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Rapid unleashing of macrophage efferocytic capacity via transcriptional pause release

Nature volume 628, pages 408–415 (2024)Cite this article

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Abstract

During development, inflammation or tissue injury, macrophages may successively engulf and process multiple apoptotic corpses via efferocytosis to achieve tissue homeostasis1. How macrophages may rapidly adapt their transcription to achieve continuous corpse uptake is incompletely understood. Transcriptional pause/release is an evolutionarily conserved mechanism, in which RNA polymerase (Pol) II initiates transcription for 20–60 nucleotides, is paused for minutes to hours and is then released to make full-length mRNA2. Here we show that macrophages, within minutes of corpse encounter, use transcriptional pause/release to unleash a rapid transcriptional response. For human and mouse macrophages, the Pol II pause/release was required for continuous efferocytosis in vitro and in vivo. Interestingly, blocking Pol II pause/release did not impede Fc receptor-mediated phagocytosis, yeast uptake or bacterial phagocytosis. Integration of data from three genomic approaches—precision nuclear run-on sequencing, RNA sequencing, and assay for transposase-accessible chromatin using sequencing (ATAC-seq)—on efferocytic macrophages at different time points revealed that Pol II pause/release controls expression of select transcription factors and downstream target genes. Mechanistic studies on transcription factor EGR3, prominently regulated by pause/release, uncovered EGR3-related reprogramming of other macrophage genes involved in cytoskeleton and corpse processing. Using lysosomal probes and a new genetic fluorescent reporter, we identify a role for pause/release in phagosome acidification during efferocytosis. Furthermore, microglia from egr3-deficient zebrafish embryos displayed reduced phagocytosis of apoptotic neurons and fewer maturing phagosomes, supporting defective corpse processing. Collectively, these data indicate that macrophages use Pol II pause/release as a mechanism to rapidly alter their transcriptional programs for efficient processing of the ingested apoptotic corpses and for successive efferocytosis.

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Fig. 1: Transcriptional pause/release contributes to efferocytosis.
Fig. 2: Importance of Pol II pause/release in continuous efferocytosis and corpse acidification.
Fig. 3: Rapid transcriptional upregulation of specific genes during efferocytosis links to pause/release.
Fig. 4: Pause/release-regulated transcription factor EGR3 affects corpse processing in vitro and in vivo.

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Data availability

All raw and processed sequencing data generated in this study have been deposited as SuperSeries in the NCBI Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE253578. This SuperSeries comprises the following SubSeries: GSE253574 (ATAC-seq), GSE253576 (PRO-seq) and GSE25377 (RNA-seq). Publicly available datasets were used in this study: MSigDB resource: https://www.gsea-msigdb.org/gsea/msigdb/, UCSC Genome Browser annotation track database: https://genome.ucsc.edu/cgi-bin/hgTables, Jaspar database: https://jaspar.elixir.no and ENSEMBL: https://useast.ensembl.org/index.html. Gating strategy for efferocytosis (Supplementary Fig. 1) and raw, uncropped images of western blots (Supplementary Figs. 2 and 3) are provided in the Supplementary Information. Source data are provided with this paper.

Code availability

Custom codes used in this stud: for ATAC-seq, https://github.com/JetBrains-Research/chipseq-smk-pipeline; for PRO-seq https://github.com/AdelmanLab/NIH_scripts, https://github.com/lh3/seqtk and https://github.com/AdelmanLab/GetGeneAnnotation_GGA.

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Acknowledgements

We thank members of Ravichandran laboratory for input and critical reading of the manuscript; the Centre for Microscopy and Image Analysis, University of Zürich, for the Olympus IXplore SpinSR10 and the Leica SP8 inverse confocal laser scanning microscopes; and the Nascent Transcriptomics Core at Harvard Medical School for generating PRO-seq libraries and for assistance with data analysis. We thank the laboratory of Todd Fehniger for sourcing of human leukocytes from ImpactLife Blood Centers, and thank J. Milbrandt for providing Egr3-knockout mice. Schematics in Figs. 1a,d,e,g–j, 2a,d,g, 3a,c,f and 4a,d,h and Extended Data Figs. 3a,c,f, 4c, 5a and 6b,e,f were created using BioRender images as templates. T.T. was supported by a predoctoral fellowship from the American Heart Association (AHA 835593). K.S.R. was supported by NIAID (R01AI159551) and BJC Investigator Funds from the Washington University School of Medicine. S.K. was supported by an F31 fellowship from the NHLBI (1F31HL160134) and J.I.E. was supported by a fellowship from the NEI (EY031211). R.M.E. was supported by T32 Immunology Grant (T32AI007163). L.B. was supported by Emmanuel van der Schueren (EvdS) starter scholarship from Kom op tegen Kanker. E.B. and A.V. were supported by grants from the Swiss National Foundation grants (SNF310030_212794 and SNF31003A_182733).

