Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

eccDNAs are apoptotic products with high innate immunostimulatory activity

Abstract

Extrachromosomal circular DNA elements (eccDNAs) have been described in the literature for several decades, and are known for their broad existence across different species1,2. However, their biogenesis and functions are largely unknown. By developing a new circular DNA enrichment method, here we purified and sequenced full-length eccDNAs with Nanopore sequencing. We found that eccDNAs map across the entire genome in a close to random manner, suggesting a biogenesis mechanism of random ligation of genomic DNA fragments. Consistent with this idea, we found that apoptosis inducers can increase eccDNA generation, which is dependent on apoptotic DNA fragmentation followed by ligation by DNA ligase 3. Importantly, we demonstrated that eccDNAs can function as potent innate immunostimulants in a manner that is independent of eccDNA sequence but dependent on eccDNA circularity and the cytosolic DNA sensor Sting. Collectively, our study not only revealed the origin, biogenesis and immunostimulant function of eccDNAs but also uncovered their sensing pathway and potential clinical implications in immune response.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Development of a three-step eccDNA purification procedure.
Fig. 2: eccDNAs are circularized genomic DNA fragments that map across the genome.
Fig. 3: Apoptotic DNA fragmentation and subsequent ligation by Lig3 are required for eccDNA production in mESCs.
Fig. 4: eccDNAs are potent immunostimulants.
Fig. 5: Sting is required for eccDNA-induced gene expression.

Similar content being viewed by others

Data availability

The eccDNA sequencing data and RNA-seq data have been deposited in the Gene Expression Omnibus (GEO) with accession number GSE165919.

Code availability

The code used to analyse eccDNA sequencing data is available at GitHub (https://github.com/YiZhang-lab/eccDNA_RCA_nanopore).

References

  1. Paulsen, T., Kumar, P., Koseoglu, M. M. & Dutta, A. Discoveries of extrachromosomal circles of DNA in normal and tumor cells. Trends Genet. 34, 270–278 (2018).

    Article  CAS  Google Scholar 

  2. Gaubatz, J. W. Extrachromosomal circular DNAs and genomic sequence plasticity in eukaryotic cells. Mutat. Res. 237, 271–292 (1990).

    Article  CAS  Google Scholar 

  3. Hotta, Y. & Bassel, A. Molecular size and circularity of DNA in cells of mammals and higher plants. Proc. Natl Acad. Sci. USA 53, 356–362 (1965).

    Article  ADS  CAS  Google Scholar 

  4. Moller, H. D. et al. Circular DNA elements of chromosomal origin are common in healthy human somatic tissue. Nat. Commun. 9, 1069 (2018).

    Article  ADS  Google Scholar 

  5. Dillon, L. W. et al. Production of extrachromosomal microDNAs is linked to mismatch repair pathways and transcriptional activity. Cell Rep. 11, 1749–1759 (2015).

    Article  CAS  Google Scholar 

  6. Hull, R. M. et al. Transcription-induced formation of extrachromosomal DNA during yeast ageing. PLoS Biol. 17, e3000471 (2019).

    Article  Google Scholar 

  7. Gresham, D. et al. Adaptation to diverse nitrogen-limited environments by deletion or extrachromosomal element formation of the GAP1 locus. Proc. Natl Acad. Sci. USA 107, 18551–18556 (2010).

    Article  ADS  CAS  Google Scholar 

  8. Sinclair, D. A. & Guarente, L. Extrachromosomal rDNA circles—a cause of aging in yeast. Cell 91, 1033–1042, (1997).

    Article  CAS  Google Scholar 

  9. Shibata, Y. et al. Extrachromosomal microDNAs and chromosomal microdeletions in normal tissues. Science 336, 82–86 (2012).

