Abstract

Türkçe Diabetes mellitus, yetersiz insülin üretimi veya yanıtı nedeniyle kalıcı olarak yüksek kan glukoz seviyeleriyle karakterize edilen yaygın bir metabolik bozukluktur. Belirtilerin yönetimi konusunda önemli ilerlemeler kaydedilmiş olsa da kesin bir tedavi halen mevcut değildir. Bu çalışma, CRISPR/dCas9 gen aktivasyon sistemini kullanarak insülin üreten β-benzeri hücrelerin β hücresi olmayan kaynaklardan elde edilmesine yönelik yeni bir stratejiyi araştırmaktadır. Pankreas gelişiminde kilit rol oynayan iki transkripsiyon faktörü olan PDX1 ve NGN3'ün aktivasyonu yoluyla β hücre farklılaşmasını artırmaya odaklandık. Bu süreci optimize etmek için üç farklı aktivatör bölgesini (VP64, VPR ve p300) karşılaştırdık ve VPR'nin en etkili aktivatör olduğunu belirledik. Özellikle VPR aktivatörü, dört gRNA ile birlikte kullanıldığında PDX1 ekspresyonunda 19 kat, NGN3 ekspresyonunda ise 256 kat artış sağladı. Bu üstünlüğün, VPR'nin VP64 ve p300'e kıyasla daha güçlü transkripsiyon aktivasyonu sağlamasından kaynaklandığını düşünüyoruz. Gen ve protein ekspresyonu sırasıyla RT-qPCR ve immün boyama teknikleriyle doğrulandı. Bulgularımız, CRISPR/dCas9 aracılı gen aktivasyonunun β hücre farklılaşmasını etkili bir şekilde indükleyebileceğini ve β hücre kaybının büyük bir sorun olduğu tip 1 diyabet tedavisi için umut vadeden bir yaklaşım sunduğunu göstermektedir. Gelecekteki çalışmalar, bu β-benzeri hücrelerin uzun vadeli fonksiyonelliğini ve stabilitesini preklinik modellerde inceleyerek terapötik potansiyellerini daha kapsamlı bir şekilde değerlendirmelidir. Transkripsiyon faktörü aktivasyonunu optimize eden bu çalışma, β hücre rejenerasyonu hakkında yeni içgörüler sunarak gen temelli diyabet tedavileri alanına önemli bir katkı sağlamaktadır.

Project Number

FYL- 2020-4878

Comparison of dCas9-activator complexes for the activation of PDX1 and NGN3 pancreatic genes using the CRISPR system

Abstract

Diabetes mellitus is a prevalent metabolic disorder characterized by persistently high blood glucose levels due to insufficient insulin production or response. Although significant progress has been made in symptom management, a definitive cure remains unavailable. This study presents a novel approach to generate insulin-producing β cells from non-β cell sources using the CRISPR/dCas9 gene activation system. We focused on enhancing β-cell differentiation by activating PDX1 and NGN3, two key transcription factors in pancreatic development. To optimize this process, we compared three activator domains (VP64, VPR, and p300) and found VPR to be the most effective. Specifically, the VPR activator led to a 19-fold increase in PDX1 expression and a 256-fold increase in NGN3 expression when combined with four gRNAs. This superiority is likely due to its stronger transcriptional activation capability, which enhances gene expression more efficiently than VP64 and p300. Gene and protein expression were confirmed through RT-qPCR and immunostaining, respectively. Our findings demonstrate that CRISPR/dCas9-mediated gene activation can effectively induce β-cell differentiation, offering a promising approach for type 1 diabetes therapy, where β-cell loss is a major challenge. Future studies should explore the long-term functionality and stability of these β-like cells in preclinical models to further assess their therapeutic potential. By optimizing transcription factor activation, our study provides new insights into β-cell regeneration, advancing the field of gene-based diabetes treatments.

Keywords

• CRISPR/dCas9Activation
• Insulin-Producing β-like Cells
• PDX1 and NGN3 Gene Regulation
• β-cell Differentiation and Regeneration
• Diabetes Gene Therapy

Supporting Institution

Akdeniz University, the Scientific Research Projects Coordination Unit

Project Number

FYL- 2020-4878

Ethical Statement

Since the article does not contain any studies with human or animal subject, its approval to the ethics committee was not required.

