Microglia maintain homeostasis in the central nervous system through phagocytic clearance of protein aggregates and cellular debris. This function deteriorates during ageing and neurodegenerative disease, concomitant with cognitive decline. However, the mechanisms of impaired microglial homeostatic function and the cognitive effects of restoring this function remain unknown. We combined CRISPR–Cas9 knockout screens with RNA sequencing analysis to discover age-related genetic modifiers of microglial phagocytosis. These screens identified CD22, a canonical B cell receptor, as a negative regulator of phagocytosis that is upregulated on aged microglia. CD22 mediates the anti-phagocytic effect of α2,6-linked sialic acid, and inhibition of CD22 promotes the clearance of myelin debris, amyloid-β oligomers and α-synuclein fibrils in vivo. Long-term central nervous system delivery of an antibody that blocks CD22 function reprograms microglia towards a homeostatic transcriptional state and improves cognitive function in aged mice. These findings elucidate a mechanism of age-related microglial impairment and a strategy to restore homeostasis in the ageing brain.
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Füger, P. et al. Microglia turnover with aging and in an Alzheimer’s model via long-term in vivo single-cell imaging. Nat. Neurosci. 20, 1371–1376 (2017).
Réu, P. et al. The lifespan and turnover of microglia in the human brain. Cell Rep. 20, 779–784 (2017).
Nimmerjahn, A., Kirchhoff, F. & Helmchen, F. Resting microglial cells are highly dynamic surveillants of brain parenchyma in vivo. Science 308, 1314–1318 (2005).
Arandjelovic, S. & Ravichandran, K. S. Phagocytosis of apoptotic cells in homeostasis. Nat. Immunol. 16, 907–917 (2015).
Schafer, D. P. et al. Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner. Neuron 74, 691–705 (2012).
Paolicelli, R. C. et al. Synaptic pruning by microglia is necessary for normal brain development. Science 333, 1456–1458 (2011).
Hong, S. et al. Complement and microglia mediate early synapse loss in Alzheimer mouse models. Science 352, 712–716 (2016).
Lui, H. et al. Progranulin deficiency promotes circuit-specific synaptic pruning by microglia via complement activation. Cell 165, 921–935 (2016).
Safaiyan, S. et al. Age-related myelin degradation burdens the clearance function of microglia during aging. Nat. Neurosci. 19, 995–998 (2016).
Deczkowska, A., Amit, I. & Schwartz, M. Microglial immune checkpoint mechanisms. Nat. Neurosci. 21, 779–786 (2018).
Hefendehl, J. K. et al. Homeostatic and injury-induced microglia behavior in the aging brain. Aging Cell 13, 60–69 (2014).
Vaughan, D. W. & Peters, A. Neuroglial cells in the cerebral cortex of rats from young adulthood to old age: an electron microscope study. J. Neurocytol. 3, 405–429 (1974).
Tremblay, M.-È., Zettel, M. L., Ison, J. R., Allen, P. D. & Majewska, A. K. Effects of aging and sensory loss on glial cells in mouse visual and auditory cortices. Glia 60, 541–558 (2012).
Sierra, A., Gottfried-Blackmore, A. C., McEwen, B. S. & Bulloch, K. Microglia derived from aging mice exhibit an altered inflammatory profile. Glia 55, 412–424 (2007).
Hickman, S. E., Allison, E. K. & El Khoury, J. Microglial dysfunction and defective beta-amyloid clearance pathways in aging Alzheimer’s disease mice. J. Neurosci. 28, 8354–8360 (2008).
Hickman, S. E. et al. The microglial sensome revealed by direct RNA sequencing. Nat. Neurosci. 16, 1896–1905 (2013).
Grabert, K. et al. Microglial brain region-dependent diversity and selective regional sensitivities to aging. Nat. Neurosci. 19, 504–516 (2016).
Morgens, D. W. et al. Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens. Nat. Commun. 8, 15178 (2017).
Haney, M. S. et al. Identification of phagocytosis regulators using magnetic genome-wide CRISPR screens. Nat. Genet. 50, 1716–1727 (2018).
Bohlen, C. J., Bennett, F. C. & Bennett, M. L. Isolation and culture of microglia. Curr. Protoc. Immunol. https://doi.org/10.1002/cpim.70 (2018).
