• Title/Summary/Keyword: Clustered regularly interspaced short palindromic repeats (CRISPR)

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Application of the CRISPR/Cas System for Point-of-care Diagnosis of Cattle Disease (현장에서 가축질병을 진단하기 위한 CRISPR/Cas 시스템의 활용)

  • Lee, Wonhee;Lee, Yoonseok
    • Journal of Life Science
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    • v.30 no.3
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    • pp.313-319
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    • 2020
  • Recently, cattle epidemic diseases are caused by a pathogen such as a virus or bacterium. Such diseases can spread through various pathways, such as feed intake, respiration, and contact between livestock. Diagnosis based on the ELISA (Enzyme-linked immunosorbent assay) and PCR (Polymerase chain reaction) methods has limitations because these traditional diagnostic methods are time consuming assays that require multiple steps and dedicated equipment. In this review, we propose the use of the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) Cas system based on DNA and RNA levels for early point-of-care diagnosis in cattle. In the CRISPR/Cas system, Cas effectors are classified into two classes and six subtypes. The Cas effectors included in class 2 are typically Cas9 in type II, Cas12 in type V (Cas12a and Cas12b) and Cas13 in type VI (Cas13a and Cas13b). The CRISPR/Cas system uses reporter molecules that are attached to the ssDNA strands. When the Cas enzyme cuts the ssDNA, these reporters either fluoresce or change color, indicating the presence of a specific disease marker. There are several steps in the development of a CRISPR/Cas system. The first is to select the Cas enzyme depending on DNA or RNA from pathogens (viruses or bacteria). Based on that, the next step is to integrate the optimal amplification, transducing method, and signal reporter. The CRISPR/Cas system is a powerful diagnostic tool using a gene-editing method, which is faster, better, and cheaper than traditional methods. This system could be used for early diagnosis of epidemic cattle diseases and help to control their spread.

In vivo multiplex gene targeting with Streptococcus pyogens and Campylobacter jejuni Cas9 for pancreatic cancer modeling in wild-type animal

  • Chang, Yoo Jin;Bae, Jihyeon;Zhao, Yang;Lee, Geonseong;Han, Jeongpil;Lee, Yoon Hoo;Koo, Ok Jae;Seo, Sunmin;Choi, Yang-Kyu;Yeom, Su Cheong
    • Journal of Veterinary Science
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    • v.21 no.2
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    • pp.26.1-26.14
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    • 2020
  • Pancreatic ductal adenocarcinoma is a lethal cancer type that is associated with multiple gene mutations in somatic cells. Genetically engineered mouse is hardly applicable for developing a pancreatic cancer model, and the xenograft model poses a limitation in the reflection of early stage pancreatic cancer. Thus, in vivo somatic cell gene engineering with clustered regularly interspaced short palindromic repeats is drawing increasing attention for generating an animal model of pancreatic cancer. In this study, we selected Kras, Trp53, Ink4a, Smad4, and Brca2 as target genes, and applied Campylobacter jejuni Cas9 (CjCas9) and Streptococcus pyogens Cas9 (SpCas9) for developing pancreatic cancer using adeno associated virus (AAV) transduction. After confirming multifocal and diffuse transduction of AAV2, we generated SpCas9 overexpression mice, which exhibited high double-strand DNA breakage (DSB) in target genes and pancreatic intraepithelial neoplasia (PanIN) lesions with two AAV transductions; however, wild-type (WT) mice with three AAV transductions did not develop PanIN. Furthermore, small-sized Cjcas9 was applied to WT mice with two AAV system, which, in addition, developed high extensive DSB and PanIN lesions. Histological changes and expression of cancer markers such as Ki67, cytokeratin, Mucin5a, alpha smooth muscle actin in duct and islet cells were observed. In addition, the study revealed several findings such as 1) multiple DSB potential of AAV-CjCas9, 2) peri-ductal lymphocyte infiltration, 3) multi-focal cancer marker expression, and 4) requirement of > 12 months for initiation of PanIN in AAV mediated targeting. In this study, we present a useful tool for in vivo cancer modeling that would be applicable for other disease models as well.