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

Author

Listed:
  • Ming-Ru Wu

    (Massachusetts Institute of Technology)

  • Lior Nissim

    (The Hebrew University of Jerusalem)

  • Doron Stupp

    (The Hebrew University of Jerusalem)

  • Erez Pery

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Adina Binder-Nissim

    (Massachusetts Institute of Technology)

  • Karen Weisinger

    (Massachusetts Institute of Technology)

  • Casper Enghuus

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Sebastian R. Palacios

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Melissa Humphrey

    (Massachusetts General Hospital)

  • Zhizhuo Zhang

    (Massachusetts Institute of Technology
    Broad Institute of MIT and Harvard)

  • Eva Maria Novoa

    (Massachusetts Institute of Technology
    Broad Institute of MIT and Harvard
    Center for Genomic Regulation (CRG))

  • Manolis Kellis

    (Massachusetts Institute of Technology
    Broad Institute of MIT and Harvard)

  • Ron Weiss

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Samuel D. Rabkin

    (Massachusetts General Hospital
    Harvard Medical School)

  • Yuval Tabach

    (The Hebrew University of Jerusalem)

  • Timothy K. Lu

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Harvard University)

Abstract

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.

Suggested Citation

  • Ming-Ru Wu & Lior Nissim & Doron Stupp & Erez Pery & Adina Binder-Nissim & Karen Weisinger & Casper Enghuus & Sebastian R. Palacios & Melissa Humphrey & Zhizhuo Zhang & Eva Maria Novoa & Manolis Kelli, 2019. "A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS)," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10912-8
    DOI: 10.1038/s41467-019-10912-8
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    Cited by:

    1. Pengcheng Zhang & Haochen Wang & Hanwen Xu & Lei Wei & Liyang Liu & Zhirui Hu & Xiaowo Wang, 2023. "Deep flanking sequence engineering for efficient promoter design using DeepSEED," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Qiuge Zhang & Samira M. Azarin & Casim A. Sarkar, 2022. "Model-guided engineering of DNA sequences with predictable site-specific recombination rates," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Yafeng Wang & Guiquan Zhang & Qingzhou Meng & Shisheng Huang & Panpan Guo & Qibin Leng & Lingyun Sun & Geng Liu & Xingxu Huang & Jianghuai Liu, 2022. "Precise tumor immune rewiring via synthetic CRISPRa circuits gated by concurrent gain/loss of transcription factors," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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