TREM2 expression is differentially associated with microglia and hematogenous monocyte/macrophages proximally and distally located to amyloid plaques

TREM2 expression is differentially associated with microglia and hematogenous monocyte/macrophages proximally and distally located to amyloid plaques | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article TREM2 expression is differentially associated with microglia and hematogenous monocyte/macrophages proximally and distally located to amyloid plaques Natalie Kozyrev, Fernando González Ibáñez, Chloe McKee, Marianela E. Traetta, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6222217/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Amyloid-β (Aβ) plaque deposition is a feature of Alzheimer’s disease. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates inflammatory responses by increasing phagocytic activity, and its expression is modulated by inflammation in the brain. One of the ligands for TREM2 is Aβ. TREM2 is highly expressed on myeloid cells, including microglia and peripheral tissue-resident macrophages. Both microglia and hematogenous macrophages interact directly with Aβ plaques. Using our 5XFAD lys -EGFP- ki transgenic mice, we studied the expression of TREM2 in plaques engaging microglia and infiltrating macrophages. We characterized the expression of TREM2 by measuring the protein level of TREM2 in the cortex at three different time points: 1.5, 3, 5, and 7 months of age. We observed a decrease in TREM2 levels in the cortex with disease progression. TREM2 levels were also lower in cells interacting with Aβ plaques compared to cells far from Aβ plaques. Finally, we performed an ultrastructural analysis of microglia and hematogenous macrophages interacting with plaques, which revealed more dystrophic mitochondria and phagocytosed material in hematogenous macrophages than in microglia. TREM2 Alzheimer’s disease Neurodegeneration Neuroinflammation Microglia Monocyte Macrophage Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights • Cortical TREM2 levels decrease with age • TREM2 is expressed by microglia and peripheral myeloid cells that interact with Aβ plaques • TREM2 is reduced in microglia and peripheral myeloid cells interacting with Aβ plaques • Aβ plaque-interacting microglia and peripheral myeloid cells show ultrastructural differences INTRODUCTION Alzheimer’s disease (AD) is a devastating age-related neurodegenerative disease characterized by the deposition of amyloid-β (Aβ) plaques and the presence of hyperphosphorylated tau tangles in neurons [ 1 , 2 ]. AD results in extensive neuronal and synaptic loss that coincides with progressive cognitive decline and memory deficits [ 3 – 5 ]. The accumulation of Aβ plaques in AD triggers the recruitment and accumulation of reactive microglial states at sites associated with Aβ pathology [ 6 , 7 ]. Microglia are innate immune cells of the brain derived from the embryonic yolk sac. In their surveillant state, they survey their microenvironment, maintain homeostasis, and perform various physiological functions [ 5 ]. In the presence of pathogens, injury, or ongoing neurodegeneration, such as AD pathology, danger-associated molecular patterns engage receptors on microglia, triggering the release of proinflammatory cytokines that transform microglia at the structural and functional levels [ 8 , 9 ]. In recent years, the term ‘disease-associated microglia’ or DAM has been applied to a specific state of microglia found proximal to areas of pathology, such as Aβ plaques, in the context of neurodegenerative diseases such as AD [ 10 , 11 ]. While DAMs engage in the phagocytosis of cellular debris, including dystrophic and dying/dead neurons, they can also actively promote inflammation, thus exacerbating cellular damage and neurotoxicity [ 10 , 12 , 13 ]. Ultrastructural studies in the context of AD pathology have identified an additional microglial state: dark microglia. These cells associate with Aβ plaques and dystrophic neurites, engulf fibrillar Aβ, and present various markers of cellular stress and metabolic alterations. [ 12 , 14 ]. Furthermore, these cells were recently shown to activate the integrated stress response and perform a detrimental role in AD pathology [ 15 ], but their temporal involvement remains to be further defined. Over the course of AD pathology, Aβ plaques and accompanying AD pathology, including chronic inflammation, cytotoxicity and neurodegeneration, persist and intensify despite the steady recruitment and accumulation of disease-associated microglial states, including DAMs and dark microglia. These findings suggest that with increasing exposure to inflammatory stimuli, these cells become unable to effectively engage in phagocytosis [ 16 ]. The inability to effectively phagocytose Aβ plaques and cellular debris may be caused by excessive debris already present inside the cells, particularly within their lysosomes, which may become enlarged, thereby reducing their capacity to degrade debris in their environment [ 16 – 19 ]. The mechanisms whereby disease-associated microglial states are rendered ineffective at phagocytosis are thought to involve dysfunctional Aβ interactions with receptor complexes expressed on microglia, including Aβ binding to triggering receptor expressed on myeloid cells 2 (TREM2) and its adaptor tyrosine kinase receptor binding protein (TyroBP) [ 20 ], leading to cell senescence [ 11 , 21 – 23 ]. This elicits proinflammatory responses recruiting other immune-sensing receptors, such as Toll-like receptor (TLR) 4 and TLR6, to trigger the release of additional proinflammatory cytokines into the extracellular space [ 24 , 25 ]. In turn, persistent proinflammatory signaling disrupts Aβ phagocytosis by downregulating microglial phagocytic receptors and enzymes [ 5 , 24 , 25 ]. Thus, microglia can be beneficial in the early stages of AD by engaging in phagocytosis and Aβ clearance. Eventually, owing to continued detrimental Aβ accumulation, microglia take on a more pathological role as they become exhausted and their functions are altered, which ultimately diminishes their ability to clear Aβ plaques. It is unknown how or when microglia shift from a neuroprotective phenotype to a neurotoxic phenotype and how Aβ triggers opposite responses from the same cell population. One possibility is that the cells that accumulate around Aβ plaques comprise not only diverse cell states but also cell types that share similar morphological characteristics. A recent study using single-cell RNA sequencing demonstrated that DAMs are composed of a mixture of two ontogenetically and functionally diverse cell populations. Both cell populations are found near Aβ plaques in AD pathology. However, one population is embryonically derived and appears to be neuroprotective, whereas the other population is derived from infiltrating monocytes that differentiate into hematogenous macrophages (hMφs) [ 26 ]. This finding is consistent with recent findings from our group, demonstrating the presence of both microglia/microglia-derived macrophages (mMφs) and hMφs aggregating around Aβ plaques [ 27 ]. Both DAM cell populations express TREM2, a cell surface transmembrane glycoprotein with a V-immunoglobulin extracellular domain and a cytosolic tail [ 28 ] that is highly expressed on myeloid cells, including microglia and peripheral tissue-resident macrophages [ 26 , 29 ]. TREM2 is beneficial in the early stages of AD but detrimental at later stages. Indeed, elevated TREM2 has been associated with increased susceptibility to late-onset AD [ 30 , 31 ]. TREM2 regulates inflammatory responses by increasing phagocytic activity [ 32 ], and its expression is modulated by inflammation in the brain. The presence and accumulation of Aβ plaques promote toxicity in the proximal extracellular space and drive increased TREM2 cell surface expression [ 33 ]. One of the ligands for TREM2 is Aβ, which is known to bind TREM2 and trigger downstream signaling [ 34 ]. The relationship between inflammation and TREM2 is complex, with in vitro and in vivo studies demonstrating conflicting results. In vitro , anti-inflammatory signaling increases TREM2 expression, whereas proinflammatory signaling decreases TREM2 expression [ 35 ]. In contrast, in vivo studies have shown increased TREM2 expression in transgenic mouse models of Aβ and tau pathology [ 36 ] and in patients with AD [ 37 ]. In the current study, our goal was threefold. First, we measured TREM2 expression within distinct immune cell populations, including microglia and mMφs, monocytes and hMφs, that aggregate around Aβ plaques to determine which cell populations express the most TREM2 and whether the pattern of TREM2 expression changes over time and with AD progression. We chose mice that present Aβ pathology at the ages of 5 and 7 months because we showed previously in our lys -EGFP- ki x 5XFAD F1 (L5F) transgenic mouse model that 5 months is the age that coincides with initial cognitive deficits in spatial learning and by 7 months the cognitive deficits and inflammatory responses in males and females was approximately equal [ 27 ]. Second, we compared the levels of TREM2 expression in cell populations localized proximally to Aβ plaques with those in cell populations located farther from Aβ plaques. The TREM2-positive cell populations were classified on the basis of phenotypic protein markers for microglia, monocytes, hMφs and ‘clusters’ composed of both microglia and hMφs, forming tightly interconnected groupings around Aβ plaques. Third, we established a TREM2 immunolabeling protocol compatible with electron microscopy (EM) to identify and provide insights into the cellular and subcellular features of TREM2-positive myeloid cells in association with Aβ plaques and dystrophic neurons. We also compared microglia and hMφs/monocytes at the ultrastructural level, quantifying their ultrastructural features, which are indicative of phagocytosis and cellular stress, and their interactions with the parenchyma. These experiments were performed via the F1 cross between the 5xFAD mouse model of AD pathology and the lys -EGFP- ki mouse model, enabling microglia and reactive mMφs to be distinguished from hMφs on the basis of specific expression of enhanced green fluorescence protein (EGFP) in mature granulo-myelomonoctic cells. RESULTS TREM2 protein quantification in the cerebral cortex Overall TREM2 protein levels were measured by via ELISA in homogenates from the cerebral cortex of L5F + and L5F - male mice at the ages of 1.5, 3, 5, and 7 months. In general, TREM2 protein levels decreased with increasing age. In L5F + male mice, significantly more TREM2 protein was detected in the cortex at the age of 1.5 months than at the age of 5 months (p < 0.0001; Fig. 1A, Supplementary Table 1) and 7 months (p < 0.0001; Fig. 1A, Supplementary Table 1). In addition, in L5F + male mice, there was significantly more TREM2 protein at age of 3 months than at 5 months (p = 0.002) and 7 months (p < 0.0001) (Fig. 1A, Supplementary Table 1). Similarly, in L5F - mice, there was significantly more TREM2 protein at age of 1.5 months than at 5 months (p = 0.009), 7 months (p = 0.014), at age of 3 months than at 5 months (p = 0.036) and 7 months (p = 0.05; Fig. 1A, Supplementary Table 1). Comparable data for L5F + and L5F - female mice can be found in Supplementary Fig. 1A and Supplementary Table 1. The decrease in TREM2 expression with age in our AD model is consistent with the reports of others, although this decrease is somewhat dependent on the mouse models studied [38,39]. TREM2 protein levels may decrease in the brain with disease progression, possibly due to movement from the brain to the cerebrospinal fluid and blood circulation during AD progression. How TREM2 expression responds to brain inflammation is controversial, as the in vitro and in vivo results differ [35]. Indeed, a recent study revealed increased soluble TREM2 in the plasma of patients with AD compared with healthy controls [40]. Percent area of Aβ plaques and TREM2 levels near Aβ plaques The percentage area of Aβ plaques in the cerebral cortex was significantly greater in L5F + males at the age of 7 months than in those at the age of 5 months (Fig. 1B, 3 p = 0.042; Supplementary Table 1). Similar data were obtained for L5F + females, as presented in Supplementary Table 1 and Supplementary Fig. 1B. There was a tendency toward increased TREM2 intensity in the area proximal to Aβ plaques in male mice, with greater intensity observed at the age of 7 months than at 5 months (Fig. 1C, p = 0.094; Table 1). However, the corresponding TREM2 intensity data in the area proximal to the Aβ plaques in L5F + females were significantly different, as presented in Supplementary Fig. 1C and Supplementary Table 1. The increased accumulation of Aβ plaques in older L5F + mice is consistent with our previous findings, reflecting the sex differences we previously reported in this mouse model [27], which represent an important hallmark of AD pathology[41]. Percent area of microglial and hematogenous myeloid cells in proximal and distal neighborhoods relative to Aβ plaques We examined the percentage area of cells known to accumulate near Aβ plaques in AD, including microglia/mMφs, monocytes, hMφs and clusters. We also analyzed the percent areas of the clusters. which were defined as a mixture of mMφ and hMφ, forming tightly interconnected networks in the vicinity of Aβ plaques. The purpose of these analyses was to measure the area occupied by each cell type in proximal and distal plaque neighborhoods. We identified microglia/mMφs as Iba1 + EGFP - , monocytes as Iba1 - EGFP + and hMφs as Iba1 + EGFP + . Clusters were defined as mixtures of mMφs and hMφs that formed tightly interconnected networks in the vicinity of Aβ plaques. The percentage area of microglia/mMφs appeared greater in proximal Aβ plaques than in distal neighborhoods at ages 5 and 7 months in L5F + male mice, but the difference was significant only at 5 months (Fig. 2, 3A, p = 0.039; Supplementary Table 1). This finding is consistent with other studies demonstrating that microglia and mMφs are attracted to areas of pathology and Aβ plaques and are among the first responders in the clearance of cellular debris [5]. In contrast, no significant differences in the percent area of microglia/mMφ were observed at the age of 7 months between the proximal and distal neighborhoods or between the ages of 5 months and 7 months within the proximal and distal neighborhoods in L5F + males. Data from L5F + females are presented, with the same trends shown in Supplementary Fig. 2 and Supplementary Fig. 3A and Supplementary Table 1. The percentage area of EGFP + Iba1 - monocytes in L5F + male mice was significantly greater at the age of 7 months than at the age of 5 months in both the proximal (p = 0.006) and distal (p = 0.004) neighborhoods (Fig. 2, 3B, Supplementary Table 1). Similar data for L5F + females are presented in Supplementary Table 1 and Supplementary Fig. 2 and 3B. Here, too, there was a significant increase in L5F + females in the proximal neighborhood in keeping with the expected sex differences that we observed in our model. Similarly, the percentage area of EGFP + Iba1 + hMφs in male L5F + mice was significantly greater at 7 months than at 5 months of age (p =0.021) 0.021) and distal (p = 0.003) neighborhoods (Fig. 2, 3C; Supplementary Table 1). This was observed only in the proximal neighborhoods in the corresponding L5F + female data (Supplementary Fig. 2 and Supplementary Fig. 3C, Supplementary Table 1). The greatest cortical area of monocytes and hMφs was in L5F + mice at older ages, suggesting that increasing inflammation and cytotoxicity in AD may trigger the infiltration of peripheral myeloid cells into the brain. Compared with those in the distal neighborhoods, the percentages of myeloid/microglia/mMφ cell clusters in the proximal neighborhoods were significantly greater in male L5F+ mice at the ages of 5 months (p < 0.0001) and 7 months (p = 0.0003; Fig. 2, 3D; Supplementary Table 1). Very similar data from female L5F + mice are presented in Supplementary Table 1 and Supplementary Fig. 2 and 3D. These data parallel the data for Iba1 + EGFP - microglia/mMφs shown in Fig. 3A, indicating that the area occupied by microglia/mMφs is greater than that occupied by EGFP + monocyte/hMφ cells, as shown when the scale range of the area for each cell type (Y-axis. Fig. 3A-C) is compared. Thus, although infiltrating monocytes and monocyte-derived hMφs contribute to the cellular inflammatory response in regions most proximal to Aβ plaques, they do not appear to play a dominant role. Immunoreactivity of TREM2 in cells from proximal and distal neighborhoods relative to Aβ plaques To link TREM2 expression with cellular morphology, we next measured the integrated optical density (IOD), which is a combination of the cellular area and signal intensity, in microglia/mMφ, monocytes, hMφs and clusters in the cortex of L5F + mice at the ages of 5 and 7 months. The purpose of the analysis was to determine the expression of TREM2 within each cell type and time points. The TREM2 IOD was greater in distal microglia/mMφ than in proximal microglia/mMφs in relation to Aβ plaques in L5F + males at the age of 5 months (Fig. 2, 3E, p = 0.016; Supplementary Table 1). The trend in the TREM2 IOD was similar at 7 months of age, but the difference was not significant. Comparable female data can be found in Supplementary Fig. 2, Supplementary Fig. 3E and Supplementary Table 1. The TREM2 IOD in monocytes increased with age and disease progression and was more abundant in distal neighborhoods than in proximal neighborhoods. In male L5F + mice, the TREM2 IOD in monocytes significantly increased from the ages of 5 months to 7 months in the proximal (Fig. 2, 3F, p = 0.008; Supplementary Table 1) and distal (Fig. 3F, p = 0.008; Supplementary Table 1) neighborhoods. Furthermore, TREM2 intensity was significantly greater in monocytes located distal than in those located proximal to Aβ plaques at both 5 months of age (Fig. 2, 3F, p = 0.021; Supplementary Table 1) and 7 months of age (Fig. 2, 3F, p = 0.021; Supplementary Table 1). Comparable data showing the TREM2 IOD in monocytes from L5F + females followed the same patterns of significant differences presented in Supplementary Fig. 2, Supplementary Fig. 3F and Supplementary Table 1. The TREM2 IOD in hMφs was significantly greater in distal neighborhoods than in proximal neighborhoods at the age of 7 months in L5F + males (p = 0.007; Fig. 2, 3G Supplementary Table 1). In addition, the TREM2 IOD in hMφs was greater at 7 months than at 5 months within the distal neighborhoods in L5F + males (p = 0.009; Fig. 2, 3G; Supplementary Table 1). Comparable data in L5F + females showing TREM2 intensity in hMφs can be viewed in Supplementary Fig. 2 and Supplementary Fig. 3G and Supplementary Table 1. The increased TREM2 expression in microglia/mMφs, monocytes and hMφs in distal plaques compared with that in proximal plaques suggests that chronic exposure to Aβ in a proinflammatory environment may reduce the expression of TREM2 in proximal cells, rendering them unable to perform phagocytosis effectively. A recent study demonstrated that exposure to inflammatory stimuli significantly reduced TREM2 expression in peripheral monocytes [40]. It is possible that inflammation, driven by exposure to high levels of Aβ, contributes to a reduction in cortical TREM2 in older L5F + mice with more advanced disease pathology. In contrast to TREM2 expression in individual cell populations, a greater TREM2 IOD was observed in proximal clusters than in distal clusters at the ages of 5 months (Fig. 2, 3H, p = 0.035; Supplementary Table 1) and 7 months (p = 0.05; Fig. 2, 3H; Supplementary Table 1) in L5F + males, but the differences were small and reached significance at only 5 months. Comparable data showing TREM2 intensity in clusters from female L5F + mice are presented in Supplementary Fig. 2, Supplementary Fig. 3H and Supplementary Table 1. Clusters, mostly located proximally to Aβ plaques, may represent a functional TREM2 population of DAMs actively engaged in the phagocytosis of Aβ plaques and cellular debris in the immediate areas surrounding plaques. Ultrastructural features of TREM2 + myeloid cells located near Aβ plaques We then characterized TREM2-expressing cells at the nanoscale via immunocytochemical EM to reveal their ultrastructural features and gain insights into their disease-associated states and roles. In the cingulate cortex of 7-month-old L5F + males, both TREM2 + and TREM2 - cells with myeloid ultrastructural features directly interact with Aβ plaques and dystrophic neurites (Fig. 4). The presence of TREM2 + and TREM2 - cells contacting dystrophic neurites provides evidence that different populations of macrophages coexist in AD mouse models. In TREM2+ cells, we detected an abundance of phagosomes and lysosomes, indicating their active role in phagocytosis., These