A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS)

Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be superior to native ones, but the design of such promot...

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Bibliographic Details
Published in:	Nature communications Vol. 10; no. 1; pp. 2880 - 10
Main Authors:	Wu, Ming-Ru, Nissim, Lior, Stupp, Doron, Pery, Erez, Binder-Nissim, Adina, Weisinger, Karen, Enghuus, Casper, Palacios, Sebastian R., Humphrey, Melissa, Zhang, Zhizhuo, Maria Novoa, Eva, Kellis, Manolis, Weiss, Ron, Rabkin, Samuel D., Tabach, Yuval, Lu, Timothy K.
Format:	Journal Article
Language:	English
Published:	London Nature Publishing Group UK 28-06-2019 Nature Publishing Group Nature Portfolio
Subjects:	13/106 13/31 14/63 38/23 38/47 49/40 631/1647/1511 631/1647/2163 631/61 631/61/201 631/67 Biotechnology Breast cancer Breast Neoplasms Cell Line, Tumor Cell Separation - methods Female Gene expression Gene Expression Regulation Gene Library Gene regulation Gene therapy Glioblastoma High-throughput screening Humanities and Social Sciences Humans Induced Pluripotent Stem Cells Learning algorithms Lentivirus Machine Learning multidisciplinary Neoplastic Stem Cells Next-generation sequencing Organoids Pluripotency Promoter Regions, Genetic Promoters Regulatory Elements, Transcriptional Science Science (multidisciplinary) Software Stem cells Transcription
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Summary:	Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be superior to native ones, but the design of such promoters is challenging and frequently requires gene regulation or transcriptome knowledge that is not readily available. Here, to overcome this challenge, we use a next-generation sequencing approach combined with machine learning to screen a synthetic promoter library with 6107 designs for high-performance SPECS for potentially any cell state. We demonstrate the identification of multiple SPECS that exhibit distinct spatiotemporal activity during the programmed differentiation of induced pluripotent stem cells (iPSCs), as well as SPECS for breast cancer and glioblastoma stem-like cells. We anticipate that this approach could be used to create SPECS for gene therapies that are activated in specific cell states, as well as to study natural transcriptional regulatory networks. Synthetic promoters can be superior to native ones but the design is challenging without knowledge of gene regulation. Here the authors develop a pipeline that allows for screening a synthetic promoter library to identify high performance promoters in potentially any given cell state of interest.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	2041-1723 2041-1723
DOI:	10.1038/s41467-019-10912-8