Evidence map›Paper›PMID 41925715›Full record

ArticleMicrobial genomics2026

Systematic characterization of PBP2 as the primary siderophore recognizer in

Linlong Yu, Guanyue Xiong, Zhiyuan Li

Abstract read
In one paragraph

Article in Microbial genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Linlong YuPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China.
Guanyue XiongCenter for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China.
Zhiyuan LiPeking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Iron is a scarce yet essential nutrient for bacteria. Microbes often acquire iron by secreting siderophores, a diverse group of small molecules that form high-affinity complexes with iron for microbial uptake. Understanding microbial iron interaction networks requires detailed characterization of siderophore recognition specificity. In Gram-positive bacteria, substrate-binding proteins (SBPs) bind iron-siderophore complexes and deliver them to ABC transporters for import. However, the SBPs responsible for selective recognition remain poorly characterized, hindering large-scale data mining and network reconstruction. Here, we addressed this knowledge gap by systematically analysing siderophore uptake systems, first in five representative genera and then across a comprehensive dataset of 16,232 Gram-positive bacterial genomes. Through a pipeline integrating genome mining, coevolutionary analysis and structural modelling, we established PBP2 (Peripla_BP_2) subtype SBPs as the primary siderophore recognizer family. We revealed that, unlike the physically clustered systems in Gram-negative bacteria, synthetase and recognizer genes in Gram-positive bacteria are sometimes genomically decoupled, yet display coordinated transcriptional regulation by iron-responsive transcription factors. Our findings underscore key differences between Gram-positive and Gram-negative iron acquisition systems, providing foundational knowledge for large-scale inference of siderophore-mediated microbial interactions.

Indexed as

ActinobacteriaBacterial ProteinsGram-Positive BacteriaSiderophoresGenome, BacterialIronPhylogenyBacterial ProteinsIronSiderophoresActinomycetesGram-positive bacteriairon acquisitionsiderophoresubstrate-binding protein

Identifiers

PMID41925715
PMCPMC13293324

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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.