    Article  ADS  CAS  Google Scholar 

  10. Zhu, J. et al. Molecular characterization of cell-free eccDNAs in human plasma. Sci. Rep. 7, 10968 (2017).

    Article  ADS  Google Scholar 

  11. Cloninger, C., Felton, M., Paul, B., Hirakawa, Y. & Metzenberg, S. Control of pH during plasmid preparation by alkaline lysis of Escherichia coli. Anal. Biochem. 378, 224–225 (2008).

    Article  CAS  Google Scholar 

  12. DeLap, R. J., Rush, M. G., Zouzias, D. & Khan, S. Isolation and preliminary characterization of the small circular DNA present in African green monkey kidney (BSC-1) cells. Plasmid 1, 508–521 (1978).

    Article  CAS  Google Scholar 

  13. Landry, J. J. et al. The genomic and transcriptomic landscape of a HeLa cell line. G3 3, 1213–1224 (2013).

    Article  Google Scholar 

  14. Tichy, E. D. Mechanisms maintaining genomic integrity in embryonic stem cells and induced pluripotent stem cells. Exp. Biol. Med. 236, 987–996 (2011).

    Article  CAS  Google Scholar 

  15. Rang, F. J., Kloosterman, W. P. & de Ridder, J. From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol. 19, 90 (2018).

    Article  Google Scholar 

  16. Joffroy, B., Uca, Y. O., Presern, D., Doye, J. P. K. & Schmidt, T. L. Rolling circle amplification shows a sinusoidal template length-dependent amplification bias. Nucleic Acids Res. 46, 538–545 (2018).

    Article  CAS  Google Scholar 

  17. Soh, Y. Q. et al. Sequencing the mouse Y chromosome reveals convergent gene acquisition and amplification on both sex chromosomes. Cell 159, 800–813 (2014).

    Article  CAS  Google Scholar 

  18. Marichal, T. et al. DNA released from dying host cells mediates aluminum adjuvant activity. Nat. Med. 17, 996–1002 (2011).

    Article  CAS  Google Scholar 

  19. Sakahira, H., Enari, M. & Nagata, S. Cleavage of CAD inhibitor in CAD activation and DNA degradation during apoptosis. Nature 391, 96–99 (1998).

    Article  ADS  CAS  Google Scholar 

  20. Li, L. Y., Luo, X. & Wang, X. Endonuclease G is an apoptotic DNase when released from mitochondria. Nature 412, 95–99 (2001).

    Article  ADS  CAS  Google Scholar 

  21. Shiokawa, D., Kobayashi, T. & Tanuma, S. Involvement of DNase γ in apoptosis associated with myogenic differentiation of C2C12 cells. J. Biol. Chem. 277, 31031–31037 (2002).

    Article  CAS  Google Scholar 

  22. Arakawa, H. et al. Functional redundancy between DNA ligases I and III in DNA replication in vertebrate cells. Nucleic Acids Res. 40, 2599–2610, (2012).

    Article  CAS  Google Scholar 

  23. Lu, G. et al. Ligase I and ligase III mediate the DNA double-strand break ligation in alternative end-joining. Proc. Natl Acad. Sci. USA 113, 1256–1260 (2016).

    Article  ADS  CAS  Google Scholar 

  24. Simsek, D. et al. Crucial role for DNA ligase III in mitochondria but not in Xrcc1-dependent repair. Nature 471, 245–248 (2011).

    Article  ADS  CAS  Google Scholar 

  25. Li, Y., Berke, I. C. & Modis, Y. DNA binding to proteolytically activated TLR9 is sequence-independent and enhanced by DNA curvature. EMBO J. 31, 919–931 (2012).

    Article  CAS  Google Scholar 

  26. Lange, S. S. & Vasquez, K. M. HMGB1: the jack-of-all-trades protein is a master DNA repair mechanic. Mol. Carcinog. 48, 571–580 (2009).

    Article  CAS  Google Scholar 

  27. Wang, Z. et al. Regulation of innate immune responses by DAI (DLM-1/ZBP1) and other DNA-sensing molecules. Proc. Natl Acad. Sci. USA 105, 5477–5482 (2008).

