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Detection of low-frequency mutations in clinical samples by increasing mutation abundance via the excision of wild-type sequences

Nature Biomedical Engineering volume 7, pages 1602–1613 (2023)Cite this article

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Abstract

The efficiency of DNA-enrichment techniques is often insufficient to detect mutations that occur at low frequencies. Here we report a DNA-excision method for the detection of low-frequency mutations in genomic DNA and in circulating cell-free DNA at single-nucleotide resolution. The method is based on a competitive DNA-binding-and-digestion mechanism, effected by deoxyribonuclease I (DNase) guided by single-stranded phosphorothioated DNA (sgDNase), for the removal of wild-type DNA strands. The sgDNase can be designed against any wild-type DNA sequences, allowing for the uniform enrichment of all the mutations within the target-binding region of single-stranded phosphorothioated DNA at mild-temperature conditions. Pretreatment with sgDNase enriches all mutant strands with initial frequencies down to 0.01% and leads to high discrimination factors for all types of single-nucleotide mismatch in multiple sequence contexts, as we show for the identification of low-abundance mutations in samples of blood or tissue from patients with cancer. The method can be coupled with next-generation sequencing, droplet digital polymerase chain reaction, Sanger sequencing, fluorescent-probe-based assays and other mutation-detection methods.

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Fig. 1: Proof of concept: phosphorothioated DNA-guided deoxyribonuclease I (sgDNase).
Fig. 2: sgDNase with single-nucleotide resolution.
Fig. 3: Enrichment of single and multiplex hotspot mutations by sgDNase pretreatment.
Fig. 4: Performance of single-plexed and multiplexed sgDNase pretreatment.
Fig. 5: Direct pretreatment of gDNA by dsgDNase.
Fig. 6: Detection of ultra-low-abundance mutations in clinical biopsy samples with sgDNase pretreatment.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. All data generated during the study are available from figshare with the identifier https://doi.org/10.6084/m9.figshare.23529204. Source data for the figures are provided with this paper.

References

  1. Vogelstein, B. et al. Genetic alterations during colorectal-tumor development. N. Engl. J. Med. 319, 525–532 (1988).

    Article  PubMed  CAS  Google Scholar 

  2. Abascal, F. et al. Somatic mutation landscapes at single-molecule resolution. Nature 593, 405–410 (2021).

  3. Diaz, L. A. & Bardelli, A. Liquid biopsies: genotyping circulating tumor DNA. J. Clin. Oncol. 32, 579–586 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Abbosh, C., Birkbak, N. J. & Swanton, C. Early stage NSCLC—challenges to implementing ctDNA-based screening and MRD detection. Nat. Rev. Clin. Oncol. 15, 577–586 (2018).

    Article  PubMed  CAS  Google Scholar 

  5. Lo, Y. M. D., Han, D. S. C., Jiang, P. & Chiu, R. W. K. Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies. Science 372, eaaw3616 (2021).

    Article  PubMed  CAS  Google Scholar 

  6. Bettegowda, C. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med. 6, 224ra24 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Baker, M. Digital PCR hits its stride. Nat. Methods 9, 541–544 (2012).

    Article  CAS  Google Scholar 

  8. Bielas, J. H. & Loeb, L. A. Quantification of random genomic mutations. Nat. Methods 2, 285–290 (2005).

    Article  PubMed  CAS  Google Scholar 

  9. Dressman, D., Yan, H., Traverso, G., Kinzler, K. W. & Vogelstein, B. Transforming single DNA molecules into fluorescent magnetic particles for detection and enumeration of genetic variations. Proc. Natl Acad. Sci. USA 100, 8817–8822 (2003).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Das, J., Ivanov, I., Sargent, E. H. & Kelley, S. O. DNA clutch probes for circulating tumor DNA analysis. J. Am. Chem. Soc. 138, 11009–11016 (2016).

    Article  PubMed  CAS  Google Scholar 

  11. Kutyavin, I. V. et al. 3′-minor groove binder-DNA probes increase sequence specificity at PCR extension temperatures. Nucleic Acids Res. 28, 655–661 (2000).

