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Enhancing microbial predator-prey detection with network and trait-based analyses
Indexado
WoS WOS:001414687600006
Scopus SCOPUS_ID:85218032180
DOI 10.1186/S40168-025-02035-8
Año 2025
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



BackgroundNetwork analyses are often applied to microbial communities using sequencing survey datasets. However, associations in such networks do not necessarily indicate actual biotic interactions, and even if they do, the nature of the interactions commonly remains unclear. While network analyses are valuable for generating hypotheses, the inferred hypotheses are rarely experimentally confirmed.ResultsWe employed cross-kingdom network analyses, applied trait-based functions to the microorganisms, and subsequently experimentally investigated the found putative predator-prey interactions to evaluate whether, and to what extent, correlations indicate actual predator-prey relationships. For this, we investigated algae and their protistan predators in biocrusts of three distinct polar regions, i.e., Svalbard, the Antarctic Peninsula, and Continental Antarctica. Network analyses using FlashWeave indicated that 89, 138, and 51 correlations occurred between predatory protists and algae, respectively. However, trait assignment revealed that only 4.7-9.3% of said correlations link predators to actually suitable prey. We further confirmed these results with HMSC modeling, which resulted in similar numbers of 7.5% and 4.8% linking predators to suitable prey for full co-occurrence and abundance models, respectively. The combination of network analyses and trait assignment increased confidence in the prediction of predator-prey interactions, as we show that 82% of all experimentally investigated correlations could be verified. Furthermore, we found that more vicious predators, i.e., predators with the highest growth rate in co-culture with their prey, exhibit higher stress and betweenness centrality - giving rise to the future possibility of determining important predators from their network statistics.ConclusionsOur results support the idea of using network analyses for inferring predator-prey interactions, but at the same time call for cautionary consideration of the results, by combining them with trait-based approaches to increase confidence in the prediction of biological interactions.FNXjBTWygxbKv-5R-GHg3pVideo AbstractConclusionsOur results support the idea of using network analyses for inferring predator-prey interactions, but at the same time call for cautionary consideration of the results, by combining them with trait-based approaches to increase confidence in the prediction of biological interactions.FNXjBTWygxbKv-5R-GHg3pVideo Abstract

Revista



Revista ISSN
Microbiome 2049-2618

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Disciplinas de Investigación



WOS
Microbiology
Scopus
Sin Disciplinas
SciELO
Sin Disciplinas

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Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



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Autores - Afiliación



Ord. Autor Género Institución - País
1 Rendon, Cristina Martinez - Univ Cologne - Alemania
Universität zu Köln - Alemania
1 Martínez Rendón, Cristina - Universität zu Köln - Alemania
Univ Cologne - Alemania
2 Braun, Christina - Friedrich Schiller Univ Jena - Alemania
Friedrich-Schiller-Universitat Jena - Alemania
3 Kappelsberger, Maria - Tech Univ Dresden - Alemania
TECHNISCHE UNIVERSITAT DRESDEN - Alemania
4 Boy, Jens - Leibniz Univ Hannover - Alemania
Gottfried Wilhelm Leibniz Universität Hannover - Alemania
5 Casanova-Katny, Angelica - Universidad Católica de Temuco - Chile
6 Glaser, Karin - TU Bergakademie Freiberg - Alemania
Technische Universität Bergakademie Freiberg - Alemania
7 Dumack, Kenneth - Univ Cologne - Alemania
Universität zu Köln - Alemania

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Financiamiento



Fuente
Deutsche Forschungsgemeinschaft
Deutsche Forschungsgemeinschaft (DFG)
Projekt DEAL

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Agradecimientos



Agradecimiento
Open Access funding enabled and organized by Projekt DEAL. This work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the priority program SPP 1158 "Antarctic Research with comparative investigations in Arctic ice areas" by the following grant number: 443133824.
Open Access funding enabled and organized by Projekt DEAL. Open Access funding enabled and organized by Projekt DEAL. This work was supported by the Deutsche Forschungsgemeinschaft (DFG) in the framework of the priority program SPP 1158 \u201CAntarctic Research with comparative investigations in Arctic ice areas\u201D by the following grant number: 443133824.

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