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. 2023 Oct 23;3(10):100598.
doi: 10.1016/j.crmeth.2023.100598. Epub 2023 Sep 29.

Chromatin accessibility profiling of targeted cell populations with laser capture microdissection coupled to ATAC-seq

Affiliations

Chromatin accessibility profiling of targeted cell populations with laser capture microdissection coupled to ATAC-seq

Caterina Carraro et al. Cell Rep Methods. .

Abstract

Spatially resolved omics technologies reveal context-dependent cellular regulatory networks in tissues of interest. Beyond transcriptome analysis, information on epigenetic traits and chromatin accessibility can provide further insights on gene regulation in health and disease. Nevertheless, compared to the enormous advancements in spatial transcriptomics technologies, the field of spatial epigenomics is much younger and still underexplored. In this study, we report laser capture microdissection coupled to ATAC-seq (LCM-ATAC-seq) applied to fresh frozen samples for the spatial characterization of chromatin accessibility. We first demonstrate the efficient use of LCM coupled to in situ tagmentation and evaluate its performance as a function of cell number, microdissected areas, and tissue type. Further, we demonstrate its use for the targeted chromatin accessibility analysis of discrete contiguous or scattered cell populations in tissues via single-nuclei capture based on immunostaining for specific cellular markers.

Keywords: ATAC-seq; CP: Molecular biology; chromatin accessibility; epigenomics; laser capture microdissection; spatial omics.

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Conflict of interest statement

Declaration of interests The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
LCM-ATAC-seq allows characterizing of tissue-specific chromatin accessibility (A) Schematic representation of the mouse lung/brain LCM-ATAC-seq workflow. (B) Overall transcription start site (TSS) enrichment profile of analyzed mouse lung/brain LCM-ATAC-seq samples. (C) Fragment size distribution (FSD) across analyzed mouse lung/brain samples. (D) Principal-component analysis (PCA) of the analyzed LCM-ATAC-seq mouse lung/brain dataset. (E) Sftpb locus accessibility across analyzed mouse lung/brain groups (normalized bigwig tracks overlayed condition-wise). Reference bulk ATAC-seq ENCODE bigwig tracks are also reported (mouse lung bulk: ENCSR102NGD dataset, ENCFF435PTI.bigwig; mouse brain bulk: ENCSR310MLB dataset, ENCFF561KNB.bigwig). FF, fresh frozen; BA, big areas (10 dissected areas, 20 cells each, for a total of ∼200 cells).
Figure 2
Figure 2
LCM-ATAC-seq profiles describe tissue-specific chromatin landscapes (A) Number of upregulated differentially accessible regions (DARs) in mouse lung compared with brain samples (padj < 0.05, log2(fold change) threshold = 1). Separate tissue-wise comparisons were performed for 50 nuclei versus 10 big area (BA) samples. (B) Number of downregulated DARs in mouse lung compared with brain samples (padj < 0.05, log2(fold change) threshold = 1). Separate tissue-wise comparisons were performed for 50 nuclei versus 10 BA samples. (C) Hierarchically clustered heatmap reporting the relative accessibility of the union of all DARs mapping in promoter regions across samples. (D) Gene set enrichment analysis (GSEA) on GO database (biological process, q < 0.25) enrichment of gene-associated DARs in clusters 1 and 2.
Figure 3
Figure 3
Investigating the chromatin accessibility of targeted tissue cell populations (A) Schematic representation of the mouse spleen LCM-ATAC-seq workflow. (B) Representative immunofluorescence B220 and CD3e staining of a mouse spleen section (5× magnification left column, 20× magnification right column). (C) FSD across analyzed samples. (D) Overall TSS enrichment profile of analyzed mouse spleen LCM-ATAC-seq samples. (E) PCA of the analyzed mouse spleen LCM-ATAC-seq dataset. (F) GSVA enrichment for B (left) and T cell (right) signatures across mouse spleen samples, plotted across groups. Wilcoxon test was applied to test significance, and p values are reported. (G) Hierarchically clustered (by column) heatmap reporting the per-gene accessibility of analyzed mouse spleen samples for key B and T cell marker genes. (H) Cd19 and Tcf7 loci accessibility in normalized TCZ versus BCZ samples aggregate bigwig tracks. (I) ChromVAR Z scores for B and T cell samples obtained for the motifs EBF1 and GATA3. Wilcoxon test was applied to test significance, and p values are reported. The bottom panel reports Ebf1 and Gata3 loci accessibility in normalized TCZ versus BCZ samples aggregate bigwig tracks. FF, fresh frozen; BCZ, B cell zone; TCZ, T cell zone; B cell/T cells 100, 100 nuclei mini-bulk from BCZ or TCZ; B cell/T cells patch, 10 patches mini-bulk from BCZ or TCZ.
Figure 4
Figure 4
Assessing the chromatin accessibility of scattered tissue cell populations (A) Schematic representation of the LCM-ATAC-seq workflow in human left lobe (LL) lung parenchyma samples. L1: lower LL; L2: upper LL. (B) Representative immunofluorescence PU.1 staining of an L2 section from donor 4 (40× magnification). (C) Overall TSS enrichment profile of analyzed human LCM-ATAC-seq samples. (D) FSD across analyzed human samples. (E) SPI1 locus accessibility in normalized PU.1 aggregate track versus lung bulk ENCODE reference (human lung bulk: ENCSR647AOY dataset, ENCFF210HIS.bigwig). (F) SFTPB locus accessibility in normalized PU.1 aggregate bigwig track versus lung bulk ENCODE reference (human lung bulk: ENCSR647AOY dataset, ENCFF210HIS.bigwig). (G) One-tailed fast gene set enrichment analysis for signatures PU1_Q6 (PU.1 transcription factor targets) and GO_BP_MYELOID_CELL_DIFFERENTIATION on PU.1 targeted cells rank of chromatin accessibility. FF, fresh frozen.

References

    1. Rood J.E., Maartens A., Hupalowska A., Teichmann S.A., Regev A. Impact of the Human Cell Atlas on medicine. Nat. Med. 2022;28:2486–2496. doi: 10.1038/s41591-022-02104-7. - DOI - PubMed
    1. Deprez M., Zaragosi L.-E., Truchi M., Becavin C., Ruiz García S., Arguel M.-J., Plaisant M., Magnone V., Lebrigand K., Abelanet S., et al. A Single-Cell Atlas of the Human Healthy Airways. Am. J. Respir. Crit. Care Med. 2020;202:1636–1645. doi: 10.1164/rccm.201911-2199OC. - DOI - PubMed
    1. Moses L., Pachter L. Museum of spatial transcriptomics. Nat. Methods. 2022;19:534–546. doi: 10.1038/s41592-022-01409-2. - DOI - PubMed
    1. Rao A., Barkley D., França G.S., Yanai I. Exploring tissue architecture using spatial transcriptomics. Nature. 2021;596:211–220. doi: 10.1038/s41586-021-03634-9. - DOI - PMC - PubMed
    1. Madissoon E., Oliver A.J., Kleshchevnikov V., Wilbrey-Clark A., Polanski K., Richoz N., Ribeiro Orsi A., Mamanova L., Bolt L., Elmentaite R., et al. A spatially resolved atlas of the human lung characterizes a gland-associated immune niche. Nat. Genet. 2023;55:66–77. doi: 10.1038/s41588-022-01243-4. - DOI - PMC - PubMed

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