# Hormone-Specific Reprogramming of the Phenylpropanoid Network in Juvenile Quercus sideroxyla Leaves Revealed by Targeted Metabolomics

## TL;DR

This study shows how different plant hormones trigger unique changes in the phenolic metabolism of oak leaves over time.

## Contribution

The study reveals hormone-specific and time-dependent reprogramming of phenolic metabolism in a woody species using targeted metabolomics.

## Key findings

- SA caused a pulsatile response in phenolic acids and ellagic-related structures.
- JA led to a sustained modulation of flavonoids and tannins with specific markers.
- ABA promoted stabilized accumulation across phenolic classes, indicating metabolic homeostasis.

## Abstract

Phytohormones are key regulators of specialized metabolism, yet hormone-specific and time-dependent phenolic reprogramming in woody species remains poorly resolved. This study evaluated the phenolic responses of juvenile Quercus sideroxyla leaves grown under controlled greenhouse conditions to salicylic acid (SA), jasmonic acid (JA), and abscisic acid (ABA) using a pulse-based elicitation design combined with targeted metabolite profiling. Aqueous acetone extracts exhibited high phenolic diversity, including phenolic acids (20 compounds), flavonoids (15 compounds), and hydrolyzable tannins (27 compounds). Partial least squares–discriminant analysis (PLS-DA), multivariate statistics (MANOVA), and Random Forest classification were employed to resolve hormone-specific phenolic signatures across time. Distinct regulatory trajectories were identified for each hormone. SA elicitation triggered a high-amplitude, pulsatile phenolic response primarily affecting precursor-associated phenolic acids and ellagic-related structures, consistent with transient metabolic priming. JA induced a gradual and sustained modulation of flavonoids and tannin pools, within which advanced caffeoylquinic esters, flavonol conjugates, and ellagitannins emerged as key discriminant markers. ABA treatment promoted progressive and stabilized accumulation across phenolic classes, supporting a role in metabolic homeostasis rather than stress induction. Biweekly sampling was essential to discriminate transient, adaptive, and stabilizing responses. Overall, the results demonstrate that Q. sideroxyla differentiates hormonal signals and translates them into distinct phenolic reprogramming patterns. The integration of time-resolved metabolomics with multivariate and machine-learning approaches provides a robust framework for hormone-guided modulation of phenolic metabolism in woody plants.