Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves.

Anne E Harman-Ware, Madhavi Z Martin, Nancy L Engle, Crissa Doeppke, Timothy J Tschaplinski

Abstract read

In one paragraph

Article in Biotechnology for biofuels and bioproducts, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Anne E Harman-Ware *Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA. anne.ware@nrel.gov.

Madhavi Z MartinBiosciences Division, Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.

Nancy L Engle *Biosciences Division, Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.

Crissa DoeppkeRenewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory, Golden, CO, 80401, USA.

Timothy J Tschaplinski *Biosciences Division, Center for Bioenergy Innovation, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.

Funding

Office of Energy Efficiency and Renewable Energy DE-AC36-08GO28308Office of Science Center for Bioenergy InnovationU.S. Department of Energy DE-AC05-00OR22725

6 · The paper itself

Abstract

backgroundHigh-throughput metabolomics analytical methodology is needed for population-scale studies of bioenergy-relevant feedstocks such as poplar (Populus sp.). Here, the authors report the relative abundance of extractable aromatic metabolites in Populus trichocarpa leaves rapidly estimated using pyrolysis-molecular beam mass spectrometry (py-MBMS). Poplar leaves were analyzed in conjunction with and validated by GC/MS analysis of extracts to determine key spectral features used to build PLS models to predict the relative composition of extractable aromatic metabolites in whole poplar leaves.

resultsThe Pearson correlation coefficient for the relative abundance of extractable aromatic metabolites based on ranking between GC/MS analysis and py-MBMS analysis of the Boardman leaf set was 0.86 with R

conclusionsThe simplified py-MBMS method is capable of rapidly screening leaf tissue for relative abundance of extractable aromatic secondary metabolites to enable prioritization of samples in large populations requiring comprehensive metabolomics that will ultimately inform plant systems biology models and advance the development of optimized biomass feedstocks for renewable fuels and chemicals.

Indexed as

High-throughput analysisMetabolomicsPopulus trichocarpaPyrolysis-molecular beam mass spectrometry

Identifiers

PMID36899393

DOI10.1186/s13068-023-02287-2

PMCPMC9999501

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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.