CRISPR Web-based editing tool

CRISPR-Cas (clustered regularly interspaced short palindromic repeats and CRISPR associated), an immune system in bacteria and archaea that targets the nucleic acids of viruses and plasmids, is currently frequently employed as a genome editing tool due to its ease of use and effectiveness [1–5]. Using its single-guide RNA (sgRNA), the most common endonuclease, type II CRISPR-Cas9, creates DNA double-stranded breaks (DSBs) at a specific spot [6–8]. The double-strand breaks trigger the cell’s own repair systems: error-prone non-homologous end joining (NHEJ) and error-free homology-directed repair (HDR), which result in gene knock-out and knock-in (or gene correction), respectively. HDR occurs less often in mammalian cells than NHEJ [9], making it more challenging to induce gene repairs such as single nucleotide changes. Moreover, Cas9 may commonly generate DSBs at unintended locations containing sequences identical to the sgRNA [10, 11].

BE-Designer and BE-Analyzer, assist researchers in selecting sgRNAs to target specific DNA sequences and evaluating base editing results using next-generation sequencing (NGS) data. BE designer consist of dCas9 [12] or nCas9 [13] coupled to a cytidine deaminase such as APOBEC1 (apolipoprotein B editing complex 1) [14] or AID (activation-induced deaminase) [15]. Later, adenine base editors (ABEs) were developed by using tRNA adenine deaminase (TadA), an enzyme that evolved to permit the direct conversion of A to G in DNA [16]. Due to their capacity to create highly exact DNA substitutions, these base editing tools will be very beneficial for gene correction [17–22]. However, to our knowledge, a user-friendly and publicly accessible web-based tool for their design and analysis has not yet been established.

BE-Designer offers researchers a list of all potential sgRNAs for targeting specific input DNA sequences, as well as helpful information like as their potential off-target locations, for the 319 species for which it is now registered. After introducing CRISPR base editors into a population of cells, scientists conduct targeted deep sequencing to quantify mutation efficiencies and study DNA mutation patterns. BE-Analyzer summarizes and analyzes NGS data in a user’s web browser; due to the benefits of JavaScript, it is not necessary to upload data to a server or install local tools. BE-Designer offers analysis for CRISPR base editors based on SpCas9 from Streptococcus pyogenes, which detects 5′-NGG-3′ protospacer-adjacent motif (PAM) sequences, and SpCas9 variants: SpCas9-VQR (5′-NGAN-3′), SpCas9-EQR (5′-NGAG-3′), SpCas9-VRER (5′-NGCG-3′), xCas9 3.7 (TLIKDIV SpCas9; 5’-NGR-3′ and 5’-NG-3′) [23–25]. BE-Designer further offers analysis for CRISPR base editors based on StCas9 from Streptococcus cus thermophilus (5′-NNAGAAW-3′), CjCas9 from Campylobacter jejuni (5′-NNNVRYAC-3′), SaCas9 from Staphylococcus aureus (5′-NNGRRT-‘3) and its engineered version, SaCas9-KKH (5’-NNNRRT-‘3) [26-28].  BE-Designer now enables the creation of sgRNA in 319 taxa, including vertebrates, insects, plants, and microbes.

Optionally, BE-Analyzer takes control data from CRISPR-untreated cells and shows the results in an extra nucleotide mutation table, allowing users to compare the data from CRISPR-treated and untreated cells with ease. BE-focused analyzer’s deep sequencing with high sensitivity and accuracy is the most effective way of evaluating base editing effects. BE-Analyzer collects and analyzes specific deep-sequencing data to compute base conversion ratios. BE-Analyzer gives a comprehensive list of all query sequences aligned to a particular wild-type (WT) sequence, allowing users to manually validate mutation patterns. BE-Analyzer operates entirely on a client-side web browser, eliminating the need to upload very large NGS datasets (1 GB) to a server, hence lowering a time-intensive step in genome editing analysis. The BE-Analyzer interface was also created using Django as the backend application. BE-basic Analyzer’s algorithm was created in C++ before being trans-compiled to WebAssembly using Emscripten (http://kripken.github.io/emscripten-site/).

