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Cas9 Protein Triggers Differential Expression of Inherent Genes Especially NGFR Expression in 293T Cells

  • Liqun Chen
  • Huilian Zhang
  • Linteng Zhang
  • Wenbo Li
  • Fengtian Fan
  • Xiaoyun Wu
  • Xueling Wu
  • Jun LinEmail author
Original Article
  • 6 Downloads

Abstract

Introduction

CRISPR/CAS9 systems, which can be utilized in vitro biological experiments, have recently captured much attention for their important roles and benefits. However, full realization of the potential of CRISPR/CAS9 approaches requires addressing many challenges and side effects. The expression of genes and potential side effects of CRISPR/CAS9 in human cells remains to be elucidated. The aim of our study was to explore the effect of CRISPR/CAS9 on gene expression in 293T cells.

Methods

A Cas9-expressing PX458 plasmid and Cas9-deactivated PX458-T2A plasmid were used to study the role of CRISPR/CAS9 on regulating gene expression in 293T cells. Gene expression in 293T cells after transfection of the PX458 plasmid or PX458-T2A plasmid was detected by RNA sequencing and correlative statistical analysis. Differential gene expression in both PX458 transfected 293T cells and PX458-T2A transfected 293T cells compared with normal 293T cells was detected using quantitative reverse transcription polymerase chain reaction (RT qPCR). The mRNA and protein levels were measured using reverse transcription PCR and Western blot. Co-IP assay combined with shotgun LC-MS/MS were used to investigate the differences of NGFR-interaction proteins between PX458 transfected 293T cells and PX458-T2A transfected 293T cells.

Results

In this study, we observed that PX458 plasmid transfection and Cas9 expression can affect the expression of different genes, including FOSB (FBJ murine osteosarcoma viral oncogene homolog B), IL-11 (Interleukin-11), MMP1 (matrix metalloproteinase), CYP2D6 (CytochromeP4502D6), and NGFR (matrix metalloproteinase 1). Downregulation of NGFR after PX458 transfection was confirmed by RT qPCR and western blot analysis. NGFR expression was significantly lower in PX458 transfected 293T cells than in normal 293T cells and PX458-T2A transfected 293T cells. The co-IP dilutions analyzed by shotgun LC-MS/MS showed a total of 183 proteins interact with NGFR in PX458 transfected 293T cells while 221 proteins interact with NGFR were identified in PX458-T2A transfected 293T cells using the MASCOT engine.

Conclusions

Cas9 expression by transfection of the PX458 plasmid was negatively correlated with the NGFR mRNA level and NGFR protein expression in 293T cells, while PX458-T2A, in which Cas9 is deactivated, did not affect NGFR expression. The decrease in NGFR expression also affects the amount of proteins that interact with NGFR. These results suggest that the effect of Cas9 on NGFR expression and the expression of other genes should be noticed when developing cell-based studies and therapies utilizing CRISPR/CAS9 systems.

Keywords

CRISPR/CAS9 PX458 PX458-T2A RNA sequencing Gene expression NGFR 

Abbreviations

T2A

2A peptide derived from insect Thosea asigna virus

GAPDH

Glyceraldehyde-3-phosphate dehydrogenase

HEK293T

Human embryonic kidney cell line

DMEM

Dulbecco’s modified Eagle’s medium

NGFR

Nerve growth factor receptor

Notes

Acknowledgments

We are grateful to the WuXi NextCODE company for RNA sequencing. We thank LetPub (https://www.letpub.com/) for its linguistic assistance during the preparation of this manuscript. We acknowledge supports from the National Natural Science Foundation of China (Grant No. 31500616) and the Natural Science Foundation of Fujian Province (Grant No. 2017 J01445).

Research Involved in Human and Animal Rights

No human studies were carried out by the authors for this article. No animal studies were carried out by the authors for this article.

Competing interests

All authors, including Liqun Chen, Huilian Zhang Linteng Zhang, Wenbo Li, Fengtian Fan, Xiaoyun Wu, Xueling Wu, Jun Lin, declare that they have no competing interests.

