Evidence map›Paper›PMID 37854706›Full record

ArticlePNAS nexus2023

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs.

Muralikrishnan Gopalakrishnan Meena, Matthew J Lane, Joanna Tannous, Alyssa A Carrell, Paul E Abraham, Richard J Giannone, Jean-Michel Ané, Nancy P Keller, Jesse L Labbé, Armin G Geiger and 3 more

Abstract read
In one paragraph

Article in PNAS nexus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
  6. A Timeline of Biosynthetic Gene Cluster Discovery inJournal of fungi (Basel, Switzerland) · 2024
    Article
  7. 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

13 authors.

Muralikrishnan Gopalakrishnan MeenaNational Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0003-4048-4639
Matthew J LaneBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0002-7750-6822
Joanna TannousBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
Alyssa A CarrellBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
Paul E AbrahamBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0003-2685-9123
Richard J GiannoneBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0001-8551-0138
Jean-Michel AnéDepartment of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID https://orcid.org/0000-0002-3128-9439
Nancy P KellerDepartment of Bacteriology, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID https://orcid.org/0000-0002-4386-9473
Jesse L LabbéBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0003-0368-2054
Armin G GeigerBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0002-3606-452X
David KainerBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0001-7271-4676
Daniel A JacobsonBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0002-9822-8251
Tomás A RushBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.ORCID https://orcid.org/0000-0002-3207-1466

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen

Identifiers

PMID37854706
PMCPMC10581544

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.