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Integrative multi-scale physiological, metabolic, and proteomic reprogramming in tomato under polyethylene microplastic stress
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Researchers grew tomatoes in soil amended with 1% or 5% polyethylene microplastics for 48 days and found dose-dependent physiological disruption — low exposure transiently boosted shoot growth, while high exposure suppressed root elongation and triggered oxidative stress, hormonal imbalance, and proteomic shifts across 103 differentially expressed proteins linked to redox regulation and amino acid metabolism.
Microplastic (MP) contamination in agricultural soils is an emerging environmental hazard with poorly understood impacts on crops. Here, we investigated concentration-dependent effects of polyethylene MPs on tomato (Solanum lycopersicum L.) by integrating physiological, biochemical, and proteomic responses under realistic soil conditions. Plants were grown for 48 days in soils amended with 0%, 1%, or 5% (w/w) MPs. Growth performance, chlorophyll content, oxidative stress markers, amino acid profiles, phytohormone levels, and root proteomes were assessed. Low MP exposure (1%) transiently enhanced shoot elongation and chlorophyll accumulation, whereas high exposure (5%) inhibited root elongation and reduced pigment levels. Roots showed progressive oxidative stress, with increased hydrogen peroxide and activation of superoxide dismutase and catalase. Amino acid profiling revealed organ- and dose-specific changes: sulfur-containing and aromatic residues accumulated in leaves at 1%, while methionine, proline, and arginine increased in roots at 5%. Hormonal balance was perturbed across tissues, particularly involving abscisic acid, salicylic acid, and indole-3-acetic acid. Proteomic analysis identified 103 differentially expressed proteins linked to amino acid metabolism, redox regulation, and hormone signaling, showing distinct patterns between low and high exposures. Collectively, these findings demonstrate that polyethylene MPs induce multi-scale, dose-dependent reprogramming in tomato, ranging from transient adaptive shifts to systemic disruption, and highlight potential molecular biomarkers for agroecosystem risk assessment.
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