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Monocytes deposit migrasomes to promote embryonic angiogenesis

Nature Cell Biology volume 24, pages 1726–1738 (2022)Cite this article

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Abstract

Pro-angiogenic factors are key regulators of angiogenesis. Here we report that highly migratory cells patrol the area of capillary formation in chick embryo chorioallantoic membrane. These cells deposit migrasomes on their migration tracks, creating migrasome-enriched areas. Single-cell sequencing identified these cells as monocytes. Depletion of monocytes impairs capillary formation. Quantitative mass spectrometry analysis reveals that monocyte migrasomes are enriched with pro-angiogenic factors. Purified migrasomes promote capillary formation and monocyte recruitment in vivo, and endothelial cell tube formation and monocyte chemotaxis in vitro. Knockdown or knockout of TSPAN4 reduces migrasome formation and impairs capillary formation and monocyte recruitment. Mechanistically, monocytes promote angiogenesis via VEGFA and CXCL12 in migrasomes. In summary, monocytes deposit migrasomes enriched in pro-angiogenic factors to promote angiogenesis.

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Fig. 1: Detection of migrasomes in chick embryo CAM.
Fig. 2: Migrasomes are generated by monocytes.
Fig. 3: Depletion of monocytes reduces the migrasome number in CAM and impairs angiogenesis.
Fig. 4: Monocyte migrasomes contain angiogenic factors and chemokine.
Fig. 5: Migrasomes induce capillary formation and recruitment of monocytes.
Fig. 6: Blocking migrasome formation impairs capillary formation.
Fig. 7: Migrasomes rescue capillary formation and monocyte recruitment defects in VEGFA-KD and CXCL12 KD CAM.

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Data availability

RNA-seq data that support the findings of this study have been deposited in the National Center for Biotechnology Information Sequence Read Archive under the accession code SAMN30722995. The mass spectrometry proteomics data have been deposited in ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier or the primary accession code PXD036647. The statistical source data for all figures and extended data figures have been provided as numerical source data. All other data supporting the findings of this study are available from the corresponding author on reasonable request. Further information and requests for resources and reagents should be directed to and will be fulfilled by L.Y. Source data are provided with this paper.

References

  1. Majesky, M. W. Vascular development. Arterioscler. Thromb. Vasc. Biol. 38, e17–e24 (2018).

    Article  CAS  Google Scholar 

  2. Chung, A. S. & Ferrara, N. Developmental and pathological angiogenesis. Annu. Rev. Cell Dev. Biol. 27, 563–584 (2011).

    Article  CAS  Google Scholar 

  3. Distler, J. H. et al. Angiogenic and angiostatic factors in the molecular control of angiogenesis. Q. J. Nucl. Med. 47, 149–161 (2003).

    CAS  Google Scholar 

  4. Risau, W. & Flamme, I. Vasculogenesis. Annu. Rev. Cell Dev. Biol. 11, 73–91 (1995).

    Article  CAS  Google Scholar 

  5. Karamysheva, A. F. Mechanisms of angiogenesis. Biochem. 73, 751–762 (2008).

    CAS  Google Scholar 

  6. Melincovici, C. S. et al. Vascular endothelial growth factor (VEGF)—key factor in normal and pathological angiogenesis. Rom. J. Morphol. Embryol. 59, 455–467 (2018).

    Google Scholar 

  7. Ribatti, D. The discovery of the fundamental role of VEGF in the development of the vascular system. Mech. Dev. 160, 103579 (2019).

    Article  CAS  Google Scholar 

  8. Takahashi, H. & Shibuya, M. The vascular endothelial growth factor (VEGF)/VEGF receptor system and its role under physiological and pathological conditions. Clin. Sci. 109, 227–241 (2005).

    Article  CAS  Google Scholar 

  9. Apte, R. S., Chen, D. S. & Ferrara, N. VEGF in signaling and disease: beyond discovery and development. Cell 176, 1248–1264 (2019).

    Article  CAS  Google Scholar 

  10. Pardali, E., Goumans, M. J. & ten Dijke, P. Signaling by members of the TGF-beta family in vascular morphogenesis and disease. Trends Cell Biol. 20, 556–567 (2010).

