Evidence map›Paper›PMID 31253799›Full record

ArticleNature communications2019

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

Ming-Ru Wu, Lior Nissim, Doron Stupp, Erez Pery, Adina Binder-Nissim, Karen Weisinger, Casper Enghuus, Sebastian R Palacios, Melissa Humphrey, Zhizhuo Zhang and 6 more

Abstract read
In one paragraph

Article in Nature communications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

53 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Logic-Gated HSV-TK/GCV Suicide Gene Circuit for Triple-Negative Breast Cancer.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  12. A unified genetic perturbation language for human cellular programming.bioRxiv : the preprint server for biology · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Gene regulation technologies for gene and cell therapy.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
  18. Efficient gene delivery admitted by small metabolites specifically targeting astrocytes in the mouse brain.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Ming-Ru WuSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Lior NissimDepartment of Biochemistry and Molecular Biology, The Institute for Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 91120, Jerusalem, Israel.
Doron StuppDepartment of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 91120, Jerusalem, Israel.ORCID http://orcid.org/0000-0002-1556-666X
Erez PerySynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Adina Binder-NissimSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Karen WeisingerSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Casper EnghuusDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Sebastian R PalaciosSynthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Melissa HumphreyBrain Tumor Research Center, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02144, USA.
Zhizhuo ZhangComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Eva Maria NovoaComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0002-9367-6311
Manolis KellisComputer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0001-7113-9630
Ron WeissDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0003-0396-2443
Samuel D RabkinBrain Tumor Research Center, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02144, USA.ORCID http://orcid.org/0000-0003-2344-2795
Yuval TabachDepartment of Developmental Biology and Cancer Research, The Institute for Medical Research Israel-Canada, Hadassah Medical School, The Hebrew University of Jerusalem, 91120, Jerusalem, Israel. yuvaltab@ekmd.huji.ac.il.
Timothy K LuSynthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. timlu@mit.edu.

Funding

Targeting Tumorigenic Pathways in Glioblastoma with Oncolytic HSVR01CA160762 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI RABKIN, SAMUEL DAVID · 2012 to 2023
$3.7M
NCI NIH HHS R01 CA160762U.S. Department of Defense (United States Department of Defense) W81XWH-16-1-0452U.S. Department of Defense (United States Department of Defense) W81XWH-16-1-0565U.S. Department of Defense (United States Department of Defense) W81XWH-18-1-0513
6 · The paper itself

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.

Indexed as

Machine LearningPromoter Regions, GeneticSoftwareBreast NeoplasmsCell Line, TumorCell SeparationFemaleGene Expression RegulationGene LibraryGlioblastomaHumansInduced Pluripotent Stem CellsLentivirusNeoplastic Stem CellsOrganoidsRegulatory Elements, Transcriptional

Identifiers

PMID31253799
PMCPMC6599391

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.