    Article  ADS  CAS  Google Scholar 

  28. Green, D. R., Ferguson, T., Zitvogel, L. & Kroemer, G. Immunogenic and tolerogenic cell death. Nat. Rev. Immunol. 9, 353–363 (2009).

    Article  CAS  Google Scholar 

  29. Sundaresan, R., Parameshwaran, H. P., Yogesha, S. D., Keilbarth, M. W. & Rajan, R. RNA-independent DNA cleavage activities of Cas9 and Cas12a. Cell Rep. 21, 3728–3739 (2017).

    Article  CAS  Google Scholar 

  30. Putney, S. D., Benkovic, S. J. & Schimmel, P. R. A DNA fragment with an α-phosphorothioate nucleotide at one end is asymmetrically blocked from digestion by exonuclease III and can be replicated in vivo. Proc. Natl Acad. Sci. USA 78, 7350–7354 (1981).

    Article  ADS  CAS  Google Scholar 

  31. Sauer, J. D. et al. The N-ethyl-N-nitrosourea-induced Goldenticket mouse mutant reveals an essential function of Sting in the in vivo interferon response to Listeria monocytogenes and cyclic dinucleotides. Infect. Immun. 79, 688–694 (2011).

    Article  CAS  Google Scholar 

  32. Hou, B., Reizis, B. & DeFranco, A. L. Toll-like receptors activate innate and adaptive immunity by using dendritic cell-intrinsic and -extrinsic mechanisms. Immunity 29, 272–282 (2008).

    Article  CAS  Google Scholar 

  33. Oberhammer, F. et al. Apoptotic death in epithelial cells: cleavage of DNA to 300 and/or 50 kb fragments prior to or in the absence of internucleosomal fragmentation. EMBO J. 12, 3679–3684 (1993).

    Article  CAS  Google Scholar 

  34. Shiokawa, D. & Tanuma, S. Differential DNases are selectively used in neuronal apoptosis depending on the differentiation state. Cell Death Differ. 11, 1112–1120 (2004).

    Article  CAS  Google Scholar 

  35. Wang, H. et al. DNA ligase III as a candidate component of backup pathways of nonhomologous end joining. Cancer Res. 65, 4020–4030 (2005).

    Article  CAS  Google Scholar 

  36. Cox, D., Yuncken, C. & Spriggs, A. I. Minute chromatin bodies in malignant tumours of childhood. Lancet 1, 55–58 (1965).

    Article  CAS  Google Scholar 

  37. Turner, K. M. et al. Extrachromosomal oncogene amplification drives tumour evolution and genetic heterogeneity. Nature 543, 122–125 (2017).

    Article  ADS  CAS  Google Scholar 

  38. Li, X. D. et al. Pivotal roles of cGAS–cGAMP signaling in antiviral defense and immune adjuvant effects. Science 341, 1390–1394 (2013).

    Article  ADS  CAS  Google Scholar 

  39. Andreeva, L. et al. cGAS senses long and HMGB/TFAM-bound U-turn DNA by forming protein–DNA ladders. Nature 549, 394–398 (2017).

    Article  ADS  CAS  Google Scholar 

  40. Tovey, M. G., Lallemand, C. & Thyphronitis, G. Adjuvant activity of type I interferons. Biol. Chem. 389, 541–545 (2008).

    Article  CAS  Google Scholar 

  41. Moore, J. B. & June, C. H. Cytokine release syndrome in severe COVID-19. Science 368, 473–474 (2020).

    Article  ADS  CAS  Google Scholar 

  42. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  43. Ignatiadis, N., Klaus, B., Zaugg, J. B. & Huber, W. Data-driven hypothesis weighting increases detection power in genome-scale multiple testing. Nat. Methods 13, 577–580 (2016).