ultrastructural features are similar to those of dark microglia. The TREM2 + cells further contained dystrophic mitochondria (Fig. 4), another feature observed in dark microglia [14], suggesting a state of cellular stress and metabolic transition from oxidative phosphorylation to glycolysis [42,43]. In addition, as in our previous investigations, APP-PS1 mice and 5xFAD mice presented the dark features of an electron-dense cytoplasm and nucleoplasm, accompanied by cellular stress markers [14]. Considering the small number of observed dark microglia, it was not possible to perform an analysis of TREM2 expression. Ultrastructural features of myeloid cells near Aβ plaques and dystrophic neurites Finally, we performed a quantitative ultrastructural analysis of EGFP + myeloid cells (hMφs and monocytes, excluding neutrophils on the basis of ultrastructural features) and EGFP - cells (microglia) from 7-month-old male L5F + mice to compare their ultrastructural features and interactions with parenchymal elements to provide additional insights into their disease-associated states and roles. Dark features were also examined. This analysis was performed in the cingulate cortex to examine myeloid cells in contact with Aβ plaques and/or dystrophic neurites. At the ultrastructural level, significant differences in terms of mitochondrial structural integrity, phagocytosis and digestion of membrane debris were detected between the EGFP+ myeloid cells and the EGFP- microglia/mMφs (Fig. 5). Compared with EGFP- myeloid cells, EGFP + myeloid cells presented a significantly greater percentage of altered mitochondria, i.e., dystrophic, holey, and electron-lucent mitochondria (Fig. 5A-C, Table 1; [EGFP + : 31.06 ± 5.31% vs EGFP - : 17.52 ± 3.29%, p = 0.0401]). PLEASE INSERT TABLE 1 NEAR THIS AREA OF TEXT-Altered mitochondria were identified by the deterioration of their double membrane, cristae, or presence of electron-lucent patches or holes within their interior. No significant differences were found between the cell populations in terms of their abundance of altered or elongated mitochondria (Table 1). These findings suggest that hMφs/monocytes may be more susceptible to metabolic dysfunction and cellular stress than microglia/mMφs are in L5F + mice. However, other well-defined ultrastructural markers of cellular stress, including ER and Golgi cisternae dilation [14,44], did not differ between cell populations (Table 1). Although the small number of dark microglia prevented quantitative analysis, these cells were not found to be EGFP + in these samples. In terms of phagocytosis and membrane debris digestion, EGFP + myeloid cells had significantly more unbound membrane inclusions located within their cytoplasm than EGFP - microglial/mMφ cells did (Fig. 5D-F) [EGFP + : 1.16 ± 0.25 vs EGFP - : 0.370 ± 0.121, p = 0.0100]. EGFP + myeloid cells and EGFP - microglia/mMφ did not differ significantly in their abundance of phagosomes containing membrane debris [EGFP + : 0.31 ± 0.12 vs EGFP - : 0.07 ± 0.051, p = 0.0976] (Table 1). Compared with those within unbound membrane inclusions, the membranes within phagosomes were circular and enclosed by a defined membrane (Figure 5D, E). Interestingly, when the total membrane load was investigated, including that of unbound membranes and membranes contained within phagosomes, EGFP + myeloid cells had significantly more total membrane inclusions than EGFP - microglia/mMφ did (Fig. 5D-G, Table 1 [EGFP + : 1.469 ± 0.280 vs EGFP - : 0.444 ± 0.123, p = 0.0027]). This finding suggests that in L5F + mice, EGFP + myeloid cells phagocytose more cellular materials than EGFP - microglia/mMφs do. Analysis of cell‒cell interactions also revealed that EGFP + cells were more likely to be in direct contact with other EGFP + myeloid cells (EGFP + 0.1875 ± 0.0833 vs EGFP - 0, p = 0.0434), thereby forming myeloid clusters (Fig. 5H, I). These results indicate that myeloid cells present ultrastructural differences from those of microglia when they are found in proximity to Aβ plaques and dystrophic neurites. DISCUSSION In the present study, we demonstrated that overall TREM2 protein levels decreased with age in the cerebral cortex of our lys -EGFP- ki x 5XFAD F1 transgenic mouse model. In addition, our detailed anatomical examination revealed that TREM2 expression in older mice was most abundant in Aβ-associated cell clusters comprising a mixture of intertwined resident reactive microglia/mMφ and hematogenous EGFP + myeloid cells proximal to Aβ plaques. TREM2 expression was highest overall for the cells observed within clusters contacting Aβ plaques as opposed to individual cells. Moreover, ultrastructural analysis confirmed that TREM2 + cells interact directly with Aβ plaques and dystrophic neurites. Similarly, TREM2 - cells were also found to be near Aβ plaques and dystrophic neurites. Myeloid cells expressing TREM2 presented markers of cellular stress and metabolic alterations. In addition, differences in these markers were quantified between microglia and peripheral myeloid cell populations. While dark microglia/myeloid cells were observed in these samples, as in previous studies conducted in APP-PS1 and 5xFAD mice, they were not found to be EGFP + . These cells are known to change in number with disease progression, which warrants further investigation. Microglia are the primary cells involved in Aβ clearance. APP may be a proinflammatory receptor on microglia that regulates their ability to acquire a proinflammatory phenotype in mouse models of AD pathology [ 45 ]. Microglial TLR4 signaling is altered in TgAPP/PS1 mice [ 46 ], and this change may contribute to Aβ accumulation in the brain. TREM2 signaling helps protect against AD pathology, and several TREM2 variants decrease the binding between TREM2 and its ligands, resulting in an increased association with increased AD risk [ 47 ]. TREM2 is essential for microglial phagocytic function and response to neurodegeneration cues [ 6 ]. The level of TREM2 expression is associated with the rate of microglial phagocytosis [ 48 ]. In vitro , when TREM2 expression is increased in bone marrow-derived myeloid precursor cells, the phagocytosis rate of apoptotic neurons, cellular debris and bacteria or bacterial products is also increased [ 49 ]. The loss of TREM2 in microglia/mMφs and other TREM2-expressing cells, such as peritoneal macrophages, can also result in a decreased rate of phagocytosis [ 50 – 52 ]. In vivo , TREM2-knockout mice exhibit reduced reactivity of microglia and other phagocytes [ 53 ]. In a multiple sclerosis mouse model, TREM2-transduced bone marrow-derived myeloid precursor cells further presented enhanced phagocytic activity [ 49 , 54 ]. A meta-analysis revealed that soluble TREM2 levels are elevated in the early stages of AD and attenuated in the subsequent dementia stage [ 55 ]. This finding is consistent with our data demonstrating that the overall level of TREM2 in the cortex decreases with age, with higher TREM2 levels in younger L5F + mice and a significant decrease in TREM2 in older mice. When TREM2 expression was examined in the context of being proximal or distal to Aβ plaques, an apparent discrepancy was found. TREM2 expression in Aβ-associated cell clusters was greater than that in individual microglial and hematogenous subsets in both the proximal and distal neighborhoods. Furthermore, TREM2 expression was greater in clusters proximal to plaques. Outside the clusters, TREM2 expression was greater in distal neighborhoods in microglia/mMφs, monocytes and hMφs. The reason for this apparent discrepancy may be that hMφs and mMφs respond to the binding of TREM2 with soluble Aβ ligands, which in turn increases TREM2 expression and activates TyroBP to stimulate phagocytosis and reduce inflammation. Higher levels of TREM2 appear to drive the aggregation of TREM2 + cells around Aβ plaques, possibly to prevent toxic levels of Aβ from accumulating near neurons, hence acting as a shield against Aβ neurotoxicity [ 56 , 57 ]. The lower expression of TREM2 in individual microglia/mMφs and hMφs proximal to Aβ plaques is consistent with recent in vitro findings that high levels of a proinflammatory mediator, lipopolysaccharides, drive the downregulation of TREM2 expression [ 40 ]. However, as we and others have shown, overall TREM2 brain levels decrease with age, yet Aβ deposition continues, driving increased inflammation and cytotoxicity that accompany AD progression [ 40 ]. Therefore, our understanding of the mechanisms underlying increased TREM2 expression and the regulation of phagocytosis in response to inflammation and the accumulation of Aβ plaques remains incomplete. Microglia may additionally become impaired, resulting in microglial scenscence due to the relentless need for Aβ phagocytosis, which eventually overwhelms and affects their phagolysosomal degradation pathways, preventing them from effectively engaging in the clearance of cellular debris and enzymatic degradation of Aβ [ 58 ]. Microglia are likely to become less efficient at phagocytosis before peripheral myeloid cells arrive, as they will have been exposed to Aβ for longer periods of time. Hence, our data suggest that the ensuing inflammatory signals recruit infiltrating hematogenous myeloid cells (hMφs, monocytes) in an effort to compensate for the decrease in microglial activity. While the area of microglia was greatest in proximal neighborhoods and at earlier time points, the area of monocytes was greatest at later time points. For monocytes, the area of hMφs was significantly greater at older ages. These findings suggest that increased inflammation accompanying AD progression likely drives the infiltration of hematogenous cells into affected brain regions. The area of clusters was significantly larger in proximal neighborhoods than in distal neighborhoods at both ages, suggesting that the cellular aggregates that form these clusters are attracted to AD pathology. Thus, the presence and accumulation of Aβ plaques promote aggregation through TREM2 and accumulation of these cellular clusters. Indeed, evidence suggests that Aβ may be an immunomodulator that intensifies inflammation and drives recruitment of peripheral monocytes and macrophages to sites of neuropathology in mouse models of AD pathology [ 59 , 60 ]. Chemokines and chemokine receptors regulate monocyte/macrophage recruitment into the CNS in mouse models of AD pathology [ 61 , 62 ]. Circulating monocytes and peripheral blood and tissue macrophages produce high levels of proinflammatory cytokines, including IL-1β and IL-18 [ 63 ], and represent a vital aspect of innate and adaptive immunity, as they mobilize in response to pathogens, Aβ and cellular debris [ 64 , 65 ]. There are some clues that the function of hMφs in regions of AD pathology may be beneficial. Previous studies have shown that when CD11b + monocytes from wild-type mice are injected into either APP-PSI or Tg2576 transgenic AD pathology mice, they rapidly enter the brain and reduce AD-associated pathology [ 66 , 67 ]. Furthermore, peripheral monocyte-derived macrophages infiltrate the brain and accumulate near areas of AD pathology, improving Aβ clearance in APP-PS1 mice [ 68 , 69 ]. Therefore, the observed increase in TREM2 on hMφs and monocytes at later ages that we observed in the present study may be a mechanism initiated to reduce inflammation associated with AD progression and help increase the phagocytosis of cellular debris and Aβ plaques [ 70 , 71 ]. In addition to confirming that both EGFP + myeloid cells and EGFP − microglia/mMφ coexist directly adjacent to Aβ plaques and dystrophic neurites, ultrastructural analysis revealed important features of these two populations of innate immune cells. TREM2 + myeloid cells and microglia exhibited increased phagocytic activity. Consistent with this finding, we detected phagosomes, indicating that TREM2 + cells are indeed actively engaged in phagocytosis in the vicinity of Aβ plaques and dystrophic neurites. Analysis of the presence of lysosomes in EGFP + myeloid cells and EGFP − microglia indicated that the latter tended to have a higher level of lysosomes, which are generally less abundant than phagosomes and more difficult to analyze quantitatively with EM. Both EGFP + cells and EGFP − microglia presented similar numbers of phagosomes that were not significantly different, which suggests that both populations are actively engaged in phagocytosis in the vicinity of Aβ plaques and dystrophic neurites. However, when the total membrane load was determined (unbound membranes plus membranes contained within phagosomes), EGFP + myeloid cells had significantly more total membranes than EGFP − microglia did. These findings are consistent with hematogenous myeloid cells and microglia, both contributing to the clearance of Aβ plaques and cellular debris from dystrophic neurites to reduce CNS inflammation at the 7-month time point in our transgenic model when these mice have established cognitive deficits [ 27 ]. Our ultrastructural analysis revealed that TREM2 + cells presented altered mitochondria, which are associated with metabolic alterations, including a transition from oxidative phosphorylation to glycolysis, in myeloid cells and microglia over the course of AD pathology [ 14 ]. These findings suggest that there is a cost in fulfilling the metabolic demand required by phagocytes to actively and continuously clear the constant deposition of Aβ plaques as well as cellular debris from dystrophic neurites. When comparing EGFP + myeloid cells and EGFP − microglia, there was also a significantly greater percentage of altered mitochondria that exhibited dystrophic, holey, and electron lucent features in EGFP + myeloid cells than in EGFP − microglia. As AD-like disease pathology in mouse models progresses with increased cognitive decline, microglia lose their ability to dampen and control Aβ-driven brain inflammation, resulting in the infiltration of myeloid innate immune cells [ 69 ]. The data presented here suggest that, compared with EGFP- microglia, EGFP + myeloid cells may be more susceptible to metabolic dysfunction and cellular stress in L5F + mice, likely because they are already highly inflamed in the brain. However, more investigations are needed to validate such an interpretation, as several well-defined ultrastructural markers of cellular stress, including ER and Golgi cisternae dilation [ 14 , 44 ], were not found to differ between the two cell types. These ultrastructural features were previously documented in both the APP-PS1 and 5xFAD mouse models across different ages [ 12 , 14 ]. Although their numbers were small in the examined region at the examined time point, which precluded quantitative analysis, they were not found to be EGFP + . Conclusions In conclusion, our study demonstrated that while overall cortical TREM2 expression decreased with age and AD progression, localized TREM2 expression was most abundant in plaque-associated cell clusters composed of hMφs and mMφs at older ages in L5F + mice. Furthermore, the presence and accumulation of Aβ plaques promoted the aggregation and accumulation of these cellular clusters. Our ultrastructural analysis revealed that dark microglia are not EGFP + , suggesting that they are not of bone marrow origin. Further analyses revealed that TREM2 + cells directly interact with Aβ plaques and dystrophic neurites and contain phagosomes, indicating their functional role in phagocytosis. Moreover, EGFP + myeloid cells had greater numbers of phagosomes than EGFP − microglia did, suggesting that phagocytic activity may be more robust in the former than in the latter cell type. Finally, this study demonstrated that increased inflammation and accompanying AD progression drive the infiltration of hMφs and monocytes into the brain, as reflected by increased areas of these cells in proximal plaque neighborhoods in older L5F + mice. Methods Animals All procedures involving animals were approved by the Committee for the Care and Use of Laboratory Animals at Western University and adhered to the Canadian Council on Animal Care guidelines (Protocol # 2016 − 104 and 2008 − 127). The lys -EGFP- ki transgenic mice were generated by the Thomas Graf laboratory [ 72 ] on a 129 mouse background and then backcrossed onto C57BL/6 mice. Since 2002, the lys -EGFP- ki mouse line has been maintained on the C57BL/6 background via homozygous mating. EGFP is strongly expressed in mature granulomyelomonocytic cells, including neutrophils, monocytes, and hMφ, and to a lesser extent in some peripheral tissue macrophages and dendritic cells [ 72 ]. The lys -EGFP- ki transgenic mice were crossed with transgenic 5xFAD mice obtained from the Mutant Mouse Regional Resource Center (MMRRC, University of California, Davis, Davis, CA; stock # 034848). The F1 hybrid offspring were used for all the experiments. The F1 mice were divided randomly into groups according to genotype, age, and sex: lys-EGFP- ki /5xFAD (L5F + ) and lys-EGFP- ki /5XFAD – (L5F – ) littermate controls. Male and female mice were used for all the experiments and were housed with lights on at 07:00 and lights off at 19:00. Groups of mice were aged to predetermined end points of 1.5, 3, 5, or 7 months. Food and water were available ad libitum . All procedures were performed in accordance with ARRIVE guidelines [ 73 , 74 ]. TREM2 ELISA The TREM2 protein levels were quantified via ELISA (MyBiosource, San Diego, CA, cat# MBS916554) according to the manufacturer’s protocol. Briefly, 100 mg of the cerebral cortex was rinsed with 1X phosphate-buffered saline (PBS), homogenized in 1 ml of 1X PBS and stored overnight at -20°C. Following two freeze‒thaw cycles designed to break the cell membranes, the homogenates were centrifuged for 5 min at 5000 × g at 2‒8°C. The supernatant was removed and assayed via TREM2 ELISA according to the manufacturer’s instructions. The optical density was read within 5 min on a microplate reader (SpectraMax M5, Molecular Devices, San Jose, CA) set to 450 nm. The TREM2 ELISA data were normalized to total protein for each tissue homogenate as measured by the Bradford protein assay (Bio-Rad Laboratories, Mississauga, ON; cat: 500–0006). Preparation of Tissue for Immunofluorescence Staining The mice were deeply anesthetized via an intraperitoneal (i.p.) injection of ketamine (80 mg/kg)/xylazine (20 mg/kg) [ketamine hydrochloride (Narketan), DIN: 02374994, Vetoquinol, Lavaltrie, QC; xylazine (Rompun), Bayer Inc., Missisauga, ON] and were transcardially perfused with ice-cold PBS (pH 7.2), followed by 4% PFA prepared in 1x PBS (pH 7.4). The brains were removed and postfixed for 24 hr in the same fixative and then transferred to increasing concentrations of sucrose solution at 4°C (10%, 20% and 30% sucrose for 24 hr intervals). After the last sucrose incubation, the brains were embedded in optimal cutting temperature (OCT) medium (Sakura Finetek, Inc., Torrance, CA) and frozen at − 80°C until sectioning. In preparation for immunofluorescence staining, brains were cryosectioned coronally at a thickness of 16 µm and collected in four sets of alternate sections. The sections were mounted on Superfrost plus-charged slides (Fisher Scientific, Pittsburgh, PA) and stored at − 20°C until further processing. Slides containing cortical brain sections were extensively washed in PBS and then blocked in PBS containing 5% normal goat serum (Jackson ImmunoResearch Laboratories, West Grove, PA) and 0.3% Triton X-100 (BioShop Canada Inc., Burlington, ON) for 3 hrs at room temperature (RT). Next, the sections were incubated with the following primary antibodies: rabbit anti-Iba1 (1:300; Abcam, Toronto, ON, Canada, cat # 178846) and sheep anti-TREM2 (1:200; R&D Systems, Minneapolis, MN, USA, cat: AF1729) in the same block overnight at 4°C. The slides were subsequently rinsed in PBS and incubated with the secondary antibodies Alexa Fluor 546 donkey anti-sheep IgG (cat: A21098) and Alexa Fluor 633 goat anti-rabbit IgG (cat: A21070; Life Technologies, Eugene, OR) for 1 hr at RT. Next, the sections were washed in PBS and incubated in a solution containing a rabbit IgG block (negative control rabbit immunoglobulin fraction [Agilent, Santa Clara, CA, cat# X0903]) in PBS at a concentration of 4 mg/ml for 1 hr at RT. This blocking step was added to minimize any binding from the rabbit secondary antibody to the conjugated primary rabbit antibody that was added in the final step. Following the blocking step, the sections were rinsed in PBS and incubated with rabbit anti-EGFP conjugated to Alexa Fluor 488 1:500 (Life Technologies, Eugene, OR, cat# A21311) and mouse anti-beta amyloid (MOAB-2) conjugated to DyLight 405 1:100 (Novus Biologicals, Centennial, CO, cat# NBP2-13075 V) overnight at 4°C. The next day, the slides were washed three times in PBS for 5 min, rinsed in double-distilled water, air-dried at RT for 30 min, and then cover-slipped with Vectashield Hardset mounting medium (Vector Laboratories, Burlingame, CA). Confocal Microscopy and