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Model construction of Niemann-Pick type C disease in zebrafish

Authors: Yusheng, Lin; Xiaolian, Cai; Guiping, Wang; Gang, Ouyang; Hong, Cao;

Model construction of Niemann-Pick type C disease in zebrafish

Abstract

Abstract Niemann-Pick type C disease (NPC) is a rare human disease, with limited effective treatment options. Most cases of NPC disease are associated with inactivating mutations of the NPC1 gene. However, cellular and molecular mechanisms responsible for the NPC1 pathogenesis remain poorly defined. This is partly due to the lack of a suitable animal model to monitor the disease progression. In this study, we used CRISPR to construct an NPC1 −/− zebrafish model, which faithfully reproduced the cardinal pathological features of this disease. In contrast to the wild type (WT), the deletion of NPC1 alone caused significant hepatosplenomegaly, ataxia, Purkinje cell death, increased lipid storage, infertility and reduced body length and life span. Most of the NPC1 −/− zebrafish died within the first month post fertilization, while the remaining specimens developed slower than the WT and died before reaching 8 months of age. Filipin-stained hepatocytes of the NPC1 −/− zebrafish were clear, indicating abnormal accumulation of unesterified cholesterol. Lipid profiling showed a significant difference between NPC1 −/− and WT zebrafish. An obvious accumulation of seven sphingolipids was detected in livers of NPC1 −/− zebrafish. In summary, our results provide a valuable model system that could identify promising therapeutic targets and treatments for the NPC disease.

Related Organizations
Keywords

Disease Models, Animal, Liver, Animals, Body Size, Niemann-Pick Disease, Type C, Motor Activity, Lipid Metabolism, Zebrafish

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Powered by OpenAIRE graph
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
27
Top 10%
Average
Top 10%