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Integrative multi-scale physiological, metabolic, and proteomic reprogramming in tomato under polyethylene
Young Sang Kwon1, Seung-Min Lee2, Yeong-Jin Kim2
1Center for National Toxicology AI and Data, Korea Institute of Toxicology, Daejeon 34114, Republic of Korea; Center for Environmental Safety Research, Division of Gyeongnam Bio-Environmental Research, Korea Institute of Toxicology, Jinju 52834, Republic of Korea.
Polyethylene microplastics (MPs) impact tomato plants differently based on concentration. Low MP levels may offer transient benefits, while high levels cause significant growth inhibition and stress, indicating dose-dependent effects on crops.
Area of Science:
- Environmental Science
- Plant Biology
- Toxicology
Background:
- Microplastic (MP) contamination is an emerging threat to agricultural soils.
- The effects of MPs on crop physiology and molecular responses are not well understood.
Purpose of the Study:
- To investigate the concentration-dependent effects of polyethylene MPs on tomato plants (Solanum lycopersicum L.).
- To integrate physiological, biochemical, and proteomic responses to assess MP impacts under realistic soil conditions.
Main Methods:
- Tomato plants were grown in soils with 0%, 1%, or 5% (w/w) polyethylene MPs for 48 days.
- Assessed growth, chlorophyll, oxidative stress, amino acids, phytohormones, and root proteomes.
- Utilized physiological, biochemical, and proteomic analyses.
Main Results:
- Low MP exposure (1%) transiently enhanced shoot growth and chlorophyll; high exposure (5%) inhibited root growth and reduced pigments.
- Progressive oxidative stress was observed in roots, with increased H2O2 and activated antioxidant enzymes (SOD, catalase).
- Dose-dependent, organ-specific changes in amino acid profiles and phytohormone levels (ABA, SA, IAA) were detected. Proteomic analysis revealed 103 differentially expressed proteins related to metabolism and signaling.
Conclusions:
- Polyethylene MPs induce multi-scale, dose-dependent reprogramming in tomato plants.
- Responses range from transient adaptive shifts to systemic disruption, highlighting potential molecular biomarkers for agroecosystem risk assessment.
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