Literature DB >> 29691708

Generation of insulin-deficient piglets by disrupting INS gene using CRISPR/Cas9 system.

Bumrae Cho1, Su Jin Kim1, Eun-Jin Lee1, Sun Mi Ahn1, Jin Seok Lee1, Dal-Young Ji1, Kiho Lee2, Jung-Taek Kang3.   

Abstract

Diabetes mellitus is a chronic disease with accompanying severe complications. Various animal models, mostly rodents due to availability of genetically modified lines, have been used to investigate the pathophysiology of diabetes. Using pigs for diabetic research can be beneficial because of their similarity in size, pathogenesis pathway, physiology, and metabolism with human. However, the use of pigs for diabetes research has been hampered due to only few pig models presenting diabetes symptoms. In this study, we have successfully generated insulin-deficient pigs by generating the indels of the porcine INS gene in somatic cells using CRISPR/Cas9 system followed by somatic cell nuclear transfer. First, somatic cells carrying a modified INS gene were generated using CRISPR/Cas9 system and their genotypes were confirmed by T7E1 assay; targeting efficiency was 40.4% (21/52). After embryo transfer, three live and five stillborn piglets were born. As expected, INS knockout piglets presented high blood glucose levels and glucose was detected in the urine. The level of insulin and c-peptide in the blood serum of INS knockout piglets were constant after feeding and the expression of insulin in the pancreas was absent in those piglets. This study demonstrates effectiveness of CRISPR/Cas9 system in generating novel pig models. We expect that these insulin-deficient pigs can be used in diabetes research to test the efficacy and safety of new drugs and the recipient of islet transplantation to investigate optimal transplantation strategies.

Entities:  

Keywords:  Animal model; CRISPR/Cas9; Diabetes mellitus; Insulin KO; Transgenic pigs

Mesh:

Substances:

Year:  2018        PMID: 29691708     DOI: 10.1007/s11248-018-0074-1

Source DB:  PubMed          Journal:  Transgenic Res        ISSN: 0962-8819            Impact factor:   2.788


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