Evidence map›Paper›PMID 31992195›Full record

ArticleBMC plant biology2020

Exploring the metabolomic diversity of plant species across spatial (leaf and stem) components and phylogenic groups.

Sunmin Lee, Dong-Gu Oh, Digar Singh, Jong Seok Lee, Sarah Lee, Choong Hwan Lee

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
4.2field-weighted citation impact, top 4% 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

35 citing papers in PubMed, 79 citations in OpenAlex.

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  18. Anti-inflammatory effects ofToxicological research · 2023
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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

6 authors at 2 institutions in 1 country.

Sunmin LeeDepartment of Bioscience and Biotechnology, Konkuk University, Seoul, 143-701, Korea.
Dong-Gu OhDepartment of Bioscience and Biotechnology, Konkuk University, Seoul, 143-701, Korea.
Digar SinghDepartment of Bioscience and Biotechnology, Konkuk University, Seoul, 143-701, Korea.
Jong Seok LeeNational Institute of Biological Resources, Environmental Research Complex, Incheon, 22755, Korea.
Sarah LeeNational Institute of Biological Resources, Environmental Research Complex, Incheon, 22755, Korea. lsr57@korea.kr.
Choong Hwan LeeDepartment of Bioscience and Biotechnology, Konkuk University, Seoul, 143-701, Korea. chlee123@konkuk.ac.kr.
Konkuk University · KRNational Institute of Biological Resources · KR

Funding

Konkuk University (KR) 2017Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries 318027-04-1-HD030National Institute of Biological Resources NIBR201916101
6 · The paper itself

Abstract

backgroundPlants have been used as an important source of indispensable bioactive compounds in various cosmetics, foods, and medicines. However, the subsequent functional annotation of these compounds seems arduous because of the largely uncharacterized, vast metabolic repertoire of plant species with known biological phenotypes. Hence, a rapid multi-parallel screening and characterization approach is needed for plant functional metabolites.

resultsFifty-one species representing three plant families, namely Asteraceae, Fabaceae, and Rosaceae, were subjected to metabolite profiling using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) and ultrahigh-performance liquid chromatography quadrupole orbitrap ion trap tandem mass spectrometry (UHPLC-Q-orbitrap-MS/MS) as well as multivariate analyses. Partial least squares discriminant analysis (PLS-DA) of the metabolite profiling datasets indicated a distinct clustered pattern for 51 species depending on plant parts (leaves and stems) and relative phylogeny. Examination of their relative metabolite contents showed that the extracts from Fabaceae plants were abundant in amino acids, fatty acids, and genistein compounds. However, the extracts from Rosaceae had higher levels of catechin and ellagic acid derivatives, whereas those from Asteraceae were higher in kaempferol derivatives and organic acids. Regardless of the different families, aromatic amino acids, branch chain amino acids, chlorogenic acid, flavonoids, and phenylpropanoids related to the shikimate pathway were abundant in leaves. Alternatively, certain amino acids (proline, lysine, and arginine) as well as fatty acids levels were higher in stem extracts. Further, we investigated the associated phenotypes, i.e., antioxidant activities, affected by the observed spatial (leaves and stem) and intra-family metabolomic disparity in the plant extracts. Pearson's correlation analysis indicated that ellagic acid, mannitol, catechin, epicatechin, and quercetin derivatives were positively correlated with antioxidant phenotypes, whereas eriodictyol was positively correlated with tyrosinase inhibition activity.

conclusionsThis work suggests that metabolite profiling, including multi-parallel approaches and integrated bioassays, may help the expeditious characterization of plant-derived metabolites while simultaneously unraveling their chemodiversity.

Indexed as

MetabolomeAmino AcidsAntioxidantsAsteraceaeChromatography, High Pressure LiquidChromatography, LiquidFabaceaeFatty AcidsFlavonoidsGas Chromatography-Mass SpectrometryMetabolic Networks and PathwaysMetabolomicsMonophenol MonooxygenasePlant ExtractsPlant LeavesPlant StemsAmino AcidsAntioxidantsFatty AcidsFlavonoidsMonophenol MonooxygenasePlant ExtractsAntioxidant activityChemodiversityMetabolite profilingPlant partsTyrosinase inhibition activity

Identifiers

PMID31992195
PMCPMC6986006
OpenAlexW3006452563

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LicenceCC BY
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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.