Evidence map›Paper›PMID 26955203›Full record

ArticlePhysica D. Nonlinear phenomena2016

Spatiotemporal dynamics of distributed synthetic genetic circuits.

Oleg Kanakov, Tetyana Laptyeva, Lev Tsimring, Mikhail Ivanchenko

Abstract read
In one paragraph

Article in Physica D. Nonlinear phenomena, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Moran Model of Spatial Alignment in Microbial Colonies.Physica D. Nonlinear phenomena · 2019
    Article
  2. Article
  3. 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

4 authors.

Oleg KanakovLobachevsky State University of Nizhniy Novgorod, Prospekt Gagarina 23, 603950 Nizhniy Novgorod, Russia.
Tetyana LaptyevaLobachevsky State University of Nizhniy Novgorod, Prospekt Gagarina 23, 603950 Nizhniy Novgorod, Russia.
Lev TsimringBioCircuits Institute, University of California - San Diego, La Jolla, CA 92093-0328, USA.
Mikhail IvanchenkoLobachevsky State University of Nizhniy Novgorod, Prospekt Gagarina 23, 603950 Nizhniy Novgorod, Russia.

Funding

SYNTHETIC SYSTEMSP50GM085764 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HASTY, JEFF M, IDEKER, TREY · 2010 to 2018
$23.3M
Engineered Gene Circuits for Basic Science and BiotechnologyR01GM069811 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HASTY, JEFF M, TSIMRING, LEV S · 2004 to 2025
$13.6M
NIGMS NIH HHS P50 GM085764NIGMS NIH HHS R01 GM069811
6 · The paper itself

Abstract

We propose and study models of two distributed synthetic gene circuits, toggle-switch and oscillator, each split between two cell strains and coupled via quorum-sensing signals. The distributed toggle switch relies on mutual repression of the two strains, and oscillator is comprised of two strains, one of which acts as an activator for another that in turn acts as a repressor. Distributed toggle switch can exhibit mobile fronts, switching the system from the weaker to the stronger spatially homogeneous state. The circuit can also act as a biosensor, with the switching front dynamics determined by the properties of an external signal. Distributed oscillator system displays another biosensor functionality: oscillations emerge once a small amount of one cell strain appears amid the other, present in abundance. Distribution of synthetic gene circuits among multiple strains allows one to reduce crosstalk among different parts of the overall system and also decrease the energetic burden of the synthetic circuit per cell, which may allow for enhanced functionality and viability of engineered cells.

Indexed as

biosensingreaction-diffusion systemssynthetic gene networks

Identifiers

PMID26955203
PMCPMC4778264

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Registered trials

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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.