Inovasi dan Praktik Terbaik dalam Model Tikus Hasil Rekayasa Genetik untuk Penelitian Praklinis dan Translasional

Raymond R. Tjandrawinata

doi:10.56951/26jxqx92

Inovasi dan Praktik Terbaik dalam Model Tikus Hasil Rekayasa Genetik untuk Penelitian Praklinis dan Translasional

Penulis

Raymond R. Tjandrawinata Center for Pharmaceutical and Nutraceutical Research and Policy, Universitas Katolik Indonesia Atma Jaya, Jakarta, Indonesia dan Dexa Group, Tangerang Selatan, Indonesia

DOI:

https://doi.org/10.56951/26jxqx92

Kata Kunci:

model tikus hasil rekayasa genetik, GEMs, CRISPR-Cas9, base editing, multi-omik, farmakokinetik, farmakodinamik, etika penelitian hewan, translasi klinis, kecerdasan buatan

Abstrak

Model tikus hasil rekayasa genetik (genetically engineered mouse models/GEMMs) telah mengalami evolusi signifikan
sejak pengembangan pertama kali pada akhir 1980-an. Dalam dekade terakhir, percepatan teknologi genome editing
seperti clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9, base editing, dan prime editing telah menghasilkan gelombang baru inovasi dalam desain dan aplikasi GEMMs. Artikel ini membahas perkembangan historis GEMMs, kemajuan teknis mutakhir di luar CRISPR, aplikasi lintas spektrum penyakit, termasuk autoimun dan kardiovaskular, integrasi multiomik, serta peran GEMMs dalam studi farmakokinetika dan farmakodinamika. Selain itu, dibahas pula aspek manajemen koloni, etika penelitian hewan, regulasi internasional, konvergensi dengan kecerdasan buatan, serta studi kasus keberhasilan translasi klinis berbasis GEMMs. Dengan mengintegrasikan literatur terbaru dari berbagai database internasional, artikel ini memberikan panduan strategis bagi peneliti dalam mengoptimalkan potensi GEMMs untuk meningkatkan akurasi dan relevansi translasional dalam pengembangan terapi inovatif.

Unduhan

Baca Selengkapnya

Referensi

1. Anzalone AV, Randolph PB, Davis JR, Sousa AA, Koblan LW, Levy JM, et al. Search-and-replace genome editing without double-strand breaks or donor DNA. Nature. 2019;576(7785):149–57. doi: 10.1038/s41586-019-1711-4

2. Anderson R, et al. Optimizing GEM colony management. J Exp Models. 2022;45(6):345–59.

3. Bhatia SN, Ingber DE. Microfluidic organs-on-chips. Nat Biotechnol. 2014;32(8):760–72. doi: 10.1038/nbt.2989.

4. Capecchi MR. Gene targeting in mice: functional analysis of the mammalian genome for the twenty-first century. Nat Rev Genet. 2005;6(6):507–12. doi: 10.1038/nrg1619.

5. Chuai G, Ma H, Yan J, Chen M, Hong N, Xue D, et al. DeepCRISPR: optimized CRISPR guide RNA design by deep learning. Genome Biol. 2018;19(1):80. doi: 10.1186/s13059-018-1459-4.

6. Doudna JA, Charpentier E. The new frontier of genome engineering with CRISPR-Cas9. Science. 2014;346(6213). doi: 10.1126/science.1258096.

7. European Parliament. Directive 2010/63/EU on the protection of animals used for scientific purposes. 2010.

8. Evans MJ, Kaufman MH. Establishment in culture of pluripotential cells from mouse embryos. Nature. 1981;292(5819):154–6. doi: 10.1038/292154a0.

9. Gaj T, Gersbach CA, Barbas 3rd CF. ZFN, TALEN, and CRISPR/Cas-based methods for genome engineering. Trends Biotechnol. 2013;31(7):397–405. doi: 10.1016/j.tibtech.2013.04.004.

10. Hasegawa M, et al. CYP -humanized mouse models for the study of drug metabolism and pharmacokinetics. Curr Drug Metab. 2011;12(7):637–44.

11. Hay M, Thomas DW, Craighead JL, Economides C, Rosenthal J. Clinical development success rates for investigational drugs. Nat Biotechnol. 2014;32(1):40–51. doi: 10.1038/nbt.2786.

12. Hsu PD, Lander ES, Zhang F. Development and applications of CRISPR-Cas9 for genome engineering. Cell 2014;157(6):1262–78. doi: 10.1016/j.cell.2014.05.010.

13. Liang P, et al. Base editing and prime editing: precision genome editing without double-strand breaks. J Genet Genomics. 2021;48(5):319–31.

14. Li S, et al. AML1-ETO driven acute myeloid leukemia mouse model. Leukemia 2016;30(5):1125–34.

15. Nakagata N. Cryopreservation of mouse spermatozoa. Mamm Genome. 2000;11(7):572–6.

16. Nishimura H, Okazaki T, Tanaka Y, Nakatani K, Hara M, Matsumori A, et al. Autoimmune dilated cardiomyopathy in PD-1 receptor-deficient mice. Science. 1999;291(5502):319–22. doi: 10.1007/s003350010109.

17. Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, et al. Integrative genomics viewer. Nat Biotechnol. 2011;29(1):24–6. doi: 10.1038/nbt.1754.

18. Russell WMS, Burch RL. The principles of humane experimental technique. London: Methuen; 1959.

19. Sauer B. Inducible gene targeting in mice using the Cre/lox system. Methods. 1998;14(4):381–92. doi: 10.1006/meth.1998.0593.

20. Sharma A, et al. Artificial intelligence in genetic engineering and drug discovery. Drug Discov Today. 2021;26(4):933–43.

21. Silver LM. Mouse genetics: concepts and applications. Oxford: Oxford University Press; 1995.

22. Ståhl PL, Salmén F, Vickovic S, Lundmark A, Navarro JF, Magnusson J, et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science. 2016;353(6294):78–82. doi: 10.1126/science.aaf2403.

23. Thomas G, et al. Challenges in translational drug development. Drug Discov Today. 2022;27(5):1053–65.

24. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457(7228):480–4. doi: 10.1038/nature07540.

25. Yoshitomi H, et al. A role for innate immunity in the pathogenesis of rheumatoid arthritis. Nature. 2005;435(7040):243–7.

26. Zhang SH, Reddick RL, Piedrahita JA, Maeda N. Spontaneous hypercholesterolemia and atherosclerosis in mice lacking apolipoprotein E. Science. 1992;258(5081):468–71. doi: 10.1126/science.1411543.

27. Zheng GXY, Teery JM, Belgrader P, Rvykin P, Bent ZW, Wilson R, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun. 2017;8. doi: 10.1038/ncomms14049.