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• W4309593279 abstract "•Microglial-enriched spatial transcriptomics reveals effects of plaque contact•Trem2 among genes only increases in microglia on plaques in AppNLF/NLF (NLF) mice•No increased expression of Trem2 and a small gene module in NLFTrem2R47H/R47H mice•Trem2 module includes: complement C1qa,c; phagosome Plek, Cd68,; lysosome Ctss, Ctsz, Grn Using spatial cell-type-enriched transcriptomics, we compare plaque-induced gene (PIG) expression in microglia-touching plaques, neighboring plaques, and far from plaques in an aged Alzheimer’s mouse model with late plaque development. In 18-month-old APPNL-F/NL-F knockin mice, with and without the Alzheimer’s disease risk mutation Trem2R47H/R47H, we report that expression of 38/55 PIGs have plaque-induced microglial upregulation, with a subset only upregulating in microglia directly contacting plaques. For seven PIGs, including Trem2, this upregulation is prevented in APPNL-F/NL-FTrem2R47H/R47H mice. These TREM2-dependent genes are all involved in phagocytic and degradative processes that we show correspond to a decrease in phagocytic markers and an increase in the density of small plaques in Trem2-mutated mice. Furthermore, despite the R47H mutation preventing increased Trem2 gene expression, TREM2 protein levels and microglial density are still marginally increased on plaques. Hence, both microglial contact with plaques and functioning TREM2 are necessary for microglia to respond appropriately to amyloid pathology. Using spatial cell-type-enriched transcriptomics, we compare plaque-induced gene (PIG) expression in microglia-touching plaques, neighboring plaques, and far from plaques in an aged Alzheimer’s mouse model with late plaque development. In 18-month-old APPNL-F/NL-F knockin mice, with and without the Alzheimer’s disease risk mutation Trem2R47H/R47H, we report that expression of 38/55 PIGs have plaque-induced microglial upregulation, with a subset only upregulating in microglia directly contacting plaques. For seven PIGs, including Trem2, this upregulation is prevented in APPNL-F/NL-FTrem2R47H/R47H mice. These TREM2-dependent genes are all involved in phagocytic and degradative processes that we show correspond to a decrease in phagocytic markers and an increase in the density of small plaques in Trem2-mutated mice. Furthermore, despite the R47H mutation preventing increased Trem2 gene expression, TREM2 protein levels and microglial density are still marginally increased on plaques. Hence, both microglial contact with plaques and functioning TREM2 are necessary for microglia to respond appropriately to amyloid pathology. IntroductionThe importance of the microglial membrane receptor TREM2 in Alzheimer’s disease (AD) is now well known. The initial evidence came from genome-wide association studies (GWAS), which convincingly demonstrated that TREM2 has several variants that increase the risk of reaching the stage of AD diagnosis. TREM2R47H, the most common risk variant, has an effect size similar to that of the APOE4 allele in people of White European descent.1Guerreiro R. Wojtas A. Bras J. Carrasquillo M. Rogaeva E. Majounie E. Cruchaga C. Sassi C. Kauwe J.S. Younkin S. et al.TREM2 variants in Alzheimer's disease.N. Engl. J. Med. 2013; 368: 117-127https://doi.org/10.1056/NEJMoa1211851Crossref PubMed Scopus (1830) Google Scholar,2Jonsson T. Stefansson H. Steinberg S. Jonsdottir I. Jonsson P.V. Snaedal J. Bjornsson S. Huttenlocher J. Levey A.I. Lah J.J. et al.Variant of TREM2 associated with the risk of Alzheimer's disease.N. Engl. J. Med. 2013; 368: 107-116https://doi.org/10.1056/NEJMoa1211103Crossref PubMed Scopus (1593) Google Scholar,3Gratuze M. Leyns C.E.G. Holtzman D.M. New insights into the role of TREM2 in Alzheimer's disease.Mol. Neurodegener. 2018; 13: 66https://doi.org/10.1186/s13024-018-0298-9Crossref PubMed Scopus (189) Google Scholar Considerable work has been undertaken using mouse models carrying familial AD mutations, Trem2 knockout mice, and primary microglial cultures,4Liu W. Taso O. Wang R. Bayram S. Graham A.C. Garcia-Reitboeck P. Mallach A. Andrews W.D. Piers T.M. Botia J.A. et al.Trem2 promotes anti-inflammatory responses in microglia and is suppressed under pro-inflammatory conditions.Hum. Mol. Genet. 