Phototrophic microorganisms are promising resources for green biotechnology. Compared to heterotrophic microorganisms, however, the cellular economy of phototrophic growth is still insufficiently understood. We provide a quantitative analysis of light-limited, light-saturated, and light-inhibited growth of the cyanobacterium Synechocystis sp. PCC 6803 using a reproducible cultivation setup. We report key physiological parameters, including growth rate, cell size, and photosynthetic activity over a wide range of light intensities. Intracellular proteins were quantified to monitor proteome allocation as a function of growth rate. Among other physiological acclimations, we identify an upregulation of the translational machinery and downregulation of light harvesting components with increasing light intensity and growth rate. The resulting growth laws are discussed in the context of a coarse-grained model of phototrophic growth and available data obtained by a comprehensive literature search. Our insights into quantitative aspects of cyanobacterial acclimations to different growth rates have implications to understand and optimize photosynthetic productivity.

Photoautotrophic growth depends upon an optimal allocation of finite cellular resources to diverse intracellular processes. Commitment of a certain mass fraction of the proteome to a specific cellular function typically reduces the proteome available for other cellular functions. Here, we develop a semi-quantitative kinetic model of cyanobacterial phototrophic growth to describe such trade-offs of cellular protein allocation. The model is based on coarse-grained descriptions of key cellular processes, in particular carbon uptake, metabolism, photosynthesis, and protein translation. The model is parameterized using literature data and experimentally obtained growth curves. Of particular interest are the resulting cyanobacterial growth laws as fundamental characteristics of cellular growth. We show that the model gives rise to similar growth laws as observed for heterotrophic organisms, with several important differences due to the distinction between light energy and carbon uptake. We discuss recent experimental data supporting the model results and show that coarse-grained growth models have implications for our understanding of the limits of phototrophic growth and bridge a gap between molecular physiology and ecology.

Phototrophic microorganisms are promising resources for green biotechnology. 13 Compared to heterotrophic microorganisms, however, the cellular economy of phototrophic 14 growth is still insufficiently understood. We provide a quantitative analysis of light-limited, 15 light-saturated, and light-inhibited growth of the cyanobacterium Synechocystis sp. PCC 6803 using 16 a reproducible cultivation setup. We report key physiological parameters, including growth rate, cell 17 size, and photosynthetic activity over a wide range of light intensities. Intracellular proteins were 18 quantified to monitor proteome allocation as a function of growth rate. Among other physiological 19 adaptations, we identify an upregulation of the translational machinery and downregulation of light 20 harvesting components with increasing light intensity and growth rate. The resulting growth laws 21 are discussed in the context of a coarse-grained model of phototrophic growth and available data 22 obtained by a comprehensive literature search. Our insights into quantitative aspects of 23 cyanobacterial adaptations to different growth rates have implications to understand and optimize 24 photosynthetic productivity. 25 26 2014). While quantitative insight into the cellular economy of phototrophic microorganisms is 36 still scarce, the cellular economy of heterotrophic growth has been studied extensively-starting 37 with the seminal works of Monod, Neidhardt, and others (Neidhardt et al., 1990; Neidhardt, 1999; 38 Jun et al., 2018) to more recent quantitative studies of microbial resource allocation (Molenaar 39 et al.40 Maitra and Dill, 2015; Weiße et al., 2015). In response to changing environments, heterotrophic 41 1 of 28 Manuscript submitted to eLife microorganisms are known to differentially allocate their resources: with increasing growth rate, 42 heterotrophic microorganisms typically exhibit upregulation of ribosomes and other proteins 43 related to translation and protein synthesis (Scott et al., 2010; Molenaar et al., 2009; Peebo et al., 44 2015), exhibit complex changes in transcription profiles, e.g. (Klumpp et al., 2009; Matsumoto et al., 45 2013), and increase cell size (Kafri et al., 2016). The molecular limits of heterotrophic growth have 46 been described thoroughly (Kafri et al., 2016; Erickson et al., 2017; Scott et al., 2014; Metzl-Raz 47 et al., 2017; Klumpp et al., 2013). 48 In contrast, only few studies so far have addressed the limits of cyanobacterial growth from an 49 experimental perspective (Bernstein et al., 2016; Yu et al., 2015; Abernathy et al., 2017; Ungerer 50 et al., 2018; Jahn et al., 2018). Of particular interest were the adaptations that enable fast pho-51 toautotrophic growth (Bernstein et al., 2016; Yu et al., 2015; Abernathy et al., 2017; Ungerer et al., 52 2018). The cyanobacterium with the highest known photoautotrophic growth rate, growing with a 53 doubling time of up to ∼ 1.5h, is the strain Synechococcus elongatus UTEX 2973 (Ungerer et al., 54 2018). Compared to its c...

