ArticleCell systems2017
A Blueprint for a Synthetic Genetic Feedback Controller to Reprogram Cell Fate.
Article in Cell systems, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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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.
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Who cites it
50 citing papers in PubMed.
- Computational blueprints for cell fate programming.Stem cell reports · 2026Review
- Stochastic modeling of epigenetic memory.NPJ systems biology and applications · 2026Review
- Tuning evolvability via plasmid copy number and regulatory architecture.Nature communications · 2025Article
- Engineering development: From the repressilator and toggle switch to synthetic developmental biology.Developmental biology · 2025Review
- Engineering Cell Fate with Adaptive Feedback Control.ACS synthetic biology · 2025Article
- In silico modeling of directed differentiation of induced pluripotent stem cells to definitive endoderm.PLoS computational biology · 2025Article
- Splicing to keep splicing: A feedback system for cellular homeostasis and state transition.Clinical and translational medicine · 2025Review
- Small molecule- and cell contact-inducible systems for controlling expression and differentiation in mouse embryonic stem cells.Development (Cambridge, England) · 2025Article
- The regulatory architecture of the primed pluripotent cell state.Nature communications · 2025Article
- Accelerating Diverse Cell-Based Therapies Through Scalable Design.Annual review of chemical and biomolecular engineering · 2024Review
- A logic-incorporated gene regulatory network deciphers principles in cell fate decisions.eLife · 2024Article
- Competition and evolutionary selection among core regulatory motifs in gene expression control.Nature communications · 2023Article
- Synthetic genetic circuits to uncover the OCT4 trajectories of successful reprogramming of human fibroblasts.Science advances · 2023Article
- Structural identifiability of biomolecular controller motifs with and without flow measurements as model output.PLoS computational biology · 2023Article
- Performance Prediction of Fundamental Transcriptional Programs.ACS synthetic biology · 2023Article
- An Optogenetic-Controlled Cell Reprogramming System for Driving Cell Fate and Light-Responsive Chimeric Mice.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Towards AI-driven longevity research: An overview.Frontiers in aging · 2023Review
- Computational approaches for direct cell reprogramming: from the bulk omics era to the single cell era.Briefings in functional genomics · 2022Article
- Epigenetics, Enhancer Function and 3D Chromatin Organization in Reprogramming to Pluripotency.Cells · 2022Review
- scREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model.NAR genomics and bioinformatics · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell's phenotype. In practice, reprogramming is often performed by constant overexpression of specific transcription factors (TFs). This process can be unreliable and inefficient. Here, we address this problem by introducing a new approach to reprogramming based on mathematical analysis. We demonstrate that reprogramming GRNs using constant overexpression may not succeed in general. Instead, we propose an alternative reprogramming strategy: a synthetic genetic feedback controller that dynamically steers the concentration of a GRN's key TFs to any desired value. The controller works by adjusting TF expression based on the discrepancy between desired and actual TF concentrations. Theory predicts that this reprogramming strategy is guaranteed to succeed, and its performance is independent of the GRN's structure and parameters, provided that feedback gain is sufficiently high. As a case study, we apply the controller to a model of induced pluripotency in stem cells.
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Registered trials
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.