Evidence map›Paper›PMID 41400283›Full record

ArticleJournal of experimental botany2026

Streamlining the isolation of fungal hyphae: a semi-automated approach for soil substrates.

Isabelle Elisabeth Metzen, Marcel Bucher

Abstract read
In one paragraph

Article in Journal of experimental botany, 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

2 authors.

Isabelle Elisabeth MetzenInstitute for Plant Sciences, Cologne Biocenter, University of Cologne, Zuelpicher Straße 47b, D-50674 Cologne, Germany.ORCID 0000-0001-6147-5796
Marcel BucherInstitute for Plant Sciences, Cologne Biocenter, University of Cologne, Zuelpicher Straße 47b, D-50674 Cologne, Germany.ORCID 0000-0003-1680-9413

Funding

Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
6 · The paper itself

Abstract

Extracting fungal hyphae with their naturally associated microbiota from soil samples presents a significant challenge due to their small size, typically in the micrometer range, and the formation of dynamic fungal networks. We combined elements of previous protocols and automated the wet-sieving steps of the methodology to efficiently extract fungal hyphae from various soil types, including natural loamy soils. This approach reduces manual handling, minimizes operator-dependent variability, and shortens processing time by up to 2.5-fold. Unlike earlier methods that require sand or glass bead supplementation, which can introduce artificial conditions and limit large-scale field applications, our sieving and sucrose centrifugation (SSC) method avoids these drawbacks. The SSC technique both enables quantification of hyphal length density (HLD) and, importantly, preserves surface-associated microbes for downstream analyses. Among the tested methods, SSC yielded the highest HLD. Using a combination of microscopy, molecular techniques, and next-generation sequencing (NGS), we demonstrate that this method allows targeted study of bacteria tightly attached to fungal hyphae. Furthermore, the SSC approach effectively enriched fungal hyphae from a highly diverse soil community, establishing a dependable tool for advancing research on fungal hyphae as microbial hotspots in soil ecosystems.

Indexed as

FungiHyphaeSoil MicrobiologyCentrifugationSoilSoilHyphal length densityhyphoplanehyphoplane microbiomehyphospheremicrobe–microbe interactionsoptimization of fungal hyphae isolationsieving and sucrose centrifugationsoil microbial communities

Identifiers

PMID41400283
PMCPMC13462798

What OpenQuestion holds

Textmetadata
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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.