Model Organisms and Systems in Life Sciences

Mert Polat; Feride İffet Şahin; Yunus Kasım Terzi

doi:10.7197/cmj.991430

Review

Year 2022, , 1 - 8, 30.03.2022

Mert Polat , Feride İffet Şahin , Yunus Kasım Terzi

https://doi.org/10.7197/cmj.991430

Abstract

Supporting Institution

Bulunmamaktadır

Project Number

Bulunmamaktadır

Thanks

Bulunmamaktadır

References

1. Jackson M, Marks L, May GHW, Wilson JB. The genetic basis of disease. Essays Biochem. 2018;62(5):643-723.
2. WHO. https://www.who.int/health-topics/congenital-anomalies 2020
3. Clevers H. Modeling Development and Disease with Organoids. Cell. 2016;165(7):1586-97.
4. Morrison TM, Dreher ML, Nagaraja S, Angelone LM, Kainz W. The Role of Computational Modeling and Simulation in the Total Product Life Cycle of Peripheral Vascular Devices. J Med Device. 2017;11(2).
5. Dietrich MR, Ankeny RA, Crowe N, Green S, Leonelli S. How to choose your research organism. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 2020;80:101227.
6. de Magalhães JP. The big, the bad and the ugly: Extreme animals as inspiration for biomedical research. EMBO Rep. 2015;16(7):771-6.
7. Wilson-Sanders SE. Invertebrate models for biomedical research, testing, and education. Ilar j. 2011;52(2):126-52.
8. Yamamoto-Hino M, Goto S. In Vivo RNAi-Based Screens: Studies in Model Organisms. Genes (Basel). 2013;4(4):646-65.
9. Ugur B, Chen K, Bellen HJ. Drosophila tools and assays for the study of human diseases. Dis Model Mech. 2016;9(3):235-44.
10. Kim Y, Park Y, Hwang J, Kwack K. Comparative genomic analysis of the human and nematode Caenorhabditis elegans uncovers potential reproductive genes and disease associations in humans. Physiol Genomics. 2018;50(11):1002-14.
11. Koon AC, Chan HYE. Drosophila melanogaster As a Model Organism to Study RNA Toxicity of Repeat Expansion-Associated Neurodegenerative and Neuromuscular Diseases. Front Cell Neurosci. 2017;11:70-.
12. Hirth F. Drosophila melanogaster in the study of human neurodegeneration. CNS Neurol Disord Drug Targets. 2010;9(4):504-23.
13. Tolwinski NS. Introduction: Drosophila-A Model System for Developmental Biology. J Dev Biol. 2017;5(3):9.
14. Calabrese EJ. Was Muller's 1946 Nobel Prize research for radiation-induced gene mutations peer-reviewed? Philos Ethics Humanit Med. 2018;13(1):6.
15. Markow TA. The secret lives of Drosophila flies. Elife. 2015;4:e06793.
16. Hattori D, Aso Y, Swartz KJ, Rubin GM, Abbott LF, Axel R. Representations of Novelty and Familiarity in a Mushroom Body Compartment. Cell. 2017;169(5):956-69.e17.
17. Ariffin JK, Sweet MJ. Differences in the repertoire, regulation and function of Toll-like Receptors and inflammasome-forming Nod-like Receptors between human and mouse. Curr Opin Microbiol. 2013;16(3):303-10.
18. Vijay K. Toll-like receptors in immunity and inflammatory diseases: Past, present, and future. Int Immunopharmacol. 2018;59:391-412.
19. O'Neill LA, Golenbock D, Bowie AG. The history of Toll-like receptors - redefining innate immunity. Nat Rev Immunol. 2013;13(6):453-60.
20. Gho M, Schweisguth F. Frizzled signalling controls orientation of asymmetric sense organ precursor cell divisions in Drosophila. Nature. 1998;393(6681):178-81.
21. Bello B, Reichert H, Hirth F. The brain tumor gene negatively regulates neural progenitor cell proliferation in the larval central brain of Drosophila. Development. 2006;133(14):2639-48.
22. Ghaemi R, Tong J, Gupta BP, Selvaganapathy PR. Microfluidic Device for Microinjection of Caenorhabditis elegans. Micromachines (Basel). 2020;11(3):295.
23. Arata Y, Oshima T, Ikeda Y, Kimura H, Sako Y. OP50, a bacterial strain conventionally used as food for laboratory maintenance of C. elegans, is a biofilm formation defective mutant. MicroPubl Biol. 2020;2020:10.17912/micropub.biology.000216.
24. Conte D, Jr., MacNeil LT, Walhout AJM, Mello CC. RNA Interference in Caenorhabditis elegans. Curr Protoc Mol Biol. 2015;109:26.3.1-.3.30.