  12. Singh, S. K., Nielsen, P., Koshkin, A. A. & Wengel, J. LNA (locked nucleic acids): synthesis and high-affinity nucleic acid recognition. Chem. Commun. 1998, 455–456 (1998).

  13. Schmitt, M. W. et al. Detection of ultra-rare mutations by next-generation sequencing. Proc. Natl Acad. Sci. USA 109, 14508–14513 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Milbury, C. A., Li, J. & Makrigiorgos, G. M. PCR-based methods for the enrichment of minority alleles and mutations. Clin. Chem. 55, 632–640 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Li, J. et al. Replacing PCR with COLD-PCR enriches variant DNA sequences and redefines the sensitivity of genetic testing. Nat. Med. 14, 579–584 (2008).

    Article  PubMed  CAS  Google Scholar 

  16. How Kit, A. et al. Sensitive detection of KRAS mutations using enhanced-ice-COLD-PCR mutation enrichment and direct sequence identification. Hum. Mutat. 34, 1568–1580 (2013).

    Article  PubMed  Google Scholar 

  17. Dominguez, P. L. & Kolodney, M. S. Wild-type blocking polymerase chain reaction for detection of single nucleotide minority mutations from clinical specimens. Oncogene 24, 6830–6834 (2005).

    Article  PubMed  CAS  Google Scholar 

  18. Oldenburg, R. P., Liu, M. S. & Kolodney, M. S. Selective amplification of rare mutations using locked nucleic acid oligonucleotides that competitively inhibit primer binding to wild-type DNA. J. Invest. Dermatol. 128, 398–402 (2008).

    Article  PubMed  CAS  Google Scholar 

  19. Wu, L. R., Chen, S. X., Wu, Y., Patel, A. A. & Zhang, D. Y. Multiplexed enrichment of rare DNA variants via sequence-selective and temperature-robust amplification. Nat. Biomed. Eng. 1, 714–723 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Song, P. et al. Selective multiplexed enrichment for the detection and quantitation of low-fraction DNA variants via low-depth sequencing. Nat. Biomed. Eng. 5, 690–701 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Darbeheshti, F., Yu, F., Ahmed, F., Adalsteinsson, V. A. & Makrigiorgos, G. M. Recent developments in mutation enrichment and detection technologies. Clin. Chem. 68, 1250–1260 (2022).

    Article  PubMed  Google Scholar 

  22. Song, C. et al. Elimination of unaltered DNA in mixed clinical samples via nuclease-assisted minor-allele enrichment. Nucleic Acids Res. 44, e146 (2016).

    PubMed  PubMed Central  Google Scholar 

  23. Zhulidov, P. A. et al. Simple cDNA normalization using kamchatka crab duplex-specific nuclease. Nucleic Acids Res. 32, e37 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gu, W. et al. Depletion of abundant sequences by hybridization (DASH): using Cas9 to remove unwanted high-abundance species in sequencing libraries and molecular counting applications. Genome Biol. 17, 41 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Fu, Y. et al. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat. Biotechnol. 31, 822–826 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Song, J. et al. Highly specific enrichment of rare nucleic acid fractions using Thermus thermophilus argonaute with applications in cancer diagnostics. Nucleic Acids Res. 48, e19 (2020).

    Article  PubMed  Google Scholar 

  27. Liu, Q. et al. Argonaute integrated single-tube PCR system enables supersensitive detection of rare mutations. Nucleic Acids Res. 49, e75 (2021).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Haldar, T. et al. Unexpected complexity in the products arising from NaOH-, heat-, amine-, and glycosylase-induced strand cleavage at an abasic site in DNA. Chem. Res. Toxicol. 35, 218–232 (2022).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Xiao, X., Wu, T., Gu, F. & Zhao, M. Generation of artificial sequence-specific nucleases via a preassembled inert-template. Chem. Sci. 7, 2051–2057 (2016).

    Article  PubMed  CAS  Google Scholar 

  30. Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  PubMed  CAS  Google Scholar 

  31. Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).