References

1. 1. Akinci, E., Banga, A., Greder, L.V., Dutton, J.R. & Slack, J.M. 2012. Reprogramming of pancreatic exocrine cells towards a beta (β) cell character using Pdx1, Ngn3 and MafA. Biochemistry Journal, 442(3): 539-550. https://doi.org/10.1042/bj20111678
2. 2. Balboa, D., Weltner, J., Eurola, S., Trokovic, R., Wartiovaara, K. & Otonkoski, T. 2015. Conditionally Stabilized dCas9 Activator for Controlling Gene Expression in Human Cell Reprogramming and Differentiation. Stem Cell Reports, 5(3): 448-459. https://doi.org/10.1016/j.stemcr.2015.08.001
3. 3. Beerli, R.R., Dreier, B. & Barbas, C.F., 3rd. 2000. Positive and negative regulation of endogenous genes by designed transcription factors. Proceedings of the National Academy of Sciences of the United States of America, 97(4): 1495-1500. https://doi.org/10.1073/pnas.040552697
4. 4. Casas-Mollano, J.A., Zinselmeier, M.H., Erickson, S.E. & Smanski, M.J. 2020. CRISPR-Cas Activators for Engineering Gene Expression in Higher Eukaryotes. The CRISPR Journal 3(5): 350-364. https://doi.org/10.1089/crispr.2020.0064
5. 5. Cavelti-Weder, C., Zumsteg, A., Li, W. & Zhou, Q. 2017. Reprogramming of Pancreatic Acinar Cells to Functional Beta Cells by In Vivo Transduction of a Polycistronic Construct Containing Pdx1, Ngn3, MafA in Mice. Current Protocols in Stem Cell Biology, 40: 4a.10.11-14a.10.12. https://doi.org/10.1002/cpsc.21
6. 6. Chavez, A., Scheiman, J., Vora, S., Pruitt, B.W., Tuttle, M., P R Iyer, E., Lin, S., Kiani, S., Guzman, C.D., Wiegand, D.J., Ter-Ovanesyan, D., Braff, J.L., Davidsohn, N., Housden, B.E., Perrimon, N., Weiss, R., Aach, J., Collins, J.J. & Church, G.M. 2015. Highly efficient Cas9-mediated transcriptional programming. Nature Methods, 12(4): 326-328. https://doi.org/10.1038/nmeth.3312
7. 7. Chen, M. & Qi, L.S. 2017. Repurposing CRISPR System for Transcriptional Activation. Advances in experimental medicine and biology, 983, 147-157. https://doi.org/10.1007/978-981-10-4310-9_10
8. 8. Cheng, A.W., Wang, H., Yang, H., Shi, L., Katz, Y., Theunissen, T.W., Rangarajan, S., Shivalila, C.S., Dadon, D.B. & Jaenisch, R. 2013. Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system. Cell Research, 23(10): 1163-1171. https://doi.org/10.1038/cr.2013.122