25. Dickinson DJ, Goldstein B. CRISPR-Based Methods for Caenorhabditis elegans Genome Engineering. Genetics. 2016;202(3):885-901.
26. Okazaki A, Sudo Y, Takagi S. Optical silencing of C. elegans cells with arch proton pump. PLoS One. 2012;7(5):e35370.
27. Apfeld J, Alper S. What Can We Learn About Human Disease from the Nematode C. elegans? Methods Mol Biol. 2018;1706:53-75.
28. Taormina G, Ferrante F, Vieni S, Grassi N, Russo A, Mirisola MG. Longevity: Lesson from Model Organisms. Genes (Basel). 2019;10(7):518.
29. Fierst JL, Willis JH, Thomas CG, Wang W, Reynolds RM, Ahearne TE, et al. Reproductive Mode and the Evolution of Genome Size and Structure in Caenorhabditis Nematodes. PLoS Genet. 2015;11(6):e1005323-e.
30. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science. 1998;282(5396):2012-8.
31. Kemphues KJ. Horvitz and Sulston on Caenorhabditis elegans Cell Lineage Mutants. Genetics. 2016;203(4):1485-7.
32. Karathia H, Vilaprinyo E, Sorribas A, Alves R. Saccharomyces cerevisiae as a model organism: a comparative study. PloS one. 2011;6(2):e16015-e.
33. Murakami C, Kaeberlein M. Quantifying yeast chronological life span by outgrowth of aged cells. J Vis Exp. 2009(27).
34. Biddick R, Young ET. The disorderly study of ordered recruitment. Yeast. 2009;26(4):205-20.
35. Owsianowski E, Walter D, Fahrenkrog B. Negative regulation of apoptosis in yeast. Biochim Biophys Acta. 2008;1783(7):1303-10.
36. Dymond J, Boeke J. The Saccharomyces cerevisiae SCRaMbLE system and genome minimization. Bioeng Bugs. 2012;3(3):168-71.
37. Lundblad V, Struhl K. Yeast. Curr Protoc Mol Biol. 2010;92(1):13.0.1-.0.4.
38. Amati BB, Gasser SM. Chromosomal ARS and CEN elements bind specifically to the yeast nuclear scaffold. Cell. 1988;54(7):967-78.
39. Evans BJ, Carter TF, Greenbaum E, Gvoždík V, Kelley DB, McLaughlin PJ, et al. Genetics, Morphology, Advertisement Calls, and Historical Records Distinguish Six New Polyploid Species of African Clawed Frog (Xenopus, Pipidae) from West and Central Africa. PloS one. 2015;10(12):e0142823-e.
40. Wlizla M, McNamara S, Horb ME. Generation and Care of Xenopus laevis and Xenopus tropicalis Embryos. Methods Mol Biol. 2018;1865:19-32.
41. Amemiya CT, Alföldi J, Lee AP, Fan S, Philippe H, Maccallum I, et al. The African coelacanth genome provides insights into tetrapod evolution. Nature. 2013;496(7445):311-6.
42. Vize PD, Zorn AM. Xenopus genomic data and browser resources. Developmental Biology. 2017;426(2):194-9.
43. Hellsten U, Khokha MK, Grammer TC, Harland RM, Richardson P, Rokhsar DS. Accelerated gene evolution and subfunctionalization in the pseudotetraploid frog Xenopus laevis. BMC Biology. 2007;5(1):31.
44. Krylov V, Tlapakova T. Xenopus Cytogenetics and Chromosomal Evolution. Cytogenetic and Genome Research. 2015;145(3-4):192-200.
45. Furman BL, Bewick AJ, Harrison TL, Greenbaum E, Gvoždík V, Kusamba C, et al. Pan-African phylogeography of a model organism, the African clawed frog 'Xenopus laevis'. Mol Ecol. 2015;24(4):909-25.
46. Deryckere A, Styfhals R, Vidal EAG, Almansa E, Seuntjens E. A practical staging atlas to study embryonic development of Octopus vulgaris under controlled laboratory conditions. BMC Dev Biol. 2020;20(1):7-.
47. Perlman RL. Mouse models of human disease: An evolutionary perspective. Evol Med Public Health. 2016;2016(1):170-6.
48. Phifer-Rixey M, Nachman MW. Insights into mammalian biology from the wild house mouse Mus musculus. Elife. 2015;4.
49. Zahn-Zabal M, Dessimoz C, Glover NM. Identifying orthologs with OMA: A primer. F1000Res. 2020;9:27-.
50. Bult CJ, Blake JA, Smith CL, Kadin JA, Richardson JE, Mouse Genome Database G. Mouse Genome Database (MGD) 2019. Nucleic Acids Res. 2019;47(D1):D801-D6.
51. Gurumurthy CB, Lloyd KCK. Generating mouse models for biomedical research: technological advances. Dis Model Mech. 2019;12(1):dmm029462.
52. Trigueiro NSS, Canedo A, Braga DLS, Luchiari AC, Rocha TL. Zebrafish as an Emerging Model System in the Global South: Two Decades of Research in Brazil. Zebrafish. 2020;17(6):412-25.
