Cited by 463Neuroinflammation and Neurodegeneration MechanismsSingle-cell and spatial transcriptomicsNeurogenesis and neuroplasticity mechanisms

The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index; 32 of the 45 sources its claims cite were checked for support.

Cross-Species Single-Cell Analysis Reveals Divergence of the Primate Microglia Program

Open access

Abstract

Microglia, the brain-resident immune cells, are critically involved in many physiological and pathological brain processes, including neurodegeneration. Here we characterize microglia morphology and transcriptional programs across ten species spanning more than 450 million years of evolution. We find that microglia express a conserved core gene program of orthologous genes from rodents to humans, including ligands and receptors associated with interactions between glia and neurons. In most species, microglia show a single dominant transcriptional state, whereas human microglia display significant heterogeneity. In addition, we observed notable differences in several gene modules of rodents compared with primate microglia, including complement, phagocytic, and susceptibility genes to neurodegeneration, such as Alzheimer's and Parkinson's disease. Our study provides an essential resource of conserved and divergent microglia pathways across evolution, with important implications for future development of microglia-based therapies in humans.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Geirsdottir et al. profile microglia morphology and transcriptomes across evolutionarily distant species and find a conserved core microglial program alongside primate-specific divergence. Human microglia are notably heterogeneous and express more neurodegeneration susceptibility genes than rodent microglia.

Key findings

  • A conserved microglia core program was identified across species: 8,890 genes were expressed in microglia of at least one species, clustering into 17 prominent gene clusters, with core signature clusters 1–10 expressed in all species but less in zebrafish and chicken; 163 genes were conserved and unique to microglia versus other tissue macrophages.
  • Most species showed a single dominant microglial transcriptional state, whereas human microglia displayed significant heterogeneity; a putative senescent-like subset comprised roughly 20% of all human microglia, was consistent across all six sampled individuals, and co-expressed CDKN1, CCL3, CCL4, CCL3L3, and CCL4L2 with higher TNF and IL1B.
  • Human PD and AD susceptibility gene expression correlated most with macaque (PD, r = 0.73; AD, r = 0.59), while mice, rats, and hamsters showed moderate to low correlation (r = 0.16–0.40); no significant enrichment or depletion was seen for schizophrenia or Huntington’s disease genes.
  • Histological analysis across 18 species found the highest microglial density in leech ganglia (299.0 ± 41.4 Iba1+ microglia/mm²) and lowest in axolotls (11.1 ± 0.7/mm²); mouse frontal cortex had 65.8 ± 1.09 cells/mm² versus human frontal cortex 35.5 ± 2.48 cells/mm².

Methods

  • Microglia morphology was assessed by immunohistochemistry and 3D Imaris reconstruction across 18 species, using Iba1, mPEG1-GFP for zebrafish, and CSF1R-mApple for chicken.
  • For transcriptomics, brains from eight species with high-quality reference genomes (human, macaque, marmoset, sheep, mouse, hamster, chicken, zebrafish) were processed by FACS: CD45+ cells for MARS-seq2.0 scRNA-seq and CD11b+CD45lo microglia (or GFP+ zebrafish, CD45+CSF1RmApple+ chicken) for bulk RNA-seq; 4,458 QC-positive microglia cells and 3–6 bulk samples per species were collected, with rat and blind mole rat later added for single-cell comparisons.
  • Analysis used an ortholog “metagene” strategy, metacell clustering, scRNA-seq-based deconvolution of bulk RNA-seq to remove contaminating cells, rank-based normalization, k-means clustering, and GWAS enrichment with NHGRI-EBI gene lists and hypergeometric tests (p < 0.01); human brain tissue came from healthy regions of individuals undergoing epilepsy surgery.

