Evidence map›Paper›PMID 42308253›Full record

ArticlePloS one2026

Siderophore screening in marine sponge extracts using LC-HRMS and an R-based metabolomics workflow.

Alejandro García Ríos, Massuo Jorge Kato, Lydia Fumiko Yamaguchi, Breno Pannia Espósito, Ailan Farid Arenas-Soto

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Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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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.

Alejandro García RíosLaboratorio de Química Bioinorgánica y Metalofármacos, Instituto de Química, Universidade de São Paulo, Sao Paulo, Sao Paulo, Brasil.ORCID 0000-0002-0844-6977
Massuo Jorge KatoLaboratório de Química de Produtos Naturais, Instituto de Química, Universidade de São Paulo, Sao Paulo, Sao Paulo, Brasil.
Lydia Fumiko YamaguchiLaboratório de Química de Produtos Naturais, Instituto de Química, Universidade de São Paulo, Sao Paulo, Sao Paulo, Brasil.
Breno Pannia EspósitoLaboratorio de Química Bioinorgánica y Metalofármacos, Instituto de Química, Universidade de São Paulo, Sao Paulo, Sao Paulo, Brasil.
Ailan Farid Arenas-SotoGrupo de Investigación y Asesoría en Estadística, Universidad del Quindío, Armenia, Quindio, Colombia.ORCID 0000-0002-0331-5556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Siderophores are pivotal ‌‌iron-acquisition biomolecules integral to microbial survival, pathogenicity, and ecology. Elucidating these compounds offers critical insights into the microbial dynamics of marine holobionts and potential therapeutic applications. In this study, we present a culture-independent, data-centric strategy to annotate siderophores from the body mass of three marine sponge species: Dragmacidon reticulatum, Aplysina fulva, and Amphimedon viridis. Utilizing Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) coupled with a custom R-based analytical workflow (XCMS and MetaboAnnotation), we putatively annotated 59 siderophores. We employed a validation pipeline, utilizing iron-adduct calculations [M-2H + Fe]+, [M-H + Fe]2+, [2M-2H + Fe]+, mass accuracy thresholds (<3 ppm), retention time deviation (Coefficient of variation < 2%), and chromatograph peak analysis. According to the Metabolomics Standards Initiative (MSI), these annotations correspond to Level 2 (putatively annotated compounds) because they are based on accurate mass matching without chemical standard confirmation. Notably, iron supplementation during extraction did not significantly alter siderophore detection, suggesting constitutive production or environmental saturation. This workflow bypasses the limitations of traditional cultivation, revealing a diverse landscape of iron-chelating metabolites, including Ferricrocin, Aeruginic acid, and Madurastatin directly within the sponge's body.

Indexed as

MetabolomicsPoriferaSiderophoresAnimalsChromatography, LiquidLiquid Chromatography-Mass SpectrometryMass SpectrometryWorkflowSiderophores

Identifiers

PMID42308253
PMCPMC13274820

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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.