    Article  CAS  Google Scholar 

  44. Du, Q., Kotlyar, A. & Vologodskii, A. Kinking the double helix by bending deformation. Nucleic Acids Res. 36, 1120–1128 (2008).

    Article  CAS  Google Scholar 

  45. Liu, D. et al. Branched kissing loops for the construction of diverse RNA homooligomeric nanostructures. Nat. Chem. 12, 249–259 (2020).

    Article  CAS  Google Scholar 

  46. Li, H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34, 3094–3100 (2018).

    Article  CAS  Google Scholar 

  47. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  Google Scholar 

  48. Gel, B. & Serra, E. karyoploteR: an R/Bioconductor package to plot customizable genomes displaying arbitrary data. Bioinformatics 33, 3088–3090 (2017).

    Article  CAS  Google Scholar 

  49. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  Google Scholar 

  50. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  Google Scholar 

  51. Ramirez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).

    Article  CAS  Google Scholar 

  52. Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).

    Article  CAS  Google Scholar 

  53. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Article  CAS  Google Scholar 

  54. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank D. Schatz (Yale University) for the antibody to mouse Lig4, R. Rajan (University of Oklahoma) for the initial gift of FnoCas protein, X. Zhang for help in BMDC preparation, P. Yin for allowing us to use the AFM instrument and J. Lieberman for critical reading of the manuscript. H.C. was supported by a Leukemia and Lymphoma Society Fellow Award. D.L. is a Merck Fellow of the Life Sciences Research Foundation. This work was supported by the Howard Hughes Medical Institute. F.W.A. and Y.Z. are Investigators of the Howard Hughes Medical Institute.

Author information

Authors and Affiliations

Authors

Contributions

Y.Z. conceived the project; Y.W. and Y.Z. designed the experiments; Y.W. performed the majority of the experiments; H.C. generated the ligase-knockout cell lines; M.W. developed the method to call eccDNA from Nanopore data and performed all bioinformatics analyses; M.N.D. performed pilot analysis of eccDNA sequencing data; D.L. helped with the SAFM imaging; F.W.A. supervised the work by H.C.; Y.W. and Y.Z. wrote the manuscript.

Corresponding author

Correspondence to Yi Zhang.

Ethics declarations

Competing interests

A patent application (with the patent agency Wolf, Greenfield & Sacks) covering the eccDNA purification method and the application of eccDNA as an immunostimulatant has been filed by the Boston Children’s Medical Center Corporation.

Additional information

Peer review information Nature thanks Birgitte Regenberg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Selective binding of eccDNAs to beads and high sensitivity of DNA detection by SYBR Gold staining.

a, Representative gel image showing selective binding of circular DNA to magnetic silica beads in solution A. The assay was tested with 200× (mass) linear DNA (lane 4 and 6) and 1X (mass) DNA circles (lane 5 and 6). Lanes 1-3 indicate the input DNAs. Lane 1, 0.5% of input linear DNA for lane 4 was loaded; lane 2, equal amount of input circular DNAs for lane 5 were loaded; lane 3, 0.5% of input linear DNA and equal amount of input circular DNAs for lane 6 were loaded. Lanes 4-6 were DNAs recovered from Solution A. lane 4, 200× (mass) linear DNA alone undergone purification by solution A; lane 5, 1× (mass) DNA circles undergone purification by solution A; lane 6 mixture of 200× (mass) linear DNA and 1× (mass) DNA circles undergone purification by solution A. Note, only circular DNAs were recovered. The recovery rate was very high, particularly for the smaller circular DNAs, C2: a 200 bp circle, C5: a 525 bp circle. b, High sensitivity of DNA detection using vertical agarose gel electrophoresis and SYBR Gold staining. 0.2 μl commercial DNA ladder (total of 10 ng) was undergone 5× series dilutions and fractionated by 1% vertical agarose gel electrophoresis, stained by SYBR Gold, DNA in lane-4 were 125× diluted of that in lane-1, and could still be visualized. The detection limit is estimated as 5-10 pg/band. Results in ab are representative of three independent experiments.