2020; 29: 3224-3248https://doi.org/10.1093/hmg/ddaa209Crossref PubMed Scopus (28) Google Scholar reviewed in Gratuze et al. and Kulkarni et al.,3Gratuze M. Leyns C.E.G. Holtzman D.M. New insights into the role of TREM2 in Alzheimer's disease.Mol. Neurodegener. 2018; 13: 66https://doi.org/10.1186/s13024-018-0298-9Crossref PubMed Scopus (189) Google Scholar,5Kulkarni B. Kumar D. Cruz-Martins N. Sellamuthu S. Role of TREM2 in alzheimer's disease: a long road ahead.Mol. Neurobiol. 2021; 58: 5239-5252https://doi.org/10.1007/s12035-021-02477-9Crossref PubMed Scopus (4) Google Scholar revealing that TREM2 pushes microglia away from an inflammatory cytokine-producing phenotype toward an anti-inflammatory phagocytic phenotype4Liu W. Taso O. Wang R. Bayram S. Graham A.C. Garcia-Reitboeck P. Mallach A. Andrews W.D. Piers T.M. Botia J.A. et al.Trem2 promotes anti-inflammatory responses in microglia and is suppressed under pro-inflammatory conditions.Hum. Mol. Genet. 2020; 29: 3224-3248https://doi.org/10.1093/hmg/ddaa209Crossref PubMed Scopus (28) Google Scholar and has been reported to be instrumental in the increased density of microglia around plaques. Moreover, microarray analysis of transgenic mice, carrying familial AD mutations, revealed Trem2 and an array of co-expressed genes to be upregulated in the hippocampus and cortex,6Matarin M. Salih D.A. Yasvoina M. Cummings D.M. Guelfi S. Liu W. Nahaboo Solim M.A. Moens T.G. Paublete R.M. Ali S.S. et al.A genome-wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology.Cell Rep. 2015; 10: 633-644https://doi.org/10.1016/j.celrep.2014.12.041Abstract Full Text Full Text PDF PubMed Scopus (150) Google Scholar a finding repeatedly confirmed with RNA-seq, both in whole tissue7Salih D.A. Bayram S. Guelfi S. Reynolds R.H. Shoai M. Ryten M. Brenton J.W. Zhang D. Matarin M. Botia J.A. et al.Genetic variability in response to amyloid beta deposition influences Alzheimer's disease risk.Brain Commun. 2019; 1: fcz022https://doi.org/10.1093/braincomms/fcz022Crossref PubMed Scopus (29) Google Scholar and in single-cell studies. Such single-cell RNA-seq studies have confirmed patterns of gene expression defining “disease-associated microglia” (DAM) genes8Deczkowska A. Keren-Shaul H. Weiner A. Colonna M. Schwartz M. Amit I. Disease-associated microglia: a universal immune sensor of neurodegeneration.Cell. 2018; 173: 1073-1081https://doi.org/10.1016/j.cell.2018.05.003Abstract Full Text Full Text PDF PubMed Scopus (418) Google Scholar in relation to amyloidβ (Aβ)9Keren-Shaul H. Spinrad A. Weiner A. Matcovitch-Natan O. Dvir-Szternfeld R. Ulland T.K. David E. Baruch K. Lara-Astaiso D. Toth B. et al.A unique microglia type Associated with restricting development of alzheimer's disease.Cell. 2017; 169: 1276-1290.e17https://doi.org/10.1016/j.cell.2017.05.018Abstract Full Text Full Text PDF PubMed Scopus (1882) Google Scholar and Tau pathology.10Lee S.H. Meilandt W.J. Xie L. Gandham V.D. Ngu H. Barck K.H. Rezzonico M.G. Imperio J. Lalehzadeh G. Huntley M.A. et al.Trem2 restrains the enhancement of tau accumulation and neurodegeneration by beta-amyloid pathology.Neuron. 2021; 109: 1283-1301.e6https://doi.org/10.1016/j.neuron.2021.02.010Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar A recent study using spatial transcriptomics in relation to plaque density defined a further overlapping group of genes referred to as plaque-induced genes, PIGs.11Chen W.T. Lu A. Craessaerts K. Pavie B. Sala Frigerio C. Corthout N. Qian X. Lalakova J. Kuhnemund M. Voytyuk I. et al.Spatial transcriptomics and in situ sequencing to study alzheimer's disease.Cell. 2020; 182: 976-991.e19https://doi.org/10.1016/j.cell.2020.06.038Abstract Full Text Full Text PDF PubMed Scopus (192) Google ScholarMost of the mouse studies published have focused on transgenic mice that overexpress familial AD mutations in App and/or Psen1 or Psen2 genes. Moreover, when knockin mice are used, the most popular model has been the AppNL−G-F/NL−G-F (NLGF) mouse,12Saito T. Matsuba Y. Mihira N. Takano J. Nilsson P. Itohara S. Iwata N. Saido T.C. Single App knock-in mouse models of Alzheimer's disease.Nat. Neurosci. 