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 Chla 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). We reveal significant cell-to-cell heterogeneity and a strong correlation between qT and qE, undetectable in bulk measurements. This study highlights the value of single-cell phenotypic analysis 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.
Lahlou et al. (Sun,) studied this question.