Extended Data Fig. 2 Summary of the nanopore sequencing data.

a, Diagram of nanopore long read sequencing of eccDNA. Tandem copies of eccDNAs were self-concatenated to long molecule by rolling cycle amplification (RCA), and directly read through by Oxford Nanopore. Each copy of eccDNA molecule in a single long molecule was sequenced multiple times. “S”: split site. b, Summary of mESC eccDNA long reads from an Oxford Nanopore MinION flow cell. c, Diagram showing how the eccDNA full-length sequence is called and categorized. Nanopore reads from (a), the dashed box, were aligned to a single locus (Continuous) or to multiple loci (Non-continuous) in genome. Continuous: an example of six sub-regions of a long nanopore read repeatedly aligned to a single locus, where full length sequence of eccDNA was presented with only one split site (S); Non-continuous: an example of eight sub-regions of a single long read sequentially aligned to two separate loci (Locus-1 and Locus-2), representing an eccDNA ligated by two genomic fragments (2f ecc) with two split sites (S1 and S2). d, Criteria for eccDNA calling. EccDNAs were called based on their number of full passes aligned to the genome. Long reads with less than two full passes were discarded (left and middle panel). Left, Nanopore read that hits genome only once either fails to designate the genomic start and end site of eccDNA (up panel), or miss the middle region (bottom panel) that may or may not include in the original eccDNA molecule (Uncertain); Middle, because of potential sequencing error of Oxford Nanopore, reads that hit genome more than once but less than twice (1 full pass) were also discarded due to the lack of confirmation in eccDNA calling, particularly on designating the start and end site of eccDNA. Right, eccDNA molecules were called from long reads when covered at least twice (>=2 full pass) on their aligned loci.

Extended Data Fig. 3 Summary of Illumina short read sequencing and Chromosomal distribution of eccDNA fragments.

a, Summary of eccDNA short read sequencing without RCA. Purified eccDNA was directly tagmented with Tn5 (Illumina Nextera), and sequenced with Illumina Hiseq 2500 in PE150 mode. b, Chromosomal distribution of eccDNA short reads.

Extended Data Fig. 4 Effects of Endonuclease G, DNase γ, and DNA ligases knockout on apoptosis and eccDNA generation.

a, Quantification of eccDNA from cells of the indicated treatment. EccDNA production was presented as nanogram per 10 million cells; ud, under detection limit. Bars indicate mean ± s.e.m. of three independent experiments. b, Diagram illustration and PCR confirmation of the EndoG knockout mESC line. Gene structure of EndoG, sgRNAs (red arrows), two sets of screen primers for internal sites (black arrowhead, “n” =negative knockout cell line) and external sites (red arrowhead, “p” =positive knockout cell line) were shown. c, Diagram illustration and PCR confirmation of the DNase γ knockout mESC lines. Gene structure of DNase γ, sgRNAs (red arrows), two sets of screen primers for internal sites (black arrowhead, “n” =negative knockout cell line) and external sites (red arrowhead, “p” =positive knockout cell line) were shown. d, Cell viability is not affected by EndoG or DNase γ KO. Cell viability was evaluated by flow cytometry, after staining with Far Red Live/Dead Cell Stain Kit, FSC-A/SSC-A and FSC-A/FSC-H were sequentially used to exclude debris and gate on singlets, respectively, then gate on APC+ as dead cells. Bars indicate mean ± s.e.m. of dead cell ratio from three independent experiments. e, Deficiency of DNase γ or EndoG in mESC do not significantly alter UV-induced cell death. Cell death was measured by flow cytometry, after staining with Far Red Live/Dead Cell Stain Kit, FSC-A/SSC-A and FSC-A/FSC-H were sequentially used to exclude debris and gate on singlets, respectively, then gate on APC+ as dead cells. Bar indicate mean ± s.e.m. of dead cell ratio of 3 independent experiments. f, Quantification of eccDNAs presented in Fig. 3d. EccDNAs below the mtDNA band were quantified by densitometry (by Image J 1.53e) and presented as relative levels to that in WT cells of parallel eccDNA purifications. Bars indicate mean ± s.e.m. of three independent experiments. g, Quantification of eccDNA below the mtDNA band by densitometry (by Image J 1.53e). Data are presented as relative levels to that purified from WT cells of parallel eccDNA purifications (Fig. 3g), bars indicate mean ± s.e.m. of three independent experiments. Ordinary one-way ANOVA with Tukey’s multiple comparison test was used for multiple comparisons in e, f, g. **, p<0.01; ns, no significant.