2014; 17: 661-663https://doi.org/10.1038/nn.3697Crossref PubMed Scopus (499) Google Scholar which harbors three familial AD mutations in App and includes a humanized Aβ sequence. Similarly to transgenic models, NLGF mice deposit plaques rapidly and early, such that the most rapid increase in plaque load occurs between 2 and 4 months of age, reaching almost maximal density by 9 months.13Benitez D.P. Jiang S. Wood J. Wang R. Hall C.M. Peerboom C. Wong N. Stringer K.M. Vitanova K.S. Smith V.C. et al.Knock-in models related to Alzheimer's disease: synaptic transmission, plaques and the role of microglia.Mol. Neurodegener. 2021; 16: 47https://doi.org/10.1186/s13024-021-00457-0Crossref PubMed Scopus (9) Google Scholar Sporadic AD develops slowly from midlife into old age, so the reaction of microglia to this rapid rise of plaques in young animals may be very different and less relevant than their response to slow deposition starting later in life. A further difference is that the inclusion of the Arctic mutation in the NLGF mouse within the Aβ sequence results in a more fibrillar form of Aβ causing rapid deposition and probably lower levels of soluble Aβ in the neuropil. Consequently, we suggest that the AppNL−F/NL−F (NLF) mouse12Saito T. Matsuba Y. Mihira N. Takano J. Nilsson P. Itohara S. Iwata N. Saido T.C. Single App knock-in mouse models of Alzheimer's disease.Nat. Neurosci. 2014; 17: 661-663https://doi.org/10.1038/nn.3697Crossref PubMed Scopus (499) Google Scholar is a better model of sporadic AD than the NLGF mouse as, in NLF mice, the Aβ sequence is the same as in the sporadic disease, and the plaques begin to develop slowly in midlife and increase through to at least 24 months of age. Although using these very old mice is inconvenient and increases the cost of studies, the increased relevance of combining slow development and, importantly, the element of old age outweighs these disadvantages. However, until recently, analyzing changes in gene expression was very difficult in NLF mice because, even at 24 months of age, genes such as Trem2 show only modest changes, despite evident synaptic differences and increased microglial density.13Benitez D.P. Jiang S. Wood J. Wang R. Hall C.M. Peerboom C. Wong N. Stringer K.M. Vitanova K.S. Smith V.C. et al.Knock-in models related to Alzheimer's disease: synaptic transmission, plaques and the role of microglia.Mol. Neurodegener. 2021; 16: 47https://doi.org/10.1186/s13024-021-00457-0Crossref PubMed Scopus (9) Google Scholar It is this combination of high cost and low reward that has made NLFs a less popular model, despite the similarity to the progression of human sporadic AD. However, with the introduction of spatial cell-type-enriched transcriptomics, more subtle and direct analysis of plaque-induced microglial gene expression changes becomes possible, without the diluting effects of bulk analysis.Using spatial transcriptomics in this more relevant mouse model, we initially compare microglial-enriched expression of PIGs. PIGs were defined by Chen et al. (2020)11Chen W.T. Lu A. Craessaerts K. Pavie B. Sala Frigerio C. Corthout N. Qian X. Lalakova J. Kuhnemund M. Voytyuk I. et al.Spatial transcriptomics and in situ sequencing to study alzheimer's disease.Cell. 2020; 182: 976-991.e19https://doi.org/10.1016/j.cell.2020.06.038Abstract Full Text Full Text PDF PubMed Scopus (192) Google Scholar in NLGF mice as genes that upregulate in response to plaque density in different brain regions and across multiple cell types. For more than half of these genes, we confirm, in NLF mice, that association with plaque increases expression. Importantly, in a subset of these genes, this only occurs in microglia directly in contact with plaques and not in immediately neighboring regions.We particularly study Trem2 as one of the genes upregulated specifically on plaques in these mice. We compared the effects in NLF mice to NLF mice in which Trem2R47H/R47H is knocked in (NLFTrem2R47H double homozygous mice) and validated our findings at the protein level using immunohistochemistry. The lack of Trem2 upregulation in the NLFTrem2R47H mice could then be used to assess whether increased microglial density at plaques depends on Trem2 genotype. Surprisingly, in NLFTrem2R47H mice, the density of microglia increased considerably, which may be due to a modest increase in TREM2 protein expression, in the absence of increased gene expression.ResultsIn NLF mice, plaques are first detected at 9 to 10 months of age. Deposition then slowly increases through to 24 months of age.13Benitez D.P. Jiang S. Wood J. Wang R. Hall C.M. Peerboom C. Wong N. Stringer K.M. Vitanova K.S. Smith V.C. et al.Knock-in models related to Alzheimer's disease: synaptic transmission, plaques and the role of microglia.Mol. Neurodegener. 