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bioRxiv · 10.1101/2025.10.30.685699

Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy

Abstract

Although modern mass spectrometry (MS) based proteomics has been broadly employed by the plant science community, proteomics analysis of plant tissues remains highly challenging to general plant biology laboratories, mainly due to the lack of effective and easily adaptable strategies that can process plant samples for MS analysis rapidly and reliably. Existing methods often involves lengthy mechanical disruption and protein extraction, which not only require large starting materials but also can cause significant variations, compromising quantitation accuracy. Here, we present an "in-cell proteomics" strategy and benchmark its performance against conventional processing methods using several model plants, including Arabidopsis thaliana, Nicotiana benthamiana, Zea mays and Sorghum bicolor. The comprehensive datasets from this study indicate that the on-filter in-cell (OFIC) processing-based "in-cell proteomics" strategy can eliminate cell lysis of plant leaves and pollen grains, and process proteins directly, enabling the identification of 9,000 to 12,000 proteins from leaves, and 7,000 to 9,000 proteins from pollen grains using one-shot LCMS. The OFIC strategy demonstrated broadly equivalent or better performance over conventional approaches in the context of simplicity, speed, digestion effectiveness, and quantitation accuracy. Applying the strategy to investigate plant leaf infection of N. benthamiana leaves revealed interesting signature proteins that respond differentially to host-adapted Colletotrichum destructivum and nonhost-adapted Colletotrichum sublineola fungus. The single-vessel approach bypasses cell disruption, substantially simplifying plant sample preparation while reducing the required sample input and enhancing proteomic sensitivity. It offered a generalizable approach to study plant leaf infection and other significant questions in plant biology and beyond.

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BibTeXRIS

Adekanye, D., Kusuru, M., Caplan, J. L., Yu, Y.. 2025-10-31. Toward simple, rapid, and deep plant proteome analysis with an in-cell proteomics strategy. https://doi.org/10.1101/2025.10.30.685699

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