Limitations

  • Stated: the authors caution that human CNS tissue studies cannot exclude that patients’ microglia do not accurately recapitulate the in situ states of healthy brains, despite careful sample acquisition and processing and similar results in comparable studies.
  • Stated/evident: human samples were from epilepsy surgery (healthy regions with absence of pathology confirmed histologically), so they may not represent healthy brain microglia; sample sizes were small (3–6 individuals per species, human n = 6, with some species using pooled brains).
  • Evident from text: cross-species bulk RNA-seq normalization is challenging, deconvolution depends on scRNA-defined contaminating clusters, chicken and zebrafish were removed from mammalian comparisons, and microglial heterogeneity may be influenced by tissue source or processing.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.cell.2019.11.010

Cites

103 of 103 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

32 of 45 cited sources checked · 10 supported · 0 flagged · accuracy not yet measured

Show all 57 claims

  • Probably not a substantial claim. 36
  • It may state two separate claims as one. 36
  • The quote only partly states this claim. 1
62 of 62
  • The paper relies on this without support.

    Large differences exist in multiple characteristics of disease manifestation between human and animal models.

    “Despite immense efforts over the past decades to find a cure for neurodegenerative disorders using transgenic animal models, large differences are observed in multiple characteristics of disease manifestation in human versus animal models.”
  • The paper relies on this without support.

    Effective development of therapies for neurodegenerative diseases is limited.

    “Effective development of therapies for neurodegenerative diseases is limited.”
  • The paper relies on this without support.

    Bulk RNA-seq data can contain a mixture of cell types due to sample acquisition impurity and existence of outlier and/or 'contaminating' cells.

    “Bulk RNA-seq data can contain a mixture of cell types due to sample acquisition impurity and existence of outlier and/or ''contaminating'' cells.”
  • The paper relies on this without support.

    Comparing bulk RNA-seq data between species is especially challenging due to differences in the total number of genes, total read number, housekeeping genes expression profiles, and possible other factors that affect conventional RNA-seq normalization methods.

    “Comparing bulk RNA-seq data between species is especially challenging due to differences in the total number of genes, total read number, housekeeping genes expression profiles, and possible other factors that affect conventional RNA-seq normalization methods.”
  • The paper relies on this without support.

    Human brain tissue from epilepsy surgery patients' healthy regions is representative of normal human microglia.

    “Human brain tissue was collected from healthy brain regions of individuals that underwent epilepsy surgery.”
    “Absence of pathology in the sample was confirmed by histological analysis in the respective area by a neuropathologist.”
  • The paper relies on this without support.

    Post mortem samples with no indication of tumor or inflammatory disease are representative of normal human microglia.

    “In post mortem sample collection, samples were included in the study only if no indication of a tumor or inflammatory disease was examined by histological analysis.”
  • The paper relies on this without support.

    Orthologous genes across the compared species are functionally comparable for cross-species microglia transcriptome comparison.

    “All genes from microglia core gene module (Figure 3A) were plotted unless an orthologous gene did not exist in one of the two compared species.”
    “Genes with no orthologs are marked with a diagonally striped bar.”
7 of 7

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Complement and apoptotic-clearance Figure S6 references are reversed

    Minor

    The results cite S6F for apoptotic cell clearance and S6G for the complement pathway. The supplementary legend assigns S6F to complement and S6G to apoptotic cell clearance.

  • PCA methods point to the wrong supplementary figure

    Minor

    The methods place the PCA in Figure S4, whereas the supplementary legend identifies the PCA plot as Figure S3B; Figure S4 is described as histology of P2Y12 and PU.1.

  • Macaque and marmoset Figure S5 references are reversed

    Minor

    The results assign macaque to Figure S5A and marmoset to Figure S5B, but the supplementary legend assigns S5A to marmoset and S5B to macaque.

  • Non-human-primate CD45 antibody has conflicting catalogue numbers

    Minor

    The flow-cytometry antibody table and key resources table list the same non-human-primate CD45-PE antibody from Miltenyi Biotec with different catalogue numbers.