Bohlen, C. J. et al. Diverse requirements for microglial survival, specification, and function revealed by defined-medium cultures. Neuron 94, 759–773 (2017).
Butovsky, O. et al. Identification of a unique TGF-β-dependent molecular and functional signature in microglia. Nat. Neurosci. 17, 131–143 (2014).
Morgens, D. W., Deans, R. M., Li, A. & Bassik, M. C. Systematic comparison of CRISPR/Cas9 and RNAi screens for essential genes. Nat. Biotechnol. 34, 634–636 (2016).
Macauley, M. S., Crocker, P. R. & Paulson, J. C. Siglec-mediated regulation of immune cell function in disease. Nat. Rev. Immunol. 14, 653–666 (2014).
Nitschke, L., Carsetti, R., Ocker, B., Köhler, G. & Lamers, M. C. CD22 is a negative regulator of B-cell receptor signalling. Curr. Biol. 7, 133–143 (1997).
Li, Y.-Q., Sun, L. & Li, J. Macropinocytosis-dependent endocytosis of Japanese flounder IgM+ B cells and its regulation by CD22. Fish Shellfish Immunol. 84, 138–147 (2019).
Linnartz-Gerlach, B., Kopatz, J. & Neumann, H. Siglec functions of microglia. Glycobiology 24, 794–799 (2014).
Griciuc, A. et al. Alzheimer’s disease risk gene CD33 inhibits microglial uptake of amyloid beta. Neuron 78, 631–643 (2013).
Bennett, M. L. et al. New tools for studying microglia in the mouse and human CNS. Proc. Natl Acad. Sci. USA 113, E1738–E1746 (2016).
Zhang, Y. et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014).
Müller, J. et al. CD22 ligand-binding and signaling domains reciprocally regulate B-cell Ca2+ signaling. Proc. Natl Acad. Sci. USA 110, 12402–12407 (2013).
Hudak, J. E., Canham, S. M. & Bertozzi, C. R. Glycocalyx engineering reveals a Siglec-based mechanism for NK cell immunoevasion. Nat. Chem. Biol. 10, 69–75 (2014).
Ereño-Orbea, J. et al. Molecular basis of human CD22 function and therapeutic targeting. Nat. Commun. 8, 764 (2017).
Dahlgren, K. N. et al. Oligomeric and fibrillar species of amyloid-beta peptides differentially affect neuronal viability. J. Biol. Chem. 277, 32046–32053 (2002).
Deczkowska, A. et al. Disease-associated microglia: a universal immune sensor of neurodegeneration. Cell 173, 1073–1081 (2018).
Deczkowska, A. et al. Mef2C restrains microglial inflammatory response and is lost in brain ageing in an IFN-I-dependent manner. Nat. Commun. 8, 717 (2017).
Wang, Y. et al. TREM2 lipid sensing sustains the microglial response in an Alzheimer’s disease model. Cell 160, 1061–1071 (2015).
Marciniak, E. et al. The chemokine MIP-1α/CCL3 impairs mouse hippocampal synaptic transmission, plasticity and memory. Sci. Rep. 5, 15862 (2015).
Cole, A. J., Saffen, D. W., Baraban, J. M. & Worley, P. F. Rapid increase of an immediate early gene messenger RNA in hippocampal neurons by synaptic NMDA receptor activation. Nature 340, 474–476 (1989).
Sheng, M., McFadden, G. & Greenberg, M. E. Membrane depolarization and calcium induce c-fos transcription via phosphorylation of transcription factor CREB. Neuron 4, 571–582 (1990).
Gosselin, D. et al. Environment drives selection and function of enhancers controlling tissue-specific macrophage identities. Cell 159, 1327–1340 (2014).
Lavin, Y. et al. Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment. Cell 159, 1312–1326 (2014).
Bennett, F. C. et al. A combination of ontogeny and CNS environment establishes microglial identity. Neuron 98, 1170–1183 (2018).
Li, Q. et al. Developmental heterogeneity of microglia and brain myeloid cells revealed by deep single-cell RNA sequencing. Neuron 101, 207–223 (2019).
Kress, B. T. et al. Impairment of paravascular clearance pathways in the aging brain. Ann. Neurol. 76, 845–861 (2014).
Da Mesquita, S. et al. Functional aspects of meningeal lymphatics in ageing and Alzheimer’s disease. Nature 560, 185–191 (2018).