9. 9. CRISPR-ERA. 2025. gRNA design tool for CRISPR-mediated gene editing. http://CRISPR-ERA.stanford.edu (Date accessed: 23.03.2025).
10. 10. Dadheech, N. & James Shapiro, A.M. 2019. Human Induced Pluripotent Stem Cells in the Curative Treatment of Diabetes and Potential Impediments Ahead, pp. 25-35. In K. Turksen (Ed.), Cell Biology and Translational Medicine, Volume 5: Stem Cells: Translational Science to Therapy, Springer International Publishing, Cham.
11. 11. Database, E.P. 2025. Eukaryotic Promoter Database. http://epd.vital-it.ch (Date accessed: 23.03.2025).
12. 12. Dominguez, A., Chavez, M.G., Urke, A., Gao, Y., Wang, L. & Qi, L.S. 2022. CRISPR-Mediated Synergistic Epigenetic and Transcriptional Control. The CRISPR Journal, 5(2): 264-275. https://doi.org/10.1089/crispr.2021.0099
13. 13. Dreos, R., Ambrosini, G., Groux, R., Cavin Périer, R. & Bucher, P. 2017. The eukaryotic promoter database in its 30th year: focus on non-vertebrate organisms. Nucleic Acids Research, 45(D1): D51-d55. https://doi.org/10.1093/nar/gkw1069
14. 14. Elhanani, O., Salame, T.M., Sobel, J., Leshkowitz, D., Povodovski, L., Vaknin, I., Kolodkin-Gal, D. & Walker, M.D. 2020. REST Inhibits Direct Reprogramming of Pancreatic Exocrine to Endocrine Cells by Preventing PDX1-Mediated Activation of Endocrine Genes. Cell Reports, 31(5): 107591. https://doi.org/10.1016/j.celrep.2020.107591
15. 15. Gilbert, L.A., Larson, M.H., Morsut, L., Liu, Z., Brar, G.A., Torres, S.E., Stern-Ginossar, N., Brandman, O., Whitehead, E.H., Doudna, J.A., Lim, W.A., Weissman, J.S. & Qi, L.S. 2013. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell, 154(2): 442-451. https://doi.org/10.1016/j.cell.2013.06.044
16. 16. Giménez, C.A., Ielpi, M., Mutto, A., Grosembacher, L., Argibay, P. & Pereyra-Bonnet, F. 2016. CRISPR-on system for the activation of the endogenous human INS gene. Gene Therapy, 23(6): 543-547. https://doi.org/10.1038/gt.2016.28
17. 17. Graf, R., Li, X., Chu, V.T. & Rajewsky, K. 2019. sgRNA Sequence Motifs Blocking Efficient CRISPR/Cas9-Mediated Gene Editing. Cell Reports, 26(5): 1098-1103. https://doi.org/10.1016/j.celrep.2019.01.024
18. 18. Guo, P., Zhang, T., Lu, A., Shiota, C., Huard, M., Whitney, K.E. & Huard, J. 2023. Specific reprogramming of alpha cells to insulin-producing cells by short glucagon promoter-driven Pdx1 and MafA. Molecular Therapy Methods & Clinical Development, 28: 355-365. https://doi.org/10.1016/j.omtm.2023.02.003
19. 19. Hilton, I.B., D'Ippolito, A.M., Vockley, C.M., Thakore, P.I., Crawford, G.E., Reddy, T.E. & Gersbach, C.A. 2015. Epigenome editing by a CRISPR-Cas9-based acetyltransferase activates genes from promoters and enhancers. Nature Biotechnology, 33(5): 510-517. https://doi.org/10.1038/nbt.3199
20. 20. Hsu, M.N., Chang, Y.H., Truong, V.A., Lai, P.L., Nguyen, T.K.N. & Hu, Y.C. 2019. CRISPR technologies for stem cell engineering and regenerative medicine. Biotechnology Advances, 37(8): 107447. https://doi.org/10.1016/j.biotechadv.2019.107447
21. 21. Konermann, S., Brigham, M.D., Trevino, A.E., Joung, J., Abudayyeh, O.O., Barcena, C., Hsu, P.D., Habib, N., Gootenberg, J.S., Nishimasu, H., Nureki, O. & Zhang, F. 2015. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature, 517(7536): 583-588. https://doi.org/10.1038/nature14136
22. 22. Kunii, A., Hara, Y., Takenaga, M., Hattori, N., Fukazawa, T., Ushijima, T., Yamamoto, T. & Sakuma, T. 2018. Three-Component Repurposed Technology for Enhanced Expression: Highly Accumulable Transcriptional Activators via Branched Tag Arrays. The CRISPR Journal 1(5): 337-347. https://doi.org/10.1089/crispr.2018.0009
