Pulse Brain · Growing Health Evidence Index
Tier 3 — Observational / field trialConference paper

Plant nutritional and metabolic responses to drought and elevated CO <sub>2</sub> revealed by machine learning-enabled non-targeted metabolomics

Hsin-Fang Chang, Theresa Caso‐McHugh, David L. Des Marais

bioRxiv (Cold Spring Harbor Laboratory) · 2025

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Summary

This controlled study integrated plant physiology, transcriptomics, and machine learning-enabled metabolomics to elucidate how elevated atmospheric CO₂ and drought stress interact to reshape nutrient dynamics in a model cereal crop. The findings demonstrate that CO₂ and water availability have tissue-specific, stress-dependent effects on crop nutrient composition—notably impairing nitrogen status whilst selectively enhancing iron accumulation in shoots during drought—with potential implications for breeding and agronomic management under climate change.

UK applicability

As the United Kingdom experiences projected increases in summer drought frequency and atmospheric CO₂, these mechanistic insights into how cereals partition nutrients under combined stresses are relevant to UK cereal breeding and nitrogen management strategy. However, findings from Brachypodium (a model species with simplified genetics) will require validation in commercial wheat and barley cultivars under field conditions before direct agronomic recommendations can be made.

Key measures

Plant elemental composition (ionome), non-targeted metabolomics, transcriptomics, nitrogen uptake (nitrate vs. ammonium), iron partitioning, sphingolipid accumulation in shoots and roots

Outcomes reported

The study measured plant elemental composition, metabolomic profiles, and transcript expression in Brachypodium distachyon under factorial combinations of ambient/elevated CO₂ and well-watered/drought conditions. Results revealed differential impacts on nutrient status, nitrogen uptake, iron partitioning, and sphingolipid accumulation across plant tissues.

Theme
Climate & resilience
Subject
Crop nutrient density & mineral composition
Study type
Research
Study design
Controlled factorial experiment
Source type
Conference paper
Status
Preprint
System type
Laboratory / in vitro
DOI
10.1101/2025.01.02.631073
Catalogue ID
SNmov5i0e3-77xuq6

Topic tags

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