured in the healthy brain (left) is disrupted by the presence of plaques (right) in AD brain with individual microglial territories becoming smaller near plaques (darker areas) and larger in adjacent areas (lighter areas), suggest microglial cell aggregation near deposits and their depletion from adjacent areas. Scale bars: 200 µm (a) 20 µm (b,c).
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Related In: Results  -  Collection

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f2: Exposing macro- and microscopic AD pathology in post-mortem brain samples.(a) Maximum projection of a vertical column of cortical tissue (5.1 mm X 0.468 mm and 40 μm thick) from an AD patient brain samples (female, 85 years old) and labeled with an AT8 antibody (Phospho-PHF-tau pSer202+Thr205) and Thiazine-red (TR) that reveal Aβ plaques, PHF, and NFTs. (b,c) Individual maximum projections of image fields from panel (a). (d) Maximum projection showing a 4.6 mm2 (x: 2.35 mm, y: 1.95 mm) of temporal cortex from an AD sample (male, 87 years old) with a 30 μm imaging depth and labeled for Iba1 (microglia; magenta), GFAP (astrocytes; green), and Thiazine-Red (plaques, cyan). TR staining reveals the presence of subgroups of plaques/aggregates. The dense-core Aβ plaques (C, dashed white hexagons) are the most numerous while larger fibrillar amyloid plaques (F, dashed yellow squares) are found in older patients. PHF aggregates are also frequently observed (P, dashed orange triangles). Iba1+ cell clusters are detected around dense-core and fibrillar plaques but are absent around PHF aggregates. Coronas of reactive astrocytes are observed around the 3 types of plaques/aggregates. (e,f) General distribution of Iba1+ microglia in control and AD brain tissue (1 mm2). Topological density of Iba1-positive microglia before and after Voronoi segmentation, in which individual microglia territories are color-coded according to their surface area. The homogeneity of microglial cell distribution that we have measured in the healthy brain (left) is disrupted by the presence of plaques (right) in AD brain with individual microglial territories becoming smaller near plaques (darker areas) and larger in adjacent areas (lighter areas), suggest microglial cell aggregation near deposits and their depletion from adjacent areas. Scale bars: 200 µm (a) 20 µm (b,c).
Mentions: The anatomical distribution of Aβ plaques and neurofibrillary tangles (NFTs) through the course of AD has been characterized in human AD post-mortem samples two decades ago2223. Aβ plaques are commonly categorized according their morphology and the presence of surrounding abnormal neuronal structures24. Thus, Aβ plaques are commonly divided into two sub-groups, dense-core and diffuse plaques, with dense-core plaques commonly associated with surrounding dysmorphic glial cells and neurons/neurites24. However there is a need to update these classifications that were originally based upon traditional immunohistochemistry techniques that do not provide sufficient resolution to detect more subtle alterations in the spatial organisation of neuronal and glial cells in AD brain. Although the mechanisms underlying the neurodegenerative events in AD remain to be fully understood, the disease is recognized as a multifactorial disorder4. Aβ plaques, NFTs, glial reactivity, and inflammation are all signatures of the disease. However, exactly how these pathological features are spatially coordinated in the AD brain requires further investigation. With a cohort of AD samples (Table 1), we applied the labeling/imaging method to resolve cellular and subcellular changes in AD. We applied Thiazine Red (TR) labelling which is commonly used on post-mortem samples for diagnostic purposes25 to reliably mark dense-core Aβ plaques and tangles. Importantly, TR is also compatible with multi-antibody labeling procedures, penetrating deep into thick brain tissue (Suppl. Figs 1 and 2). While large 3D image landscapes showed the overall organization Aβ plaques, aggregates of paired-helical filaments (PHFs), and NFTs2324 (Fig. 2a), individual image stacks embedded within these landscapes unveiled the detailed 3D pathology of degenerating neurons (Fig. 2b,c). To understand microglial-astrocyte relationships with pathological hallmarks of AD, we labeled for Iba1+ microglia and GFAP+ astrocytes and performed 3D imaging of millimeter-size territories of frontal cortex. This revealed a striking arrangement of astrocytes and microglia near large Aβ deposits and arrays of PHFs (Fig. 2d). GFAP+ astrocytes densely populated areas of high Aβ plaque load and NFT density. Iba1+ microglia also showed an altered distribution, albeit in a different manner, than astrocytes. Maximum projections of image stacks enabled Voronoi tessellation and nearest-neighbor distance analysis of microglia, revealing their irregular distribution in AD with microglial aggregation near plaques and depletion in adjacent zones (Fig. 2e,f; Suppl. Fig. 3d,e).

Bottom Line: Applying the method to AD samples, we expose complex features of microglial cells and astrocytes in the disease.Through this methodology, we show that these cells form specialized 3D structures in AD that we refer to as reactive glial nets (RGNs).The method provided here will help reveal novel features of the healthy and diseased human brain, and aid experimental design in translational brain research.

View Article: PubMed Central - PubMed

Affiliation: Centre for Research in Neuroscience, Department of Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada.

ABSTRACT
Fixed human brain samples in tissue repositories hold great potential for unlocking complexities of the brain and its alteration with disease. However, current methodology for simultaneously resolving complex three-dimensional (3D) cellular anatomy and organization, as well as, intricate details of human brain cells in tissue has been limited due to weak labeling characteristics of the tissue and high background levels. To expose the potential of these samples, we developed a method to overcome these major limitations. This approach offers an unprecedented view of cytoarchitecture and subcellular detail of human brain cells, from cellular networks to individual synapses. Applying the method to AD samples, we expose complex features of microglial cells and astrocytes in the disease. Through this methodology, we show that these cells form specialized 3D structures in AD that we refer to as reactive glial nets (RGNs). RGNs are areas of concentrated neuronal injury, inflammation, and tauopathy and display unique features around β-amyloid plaque types. RGNs have conserved properties in an AD mouse model and display a developmental pattern coinciding with the progressive accumulation of neuropathology. The method provided here will help reveal novel features of the healthy and diseased human brain, and aid experimental design in translational brain research.

No MeSH data available.


Related in: MedlinePlus