  • Single-cell comparison is incorrectly cited as Figure S4A

    Minor

    The methods cite Figure S4A for a single-cell expression comparison, but the supplementary legend describes S4A as P2Y12 histology. It describes the cross-species single-cell expression heatmap under Figure S3A.

5 of 5

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Metadata

Authors
Geirsdottir, L., David, E., Keren-Shaul, H., Weiner, A., Bohlen, S. C., Neuber, J., Balic, A., Giladi, A., Sheban, F., Dutertre, C.-A., Pfeifle, C., Peri, F., Raffo-Romero, A., Vizioli, J., Matiasek, K., Scheiwe, C., Meckel, S., Mätz-Rensing, K., van der Meer, F., Thormodsson, F. R., Stadelmann, C., Zilkha, N., Kimchi, T., Ginhoux, F., Ulitsky, I., Erny, D., Amit, I., & Prinz, M.
Affiliations
  • Weizmann Institute of Science (IL)
  • University of Freiburg (DE)
  • Roslin Institute (GB)
  • Agency for Science, Technology and Research (SG)
  • Max Planck Institute for Evolutionary Biology (DE)
  • University of Zurich (CH)
  • Inserm (FR)
  • Ludwig-Maximilians-Universität München (DE)
  • Innovation Center Iceland (IS)
  • Universitätsmedizin Göttingen (DE)
Corresponding author
  • Erny, Daniel
  • Amit, Ido
  • Prinz, Marco
Venue
Cell
Publisher
Elsevier BV
Published
2019-12
Volume
179
Issue
7
Pages
1609-1622.e16
ISSN
0092-8674 (ISSN-L)
OpenAlex
W2996729595
Cited by
461
References
93
Citations by year
2026: 49 · 2025: 48 · 2024: 78 · 2023: 62 · 2022: 92 · 2021: 79 · 2020: 53
FWCI
20.71
Type
journal article
Language
en
Update notices
erratum (2020-04-30)
Open access
Locations
  • Cell (publishedVersion)
  • PubMed (publishedVersion)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc-nd)
  • HAL (Le Centre pour la Communication Scientifique Directe) (submittedVersion)
  • GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
  • MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
  • Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
Funders
  • Chan Zuckerberg Initiative
  • HHMI
  • European Research Council (ERC-COG 724471-HemTree2.0)
  • MRA (509044)
  • DFG (SFB/TRR167, SFB 992, SFB1160, Reinhart Koselleck, 390939984)
  • Ernest and Bonnie Beutler Research Program for Excellence in Genomic Medicine
  • Helen and Martin Kimmel
  • Wolfson Foundation and Family Charitable Trust
  • Thompson Family Foundation Alzheimer’s Research Fund
  • Adelis Foundation
  • Eden and Steven Romick Post-Doctoral Fellowship Fund
  • International Progressive MS Alliance (PA-1604-08459)
  • Berta Ottenstein Programme for Clinician Scientists
  • Sobek Foundation
  • Ernst-Jung Foundation
  • Ministry of Science, Research and Arts, Baden-Wuerttemberg (Sonderlinie “Neuroinflammation”)
  • ISF (1324/15)
  • Minerva Foundation
  • Biotechnology and Biological Sciences Research Council of the United Kingdom
  • Institute Strategic Programme (BBS/E/D/10002071)
  • EMBO
  • Singapore Immunology Network
  • Singapore National Research Foundation (NRF2016NRF-NRFI001-02)
Topics
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
Keywords
microglia, primate evolution, single-cell transcriptomics, microglial heterogeneity, microglial morphology, microglia-neuron interaction, complement system, phagocytosis, Alzheimer's disease, Parkinson's disease, cross-species comparison
MeSH terms
Animals, Chickens, Humans, Primates, Reptiles, Rodentia, Sheep, Swine, Zebrafish, Microglia, Evolution, Molecular, Neurodegenerative Diseases, Genetic Predisposition to Disease, Gene Expression Profiling, Gene Regulatory Networks, Single-Cell Analysis, Transcriptome

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