  32. Gilar, M. et al. Ion-pair reversed-phase high-performance liquid chromatography analysis of oligonucleotides: retention prediction. J. Chromatogr. A 958, 167–182 (2002).

    Article  PubMed  CAS  Google Scholar 

  33. Wu, T. et al. DNA terminal structure-mediated enzymatic reaction for ultra-sensitive discrimination of single nucleotide variations in circulating cell-free DNA. Nucleic Acids Res. 46, e24 (2018).

    Article  PubMed  CAS  Google Scholar 

  34. Shepherd, F. A. et al. Erlotinib in previously treated non-small-cell lung cancer. N. Engl. J. Med. 353, 123–132 (2005).

    Article  PubMed  CAS  Google Scholar 

  35. Soria, J. C. et al. Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N. Engl. J. Med. 378, 113–125 (2018).

    Article  PubMed  CAS  Google Scholar 

  36. Hoshika, S. et al. Hachimoji DNA and RNA: a genetic system with eight building blocks. Science 363, 884–887 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Watkins, N. E. Jr. & SantaLucia, J. Jr. Nearest-neighbor thermodynamics of deoxyinosine pairs in DNA duplexes. Nucleic Acids Res. 33, 6258–6267 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Zhang, D. Y. & Seelig, G. Dynamic DNA nanotechnology using strand-displacement reactions. Nat. Chem. 3, 103–113 (2011).

    Article  PubMed  CAS  Google Scholar 

  39. Limaye, N. et al. Somatic mutations in angiopoietin receptor gene TEK cause solitary and multiple sporadic venous malformations. Nat. Genet. 41, 118–124 (2009).

    Article  PubMed  CAS  Google Scholar 

  40. Soblet, J. et al. Blue Rubber Bleb Nevus (BRBN) syndrome is caused by somatic TEK (TIE2) mutations. J. Invest. Dermatol. 137, 207–216 (2017).

    Article  PubMed  CAS  Google Scholar 

  41. Martinez-Lopez, A. et al. CLOVES syndrome: review of a PIK3CA-related overgrowth spectrum (PROS). Clin. Genet. 91, 14–21 (2017).

    Article  PubMed  CAS  Google Scholar 

  42. Wassef, M. et al. Vascular anomalies classification: recommendations from the International Society for the Study of Vascular Anomalies. Pediatrics 136, E203–E214 (2015).

    Article  PubMed  Google Scholar 

  43. Kurreck, J. Antisense technologies. Improvement through novel chemical modifications. Eur. J. Biochem. 270, 1628–1644 (2003).

    Article  PubMed  CAS  Google Scholar 

  44. Stein, C. A. & Cheng, Y. C. Antisense oligonucleotides as therapeutic agents—is the bullet really magical. Science 261, 1004–1012 (1993).

    Article  PubMed  CAS  Google Scholar 

  45. Liang, C. & Allen, L. C. Sulfur does not form double bonds in phosphorothioate anions. J. Am. Chem. Soc. 109, 6449–6453 (1987).

    Article  CAS  Google Scholar 

  46. Wang, L. et al. Phosphorothioation of DNA in bacteria by dnd genes. Nat. Chem. Biol. 3, 709–710 (2007).

    Article  PubMed  CAS  Google Scholar 

  47. Pechenaya, V. I. Influence of electrostatic interactions on the sugar phosphate backbone conformation in DNA. Biopolymers 33, 37–44 (1993).

    Article  PubMed  CAS  Google Scholar 

  48. Horton, N. C., Connolly, B. A. & Perona, J. J. Inhibition of EcoRV endonuclease by deoxyribo-3′-S-phosphorothiolates: a high-resolution X-ray crystallographic study. J. Am. Chem. Soc. 122, 3314–3324 (2000).

  49. Zhang, Y. C. et al. Theoretical study on steric effects of DNA phosphorothioation: B-helical destabilization in Rp-phosphorothioated DNA. J. Phys. Chem. B 116, 10639–10648 (2012).

    Article  PubMed  CAS  Google Scholar 

  50. Thorogood, H., Grasby, J. A. & Connolly, B. A. Influence of the phosphate backbone on the recognition and hydrolysis of DNA by the EcoRV restriction endonuclease—a study using oligodeoxynucleotide phosphorothioates. J. Biol. Chem. 271, 8855–8862 (1996).

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

We thank the National Center for Protein Science at Peking University (Beijing, China) for assistance with droplet digital PCR. This work was supported by the National Natural Science Foundation of China (22174005, 21974005, 21575008).

Author information

Author notes

  1. These authors contributed equally: Wei Chen, Haiqi Xu, Shenbin Dai.

Authors and Affiliations

  1. Beijing National Laboratory for Molecular Sciences and MOE Key Laboratory of Bioorganic Chemistry and Molecular Engineering, College of Chemistry and Molecular Engineering, Peking University, Beijing, China

    Wei Chen, Haiqi Xu, Shenbin Dai, Jiayu Wang, Ziyu Yang, Yuewen Jin, Mengbing Zou, Xianjin Xiao, Tongbo Wu & Meiping Zhao

  2. Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Xianjin Xiao

  3. School of Pharmacy, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

    Tongbo Wu

  4. Department of Dermatology, Peking University First Hospital, Beijing Key Laboratory of Molecular Diagnosis on Dermatoses and National Clinical Research Center for Skin and Immune Diseases, Beijing, China

    Wei Yan & Zhimiao Lin

  5. Department of Dermatology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China

    Bin Zhang

  6. Department of Dermatology, Zhengzhou University, Affiliated Children’s Hospital, Henan Children’s Hospital, Zhengzhou Children’s Hospital, Zhengzhou, China

    Bin Zhang

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Contributions

M. Zhao conceived the project. M. Zhao, W.C., T.W. and X.X. performed the sequences and experiments design. W.C., H.X. and S.D. conducted the experiments and data analysis. J.W., Z.Y., Y.J. and M. Zou helped improve some experiments. Z.L., W.Y. and B.Z. provided blood and tissue samples from patients with venous malformations. X.X. provided blood and tissue samples from patients with NSCLC or colorectal cancer. W.C., T.W. and M. Zhao wrote the manuscript.

Corresponding authors

Correspondence to Xianjin Xiao, Tongbo Wu or Meiping Zhao.

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Competing interests

Peking University holds an issued Chinese patent (patent number: ZL 2019 1 0052680.4) on this work. The authors declare no other competing interests.

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Nature Biomedical Engineering thanks Feng Li, David Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Multiplexed sgDNase pretreatment.

Next-generation sequencing results of the five EGFR and KRAS mutations (EGFR L858R, EGFR 19del, EGFR G719S, EGFR T790M and KRAS G13D) in mixed synthetic samples before (a1-a5) and after (b1-b5) 5-plex sgDNase pretreatment. The initial mutation abundance was 0.4% for EGFR G719S and 0.1% for other tested mutation. The five target mutations were pretreated by sgDNase simultaneously. The variant to noise plots derived from Illumina MiSeq sequencing data are depicted.

Source Data

Extended Data Fig. 2 Detection of low-abundance mutations in clinical samples with sgDNase pretreatment.

NGS measurement results of the abundance of EGFR L858R mutation in a gDNA (P2-T) and b cfDNA (P2-B) without sgDNase pretreatment. Variant to noise plots derived from Illumina MiSeq sequencing data are depicted.

Source Data

Extended Data Fig. 3 Summary of sample test results with sgDNase pretreatment.

a, Beeswarm plot of post-VAFs of 309 negative control gDNA samples and 267 positive samples with pre-VAF at 0.01% after sgDNase pretreatment. b, Receiver operator characteristic (ROC) plot for post-VAFs of samples in a after pretreatment by sgDNase.

Source Data

Supplementary information

Supplementary Information

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Chen, W., Xu, H., Dai, S. et al. Detection of low-frequency mutations in clinical samples by increasing mutation abundance via the excision of wild-type sequences. Nat. Biomed. Eng 7, 1602–1613 (2023). https://doi.org/10.1038/s41551-023-01072-8

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