23. 23. Lee, M.-H., Thomas, J.L., Lin, C.-Y., Li, Y.-C.E. & Lin, H.-Y. 2023. Nanoparticle-mediated CRISPR/dCas9a activation of multiple transcription factors to engineer insulin-producing cells. Journal of Materials Chemistry B, 11(9): 1866-1870. https://doi.org/10.1039/D2TB02431D
24. 24. Maeder, M.L., Linder, S.J., Cascio, V.M., Fu, Y., Ho, Q.H. & Joung, J.K. 2013. CRISPR RNA–guided activation of endogenous human genes. Nature Methods, 10(10): 977-979. https://doi.org/10.1038/nmeth.2598
25. 25. Maxwell, K.G., Augsornworawat, P., Velazco-Cruz, L., Kim, M.H., Asada, R., Hogrebe, N.J., Morikawa, S., Urano, F. & Millman, J.R. 2020. Gene-edited human stem cell–derived β cells from a patient with monogenic diabetes reverse preexisting diabetes in mice. Science Translational Medicine, 12(540): eaax9106. https://doi.org/doi:10.1126/scitranslmed.aax9106
26. 26. Nuñez, J.K., Chen, J., Pommier, G.C., Cogan, J.Z., Replogle, J.M., Adriaens, C., Ramadoss, G.N., Shi, Q., Hung, K.L., Samelson, A.J., Pogson, A.N., Kim, J.Y.S., Chung, A., Leonetti, M.D., Chang, H.Y., Kampmann, M., Bernstein, B.E., Hovestadt, V., Gilbert, L.A. & Weissman, J.S. 2021. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell, 184(9): 2503-2519.e2517. https://doi.org/10.1016/j.cell.2021.03.025
27. 27. Perez-Pinera, P., Kocak, D.D., Vockley, C.M., Adler, A.F., Kabadi, A.M., Polstein, L.R., Thakore, P.I., Glass, K.A., Ousterout, D.G., Leong, K.W., Guilak, F., Crawford, G.E., Reddy, T.E. & Gersbach, C.A. 2013. RNA-guided gene activation by CRISPR-Cas9–based transcription factors. Nature Methods, 10(10): 973-976. https://doi.org/10.1038/nmeth.2600
28. 28. Pollock, S.D., Galicia-Silva, I.M., Liu, M., Gruskin, Z.L. & Alvarez-Dominguez, J.R. 2023. Scalable generation of 3D pancreatic islet organoids from human pluripotent stem cells in suspension bioreactors. STAR Protocols, 4(4): 102580. https://doi.org/10.1016/j.xpro.2023.102580
29. 29. Qi, L.S., Larson, M.H., Gilbert, L.A., Doudna, J.A., Weissman, J.S., Arkin, A.P. & Lim, W.A. 2013. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell, 152(5): 1173-1183. https://doi.org/10.1016/j.cell.2013.02.022
30. 30. Razavi, Z., Soltani, M., Souri, M. & van Wijnen, A.J. 2024. CRISPR innovations in tissue engineering and gene editing. Life Sciences, 358: 123120. https://doi.org/10.1016/j.lfs.2024.123120
31. 31. Richter, M.F., Zhao, K.T., Eton, E., Lapinaite, A., Newby, G.A., Thuronyi, B.W., Wilson, C., Koblan, L.W., Zeng, J., Bauer, D.E., Doudna, J.A. & Liu, D.R. 2020. Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity. Nature Biotechnology, 38(7): 883-891. https://doi.org/10.1038/s41587-020-0453-z
32. 32. Riedmayr, L.M., Hinrichsmeyer, K.S., Karguth, N., Böhm, S., Splith, V., Michalakis, S. & Becirovic, E. 2022. dCas9-VPR-mediated transcriptional activation of functionally equivalent genes for gene therapy. Nature Protocols, 17(3): 781-818. https://doi.org/10.1038/s41596-021-00666-3
33. 33. Seo, J.H., Shin, J.H., Lee, J., Kim, D., Hwang, H.-Y., Nam, B.-G., Lee, J., Kim, H.H. & Cho, S.-R. 2023. DNA double-strand break-free CRISPR interference delays Huntington’s disease progression in mice. Communications Biology, 6(1): 466. https://doi.org/10.1038/s42003-023-04829-8
34. 34. Soria, B. 2001. In-vitro differentiation of pancreatic β-cells. Differentiation, 68(4-5): 205-219. https://doi.org/10.1046/j.1432-0436.2001.680408.x
35. 35. Wang, D., Zhang, C., Wang, B., Li, B., Wang, Q., Liu, D., Wang, H., Zhou, Y., Shi, L., Lan, F. & Wang, Y. 2019. Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning. Nature Communications, 10(1): 4284. https://doi.org/10.1038/s41467-019-12281-8