2021; 16: 47https://doi.org/10.1186/s13024-021-00457-0Crossref PubMed Scopus (9) Google Scholar In the present study, we investigate the spatial distribution of gene expression in 18-month-old NLF and NLFTrem2R47H mice.For spatial transcriptomics analysis, we labeled plaque pathology and associated glial cells using immunohistochemistry toward TMEM119 (microglia), GFAP (astrocytes), and Aβ40/Aβ42 (plaques) (Figure 1A ). We then selected large regions of interest (ROIs) that were densely filled with plaques and nearby ROIs without plaques (Figures 1Bi and 1Bii). Most plaques in the hippocampus of the NLF mouse hippocampal sections used in this study were found in and around the stratum lacunosum moleculare of CA1–3 and the stratum moleculare of the dentate gyrus (Figure 1Bii). It is thus possible, in each brain section, to define ROIs in which all pixels are within ∼30 μm of a plaque and other ROIs in which no plaques are detected. We then defined cell-type-enriched areas of interest (AOIs) for microglia or astrocytes within each ROI. For the present study, we focused on microglia and determined genome-wide RNA signatures from the following three types of AOIs in NLF and NLFTrem2R47H mice: (1) “on plaque,” all the microglia in the plaque ROIs that colocalized with Aβ (Figure 1Ci); (2) “periplaque,” all the microglia in the plaque ROI that did not colocalize with Aβ (Figure 1Cii); and (3) “away” from plaque, all the microglia in the ROIs without plaques. In addition, ROIs in equivalent positions were studied in wild-type (WT) and Trem2R47H mice, so that the same regions could be compared without plaques. Before collecting RNA signatures from the microglial AOIs, signatures were collected from the regions labeled with the GFAP antibody in order to decrease contamination from overlapping astrocytes. However, it is important to note that the results represent enrichment for microglia rather than selective analysis of microglial genes. Indeed, some highly expressed genes from astrocytes and neurons are also detected in the microglial gene set. Nevertheless, a useful degree of separation between cell types is achieved, as can be seen when comparing the expression of genes previously defined as microglia enriched14Ximerakis M. Lipnick S.L. Innes B.T. Simmons S.K. Adiconis X. Dionne D. Mayweather B.A. Nguyen L. Niziolek Z. Ozek C. et al.Single-cell transcriptomic profiling of the aging mouse brain.Nat. Neurosci. 2019; 22: 1696-1708https://doi.org/10.1038/s41593-019-0491-3Crossref PubMed Scopus (167) Google Scholar,15Zhang Y. Chen K. Sloan S.A. Bennett M.L. Scholze A.R. O'Keeffe S. Phatnani H.P. Guarnieri P. Caneda C. Ruderisch N. et al.An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.J. Neurosci. 2014; 34: 11929-11947https://doi.org/10.1523/JNEUROSCI.1860-14.2014Crossref PubMed Scopus (2831) Google Scholar (Figure S1A) and in principal components analysis (Figure S1B). Note that although TMEM119 has been previously reported to decrease in expression in DAM microglia,9Keren-Shaul H. Spinrad A. Weiner A. Matcovitch-Natan O. Dvir-Szternfeld R. Ulland T.K. David E. Baruch K. Lara-Astaiso D. Toth B. et al.A unique microglia type Associated with restricting development of alzheimer's disease.Cell. 2017; 169: 1276-1290.e17https://doi.org/10.1016/j.cell.2017.05.018Abstract Full Text Full Text PDF PubMed Scopus (1882) Google Scholar,16Grubman A. Choo X.Y. Chew G. Ouyang J.F. Sun G. Croft N.P. Rossello F.J. Simmons R. Buckberry S. Landin D.V. et al.Transcriptional signature in microglia associated with Abeta plaque phagocytosis.Nat. Commun. 