Image Analyses in Image-Pro Short, 5-slice z stacks (0.25 mm thick) of cortical brain sections containing cortical layer 5, as this area of the cortex was previously implicated in AD pathology [ 75 ], were acquired on a Leica-TSC SP8 confocal microscope (Leica Microsystems, Concord, ON, Canada) at 63 X (N.A. ¼ 1.4) magnification with oil immersion (Leica Microsystems, Concord, ON, Canada). Each z stack had a total of four channels, including Alexa 405 to visualize Aβ plaques, Alexa 488 for EGFP, Alexa 546 for TREM2 and Alexa 633 for Iba1. A total of 8–12 z stacks were acquired per animal, and there were 4–5 mice per group. After careful review of the images, a single layer representing the most intact cells was selected from all the animals for analysis. For image data analysis, custom-written macros were created in ImagePro (Media Cybernetics, Inc. Rockville, MD) via machine learning algorithms. Briefly, four channel images were generated: Alexa 405 for Aβ plaques, Alexa 488 for EGFP, Alexa 546 for TREM2 and Alexa 633 for Iba1. An image was created for each channel via the Image-Pro “medium edges” algorithm, which maintains intact intensity data. The purpose of this step was to connect the microglial processes to each other and their cell bodies where they were in separate z-stack layers. For the cellular and plaque channels, the images were preprocessed through Gaussian filtering (3x3 100% × 20 passes) to remove noise and improve cellular object recognition. In addition, a color-composite image was generated using the green EGFP EDF image overlaid on both the red Iba1 channel and the TREM2 channel image, which was pseudocolored pure blue. These images were used to train machine learning to recognize four distinct cell types on the basis of size, color and morphology: monocytes/neutrophils (EGFP-positive, Iba1-negative), hematogenous macrophages (EGFP-positive, Iba1-positive), microglia (EGFP-negative, Iba1-positive) and clusters, which referenced groups of cells in very close proximity to each other and/or touching and were composed of a combination of microglia and hMφ. Before generating outlines of the Aβ plaques from the Alexa 405 channel, a binary mask of the eGFP+/Iba1- cells was generated from the green/488 nm channel image and then subtracted from the 405 channel image to remove eGFP+/Iba1- cellular crosstalk that might read as a false positive plaque signal, leaving only the plaque signal visible. Using the Aβ channel image (Fig. 6 C-D), the outlines of the Aβ plaques were then selected and grown to 200 pixels (28.4 µm), representing the area of the cells proximal to the Aβ plaques (Fig. 6 B). Areas outside the 200 pixels were designated distal areas in relation to Aβ plaques. These enlarged plaque areas were saved as regions of interest designated “plaque neighborhoods”. Next, a series of region of interest (ROI) analyses were performed on the composite images. First, the plaque ROIs were reapplied to the merged red, green and blue images (Fig. 6 E-H). Using machine learning, outlines for each cell type were generated from the color-composite images and stored as new, cell specific, precisely located ROIs, designated by location as either “proximal” or “distal” to the plaques (Fig. 6 H). The sum of the IOD and sum of the area of staining was obtained within the outlines of each of the four cell types, both proximally (Fig. 6 E, F) and distally (Fig. 6 G, H) to the plaques. As the TREM2 channel image was pseudocolored pure blue and incorporated when the composite images were generated, blue signal IOD data were used to determine the TREM2 protein content within the outlines of the cells. Preparation of Tissue for EM The animals used for the EM experiments received i.p. injections of Methoxy-X04 (Tocris Bioscience, Bristol, United Kingdom; cat# 4920) at a dose of 10 g/kg, enabling the visualization of fibrillar Aβ via fluorescence microscopy for the screening of sections containing Aβ plaques prior to processing via EM [ 77 ]. Twenty-four hours later, the mice were anesthetized via i.p. injection of ketamine (80 mg/kg)/xylazine (20 mg/kg) [ketamine hydrochloride (Narketan), DIN: 02374994, Vetoquinol, Lavaltrie, QC; xylazine (Rompun), Bayer Inc., Missisauga, ON] followed by transcardial perfusion with 75 ml of 3.5% acrolein (Polysciences, Inc., Warrington, PA; cat # 00016) diluted in 1x phosphate buffer (PB): pH 7.4, and 150 ml of 4% paraformaldehyde [PFA (BioShop Canada Inc., Burlington, ON; cat # 30535–89 − 4), diluted in 1X PBS: pH 7.4]. Coronal brain sections (50 µm thick) were cut in ice-cold PBS on a vibratome (Leica VT1000S) and stored at -20°C in a cryoprotectant solution [30% glycerol, 30% ethylene glycol, 40% 1x PBS] until further processing. Anti‑GFP and anti-TREM2 immunohistochemistry for EM For EM imaging, sections from 7-month-old L5F + and L5F − male mice were selected. Three sections containing the cingulate cortex corresponding to bregma levels ranging from − 1.91 mm to -2.27 mm were selected on the basis of the stereotaxic atlas by Paxinos and Franklin (4th edition) [ 78 ]. The sections were washed with PBS three times for 10 min for TREM2 immunolabeling, incubated in citrate buffer for 15 min at 70°C and then washed with PBS three times for 10 min. The samples were then quenched with 0.3% H 2 O 2 in PBS for 5 min and washed with PBS five times for 5 min. The sections were incubated in 0.1% NaBH 4 for 30 min, followed by five washes of 5 min with PBS. The samples were then incubated in blocking buffer (10% normal donkey serum, 3% bovine serum albumin [BSA], 0.3% Triton X-100) for 1 hr. Next, the sections were incubated overnight at 4°C in blocking buffer with a primary antibody cocktail ([1:1000] rabbit anti-GFP primary antibody (Invitrogen, cat# A11122, or ([1:100] sheep anti-TREM2 primary antibody (R&D Systems, Minneapolis, MN, cat# AF1729)). The next day, after reaching RT, the sections were washed with PBS three times for 10 min and incubated in TBS containing biotinylated donkey anti-rabbit secondary antibody ([1:200] cat# 711–065–152, Jackson ImmunoResearch) for 1.5 hr at RT for GFP immunolabeling or TBS with 0.05% Triton X-100 donkey anti-sheep secondary antibody ([1:300] cat# 713–066–147, Jackson ImmunoResearch) for 2 hr at RT for TREM2 immunolabeling. The sections were subsequently incubated with avidin-biotin complex solution (Vector Laboratories, Burlingame, CA, USA; cat# PK-6100) [1:100] in TBS for 1 hr at RT. The samples were stained with 0.05% diaminobenzidine (DAB; Millipore Sigma cat# D5905-50TAB) with 0.015% H 2 O 2 in Tris-buffer (TB, pH 8.0) for 5 min at RT. The samples were next fixed in osmium-thiocarbohydrazide-osmium to enhance contrast for scanning electron microscopy [ 13 ]. The sections were incubated in a 1:1 solution of 4% aqueous osmium tetroxide (Electron Microscopy Sciences [EMS], Hatfield, PA, USA, cat# 19170) and 3% potassium ferrocyanide (Bioshop, Burlington, ON, Canada, cat# PFC232.250) in double distilled (dd) H 2 O for 1 hr. The sections were washed with ddH 2 O three times for 5 min and incubated in 1% thiocarbohydrazide (EMS, cat# 2231-57-4) diluted in ddH 2 O for 20 min. After the sections were washed three times for 5 min, they were incubated for 30 min in 2% osmium tetroxide diluted in ddH 2 O and then dehydrated in increasing concentrations of ethanol (two times in 35%, one time in 50%, 70%, 80%, 90%, and three times 100%), followed by three incubations of 5 min in propylene oxide. After dehydration, the sections were flat-embedded in Durcupan ACM resin (Millipore Sigma, cat# 44611–44614). In brief, the sections were infiltrated with resin at RT overnight. They were carefully placed on a fine layer of resin between 2 sheets of ACLAR® embedding films (EMS, cat# 50425-25) for polymerization at 55°C for 72 hr. After polymerization, a section containing the region of interest was excised and glued to a Durcupan resin block for ultrathin sectioning, sections immunolabeled for GFP were cut via an Ultracut UC7 ultramicrotome (Leica Biosystems), and sections immunolabeled for TREM2 were cut via an ARTOS 3D ultramicrotome (Leica Biosystems). Ultrathin sections of ~ 75 nm thickness were collected on a silicon nitride chip and placed on sample mounts for SEM. The cells were imaged at a resolution of 5 nm per pixel via a crossbeam 540 or a crossbeam 350 field emission SEM with a Gemini column (Zeiss). Images were exported as TIFF files via Zeiss ATLAS Engine 5 software (Fibics). Examples of TREM2-positive (TREM2 + ) cells from L5F + male mice are shown. The cells were sampled in direct contact with Aβ plaques or dystrophic neurites. Ultrastructural analysis Microglia and hematogenous macrophages were identified by their shared ultrastructural features: their dark irregular cytoplasm, heterogeneous chromatin pattern, distinctive long stretches of endoplasmic reticulum (ER) cisternae and lipidic inclusions (i.e., lipofuscin, lipid bodies or droplets, and lysosomes) [ 44 , 79 ]. Hematogenous macrophages were specifically identified as immunopositive for EGFP (EGFP+). Microglia were specifically identified as immunonegative for EGFP (EGFP-). Neutrophils can be recognized by their ultrastructural features, which are characterized by a lobulated nucleus with heterochromatin distributed on the edges and euchromatin close to nuclear pores, as well as various types of granules in the cytoplasm [ 80 ]. Only cells contacting Aβ plaques or dystrophic neurites [ 14 ] present in the LF5 + mouse samples were included in the analysis. The ultrastructural analysis included 8–14 EGFP + cells (hMφ) and 8–10 EGFP − cells (microglia) per animal, resulting in a total of 32 EGFP + cells and 27 EGFP − cells. The quantitative analysis was performed by a researcher blinded to the experimental conditions via QuPath software. The cytoplasm of each cell was traced manually via the ImageJ extension of QuPath using the freehand tool to ensure accurate delineation of the plasma membrane from surrounding parenchymal elements. The ultrastructural analysis included the assessment of mitochondria, ER cisternae, Golgi apparatus cisternae, lysosomes, lipofuscin granules, nuclear membrane alterations and autophagosomes. These organelles were quantified, and their health status was assessed [ 44 , 81 ]. Lysosomes were characterized by their circular shape and either homogenous (primary) or heterogeneous (secondary and tertiary) interior. The primary lysosomes were small and highly circular, whereas the secondary lysosomes were larger. Tertiary lysosomes, the largest type of lysosome, consisted of lipids fused to one or more lipofuscin granules [ 82 , 83 ]. Lipids were identified by their highly circular and electron-dense outline, with either a homogenous electron-dense interior or an interior filled with several electron-lucent inclusions. Lipofuscin granules were recognized by their irregular shape, granular appearance, and fingerprint-like pattern [ 44 , 84 ]. The number of phagocytic inclusions (phagosomes) within the cytoplasm was quantified to investigate phagocytic activity. Empty phagosomes have a circular outer membrane and an electron-lucent interior, whereas phagosomes containing debris contained partially digested cellular contents [ 81 ]. The latter were further divided into phagosomes containing membrane materials and phagosomes containing partially digested cellular contents other than membranes such as synaptic elements. The presence of unbound membranes, i.e., membranes not enclosed within a phagosome and appearing as linear stretches of thin electron-dense membranes inside the cytoplasm, was also quantified. To quantify cellular stress and metabolic dysfunction, the abundance and percentage of unaltered (healthy) compared with altered mitochondria in each analyzed cell determined. Healthy mitochondria were characterized by their electron-dense appearance and intact double membrane and cristae [ 44 , 81 ]. Altered mitochondria were classified into one of the following three categories: dystrophic, holey, or electron-lucent. Dystrophic mitochondria had a deteriorated double membrane or cristae, appearing as electron-lucent patches [ 81 ]. Holey mitochondria were donut-shaped [ 85 ], while electron-lucent mitochondria containedcontained a predominantly white interior with fractured cristae [ 44 , 86 ]. The abundance and percentage of nonelongated (measuring < 1000 nm in length) compared with elongated (measuring ≥ 1000 nm in length) mitochondria were quantified to provide insight into mitochondrial fission‒fusion processes [ 14 ]. The ER cisternae were identified by their long thin stretches, and the Golgi cisternae were identified by their set of flattened stacked sacks. The dilated ER and Golgi cisternae were used as markers of cellular stress and were characterized by their swollen electron‒lucent appearance and cisternal diameter, which is ≥ 50 nm in length [ 44 , 83 ]. Nuclear alterations, including membrane indentations and knots (bundling of the nuclear membrane), were also quantified [ 44 , 86 ]. To gain insight into microglial interactions with parenchymal elements, microglial contacts with axon terminals were recognized by the presence of several synaptic vesicles and dendritic spines combined with the presence of postsynaptic densities and synaptic clefts at both the axon terminal and dendritic spine, were quantified. [ 44 , 81 ]. Microglial contacts with myelinated axons, both healthy and dystrophic, as well as contacts with other cells, including neurons, astrocytes, oligodendrocytes, myeloid cells (EGFP + ), microglia (EGFP − ), and blood vessels, were also quantified [ 86 ]. Statistical Analyses All the data were analyzed via GraphPad Prism software (version 9; GraphPad Software, La Jolla, CA) and are expressed as the means +/- standard errors of the means [ 13 ]. TREM2 ELISA data were analyzed via two-way analysis of variance (ANOVA) [ 87 ] with a mixed model and Tukey’s multiple comparisons tests, which were used to compare different time points. Image data were analyzed via two-way ANOVA and Tukey’s multiple comparisons tests. For these analyses, the two examined time points (5 and 7 months) and neighborhoods (proximal and distal to Aβ plaques) were compared. The Aβ plaque area and TREM2 area in the Aβ plaque region were analyzed via two-way ANOVA and Tukey’s multiple comparisons test, and the results were compared between males at 5 and 7 months. Supplementary Fig. 1 contains data showing the Aβ plaque area and TREM2 area in the Aβ plaque regions of females at 5 and 7 months. The normality of the ultrastructural data was tested via the Shapiro‒Wilk test. Comparisons of ultrastructural features between EGFP + and EGFP − cells were performed via unpaired, two-tailed Student’s t tests. The sample size (n) refers to individual cells as previously described to consider intercellular heterogeneity [ 83 – 85 , 88 – 90 ]. Statistically significant differences were determined as those for which p \(\:\le\:\) 0.05. Details of the ultrastructural analyses are presented in Table 1 . Details of all other statistical analyses are presented in Supplementary Data Table 1 . Abbreviations Aβ amyloid β AD Alzheimer's Disease ANOVA analysis of variance ApoE apolipoprotein E APP amyloid precursor protein BSA bovine serum albumin DAB diaminobenzidine DAM disease-associated microglial EDF extended depth of focus EM electron microscopy EMS Electron Microscopy Sciences ER endoplasmic reticulum hMφ hematogenous macrophage (derived from monocytes) Iba1 ionized calcium binding adapter protein 1 IOD integrated optical density LF5 lys -EGFP- ki × 5XFAD F1 hybrid transgenic mouse lys -EGFP- ki lysozyme M-Enhanced Green Fluorescent Protein-knock in mMφ microglia/microglia-derived macrophage OCT optimal cutting temperature PBS Phosphate-buffered saline PS1 presenilin 1 ROI region of interest TLR Toll-like receptor TREM2 triggering receptor expressed by myeloid cells TB Tris buffer TBS Tris-buffered saline TyroBP tyrosine kinase receptor binding protein Declarations Acknowledgments We thank Drs. Marco and Vania Prado for crossing and breeding the mice needed for this project. We thank Christy Barreira and Corby Fink for their technical and administrative support. We acknowledge that the University of Western Ontario is located in the traditional territories of the Anishinaabek, Haudenosaunee, Lūnaapéewak and Chonnonton Nations on lands connected with the London Township and Sombra Treaties of 1796 and the Dish with One Spoon Covenant Wampum. This land continues to be home to diverse indigenous peoples whom we recognize as contemporary stewards of the land. We also acknowledge the lək̓ʷəŋən people whose traditional territory the University of Victoria stands and the Songhees, Esquimalt and WSÁNEĆ people whose historical relationships with the land continue to this day. Author contributions GAD, RJR NK and M-ET conceived and designed the study. NK, KN, FGI, CK, MET and VT participated in data collection and analysis. NK and FGI drafted the manuscript. GAD, JR, M-ET, CK and MET provided critical manuscript revisions. All the authors read and approved the final manuscript. Funding This project was supported by funding from the Canadian Health Institutes of Health Research Canadian Consortium on Neurodegeneration in Aging. MET is a Tier 2 Canada Research Chair in Neurobiology of Aging and Cognition . FGI is a Michael Smith Health Research BC postdoctoral fellow and was supported by a doctoral scholarship from the Mexican Council of Humanities, Science and Technology [CONAHCYT/formerly CONACYT]. The Tremblay laboratory’s scanning electron microscope was acquired with a CFI John R. Evans Leaders Fund (#39965). Availability of data and materials The data sets used or analyzed during this study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing interests The authors declare that they have no competing interests. Author details 1 Translational Neuroscience Group, Robarts Research Institute, University of Western Ontario, 1151 Richmond Street North, London, Ontario N6A 5B7, Canada; 2 Division of Medical Sciences, Medical Sciences Building, University of Victoria, 9882 Ring Rd, Victoria, BC V8P 3E6 Canada, 3 Biotron, Room Bio 105, Department of Biology, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1, 4 Department of Physiology & Pharmacology, Medical Sciences Building, Room 216, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1, 5 Department of Microbiology & Immunology, Dental Science Building, Room 3014, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1 References Selkoe DJ. The molecular pathology of Alzheimer’s disease. Neuron [Internet]. 1991 [cited 2024 Oct 8];6:487–98. Available from: https://pubmed.ncbi.nlm.nih.gov/1673054/ Jorfi M, Maaser-Hecker A, Tanzi RE. 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Available from: https://pubmed.ncbi.nlm.nih.gov/30332405/ Tables Table 1. Ultrastructural features of GFP + vs GFP - cells. Parameters Mean ± standard error of the mean p GFP + GFP - Contacts CNS cells # Astrocytes 0.0625 ± 0.0435 0.0370 ± 0.0370 0.6640 # Neurons 0.000 ± 0.000 0.000 ± 0.000 NA # Oligodendrocytes 0.000 ± 0.000 0.0370 ± 0.0370 0.2801 # Oligodendrocyte precursors 0.000 ± 0.000 0.000 ± 0.000 NA # Another myeloid cell 0.1875 ± 0.0833 0.000 ± 0.000 0.0434 Parenchymal elements # Axon terminals 2.688 ± 0.315 2.704 ± 0.3239 0.9735 # Dendritic spines 0.2500 ± 0.0898 0.1852 ± 0.0930 0.6196 # Synaptic clefts 0.6250 ± 0.1892 0.5926 ± 0.1438 0.8951 # Healthy myelinated axons 0.1563 ± 0.0792 0.1111 ± 0.0815 0.6941 # Dystrophic myelinated axons 1.031 ± 0.1878 0.7407 ± 0.0859 0.1906 # Total myelinated axons 1.188 ± 0.2127 0.8519 ± 0.1275 0.2014 % Dystrophic myelinated axon 92.67 ± 3.611 94.17 ± 4.060 0.7837 Other # Blood vessel 0.000 ± 0.000 0.000 ± 0.000 NA Organelles Lysosomes # Primary lysosomes 0.000 ± 0.000 0.000 ± 0.000 NA # Secondary lysosomes 0.000 ± 0.000 0.0370 ± 0.000 0.2801 # Tertiary lysosomes 0.000 ± 0.000 0.0741 ± 0.0514 0.1213 # Total lysosomes 0.000 ± 0.000 0.1111 ± 0.0616 0.0542 Phagosomes # Empty 0.1250 ± 0.0594 0.2222 ± 0.0975 0.3821 # Containing membrane debris 0.3125 ± 0.1225 0.0741 ± 0.0514 0.0976 # Containing debris other than membranes 0.3438 ± 0.1239 0.2593 ± 0.1262 0.6366 # Total phagosomes with content 0.6563 ± 0.2182 0.3333 ± 0.1510 0.2455 # Total (empty + with content) 0.7813 ± 0.2407 0.5556 ± 0.2157 0.4950 # Autophagosomes 0.0313 ± 0.0313 0.000 ± 0.000 0.3628 Mitochondria # Unaltered (healthy) 7.313 ± 1.374 8.185 ± 1.406 0.6605 # Altered 1.938 ± 0.3205 1.926 ± 0.4234 0.9824 # Dystrophic 0.6875 ± 0.1519 0.8889 ± 0.2633 0.4943 # Holey 0.2188 ± 0.1165 0.0370 ± 0.0370 0.1724 # Electron-lucent 1.031 ± 0.2396 1.000 ± 0.2722 0.9314 # Elongated 0.9063 ± 0.2026 0.7407 ± 0.2647 0.6160 % Elongated 9.492 ± 2.345 4.881 ± 1.713 0.1259 Endoplasmic reticulum # Dilated 2.656 ± 0.5210 2.852 ± 0.6055 0.8064 % Dilated 14.69 ± 2.278 16.21 ± 3.021 0.6841 Golgi # Dilated 0.000 ± 0.000 0.0370 ± 0.0370 0.2801 % Dilated 0.000 ± 0.000 20.00 ± 20.00 0.7040 Nucleus # Indentations/Protrusions 0.0316 ± 0.0316 0.0741 ± 0.0514 0.4643 # Alterations 0.0313 ± 0.0313 0.0370 ± 0.0370 0.9047 Other # Lipids 0.0625 ± 0.0625 0.1852 ± 0.0930 0.2658 # Lipofuscin granules 0.9688 ± 0.3404 1.000 ± 0.3112 0.9470 Additional Declarations No competing interests reported. Supplementary Files Supplfigure1TREM2ELISAplaqueareaandintensityinplaquesfemales.tif Supplementaryfig2TREM2images5and7monthfemalesrevised.tif NewSupplementaryFig3PercentcellareaandTREM2IODinfemales.tif Supplementary.