Endophyte-induced systemic spatial reprogramming of metabolism in Populus trichocarpa roots under drought
Jayde Aufrecht1, Dušan Veličković1, Robert Tournay2
1Environmental Molecular Sciences Laboratory (EMSL), Pacific Northwest National Laboratory (PNNL), Richland, 99352, WA, USA.
The New Phytologist
|May 12, 2026
Summary
Beneficial endophytes alter plant metabolism, but how these changes scale up was unknown. This study used chemical imaging and machine learning to map these metabolic shifts in Populus trichocarpa roots, revealing cell-type specific changes.
Area of Science:
- Plant biology
- Microbiology
- Metabolomics
Background:
- Beneficial endophytes enhance plant resilience in stressful conditions by modifying host metabolism.
- The propagation of cellular metabolic alterations to a systems biology scale by endophytes remains poorly understood.
Purpose of the Study:
- To investigate how beneficial endophytes impact plant metabolism at the root-zone and cell-type levels.
- To identify specific root metabolites and exudates that correlate with endophyte treatment using machine learning.
Main Methods:
- Utilized high-resolution chemical imaging to map metabolic profiles in Populus trichocarpa roots.
- Employed machine learning models to analyze spatial metabolomics data and identify predictive metabolites.
- Quantified endophyte abundance in root tissues.
Main Results:
- A nine-strain endophyte consortium induced distinct metabolic changes in droughted root tissues, varying by cell type and root zone.
- Endophyte abundance correlated significantly with specific metabolite levels.
- Spatial metabolomics combined with machine learning successfully identified localized metabolic patterns.
Conclusions:
- Spatial metabolomics and machine learning provide powerful tools for dissecting plant-microbe metabolic interactions.
- Endophyte-induced metabolic alterations are localized and cell-type specific.
- This approach can generate new hypotheses regarding the mechanisms of endophyte-mediated plant benefits.
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