Author information

Authors and Affiliations

  1. Division of Immunobiology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

    Turan Tufan, Gamze Comertpay, Marina Terekhova, Shannon Kelley, Pavel Zakharov, Rochelle M. Ellison, Oleg Shpynov, Jerry Sun, Yitan Chen, Marta Stremska, J. Iker Etchegaray, Maxim N. Artyomov & Kodi S. Ravichandran

  2. Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

    Ambra Villani, Enno Bockelmann & Francesca Peri

  3. Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA

    Geoffrey M. Nelson & Seth R. Goldman

  4. JetBrains Research, Munich, Germany

    Oleg Shpynov

  5. Department of Neuroscience and MIC, University of Virginia, Charlottesville, VA, USA

    Michael Raymond & Kodi S. Ravichandran

  6. Department of Pediatrics, Division of Rheumatology and Immunology, Washington University in St. Louis, St. Louis, MO, USA

    Lance W. Peterson

  7. Unit for Cell Clearance in Health and Disease, VIB-UGent Center for Inflammation Research and the Department of Biomedical Molecular Biology, Ghent University, Ghent, Belgium

    Laura Boeckaerts & Kodi S. Ravichandran

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  1. Turan Tufan
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Contributions

T.T. and K.S.R. designed all experiments and wrote the manuscript. T.T. performed most of the experiments. A.V., E.B. and F.P. assisted with the zebrafish experiments. S.R.G. assisted with the PRO-seq libraries. G.M.N. assisted with the PRO-seq analysis. O.S. and M.N.A. assisted with the ATAC-seq analysis. M.T. and P.Z. assisted with the RNA-seq analysis. G.C., S.K., R.M.E., J.S., Y.C., M.S., J.I.E. and L.B. assisted with various experiments. L.W.P. assisted with the generation of human PBMCs. M.R. assisted with the CharOFF construction.

Corresponding author

Correspondence to Kodi S. Ravichandran.

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Extended data figures and tables

Extended Data Fig. 1 Upregulated genes exhibit reduced pausing indices and pathway divergence during efferocytosis.

a, Gene Ontology pathway analysis (MSigDB) of upregulated and downregulated genes (determined by DESeq2, using the Wald test, padj<0.001) from the PRO-seq data at 45 min of efferocytosis (versus resting macrophages). b, Metagene plot of PRO-seq reads for the 331 genes upregulated in macrophages after 45 min efferocytosis (per Wald test) c, Heat map of PRO-seq signals around the proximal promoter region and gene body of the 331 genes upregulated in macrophages after 45 min efferocytosis. d, e, Cumulative distribution of pausing indices (from four independent experiments) of 331 upregulated genes (n-331) (d) and 105 randomly selected unchanged genes (e) as determined by DESeq2 and the Wald test (left). Pausing indices for each gene are compared between resting macrophages and macrophages after 45 min (top) or 90 min (bottom) of efferocytosis. Paired tow-tailed t-tests. ****p < 0.0001, ns: not significant. f, Upregulated genes (331) were divided into highly paused (PI > 4) and lowly paused genes (PI < 4), and pathway analysis performed via GSEA-MSigDB data base (https://www.gsea-msigdb.org/gsea/msigdb). In all figures, data are from four independent experimental replicates.

Source Data

Extended Data Fig. 2 Pause/release effects on efferocytosis versus Fc receptor-mediated phagocytosis.

