Evidence map›Paper›PMID 38166159›Full record

ArticleACS synthetic biology2024

Modularized Design and Construction of Tunable Microbial Consortia with Flexible Topologies.

Xingwen Chen, Changhan He, Qi Zhang, Samat Bayakmetov, Xiao Wang

Abstract read
In one paragraph

Article in ACS synthetic biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Article
  3. Microbial biotechnology meets ecological theory: a unified framework to design industrial microbial consortia.International microbiology : the official journal of the Spanish Society for Microbiology · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Review
  8. 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

5 authors.

Xingwen ChenSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0009-0005-5992-8326
Changhan HeDepartment of Mathematics, University of California Irvine, Irvine, California 92697, United States.
Qi ZhangSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Samat BayakmetovSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States.
Xiao WangSchool of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States.ORCID 0000-0002-4056-0155

Funding

Predictive Modeling of Pattern Formation Driven by Synthetic Gene NetworksR01GM131405 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI KUANG, YANG · 2018 to 2021
$1.5M
Model-guided design of RNA stabilizing elements for improved coronavirus diagnosticsR01EB031893 · NIBIB · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI GREEN, ALEXANDER ARTHUR, WANG, XIAO · 2021 to 2022
$1.3M
NIBIB NIH HHS R01 EB031893NIGMS NIH HHS R01 GM131405
6 · The paper itself

Abstract

Complex and fluid bacterial community compositions are critical to diversity, stability, and function. However, quantitative and mechanistic descriptions of the dynamics of such compositions are still lacking. Here, we develop a modularized design framework that allows for bottom-up construction and the study of synthetic bacterial consortia with different topologies. We showcase the microbial consortia design and building process by constructing amensalism and competition consortia using only genetic circuit modules to engineer different strains to form the community. Functions of modules and hosting strains are validated and quantified to calibrate dynamic parameters, which are then directly fed into a full mechanistic model to accurately predict consortia composition dynamics for both amensalism and competition without further fitting. More importantly, such quantitative understanding successfully identifies the experimental conditions to achieve coexistence composition dynamics. These results illustrate the process of both computationally and experimentally building up bacteria consortia complexity and hence achieve robust control of such fluid systems.

Indexed as

BacteriaMicrobial Consortiaamensalismbacterial growthcompetitionmicrobial consortiamicrobial ecology

Identifiers

PMID38166159
PMCPMC10805104

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.