In multicellular organisms, the specification, coordination, and compartmentalization of cell types enable the formation of complex body plans. However, some eukaryotic protists such as slime molds generate diverse and complex structures while remaining in a multinucleate syncytial state. It is unknown if different regions of these giant syncytial cells have distinct transcriptional responses to environmental encounters and if nuclei within the cell diversify into heterogeneous states. Here, we performed spatial transcriptome analysis of the slime mold Physarum polycephalum in the plasmodium state under different environmental conditions and used single-nucleus RNA-sequencing to dissect gene expression heterogeneity among nuclei. Our data identifies transcriptome regionality in the organism that associates with proliferation, syncytial substructures, and localized environmental conditions. Further, we find that nuclei are heterogenous in their transcriptional profile and may process local signals within the plasmodium to coordinate cell growth, metabolism, and reproduction. To understand how nuclei variation within the syncytium compares to heterogeneity in single-nucleus cells, we analyzed states in single Physarum amoebal cells. We observed amoebal cell states at different stages of mitosis and meiosis, and identified cytokinetic features that are specific to nuclei divisions within the syncytium. Notably, we do not find evidence for predefined transcriptomic states in the amoebae that are observed in the syncytium. Our data shows that a single-celled slime mold can control its gene expression in a region-specific manner while lacking cellular compartmentalization and suggests that nuclei are mobile processors facilitating local specialized functions. More broadly, slime molds offer the extraordinary opportunity to explore how organisms can evolve regulatory mechanisms to divide labor, specialize, balance competition with cooperation, and perform other foundational principles that govern the logic of life.

In multicellular organisms, the specification, coordination, and compartmentalization of cell types enable the formation of complex body plans. However, some eukaryotic protists such as slime molds generate diverse and complex structures while remaining in a multinucleated syncytial state. It is unknown if different regions of these giant syncytial cells have distinct transcriptional responses to environmental encounters, and if nuclei within the cell diversify into heterogeneous states. Here we performed spatial transcriptome analysis of the slime mold Physarum polycephalum in the plasmodium state under different environmental conditions, and used single-nucleus RNA-sequencing to dissect gene expression heterogeneity among nuclei. Our data identifies transcriptome regionality in the organism that associates with proliferation, syncytial substructures, and localized environmental conditions. Further, we find that nuclei are heterogenous in their transcriptional profile, and may process local signals within the plasmodium to coordinate cell growth, metabolism, and reproduction. To understand how nuclei variation within the syncytium compares to heterogeneity in single-nucleated cells, we analyzed states in single Physarum amoebal cells. We observed amoebal cell states at different stages of mitosis and meiosis, and identified cytokinetic features that are specific to nuclei divisions within the syncytium. Notably, we do not find evidence for predefined transcriptomic states in the amoebae that are observed in the syncytium. Our data shows that a single-celled slime mold can control its gene expression in a region-specific manner while lacking cellular compartmentalization, and suggests that nuclei are mobile processors facilitating local specialized functions. More broadly, slime molds offer the extraordinary opportunity to explore how organisms can evolve regulatory mechanisms to divide labor, specialize, balance competition with cooperation, and perform other foundational principles that govern the logic of life.