References

  1. 1.
    Baeza-Raja, B., P. Li, N. Le Moan, et al. p75 neurotrophin receptor regulates glucose homeostasis and insulin sensitivity. Proc. Natl. Acad. Sci. USA 109(15):5838–5843, 2012.CrossRefGoogle Scholar
  2. 2.
    Bolger, A. M., M. Lohse, and B. Usadel. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15):2114–2120, 2014.CrossRefGoogle Scholar
  3. 3.
    Cassiman, D., C. Denef, V. J. Desmet, and T. Roskams. Human and rat hepatic stellate cells express neurotrophins and neurotrophin receptors. Hepatology 33(1):148–158, 2001.CrossRefGoogle Scholar
  4. 4.
    Chandrasegaran, S., and D. Carroll. Origins of programmable nucleases for genome engineering. J. Mol. Biol. 428(5 Pt B):963–989, 2016.CrossRefGoogle Scholar
  5. 5.
    Crudele, J. M., and J. S. Chamberlain. Cas9 immunity creates challenges for CRISPR gene editing therapies. Nat. Commun. 9(1):3497–3497, 2018.CrossRefGoogle Scholar
  6. 6.
    Deponti, D., R. Buono, G. Catanzaro, et al. The low-affinity receptor for neurotrophins p75NTR plays a key role for satellite cell function in muscle repair acting via RhoA. Mol. Biol. Cell 20(16):3620–3627, 2009.CrossRefGoogle Scholar
  7. 7.
    Dobin, A., C. A. Davis, F. Schlesinger, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21, 2013.CrossRefGoogle Scholar
  8. 8.
    Findlay, G. M., E. A. Boyle, R. J. Hause, J. C. Klein, and J. Shendure. Saturation editing of genomic regions by multiplex homology-directed repair. Nature 513(7516):120–123, 2014.CrossRefGoogle Scholar
  9. 9.
    Fu, Y. F., J. D. Sander, D. Reyon, V. M. Cascio, and J. K. Joung. Improving CRISPR-Cas nuclease specificity using truncated guide RNAs. Nat. Biotechnol. 32(3):279–284, 2014.CrossRefGoogle Scholar
  10. 10.
    Gilbert, L. A., M. A. Horlbeck, B. Adamson, et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159(3):647–661, 2014.CrossRefGoogle Scholar
  11. 11.
    Grunewald, J., R. Zhou, S. P. Garcia, et al. Transcriptome-wide off-target RNA editing induced by CRISPR-guided DNA base editors. Nature 569:433, 2019.CrossRefGoogle Scholar
  12. 12.
    Horvath, P., and R. Barrangou. CRISPR/Cas, the immune system of bacteria and archaea. Science 327(5962):167–170, 2010.CrossRefGoogle Scholar
  13. 13.
    Hsu, P. D., D. A. Scott, J. A. Weinstein, et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31(9):827–832, 2013.CrossRefGoogle Scholar
  14. 14.
    Ishino, Y., H. Shinagawa, K. Makino, M. Amemura, and A. Nakata. Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. J. Bacteriol. 169(12):5429–5433, 1987.CrossRefGoogle Scholar
  15. 15.
    Jansen, R., J. D. A. van Embden, W. Gaastra, and L. M. Schouls. Identification of genes that are associated with DNA repeats in prokaryotes. Mol. Microbiol. 43(6):1565–1575, 2002.CrossRefGoogle Scholar
  16. 16.
    Jiang, W. Y., D. Bikard, D. Cox, F. Zhang, and L. A. Marraffini. RNA-guided editing of bacterial genomes using CRISPR-Cas systems. Nat. Biotechnol. 31(3):233–239, 2013.CrossRefGoogle Scholar
  17. 17.
    Jung, T. Y., Y. An, K. H. Park, M. H. Lee, B. H. Oh, and E. Woo. Crystal structure of the Csm1 subunit of the Csm complex and its single-stranded DNA-specific nuclease activity. Structure 23(4):782–790, 2015.CrossRefGoogle Scholar
  18. 18.
    Konermann, S., M. D. Brigham, A. E. Trevino, et al. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 517(7536):583–588, 2015.CrossRefGoogle Scholar
  19. 19.
    Li, B., and C. N. Dewey. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12:323, 2011.CrossRefGoogle Scholar
  20. 20.
    Liepinsh, E., L. L. Ilag, G. Otting, and C. F. Ibanez. NMR structure of the death domain of the p75 neurotrophin receptor. EMBO J. 16(16):4999–5005, 1997.CrossRefGoogle Scholar
  21. 21.
    Liu, J. J., N. Orlova, B. L. Oakes, et al. CasX enzymes comprise a distinct family of RNA-guided genome editors. Nature 566(7743):218, 2019.CrossRefGoogle Scholar
  22. 22.
    Liu, B., A. Saber, and H. J. Haisma. CRISPR/CAS9: a powerful tool for identification of new targets for cancer treatment. Drug Discov. Today 24:955–970, 2019.CrossRefGoogle Scholar
  23. 23.
    Makarova, K. S., L. Aravind, Y. I. Wolf, and E. V. Koonin. Unification of Cas protein families and a simple scenario for the origin and evolution of CRISPR-Cas systems. Biol. Direct. 6:38, 2011.CrossRefGoogle Scholar
  24. 24.