    Article  CAS  Google Scholar 

  11. Vempati, P., Popel, A. S. & Mac Gabhann, F. Extracellular regulation of VEGF: isoforms, proteolysis, and vascular patterning. Cytokine Growth Factor Rev. 25, 1–19 (2014).

    Article  CAS  Google Scholar 

  12. Poltorak, Z. et al. VEGF145, a secreted vascular endothelial growth factor isoform that binds to extracellular matrix. J. Biol. Chem. 272, 7151–7158 (1997).

    Article  CAS  Google Scholar 

  13. Vempati, P., Popel, A. S. & Mac Gabhann, F. Formation of VEGF isoform-specific spatial distributions governing angiogenesis: computational analysis. BMC Syst. Biol. 5, 59 (2011).

    Article  CAS  Google Scholar 

  14. Poltorak, Z., Cohen, T. & Neufeld, G. The VEGF splice variants: properties, receptors, and usage for the treatment of ischemic diseases. Herz 25, 126–129 (2000).

    Article  CAS  Google Scholar 

  15. Qian, B. Z. & Pollard, J. W. Macrophage diversity enhances tumor progression and metastasis. Cell 141, 39–51 (2010).

    Article  CAS  Google Scholar 

  16. Leek, R. D. et al. Association of macrophage infiltration with angiogenesis and prognosis in invasive breast carcinoma. Cancer Res. 56, 4625–4629 (1996).

    CAS  Google Scholar 

  17. Ruhrberg, C. & De Palma, M. A double agent in cancer: deciphering macrophage roles in human tumors. Nat. Med. 16, 861–862 (2010).

    Article  CAS  Google Scholar 

  18. Priceman, S. J. et al. Targeting distinct tumor-infiltrating myeloid cells by inhibiting CSF-1 receptor: combating tumor evasion of antiangiogenic therapy. Blood 115, 1461–1471 (2010).

    Article  CAS  Google Scholar 

  19. Stockmann, C. et al. Deletion of vascular endothelial growth factor in myeloid cells accelerates tumorigenesis. Nature 456, 814–818 (2008).

    Article  CAS  Google Scholar 

  20. Fantin, A. et al. Tissue macrophages act as cellular chaperones for vascular anastomosis downstream of VEGF-mediated endothelial tip cell induction. Blood 116, 829–840 (2010).

    Article  CAS  Google Scholar 

  21. Cattin, A. L. et al. Macrophage-induced blood vessels guide Schwann cell-mediated regeneration of peripheral nerves. Cell 162, 1127–1139 (2015).

    Article  CAS  Google Scholar 

  22. Ma, L. et al. Discovery of the migrasome, an organelle mediating release of cytoplasmic contents during cell migration. Cell Res. 25, 24–38 (2015).

    Article  CAS  Google Scholar 

  23. Huang, Y. et al. Migrasome formation is mediated by assembly of micron-scale tetraspanin macrodomains. Nat. Cell Biol. 21, 991–1002 (2019).

    Article  CAS  Google Scholar 

  24. Wu, D. et al. Pairing of integrins with ECM proteins determines migrasome formation. Cell Res. 27, 1397–1400 (2017).

    Article  CAS  Google Scholar 

  25. Jiang, D. et al. Migrasomes provide regional cues for organ morphogenesis during zebrafish gastrulation. Nat. Cell Biol. 21, 966–977 (2019).

    Article  CAS  Google Scholar 

  26. Chen, L., Ma, L. & Yu, L. WGA is a probe for migrasomes. Cell Discov. 5, 13 (2019).

    Article  CAS  Google Scholar 

  27. Grad, E. et al. The role of monocyte subpopulations in vascular injury following partial and transient depletion. Drug Deliv. Transl. Res. 8, 945–953 (2018).

    Article  CAS  Google Scholar 

  28. Bruhl, H. et al. Targeting of Gr-1+,CCR2+ monocytes in collagen-induced arthritis. Arthritis Rheum. 56, 2975–2985 (2007).

    Article  Google Scholar 

  29. Udalova, I. A., Mantovani, A. & Feldmann, M. Macrophage heterogeneity in the context of rheumatoid arthritis. Nat. Rev. Rheumatol. 12, 472–485 (2016).