Extended Data Fig. 5 EccDNAs are potent immunostimulants for BMDCs.

a, Confirmation of BMDC identity by flow cytometry. After differentiating bone marrow cells with 20 ng/ml GM-CSF for 7 days, cell debris (left) were first excluded and singlets (middle) were then phenotyped on the basis of their CD11c and major histocompatibility complex II (MHCII) expression (right) to define BMDC, the numbers indicate the percentage of gated cells. Data were further analyzed with FlowJo. V10.8.0 and shown as representative of 2 independent experiments. b, Various DNAs were resolved by agarose gel electrophoresis. Li-DNA: sheared linear genomic DNA; poly(dG:dC), poly(deoxyguanylic-deoxycytidylic). Representative gel of three independent experiments was shown. c, d, Bar graphs showing the relative mRNA (c) and protein (ELISA) (d) levels of IL-6 and TNF-α. Data is shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment in three independent experiments. e, f, DNase I pretreatment abolishes IL-6 and TNF-α induction by eccDNA. Equal amount of DNA (120 ng/ml) used to prepare transfection mixtures were pre-treated with or without DNase I as indicated, then transfected to BMDCs. 12 h later, total RNA was extracted for RT-qPCR (e) and medium was collected for ELISA (f). Data are shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment in three independent experiments. Comparisons in cf were done on biological replicates by Ordinary one-way ANOVA with Tukey’s multiple comparison test. *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001; ns, no significant; nd, not detected.

Extended Data Fig. 6 EccDNAs are potent immunostimulants for BMDMs.

a, Confirmation of BMDMs identify by flow cytometry. After differentiating bone marrow cells with L929 conditioned medium for 7 days, cells debris (left) were first excluded and singlets (middle) were phenotyped on the basis of F4/80 and CD11b expression (right) to define BMDM, the numbers indicate the percentage of gated cells. Data were further analyzed with FlowJo. V10.8.0 and shown as representative of 2 independent experiments. b, c, EccDNAs induce cytokine genes in BMDMs. Bar graphs showing the induction of mRNA (b) and protein (c) of IL-6 and TNF-α in BMDMs that transfected with varying levels of eccDNA, compared with fragmented linear DNA, and poly(dG:dC). RT-qPCR were performed after 12-hours transfection. ELISA analysis (c) was performed after 24-hours transfection. Data are shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment of three independent experiments. Comparisons were performed on biological replicates with equal amount of DNA transfection by Ordinary one-way ANOVA with Tukey’s multiple comparison test. *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001; ns, no significant; nd, not detected.

Extended Data Fig. 7 The circularity of eccDNAs, but not the sequence, is critical for their immunostimulant activity.

