Evidence map›Paper›PMID 42420739›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2026

Coupled Perturbations of Gene Circuit Dynamics by Resource Competition and Growth Dilution.

Abdelrahaman Youssef, Rong Zhang, Xiao-Jun Tian

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Abdelrahaman YoussefSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Rong ZhangSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
Xiao-Jun TianSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA. xiaojun.tian@asu.edu.

Funding

Multi-Scale Engineering of Heterogeneity in the Host-Aware Synthetic Gene CircuitsR35GM142896 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI TIAN, XIAOJUN · 2021 to 2025
$2.0M
NIGMS NIH HHS R35 GM142896
6 · The paper itself

Abstract

Resource competition and growth-mediated dilution are major sources of context dependence in synthetic gene circuits. However, their coupled effects on circuit behavior remain insufficiently dissected. This chapter presents a step-by-step experimental workflow for constructing and characterizing inhibitory genetic cascades in E. coli to examine whether and how circuit dynamics depend on these two contextual factors. The protocol details the design and assembly of inhibitory circuits with tunable promoter strength, ribosome binding site strength, and plasmid copy number. Methods are provided for quantifying circuit dynamics using plate-reader fluorescence assays under varying inducer doses, with and without preinduction, and across different growth conditions. Finally, data processing and analysis procedures are outlined to characterize module interdependences and expression dynamics. Collectively, this protocol provides a practical framework for investigating how shared cellular resources and growth processes shape gene circuit behavior and serves as a guide for studying multiple context-dependent effects in synthetic biology.

Indexed as

Escherichia coliGene Expression Regulation, BacterialGene Regulatory NetworksSynthetic BiologyPlasmidsPromoter Regions, GeneticRibosomesGene expression dynamicsGrowth-mediated dilutionHost-circuit interactionsInhibitory genetic cascadesResource competition

Identifiers

PMID42420739
PMCPMC13520777

What OpenQuestion holds

Textmetadata
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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.