Evidence map›Paper›PMID 42012223›Full record

ArticlemSystems2026

Navigating complexity: key considerations for studying fungal-bacterial interactions.

Gaëtan Martin, Giovana S Slanzon, Ishwora Dhungana, Rishi R Prasadh, Caio César Pires de Paula, Nhu H Nguyen

Abstract read
In one paragraph

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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Gaëtan Martin *Department of Tropical Plant and Soil Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.
Giovana S Slanzon *Department of Tropical Plant and Soil Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.ORCID 0000-0002-3629-8844
Ishwora DhunganaDepartment of Tropical Plant and Soil Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.
Rishi R PrasadhDepartment of Tropical Plant and Soil Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.
Caio César Pires de PaulaDepartment of Ecosystem Biology, Faculty of Science, University of South Bohemia, České Budĕjovice, Czech Republic.
Nhu H NguyenDepartment of Tropical Plant and Soil Sciences, University of Hawai'i at Mānoa, Honolulu, Hawaii, USA.ORCID 0000-0001-8276-7042

Funding

NIH HHS 1R01GM163239U.S. Department of Energy DE-SC0023106
6 · The paper itself

Abstract

Fungal-bacterial interactions are widespread phenomena that are currently gaining attention across diverse research fields. But what are interactions, how do we identify them, and why should we adopt ecological theory when studying them? While microbial interactions are often conceptualized and characterized as static properties, these relationships are dynamic and complex. They are shaped by the interplay of numerous variables, which themselves fluctuate over space and time, that scale from molecules to ecosystems. In this perspective, we discuss the theoretical and practical challenges of studying the interactions between these two ubiquitous and diverse groups of microorganisms and propose a framework grounded on mechanistic and systems approaches rather than relying on correlations or fragmented practices. We hope to inspire efforts to build and integrate a more comprehensive understanding of this fascinating and quickly growing subdiscipline of microbial ecology.

Indexed as

BacteriaBacterial Physiological PhenomenaFungiMicrobial Interactionsbacterial-fungal interactionsBFIcross-domaincross-kingdominteraction phasesinteractionsmicrobial theory

Identifiers

PMID42012223
PMCPMC13185628

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.