. Spatial and temporal transcriptomics reveal microglia-astroglia crosstalk in the amyloid-β plaque cell niche of Alzheimer’s disease. bioRχiv August 12, 2019.

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  1. Wei-Ting and collaborators present, to the best of our knowledge, the first application of spatial transcriptomics and in situ sequencing to a murine model of Alzheimer’s disease (AD). This study, motivated by the empirical study of a complex “cellular phase of AD” (De Strooper and Karran, 2016) in response to amyloid plaques identified 57 responsive genes with correlated expression. This network module involves amyloid Plaque Induced Genes (PIGs) whose correlation is driven by patterns of expression that correlate with plaque load, occur in proximity to plaques, and involve multicellular populations of glial cell types. Consistent with the hypothesis of inflammatory-like cellular alterations potentially triggering brain dyshomeostasis in response to pathology, the responsive gene network involves alteration of complement, oxidative stress, and inflammation pathways, as well as brain-wide dysregulated microglia and astrocyte crosstalk.

    Interestingly, the authors also identified a separate gene network that suggests abnormal myelination. In particular, oligodendrocyte-expressing genes were altered in response to pathology, showing a qualitatively distinct response conditional on the stage of pathology, being overexpressed in early stages and downregulated in late. Gene co-expression analysis further revealed a gene module consistent with the observed differential expression, and involving both oligodendrocytes and oligodendrocyte precursor cells (the OL module). Notably, a pathology-responsive expression signature suggestive of general alterations in myelination is consistent with what we found while analyzing the single-cell heterogeneity of postmortem cortical samples (Mathys et al. 2019). The authors’ observations also suggest that, in contrast to the inflammatory PIG module, which showed a regional homogeneous response, the particular response dynamics of the OL module might reflect differential brain region vulnerability. Further single-cell studies involving multiple brain regions will likely help exploring these observations and spatial heterogeneity in the context of the human brain.

    Although spatial information is lost during single-cell or nuclei profiling of human postmortem samples, the identification of robust gene in situ co-expression signatures in the vicinity of pathogenic hallmarks of neurodegeneration—such as the one provided here by the authors—might potentially aid the computational inference of spatial information in human data. Can we guess whether clear subpopulations of cells in human brain AD atlases were originally localized to the vicinity of plaques? Is all this information really lost? These are interesting questions we can now start exploring thanks to both the increasingly available single-cell profiles of human brain pathology and, as coherently shown in this study, to the application of new technologies of spatial and in situ transcriptomics to multiple brain regions of animal models.

    References:

    . The Cellular Phase of Alzheimer's Disease. Cell. 2016 Feb 11;164(4):603-15. PubMed.

    . Single-cell transcriptomic analysis of Alzheimer's disease. Nature. 2019 Jun;570(7761):332-337. Epub 2019 May 1 PubMed.

    View all comments by Li-Huei Tsai
  2. This work by De Strooper and colleagues adds very interesting new aspects to previous work by several groups on transcriptomic changes in glia that have shaped our understanding of the diversity of glial phenotypes in neurodegeneration and the pathways involved in disease development and progression.

    One important aspect concerns the methods that are used here: This is the first time that techniques such as spatial transcriptomics and in situ sequencing have been applied to brain tissue with Aβ pathology, thus adding an additional layer of information to our understanding of the transcriptomic response to Aβ plaques. The strength of this approach is clearly that spatial information is preserved and that transcriptomic changes can be comprehensively studied in defined brain regions with high resolution in an unbiased manner. Another advantage is that the transcriptomic analysis in not confined to one cell type only (such as microglia) but that reaction of several cell types can synchronously be deducted, thus potentially uncovering inter-cell-dependent responses to pathological insults.

    Furthermore, there are several very interesting biological/pathophysiological conclusions that can be drawn from this study.

    For example, the authors characterize a number of genes from a co-expression network that are spatially correlated with Aβ plaques and, hence, called Plaque-Induced Genes, or PIGs. Although some of them have been described in bulk RNA-sequencing data in mouse models with Aβ pathology either in whole tissue (e.g., complement-related genes such as C1qa, C1qb, C1qc, and C4a; Srinivasan et al., 2016) or in isolated microglia (Orre et al., 2014), here the authors spatially link the upregulation of these genes to the plaque microenvironment, a clearly novel and important finding, which needs further investigation.

    Another very interesting aspect is the response of oligodendrocytes to Aβ pathology. The authors find an upregulation of oligodendrocyte genes very early during disease progression and a depletion of oligodendrocyte genes during late stages of disease. This finding is new and especially interesting in relation to the recent single-nucleus RNA-Seq study in human AD tissue by Mathys et al., in which increased AD pathology correlated with a global transcriptional activation in oligodendrocytes in male patients (Mathys et al., 2019). 

    One can easily envision questions that would be very interesting to investigate in follow-up studies: What does the transcriptomic response look like in human tissue in different brain regions at different neuropathological stages and in response to different Aβ plaque types? Is the transcriptomic response to other types of pathology of neurodegeneration (e.g., tau pathology) similar, and does it show specific spatial distribution? Is the plaque-dependent response in microglia, astrocytes and oligodendrocytes caused by inter-cellular crosstalk or by a stereotypical cellular reaction to the plaque microenvironment? Are there sex-related differences (given that this study focused on male mice)?

    Finally, and perhaps most importantly: What is the impact of this plaque-dependent gene expression program on cellular function and how can gene expression or cellular response be targeted for future therapy?

    References:

    . Untangling the brain's neuroinflammatory and neurodegenerative transcriptional responses. Nat Commun. 2016 Apr 21;7:11295. PubMed.

    . Isolation of glia from Alzheimer's mice reveals inflammation and dysfunction. Neurobiol Aging. 2014 Dec;35(12):2746-60. Epub 2014 Jun 14 PubMed.

    . Single-cell transcriptomic analysis of Alzheimer's disease. Nature. 2019 Jun;570(7761):332-337. Epub 2019 May 1 PubMed.

    View all comments by Marc Beyer
  3. A central question in AD research is the relationship between amyloid plaques and neurodegeneration. In this highly innovative study, the authors focus on the spatial localization of changes in cell types and their signatures, specifically with respect to amyloid plaques in mouse models of Alzheimer’s disease. The use of high-throughput spatial arrays, which allow for genome-wide measurements in space, combined with targeted investigation of key “plaque-induced genes” at the single-cell level allows the authors to investigate cell-type-specific changes and interactions that are likely to be set off by the deposition of these plaques. In support of the “cellular model” of AD progression espoused by the authors, they identify rings of altered cell-type signatures among microglia and astrocytes with distance from amyloid plaques, suggesting that these changes may lead to the sustained alterations in downstream cell types that are hallmarks of AD. Overall, the use of novel spatial transcriptomics techniques, combined with validation studies looking at spatial changes at the single-cell level, lead to a new way of characterizing the cascade of molecular changes in AD.

    View all comments by Vilas Menon

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