    Article  CAS  Google Scholar 

  30. Jaipersad, A. S., Lip, G. Y., Silverman, S. & Shantsila, E. The role of monocytes in angiogenesis and atherosclerosis. J. Am. Coll. Cardiol. 63, 1–11 (2014).

    Article  CAS  Google Scholar 

  31. Moldovan, L. & Moldovan, N. I. Role of monocytes and macrophages in angiogenesis. EXS 94, 127–146 (2005).

    Google Scholar 

  32. Zhao, X. et al. Identification of markers for migrasome detection. Cell Disco. 5, 27 (2019).

    Article  CAS  Google Scholar 

  33. Sica, A., Erreni, M., Allavena, P. & Porta, C. Macrophage polarization in pathology. Cell. Mol. Life Sci. 72, 4111–4126 (2015).

    Article  CAS  Google Scholar 

  34. Ginhoux, F. & Jung, S. Monocytes and macrophages: developmental pathways and tissue homeostasis. Nat. Rev. Immunol. 14, 392–404 (2014).

    Article  CAS  Google Scholar 

  35. Riabov, V. et al. Role of tumor associated macrophages in tumor angiogenesis and lymphangiogenesis. Front Physiol. 5, 75 (2014).

    Article  Google Scholar 

  36. Vannella, K. M. & Wynn, T. A. Mechanisms of organ injury and repair by macrophages. Annu. Rev. Physiol. 79, 593–617 (2017).

    Article  CAS  Google Scholar 

  37. Allavena, P., Sica, A., Solinas, G., Porta, C. & Mantovani, A. The inflammatory micro-environment in tumor progression: the role of tumor-associated macrophages. Crit. Rev. Oncol. Hematol. 66, 1–9 (2008).

    Article  Google Scholar 

  38. Wyckoff, J. B. et al. Direct visualization of macrophage-assisted tumor cell intravasation in mammary tumors. Cancer Res. 67, 2649–2656 (2007).

    Article  CAS  Google Scholar 

  39. Das, A. et al. Monocyte and macrophage plasticity in tissue repair and regeneration. Am. J. Pathol. 185, 2596–2606 (2015).

    Article  CAS  Google Scholar 

  40. Wynn, T. A. & Vannella, K. M. Macrophages in tissue repair, regeneration, and fibrosis. Immunity 44, 450–462 (2016).

    Article  CAS  Google Scholar 

  41. Murray, P. J. Immune regulation by monocytes. Semin. Immunol. 35, 12–18 (2018).

    Article  CAS  Google Scholar 

  42. Shi, C. & Pamer, E. G. Monocyte recruitment during infection and inflammation. Nat. Rev. Immunol. 11, 762–774 (2011).

    Article  CAS  Google Scholar 

  43. Pakshir, P. & Hinz, B. The big five in fibrosis: macrophages, myofibroblasts, matrix, mechanics, and miscommunication. Matrix Biol. 68-69, 81–93 (2018).

    Article  CAS  Google Scholar 

  44. Evans, M. A. et al. Macrophage-mediated delivery of light activated nitric oxide prodrugs with spatial, temporal and concentration control. Chem. Sci. 9, 3729–3741 (2018).

    Article  CAS  Google Scholar 

  45. Theoret, C. L., Barber, S. M. & Gordon, J. R. Temporal localization of immunoreactive transforming growth factor beta1 in normal equine skin and in full-thickness dermal wounds. Vet. Surg. 31, 274–280 (2002).

    Article  Google Scholar 

  46. Sauka-Spengler, T. & Barembaum, M. Gain- and loss-of-function approaches in the chick embryo. Methods Cell. Biol. 87, 237–256 (2008).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to the members of the Yu groups for their helpful discussions and suggestions. This research was supported by the Ministry of Science and Technology of the People’s Republic of China (grant no. 2017YFA0503404), the National Natural Science Foundation of China (grant nos. 31790401, 92054301 and 32030023) and the Beijing Municipal Science & Technology Commission (grant nos. Z201100005320019 and Z211100003321002) and internal grant from Tsinghua university (2030 plan). We thank the State Key Laboratory of Membrane Biology for facility support and assistance with spinning disk microscopy. We thank the Protein Chemistry Facility at the Centre for Biomedical Analysis of Tsinghua University for mass spectrometry sample analysis. We acknowledge the assistance of the Imaging Core Facility, Technology Center for Protein Sciences, Tsinghua University for assistance with Imaris analysis. We acknowledge the assistance of SLSTU-Nikon Biological Imaging Center for assistance with using the NIKON A1RSiHD25 laser scanning confocal microscope and software. We thank the Core Facility, Center of Biomedical Analysis, Tsinghua University for technical support with flow cytometry and data analysis.