a, Bar graphs showing the relative IL-6 and TNF-α mRNA levels. Data is shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment in three independent experiments. b, c, Bar graphs showing the relative IL-6 and TNF-α mRNA levels (b), and protein (ELISA) levels (c). Data is shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment in three independent experiments. d, Diagram of DNA transfection efficiency and stability assay. Step-1: 5 Phosphorothioate (purple “*”) end-protected synthetic linear DNA (PS-syn-linear) and its circular form with equal number of phosphorothioate bonds (PS-Syn-circular) were transfected to BMDCs in the same way as in Fig. 5 for either 1 or 12 h. Step-2: cells were lysed in 100 μl lysis buffer and treated with Thermoliable Proteinase K to prepare total DNA. Step-3: 4 μl total DNA was used for qPCR with a set of primers that amplify a 117 bp fragment in both linear and circular DNA. e, qPCR analysis of the samples prepared as described in (d). Transfected DNA level was normalized to that of 10 ng/ml PS-syn-linear transfection (n= 4 or 6, as indicated by dotes). Bars indicate mean ± s.e.m. of three independent experiments. f, 12 h after transfection of indicated DNA at 30 ng/ml, medium was collected for ELISA essay, Data are shown as mean ± s.e.m. of replicates (n=4 per group) of a representative experiment in three independent experiments. Comparisons in ac were performed on biological replicates by Ordinary one-way ANOVA with Tukey’s multiple comparison test; two-tailed unpaired t tests (e, f). *, p<0.05; **, p<0.01; ***, p<0.001; ****, p<0.0001; ns, no significant.

Extended Data Fig. 8 Reproducibility of the BMDC transcriptomes.

ac, Scatter plot of pair-wise comparison of the transcriptomes of three independent BMDC samples of untreated (a), treated with eccDNA (b) or linear DNA (c). The x and y-axis are log2(FPKM+0.1).

Extended Data Fig. 9 Global transcriptional response to eccDNA in BMDMs.

ac, Scatter plot of pair-wise comparison of the transcriptomes of three independent BMDM samples of untreated (a), treated with eccDNA (b) or linear DNA (Extended Data Fig. 6). The x and y-axis are log2(FPKM+0.1). d, Scatter plot showing 380 genes (left panel, red dots) that are significantly induced (FC ≥ 5, adjusted p-value < 0.001; FC and p-value were generated using DESeq242 and p-values were adjusted by IHW43) by eccDNA, but not linear DNA, in BMDMs. 24 significantly induced cytokine genes are indicated (right panel, red dots). The x and y-axis are log2-transformed normalized read counts. e, Heatmap presentation of the top 20 induced genes. f, GO terms enriched in the genes activated by eccDNA treatment in BMDMs. The number of genes in each term and the p-value of the enrichment is indicated.

Extended Data Fig. 10 Analysis of the eccDNA sensing pathway.

a, Scatter plot indicates the transcriptomes of the two replicates of synthetic circular DNA treated BMDCs are highly similar. The x and y-axis are log2(FPKM+0.1). b, Western blot confirmation of the Sting-/- and Myd88-/- cells. Blots were performed once, but cell genotypes were further confirmed by mRNA sequences from RNA-seq data (data not shown). c, Correlation of the transcriptomes of 2 replicates eccDNA treated Sting-/- and Myd88-/- BMDC. The x and y-axis are log2(FPKM+0.1).

Supplementary information

Supplementary Fig. 1

This file contains uncropped images of agarose gels and scan images of immunoblotting.

Reporting Summary

Supplementary Table 1

List of CRISPR–Cas9 guide RNA and genotyping PCR primer sequences for the different knockout cell lines

Supplementary Table 2

List of RT–qPCR primer sequences for the various cytokine genes analysed

Supplementary Table 3

List of synthetic small DNAs and their PCR amplification primer sequences

Supplementary Table 4

List of the differentially expressed genes in eccDNA-treated BMDCs

Supplementary Table 5

List of the differentially expressed genes in eccDNA-treated BMDMs

Supplementary Table 6

List of the differentially expressed genes in eccDNA-treated BMDCs in response to Sting1 or Myd88 knockout

Peer Review File

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, Y., Wang, M., Djekidel, M.N. et al. eccDNAs are apoptotic products with high innate immunostimulatory activity. Nature 599, 308–314 (2021). https://doi.org/10.1038/s41586-021-04009-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41586-021-04009-w

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing