Design of nucleic acid biosensors based on CRISPR/Cas systems and reporter split-proteins

For the diagnosis of many humans, animals and plant diseases, environmental monitoring, highly sensitive, specific, fast and easy-to-use diagnostic methods for the detection of nucleic acids of pathogens are required. Alternative to the PCR method, which requires expensive laboratory equipment, approaches based on the use of the natural ability of bacterial CRISPR/Cas9 systems to recognize DNA sequences with high specificity under isothermal conditions. The development of methods for signal registration during the formation of a DNA/RNA/Cas9-protein complex is a separate bioengineering task. In this work, we have designed and studied the applicability of a biosensor system based on a combination of the ability of dCas9-proteins to bind to target DNA sequences (without cutting them) and the capabilities of reporter split-enzymes for detecting spatial colocalization of protein complexes. Using molecular modeling methods we determined possible mutual positions of two dCas9-proteins at the target locus of genomic DNA, which allow optimal interaction of the domains of the split-enzyme attached to them. The optimal distances between the DNA binding sites of dCas9-proteins in different orientations were determined; the dependence of the system structure on the distance between the binding sites of dCas9-proteins was modeled. The genomes of a number of bacteria and viruses (including SARS-CoV-2) have been analyzed using bioinformatics methods, the possibility of targeting the dCas9-protein pairs to specific genomic loci in optimal positions has been shown. The possibility of using dCas9-proteins from various bacteria differing by PAMsequences was analyzed. Our results indicate the conceptual possibility of creating highly specific biosensors of nucleic acids based on a combination of CRISPR/Cas9 technologies and enzymatic protein split systems.

1. MacKay M.J., Hooker A.C., Afshinnekoo E. et al. The COVID-19 XPRIZE and the need for scalable, fast, and widespread testing: 9 // Nat. Biotechnol. 2020. Vol. 38. N 9. P. 1021–1024.

2. Notomi T. Loop-mediated isothermal amplification of DNA // Nucleic Acids Res. 2000. Vol. 28. N 12: e63.

3. Makarova K.S., Wolf Y.I., Iranzo J. et al. Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants // Nat. Rev. Microbiol. 2020. Vol. 18. N 2. P. 67–83.

4. Kellner M.J., Koob J., Gootenberg J.S., Abudayyeh O.O., Zhang F. SHERLOCK: Nucleic acid detection with CRISPR nucleases // Nat. Protoc. 2019. Vol. 14. N 10. P. 2986–3012.

5. Gootenberg J.S., Abudayyeh O.O., Kellner M.J., Joung J., Collins J.J., Zhang F. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6 // Science. 2018. Vol. 360. N 6387. P. 439–444.

6. Lobato I.M., O’Sullivan C.K. Recombinase polymerase amplification: Basics, applications and recent advances // TrAC Trends Anal. Chem. 2018. Vol. 98. P. 19–35.

7. Li Y., Li S., Wang J., Liu G. CRISPR/Cas systems towards next-generation biosensing // Trends Biotechnol. 2019. Vol. 37. N 7. P. 730–743.

8. Qi L.S., Larson M.H., Gilbert L.A., Doudna J.A., Weissman J.S., Arkin A.P., Lim W.A. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression // Cell. 2013. Vol. 152. N 5. P. 1173–1183.

9. Zhang L., Rube H.T., Bussemaker H.J., Pufall M.A. The effect of sequence mismatches on binding affinity and endonuclease activity are decoupled throughout the Cas9 binding site // BioRxiv. 2017: 176255.

10. Pettersen E.F., Goddard T.D., Huang C.C., Couch G.S., Greenblatt D.M., Meng E.C., Ferrin T.E. UCSF Chimera—A visualization system for exploratory research and analysis // J. Comput. Chem. 2004. Vol. 25. N 13. P. 1605–1612.

11. Huai C., Li G., Yao R., Zhang Y., Cao M., Kong L., Jia C., Yuan H., Chen H., Lu D., Huang Q. Structural insights into DNA cleavage activation of CRISPR-Cas9 system: 1 // Nat. Commun. 2017. Vol. 8. N 1: 1375.