53. Howe DG, Bradford YM, Eagle A, Fashena D, Frazer K, Kalita P, et al. The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching. Nucleic Acids Res. 2017;45(D1):D758-D68.
54. Kroeger PT, Jr., Poureetezadi SJ, McKee R, Jou J, Miceli R, Wingert RA. Production of haploid zebrafish embryos by in vitro fertilization. J Vis Exp. 2014(89):51708.
55. Paul CD, Devine A, Bishop K, Xu Q, Wulftange WJ, Burr H, et al. Human macrophages survive and adopt activated genotypes in living zebrafish. Scientific Reports. 2019;9(1):1759.
56. Howe K, Clark MD, Torroja CF, Torrance J, Berthelot C, Muffato M, et al. The zebrafish reference genome sequence and its relationship to the human genome. Nature. 2013;496(7446):498-503.
57. Covassin LD, Siekmann AF, Kacergis MC, Laver E, Moore JC, Villefranc JA, et al. A genetic screen for vascular mutants in zebrafish reveals dynamic roles for Vegf/Plcg1 signaling during artery development. Developmental biology. 2009;329(2):212-26.
58. Zakrzewski W, Dobrzyński M, Szymonowicz M, Rybak Z. Stem cells: past, present, and future. Stem Cell Res Ther. 2019;10(1):68-.
59. Kraus P, Lufkin T. Implications for a Stem Cell Regenerative Medicine Based Approach to Human Intervertebral Disk Degeneration. Front Cell Dev Biol. 2017;5:17.
60. Kim J, Koo B-K, Knoblich JA. Human organoids: model systems for human biology and medicine. Nature Reviews Molecular Cell Biology. 2020;21(10):571-84.
61. Simian M, Bissell MJ. Organoids: A historical perspective of thinking in three dimensions. J Cell Biol. 2017;216(1):31-40.
62. McCauley HA, Wells JM. Pluripotent stem cell-derived organoids: using principles of developmental biology to grow human tissues in a dish. Development (Cambridge, England). 2017;144(6):958-62.
63. Duval K, Grover H, Han L-H, Mou Y, Pegoraro AF, Fredberg J, et al. Modeling Physiological Events in 2D vs. 3D Cell Culture. Physiology (Bethesda). 2017;32(4):266-77.
64. Edmondson R, Broglie JJ, Adcock AF, Yang L. Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug Dev Technol. 2014;12(4):207-18.
65. Hayashi Y, Emoto T, Futaki S, Sekiguchi K. Establishment and characterization of a parietal endoderm-like cell line derived from Engelbreth-Holm-Swarm tumor (EHSPEL), a possible resource for an engineered basement membrane matrix. Matrix Biol. 2004;23(1):47-62.
66. Khoshdel Rad N, Aghdami N, Moghadasali R. Cellular and Molecular Mechanisms of Kidney Development: From the Embryo to the Kidney Organoid. Frontiers in cell and developmental biology. 2020;8:183-.
67. Di Lullo E, Kriegstein AR. The use of brain organoids to investigate neural development and disease. Nat Rev Neurosci. 2017;18(10):573-84.
68. Nantasanti S, de Bruin A, Rothuizen J, Penning LC, Schotanus BA. Concise Review: Organoids Are a Powerful Tool for the Study of Liver Disease and Personalized Treatment Design in Humans and Animals. Stem Cells Transl Med. 2016;5(3):325-30.
69. Mead BE, Karp JM. All models are wrong, but some organoids may be useful. Genome Biol. 2019;20(1):66-.
70. Brodland GW. How computational models can help unlock biological systems. Seminars in Cell & Developmental Biology. 2015;47-48:62-73.
71. Kaushik G, Ponnusamy MP, Batra SK. Concise Review: Current Status of Three-Dimensional Organoids as Preclinical Models. Stem Cells. 2018;36(9):1329-40.
72. Goldstein LJ, Rypins EB. A computer model of the kidney. Computer Methods and Programs in Biomedicine. 1992;37(3):191-203.
73. Sharpe J. Computer modeling in developmental biology: growing today, essential tomorrow. Development. 2017;144(23):4214-25.
74. Medvedev P. Modeling biological problems in computer science: a case study in genome assembly. Brief Bioinform. 2019;20(4):1376-83.
75. Beller CJ, Gebhard MM, Karck M, Labrosse MR. Usefulness and limitations of computational models in aortic disease risk stratification. J Vasc Surg. 2010;52(6):1572-9.
76. Wilson RC, Collins AG. Ten simple rules for the computational modeling of behavioral data. Elife. 2019;8.

Model Organisms and Systems in Life Sciences

Year 2022, , 1 - 8, 30.03.2022

Mert Polat , Feride İffet Şahin , Yunus Kasım Terzi

https://doi.org/10.7197/cmj.991430

Abstract

Approximately 6-7% of newborns have congenital anomalies. The causes of these anomalies are genetic-based, environmental, or multifactorial. The cause of almost 50% of congenital anomalies is not fully known. There are many specific birth defects as part of the syndromes. Even though the syndromes are complex, they use common signaling pathways in the developmental process. Because of the complex nature of developmental disorders, different types of model systems are necessary to understand the molecular pathogenesis of diseases. The molecular infrastructure of diseases and problems in a developmental process is revealed with different types of model systems. While studying the development of multicellular organisms, related molecular and cellular processes are examined. While conducting these studies, model organisms, organoids, and computerized (in silico) models are used. Each method has its advantages and disadvantages.
In this review, we will provide recent knowledge on the advantages and disadvantages of modeling systems used to understand developmental processes.

Keywords

model organisms, organoids, in slico modelling, computerized modelling, organism, biology

Project Number

Bulunmamaktadır

References

1. Jackson M, Marks L, May GHW, Wilson JB. The genetic basis of disease. Essays Biochem. 2018;62(5):643-723.
2. WHO. https://www.who.int/health-topics/congenital-anomalies 2020
3. Clevers H. Modeling Development and Disease with Organoids. Cell. 2016;165(7):1586-97.
4. Morrison TM, Dreher ML, Nagaraja S, Angelone LM, Kainz W. The Role of Computational Modeling and Simulation in the Total Product Life Cycle of Peripheral Vascular Devices. J Med Device. 2017;11(2).
5. Dietrich MR, Ankeny RA, Crowe N, Green S, Leonelli S. How to choose your research organism. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. 2020;80:101227.
6. de Magalhães JP. The big, the bad and the ugly: Extreme animals as inspiration for biomedical research. EMBO Rep. 2015;16(7):771-6.
7. Wilson-Sanders SE. Invertebrate models for biomedical research, testing, and education. Ilar j. 2011;52(2):126-52.
8. Yamamoto-Hino M, Goto S. In Vivo RNAi-Based Screens: Studies in Model Organisms. Genes (Basel). 2013;4(4):646-65.
9. Ugur B, Chen K, Bellen HJ. Drosophila tools and assays for the study of human diseases. Dis Model Mech. 2016;9(3):235-44.
10. Kim Y, Park Y, Hwang J, Kwack K. Comparative genomic analysis of the human and nematode Caenorhabditis elegans uncovers potential reproductive genes and disease associations in humans. Physiol Genomics. 2018;50(11):1002-14.
11. Koon AC, Chan HYE. Drosophila melanogaster As a Model Organism to Study RNA Toxicity of Repeat Expansion-Associated Neurodegenerative and Neuromuscular Diseases. Front Cell Neurosci. 2017;11:70-.
12. Hirth F. Drosophila melanogaster in the study of human neurodegeneration. CNS Neurol Disord Drug Targets. 2010;9(4):504-23.
13. Tolwinski NS. Introduction: Drosophila-A Model System for Developmental Biology. J Dev Biol. 2017;5(3):9.
14. Calabrese EJ. Was Muller's 1946 Nobel Prize research for radiation-induced gene mutations peer-reviewed? Philos Ethics Humanit Med. 2018;13(1):6.
15. Markow TA. The secret lives of Drosophila flies. Elife. 2015;4:e06793.
