Evidence map›Paper›PMID 41457566›Full record

ArticleACS synthetic biology2026

Resource Competition and Growth Dilution Modulate Synthetic Gene Cascade Dynamics.

Abdelrahaman Youssef, Sadikshya Rijal, Rong Zhang, Xiao-Jun Tian

Abstract read
In one paragraph

Article in ACS synthetic biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Abdelrahaman YoussefSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.
Sadikshya RijalSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.ORCID 0000-0001-5213-7883
Rong ZhangSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.
Xiao-Jun TianSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.ORCID 0000-0002-5601-2057

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

In synthetic biology, a key goal is to design robust and stable genetic circuits with accurate and predictable behavior. Modularity is a central principle in circuit design, enabling the construction of complex systems from smaller, well-characterized parts. However, resource competition presents a major obstacle to modularity by disrupting gene expression dynamics. Here, we constructed and characterized a library of inhibitory genetic cascades with varied promoter strengths, RBS strengths, and plasmid backbones. We found that increasing the expression of the downstream module could unexpectedly lead to a reduction in the expression of the upstream regulatory module by competing for shared cellular resources. These results indicate that resource limitations can transform a unidirectional inhibitory cascade into an unintended feedback loop. In addition, we found that growth-mediated dilution can reshape gene expression patterns, further influencing circuit dynamics. Together, these findings underscore the critical roles of both resource competition and growth dilution in shaping the behavior of synthetic gene circuits.

Indexed as

Gene Regulatory NetworksGenes, SyntheticSynthetic BiologyEscherichia coliPlasmidsPromoter Regions, Geneticcircuit dynamicsgene expression couplinggrowth-mediated dilutionhost-circuit interactionsmodule interactionresource redistribution

Identifiers

PMID41457566
PMCPMC12786678

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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.