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6222217","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":432273721,"identity":"7434e19f-5b9b-48d6-850b-6842c86ab341","order_by":0,"name":"Natalie Kozyrev","email":"","orcid":"","institution":"University of Western Ontario","correspondingAuthor":false,"prefix":"","firstName":"Natalie","middleName":"","lastName":"Kozyrev","suffix":""},{"id":432273722,"identity":"27e81aa9-2b3f-471e-9791-cf9094b3fc38","order_by":1,"name":"Fernando González Ibáñez","email":"","orcid":"","institution":"University of Victoria","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"González","lastName":"Ibáñez","suffix":""},{"id":432273723,"identity":"3820d97b-4442-4607-ba25-99558066580b","order_by":2,"name":"Chloe McKee","email":"","orcid":"","institution":"University of Victoria","correspondingAuthor":false,"prefix":"","firstName":"Chloe","middleName":"","lastName":"McKee","suffix":""},{"id":432273724,"identity":"9034599a-ab75-4320-8ea3-ec899991096e","order_by":3,"name":"Marianela E. Traetta","email":"","orcid":"","institution":"University of Victoria","correspondingAuthor":false,"prefix":"","firstName":"Marianela","middleName":"E.","lastName":"Traetta","suffix":""},{"id":432273725,"identity":"d8234270-fc4d-47d6-8637-e88f2b594474","order_by":4,"name":"Vasiliki Tellios","email":"","orcid":"","institution":"University of Western Ontario","correspondingAuthor":false,"prefix":"","firstName":"Vasiliki","middleName":"","lastName":"Tellios","suffix":""},{"id":432273726,"identity":"7c5245bb-ed72-41dd-ac5d-ea75f7e7fd1d","order_by":5,"name":"Karen L. Nygard","email":"","orcid":"","institution":"University of Western Ontario","correspondingAuthor":false,"prefix":"","firstName":"Karen","middleName":"L.","lastName":"Nygard","suffix":""},{"id":432273727,"identity":"8b25f77b-32a4-4d0f-b9c2-96536e9bea83","order_by":6,"name":"R. Jane Rylett","email":"","orcid":"","institution":"University of Western Ontario","correspondingAuthor":false,"prefix":"","firstName":"R.","middleName":"Jane","lastName":"Rylett","suffix":""},{"id":432273728,"identity":"02a6798f-f8fe-48ee-8f0a-1f06c286da4c","order_by":7,"name":"Marie-Eve Tremblay","email":"","orcid":"","institution":"University of Victoria","correspondingAuthor":false,"prefix":"","firstName":"Marie-Eve","middleName":"","lastName":"Tremblay","suffix":""},{"id":432273729,"identity":"b61ea9c4-bea6-4c28-99cb-98380eae0fa9","order_by":8,"name":"Gregory A. Dekaban","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYDCCA2wMzEBKjnQtxqRrSWwgWgff8bbEzwU1d9I33Eg+wPCjhggtkmeOHZaecexZ7oYbaQmMPceI0GJwI71BmoftcO6G2zkGzAxsxGi5/7z5N8+/w+kGYC3/iLKF7Zg0b9vhBLAWxjYitEieSUuzntl32HDm/WcJB3v7iNDCd/yY8e2Cb4fl+c4cPvjgxzcitKCAA6RqGAWjYBSMglGAAwAAzhA8hmUx6ngAAAAASUVORK5CYII=","orcid":"","institution":"University of Western Ontario","correspondingAuthor":true,"prefix":"","firstName":"Gregory","middleName":"A.","lastName":"Dekaban","suffix":""}],"badges":[],"createdAt":"2025-03-13 18:23:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6222217/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6222217/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79216411,"identity":"c7ce1c56-47b8-4af0-bb32-1e9c61185fa9","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105469,"visible":true,"origin":"","legend":"\u003cp\u003eCortical TREM2 protein levels, percent area of Aβ plaques and TREM2 intensity near Aβ plaques.\u003cstrong\u003e A\u003c/strong\u003e TREM2 ELISA demonstrated that TREM2 expression is decreased in the cerebral cortex with increasing age in male L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e and L5F\u003csup\u003e\u003cstrong\u003e- \u003c/strong\u003e\u003c/sup\u003emice. TREM2 levels significantly decreased from the age of 1.5 months to 5 months (P \u0026lt; 0.0001) and 7 months (P \u0026lt; 0.0001) and from the age of 3 months to 5 months (p = 0.002) and 7 months (p \u0026lt; 0.0001). In L5F\u003csup\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/sup\u003e males, TREM2 levels significantly decreased from the age of 1.5 months to the ages of 5 months (p = 0.009) and 7 months (p = 0.014) and from the age of 3 months to the ages of 5 months (p = 0.036) and 7 months (p = 0.05). The data are presented as the means ± SEMs and were analyzed via two-way ANOVA with Tukey’s post hoc multiple comparisons test. * p ≤ 0.05, ** p ≤ 0.01, **** p ≤ 0.0001. \u003cstrong\u003eB\u003c/strong\u003e Percent Aβ plaque area in male L5F\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003emice at 5 and 7 months of age. The percent area of Aβ plaques was significantly greater in L5F\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003emales at the age of 7 months than in those at the age of 5 months (p = 0.042). These analyses were performed on 8–12 brain sections per mouse and 4–6 mice per group. The data are presented as the means ± SEMs and were analyzed via an unpaired, two-tailed t test.\u003cu\u003e \u003c/u\u003eStatistical significance was taken at * p ≤ 0.05. \u003cstrong\u003eC\u003c/strong\u003e TREM2 intensity in Aβ plaques in L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males at ages 5 and 7 months. There were no significant differences in TREM2 intensity in Aβ plaques \u003cu\u003ein \u003c/u\u003eL5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males between the ages of 5 and 7 months. These analyses were performed on 8–12 brain sections per mouse and 4–6 mice per group.\u003cu\u003e \u003c/u\u003eThe data are presented as the means ± SEMs and were analyzed via an unpaired, two-tailed t test. Statistical significance was taken at * p ≤ 0.05.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/352bfd1a974e4af27dcbe6f2.jpg"},{"id":79216413,"identity":"37fd23dc-32e3-41a2-8aa4-cd0822515ceb","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":332579,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative confocal microscopy images of the cerebral cortex immunostained for Aβ, EGFP, TREM2 and Iba1. Images of L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003emale mice at the ages of 5 months \u003cstrong\u003e(panels A–H)\u003c/strong\u003e and 7 months \u003cstrong\u003e(panels I–P)\u003c/strong\u003e. \u003cstrong\u003eA and I:\u003c/strong\u003e\u003cu\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/u\u003eAβ;\u003cu\u003e \u003c/u\u003e\u003cstrong\u003eB and J:\u003c/strong\u003e\u003cu\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/u\u003eEGFP;\u003cu\u003e \u003c/u\u003e\u003cstrong\u003eC and K: \u003c/strong\u003eTREM2; \u003cstrong\u003eD and L: \u003c/strong\u003eIba1 immunostaining.\u003cstrong\u003e E \u003c/strong\u003eMerged image of panels \u003cstrong\u003eB \u003c/strong\u003eand\u003cstrong\u003e D\u003c/strong\u003e. \u003cstrong\u003eF \u003c/strong\u003eMerged image of panels \u003cstrong\u003eB, C\u003c/strong\u003e and \u003cstrong\u003eD\u003c/strong\u003e. \u003cstrong\u003eG\u003c/strong\u003e Merged image of panels \u003cstrong\u003eA–D\u003c/strong\u003e. \u003cstrong\u003eH\u003c/strong\u003e Enlarged image of the area outlined in panel \u003cstrong\u003eG\u003c/strong\u003e showing cells around Aβ plaques marked by arrowheads (red, resident microglia; yellow, hematogenous macrophages; white, clusters). \u003cstrong\u003eM\u003c/strong\u003e Merged image of panels \u003cstrong\u003eJ\u003c/strong\u003e and \u003cstrong\u003eL\u003c/strong\u003e. \u003cstrong\u003eN\u003c/strong\u003e Merged image of panels \u003cstrong\u003eJ, K\u003c/strong\u003e and \u003cstrong\u003eL\u003c/strong\u003e. \u003cstrong\u003eO\u003c/strong\u003e Merged image of panels \u003cstrong\u003eI–L\u003c/strong\u003e. \u003cstrong\u003eP\u003c/strong\u003e Enlarged image of the area outlined in panel \u003cstrong\u003eO\u003c/strong\u003e showing various cells around Aβ plaques marked by arrowheads (red – resident microglia; yellow – hematogenous macrophages; white – clusters; green – monocytes). Images were acquired at 63X magnification (Leica Microsystems, N.A. = 1.4). Scale bar = 25 µm. These analyses were performed on 8–12 brain sections per mouse and 4–6 mice per group.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/5499ca9112b158efc77b2da9.jpg"},{"id":79216416,"identity":"befe4342-e419-4dfc-9d52-0bd1d506959b","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":153742,"visible":true,"origin":"","legend":"\u003cp\u003ePercent area of TREM2 immunoreactivity and intensity in microglia, monocytes, hematogenous macrophages and clusters. Data were obtained in the proximal and distal neighborhoods of Aβ plaques in male L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e mice at the ages of 5 and 7 months. \u003cstrong\u003eA\u003c/strong\u003e Percent area of microglia/mMΦ (Iba1+, EGFP-) in L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males at ages 5 and 7 months. \u003cstrong\u003eB\u003c/strong\u003e Percent area of monocytes at ages 5 and 7 months in L5F+ males. \u003cstrong\u003eC\u003c/strong\u003e Percent area of hMΦ at 5 and 7 months of age in L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males. \u003cstrong\u003eD\u003c/strong\u003e The percentage area of clusters was significantly greater within proximal neighborhoods than distal neighborhoods at ages 5 and 7 months in L5F\u003csup\u003e\u003cstrong\u003e+ \u003c/strong\u003e\u003c/sup\u003emales. \u003cstrong\u003eE\u003c/strong\u003e TREM2 IOD in microglia/mMΦ (Iba1+, EGFP-) at ages 5 and 7 months in L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males. \u003cstrong\u003eF\u003c/strong\u003e TREM2 IOD in monocytes from L5F+ males at 5 and 7 months of age. \u003cstrong\u003eG\u003c/strong\u003e TREM2 IOD in hMΦs at 5 and 7 months of age in L5F\u003csup\u003e\u003cstrong\u003e+\u003c/strong\u003e\u003c/sup\u003e males. \u003cstrong\u003eH\u003c/strong\u003e TREM2 IOD in clusters of L5F+ males at 5 and 7 months of age. These analyses were performed on 8–12 brain sections per mouse and 4–6 mice per group. The data are presented as the means ± SEMs and were analyzed via two-way ANOVA with Tukey’s post hoc multiple comparisons test. * p ≤ 0.05, ** p ≤ 0.01, **** p ≤ 0.0001.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/6f2724026574d2bd90fd0f36.jpg"},{"id":79217579,"identity":"c616917b-b632-4f1d-8778-f5feb732ba27","added_by":"auto","created_at":"2025-03-25 19:13:07","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":565313,"visible":true,"origin":"","legend":"\u003cp\u003eUltrastructure of TREM2\u003csup\u003e+\u003c/sup\u003e cells. Representative 5-nm resolution scanning electron microscopy images of the cingulate cortex of 7-month-old LF5\u003csup\u003e+\u003c/sup\u003e male mice. \u003cstrong\u003eA\u003c/strong\u003e Overview of TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e- \u003c/sup\u003ecells interacting with dystrophic neurites. \u003cstrong\u003eB–D\u003c/strong\u003e Examples of TREM2\u003csup\u003e+ \u003c/sup\u003ecells. \u003cstrong\u003eE\u003c/strong\u003e Example of TREM2\u003csup\u003e-\u003c/sup\u003e cells. \u003cstrong\u003eF\u003c/strong\u003e TREM2\u003csup\u003e+ \u003c/sup\u003ecells near an Aβ plaque. \u003cstrong\u003eG\u003c/strong\u003e TREM2\u003csup\u003e+ \u003c/sup\u003edirectly contacts an Aβ plaque. \u003cstrong\u003eH\u003c/strong\u003e Example of TREM2\u003csup\u003e+\u003c/sup\u003e cells interacting with dystrophic neurites. Yellow outline = nuclear membrane, green outline = cell membrane of TREM2\u003csup\u003e+\u003c/sup\u003e cells, pink outline: cell membrane of TREM2\u003csup\u003e-\u003c/sup\u003e cells, orange arrowhead = TREM2\u003csup\u003e+\u003c/sup\u003e immunolabeling, white arrowhead = Aβ plaque.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/fa41e782fff2d4cc66bc6815.jpg"},{"id":79216412,"identity":"789f8b39-8150-4910-a4d8-f9ddbb089de2","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":324228,"visible":true,"origin":"","legend":"\u003cp\u003eUltrastructure of EGFP\u003csup\u003e+\u003c/sup\u003e \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cells. Representative 5-nm resolution scanning electron microscopy images of the cingulate cortex of 7-month-old LF5\u003csup\u003e+\u003c/sup\u003e male mice. \u003cstrong\u003eA\u003c/strong\u003e EGFP\u003csup\u003e+\u003c/sup\u003e cell with healthy mitochondria and dystrophic mitochondria. \u003cstrong\u003eB\u003c/strong\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cell with healthy mitochondria. \u003cstrong\u003eC\u003c/strong\u003e Quantitative graph representing the percentage of altered mitochondria in EGFP\u003csup\u003e+\u003c/sup\u003e \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cells. \u003cstrong\u003eD\u003c/strong\u003e EGFP\u003csup\u003e+\u003c/sup\u003e cells with unbound membrane inclusions. \u003cstrong\u003eE\u003c/strong\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cell with bound membrane inclusions. \u003cstrong\u003eF\u003c/strong\u003e Quantitative graph representing the number of unbound membrane inclusions per cell in EGFP\u003csup\u003e+\u003c/sup\u003e \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cells. \u003cstrong\u003eG\u003c/strong\u003e Quantitative graph representing the number of total membrane inclusions per cell in EGFP\u003csup\u003e+\u003c/sup\u003e \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e cells. \u003cstrong\u003eH\u003c/strong\u003e EGFP\u003csup\u003e+\u003c/sup\u003e cell contacting an EGFP\u003csup\u003e-\u003c/sup\u003e cell. \u003cstrong\u003eI\u003c/strong\u003e Quantitative graph representing the number of contacts between EGFP\u003csup\u003e+\u003c/sup\u003e or EGFP\u003csup\u003e-\u003c/sup\u003e cells and other myeloid cells. The data are shown as individual dots and are expressed as the means ± S.E.M. * p \u0026lt; 0.05, ** p \u0026lt; 0.01, unpaired Student's t test. Statistical tests were performed on 32 EGFP\u003csup\u003e+\u003c/sup\u003e cells and 27 EGFP\u003csup\u003e-\u003c/sup\u003e cells. Blue pseudocolouring = healthy mitochondria, orange pseudocolouring = dystrophic mitochondria, yellow pseudocolouring = unbound membranes, red pseudocolouring = bound membranes, yellow outline = nuclear membrane, red outline = cell membrane of EGFP+ cells, white outline = cell membrane of EGFP- cells.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/0bb4275d78371cfb3d0e9195.jpg"},{"id":79216423,"identity":"e7007afc-d62f-41d2-b209-1cf58923d1dc","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":183113,"visible":true,"origin":"","legend":"\u003cp\u003eIllustration of image analysis macro steps. Image analyses were performed via machine learning algorithms in custom-written macros generated in ImagePro (Media Cybernetics, Inc. Rockville, MD). Panels A-D are the monochrome channels obtained when the raw data images are exported from Leica software. The cells were classified into one of four categories via machine learning algorithms: microglia, blood-borne monocytes, hematogenous macrophages and clusters. These cell-based regions of interest for each cell category, including its exact location, were applied to the unaltered TREM2 image, and the mean integrated optical density and mean area of staining were obtained within the outlines of each of the four cell categories, proximally and distally to the Aβ plaques. \u003cstrong\u003eA\u003c/strong\u003eOutlines created around eGFP+ cells for the purpose of removing crosstalk in the Aβ channel. \u003cstrong\u003eB\u003c/strong\u003e Binary mask of cellular outlines. \u003cstrong\u003eC\u003c/strong\u003e The binary mask of the outlined cells is subtracted from the Aβ (405 nm) channel image to remove crosstalk (yellow arrows denote subtracted cells, the inset shows cells before subtraction), and then the plaques are outlined (red outlines).\u003cstrong\u003eD\u003c/strong\u003e Areas around Aβ \u0026nbsp;plaques grown by 200 pixels (28.4 µM) to create proximal neighborhoods \u0026nbsp;(outlined in red) and distal neighborhoods (includes area outside of red \u0026nbsp;outlines)., \u003cstrong\u003eE-H\u003c/strong\u003e Composite image of the Iba1/633 nm (red) channel, eGFP/488 (green) channel, and TREM2/546 channel is pseudocolored blue. eighbourhood proximal/distal to plaques: \u003cstrong\u003eE, G\u003c/strong\u003e Outlined cells in color show microglia immunostained with anti-Iba1 (red cells, pink outlines), monocytes immunostained with anti-EGFP (green cells, cyan outlines) [91], hematogenous macrophages double immunostained with anti-Iba1 and anti-EGFP (hMφ – yellow cells, gold outlines) and clusters (a mix of microglia and hematogenous macrophages forming interconnected groupings (large, mixed color, white outlines), usually located around Aβ plaques. \u003cstrong\u003eF, H \u003c/strong\u003eThe same cells as those in E and G are shown for visibility. Iba1+/eGFP- microglia/mMφ (pink), eGFP+/Iba1- monocytes (cyan), hematogenous macrophages/hMφ (gold) and myeloid/microglia/mMφ cell clusters (white). \u003cstrong\u003eE-H \u003c/strong\u003eTREM2 IOD data are derived from the underlying blue signal derived from within the composite image from the pure pseudocolored blue 546 channel image.\u003c/p\u003e","description":"","filename":"Picture6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/c05b674dba83dafead80491a.jpg"},{"id":80451740,"identity":"d3d46c53-6b01-4736-8c04-1a12644f08f2","added_by":"auto","created_at":"2025-04-12 14:16:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2976412,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/b2498bb1-ba05-4cb0-9915-6a042195cf2d.pdf"},{"id":79216419,"identity":"e081b842-dcb3-4a49-8b0a-97f022d946a6","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2550132,"visible":true,"origin":"","legend":"","description":"","filename":"Supplfigure1TREM2ELISAplaqueareaandintensityinplaquesfemales.tif","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/4af7b953b1ce97a3d34735df.tif"},{"id":79217224,"identity":"dd40f884-fe00-4a5a-8275-509a8b0e7294","added_by":"auto","created_at":"2025-03-25 19:05:08","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10168100,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfig2TREM2images5and7monthfemalesrevised.tif","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/b825d74b6b231209f7b1ac01.tif"},{"id":79216417,"identity":"7fb03296-673c-4336-a641-508286114e24","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1690324,"visible":true,"origin":"","legend":"","description":"","filename":"NewSupplementaryFig3PercentcellareaandTREM2IODinfemales.tif","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/5f3be07db761971bf74b6788.tif"},{"id":79216421,"identity":"a4cfb488-d820-48a9-adcb-51cd9925fd79","added_by":"auto","created_at":"2025-03-25 18:57:07","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2719159,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.docx","url":"https://assets-eu.researchsquare.com/files/rs-6222217/v1/087509501f112a49bcef2344.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"TREM2 expression is differentially associated with microglia and hematogenous monocyte/macrophages proximally and distally located to amyloid plaques","fulltext":[{"header":"Highlights","content":"\u003cp\u003e\u0026bull; Cortical TREM2 levels decrease with age\u003c/p\u003e\u003cp\u003e\u0026bull; TREM2 is expressed by microglia and peripheral myeloid cells that interact with Aβ plaques\u003c/p\u003e\u003cp\u003e\u0026bull; TREM2 is reduced in microglia and peripheral myeloid cells interacting with Aβ plaques\u003c/p\u003e\u003cp\u003e\u0026bull; Aβ plaque-interacting microglia and peripheral myeloid cells show ultrastructural differences\u003c/p\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eAlzheimer\u0026rsquo;s disease (AD) is a devastating age-related neurodegenerative disease characterized by the deposition of amyloid-β (Aβ) plaques and the presence of hyperphosphorylated tau tangles in neurons [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. AD results in extensive neuronal and synaptic loss that coincides with progressive cognitive decline and memory deficits [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The accumulation of Aβ plaques in AD triggers the recruitment and accumulation of reactive microglial states at sites associated with Aβ pathology [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroglia are innate immune cells of the brain derived from the embryonic yolk sac. In their surveillant state, they survey their microenvironment, maintain homeostasis, and perform various physiological functions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the presence of pathogens, injury, or ongoing neurodegeneration, such as AD pathology, danger-associated molecular patterns engage receptors on microglia, triggering the release of proinflammatory cytokines that transform microglia at the structural and functional levels [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In recent years, the term \u0026lsquo;disease-associated microglia\u0026rsquo; or DAM has been applied to a specific state of microglia found proximal to areas of pathology, such as Aβ plaques, in the context of neurodegenerative diseases such as AD [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. While DAMs engage in the phagocytosis of cellular debris, including dystrophic and dying/dead neurons, they can also actively promote inflammation, thus exacerbating cellular damage and neurotoxicity [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Ultrastructural studies in the context of AD pathology have identified an additional microglial state: dark microglia. These cells associate with Aβ plaques and dystrophic neurites, engulf fibrillar Aβ, and present various markers of cellular stress and metabolic alterations. