Single-cell encoded gene silencing for high-throughput combinatorial siRNA screening

Nov 19, 2024·
Feng Guo
1st Author
,
Xianglin Ji
Co-1st Author
,
Chuxiao Xiong
,
Hailiang Sun
,
Zhenghua Liang
,
Richard Yan-Do
Bao-Wen GAI
Bao-Wen GAI
Feng GAO
Feng GAO
,
Linfeng Huang
,
Zhongping Li
,
Becki Yi Kuang
,
Peng Shi
Corresponding Author
· 0 min read
Abstract
The use of combinatorial siRNAs shows great promise for drug discovery, but the identification of safe and effective siRNA combinations remains challenging. Here, we develop a massively multiplexed technology for systematic screening of siRNA-based cocktail therapeutics. We employ composite micro-carriers that are responsive to near infrared light and magnetic field to achieve photoporation-facilitated siRNA transfection to individual cells. Thus, randomized gene silencing by different siRNA formulations can be performed with high-throughput single-cell-based analyses. For screening anti-cancer siRNA cocktails, we test more than 1300 siRNA combinations for knocking down multiple genes related to tumor growth, discovering effective 3-siRNA formulations with an emphasis on the critical role of inhibiting Cyclin D1 and survivin, along with their complementary targets for synergic efficacy. This approach enables orders of magnitude reduction in time and cost associated with largescale siRNA screening, and resolves key insights to siRNA pharmacology that are not permissive to existing methods.
Type
Publication
Nature Communications
publication
Bao-Wen GAI
Authors
PhD Student
I am a PhD student working on AI methods for colorectal cancer diagnosis and prognosis.
Feng GAO
Authors
Professor
My research leverages AI and big data to improve diagnostics, prognostics, and ultimately, outcomes in cancer and other biomedical fields.