16. Hattori D, Aso Y, Swartz KJ, Rubin GM, Abbott LF, Axel R. Representations of Novelty and Familiarity in a Mushroom Body Compartment. Cell. 2017;169(5):956-69.e17.
17. Ariffin JK, Sweet MJ. Differences in the repertoire, regulation and function of Toll-like Receptors and inflammasome-forming Nod-like Receptors between human and mouse. Curr Opin Microbiol. 2013;16(3):303-10.
18. Vijay K. Toll-like receptors in immunity and inflammatory diseases: Past, present, and future. Int Immunopharmacol. 2018;59:391-412.
19. O'Neill LA, Golenbock D, Bowie AG. The history of Toll-like receptors - redefining innate immunity. Nat Rev Immunol. 2013;13(6):453-60.
20. Gho M, Schweisguth F. Frizzled signalling controls orientation of asymmetric sense organ precursor cell divisions in Drosophila. Nature. 1998;393(6681):178-81.
21. Bello B, Reichert H, Hirth F. The brain tumor gene negatively regulates neural progenitor cell proliferation in the larval central brain of Drosophila. Development. 2006;133(14):2639-48.
22. Ghaemi R, Tong J, Gupta BP, Selvaganapathy PR. Microfluidic Device for Microinjection of Caenorhabditis elegans. Micromachines (Basel). 2020;11(3):295.
23. Arata Y, Oshima T, Ikeda Y, Kimura H, Sako Y. OP50, a bacterial strain conventionally used as food for laboratory maintenance of C. elegans, is a biofilm formation defective mutant. MicroPubl Biol. 2020;2020:10.17912/micropub.biology.000216.
24. Conte D, Jr., MacNeil LT, Walhout AJM, Mello CC. RNA Interference in Caenorhabditis elegans. Curr Protoc Mol Biol. 2015;109:26.3.1-.3.30.
25. Dickinson DJ, Goldstein B. CRISPR-Based Methods for Caenorhabditis elegans Genome Engineering. Genetics. 2016;202(3):885-901.
26. Okazaki A, Sudo Y, Takagi S. Optical silencing of C. elegans cells with arch proton pump. PLoS One. 2012;7(5):e35370.
27. Apfeld J, Alper S. What Can We Learn About Human Disease from the Nematode C. elegans? Methods Mol Biol. 2018;1706:53-75.
28. Taormina G, Ferrante F, Vieni S, Grassi N, Russo A, Mirisola MG. Longevity: Lesson from Model Organisms. Genes (Basel). 2019;10(7):518.
29. Fierst JL, Willis JH, Thomas CG, Wang W, Reynolds RM, Ahearne TE, et al. Reproductive Mode and the Evolution of Genome Size and Structure in Caenorhabditis Nematodes. PLoS Genet. 2015;11(6):e1005323-e.
30. Genome sequence of the nematode C. elegans: a platform for investigating biology. Science. 1998;282(5396):2012-8.
31. Kemphues KJ. Horvitz and Sulston on Caenorhabditis elegans Cell Lineage Mutants. Genetics. 2016;203(4):1485-7.
32. Karathia H, Vilaprinyo E, Sorribas A, Alves R. Saccharomyces cerevisiae as a model organism: a comparative study. PloS one. 2011;6(2):e16015-e.
33. Murakami C, Kaeberlein M. Quantifying yeast chronological life span by outgrowth of aged cells. J Vis Exp. 2009(27).
34. Biddick R, Young ET. The disorderly study of ordered recruitment. Yeast. 2009;26(4):205-20.
35. Owsianowski E, Walter D, Fahrenkrog B. Negative regulation of apoptosis in yeast. Biochim Biophys Acta. 2008;1783(7):1303-10.
36. Dymond J, Boeke J. The Saccharomyces cerevisiae SCRaMbLE system and genome minimization. Bioeng Bugs. 2012;3(3):168-71.
37. Lundblad V, Struhl K. Yeast. Curr Protoc Mol Biol. 2010;92(1):13.0.1-.0.4.
38. Amati BB, Gasser SM. Chromosomal ARS and CEN elements bind specifically to the yeast nuclear scaffold. Cell. 1988;54(7):967-78.