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, these cells were recently shown to activate the integrated stress response and perform a detrimental role in AD pathology [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], but their temporal involvement remains to be further defined.\u003c/p\u003e \u003cp\u003eOver the course of AD pathology, Aβ plaques and accompanying AD pathology, including chronic inflammation, cytotoxicity and neurodegeneration, persist and intensify despite the steady recruitment and accumulation of disease-associated microglial states, including DAMs and dark microglia. These findings suggest that with increasing exposure to inflammatory stimuli, these cells become unable to effectively engage in phagocytosis [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The inability to effectively phagocytose Aβ plaques and cellular debris may be caused by excessive debris already present inside the cells, particularly within their lysosomes, which may become enlarged, thereby reducing their capacity to degrade debris in their environment [\u003cspan additionalcitationids=\"CR17 CR18\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The mechanisms whereby disease-associated microglial states are rendered ineffective at phagocytosis are thought to involve dysfunctional Aβ interactions with receptor complexes expressed on microglia, including Aβ binding to triggering receptor expressed on myeloid cells 2 (TREM2) and its adaptor tyrosine kinase receptor binding protein (TyroBP) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], leading to cell senescence [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This elicits proinflammatory responses recruiting other immune-sensing receptors, such as Toll-like receptor (TLR) 4 and TLR6, to trigger the release of additional proinflammatory cytokines into the extracellular space [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In turn, persistent proinflammatory signaling disrupts Aβ phagocytosis by downregulating microglial phagocytic receptors and enzymes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Thus, microglia can be beneficial in the early stages of AD by engaging in phagocytosis and Aβ clearance. Eventually, owing to continued detrimental Aβ accumulation, microglia take on a more pathological role as they become exhausted and their functions are altered, which ultimately diminishes their ability to clear Aβ plaques.\u003c/p\u003e \u003cp\u003eIt is unknown how or when microglia shift from a neuroprotective phenotype to a neurotoxic phenotype and how Aβ triggers opposite responses from the same cell population. One possibility is that the cells that accumulate around Aβ plaques comprise not only diverse cell states but also cell types that share similar morphological characteristics. A recent study using single-cell RNA sequencing demonstrated that DAMs are composed of a mixture of two ontogenetically and functionally diverse cell populations. Both cell populations are found near Aβ plaques in AD pathology. However, one population is embryonically derived and appears to be neuroprotective, whereas the other population is derived from infiltrating monocytes that differentiate into hematogenous macrophages (hMφs) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This finding is consistent with recent findings from our group, demonstrating the presence of both microglia/microglia-derived macrophages (mMφs) and hMφs aggregating around Aβ plaques [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBoth DAM cell populations express TREM2, a cell surface transmembrane glycoprotein with a V-immunoglobulin extracellular domain and a cytosolic tail [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] that is highly expressed on myeloid cells, including microglia and peripheral tissue-resident macrophages [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. TREM2 is beneficial in the early stages of AD but detrimental at later stages. Indeed, elevated TREM2 has been associated with increased susceptibility to late-onset AD [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. TREM2 regulates inflammatory responses by increasing phagocytic activity [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and its expression is modulated by inflammation in the brain. The presence and accumulation of Aβ plaques promote toxicity in the proximal extracellular space and drive increased TREM2 cell surface expression [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. One of the ligands for TREM2 is Aβ, which is known to bind TREM2 and trigger downstream signaling [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The relationship between inflammation and TREM2 is complex, with \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e studies demonstrating conflicting results. \u003cem\u003eIn vitro\u003c/em\u003e, anti-inflammatory signaling increases TREM2 expression, whereas proinflammatory signaling decreases TREM2 expression [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. In contrast, \u003cem\u003ein vivo\u003c/em\u003e studies have shown increased TREM2 expression in transgenic mouse models of Aβ and tau pathology [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and in patients with AD [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the current study, our goal was threefold. First, we measured TREM2 expression within distinct immune cell populations, including microglia and mMφs, monocytes and hMφs, that aggregate around Aβ plaques to determine which cell populations express the most TREM2 and whether the pattern of TREM2 expression changes over time and with AD progression. We chose mice that present Aβ pathology at the ages of 5 and 7 months because we showed previously in our \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e x 5XFAD F1 (L5F) transgenic mouse model that 5 months is the age that coincides with initial cognitive deficits in spatial learning and by 7 months the cognitive deficits and inflammatory responses in males and females was approximately equal [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Second, we compared the levels of TREM2 expression in cell populations localized proximally to Aβ plaques with those in cell populations located farther from Aβ plaques. The TREM2-positive cell populations were classified on the basis of phenotypic protein markers for microglia, monocytes, hMφs and \u0026lsquo;clusters\u0026rsquo; composed of both microglia and hMφs, forming tightly interconnected groupings around Aβ plaques. Third, we established a TREM2 immunolabeling protocol compatible with electron microscopy (EM) to identify and provide insights into the cellular and subcellular features of TREM2-positive myeloid cells in association with Aβ plaques and dystrophic neurons. We also compared microglia and hMφs/monocytes at the ultrastructural level, quantifying their ultrastructural features, which are indicative of phagocytosis and cellular stress, and their interactions with the parenchyma. These experiments were performed via the F1 cross between the 5xFAD mouse model of AD pathology and the \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e mouse model, enabling microglia and reactive mMφs to be distinguished from hMφs on the basis of specific expression of enhanced green fluorescence protein (EGFP) in mature granulo-myelomonoctic cells.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eTREM2 protein quantification in the cerebral cortex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall TREM2 protein levels were measured by via ELISA in homogenates from the cerebral cortex of L5F\u003csup\u003e+\u003c/sup\u003e and L5F\u003csup\u003e-\u003c/sup\u003e male mice at the ages of 1.5, 3, 5, and 7 months. In general, TREM2 protein levels decreased with increasing age. In L5F\u003csup\u003e+\u003c/sup\u003e male mice, significantly more TREM2 protein was detected in the cortex at the age of 1.5 months than at the age of 5 months (p \u0026lt; 0.0001; Fig. 1A, Supplementary Table 1) and 7 months (p \u0026lt; 0.0001; Fig. 1A, Supplementary Table 1). In addition, in L5F\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emale mice, there was significantly more TREM2 protein at age of 3 months than at 5 months (p = 0.002) and 7 months (p \u0026lt; 0.0001) (Fig. 1A, Supplementary Table 1). Similarly, in L5F\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e mice, there was significantly more TREM2 protein at age of 1.5 months than at 5 months (p = 0.009), 7 months (p = 0.014), at age of 3 months than at 5 months (p = 0.036) and 7 months (p = 0.05; Fig. 1A, Supplementary Table 1). Comparable data for L5F\u003csup\u003e+\u003c/sup\u003e and L5F\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e female mice can be found in Supplementary Fig. 1A and Supplementary Table 1. The decrease in TREM2 expression with age in our AD model is consistent with the reports of others, although this decrease is somewhat dependent on the mouse models studied [38,39]. TREM2 protein levels may decrease in the brain with disease progression, possibly due to movement from the brain to the cerebrospinal fluid and blood circulation during AD progression. How TREM2 expression responds to brain inflammation is controversial, as the \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e results differ [35]. Indeed, a recent study revealed increased soluble TREM2 in the plasma of patients with AD compared with healthy controls [40].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePercent area of A\u0026beta;\u003c/strong\u003e \u003cstrong\u003eplaques and TREM2 levels\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003enear\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;A\u0026beta;\u003c/strong\u003e \u003cstrong\u003eplaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe percentage area of A\u0026beta; plaques in the cerebral cortex was significantly greater in L5F\u003csup\u003e+\u003c/sup\u003e males at the age of 7 months than in those at the age of 5 months (Fig. 1B, 3 p = 0.042; Supplementary Table 1). Similar data were obtained for L5F\u003csup\u003e+\u003c/sup\u003e females, as presented in Supplementary Table 1 and Supplementary Fig. 1B. There was a tendency toward increased TREM2 intensity in the area proximal to A\u0026beta; plaques in male mice, with greater intensity observed at the age of 7 months than at 5 months (Fig. 1C, p = 0.094; Table 1). However, the corresponding TREM2 intensity data in the area proximal to the A\u0026beta; plaques in L5F\u003csup\u003e+\u003c/sup\u003e females were significantly different, as presented in Supplementary Fig. 1C and Supplementary Table 1. The increased accumulation of A\u0026beta; plaques in older L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice is consistent with our previous findings, reflecting the sex differences we previously reported in this mouse model [27], which represent an important hallmark of AD pathology[41].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePercent area of microglial and hematogenous myeloid cells in proximal and distal neighborhoods relative to A\u0026beta; plaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe examined the percentage area of cells known to accumulate near A\u0026beta; plaques in AD, including microglia/mM\u0026phi;s, monocytes, hM\u0026phi;s and clusters. We also analyzed the percent areas of the clusters.\u003c/p\u003e\n\u003cp\u003ewhich were defined as a mixture of mM\u0026phi; and hM\u0026phi;, forming tightly interconnected networks in the vicinity of A\u0026beta; plaques.\u003c/p\u003e\n\u003cp\u003eThe purpose of these analyses was to measure the area occupied by each cell type in proximal and distal plaque neighborhoods. We identified microglia/mM\u0026phi;s as Iba1\u003csup\u003e+\u003c/sup\u003eEGFP\u003csup\u003e-\u003c/sup\u003e, monocytes as Iba1\u003csup\u003e-\u003c/sup\u003eEGFP\u003csup\u003e+\u003c/sup\u003e and hM\u0026phi;s as Iba1\u003csup\u003e+\u003c/sup\u003eEGFP\u003csup\u003e+\u003c/sup\u003e. Clusters were defined as mixtures of mM\u0026phi;s and hM\u0026phi;s that formed tightly interconnected networks in the vicinity of A\u0026beta; plaques. The percentage area of microglia/mM\u0026phi;s\u0026nbsp;appeared greater in proximal A\u0026beta; plaques\u0026nbsp;than in\u0026nbsp;distal neighborhoods at ages 5 and 7 months in L5F\u003csup\u003e+\u003c/sup\u003e male mice, but the difference was significant only at 5 months (Fig. 2, 3A, p = 0.039; Supplementary Table 1). This finding is consistent with other studies demonstrating that microglia and mM\u0026phi;s are attracted to areas of pathology and A\u0026beta; plaques and are among the first responders in the clearance of cellular debris [5]. In contrast, no significant differences in the percent area of microglia/mM\u0026phi; were observed at the age of 7 months between the proximal and distal neighborhoods or between the ages of 5 months and 7 months within the proximal and distal neighborhoods in L5F\u003csup\u003e+\u003c/sup\u003e males. Data from L5F\u003csup\u003e+\u003c/sup\u003e females are presented, with the same trends shown in Supplementary Fig. 2 and Supplementary Fig. 3A and Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003eThe percentage area of EGFP\u003csup\u003e+\u003c/sup\u003eIba1\u003csup\u003e-\u003c/sup\u003e monocytes in L5F\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emale mice was significantly greater at the age of 7 months than at the age of 5 months in both the proximal (p = 0.006) and distal (p = 0.004) neighborhoods (Fig. 2, 3B, Supplementary Table 1). Similar data for L5F\u003csup\u003e+\u003c/sup\u003e females are presented in Supplementary Table 1 and Supplementary Fig. 2 and 3B. Here, too, there was a significant increase in L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e females in the proximal neighborhood in keeping with the expected sex differences that we observed in our model. Similarly, the percentage area of EGFP\u003csup\u003e+\u003c/sup\u003eIba1\u003csup\u003e+\u003c/sup\u003e hM\u0026phi;s in male L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u0026nbsp;\u003c/strong\u003emice was significantly greater at 7 months than at 5 months of age (p =0.021)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.021) and distal (p = 0.003) neighborhoods (Fig. 2, 3C; Supplementary Table 1). This was observed only in the proximal neighborhoods in the corresponding L5F\u003csup\u003e+\u003c/sup\u003e female data (Supplementary Fig. 2 and Supplementary Fig. 3C, Supplementary Table 1). The greatest cortical area of monocytes and hM\u0026phi;s was in L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice at older ages, suggesting that increasing inflammation and cytotoxicity in AD may trigger the infiltration of peripheral myeloid cells into the brain.\u003c/p\u003e\n\u003cp\u003eCompared with those in the distal neighborhoods, the percentages of myeloid/microglia/mM\u0026phi; cell clusters in the proximal neighborhoods were significantly greater in male L5F+ mice at the ages of 5 months (p \u0026lt; 0.0001) and 7 months (p = 0.0003; Fig. 2, 3D; Supplementary Table 1). Very similar data from female L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice are presented in Supplementary Table 1 and Supplementary Fig. 2 and 3D. These data parallel the data for Iba1\u003csup\u003e+\u003c/sup\u003eEGFP\u003csup\u003e-\u003c/sup\u003e microglia/mM\u0026phi;s shown in Fig. 3A, indicating that the area occupied by microglia/mM\u0026phi;s is greater than that occupied by EGFP\u003csup\u003e+\u003c/sup\u003e monocyte/hM\u0026phi; cells, as shown when the scale range of the area for each cell type (Y-axis. Fig. 3A-C) is compared. Thus, although infiltrating monocytes and monocyte-derived hM\u0026phi;s contribute to the cellular inflammatory response in regions most proximal to A\u0026beta; plaques, they do not appear to play a dominant role.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunoreactivity\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eof\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;TREM2 in cells from proximal and distal neighborhoods relative to A\u0026beta; plaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo link TREM2 expression with cellular morphology, we next measured the integrated optical density (IOD), which is a combination of the cellular area and signal intensity, in microglia/mM\u0026phi;, monocytes, hM\u0026phi;s and clusters in the cortex of L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice at the ages of 5 and 7 months. The purpose of the analysis was to determine the expression of TREM2 within each cell type and\u003c/p\u003e\n\u003cp\u003etime points. The TREM2 IOD was greater in distal microglia/mM\u0026phi; than in\u0026nbsp;proximal microglia/mM\u0026phi;s\u0026nbsp;in relation to A\u0026beta;\u0026nbsp;plaques in L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e males at the age of 5 months (Fig. 2, 3E, p = 0.016; Supplementary Table 1). The trend in the TREM2 IOD was similar at 7 months of age, but the difference was not significant. Comparable female data can be found in Supplementary Fig. 2, Supplementary Fig. 3E and Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003eThe TREM2 IOD in monocytes increased with age and disease progression and was more abundant in distal neighborhoods than in proximal neighborhoods. In male L5F\u003csup\u003e+\u003c/sup\u003e mice, the TREM2 IOD in monocytes significantly increased from the ages of 5 months to 7 months in the proximal (Fig. 2, 3F, p = 0.008; Supplementary Table 1) and distal (Fig. 3F, p = 0.008; Supplementary Table 1) neighborhoods. Furthermore, TREM2 intensity was significantly greater in monocytes located distal than in those located proximal to A\u0026beta; plaques at both 5 months of age (Fig. 2, 3F, p = 0.021; Supplementary Table 1) and 7 months of age (Fig. 2, 3F, p = 0.021; Supplementary Table 1). Comparable data showing the TREM2 IOD in monocytes from L5F\u003csup\u003e+\u003c/sup\u003e females followed the same patterns of significant differences presented in Supplementary Fig. 2, Supplementary Fig. 3F and Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003eThe TREM2 IOD in\u0026nbsp;hM\u0026phi;s\u0026nbsp;was significantly greater in distal\u0026nbsp;neighborhoods than in\u0026nbsp;proximal neighborhoods at\u0026nbsp;the\u0026nbsp;age\u0026nbsp;of\u0026nbsp;7 months in L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e males (p = 0.007; Fig. 2, 3G Supplementary Table 1). In addition, the TREM2 IOD in hM\u0026phi;s was greater at 7 months than at 5 months within the distal neighborhoods in L5F\u003csup\u003e+\u003c/sup\u003e males (p = 0.009; Fig. 2, 3G; Supplementary Table 1). Comparable data in L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e females showing TREM2 intensity in hM\u0026phi;s can be viewed in Supplementary Fig. 2 and Supplementary Fig. 3G and Supplementary Table 1.