Author information

Authors and Affiliations

  1. State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Centre for Life Sciences, Beijing Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China

    Cuifang Zhang, Shuyao Yin, Mingyi Gao, Helen He, Ying Li, Dong Jiang, Minghui Shi & Li Yu

  2. School of Life Science, Tsinghua University, Beijing, China

    Tianqi Li & Jianbin Wang

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  1. Cuifang Zhang
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Contributions

L.Y. conceived the project. L.Y. and C.Z. designed and C.Z. performed in vitro and in vivo experiments and analysed data. L.Y. and C.Z. wrote the manuscript. M.G., Y.L. and M.S. performed migrasome 3D reconstruction experiments. S.Y. and H.H. performed TSPAN4-KO and monocyte depletion experiments. T.L. and J.W. designed and performed the single-cell sequencing experiment. D.J. performed migrasome purification experiments. All authors discussed the manuscript, commented on the project and contributed to the preparation of the paper.

Corresponding author

Correspondence to Li Yu.

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L.Y. is the scientific founder of Migrasome therapeutics Ltd. All other authors declare no conflicts of interest.

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Nature Cell Biology thanks Rajendra Apte, Michael Sixt and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Morphology of WGAhigh/low cell.

(a) Migration of WGAhigh and WGAlow cells was monitored by time-lapse confocal microscopy. Scale bar, 5 µm. (b) Cells from (a) were quantified for migration speed. Data are presented as means ± SEM; n = 21 cells per group pooled from three independent experiments. (c) Cells from (a) were quantified for size. Data are presented as means ± SEM; n = 21 cells per group pooled from three independent experiments. P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. Source numerical data are available in source data.

Source data

Extended Data Fig. 2 Monocytes depletion by alendronate impairs angiogenesis.

(a) After treatment with control liposomes or alendronate liposomes, CAM9d were stained by CD115-Alexa488 to detect monocytes inside and outside the blood vessels. Inside vessels: CD115-Alexa488 was microinjected into the CAM vasculature. Outside vessels: CD115-Alexa488 was add onto the CAM surface. Images were taken 30 minutes after CD115-Alexa488 staining. Scale bar, 50 μm. (b-c) The numbers of monocytes inside or outside vessels were quantified according to the CD115 signal. Data are presented as mean ± SEM; n = 32 samples from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. (d) CAMs treated with control liposomes and alendronate liposomes were visualized with a stereomicroscope (left panel) or a confocal microscope after dextran-FITC microinjection (right panel). Scale bar, left panel, 500 μm; right panel, 50 μm. (e) The number of sprouting capillaries from (d) was quantified according to the intensity of the dextran signal. Data are presented as mean ± SEM; n = 32 samples from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. Source numerical data are available in source data.

Source data

Extended Data Fig. 3 mRNA levels of TGFB3 by single-cell sequencing.

(a) Violin plots showing the mRNA levels of TGFB3 from single-cell sequencing analysis of monocyte and endothelium cells.

Extended Data Fig. 4 VEGFA/CXCL12 are enriched in migrasomes from CAM or mouse monocytes.

(a) CAM9d were stained with WGA and the indicated antibodies and visualized by confocal microscopy. Scale bar, 20 μm. Immunofluorescence in CAMs was visualized by confocal z-stack imaging and presented as the maximum intensity projection. (b) Migrasomes from mouse monocytes are enriched with VEGFA and CXCL12. Mouse bone marrow monocytes (BMMs) acquired from WT C57BL/6 mice were stained with WGA and the indicated antibodies and visualized by confocal microscopy. Scale bar, 10 μm. Enlarged images of migrasomes are shown in the white boxes. Scale bar, 2.5μm.