2021; 12: 3015https://doi.org/10.1038/s41467-021-23111-1Crossref PubMed Scopus (33) Google Scholar using immunohistochemistry, we found no change in signal intensity at plaque when compared with 50 μm away (Figure S2).Note that standard analysis methods for gene expression have mostly been developed for analysis of postmortem human tissue. This requires complex normalization methods to overcome the problems of heterogeneity in the genetic and environmental background of the subjects, condition of the tissue, cause of death, postmortem interval, and other variables, depending on the source of the tissue. The situation is completely different in mice that have identical genetic backgrounds (except for the genes altered for the experiment) and controlled conditions for environment, diet, killing of the animal, treatment of the tissue, and extraction methods. Consequently, much simpler methods of normalization are sufficient, such as using housekeeping (HK) genes. As this study is concentrating on the microglial AOIs, all data were normalized to Actg1 and Actb. To verify this method, we compared HK normalization with the more standardly used edgeR-based TMM-weighted normalization17Robinson M.D. Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data.Genome Biol. 2010; 11: R25https://doi.org/10.1186/gb-2010-11-3-r25Crossref PubMed Scopus (3964) Google Scholar or Q3 normalization. Comparing the AOI counts normalized with these three methods results in a very high correlation in each case (r > 0.95; p < 0.0001).The data for all PIG genes are available at https://edwardslab.shinyapps.io/MouseacST/.Density of microglia around plaques does not influence analysis of gene expressionAs has frequently been reported, microglia cluster around plaques in both mouse models and human tissue.6Matarin M. Salih D.A. Yasvoina M. Cummings D.M. Guelfi S. Liu W. Nahaboo Solim M.A. Moens T.G. Paublete R.M. Ali S.S. et al.A genome-wide gene-expression analysis and database in transgenic mice during development of amyloid or tau pathology.Cell Rep. 2015; 10: 633-644https://doi.org/10.1016/j.celrep.2014.12.041Abstract Full Text Full Text PDF PubMed Scopus (150) Google Scholar,18Itagaki S. McGeer P.L. Akiyama H. Zhu S. Selkoe D. Relationship of microglia and astrocytes to amyloid deposits of Alzheimer disease.J. Neuroimmunol. 1989; 24: 173-182https://doi.org/10.1016/0165-5728(89)90115-xAbstract Full Text PDF PubMed Scopus (0) Google Scholar,19Medawar E. Benway T.A. Liu W. Hanan T.A. Haslehurst P. James O.T. Yap K. Muessig L. Moroni F. Nahaboo Solim M.A. et al.Effects of rising amyloidbeta levels on hippocampal synaptic transmission, microglial response and cognition in APPSwe/PSEN1M146V transgenic mice.EBioMedicine. 2019; 39: 422-435https://doi.org/10.1016/j.ebiom.2018.12.006Abstract Full Text Full Text PDF PubMed Scopus (13) Google Scholar This is also true in NLF mice, where we have reported that an overall increase in microglial density across the hippocampus of NLF mice only reaches statistical significance at 24 months.13Benitez D.P. Jiang S. Wood J. Wang R. Hall C.M. Peerboom C. Wong N. Stringer K.M. Vitanova K.S. Smith V.C. et al.Knock-in models related to Alzheimer's disease: synaptic transmission, plaques and the role of microglia.Mol. Neurodegener. 2021; 16: 47https://doi.org/10.1186/s13024-021-00457-0Crossref PubMed Scopus (9) Google Scholar In order to ensure that any change in gene expression in our spatial transcriptomics analysis was adequately corrected by the normalization procedure, we checked that expression was not substantially affected by differences in microglial density but truly reflected gene expression per microglial cell. We thus compared the distribution of microglia around individual plaques by comparing the density of IBA1-positive cells (Figures 2A and 2B ) to the expression of the microglial gene Aif1 that codes for IBA1 (Figure 2C). The expression of Aif1 in individual microglial cells would not be expected to increase substantially in response to plaques. As expected, when density of microglia was assessed on plaques and in concentric circles increasing by 10-μm radius out from the plaque edge, there was a substantial increase in density in the proximity of plaques. However, the increase in microglial density was only detectable at the plaque or within the first 10-μm ring around the plaque. By 20 μm, the density had returned to the level far from plaques, which was also not significantly different from the density in WT mice. Despite the >30-fold increase in