39. Evans BJ, Carter TF, Greenbaum E, Gvoždík V, Kelley DB, McLaughlin PJ, et al. Genetics, Morphology, Advertisement Calls, and Historical Records Distinguish Six New Polyploid Species of African Clawed Frog (Xenopus, Pipidae) from West and Central Africa. PloS one. 2015;10(12):e0142823-e.
40. Wlizla M, McNamara S, Horb ME. Generation and Care of Xenopus laevis and Xenopus tropicalis Embryos. Methods Mol Biol. 2018;1865:19-32.
41. Amemiya CT, Alföldi J, Lee AP, Fan S, Philippe H, Maccallum I, et al. The African coelacanth genome provides insights into tetrapod evolution. Nature. 2013;496(7445):311-6.
42. Vize PD, Zorn AM. Xenopus genomic data and browser resources. Developmental Biology. 2017;426(2):194-9.
43. Hellsten U, Khokha MK, Grammer TC, Harland RM, Richardson P, Rokhsar DS. Accelerated gene evolution and subfunctionalization in the pseudotetraploid frog Xenopus laevis. BMC Biology. 2007;5(1):31.
44. Krylov V, Tlapakova T. Xenopus Cytogenetics and Chromosomal Evolution. Cytogenetic and Genome Research. 2015;145(3-4):192-200.
45. Furman BL, Bewick AJ, Harrison TL, Greenbaum E, Gvoždík V, Kusamba C, et al. Pan-African phylogeography of a model organism, the African clawed frog 'Xenopus laevis'. Mol Ecol. 2015;24(4):909-25.
46. Deryckere A, Styfhals R, Vidal EAG, Almansa E, Seuntjens E. A practical staging atlas to study embryonic development of Octopus vulgaris under controlled laboratory conditions. BMC Dev Biol. 2020;20(1):7-.
47. Perlman RL. Mouse models of human disease: An evolutionary perspective. Evol Med Public Health. 2016;2016(1):170-6.
48. Phifer-Rixey M, Nachman MW. Insights into mammalian biology from the wild house mouse Mus musculus. Elife. 2015;4.
49. Zahn-Zabal M, Dessimoz C, Glover NM. Identifying orthologs with OMA: A primer. F1000Res. 2020;9:27-.
50. Bult CJ, Blake JA, Smith CL, Kadin JA, Richardson JE, Mouse Genome Database G. Mouse Genome Database (MGD) 2019. Nucleic Acids Res. 2019;47(D1):D801-D6.
51. Gurumurthy CB, Lloyd KCK. Generating mouse models for biomedical research: technological advances. Dis Model Mech. 2019;12(1):dmm029462.
52. Trigueiro NSS, Canedo A, Braga DLS, Luchiari AC, Rocha TL. Zebrafish as an Emerging Model System in the Global South: Two Decades of Research in Brazil. Zebrafish. 2020;17(6):412-25.
53. Howe DG, Bradford YM, Eagle A, Fashena D, Frazer K, Kalita P, et al. The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching. Nucleic Acids Res. 2017;45(D1):D758-D68.
54. Kroeger PT, Jr., Poureetezadi SJ, McKee R, Jou J, Miceli R, Wingert RA. Production of haploid zebrafish embryos by in vitro fertilization. J Vis Exp. 2014(89):51708.
55. Paul CD, Devine A, Bishop K, Xu Q, Wulftange WJ, Burr H, et al. Human macrophages survive and adopt activated genotypes in living zebrafish. Scientific Reports. 2019;9(1):1759.
56. Howe K, Clark MD, Torroja CF, Torrance J, Berthelot C, Muffato M, et al. The zebrafish reference genome sequence and its relationship to the human genome. Nature. 2013;496(7446):498-503.
57. Covassin LD, Siekmann AF, Kacergis MC, Laver E, Moore JC, Villefranc JA, et al. A genetic screen for vascular mutants in zebrafish reveals dynamic roles for Vegf/Plcg1 signaling during artery development. Developmental biology. 2009;329(2):212-26.
58. Zakrzewski W, Dobrzyński M, Szymonowicz M, Rybak Z. Stem cells: past, present, and future. Stem Cell Res Ther. 2019;10(1):68-.