\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe increased\u0026nbsp;TREM2 expression in microglia/mM\u0026phi;s, monocytes and\u0026nbsp;hM\u0026phi;s\u0026nbsp;in distal\u0026nbsp;plaques\u0026nbsp;compared\u0026nbsp;with that in proximal plaques\u0026nbsp;suggests that chronic exposure to A\u0026beta; in a\u0026nbsp;proinflammatory\u0026nbsp;environment may\u0026nbsp;reduce\u0026nbsp;the expression of TREM2 in proximal cells, rendering them unable to perform phagocytosis\u0026nbsp;effectively. A recent study demonstrated that exposure to inflammatory stimuli significantly reduced TREM2 expression in peripheral monocytes\u0026nbsp;[40]. It is possible that inflammation, driven by exposure to high levels of A\u0026beta;, contributes to a reduction in cortical TREM2 in older L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice with more advanced disease pathology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; In contrast to TREM2 expression in individual cell populations, a greater TREM2 IOD was observed in proximal clusters than in distal clusters at the ages of 5 months (Fig. 2, 3H, p = 0.035; Supplementary Table 1) and 7 months (p = 0.05; Fig. 2, 3H; Supplementary Table 1) in L5F\u003csup\u003e+\u003c/sup\u003e males, but the differences were small and reached significance at only 5 months. Comparable data showing TREM2 intensity in clusters from female L5F\u003csup\u003e+\u003c/sup\u003e mice are presented in Supplementary Fig. 2, Supplementary Fig. 3H and Supplementary Table 1. Clusters, mostly located proximally to A\u0026beta; plaques, may represent a functional TREM2 population of DAMs actively engaged in the phagocytosis of A\u0026beta; plaques and cellular debris in the immediate areas surrounding plaques.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUltrastructural features of TREM2\u003csup\u003e+\u003c/sup\u003e myeloid cells located near\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eA\u0026beta;\u003cem\u003e\u0026nbsp;\u003c/em\u003eplaques\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe then characterized TREM2-expressing cells at the nanoscale via immunocytochemical EM to reveal their ultrastructural features and gain insights into their disease-associated states and roles. In the cingulate cortex of 7-month-old L5F\u003csup\u003e+\u003c/sup\u003e males, both TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e cells with myeloid ultrastructural features directly interact with A\u0026beta; plaques and dystrophic neurites (Fig. 4). The presence of TREM2\u003csup\u003e+\u003c/sup\u003e and TREM2\u003csup\u003e-\u003c/sup\u003e cells contacting dystrophic neurites provides evidence that different populations of macrophages coexist in AD mouse models. In TREM2+ cells, we detected an abundance of phagosomes and lysosomes, indicating their active role in phagocytosis.,\u003c/p\u003e\n\u003cp\u003eThese ultrastructural features are similar to those of dark microglia. The TREM2\u003csup\u003e+\u003c/sup\u003e cells further contained dystrophic mitochondria (Fig. 4), another feature observed in dark microglia [14], suggesting a state of cellular stress and metabolic transition from oxidative phosphorylation to glycolysis [42,43]. In addition, as in our previous investigations, APP-PS1 mice and 5xFAD mice presented the dark features of an electron-dense cytoplasm and nucleoplasm, accompanied by cellular stress markers [14]. Considering the small number of observed dark microglia, it was not possible to perform an analysis of TREM2 expression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eUltrastructural features of myeloid cells near\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eA\u0026beta;\u0026nbsp;plaques and dystrophic neurites\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, we performed a quantitative ultrastructural analysis of EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells (hM\u0026phi;s and monocytes, excluding neutrophils on the basis of ultrastructural features) and EGFP\u003csup\u003e-\u003c/sup\u003e cells (microglia) from 7-month-old male L5F\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e mice to compare their ultrastructural features and interactions with parenchymal elements to provide additional insights into their disease-associated states and roles. Dark features were also examined. This analysis was performed in the cingulate cortex to examine myeloid cells in contact with A\u0026beta; plaques and/or dystrophic neurites.\u003c/p\u003e\n\u003cp\u003eAt the ultrastructural level, significant differences in terms of mitochondrial structural integrity, phagocytosis and digestion of membrane debris were detected between the EGFP+ myeloid cells and the EGFP- microglia/mM\u0026phi;s (Fig. 5). Compared with EGFP- myeloid cells, EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells presented a significantly greater percentage of altered mitochondria, i.e., dystrophic, holey, and electron-lucent mitochondria (Fig. 5A-C, Table 1; [EGFP\u003csup\u003e+\u003c/sup\u003e: 31.06 \u0026plusmn; 5.31% \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e: 17.52 \u0026plusmn; 3.29%, p = 0.0401]). PLEASE INSERT TABLE 1 NEAR THIS AREA OF TEXT-Altered mitochondria were identified by the deterioration of their double membrane, cristae, or presence of electron-lucent patches or holes within their interior. No significant differences were found between the cell populations in terms of their abundance of altered or elongated mitochondria (Table 1). These findings suggest that hM\u0026phi;s/monocytes may be more susceptible to metabolic dysfunction and cellular stress\u0026nbsp;than\u0026nbsp;microglia/mM\u0026phi;s are\u0026nbsp;in L5F\u003csup\u003e+\u003c/sup\u003e mice. However, other well-defined ultrastructural markers of cellular stress, including ER and Golgi cisternae dilation [14,44], did not differ between cell populations (Table 1). Although the small number of dark microglia prevented quantitative analysis, these cells were not found to be EGFP\u003csup\u003e+\u003c/sup\u003e in these samples.\u003c/p\u003e\n\u003cp\u003eIn terms of phagocytosis and membrane debris digestion, EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells had significantly more unbound membrane inclusions located within their cytoplasm than EGFP\u003csup\u003e-\u003c/sup\u003e microglial/mM\u0026phi; cells did (Fig. 5D-F) [EGFP\u003csup\u003e+\u003c/sup\u003e: 1.16 \u0026plusmn; 0.25 \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e: 0.370 \u0026plusmn; 0.121, p = 0.0100]. EGFP\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e myeloid cells and EGFP\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e microglia/mM\u0026phi; did not differ significantly in their abundance of phagosomes containing membrane debris [EGFP\u003csup\u003e+\u003c/sup\u003e: 0.31 \u0026plusmn; 0.12 \u003cem\u003evs\u003c/em\u003e EGFP\u003csup\u003e-\u003c/sup\u003e: 0.07 \u0026plusmn; 0.051, p = 0.0976] (Table 1). Compared with those within unbound membrane inclusions, the membranes within phagosomes were circular and enclosed by a defined membrane (Figure 5D, E). Interestingly, when the total membrane load was investigated, including that of unbound membranes and membranes contained within phagosomes, EGFP\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e myeloid cells had significantly more total membrane inclusions than EGFP\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e microglia/mM\u0026phi; did (Fig. 5D-G, Table 1 [EGFP\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e: 1.469 \u0026plusmn; 0.280 \u003cem\u003evs\u003c/em\u003e EGFP\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e: 0.444 \u0026plusmn; 0.123, p = 0.0027]). This finding suggests that in L5F\u003csup\u003e+\u003c/sup\u003e mice, EGFP\u003csup\u003e+\u0026nbsp;\u003c/sup\u003emyeloid cells phagocytose more cellular materials than EGFP\u003csup\u003e-\u0026nbsp;\u003c/sup\u003emicroglia/mM\u0026phi;s do. Analysis of cell‒cell interactions also revealed that EGFP\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003ecells were more likely to be in direct contact with other EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells (EGFP\u003cstrong\u003e\u003csup\u003e+\u003c/sup\u003e\u003c/strong\u003e 0.1875 \u0026plusmn; 0.0833 \u003cem\u003evs\u003c/em\u003e EGFP\u003cstrong\u003e\u003csup\u003e-\u003c/sup\u003e\u003c/strong\u003e 0, p = 0.0434), thereby forming myeloid clusters (Fig. 5H, I). These results indicate that myeloid cells present ultrastructural differences from those of microglia when they are found in proximity to A\u0026beta; plaques and dystrophic neurites.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn the present study, we demonstrated that overall TREM2 protein levels decreased with age in the cerebral cortex of our \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e x 5XFAD F1 transgenic mouse model. In addition, our detailed anatomical examination revealed that TREM2 expression in older mice was most abundant in Aβ-associated cell clusters comprising a mixture of intertwined resident reactive microglia/mMφ and hematogenous EGFP\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e myeloid cells proximal to Aβ plaques. TREM2 expression was highest overall for the cells observed within clusters contacting Aβ plaques as opposed to individual cells. Moreover, ultrastructural analysis confirmed that TREM2\u003csup\u003e+\u003c/sup\u003e cells interact directly with Aβ plaques and dystrophic neurites. Similarly, TREM2\u003csup\u003e-\u003c/sup\u003e cells were also found to be near Aβ plaques and dystrophic neurites. Myeloid cells expressing TREM2 presented markers of cellular stress and metabolic alterations. In addition, differences in these markers were quantified between microglia and peripheral myeloid cell populations. While dark microglia/myeloid cells were observed in these samples, as in previous studies conducted in APP-PS1 and 5xFAD mice, they were not found to be EGFP\u003csup\u003e+\u003c/sup\u003e. These cells are known to change in number with disease progression, which warrants further investigation.\u003c/p\u003e \u003cp\u003eMicroglia are the primary cells involved in Aβ clearance. APP may be a proinflammatory receptor on microglia that regulates their ability to acquire a proinflammatory phenotype in mouse models of AD pathology [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Microglial TLR4 signaling is altered in TgAPP/PS1 mice [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and this change may contribute to Aβ accumulation in the brain. TREM2 signaling helps protect against AD pathology, and several TREM2 variants decrease the binding between TREM2 and its ligands, resulting in an increased association with increased AD risk [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. TREM2 is essential for microglial phagocytic function and response to neurodegeneration cues [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The level of TREM2 expression is associated with the rate of microglial phagocytosis [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. \u003cem\u003eIn vitro\u003c/em\u003e, when TREM2 expression is increased in bone marrow-derived myeloid precursor cells, the phagocytosis rate of apoptotic neurons, cellular debris and bacteria or bacterial products is also increased [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The loss of TREM2 in microglia/mMφs and other TREM2-expressing cells, such as peritoneal macrophages, can also result in a decreased rate of phagocytosis [\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. \u003cem\u003eIn vivo\u003c/em\u003e, TREM2-knockout mice exhibit reduced reactivity of microglia and other phagocytes [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In a multiple sclerosis mouse model, TREM2-transduced bone marrow-derived myeloid precursor cells further presented enhanced phagocytic activity [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA meta-analysis revealed that soluble TREM2 levels are elevated in the early stages of AD and attenuated in the subsequent dementia stage [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. This finding is consistent with our data demonstrating that the overall level of TREM2 in the cortex decreases with age, with higher TREM2 levels in younger L5F\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e mice and a significant decrease in TREM2 in older mice.\u003c/p\u003e \u003cp\u003eWhen TREM2 expression was examined in the context of being proximal or distal to Aβ plaques, an apparent discrepancy was found. TREM2 expression in Aβ-associated cell clusters was greater than that in individual microglial and hematogenous subsets in both the proximal and distal neighborhoods. Furthermore, TREM2 expression was greater in clusters proximal to plaques. Outside the clusters, TREM2 expression was greater in distal neighborhoods in microglia/mMφs, monocytes and hMφs. The reason for this apparent discrepancy may be that hMφs and mMφs respond to the binding of TREM2 with soluble Aβ ligands, which in turn increases TREM2 expression and activates TyroBP to stimulate phagocytosis and reduce inflammation. Higher levels of TREM2 appear to drive the aggregation of TREM2\u003csup\u003e+\u003c/sup\u003e cells around Aβ plaques, possibly to prevent toxic levels of Aβ from accumulating near neurons, hence acting as a shield against Aβ neurotoxicity [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The lower expression of TREM2 in individual microglia/mMφs and hMφs proximal to Aβ plaques is consistent with recent \u003cem\u003ein vitro\u003c/em\u003e findings that high levels of a proinflammatory mediator, lipopolysaccharides, drive the downregulation of TREM2 expression [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, as we and others have shown, overall TREM2 brain levels decrease with age, yet Aβ deposition continues, driving increased inflammation and cytotoxicity that accompany AD progression [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Therefore, our understanding of the mechanisms underlying increased TREM2 expression and the regulation of phagocytosis in response to inflammation and the accumulation of Aβ plaques remains incomplete. Microglia may additionally become impaired, resulting in microglial scenscence due to the relentless need for Aβ phagocytosis, which eventually overwhelms and affects their phagolysosomal degradation pathways, preventing them from effectively engaging in the clearance of cellular debris and enzymatic degradation of Aβ [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Microglia are likely to become less efficient at phagocytosis before peripheral myeloid cells arrive, as they will have been exposed to Aβ for longer periods of time. Hence, our data suggest that the ensuing inflammatory signals recruit infiltrating hematogenous myeloid cells (hMφs, monocytes) in an effort to compensate for the decrease in microglial activity.\u003c/p\u003e \u003cp\u003eWhile the area of microglia was greatest in proximal neighborhoods and at earlier time points, the area of monocytes was greatest at later time points. For monocytes, the area of hMφs was significantly greater at older ages. These findings suggest that increased inflammation accompanying AD progression likely drives the infiltration of hematogenous cells into affected brain regions. The area of clusters was significantly larger in proximal neighborhoods than in distal neighborhoods at both ages, suggesting that the cellular aggregates that form these clusters are attracted to AD pathology. Thus, the presence and accumulation of Aβ plaques promote aggregation through TREM2 and accumulation of these cellular clusters. Indeed, evidence suggests that Aβ may be an immunomodulator that intensifies inflammation and drives recruitment of peripheral monocytes and macrophages to sites of neuropathology in mouse models of AD pathology [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Chemokines and chemokine receptors regulate monocyte/macrophage recruitment into the CNS in mouse models of AD pathology [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Circulating monocytes and peripheral blood and tissue macrophages produce high levels of proinflammatory cytokines, including IL-1β\u0026ensp;and IL-18 [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], and represent a vital aspect of innate and adaptive immunity, as they mobilize in response to pathogens, Aβ and cellular debris [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are some clues that the function of hMφs in regions of AD pathology may be beneficial. Previous studies have shown that when CD11b\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e monocytes from wild-type mice are injected into either APP-PSI or Tg2576 transgenic AD pathology mice, they rapidly enter the brain and reduce AD-associated pathology [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Furthermore, peripheral monocyte-derived macrophages infiltrate the brain and accumulate near areas of AD pathology, improving Aβ\u0026ensp;clearance in APP-PS1 mice [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Therefore, the observed increase in TREM2 on hMφs and monocytes at later ages that we observed in the present study may be a mechanism initiated to reduce inflammation associated with AD progression and help increase the phagocytosis of cellular debris and Aβ plaques [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to confirming that both EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells and EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia/mMφ coexist directly adjacent to Aβ plaques and dystrophic neurites, ultrastructural analysis revealed important features of these two populations of innate immune cells. TREM2\u003csup\u003e+\u003c/sup\u003e myeloid cells and microglia exhibited increased phagocytic activity. Consistent with this finding, we detected phagosomes, indicating that TREM2\u003csup\u003e+\u003c/sup\u003e cells are indeed actively engaged in phagocytosis in the vicinity of Aβ plaques and dystrophic neurites. Analysis of the presence of lysosomes in EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells and EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia indicated that the latter tended to have a higher level of lysosomes, which are generally less abundant than phagosomes and more difficult to analyze quantitatively with EM. Both EGFP\u003csup\u003e+\u003c/sup\u003e cells and EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia presented similar numbers of phagosomes that were not significantly different, which suggests that both populations are actively engaged in phagocytosis in the vicinity of Aβ plaques and dystrophic neurites. However, when the total membrane load was determined (unbound membranes plus membranes contained within phagosomes), EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells had significantly more total membranes than EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia did. These findings are consistent with hematogenous myeloid cells and microglia, both contributing to the clearance of Aβ plaques and cellular debris from dystrophic neurites to reduce CNS inflammation at the 7-month time point in our transgenic model when these mice have established cognitive deficits [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur ultrastructural analysis revealed that TREM2\u003csup\u003e+\u003c/sup\u003e cells presented altered mitochondria, which are associated with metabolic alterations, including a transition from oxidative phosphorylation to glycolysis, in myeloid cells and microglia over the course of AD pathology [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These findings suggest that there is a cost in fulfilling the metabolic demand required by phagocytes to actively and continuously clear the constant deposition of Aβ plaques as well as cellular debris from dystrophic neurites. When comparing EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells and EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia, there was also a significantly greater percentage of altered mitochondria that exhibited dystrophic, holey, and electron lucent features in EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells than in EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e microglia. As AD-like disease pathology in mouse models progresses with increased cognitive decline, microglia lose their ability to dampen and control Aβ-driven brain inflammation, resulting in the infiltration of myeloid innate immune cells [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The data presented here suggest that, compared with EGFP- microglia, EGFP\u003csup\u003e+\u003c/sup\u003e myeloid cells may be more susceptible to metabolic dysfunction and cellular stress in L5F\u003csup\u003e+\u003c/sup\u003e mice, likely because they are already highly inflamed in the brain. However, more investigations are needed to validate such an interpretation, as several well-defined ultrastructural markers of cellular stress, including ER and Golgi cisternae dilation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], were not found to differ between the two cell types. These ultrastructural features were previously documented in both the APP-PS1 and 5xFAD mouse models across different ages [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although their numbers were small in the examined region at the examined time point, which precluded quantitative analysis, they were not found to be EGFP\u003csup\u003e+\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our study demonstrated that while overall cortical TREM2 expression decreased with age and AD progression, localized TREM2 expression was most abundant in plaque-associated cell clusters composed of hMφs and mMφs at older ages in L5F\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e mice. Furthermore, the presence and accumulation of Aβ plaques promoted the aggregation and accumulation of these cellular clusters. Our ultrastructural analysis revealed that dark microglia are not EGFP\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e, suggesting that they are not of bone marrow origin. Further analyses revealed that TREM2\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e cells directly interact with Aβ plaques and dystrophic neurites and contain phagosomes, indicating their functional role in phagocytosis. Moreover, EGFP\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e myeloid cells had greater numbers of phagosomes than EGFP\u003csup\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/sup\u003e microglia did, suggesting that phagocytic activity may be more robust in the former than in the latter cell type. Finally, this study demonstrated that increased inflammation and accompanying AD progression drive the infiltration of hMφs and monocytes into the brain, as reflected by increased areas of these cells in proximal plaque neighborhoods in older L5F\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e mice.