    Osakabe, Y., and K. Osakabe. Genome editing with engineered nucleases in plants. Plant Cell Physiol. 56(3):389–400, 2014.CrossRefGoogle Scholar
  25. 25.
    Passino, M. A., R. A. Adams, S. L. Sikorski, and K. Akassoglou. Regulation of hepatic stellate cell differentiation by the neurotrophin receptor p75NTR. Science 315(5820):1853–1856, 2007.CrossRefGoogle Scholar
  26. 26.
    Peeraully, M. R., J. R. Jenkins, and P. Trayhurn. NGF gene expression and secretion in white adipose tissue: regulation in 3T3-L1 adipocytes by hormones and inflammatory cytokines. Am J Physiol. Endocrinol. Metab. 287(2):E331–E339, 2004.CrossRefGoogle Scholar
  27. 27.
    Raitskin, O., and N. J. Patron. Multi-gene engineering in plants with RNA-guided Cas9 nuclease. Curr. Opin. Biotechnol. 37:69–75, 2016.CrossRefGoogle Scholar
  28. 28.
    Ran, F. A., P. D. Hsu, J. Wright, V. Agarwala, D. A. Scott, and F. Zhang. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8(11):2281–2308, 2013.CrossRefGoogle Scholar
  29. 29.
    Robinson, M. D., D. J. McCarthy, and G. K. Smyth. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140, 2010.CrossRefGoogle Scholar
  30. 30.
    Rodriguez-Rodriguez, D. R., R. Ramirez-Solis, M. A. Garza-Elizondo, M. L. Garza-Rodriguez, and H. A. Barrera-Saldana. Genome editing: a perspective on the application of CRISPR/CAS9 to study human diseases (Review). Int. J. Mol. Med. 43(4):1559–1574, Apr 2019.Google Scholar
  31. 31.
    Shalem, O., N. E. Sanjana, E. Hartenian, et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343(6166):84–87, 2014.CrossRefGoogle Scholar
  32. 32.
    Tian, X., T. Gu, S. Patel, A. M. Bode, M. H. Lee, and Z. Dong. CRISPR/CAS9—an evolving biological tool kit for cancer biology and oncology. NPJ Precis. Oncol. 3:8, 2019.CrossRefGoogle Scholar
  33. 33.
    Vora, S., M. Tuttle, J. Cheng, and G. Church. Next stop for the CRISPR revolution: RNA-guided epigenetic regulators. FEBS J. 283(17):3181–3193, 2016.CrossRefGoogle Scholar
  34. 34.
    Wang, D., J. Huang, X. Wang, et al. The eradication of breast cancer cells and stem cells by 8-hydroxyquinoline-loaded hyaluronan modified mesoporous silica nanoparticle-supported lipid bilayers containing docetaxel. Biomaterials 34(31):7662–7673, 2013.CrossRefGoogle Scholar
  35. 35.
    Wang, T., J. J. Wei, D. M. Sabatini, and E. S. Lander. Genetic screens in human cells using the CRISPR-Cas9 system. Science 343(6166):80–84, 2014.CrossRefGoogle Scholar
  36. 36.
    Wang, H., H. Yang, C. S. Shivalila, et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153(4):910–918, 2013.CrossRefGoogle Scholar
  37. 37.
    Wyvekens, N., V. V. Topkar, C. Khayter, J. K. Joung, and S. Q. Tsai. Dimeric CRISPR RNA-guided FokI-dCas9 nucleases directed by truncated gRNAs for highly specific genome editing. Hum. Gene Ther. 26(7):425–431, 2015.CrossRefGoogle Scholar
  38. 38.
    Xiao, Q., D. Guo, and S. Chen. Application of CRISPR/CAS9-based gene editing in HIV-1/AIDS therapy. Front. Cell. Infect. Microbiol. 9:69, 2019.CrossRefGoogle Scholar
  39. 39.
    Yang, H., H. Wang, C. S. Shivalila, A. W. Cheng, L. Shi, and R. Jaenisch. One-step generation of mice carrying reporter and conditional alleles by CRISPR/Cas-mediated genome engineering. Cell 154(6):1370–1379, 2013.CrossRefGoogle Scholar
  40. 40.
    Yao, S., Z. He, and C. Chen. CRISPR/CAS9-mediated genome editing of epigenetic factors for cancer therapy. Hum. Gene Ther. 26(7):463–471, 2015.CrossRefGoogle Scholar
  41. 41.
    Zhang, D. D., Z. X. Li, and J. F. Li. Targeted gene manipulation in plants using the CRISPR/Cas technology. J. Genet. Genom. 43(5):251–262, 2016.CrossRefGoogle Scholar
  42. 42.
    Zhang, Y., X. Ma, X. Xie, and Y. G. Liu. CRISPR/CAS9-based genome editing in plants. Prog. Mol. Biol. Transl. Sci. 149:133–150, 2017.CrossRefGoogle Scholar
  43. 43.
    Zhou, Y., S. Zhu, C. Cai, et al. High-throughput screening of a CRISPR/CAS9 library for functional genomics in human cells. Nature 509(7501):487–491, 2014.CrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 2019

Authors and Affiliations

  1. 1.College of Biological Science and EngineeringFuzhou UniversityFuzhouChina
  2. 2.Institute of Apply GenomicsFuzhou UniversityFuzhouChina
  3. 3.Fujian Key Laboratory of Marine Enzyme EngineeringFuzhou UniversityFuzhouChina

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