Mechanisms of metabolic adaptation in the duckweed Lemna gibba: an integrated metabolic, transcriptomic and flux analysis.

Duckweeds Lemna gibba Metabolic flux analysis Metabolome analysis Transcriptome analysis

Journal

BMC plant biology
ISSN: 1471-2229
Titre abrégé: BMC Plant Biol
Pays: England
ID NLM: 100967807

Informations de publication

Date de publication:
03 Oct 2023
Historique:
received: 08 05 2023
accepted: 20 09 2023
medline: 5 10 2023
pubmed: 4 10 2023
entrez: 3 10 2023
Statut: epublish

Résumé

Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.

Sections du résumé

BACKGROUND BACKGROUND
Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions.
RESULTS RESULTS
To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by
CONCLUSIONS CONCLUSIONS
Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.

Identifiants

pubmed: 37789269
doi: 10.1186/s12870-023-04480-9
pii: 10.1186/s12870-023-04480-9
pmc: PMC10546790
doi:

Substances chimiques

Glutamine 0RH81L854J
Nitrates 0
Nitrogen N762921K75

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

458

Subventions

Organisme : U.S. Department of Energy
ID : DE-SC0018244
Organisme : U.S. Department of Energy
ID : DE-SC0018244
Organisme : U.S. Department of Energy
ID : DE-SC0012704
Organisme : U.S. Department of Energy
ID : DE-SC0018244
Organisme : U.S. Department of Energy
ID : DE-SC0018244
Organisme : U.S. Department of Energy
ID : DE-SC0018244

Informations de copyright

© 2023. BioMed Central Ltd., part of Springer Nature.

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Auteurs

Hai Shi (H)

Biology Department, Brookhaven National Laboratory, Upton, NY, 11973, USA.

Evan Ernst (E)

Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY, 11724, USA.
Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY, 11724, USA.

Nicolas Heinzel (N)

Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research, D-06466, Seeland OT Gatersleben, Germany.

Sean McCorkle (S)

Brookhaven National Laboratory, Computational Science Initiative, Upton, NY, 11973, USA.

Hardy Rolletschek (H)

Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research, D-06466, Seeland OT Gatersleben, Germany.

Ljudmilla Borisjuk (L)

Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research, D-06466, Seeland OT Gatersleben, Germany.

Stefan Ortleb (S)

Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research, D-06466, Seeland OT Gatersleben, Germany.

Robert Martienssen (R)

Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY, 11724, USA.
Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY, 11724, USA.

John Shanklin (J)

Biology Department, Brookhaven National Laboratory, Upton, NY, 11973, USA.

Jorg Schwender (J)

Biology Department, Brookhaven National Laboratory, Upton, NY, 11973, USA. schwend@bnl.gov.

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