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003e All procedures involving animals were approved by the Committee for the Care and Use of Laboratory Animals at Western University and adhered to the Canadian Council on Animal Care guidelines (Protocol # 2016\u0026thinsp;\u0026minus;\u0026thinsp;104 and 2008\u0026thinsp;\u0026minus;\u0026thinsp;127). The \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e transgenic mice were generated by the Thomas Graf laboratory [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] on a 129 mouse background and then backcrossed onto C57BL/6 mice. Since 2002, the \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e mouse line has been maintained on the C57BL/6 background via homozygous mating. EGFP is strongly expressed in mature granulomyelomonocytic cells, including neutrophils, monocytes, and hMφ, and to a lesser extent in some peripheral tissue macrophages and dendritic cells [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e transgenic mice were crossed with transgenic 5xFAD mice obtained from the Mutant Mouse Regional Resource Center (MMRRC, University of California, Davis, Davis, CA; stock # 034848). The F1 hybrid offspring were used for all the experiments. The F1 mice were divided randomly into groups according to genotype, age, and sex: lys-EGFP-\u003cem\u003eki\u003c/em\u003e/5xFAD (L5F\u003csup\u003e+\u003c/sup\u003e) and lys-EGFP-\u003cem\u003eki\u003c/em\u003e/5XFAD\u003csup\u003e\u0026ndash;\u003c/sup\u003e (L5F\u003csup\u003e\u0026ndash;\u003c/sup\u003e) littermate controls. Male and female mice were used for all the experiments and were housed with lights on at 07:00 and lights off at 19:00. Groups of mice were aged to predetermined end points of 1.5, 3, 5, or 7 months. Food and water were available \u003cem\u003ead libitum\u003c/em\u003e. All procedures were performed in accordance with ARRIVE guidelines [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTREM2 ELISA\u003c/h2\u003e \u003cp\u003eThe TREM2 protein levels were quantified via ELISA (MyBiosource, San Diego, CA, cat# MBS916554) according to the manufacturer\u0026rsquo;s protocol. Briefly, 100 mg of the cerebral cortex was rinsed with 1X phosphate-buffered saline (PBS), homogenized in 1 ml of 1X PBS and stored overnight at -20\u0026deg;C. Following two freeze‒thaw cycles designed to break the cell membranes, the homogenates were centrifuged for 5 min at 5000 \u0026times; g at 2‒8\u0026deg;C. The supernatant was removed and assayed via TREM2 ELISA according to the manufacturer\u0026rsquo;s instructions. The optical density was read within 5 min on a microplate reader (SpectraMax M5, Molecular Devices, San Jose, CA) set to 450 nm. The TREM2 ELISA data were normalized to total protein for each tissue homogenate as measured by the Bradford protein assay (Bio-Rad Laboratories, Mississauga, ON; cat: 500\u0026ndash;0006).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePreparation of Tissue for Immunofluorescence Staining\u003c/h2\u003e \u003cp\u003eThe mice were deeply anesthetized via an intraperitoneal (i.p.) injection of ketamine (80 mg/kg)/xylazine (20 mg/kg) [ketamine hydrochloride (Narketan), DIN: 02374994, Vetoquinol, Lavaltrie, QC; xylazine (Rompun), Bayer Inc., Missisauga, ON] and were transcardially perfused with ice-cold PBS (pH 7.2), followed by 4% PFA prepared in 1x PBS (pH 7.4). The brains were removed and postfixed for 24 hr in the same fixative and then transferred to increasing concentrations of sucrose solution at 4\u0026deg;C (10%, 20% and 30% sucrose for 24 hr intervals). After the last sucrose incubation, the brains were embedded in optimal cutting temperature (OCT) medium (Sakura Finetek, Inc., Torrance, CA) and frozen at \u0026minus;\u0026thinsp;80\u0026deg;C until sectioning. In preparation for immunofluorescence staining, brains were cryosectioned coronally at a thickness of 16 \u0026micro;m and collected in four sets of alternate sections. The sections were mounted on Superfrost plus-charged slides (Fisher Scientific, Pittsburgh, PA) and stored at \u0026minus;\u0026thinsp;20\u0026deg;C until further processing. Slides containing cortical brain sections were extensively washed in PBS and then blocked in PBS containing 5% normal goat serum (Jackson ImmunoResearch Laboratories, West Grove, PA) and 0.3% Triton X-100 (BioShop Canada Inc., Burlington, ON) for 3 hrs at room temperature (RT). Next, the sections were incubated with the following primary antibodies: rabbit anti-Iba1 (1:300; Abcam, Toronto, ON, Canada, cat # 178846) and sheep anti-TREM2 (1:200; R\u0026amp;D Systems, Minneapolis, MN, USA, cat: AF1729) in the same block overnight at 4\u0026deg;C. The slides were subsequently rinsed in PBS and incubated with the secondary antibodies Alexa Fluor 546 donkey anti-sheep IgG (cat: A21098) and Alexa Fluor 633 goat anti-rabbit IgG (cat: A21070; Life Technologies, Eugene, OR) for 1 hr at RT. Next, the sections were washed in PBS and incubated in a solution containing a rabbit IgG block (negative control rabbit immunoglobulin fraction [Agilent, Santa Clara, CA, cat# X0903]) in PBS at a concentration of 4 mg/ml for 1 hr at RT. This blocking step was added to minimize any binding from the rabbit secondary antibody to the conjugated primary rabbit antibody that was added in the final step. Following the blocking step, the sections were rinsed in PBS and incubated with rabbit anti-EGFP conjugated to Alexa Fluor 488 1:500 (Life Technologies, Eugene, OR, cat# A21311) and mouse anti-beta amyloid (MOAB-2) conjugated to DyLight 405 1:100 (Novus Biologicals, Centennial, CO, cat# NBP2-13075 V) overnight at 4\u0026deg;C. The next day, the slides were washed three times in PBS for 5 min, rinsed in double-distilled water, air-dried at RT for 30 min, and then cover-slipped with Vectashield Hardset mounting medium (Vector Laboratories, Burlingame, CA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eConfocal Microscopy and Image Analyses in Image-Pro\u003c/h2\u003e \u003cp\u003eShort, 5-slice z stacks (0.25 mm thick) of cortical brain sections containing cortical layer 5, as this area of the cortex was previously implicated in AD pathology [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e], were acquired on a Leica-TSC SP8 confocal microscope (Leica Microsystems, Concord, ON, Canada) at 63 X (N.A. \u0026frac14; 1.4) magnification with oil immersion (Leica Microsystems, Concord, ON, Canada). Each z stack had a total of four channels, including Alexa 405 to visualize Aβ plaques, Alexa 488 for EGFP, Alexa 546 for TREM2 and Alexa 633 for Iba1. A total of 8\u0026ndash;12 z stacks were acquired per animal, and there were 4\u0026ndash;5 mice per group. After careful review of the images, a single layer representing the most intact cells was selected from all the animals for analysis.\u003c/p\u003e \u003cp\u003eFor image data analysis, custom-written macros were created in ImagePro (Media Cybernetics, Inc. Rockville, MD) via machine learning algorithms. Briefly, four channel images were generated: Alexa 405 for Aβ plaques, Alexa 488 for EGFP, Alexa 546 for TREM2 and Alexa 633 for Iba1. An image was created for each channel via the Image-Pro \u0026ldquo;medium edges\u0026rdquo; algorithm, which maintains intact intensity data. The purpose of this step was to connect the microglial processes to each other and their cell bodies where they were in separate z-stack layers. For the cellular and plaque channels, the images were preprocessed through Gaussian filtering (3x3 100% \u0026times; 20 passes) to remove noise and improve cellular object recognition. In addition, a color-composite image was generated using the green EGFP EDF image overlaid on both the red Iba1 channel and the TREM2 channel image, which was pseudocolored pure blue. These images were used to train machine learning to recognize four distinct cell types on the basis of size, color and morphology: monocytes/neutrophils (EGFP-positive, Iba1-negative), hematogenous macrophages (EGFP-positive, Iba1-positive), microglia (EGFP-negative, Iba1-positive) and clusters, which referenced groups of cells in very close proximity to each other and/or touching and were composed of a combination of microglia and hMφ.\u003c/p\u003e \u003cp\u003eBefore generating outlines of the Aβ plaques from the Alexa 405 channel, a binary mask of the eGFP+/Iba1- cells was generated from the green/488 nm channel image and then subtracted from the 405 channel image to remove eGFP+/Iba1- cellular crosstalk that might read as a false positive plaque signal, leaving only the plaque signal visible. Using the Aβ channel image (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eC-D), the outlines of the Aβ plaques were then selected and grown to 200 pixels (28.4 \u0026micro;m), representing the area of the cells proximal to the Aβ plaques (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Areas outside the 200 pixels were designated distal areas in relation to Aβ plaques. These enlarged plaque areas were saved as regions of interest designated \u0026ldquo;plaque neighborhoods\u0026rdquo;. Next, a series of region of interest (ROI) analyses were performed on the composite images. First, the plaque ROIs were reapplied to the merged red, green and blue images (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-H). Using machine learning, outlines for each cell type were generated from the color-composite images and stored as new, cell specific, precisely located ROIs, designated by location as either \u0026ldquo;proximal\u0026rdquo; or \u0026ldquo;distal\u0026rdquo; to the plaques (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). The sum of the IOD and sum of the area of staining was obtained within the outlines of each of the four cell types, both proximally (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eE, F) and distally (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003eG, H) to the plaques. As the TREM2 channel image was pseudocolored pure blue and incorporated when the composite images were generated, blue signal IOD data were used to determine the TREM2 protein content within the outlines of the cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePreparation of Tissue for EM\u003c/h2\u003e \u003cp\u003eThe animals used for the EM experiments received i.p. injections of Methoxy-X04 (Tocris Bioscience, Bristol, United Kingdom; cat# 4920) at a dose of 10 g/kg, enabling the visualization of fibrillar Aβ via fluorescence microscopy for the screening of sections containing Aβ plaques prior to processing via EM [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Twenty-four hours later, the mice were anesthetized via i.p. injection of ketamine (80 mg/kg)/xylazine (20 mg/kg) [ketamine hydrochloride (Narketan), DIN: 02374994, Vetoquinol, Lavaltrie, QC; xylazine (Rompun), Bayer Inc., Missisauga, ON] followed by transcardial perfusion with 75 ml of 3.5% acrolein (Polysciences, Inc., Warrington, PA; cat # 00016) diluted in 1x phosphate buffer (PB): pH 7.4, and 150 ml of 4% paraformaldehyde [PFA (BioShop Canada Inc., Burlington, ON; cat # 30535\u0026ndash;89\u0026thinsp;\u0026minus;\u0026thinsp;4), diluted in 1X PBS: pH 7.4]. Coronal brain sections (50 \u0026micro;m thick) were cut in ice-cold PBS on a vibratome (Leica VT1000S) and stored at -20\u0026deg;C in a cryoprotectant solution [30% glycerol, 30% ethylene glycol, 40% 1x PBS] until further processing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAnti‑GFP and anti-TREM2 immunohistochemistry for EM\u003c/h2\u003e \u003cp\u003eFor EM imaging, sections from 7-month-old L5F\u003csup\u003e+\u003c/sup\u003e and L5F\u003csup\u003e\u0026minus;\u003c/sup\u003e male mice were selected. Three sections containing the cingulate cortex corresponding to bregma levels ranging from \u0026minus;\u0026thinsp;1.91 mm to -2.27 mm were selected on the basis of the stereotaxic atlas by Paxinos and Franklin (4th edition) [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. The sections were washed with PBS three times for 10 min for TREM2 immunolabeling, incubated in citrate buffer for 15 min at 70\u0026deg;C and then washed with PBS three times for 10 min. The samples were then quenched with 0.3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in PBS for 5 min and washed with PBS five times for 5 min. The sections were incubated in 0.1% NaBH\u003csub\u003e4\u003c/sub\u003e for 30 min, followed by five washes of 5 min with PBS. The samples were then incubated in blocking buffer (10% normal donkey serum, 3% bovine serum albumin [BSA], 0.3% Triton X-100) for 1 hr. Next, the sections were incubated overnight at 4\u0026deg;C in blocking buffer with a primary antibody cocktail ([1:1000] rabbit anti-GFP primary antibody (Invitrogen, cat# A11122, or ([1:100] sheep anti-TREM2 primary antibody (R\u0026amp;D Systems, Minneapolis, MN, cat# AF1729)). The next day, after reaching RT, the sections were washed with PBS three times for 10 min and incubated in TBS containing biotinylated donkey anti-rabbit secondary antibody ([1:200] cat# 711\u0026ndash;065\u0026ndash;152, Jackson ImmunoResearch) for 1.5 hr at RT for GFP immunolabeling or TBS with 0.05% Triton X-100 donkey anti-sheep secondary antibody ([1:300] cat# 713\u0026ndash;066\u0026ndash;147, Jackson ImmunoResearch) for 2 hr at RT for TREM2 immunolabeling. The sections were subsequently incubated with avidin-biotin complex solution (Vector Laboratories, Burlingame, CA, USA; cat# PK-6100) [1:100] in TBS for 1 hr at RT. The samples were stained with 0.05% diaminobenzidine (DAB; Millipore Sigma cat# D5905-50TAB) with 0.015% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e in Tris-buffer (TB, pH 8.0) for 5 min at RT. The samples were next fixed in osmium-thiocarbohydrazide-osmium to enhance contrast for scanning electron microscopy [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The sections were incubated in a 1:1 solution of 4% aqueous osmium tetroxide (Electron Microscopy Sciences [EMS], Hatfield, PA, USA, cat# 19170) and 3% potassium ferrocyanide (Bioshop, Burlington, ON, Canada, cat# PFC232.250) in double distilled (dd) H\u003csub\u003e2\u003c/sub\u003eO for 1 hr. The sections were washed with ddH\u003csub\u003e2\u003c/sub\u003eO three times for 5 min and incubated in 1% thiocarbohydrazide (EMS, cat# 2231-57-4) diluted in ddH\u003csub\u003e2\u003c/sub\u003eO for 20 min. After the sections were washed three times for 5 min, they were incubated for 30 min in 2% osmium tetroxide diluted in ddH\u003csub\u003e2\u003c/sub\u003eO and then dehydrated in increasing concentrations of ethanol (two times in 35%, one time in 50%, 70%, 80%, 90%, and three times 100%), followed by three incubations of 5 min in propylene oxide. After dehydration, the sections were flat-embedded in Durcupan ACM resin (Millipore Sigma, cat# 44611\u0026ndash;44614). In brief, the sections were infiltrated with resin at RT overnight. They were carefully placed on a fine layer of resin between 2 sheets of ACLAR\u0026reg; embedding films (EMS, cat# 50425-25) for polymerization at 55\u0026deg;C for 72 hr. After polymerization, a section containing the region of interest was excised and glued to a Durcupan resin block for ultrathin sectioning, sections immunolabeled for GFP were cut via an Ultracut UC7 ultramicrotome (Leica Biosystems), and sections immunolabeled for TREM2 were cut via an ARTOS 3D ultramicrotome (Leica Biosystems). Ultrathin sections of ~\u0026thinsp;75 nm thickness were collected on a silicon nitride chip and placed on sample mounts for SEM. The cells were imaged at a resolution of 5 nm per pixel via a crossbeam 540 or a crossbeam 350 field emission SEM with a Gemini column (Zeiss). Images were exported as TIFF files via Zeiss ATLAS Engine 5 software (Fibics). Examples of TREM2-positive (TREM2\u003csup\u003e+\u003c/sup\u003e) cells from L5F\u003csup\u003e+\u003c/sup\u003e male mice are shown. The cells were sampled in direct contact with Aβ plaques or dystrophic neurites.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eUltrastructural analysis\u003c/h2\u003e \u003cp\u003eMicroglia and hematogenous macrophages were identified by their shared ultrastructural features: their dark irregular cytoplasm, heterogeneous chromatin pattern, distinctive long stretches of endoplasmic reticulum (ER) cisternae and lipidic inclusions (i.e., lipofuscin, lipid bodies or droplets, and lysosomes) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Hematogenous macrophages were specifically identified as immunopositive for EGFP (EGFP+). Microglia were specifically identified as immunonegative for EGFP (EGFP-). Neutrophils can be recognized by their ultrastructural features, which are characterized by a lobulated nucleus with heterochromatin distributed on the edges and euchromatin close to nuclear pores, as well as various types of granules in the cytoplasm [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Only cells contacting Aβ plaques or dystrophic neurites [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] present in the LF5\u003csup\u003e\u003cb\u003e+\u003c/b\u003e\u003c/sup\u003e mouse samples were included in the analysis. The ultrastructural analysis included 8\u0026ndash;14 EGFP\u003csup\u003e+\u003c/sup\u003e cells (hMφ) and 8\u0026ndash;10 EGFP\u003csup\u003e\u003cb\u003e\u0026minus;\u003c/b\u003e\u003c/sup\u003e cells (microglia) per animal, resulting in a total of 32 EGFP\u003csup\u003e+\u003c/sup\u003e cells and 27 EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e cells. The quantitative analysis was performed by a researcher blinded to the experimental conditions via QuPath software. The cytoplasm of each cell was traced manually via the ImageJ extension of QuPath using the freehand tool to ensure accurate delineation of the plasma membrane from surrounding parenchymal elements. The ultrastructural analysis included the assessment of mitochondria, ER cisternae, Golgi apparatus cisternae, lysosomes, lipofuscin granules, nuclear membrane alterations and autophagosomes. These organelles were quantified, and their health status was assessed [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Lysosomes were characterized by their circular shape and either homogenous (primary) or heterogeneous (secondary and tertiary) interior. The primary lysosomes were small and highly circular, whereas the secondary lysosomes were larger. Tertiary lysosomes, the largest type of lysosome, consisted of lipids fused to one or more lipofuscin granules [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Lipids were identified by their highly circular and electron-dense outline, with either a homogenous electron-dense interior or an interior filled with several electron-lucent inclusions. Lipofuscin granules were recognized by their irregular shape, granular appearance, and fingerprint-like pattern [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. The number of phagocytic inclusions (phagosomes) within the cytoplasm was quantified to investigate phagocytic activity. Empty phagosomes have a circular outer membrane and an electron-lucent interior, whereas phagosomes containing debris contained partially digested cellular contents [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. The latter were further divided into phagosomes containing membrane materials and phagosomes containing partially digested cellular contents other than membranes such as synaptic elements. The presence of unbound membranes, i.e., membranes not enclosed within a phagosome and appearing as linear stretches of thin electron-dense membranes inside the cytoplasm, was also quantified. To quantify cellular stress and metabolic dysfunction, the abundance and percentage of unaltered (healthy) compared with altered mitochondria in each analyzed cell determined. Healthy mitochondria were characterized by their electron-dense appearance and intact double membrane and cristae [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Altered mitochondria were classified into one of the following three categories: dystrophic, holey, or electron-lucent. Dystrophic mitochondria had a deteriorated double membrane or cristae, appearing as electron-lucent patches [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Holey mitochondria were donut-shaped [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e], while electron-lucent mitochondria containedcontained a predominantly white interior with fractured cristae [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. The abundance and percentage of nonelongated (measuring\u0026thinsp;\u0026lt;\u0026thinsp;1000 nm in length) compared with elongated (measuring\u0026thinsp;\u0026ge;\u0026thinsp;1000 nm in length) mitochondria were quantified to provide insight into mitochondrial fission‒fusion processes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The ER cisternae were identified by their long thin stretches, and the Golgi cisternae were identified by their set of flattened stacked sacks. The dilated ER and Golgi cisternae were used as markers of cellular stress and were characterized by their swollen electron‒lucent appearance and cisternal diameter, which is \u0026ge;\u0026thinsp;50 nm in length [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Nuclear alterations, including membrane indentations and knots (bundling of the nuclear membrane), were also quantified [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. To gain insight into microglial interactions with parenchymal elements, microglial contacts with axon terminals were recognized by the presence of several synaptic vesicles and dendritic spines combined with the presence of postsynaptic densities and synaptic clefts at both the axon terminal and dendritic spine, were quantified. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Microglial contacts with myelinated axons, both healthy and dystrophic, as well as contacts with other cells, including neurons, astrocytes, oligodendrocytes, myeloid cells (EGFP\u003csup\u003e+\u003c/sup\u003e), microglia (EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e), and blood vessels, were also quantified [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eAll the data were analyzed via GraphPad Prism software (version 9; GraphPad Software, La Jolla, CA) and are expressed as the means +/- standard errors of the means [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. TREM2 ELISA data were analyzed via two-way analysis of variance (ANOVA) [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e] with a mixed model and Tukey\u0026rsquo;s multiple comparisons tests, which were used to compare different time points. Image data were analyzed via two-way ANOVA and Tukey\u0026rsquo;s multiple comparisons tests. For these analyses, the two examined time points (5 and 7 months) and neighborhoods (proximal and distal to Aβ plaques) were compared. The Aβ plaque area and TREM2 area in the Aβ plaque region were analyzed via two-way ANOVA and Tukey\u0026rsquo;s multiple comparisons test, and the results were compared between males at 5 and 7 months. Supplementary Fig.\u0026nbsp;1 contains data showing the Aβ plaque area and TREM2 area in the Aβ plaque regions of females at 5 and 7 months. The normality of the ultrastructural data was tested via the Shapiro‒Wilk test. Comparisons of ultrastructural features between EGFP\u003csup\u003e+\u003c/sup\u003e and EGFP\u003csup\u003e\u0026minus;\u003c/sup\u003e cells were performed via unpaired, two-tailed Student\u0026rsquo;s t tests. The sample size (n) refers to individual cells as previously described to consider intercellular heterogeneity [\u003cspan additionalcitationids=\"CR84\" citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan additionalcitationids=\"CR89\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Statistically significant differences were determined as those for which p \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\le\\:\\)\u003c/span\u003e\u003c/span\u003e 0.05. Details of the ultrastructural analyses are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Details of all other statistical analyses are presented in Supplementary Data Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAβ\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;amyloid β\u003c/p\u003e\n\u003cp\u003eAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Alzheimer's Disease\u003c/p\u003e\n\u003cp\u003eANOVA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;analysis of variance\u003c/p\u003e\n\u003cp\u003eApoE\u0026nbsp; \u0026nbsp;\u0026nbsp;apolipoprotein E\u003c/p\u003e\n\u003cp\u003eAPP\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;amyloid precursor protein\u003c/p\u003e\n\u003cp\u003eBSA\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;bovine serum albumin\u003c/p\u003e\n\u003cp\u003eDAB\u0026nbsp; \u0026nbsp; \u0026nbsp;diaminobenzidine\u003c/p\u003e\n\u003cp\u003eDAM\u0026nbsp; \u0026nbsp;\u0026nbsp;disease-associated microglial\u003c/p\u003e\n\u003cp\u003eEDF\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;extended depth of focus\u003c/p\u003e\n\u003cp\u003eEM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;electron microscopy\u003c/p\u003e\n\u003cp\u003eEMS\u0026nbsp; \u0026nbsp; \u0026nbsp;Electron Microscopy Sciences\u003c/p\u003e\n\u003cp\u003eER\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;endoplasmic reticulum\u003c/p\u003e\n\u003cp\u003ehMφ\u0026nbsp; \u0026nbsp;\u0026nbsp;hematogenous macrophage (derived from monocytes)\u003c/p\u003e\n\u003cp\u003eIba1\u0026nbsp; \u0026nbsp; \u0026nbsp;ionized calcium binding adapter protein 1\u003c/p\u003e\n\u003cp\u003eIOD\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;integrated optical density\u003c/p\u003e\n\u003cp\u003eLF5 \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e × 5XFAD F1 hybrid transgenic mouse\u003c/p\u003e\n\u003cp\u003e\u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e lysozyme M-Enhanced Green Fluorescent Protein-knock in\u003c/p\u003e\n\u003cp\u003emMφ\u0026nbsp; \u0026nbsp; microglia/microglia-derived macrophage\u003c/p\u003e\n\u003cp\u003eOCT\u0026nbsp; \u0026nbsp; \u0026nbsp;optimal cutting temperature\u003c/p\u003e\n\u003cp\u003ePBS\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Phosphate-buffered saline\u003c/p\u003e\n\u003cp\u003ePS1\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;presenilin 1\u003c/p\u003e\n\u003cp\u003eROI\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;region of interest\u003c/p\u003e\n\u003cp\u003eTLR\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Toll-like receptor\u003c/p\u003e\n\u003cp\u003eTREM2\u0026nbsp;triggering receptor expressed by myeloid cells\u003c/p\u003e\n\u003cp\u003eTB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tris buffer\u003c/p\u003e\n\u003cp\u003eTBS\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tris-buffered saline\u003c/p\u003e\n\u003cp\u003eTyroBP tyrosine kinase receptor binding protein\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Drs. Marco and Vania Prado for crossing and breeding the mice needed for this project. We thank Christy Barreira and Corby Fink for their technical and administrative support.\u0026nbsp;We acknowledge that the University of Western Ontario is located in the traditional territories of the Anishinaabek, Haudenosaunee, Lūnaap\u0026eacute;ewak and Chonnonton Nations on lands connected with the London Township and Sombra Treaties of 1796 and the Dish with One Spoon Covenant Wampum. This land continues to be home to diverse indigenous peoples whom we recognize as contemporary stewards of the land. We also acknowledge the lək̓ʷəŋən people whose traditional territory the University of Victoria stands and the Songhees, Esquimalt and WS\u0026Aacute;NEĆ people whose historical relationships with the land continue to this day.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGAD, RJR NK and M-ET conceived and designed the study. NK, KN, FGI, CK, MET and VT participated in data collection and analysis. NK and FGI drafted the manuscript. GAD, JR, M-ET, CK and MET provided critical manuscript revisions. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was supported by funding from the Canadian Health Institutes of Health Research Canadian Consortium on Neurodegeneration in Aging. MET is a Tier 2 Canada Research Chair in \u003cem\u003eNeurobiology of Aging and Cognition\u003c/em\u003e. FGI is a Michael Smith Health Research BC postdoctoral fellow and was supported by a doctoral scholarship from the Mexican Council of Humanities, Science and Technology [CONAHCYT/formerly CONACYT]. The Tremblay laboratory\u0026rsquo;s scanning electron microscope was acquired with a CFI John R. Evans Leaders Fund (#39965).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data sets used or analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eTranslational Neuroscience Group, Robarts Research Institute, University of Western Ontario, 1151 Richmond Street North, London, Ontario N6A 5B7, Canada;\u003csup\u003e2\u003c/sup\u003eDivision of Medical Sciences, Medical Sciences Building, University of Victoria, 9882 Ring Rd, Victoria, BC V8P 3E6 Canada, \u003csup\u003e3\u003c/sup\u003eBiotron, Room Bio 105, Department of Biology, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1, \u003csup\u003e4\u003c/sup\u003eDepartment of Physiology \u0026amp; Pharmacology, Medical Sciences Building, Room 216, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1, \u003csup\u003e5\u003c/sup\u003eDepartment of Microbiology \u0026amp; Immunology, Dental Science Building, Room 3014, University of Western Ontario, 1151 Richmond Street North, London, Ontario, Canada, N6A 5C1\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSelkoe DJ. 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Available from: https://pubmed.ncbi.nlm.nih.gov/30332405/\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Ultrastructural features of GFP\u003csup\u003e+\u003c/sup\u003e \u003cem\u003evs\u003c/em\u003e GFP\u003csup\u003e-\u003c/sup\u003e cells.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMean ± standard error of the mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGFP\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGFP\u003csup\u003e-\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eContacts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCNS cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Astrocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0625 ± 0.0435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6640\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Neurons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Oligodendrocytes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Oligodendrocyte precursors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Another myeloid cell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1875 ± 0.0833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0434\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eParenchymal elements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Axon terminals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.688 ± 0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.704 ± 0.3239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9735\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Dendritic spines\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2500 ± 0.0898\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1852 ± 0.0930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Synaptic clefts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6250 ± 0.1892\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5926 ± 0.1438\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8951\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Healthy myelinated axons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1563 ± 0.0792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1111 ± 0.0815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6941\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Dystrophic myelinated axons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.031 ± 0.1878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7407 ± 0.0859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1906\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Total myelinated axons\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.188 ± 0.2127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8519 ± 0.1275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% Dystrophic myelinated axon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e92.67 ± 3.611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e94.17 ± 4.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7837\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Blood vessel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOrganelles\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLysosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Primary lysosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Secondary lysosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Tertiary lysosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0741 ± 0.0514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1213\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Total lysosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1111 ± 0.0616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePhagosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Empty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1250 ± 0.0594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2222 ± 0.0975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Containing membrane debris\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3125 ± 0.1225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0741 ± 0.0514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Containing debris other than membranes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3438 ± 0.1239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2593 ± 0.1262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6366\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Total phagosomes with content\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6563 ± 0.2182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3333 ± 0.1510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2455\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Total (empty + with content)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7813 ± 0.2407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.5556 ± 0.2157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4950\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Autophagosomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0313 ± 0.0313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.3628\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMitochondria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Unaltered (healthy)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.313 ± 1.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.185 ± 1.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Altered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.938 ± 0.3205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.926 ± 0.4234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9824\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Dystrophic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6875 ± 0.1519\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8889 ± 0.2633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4943\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Holey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2188 ± 0.1165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1724\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Electron-lucent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.031 ± 0.2396\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000 ± 0.2722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9314\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Elongated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9063 ± 0.2026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7407 ± 0.2647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6160\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% Elongated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.492 ± 2.345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.881 ± 1.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEndoplasmic reticulum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Dilated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.656 ± 0.5210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.852 ± 0.6055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8064\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% Dilated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14.69 ± 2.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.21 ± 3.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6841\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGolgi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Dilated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2801\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e% Dilated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000 ± 0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20.00 ± 20.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.7040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Indentations/Protrusions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0316 ± 0.0316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0741 ± 0.0514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Alterations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0313 ± 0.0313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0370 ± 0.0370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9047\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Lipids\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.0625 ± 0.0625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1852 ± 0.0930\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.2658\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e# Lipofuscin granules\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9688 ± 0.3404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000 ± 0.3112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"TREM2, Alzheimer’s disease, Neurodegeneration, Neuroinflammation, Microglia, Monocyte, Macrophage","lastPublishedDoi":"10.21203/rs.3.rs-6222217/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6222217/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAmyloid-β (Aβ) plaque deposition is a feature of Alzheimer\u0026rsquo;s disease. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates inflammatory responses by increasing phagocytic activity, and its expression is modulated by inflammation in the brain. One of the ligands for TREM2 is Aβ. TREM2 is highly expressed on myeloid cells, including microglia and peripheral tissue-resident macrophages. Both microglia and hematogenous macrophages interact directly with Aβ plaques. Using our 5XFAD \u003cem\u003elys\u003c/em\u003e-EGFP-\u003cem\u003eki\u003c/em\u003e transgenic mice, we studied the expression of TREM2 in plaques engaging microglia and infiltrating macrophages. We characterized the expression of TREM2 by measuring the protein level of TREM2 in the cortex at three different time points: 1.5, 3, 5, and 7 months of age. We observed a decrease in TREM2 levels in the cortex with disease progression. TREM2 levels were also lower in cells interacting with Aβ plaques compared to cells far from Aβ plaques. Finally, we performed an ultrastructural analysis of microglia and hematogenous macrophages interacting with plaques, which revealed more dystrophic mitochondria and phagocytosed material in hematogenous macrophages than in microglia.\u003c/p\u003e","manuscriptTitle":"TREM2 expression is differentially associated with microglia and hematogenous monocyte/macrophages proximally and distally located to amyloid plaques","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-25 18:57:02","doi":"10.21203/rs.3.rs-6222217/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f4b542f3-e43e-489a-8a12-e2b1b55439a2","owner":[],"postedDate":"March 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-12T14:08:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-25 18:57:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6222217","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6222217","identity":"rs-6222217","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}