Evidence map›Paper›PMID 41675503›Full record

ArticleQuantitative biology (Beijing, China)2025

Forging the iron-net: Towards a quantitative understanding of microbial communities via siderophore-mediated interactions.

Shaohua Gu, Jiqi Shao, Ruolin He, Guanyue Xiong, Zeyang Qu, Yuanzhe Shao, Linlong Yu, Di Zhang, Fanhao Wang, Ruichen Xu and 6 more

Abstract read
In one paragraph

Article in Quantitative biology (Beijing, China), 2025. 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. Article
  2. Article
  3. 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

16 authors.

Shaohua GuCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Jiqi ShaoCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Ruolin HeCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Guanyue XiongCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Zeyang QuCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Yuanzhe ShaoPeking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Linlong YuPeking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Di ZhangCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Fanhao WangCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.
Ruichen XuSchool of Life Sciences Shandong University Qingdao China.
Peng GuoSchool of Life Sciences Shandong University Qingdao China.
Ningbo XiJiangsu Provincial Key Laboratory for Organic Solid Waste Utilization Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization National Engineering Research Center for Organic-based Fertilizers Nanjing Agricultural University Nanjing China.
Yinxiang LiSchool of Physics Peking University Beijing China.
Yanzhao WuCollege of Computer Science and Technology (College of Data Science) Taiyuan University of Technology Taiyuan China.
Zhong WeiJiangsu Provincial Key Laboratory for Organic Solid Waste Utilization Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization National Engineering Research Center for Organic-based Fertilizers Nanjing Agricultural University Nanjing China.
Zhiyuan LiCenter for Quantitative Biology Academy for Advanced Interdisciplinary Studies Peking University Beijing China.ORCID https://orcid.org/0000-0001-6662-2636

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Iron is a critical yet limited nutrient for microbial growth. To scavenge iron, most microbes produce siderophores-diverse small molecules with high iron affinities. Different siderophores are specifically recognized and uptaken by corresponding recognizers, enabling targeted interventions and intriguing cheater-producer dynamics. We propose constructing a comprehensive iron interaction network, or "iron-net", across the microbial world. Such a network offers the potential for precise manipulation of the microbiota, with conceivable applications in medicine, agriculture, and industry as well as advancing microbial ecology and evolution theories. Previously, our successful construction of an iron-net in the

Indexed as

ecologyevolutioniron‐netmicrobial communitysiderophores

Identifiers

PMID41675503
PMCPMC12806101

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.