density of microglia at the plaque, no significant effect of region or genotype was detected in Aif1 expression. Other microglial genes not affected by the vicinity to plaques include Tmem119 and P2y12.Figure 2Microglial density compared with Aif1 expressionShow full caption(A) Microglia were labeled with an antibody against IBA1 (red), plaques with LCOs (not shown), and nuclei with DAPI (white). For NLF mice, a circle was drawn around the circumference of the plaque, and concentric circles were drawn around this central ring with radii increasing by 10 μm. Microglia were counted in the inner circle and each circle of increasing size. A microglial cell touching a circle was considered to lie inside that circle, and density was calculated. For WT mice, a central circle with a 10-μm radius was placed pseudo-randomly to represent similar areas to those assessed in the NLF mice. Microglial density was counted as for NLF mice.(B) Quantification of microglial density in NLF mice reveals a 30-fold higher density on the plaque compared with WT mice; one-way repeated measures ANOVA: main effect of distance, p < 0.0001.(C) the expression of Aif1 (which encodes IBA1) in NLF mice was not significantly increased either compared with WT mice or with distance from plaque. Data are expressed as mean + SEM. n = 6 mice per genotype in (B), and n = 6 NLF, n = 4 WT mice in (C).View Large Image Figure ViewerDownload Hi-res image Download (PPT)It should be noted that for all immunohistochemistry experiments, the plaque has been labeled with luminescent conjugated oligothiophenes (LCOs, “Amytracker”). Use of LCOs will define only deposited Aβ20Hammarstrom P. Simon R. Nystrom S. Konradsson P. Aslund A. Nilsson K.P. A fluorescent pentameric thiophene derivative detects in vitro-formed prefibrillar protein aggregates.Biochemistry. 2010; 49: 6838-6845https://doi.org/10.1021/bi100922rCrossref PubMed Scopus (75) Google Scholar,21Klingstedt T. Aslund A. Simon R.A. Johansson L.B. Mason J.J. Nystrom S. Hammarstrom P. Nilsson K.P. Synthesis of a library of oligothiophenes and their utilization as fluorescent ligands for spectral assignment of protein aggregates.Org. Biomol. Chem. 2011; 9: 8356-8370https://doi.org/10.1039/c1ob05637aCrossref PubMed Scopus (122) Google Scholar,22Klingstedt T. Blechschmidt C. Nogalska A. Prokop S. Haggqvist B. Danielsson O. Engel W.K. Askanas V. Heppner F.L. Nilsson K.P. Luminescent conjugated oligothiophenes for sensitive fluorescent assignment of protein inclusion bodies.Chembiochem. 2013; 14: 607-616https://doi.org/10.1002/cbic.201200731Crossref PubMed Scopus (35) Google Scholar and so is rather more stringent in terms of defining the plaque than the Aβ42 antibody used for the transcriptomics, above which may label more diffuse Aβ around the plaque.Most, but not all, previously defined plaque-induced genes, including Trem2, show significant differences between microglia on plaques and far from plaquesAs a first step in comparing the regional expression of relevant genes in relation to the position of plaques, we compared the microglial-enriched expression of the genes previously defined as PIGs11Chen W.T. Lu A. Craessaerts K. Pavie B. Sala Frigerio C. Corthout N. Qian X. Lalakova J. Kuhnemund M. Voytyuk I. et al.Spatial transcriptomics and in situ sequencing to study alzheimer's disease.Cell. 2020; 182: 976-991.e19https://doi.org/10.1016/j.cell.2020.06.038Abstract Full Text Full Text PDF PubMed Scopus (192) Google Scholar (Figures 3A–3C ).Figure 3Expression of PIGs in relation to plaques in NLF miceShow full caption38 of the 55 PIGs tested in NLF mice show significant main effect of relation to plaque in a two-way repeated measures ANOVA; bar color and dagger symbol represent the result of Tukey post hoc correction for multiple comparisons between relation to plaque and gene.(A) 23 genes were only upregulated when microglia are touching plaques.(B) 11 genes show a graded response in which expression gradually increases from away through to plaque regions.(C) Four genes are equally upregulated in the plaque and periplaque regions, both with increased expression compared with away. For other PIGs, there was no significant effect of relation to plaque (not shown). Data are presented as mean + SEM; n = 6 mice. Transcripts were averaged from one to three AOI per mouse. Y axis is fold change compared with the away region.