a, Immunoblotting showing CDK9, Ser2P and β-Actin protein levels in macrophages treated with either DMSO or flavopiridol (10 µM) for 30 min. n = 3 independent experiments. b, Macrophages treated with DMSO or CDK9 inhibitors were incubated with TAMRA (pH-insensitive)-stained apoptotic Jurkat cells for 30 min. c, CDK9, Ser2P and β-Actin levels in macrophages treated with PROTAC-CDK9 (20 µM) for indicated times (left) or NVP-2 (concentrations indicated) for 30 min (right). n = 1 experiment. d, Efferocytosis quantified in macrophages with concurrent CDK9 inhibitors and apoptotic cells addition. n = 4 (left) and n = 3 (right) independent experiments. Paired two-tailed t-test. e, Uptake of anti-CD90.2-opsonized thymocytes by macrophages treated with NVP-2 (10 µM) or THAL-SNS-032 (20 µM) for 30 min. f, Editing efficiency in CRISPR/Cas9-generated NELFB- and NELFCD-deficient macrophages. n = 1 experiment. g, Efferocytosis kinetics were measured by live cell imaging (Incucyte) using WT and NELF-deficient macrophages incubated with CypHer5E-stained apoptotic Jurkat cells. Cytochalasin D was used as a control. Data are mean ± SEM. n = 4 independent experiments. Area under curve analysis and then unpaired two-tailed t-test with Welch’s correction. h, i, Continuous efferocytosis by human macrophages (left, n = 4 and right, n = 3 human donors of PBMCs; paired two-tailed t-test) (h) and mouse macrophages (i) treated with DMSO or CDK9 inhibitors. j, Second corpse uptake by mouse macrophages treated with CDK9 inhibitors and fed CypHer5E- and TAMRA-stained apoptotic Jurkat cells at a ratio of 1:1:1 apoptotic cell to phagocyte for 30 min. Double-positive macrophages have engulfed at least two corpses. n = 7 (left) and n = 6 (right) independent experiments. Paired two-tailed t-test. k, l, Continuous uptake of opsonized thymocytes in macrophages treated with DMSO or PROTAC-CDK9. d, g, h, j, Some of control samples were concurrently used in parallel experiments. b, e, i, l, In box and whiskers graphs (the center line denotes median, box edges encompass 25th to 75th percentiles, min to max points), dots show values from four independent experiments, unpaired two-tailed t-test. In all figures, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.001, ns: not significant. Schematics in b,f,i–k created with BioRender.com.

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Extended Data Fig. 3 Acidification and specific gene expression patterns during efferocytosis.

a, Continuous efferocytosis of CSFE+ (first round) and TAMRA+ (second round) apoptotic cells by macrophages pre-treated for 30 min with DMSO or bafilomycin A1. n = 4 independent experiments, paired two-tailed t-test. b, Relative expression (as determined by qPCR) of the indicated genes over time in macrophages during phagocytosis of synthetic beads. Data are mean ± SEM. c, PtdSer exposure was induced in RBCs using a calcium ionophore (A23187) and quantified by annexin V staining (left). The uptake of CypHer5E-stained PtdSer+ RBCs by mouse macrophages was assessed by flow cytometry (right) n = 4 independent experiments. Unpaired two-tailed t-test. d, Relative expression of EGR3 (as determined by qPCR) in human macrophages treated with DMSO or flavopiridol during efferocytosis. n:5 human donors of PBMCs; one-way ANOVA with Tukey’s multiple comparisons. a, c, d, In box and whiskers graphs, the center line denotes median, box edges encompass 25th to 75th percentiles, min to max points, and dots show independent data points. In all figures, *p < 0.05, **p < 0.01, ****p < 0.0001, ns: not significant. Schematics in a,c,d created with BioRender.com.

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Extended Data Fig. 4 EGR3 upregulation via Pol II pause/release during efferocytosis.

a, Heat map (derived from RNA-seq analysis) depicting differentially upregulated transcription factors (Wald test and corrected for multiple testing using the Benjamini and Hochberg method) at 45 min efferocytosis. Genes were ranked by fold-change. Data are from four independent experimental replicates. b, PRO-seq tracks (left) and relative pausing index (right) for Egr3 in resting macrophages and during efferocytosis. n = 4 independent experimental replicates. c, Schematic depicting ATAC-seq experiment in which mouse macrophages were fed apoptotic human Jurkat cells for 15 min, 30 min or 45 min of efferocytosis. n = 4 independent experimental replicates. d, Tracks of ATAC-seq showing chromatin accessibility in the promoter region of Egr3 in the resting state and during efferocytosis. Data derived from four independent experimental replicates. e, Relative expression of Egr3 in macrophages (as determined by qPCR) following Egr3 knockdown via shRNA (left) and Egr3 overexpression via retroviral vector (right). Data are presented as mean ± SEM. n = 3 independent experiments. f, Uptake of CypHer5E-stained apoptotic cells by wild type and Egr3-OE macrophages treated with either DMSO or flavopiridol. Two-way ANOVA with Tukey’s multiple comparisons. *p < 0.05 g, Fc receptor-mediated phagocytosis of CSFE-stained opsonized thymocytes by wild type, Egr3-deficient and Egr3-OE macrophages was assessed by flow cytometry after 30 min. Thymocytes opsonized with IgG was used as a control. One-way ANOVA with Tukey’s multiple comparisons. ns: non-significant. (f, g) Box and whiskers graphs (the center line denotes median, box edges encompass 25th to 75th percentiles, min to max points), and dots show values from four independent experiments. Schematics in c created with BioRender.com.