Bradshaw, E. M. et al. CD33 Alzheimer’s disease locus: altered monocyte function and amyloid biology. Nat. Neurosci. 16, 848–850 (2013).
Siddiqui, S. S. et al. The Alzheimer’s disease-protective CD33 splice variant mediates adaptive loss of function via diversion to an intracellular pool. J. Biol. Chem. 292, 15312–15320 (2017).
Kleinberger, G. et al. TREM2 mutations implicated in neurodegeneration impair cell surface transport and phagocytosis. Sci. Transl. Med. 6, 243ra86 (2014).
Huang, K.-L. et al. A common haplotype lowers PU.1 expression in myeloid cells and delays onset of Alzheimer’s disease. Nat. Neurosci. 20, 1052–1061 (2017).
Friedman, B. A. et al. Diverse brain myeloid expression profiles reveal distinct microglial activation states and aspects of Alzheimer’s disease not evident in mouse models. Cell Reports 22, 832–847 (2018).
Olah, M. et al. A single cell-based atlas of human microglial states reveals associations with neurological disorders and histopathological features of the aging brain. Preprint at https://doi.org/10.1101/343780 (2018).
Zhang, Y. et al. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron 89, 37–53 (2016).
Lambert, J.-C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013).
Funikov, S. Y. et al. FUS(1–359) transgenic mice as a model of ALS: pathophysiological and molecular aspects of the proteinopathy. Neurogenetics 19, 189–204 (2018).
Cougnoux, A. et al. Microglia activation in Niemann-Pick disease, type C1 is amendable to therapeutic intervention. Hum. Mol. Genet. 27, 2076–2089 (2018).
Xiao, H., Woods, E. C., Vukojicic, P. & Bertozzi, C. R. Precision glycocalyx editing as a strategy for cancer immunotherapy. Proc. Natl Acad. Sci. USA 113, 10304–10309 (2016).
Rillahan, C. D. et al. Global metabolic inhibitors of sialyl- and fucosyltransferases remodel the glycome. Nat. Chem. Biol. 8, 661–668 (2012).
Larocca, J. N. & Norton, W. T. Isolation of myelin. Curr. Protoc. Cell Biol. 3, cb0325s33 (2007).
Stine, W. B., Jungbauer, L., Yu, C. & LaDu, M. J. in Biological Microarrays (eds Khademhosseini, A. et al.) 13–32 (Humana Press, 2010).
Polinski, N. K. et al. Best practices for generating and using α-synuclein pre-formed fibrils to model Parkinson’s disease in rodents. J. Parkinsons Dis. 8, 303–322 (2018).
Wolf, A., Bauer, B., Abner, E. L., Ashkenazy-Frolinger, T. & Hartz, A. M. S. A comprehensive behavioral test battery to assess learning and memory in 129S6/Tg2576 mice. PLoS ONE 11, e0147733 (2016).
Castellano, J. M. et al. Human umbilical cord plasma proteins revitalize hippocampal function in aged mice. Nature 544, 488–492 (2017).
The Tabula Muris Consortium. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature 562, 367–372 (2018).
Keren-Shaul, H. et al. A unique microglia type associated with restricting development of Alzheimer’s disease. Cell 169, 1276–1290 (2017).
Krasemann, S. et al. The TREM2-APOE pathway drives the transcriptional phenotype of dysfunctional microglia in neurodegenerative diseases. Immunity 47, 566–581 (2017).
We thank the members of the Wyss-Coray, Bassik and Bertozzi laboratories for feedback and support; M. Macauley, Q. Li and S. Nagaraja for helpful discussions, M. Bennett and F.C. Bennett for critical reading of the manuscript, H. Zhang and K. Dickey for laboratory management, R. Ballet, E. Butcher, J. Paulson and L. Nitscke for Cd22−/− mice, B. Lehallier for RNA-seq analysis scripts, L. Zhou for RNAscope advice, J. Hudak for reagents, H. Yousef for histology protocols and C. Cain for flow cytometry technical expertise. This work was funded by the Department of Veterans Affairs (T.W.-C.), the National Institute on Aging (R01-AG045034 and DP1-AG053015 to T.W.-C., F30AG060638 to J.V.P.), the National Institute of General Medical Sciences (R01-GM059907 to C.R.B.), the NOMIS Foundation (T.W.-C.), The Glenn Foundation for Aging Research (T.W.-C.), the Stanford University Medical Scientist Training Program (T32GM007365, J.V.P., B.A.H.S., L.B. and M.S.), the Big Idea Brain Rejuvenation Project from the Wu Tsai Neurosciences Institute (T.W.-C., M.C.B. and C.R.B.) and Cure Alzheimer’s Fund (T.W.-C.). This work used the Stanford Center for Genomics and Personalized Medicine (NIH S10OD020141).
