Interplay between high-energy quenching and state transitions in Chlamydomonas reinhardtii: a single-cell approach

Abstract

Studying cell-to-cell heterogeneity is essential to understand how unicellular organisms respond to stresses. We introduce a single-cell analysis framework that enables the study of intercellular heterogeneity of photosynthetic traits, particularly their interactions within individual cells that have identical genotypes, cellular contexts and histories. Our approach combines single-cell imaging of chlorophyll a fluorescence with machine learning and we study light stress responses in Chlamydomonas reinhardtii as a proof-of- concept. This framework allows us to score the extent of high-light responses such as state transitions (qT) and high-energy quenching (qE), to reveal significant cell-to-cell heterogeneity and to reveal a strong correlation between qT and qE, undetectable in bulk measurements. This study highlights the value of single-cell phenotypic analysis for for investigating light stress responses in unicellular organisms. We detail the key aspects that come into play to generalize the method to other complex stress responses involving multiple traits.

Plant phenotyping relevance

単一細胞のクロロフィル蛍光イメージングと機械学習を組み合わせ、光ストレス応答などの植物生理形質を抽出・評価する分析フレームワークが研究の中心である。

Code and data availability

The supplied blocks describe single-cell chlorophyll fluorescence measurements and a machine learning pipeline (dictionary learning + LDA) for scoring NPQ components in Chlamydomonas, but contain no data availability, code deposit, or public repository statements. No paper-specific public dataset, images, code, or模型 is

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