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MAcro Plant Projection Imaging (MAPPI): An open, scalable platform for whole-plant fluorescence real-time imaging

Science Advances · 23 Jan 2026 · 10.1126/sciadv.aea4466

Abstract

Understanding how plants perceive and respond to environmental and developmental cues requires tools capable of monitoring molecular signals in vivo, across whole tissues, and in real time. Genetically encoded fluorescent indicators, coupled with fluorescence microscopy, have transformed plant biology, but their application remains largely confined to small model organisms and specialized microscopy instrumentation. Here, we present MAcro Plant Projection Imaging (MAPPI), an open-source, low-cost, and modular fluorescence imaging platform for soil-grown plants beyond the model organism or seedling stage. MAPPI enables wide field-of-view, dual-projection imaging of fluorescent reporters, supporting real-time visualization of systemic signals under near-physiological conditions. We validate MAPPI by tracking calcium and l -glutamate dynamics in adult Nicotiana benthamiana plants, revealing developmentally regulated long-distance calcium waves triggered by wounding, burning, or submergence, including bidirectional shoot-to-root and root-to-shoot signaling. By democratizing access to whole-plant functional imaging, MAPPI provides a scalable tool for dissecting signal propagation, stress adaptation, and systemic communication in both model and nonmodel species.

Plant phenotyping relevance

植物全体の蛍光シグナルをリアルタイム取得する低コスト・オープンな画像プラットフォームを開発し、成体植物で検証しているため、植物表現型取得法が研究の中心です。

abstractHere, we present MAcro Plant Projection Imaging (MAPPI), an open-source, low-cost, and modular fluorescence imaging platform for soil-grown plants beyond the model organism or seedling stage.
abstractWe validate MAPPI by tracking calcium and l -glutamate dynamics in adult Nicotiana benthamiana plants

Code and data availability

The authors publicly deposit raw imaging data and MAPPI analysis code on Zenodo, host the MAPPI acquisition/analysis code on GitHub, and release the napari-roi-registration image registration plugin on GitHub. All are paper-specific, public, and actionable.

Datasetpublic

The raw data for the images presented in the manuscript and the code to run the MAPPI system are available on Zenodo ( https://doi.org/10.5281/zenodo.15845576 ).

Open resource ↗Zenodo · 10.5281/zenodo.15845576 · lines:170-466
Codepublic

The code to run the MAPPI system is also available on the dedicated GitHub repository ( https://github.com/micropolimi/MAPPI ) along with the code used to analyze the data.

Open resource ↗GitHub · micropolimi/MAPPI · lines:170-466
Codepublic

The software is open-source and available on GitHub ( https://github.com/GiorgiaTortora/napari-roi-registration ) and the napari-hub ( www.napari-hub.org/plugins/napari-roi-registration ).

Open resource ↗GitHub · GiorgiaTortora/napari-roi-registration · lines:156-169

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