Extended Data Fig. 5 Migrasome delivery promotes EC proliferation and sprouting.

(a) Dissected CAMs from E8d were mounted on the top of a collagen I-Matrigel matrix mix, and soft agarose with migrasomes (+Mig) or without migrasomes (-Mig) was added on opposite sides of the CAM. 2, 4 and 6 days after mounting, the samples were visualized by confocal microscopy. Scale bar, 200 µm. (b) The proliferation of ECs and sprouting progression from (a) was quantified by the tube length from the edge of CAM to the angiogenic front. Data are presented as mean ± SEM; n =30 fields of CAM leaflets from five independent experiments; P values were calculated using a two-way ANOVA unpaired multiple comparisons, N.S: no significance (P=0.9681); P < 0.0001. Source numerical data are available in source data.

Source data

Extended Data Fig. 6 Migrasome triggers VEGFR2 and AKT phosphorylation.

(a) Cells were treated with migrasome or VEGF165 for 24 hours and the Lysates of cell were analysed by western blot using indicated antibody. 3 repeats were shown (repeat 1 is figure 5q). (b) The relative fold change of indicated signal in the control, VEGF165 and migrasome treated cells was quantified. Data are presented as mean ± SEM; n = 3 from three independent experiments; P values were calculated using a one-way ANOVA unpaired multiple comparisons. VEGFR2 protein level: (N.S: no significance; P=0.9981, Control/control vs. VEGF/control; P=0.9725, Control/control vs. Mig/control). p-VEGFR2 protein level: (P=0.0325, Control/control vs. VEGF/control; P=0.0037, Control/control vs. Mig/control). AKT protein level: (N.S: no significance; P=0.6451, Control/control vs. VEGF/control; P=0.2196, Control/control vs. Mig/control). p-AKT protein level: (P=0.0263, Control/control vs. VEGF/control; P=0.0263, Control/control vs. Mig/control). Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 7 Migrasomes rescue TSPAN4 KD induced capillarization and monocyte recruitment defects.

(a) Migrasomes were delivered to CAM9d by mixing them with Matrigel. After 48 h, CAMs were visualized by stereomicroscopy. Scale bar, 500 µm. (b) Migrasomes were delivered to CAM9d by mixing them with low-melting-point agarose. After 48 h, CAMs were visualized by stereomicroscopy. Scale bar, 500 µm. (c) CAMs from (a) were quantified for the number of newly formed capillaries. Data are presented as mean ± SEM; n =15 fields from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. (d) CAMs from (b) were quantified for the number of sprouting capillaries. Data are presented as mean ± SEM; n =15 fields from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. (e) 48 h after transfection with control of TSPAN4 (T4) siRNA, migrasomes embedded in low-melting-point agarose were added to CAMs. 48 h later, CAMs were visualized by stereomicroscopy. Scale bar, 500 μm. (f) CAMs from (e) were quantified for the relative change in the in the number of sprouting capillaries. Data are presented as means ± SEM, n = 7 fields from three independent experiments, P values were calculated using a two way ANOVA unpaired multiple comparisons, N.S: no significance (P=0.0640), P < 0.0001. Source numerical data are available in source data.

Source data

Extended Data Fig. 8 TSPAN4 KO impairs migrasome formation.

(a) Diagram showing the strategy for knocking out TSPAN4 and knocking in mCherry in chick embryos. The mCherry coding sequence was inserted into TSPAN4 at the position targeted by the sgRNA. Thus, an mCherry-positive signal indicates that native TSPAN4 gene expression was silenced simultaneously. (b) Time-lapse imaging of migration and migrasome formation by WGAhigh cells isolated from WT or TSPAN4-KO CAM8d. Cells were stained by WGA and observed by spinning disk microscopy. Scale bar, 5 µm. (c) CAMs from Fig. 6k and 6l were stained for WGA and observed by spinning disk microscopy. Scale bar, 30 µm. (d) CAMs from Fig. 6k and 6l were quantified for the number of WGAhigh cells. Data are presented as mean ± SEM; n = 15 cells from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. Source numerical data are available in source data.

Source data

Extended Data Fig. 9 Migrasomes rescue VEGFA/CXCL12 KD induced capillarization and monocyte recruitment defects.