C.R.B. is a co-founder and Scientific Advisory Board member of Palleon Pharmaceuticals, Enable Bioscience, InterVenn Bio and Redwood Bioscience (a subsidiary of Catalent), and a member of the Board of Directors of Eli Lilly and Company. T.W.-C., C.R.B., M.C.B., J.V.P., B.A.H.S. and M.S.H. are co-inventors on a patent application related to the work published in this paper.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
a, Intersection and disjunction of 361 genes involved in phagocytosis19 expressed (fragments per kilobase of transcript per million mapped reads, FPKM >5) by BV2 cells (PRJNA407656) and primary microglia. b, Gating scheme for FACS separation of phagocytic and non-phagocytic BV2 cells, treated with vehicle (grey) or the actin-polymerization inhibitor, cytochalasin D (red). c, Time-lapse microscopy readout of phagocytosis by BV2 cells treated with vehicle (grey) or cytochalasin D (red) (n = 3, mean ± s.e.m.). d, e, Results from CRISPR–Cas9 screen targeting 954 membrane proteins (d) or 2,015 drug targets, kinases and phosphatases (e) in BV2 cells. Knockouts that promote phagocytosis (red) have a positive effect size and knockouts that inhibit phagocytosis (blue) have a negative effect size (screen performed in technical duplicate; dotted line, P = 0.05, two-sided t-test). f, g, Distributions of negative control sgRNAs (grey) and RAB9-targeting (f) or CMAS-targeting (g) sgRNAs (blue). Positive values indicate enrichment in the phagocytic fraction, and negative values indicate enrichment in the non-phagocytic fraction. h, Statistical overrepresentation test showing enrichment of Reactome pathway annotations within phagocytosis-promoting (red) and -inhibiting (blue) hits (Fisher’s exact test). i, CD22 expression in wild-type (blue), CD22-KO (green) and isotype-control stained (black) BV2 cells assessed by flow cytometry. j, Confluence of control (grey) and CD22-KO (green) BV2 cells during time-lapse microscopy phagocytosis assays (n = 3, mean ± s.e.m.). k, Number of beads ingested per cell were calculated in control and CD22-KO BV2 cells after 8 h of phagocytosis. While CD22-KO cells display enhanced phagocytosis at a population level (n = 3, *P < 0.05, two-sided t-test, mean ± s.e.m.), we observed no significant differences in the number of beads ingested per cell (two-way ANOVA). Red dot represents mean phagocytic index of the entire cell population. Data in b, c, i–k were replicated in at least two independent experiments. Source data
Extended Data Fig. 2 Immunophenotyping of sialic acid-related molecules on young and aged microglia.
a–c, e, f, Flow cytometry analysis of young (red) and aged (blue) microglia for expression of fluorescence minus one (FMO) background fluorescence (a), plant-derived lectin ligands (b), conserved Siglecs (c), mouse-specific CD33-related Siglecs (e) and recombinant Siglec ligands (f). MFI shown on a biexponential scale. d, Microglia from wild-type or Cd22−/− aged mice were stained with the particular anti-CD22 clone (Ox97) used for immunophenotyping. Cd22−/− microglia show no staining relative to FMO. g, Gating strategy to immunophenotype microglia while minimizing autofluorescence. All data were replicated in at least two independent experiments.