12. Gowers R., Linke M., Barnoud J., Reddy T., Melo M., Seyler S., Domański J., Dotson D., Buchoux S., Kenney I., Beckstein O. MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations // Proceedings of the 15th Python in Science Conference. Austin: SciPy, 2016. P. 98–105.

13. Harris C.R., Millman K.J., van der Walt S.J. et al. Array programming with NumPy: 7825 // Nature. 2020. Vol. 585. N 7825. P. 357–362.

14. Hunter J.D. Matplotlib: A 2D graphics environment // Comput. Sci. Eng. 2007. Vol. 9. N 3. P. 90–95.

15. Pruitt K.D., Tatusova T., Maglott D.R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins // Nucleic Acids Res. 2007. Vol. 35. Database issue. P. D61–D65.

16. Katoh K., Rozewicki J., Yamada K.D. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization // Brief. Bioinform. 2019. Vol. 20. N 4. P. 1160–1166.

17. Wehr M.C., Rossner M.J. Split protein biosensor assays in molecular pharmacological studies // Drug Discov. Today. 2016. Vol. 21. N 3. P. 415–429.

18. Azad T., Tashakor A., Hosseinkhani S. Splitluciferase complementary assay: applications, recent developments, and future perspectives // Anal. Bioanal. Chem. 2014. Vol. 406. N 23. P. 5541–5560.

19. Porter J.R., Stains C.I., Segal D.J., Ghosh I. Split beta-lactamase sensor for the sequence-specific detection of DNA methylation // Anal. Chem. 2007. Vol. 79. N 17. P. 6702–6708.

20. Chen X., Zaro J., Shen W.-C. Fusion protein linkers: Property, design and functionality // Adv. Drug Deliv. Rev. 2013. Vol. 65. N 10. P. 1357–1369.

21. Soranno A., Longhi R., Bellini T., Buscaglia M. Kinetics of contact formation and end-to-end distance distributions of swollen disordered peptides // Biophys. J. 2009. Vol. 96. N 4. P. 1515–1528.

22. Zhao S., Lou J., Cao L., Zheng H., Chong M.K.C., Chen Z., Chan R.W.Y., Zee B.C.Y., Chan P.K.S., Wang M.H. Quantifying the transmission advantage associated with N501Y substitution of SARS-CoV-2 in the United Kingdom: An early data-driven analysis // J. Travel Med. 2021. Vol. 28. N 2: taab011.

23. Wang M., Zhang R., Li J. CRISPR/cas systems redefine nucleic acid detection: Principles and methods // Biosens. Bioelectron. 2020. Vol. 165: 112430.

24. Broughton J.P., Deng X., Yu G. et al. CRISPR-Cas12-based detection of SARS-CoV-2 // Nat. Biotechnol. 2020. Vol. 38. N 7. P. 870–874.

25. Zhou W., Hu L., Ying L., Zhao Z., Chu P.K., Yu X.-F. A CRISPR–Cas9-triggered strand displacement amplification method for ultrasensitive DNA detection: 1 // Nat. Commun. 2018. Vol. 9. N 1: 5012.

26. Wang R., Zhao X., Chen X., Qiu X., Qing G., Zhang H., Zhang L., Hu X., He Z., Zhong D., Wang Y., Luo Y. Rolling circular amplification (RCA)-Assisted CRISPR/Cas9 cleavage (RACE) for highly specific detection of multiple extracellular vesicle MicroRNAs // Anal. Chem. 2020. Vol. 92. N 2. P. 2176–2185.

27. Wang X., Xiong E., Tian T., Cheng M., Lin W., Wang H., Zhang G., Sun J., Zhou X. Clustered regularly interspaced short palindromic repeats/Cas9-mediated lateral flow nucleic acid assay // ACS Nano. 2020. Vol. 14. N 2. P. 2497–2508.

28. Slaymaker I.M., Gao L., Zetsche B., Scott D.A., Yan W.X., Zhang F. Rationally engineered Cas9 nucleases with improved specificity // Science. 2016. Vol. 351. N 6268. P. 84–88.