Protocol for image-based small-molecule screen to identify neuroprotective compounds for dopaminergic neurons in zebrafish.
Protocol for image-based small-molecule screen to identify neuroprotective compounds for dopaminergic neurons in zebrafish.
复制标题
基于图像的小分子筛选的方案,以鉴定斑马鱼中多巴胺能神经元的神经保护化合物。
DOI:
10.1016/j.xpro.2024.102837
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发表时间:
2024-03-15
期刊:
影响因子:
--
通讯作者:
Guo, Su
中科院分区:
文献类型:
--
作者:
Kim, Gha-hyun Jeffrey;Chen, Min;Kwok, Sharie;Guo, Su
Whole-organism-based screen holds promise for discovering biologically active compounds. However, high-content imaging is challenging due to the difficulty of positioning live animals and individual variability of neuron counts. Here, we present a protocol to identify neuroprotective compounds for dopaminergic neurons in zebrafish using an image-based small-molecule screen. We describe steps for raising larvae, agarose embedding, and treatment to induce neurodegeneration. We then detail procedures for live confocal imaging, image processing, and data analysis. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021). Whole-organism in vivo imaging-based screening protocol for neurodegenerative diseases Step-by-step guide to embed and position larvae dorsal down in 96-well plates Live confocal imaging before and after treatment of zebrafish larvae diencephalon Automated pipeline for quantifying dopamine neuron loss with open-source program Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Whole-organism-based screen holds promise for discovering biologically active compounds. However, high-content imaging is challenging due to the difficulty of positioning live animals and individual variability of neuron counts. Here, we present a protocol to identify neuroprotective compounds for dopaminergic neurons in zebrafish using an image-based small-molecule screen. We describe steps for raising larvae, agarose embedding, and treatment to induce neurodegeneration. We then detail procedures for live confocal imaging, image processing, and data analysis.
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影响因子:
5.6
作者:
Kim GJ;Mo H;Liu H;Okorie M;Chen S;Zheng J;Li H;Arkin M;Huang B;Guo S
通讯作者:
Guo S
DOI:
10.3390/molecules23010040
发表时间:
2017-12-25
期刊:
Molecules (Basel, Switzerland)
影响因子:
--
作者:
Haddad F;Sawalha M;Khawaja Y;Najjar A;Karaman R
通讯作者:
Karaman R
影响因子:
7.7
作者:
Kim GJ;Mo H;Liu H;Wu Z;Chen S;Zheng J;Zhao X;Nucum D;Shortland J;Peng L;Elepano M;Tang B;Olson S;Paras N;Li H;Renslo AR;Arkin MR;Huang B;Lu B;Sirota M;Guo S
通讯作者:
Guo S
影响因子:
3
作者:
Stirling DR;Swain-Bowden MJ;Lucas AM;Carpenter AE;Cimini BA;Goodman A
通讯作者:
Goodman A