Evidence map›Paper›PMID 26656950›Full record

ArticleNucleic acids research2016

Dealing with the genetic load in bacterial synthetic biology circuits: convergences with the Ohm's law.

M Carbonell-Ballestero, E Garcia-Ramallo, R Montañez, C Rodriguez-Caso, J Macía

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

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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

5 authors.

M Carbonell-BallesteroICREA-Complex Systems Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain Department of Experimental and Health Sciences. Universitat Pompeu Fabra, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Psg. de la Barceloneta 37, 08003 Barcelona, Spain.
E Garcia-RamalloICREA-Complex Systems Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain Department of Experimental and Health Sciences. Universitat Pompeu Fabra, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Psg. de la Barceloneta 37, 08003 Barcelona, Spain.
R MontañezICREA-Complex Systems Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain Department of Experimental and Health Sciences. Universitat Pompeu Fabra, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Psg. de la Barceloneta 37, 08003 Barcelona, Spain.
C Rodriguez-CasoICREA-Complex Systems Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain Department of Experimental and Health Sciences. Universitat Pompeu Fabra, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Psg. de la Barceloneta 37, 08003 Barcelona, Spain carlos.rodriguez@upf.edu.
J MacíaICREA-Complex Systems Laboratory, Universitat Pompeu Fabra, 08003 Barcelona, Spain Department of Experimental and Health Sciences. Universitat Pompeu Fabra, 08003 Barcelona, Spain Institut de Biologia Evolutiva, CSIC-UPF, Psg. de la Barceloneta 37, 08003 Barcelona, Spain javier.macia@upf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Synthetic biology seeks to envision living cells as a matter of engineering. However, increasing evidence suggests that the genetic load imposed by the incorporation of synthetic devices in a living organism introduces a sort of unpredictability in the design process. As a result, individual part characterization is not enough to predict the behavior of designed circuits and thus, a costly trial-error process is eventually required. In this work, we provide a new theoretical framework for the predictive treatment of the genetic load. We mathematically and experimentally demonstrate that dependences among genes follow a quantitatively predictable behavior. Our theory predicts the observed reduction of the expression of a given synthetic gene when an extra genetic load is introduced in the circuit. The theory also explains that such dependence qualitatively differs when the extra load is added either by transcriptional or translational modifications. We finally show that the limitation of the cellular resources for gene expression leads to a mathematical formulation that converges to an expression analogous to the Ohm's law for electric circuits. Similitudes and divergences with this law are outlined. Our work provides a suitable framework with predictive character for the design process of complex genetic devices in synthetic biology.

Indexed as

Genetic LoadSynthetic BiologyAlgorithmsBacteriaEscherichia coliGene Expression Regulation, BacterialModels, Biological

Identifiers

PMID26656950
PMCPMC4705654

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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.