Evidence map›Paper›PMID 33680356›Full record

ArticleComputational and structural biotechnology journal2021

Maize specialized metabolome networks reveal organ-preferential mixed glycosides.

Sandrien Desmet, Yvan Saeys, Kevin Verstaen, Rebecca Dauwe, Hoon Kim, Claudiu Niculaes, Atsushi Fukushima, Geert Goeminne, Ruben Vanholme, John Ralph and 2 more

Open access · goldAbstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

8 citing papers in PubMed, 19 citations in OpenAlex.

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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

12 authors at 6 institutions in 5 countries.

Sandrien DesmetDepartment of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Gent, Belgium.
Yvan SaeysDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, B-9052 Gent, Belgium.
Kevin VerstaenData Mining and Modelling for Biomedicine, Center for Inflammation Research, VIB, B-9052 Gent, Belgium.
Rebecca DauweUnité de Recherche BIOPI EA3900, Université de Picardie Jules Verne, 80000 Amiens, France.
Hoon KimDepartment of Biochemistry and the U.S. Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin, Madison, WI 53726, United States.
Claudiu NiculaesPlant Breeding, TUM School of Life Sciences Weihenstephan, Technical University of Munich, 85354 Freising, Germany.
Atsushi FukushimaRIKEN Center for Sustainable Resource Science, Yokohama, Kanagawa 230-0045, Japan.
Geert GoeminneDepartment of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Gent, Belgium.
Ruben VanholmeDepartment of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Gent, Belgium.
John RalphDepartment of Biochemistry and the U.S. Department of Energy Great Lakes Bioenergy Research Center, Wisconsin Energy Institute, University of Wisconsin, Madison, WI 53726, United States.
Wout BoerjanDepartment of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Gent, Belgium.
Kris MorreelDepartment of Plant Biotechnology and Bioinformatics, Ghent University, B-9052 Gent, Belgium.
Ghent University · BEUniversity of Wisconsin–Madison · USBiologie des Plantes et Innovation · FRRIKEN Center for Sustainable Resource Science · JPTechnical University of Munich · DEVIB-UGent Center for Inflammation Research · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the scientific and economic importance of maize, little is known about its specialized metabolism. Here, five maize organs were profiled using different reversed-phase liquid chromatography-mass spectrometry methods. The resulting spectral metadata, combined with candidate substrate-product pair (CSPP) networks, allowed the structural characterization of 427 of the 5,420 profiled compounds, including phenylpropanoids, flavonoids, benzoxazinoids, and auxin-related compounds, among others. Only 75 of the 427 compounds were already described in maize. Analysis of the CSPP networks showed that phenylpropanoids are present in all organs, whereas other metabolic classes are rather organ-enriched. Frequently occurring CSPP mass differences often corresponded with glycosyl- and acyltransferase reactions. The interplay of glycosylations and acylations yields a wide variety of mixed glycosides, bearing substructures corresponding to the different biochemical classes. For example, in the tassel, many phenylpropanoid and flavonoid-bearing glycosides also contain auxin-derived moieties. The characterized compounds and mass differences are an important step forward in metabolic pathway discovery and systems biology research. The spectral metadata of the 5,420 compounds is publicly available (DynLib spectral database, https://bioit3.irc.ugent.be/dynlib/).

Indexed as

Mass spectrometrySpecialized metabolismSpectral metadata analysisZea mays

Identifiers

PMID33680356
PMCPMC7890092
OpenAlexW3121333313

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.