(D) Pie charts illustrating the percentage of genes that are identified as microglial (green), astrocytic (orange), both (light green), or neither (gray). Cell specificity was assessed according to comparative single-cell RNA-seq analysis from wild-type mice whole brain14Ximerakis M. Lipnick S.L. Innes B.T. Simmons S.K. Adiconis X. Dionne D. Mayweather B.A. Nguyen L. Niziolek Z. Ozek C. et al.Single-cell transcriptomic profiling of the aging mouse brain.Nat. Neurosci. 2019; 22: 1696-1708https://doi.org/10.1038/s41593-019-0491-3Crossref PubMed Scopus (167) Google Scholar or cortex Barres Brain RNA-seq database.15Zhang Y. Chen K. Sloan S.A. Bennett M.L. Scholze A.R. O'Keeffe S. Phatnani H.P. Guarnieri P. Caneda C. Ruderisch N. et al.An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.J. Neurosci. 2014; 34: 11929-11947https://doi.org/10.1523/JNEUROSCI.1860-14.2014Crossref PubMed Scopus (2831) Google Scholar Genes were considered specific to microglia or astrocytes if expressed ≥ 2-fold compared with all other tested cell types. n = 6 mice. Statistical difference as indicated ∗∗∗∗/††††p < 0.0001; ∗∗∗/†††p < 0.001; ∗∗/††p < 0.01; ∗/†p < 0.05.View Large Image Figure ViewerDownload Hi-res image Download (PPT)Of the 55 tested PIGs, expression of 38 genes showed a significant main effect of relation to plaque in the microglial AOIs (one-way ANOVA). (Two pseudogenes reported as PIGs [Gpx4-ps and Cd63-ps] were not available in the Nanostring platform.) We divided the differentially expressed genes into three groups: (1) genes only significantly raised in microglia touching plaques (Figure 3A), (2) genes with expression that decreased gradually with the plaque region showing significantly higher expression than the away region but the periplaque region not differing significantly from either, or differing significantly from both (Figure 3B), and (3) genes that were not different between plaque and periplaque but significantly upregulated in both the plaque and periplaque region compared with the away AOIs (Figure 3C). Two additional PIG genes (H2-k1 and Ctsh) were also of interest as they appeared to have a U-shaped response to plaque proximity, being significantly increased in the periplaque area but returning to background levels of expression on the plaque (data not shown). This could suggest an effect on expression of these genes of low concentrations of soluble Aβ in the periplaque region that was lost at higher concentrations near the plaque.Group 1 was of particular interest, as these genes are most likely responding to contact with the plaque itself, rather than to soluble Aβ or other secreted substances at a distance from the plaque. This group included Trem2 and its downstream signaling partner Tyrobp, as well as several of the complement and lysosomal genes that have previously been implicated in AD.Note that not all PIGs are thought to be microglial genes. We thus compared the different groups in terms of previously defined relative distribution in microglia or astrocytes in single-cell transcriptomic analysis comparing specific cell types.14Ximerakis M. Lipnick S.L. Innes B.T. Simmons S.K. Adiconis X. Dionne D. Mayweather B.A. Nguyen L. Niziolek Z. Ozek C. et al.Single-cell transcriptomic profiling of the aging mouse brain.Nat. Neurosci. 2019; 22: 1696-1708https://doi.org/10.1038/s41593-019-0491-3Crossref PubMed Scopus (167) Google Scholar Figure 3D indicates the proportion of genes in each group that have been reported to be at least 2-fold enriched for microglia or astrocytes compared with all other cell types in whole brain. Genes that were not defined as astrocytic or microglial in the Ximerakis et al. database were further as" @default.
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• W4309593279 date "2022-11-01" @default.
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• W4309593279 title "Plaque contact and unimpaired Trem2 is required for the microglial response to amyloid pathology" @default.
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• W4309593279 doi "https://doi.org/10.1016/j.celrep.2022.111686" @default.
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