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Extended Data Fig. 5 egr3-deficient microglia in Zebrafish development exhibits impaired efferocytic capacity.

a, Schematic depicting the genome editing approach in zebrafish embryos (see method section for details). b, Percentage of injected embryos with confirmed deletion in exon 2 of egr3 across six independent experiments. CRISPANTs embryos (296 bp deletion) = 84.49%. Data are presented as mean ± s.d. N = 6 and 109 embryos analyzed. c, Immunoblotting (left) and quantification (right) of egr3 protein in control versus egr3 CRISPANTs embryos. n = 1 experiment. d, Representative dorsal images of non-injected irf8st95/st95 zebrafish embryo brain after Acridine Orange (AO) staining for apoptotic cells (top) and its segmentation (bottom). Quantification (right) of the basal levels of apoptosis in the optic tecta (OT) of non-injected irf8st95/st95 controls (N = 26) and egr3 CRISPANT (N = 23) embryos using Imaris automatic spot detection. Box and whiskers graphs (the center line denotes median, box edges encompass 25th to 75th percentiles, min to max points), unpaired two-tailed t-test. e, Representative images of a WT microglia at 3 days post fertilization (dpf) having the cytoplasm labelled in green (TgBAC(csf1ra:GAL4-VP16); Tg(UAS:nfsb-mCherry)) and freshly formed phagosomes labeled in magenta (Tg(UAS:mNeonGreen-Rab5)). The upper panel timepoint 1 (T1), in which the phagosome (arrowhead) is visible from the cell body (mCherry-green) but not yet in the Rab5 channel (mNeonGreen-magenta). T2 (4.5 min later) shows Rab5 recruitment to freshly formed phagosomes (arrowhead), indicating successful phagocytosis. Scale bar 10 µm. f, Quantification of phagocytic events (Rab5+ vesicles formed) in each microglia per hour counted. Violin plot, unpaired two-tailed t-test. g, Percentage of microglia having one or no successful phagocytic event (Rab5+ vesicles) per hour over the total. WT controls= 19.3%; egr3 CRISPANTs= 56.4%. e-g, T2 in WT control (N = 7 and n = 88) and egr3 CRISPANT (N = 7 and n = 101) where N=number of embryos and n=number of microglia cells quantified. h, Heat map of differential expression of EGR3-regulated genes that are associated with endosomal pathways. The Wald test corrected for multiple testing using the Benjamini and Hochberg method. padj<0.05. i, j, Knockdown efficiency of siRNAs targeting Dmxl2 and Elmo1. Unpaired two-tailed t-test. Three independent experiments, data are presented as mean ± SEM. k, Defective acidification in Dmxl2-deficient macrophages as shown by lysotracker staining during efferocytosis. n:3 independent experiments, paired two-tailed t-test. In all figures, *p < 0.05, **p < 0.01, ****p < 0.0001, ns: non-significant. Schematics in a created with BioRender.com.

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Extended Data Fig. 6 The pre-corpse internalization stages of efferocytosis impact Pol II release.

a, b, Defective acidification in Egr3-deficient macrophages as shown by lysotracker staining during efferocytosis (a) and GFP quenching in macrophages engulfing CharOFF cells (b). a, Box and whiskers graphs (the center line denotes median, box edges encompass 25th to 75th percentiles, min to max points). n = 4, paired two-tailed t-test. b, n = 3; ratio paired two-tailed t-test. c, Relative expression level of Egr1 and Egr3 (as determined by qPCR) in DMSO (n = 4) and flavopiridol (n = 3)-treated macrophages incubated with medium alone, supernatant from live Jurkat cells, and supernatant from apoptotic Jurkat cells for 30 min. Data are presented as mean ± SEM. Unpaired two-tailed t-test. d, e, Relative expression of Egr1 (n = 7) and Egr3 (n = 5) in CytoD (actin polymerization inhibitor)-treated macrophages with and without apoptotic cells (d) and DMSO or BMS (pan-TAM inhibitor) during efferocytosis (e). Paired two-tailed t-test. f, Relative expression of Egr3 in macrophages treated with either IgG (antibody control) or Axl and MerTK (20 nM) activating antibodies for 30 min. n:3, unpaired two-tailed t-test. In all figures, data points represent individual values for ‘n’ biologically independent experiments. *p < 0.05, **p < 0.01, ***p < 0.001. Schematics in b,e,f created with BioRender.com.

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Tufan, T., Comertpay, G., Villani, A. et al. Rapid unleashing of macrophage efferocytic capacity via transcriptional pause release. Nature 628, 408–415 (2024). https://doi.org/10.1038/s41586-024-07172-y

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