a, Flow cytometry gating scheme for analysis of CD22 expression in peripheral blood-derived myeloid cells (CD45+CD11b+), immature B cells (CD45+B220+CD22lo) and mature B cells (CD45+B220+CD22hi). Quantibrite beads are shown in the top right panel. b, Quantification of flow cytometry analysis showing the number of CD22 molecules on various cell types, interpolated from the Quantibrite bead standard curve (n = 3, mean ± s.e.m.). c, CD22 expression in various cell types of the young mouse CNS, showing exclusive expression in microglia. Data from Barres laboratory RNA-seq (http://www.brainrnaseq.org/). d, t-distributed stochastic neighbor embedding (t-SNE) plot showing scRNA-seq of CD22 expression in microglia isolated from E14.5, P7 and adult mouse brains. CD22 is enriched in a subpopulation of P7 microglia. Data from ref. 44 (https://myeloidsc.appspot.com/). e, t-SNE plot showing scRNA-seq analysis of CD22 expression in cells from 20 different mouse tissues. CD22 is expressed in B cells and microglia, but is absent from non-myeloid brain cells (n = 7, young mice). Data from the Tabula Muris Consortium64. f, Violin plots of log-normalized CD22 counts per million reads (CPM) showing high expression in B cells from multiple organs and in microglia (n = 7, young mice). Data from the Tabula Muris Consortium. Data in a, b were replicated in at least 2 independent experiments. Source data
a, S. nigra agglutinin (SNA, recognizes α2,6-linked sialic acid) and Maackia amurensis agglutinin II (MAA II, recognizes α2,3-linked sialic acid) ligand expression in wild-type BV2 cells (orange), wild-type BV2 cells pretreated with sialidase (blue), and CMAS-KO cells (red) assessed by flow cytometry. Sialidase treatment and CMAS-KO reduce sialic acid ligands on the cell surface. b, Western blot showing SHP1 protein expression in wild-type and PTPN6-KO BV2 cells. For raw source image, see Supplementary Fig. 1. c, Confluence of control (grey), CMAS-KO (red), and PTPN6-KO (blue) BV2 cells during time-lapse microscopy phagocytosis assays (n = 3, mean ± s.e.m.). d, e, Phagocytosis of pH-sensitive fluorescent beads by untreated (black) and sialidase-treated (red) BV2 cells (d) or vehicle-treated and 3FAX-Neu5Ac-treated BV2 cells (e) before phagocytosis (n = 3, **P < 0.005, two-sided t-test; mean ± s.e.m.). f, Phagocytosis of pH-sensitive fluorescent beads by wild-type (black), wild-type + sialidase (red), CD22-KO (blue), or CD22-KO + sialidase (green) BV2 cells (n = 3, *P < 0.05, one-way ANOVA with Tukey’s multiple comparisons correction; mean ± s.e.m.). g, Microglia were acutely isolated from the brains of aged (18-month-old) wild-type (left) or Cd22−/− (right) mice, treated with or without sialidase, and incubated with pH-sensitive fluorescent latex beads. Microglia specific phagocytosis was measured using flow cytometry (n = 6, *P < 0.05, paired two-sided t-test). h, Representative images of BV2 cells coated with AlexaFluor 488-conjugated glycopolymers (green) and stained with a plasma-membrane-specific dye (CellMask, red) showing overlap (orange). Scale bars, 25 μm. i, Recombinant mouse CD22-human Fc fusion protein was pre-complexed with AF647 anti-human Fc secondary antibody, treated with various concentrations of IgG (black) or anti-CD22 (blue, red), and subsequently allowed to bind to ligands on the surface of BV2 cells or BV2 cells pretreated with sialidase (red). Binding was measured by flow cytometry. j, Internalization of IgG (black), function blocking anti-CD22 (clone Cy34.1, blue), and non-function-blocking anti-CD22 (clone OX96, green) conjugated to a pH-sensitive fluorescent dye by BV2 cells assessed by time-lapse microscopy (n = 3, mean ± s.e.m.). k, Western blot quantification of ratio of active p-SHP1 to total SHP1 protein in BV2 cells pretreated with various concentrations of anti-CD22. Blue line represents the fitted variable slope inhibitor-response curve. For raw source image, see Supplementary Fig. 1. All data were replicated in at least two independent experiments. Source data
