Evidence map›Paper›PMID 33173034›Full record

ArticleNature communications2020

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells.

Ross D Jones, Yili Qian, Velia Siciliano, Breanna DiAndreth, Jin Huh, Ron Weiss, Domitilla Del Vecchio

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed
5.3field-weighted citation impact, top 3% of its field
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

80 citing papers in PubMed, 120 citations in OpenAlex.

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  6. Programming Next-Generation Synthetic Biosensors by Genetic Circuit Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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20 more citing papers are in PubMed but not listed here.

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

7 authors at 2 institutions in 2 countries.

Ross D JonesDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID 0000-0003-0891-6761
Yili QianSynthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID 0000-0002-1097-0401
Velia SicilianoDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID 0000-0001-7734-9153
Breanna DiAndrethDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID 0000-0002-0302-6834
Jin HuhDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Ron WeissDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. rweiss@mit.edu.ORCID 0000-0003-0396-2443
Domitilla Del VecchioSynthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. ddv@mit.edu.ORCID 0000-0001-6472-8576
Massachusetts Institute of Technology · USItalian Institute of Technology · IT

Funding

MIT Center for Integrative Synthetic BiologyP50GM098792 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI WEISS, RON · 2013 to 2017
$11.0M
NIGMS NIH HHS P50 GM098792
6 · The paper itself

Abstract

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

Indexed as

AnimalsCell LineEndoribonucleasesGene ExpressionGenetic EngineeringHumansMammalsModels, BiologicalSynthetic BiologyEndoribonucleases

Identifiers

PMID33173034
PMCPMC7656454
OpenAlexW3103811267

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.