References-

  1. Kim H, Kim J-S. A guide to genome engineering with programmable nucleases. Nat Rev Genet. 2014;15:321–34.
  2. Baek K, Kim DH, Jeong J, Sim SJ, Melis A, Kim J-S, et al. DNA-free two-gene knockout in Chlamydomonas reinhardtii via CRISPR-Cas9 ribonucleoproteins. Sci Rep. 2016;6:30620.
  3. Koonin EV, Makarova KS, Zhang F. Diversity, classification and evolution of CRISPR-Cas systems. Curr Opin Microbiol. 2017;37:67–78.
  4. Doudna JA, Charpentier E. The new frontier of genome engineering with CRISPR-Cas9. Science. 2014;346:–1258096.
  5. Sander JD, Joung JK. CRISPR-Cas systems for editing, regulating and targeting genomes. Nat Biotechnol. 2014;32:347–55.
  6. Nishimasu H, Ran FA, Hsu PD, Konermann S, Shehata SI, Dohmae N, et al. Crystal structure of Cas9 in complex with guide RNA and target DNA. Cell. 2014;156:935–49.
  7. Cong L, Ran FA, Cox D, Lin S, Barretto R, Habib N, et al. Multiplex genome engineering using CRISPR/Cas systems. Science. 2013;339:819–23.
  8. Jinek M, Chylinski K, Fonfara I, Hauer M, Doudna JA, Charpentier E. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science. 2012;337:816–21.
  9. Mao Z, Bozzella M, Seluanov A, Gorbunova V. DNA repair by nonhomologous end joining and homologous recombination during cell cycle in human cells. Cell Cycle. 2008;7:2902–6.
  10. Cho SW, Kim S, Kim Y, Kweon J, Kim HS, Bae S, et al. Analysis of off-target effects of CRISPR/Cas-derived RNA-guided endonucleases and nickases. Genome Res. 2014;24:132–41.
  11. Fu Y, Foden JA, Khayter C, Maeder ML, Reyon D, Joung JK, et al. High-frequency off-target mutagenesis induced by CRISPR-Cas nucleases in human cells. Nat Biotechnol. 2013;31:822–6.
  12. Bikard D, Jiang W, Samai P, Hochschild A, Zhang F, Marraffini LA. Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system. Nucleic Acids Res. 2013;41:7429–37.
  13. Ran FA, Hsu PD, Lin C-Y, Gootenberg JS, Konermann S, Trevino AE, et al. Double nicking by RNA-guided CRISPR Cas9 for enhanced genome editing specificity. Cell. 2013;154:1380–9.
  14. Komor AC, Kim YB, Packer MS, Zuris JA, Liu DR. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Natur. 2016;533:420–4.
  15. Nishida K, Arazoe T, Yachie N, Banno S, Kakimoto M, Tabata M, et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science. 2016;353:aaf8729.
  16. Gaudelli NM, Komor AC, Rees HA, Packer MS, Badran AH, Bryson DI, et al. Programmable base editing of a•T to G•C in genomic DNA without DNA cleavage. Nature. 2017;551:464–71.
  17. Kim K, Ryu S-M, Kim S-T, Baek G, Kim D, Lim K, et al. Highly efficient RNAguided base editing in mouse embryos. Nat Biotechnol. 2017;35:435–7.
  18. Zong Y, Wang Y, Li C, Zhang R, Chen K, Ran Y, et al. Precise base editing in rice, wheat and maize with a Cas9-cytidine deaminase fusion. Nat Biotechnol. 2017;35:438–40
  19. Liang P, Ding C, Sun H, Xie X, Xu Y, Zhang X, et al. Correction of βthalassemia mutant by base editor in human embryos. Protein Cell. 2017;8: 811–22.
  20. Liang P, Sun H, Sun Y, Zhang X, Xie X, Zhang J, et al. Effective gene editing by high-fidelity base editor 2 in mouse zygotes. Protein Cell. 2017;8:601–11.
  21. Kuscu C, Parlak M, Tufan T, Yang J, Szlachta K, Wei X, et al. CRISPR-STOP: gene silencing through base-editing-induced nonsense mutations. Nat Methods. 2017;14:710–2.
  22. Billon P, Bryant EE, Joseph SA, Nambiar TS, Hayward SB, Rothstein R, et al. CRISPR-Mediated Base Editing Enables Efficient Disruption of Eukaryotic Genes through Induction of STOP Codons. Mol Cell. 2017;67:1068–1079.e4.
  23. Kleinstiver BP, Prew MS, Tsai SQ, Topkar VV, Nguyen NT, Zheng Z, et al. Engineered CRISPR-Cas9 nucleases with altered PAM specificities. Nature. 2015;523:481–5.
  24. Nishimasu H, Shi X, Ishiguro S, Gao L, Hirano S, Okazaki S, et al. Engineered CRISPR-Cas9 nuclease with expanded targeting space. Science. 2018;361: 1259–62.
  25. Hu JH, Miller SM, Geurts MH, Tang W, Chen L, Sun N, et al. Evolved Cas9 variants with broad PAM compatibility and high DNA specificity. Nature. 2018;556:57–63.
  26. Kleinstiver BP, Prew MS, Tsai SQ, Nguyen NT, Topkar VV, Zheng Z, et al. Broadening the targeting range of Staphylococcus aureus CRISPR-Cas9 by modifying PAM recognition. Nat Biotechnol. 2015;33:1293–8.
  27. Kim E, Koo T, Park SW, Kim D, Kim K, Cho H-Y, et al. In vivo genome editing with a small Cas9 orthologue derived from campylobacter jejuni. Nat Commun. 2017;8:14500.
  28. Müller M, Lee CM, Gasiunas G, Davis TH, Cradick TJ, Siksnys V, et al. Streptococcus thermophilus CRISPR-Cas9 systems enable specific editing of the human genome. Mol Ther. 2016;24:636–44.
WhatsApp chat