59. Kraus P, Lufkin T. Implications for a Stem Cell Regenerative Medicine Based Approach to Human Intervertebral Disk Degeneration. Front Cell Dev Biol. 2017;5:17.
60. Kim J, Koo B-K, Knoblich JA. Human organoids: model systems for human biology and medicine. Nature Reviews Molecular Cell Biology. 2020;21(10):571-84.
61. Simian M, Bissell MJ. Organoids: A historical perspective of thinking in three dimensions. J Cell Biol. 2017;216(1):31-40.
62. McCauley HA, Wells JM. Pluripotent stem cell-derived organoids: using principles of developmental biology to grow human tissues in a dish. Development (Cambridge, England). 2017;144(6):958-62.
63. Duval K, Grover H, Han L-H, Mou Y, Pegoraro AF, Fredberg J, et al. Modeling Physiological Events in 2D vs. 3D Cell Culture. Physiology (Bethesda). 2017;32(4):266-77.
64. Edmondson R, Broglie JJ, Adcock AF, Yang L. Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug Dev Technol. 2014;12(4):207-18.
65. Hayashi Y, Emoto T, Futaki S, Sekiguchi K. Establishment and characterization of a parietal endoderm-like cell line derived from Engelbreth-Holm-Swarm tumor (EHSPEL), a possible resource for an engineered basement membrane matrix. Matrix Biol. 2004;23(1):47-62.
66. Khoshdel Rad N, Aghdami N, Moghadasali R. Cellular and Molecular Mechanisms of Kidney Development: From the Embryo to the Kidney Organoid. Frontiers in cell and developmental biology. 2020;8:183-.
67. Di Lullo E, Kriegstein AR. The use of brain organoids to investigate neural development and disease. Nat Rev Neurosci. 2017;18(10):573-84.
68. Nantasanti S, de Bruin A, Rothuizen J, Penning LC, Schotanus BA. Concise Review: Organoids Are a Powerful Tool for the Study of Liver Disease and Personalized Treatment Design in Humans and Animals. Stem Cells Transl Med. 2016;5(3):325-30.
69. Mead BE, Karp JM. All models are wrong, but some organoids may be useful. Genome Biol. 2019;20(1):66-.
70. Brodland GW. How computational models can help unlock biological systems. Seminars in Cell & Developmental Biology. 2015;47-48:62-73.
71. Kaushik G, Ponnusamy MP, Batra SK. Concise Review: Current Status of Three-Dimensional Organoids as Preclinical Models. Stem Cells. 2018;36(9):1329-40.
72. Goldstein LJ, Rypins EB. A computer model of the kidney. Computer Methods and Programs in Biomedicine. 1992;37(3):191-203.
73. Sharpe J. Computer modeling in developmental biology: growing today, essential tomorrow. Development. 2017;144(23):4214-25.
74. Medvedev P. Modeling biological problems in computer science: a case study in genome assembly. Brief Bioinform. 2019;20(4):1376-83.
75. Beller CJ, Gebhard MM, Karck M, Labrosse MR. Usefulness and limitations of computational models in aortic disease risk stratification. J Vasc Surg. 2010;52(6):1572-9.
76. Wilson RC, Collins AG. Ten simple rules for the computational modeling of behavioral data. Elife. 2019;8.

There are 76 citations in total.

Details

Primary Language	English
Subjects	Health Care Administration
Journal Section	Reviews
Authors	Mert Polat 0000-0002-9555-4932 Feride İffet Şahin 0000-0001-7308-9673 Yunus Kasım Terzi 0000-0001-5612-9696
Project Number	Bulunmamaktadır
Publication Date	March 30, 2022
Acceptance Date	March 20, 2022
Published in Issue	Year 2022

Cite

AMA	Polat M, Şahin Fİ, Terzi YK. Model Organisms and Systems in Life Sciences. CMJ. March 2022;44(1):1-8. doi:10.7197/cmj.991430

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