An efficient high throughput metabotyping platform for screening of biomass willows

Area of Science:

• Plant Science
• Metabolomics
• Biotechnology

Background:

• Improving woody biomass crops like willow and poplar is crucial for carbon sequestration and developing sustainable alternatives to petrochemicals.
• Selection for specific metabolic traits is key to enhancing biomass yield and carbon capture in these crops.

Purpose of the Study:

• To develop and optimize a robust metabotyping screen for willow (Salix) using 1D 1H-NMR-MS.
• To enable high-throughput screening of willow genetic collections for improved metabolic traits related to carbon sequestration.

Main Methods:

• Developed a protocol to overcome spectral alignment issues in 1D 1H-NMR-MS caused by pH variations and high organic acid/metal cation content.
• Normalized metabolic profiles from leaf and stem tissues to a constant weight of the soluble metabolome for statistical comparison.
• Created and applied a Salix metabolite spectral library with Chenomx software for automated quantification of 56 primary and secondary metabolites.

Main Results:

• Established a robust metabotyping method for willow, allowing direct comparison of metabolic profiles across different plant tissues and varieties.
• Demonstrated variation in metabolic fingerprints from the top to the bottom of willow plants.
• Achieved automated quantitative data extraction for a wide range of metabolites.

Conclusions:

• The optimized metabotyping screen and automated quantitation facilitate high-throughput screening of willow genetic collections.
• The method provides genotype- and tissue-specific data essential for future metabolic network modeling of carbon flow.
• This advancement supports the selection of willow varieties with enhanced carbon sequestration capabilities.