(a) CAMs were treated with VEGFA siRNA. 72 h after transfection, the CAMs were harvested, and the VEGFA knockdown efficiency in the CAMs was determined using q–PCR. Data are presented as mean ± SEM; n = 16 pieces from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. (b) CAMs treated with CXCL12 siRNA for 72 h were harvested, and CXCL12 knockdown efficiency in CAM pieces was detected by q–PCR. Data are presented as mean ± SEM; n = 16 pieces from three independent experiments; P values were calculated using a two-tailed, unpaired t-test, P < 0.0001. (c) VEGFA and CXCL12 knockdown efficiencies in siRNA-treated CAM pieces were determined by western blot analysis using then indicated antibodies. (d) CAMs were transfected with the indicated siRNAs. After 48 h, migrasomes embedded in low-melting-point agarose were added. After another 48 h, CAMs were visualized by stereomicroscopy. Scale bar, 1 mm. (e) CAMs treated with VEGF siRNA (top) or CXCL12 siRNA (bottom) from (d) were quantified for the change in the number of sprouting capillaries. Data are presented as mean ± SEM; n = 9 fields from three independent experiments; in siVEGFA group, P values were calculated using a two way ANOVA unpaired multiple comparisons, N.S: no significance (P=0.7626, 96h/0h, siNC+Migrasome vs. siVEGFA+Migrasome); P = 0.0003(96h/0h, siNC+Agarose vs. siNC+Migrasome); P < 0.0001; in siCXCL12 group, P values were calculated using a two way ANOVA unpaired multiple comparisons, P=0.0028 (96h/0h, siNC+Migrasome vs. siCXCL12+Migrasome); P=0.0012 (96h/0h, siCXCL12+Agarose vs. siCXCL12+Migrasome); P<0.0001. Source numerical data and unprocessed blots are available in source data.

Source data

Supplementary information

Supplementary Information

Unprocessed western blots for Figs. 4c,h and 5q and Extended Data Figs. 6a and 9c. Video and table legends.

Reporting Summary

Supplementary Table 1

Oligonucleotide sequences for all TSPAN4, VEGFA, CXCL12 KD siRNA, TSPAN4 knockout gRNA and primers for sequences identification. All sequences shown from 5′ to 3′.

Supplementary Video 1

Migrasome formation in CAM9d in vivo level.

Source data

Source Data Fig. 1

Numerical source data for Fig. 1 statistic results are provided.

Source Data Fig. 2

Numerical source data for Fig. 2 statistic results are provided.

Source Data Fig. 3

Numerical source data for Fig. 3 statistic results are provided.

Source Data Fig. 4

Unprocessed western blots for Fig. 4.

Source Data Fig. 5

Numerical source data for Fig. 5 statistic results are provided.

Source Data Fig. 5

Unprocessed western blots for Fig. 5.

Source Data Fig. 6

Numerical source data for Fig. 6 statistic results are provided.

Source Data Fig. 7

Numerical source data for Fig. 7 statistic results are provided.

Source Data Extended Data Fig. 1

Numerical source data for Extended Data Fig. 1 statistic results are provided.

Source Data Extended Data Fig. 2

Numerical source data for Extended Data Fig. 2 statistic results are provided.

Source Data Extended Data Fig. 5

Numerical source data for Extended Data Fig. 5 statistic results are provided.

Source Data Extended Data Fig. 6

Unprocessed western blots for Extended Data Fig. 6.

Source Data Extended Data Fig. 6

Numerical source data for Extended Data Fig. 6 statistic results are provided.

Source Data Extended Data Fig. 7

Numerical source data for Extended Data Fig. 7 statistic results are provided.

Source Data Extended Data Fig. 8

Numerical source data for Extended Data Fig. 8 statistic results are provided.

Source Data Extended Data Fig. 9

Unprocessed western blots for Extended Data Fig. 9.

Source Data Extended Data Fig. 9

Numerical source data for Extended Data Fig. 9 statistic results are provided.

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Zhang, C., Li, T., Yin, S. et al. Monocytes deposit migrasomes to promote embryonic angiogenesis. Nat Cell Biol 24, 1726–1738 (2022). https://doi.org/10.1038/s41556-022-01026-3

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