a, Representative images of myelin labelled with a pH-sensitive fluorescent dye (CypHer5E, white), a constitutively fluorescent dye (AF555, red) and stained for IBA1 (green). The majority of AF555 overlapping with IBA1 is also positive for CypHer5E, indicating localization to an acidified compartment. Scale bars, 100 μm. b, 3D reconstruction of a microglial cell (IBA1, green) with ingested myelin (CypHer5E and AF555, white and red, yellow arrow) near un-ingested myelin (AF555, red, white arrow). Scale bar, 5 μm. c, Microgliosis, as assessed by percentage of IBA1+ area at the injection site, was not altered by CD22 blockade (n = 8, paired two-sided t-test). d, Representative images of myelin (red) overlaid with the myeloid marker IBA1 (green) at the injection site of IgG (left) or PBS (middle) treated hemispheres of the same aged brain, or an image of a stab wound control (not injected with myelin). Scale bars, 100 μm. e, Microgliosis, as assessed by percentage of IBA1+ area at the injection site, was not altered by IgG compared to the stab wound control (n = 2, paired two-sided t-test). f, Clearance of myelin debris in the IgG (black) or PBS (blue) treated hemispheres assessed 48 h post-injection (n = 4, paired two-sided t-test). g, Representative images of IBA1 (grey), a macrophage marker, and TMEM119 (magenta), a microglia-specific marker, at the injection site in IgG (left) or anti-CD22 (right) treated hemispheres of the same aged brain. Scale bars, 100 μm. h, Percentage of IBA1+ phagocytes expressing TMEM119 at the injection site (n = 4, paired two-sided t-test). i, Clearance of myelin debris in young (2.5-month-old) wild-type (black) or Cd22−/− (blue) mice was assessed 48 h after injection (n = 4, two-sided t-test; mean ± s.e.m.). j, Representative images of total Aβ (white), thioflavin S+ fibrillar Aβ (green) and IBA1 (red) in transgenic mice expressing human APP with Swedish and London familial AD mutations (left) or wild-type mice injected with Aβ oligomers 48 h before analysis (right). k, Representative images of Aβ (red, left column) and Aβ overlaid with the myeloid marker IBA1 (green, right column) at the injection site (±2 mm lateral, 0 mm A–P, −1.5mm D–V, relative to bregma) of IgG (top row) or anti-CD22 (bottom row) treated hemispheres of the same aged brain. Scale bars, 100 μm. l, Microgliosis, as assessed by percentage of IBA1+ area at the Aβ oligomer injection site, was not altered by CD22 blockade (n = 8, paired two-sided t-test). m, Representative images of α-synuclein and IBA1 at the injection site in IgG and anti-CD22 treated mice. Scale bars, 100 μm. n, Clearance of α-synuclein fibrils in the IgG (black) or anti-CD22 (green) treated hemispheres assessed 48 h post-injection (n = 7, *P < 0.05, paired two-sided t-test). o, Microgliosis, as assessed by percentage of IBA1+ area at the α-synuclein fibril injection site, was not altered by CD22 blockade (n = 7, paired two-sided t-test). All data were replicated in at least two independent experiments. Source data
Extended Data Fig. 6 Specificity and distribution of long-term, CNS-targeted antibody infusion via osmotic pump.
a, Representative images of CD19+ B cells (red, top row), DAPI (blue, middle row), and merged (bottom row) in the spleen (left, positive control) and hippocampus (right) of a mouse treated with anti-CD22 via intracerebroventricular osmotic pump. b, Concentration of trans-cyclooctene-labelled anti-CD22 in the plasma seven days after administration of 200 μg anti-CD22 via intraperitoneal injection (n = 1) or intracerebroventricular osmotic pump infusion (n = 4), assessed by in-gel fluorescence and quantification based on a standard curve (mean ± s.e.m.). For raw source image, see Supplementary Fig. 1. c, Representative images of coronal brain sections of untreated (left column) and IgG treated (right column) mice. IgG was labelled with an Alexa Fluor 647–NHS ester (top row, white) to assess antibody distribution throughout the brain (bottom row, DAPI, blue). In addition to the para-ventricular areas, antibodies penetrated the thalamus and hippocampus. d, Flow cytometry analysis of Alexa Fluor 647-labelled antibody on microglia isolated from untreated (black), IgG (red) or anti-CD22 (blue) infused mice. Microglia from anti-CD22 treated mice display elevated Alexa Fluor 647 signal, indicative of antibody target engagement. Data in a, c and d were replicated in at least two independent experiments. Source data
Extended Data Fig. 7 Anti-CD22 treatment partially reverses age- and disease-related microglia transcriptional signatures.
a, Venn diagram showing the lack of any intersection among 315 genes differentially expressed between IgG (n = 7) and anti-CD22 (n = 7) treated microglia and 40 genes differentially expressed between untreated (n = 2) and IgG (n = 7) treated microglia at an FDR cutoff of 10% (Benjamini–Hochberg method). b, Hierarchical clustering of normalized read counts from IgG and anti-CD22 treated microglia, normalized by row mean. The top-100 differentially expressed genes are shown (n = 7). c, Enrichr Gene Ontology analysis of genes upregulated (red) and downregulated (blue) by anti-CD22 treatment (Fisher’s exact test, Benjamini–Hochberg FDR). d, GSEA showing normalized enrichment score for microglia genes modulated by anti-CD22 treatment within the gene signature for: ageing microglia (this study), disease-associate microglia65 (DAM), microglial neurodegenerative phenotype66 (MGnD), and microglia from lipopolysaccharide treated mice29 (LPS) (*FDR < 0.05). e–h, GSEA showing enrichment distribution for microglia genes modulated by anti-CD22 treatment within the gene signature for ageing microglia (e), DAM (f), MGnD (g), and LPS-activated microglia (h). Source data
a, Western blot for SALL1 and α-tubulin (loading control) in whole-hippocampus lysates from IgG and anti-CD22 treated mice. For raw source image, see Supplementary Fig. 1. b, Quantification of blot in a, showing upregulation of SALL1 protein in anti-CD22 hippocampi (n = 3, *P < 0.05, two-sided t-test, mean ± s.e.m.). c, Protein concentration of CCL3 in the supernatant of acutely isolated aged microglia treated for 8 h with IgG or anti-CD22 in the absence or presence of Aβ oligomers (n = 4, *P < 0.05, ANOVA with Sidak’s multiple hypothesis correction, mean ± s.e.m.). d, Representative images of p-CREB expression (red) in the dentate gyrus of IgG (left) and anti-CD22 (right) treated mice. e, Quantification of p-CREB mean intensity in the dentate gyrus of IgG (black) and anti-CD22 (green) treated mice (n = 7, two-sided t-test, mean ± s.e.m.). f, Quantification of total doublecortin-positive cells in three equally-spaced dentate gyrus sections of IgG (black) and anti-CD22 (green) treated mice (n = 3, N.S. not significant, two-sided t-test, mean ± s.e.m.). g–i, Quantification of C1q mean intensity (g) and synaptophysin (h; pre-synaptic marker) or PSD-95 (i; post-synaptic marker) density in the hippocampus of IgG (black) and anti-CD22 (green) treated mice (n = 3, two-sided t-test, mean ± s.e.m.). All data were replicated in at least two independent experiments. Source data
a, Working memory and exploratory behaviour in aged (18-month-old) mice treated with IgG (black) or anti-CD22 (green) via intraperitoneal injection twice weekly for one month as assessed by percentage of time spent in the novel arm in a forced alternation Y-maze test (n = 6, two-sided t-test, mean ± s.e.m.). b, Contextual memory aged (18-month-old) mice treated with IgG (black) or anti-CD22 (green) via intraperitoneal injection twice weekly for one month as assessed by percentage of time displaying freezing behaviour in a contextual-fear-conditioning test (n = 6, two-sided t-test, mean ± s.e.m.). Source data
Microglial phagocytosis declines with age, accompanied by increased CD22 expression. CD22 blockade restores phagocytosis, promotes a homeostatic transcriptional state, and improves cognitive function in aged mice.
Raw western blot source images. Arrows indicate band of interest. Boxes indicate cropping for representative images. α-tubulin was probed on the same membrane as proteins of interest as a loading control.
Raw sgRNA counts in non-phagocytic and phagocytic populations from membrane proteins and drug targets CRISPR screens.
casTLE analysed hit results from membrane proteins and drug targets CRISPR screens.
DESeq2 output comparing microglia isolated from aged (20 month) and young (3 month) hippocampi.
DESeq2 output comparing microglia isolated from anti-CD22 and IgG treated aged (18 month) mice.
Time-lapse video of phagocytosis of pH-sensitive fluorescent latex beads by BV2 cells infected with a safe-targeting control sgRNA.
Time-lapse video of phagocytosis of pH-sensitive fluorescent latex beads by BV2 cells infected with a CD22-targeting sgRNA.
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Pluvinage, J.V., Haney, M.S., Smith, B.A.H. et al. CD22 blockade restores homeostatic microglial phagocytosis in ageing brains. Nature 568, 187–192 (2019). https://doi.org/10.1038/s41586-019-1088-4
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