Quantitative insights into the cyanobacterial cell economy

Abstract

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...

Growth of Cyanobacteria Is Constrained by the Abundance of Light and Carbon Assimilation Proteins

“…To obtain reliable growth conditions and proteome profiles under different light and CO 2 regimes, we used a multiplex turbidostat continuous cultivation system (details in STAR Methods). The turbidostat is ideal for cultivation of cyanobacteria because the incident light intensity per biomass is kept constant over time to prevent culture self-shading (Zav rel et al, 2015;Du et al, 2016). To ensure a steady state, cells were cultivated under each condition for a minimum of five reactor volume retention times (RT = 1/m) after the growth rate (m) and the relative chlorophyll content (optical density 680 (OD 680 )/OD 720 had stabilized) (see Figure S1 for example cultivations and Table S1 for a complete list of all performed cultivations).…”

A quantitative description of light-limited cyanobacterial growth using flux balance analysis

“…The latter is derived from measurements of the mass fractions of protein and glycogen as a function of light intensity, with the remaining components scaled accordingly. Figure 2 summarizes the available growth data [1], including the specific growth rate as a function of light intensity, the respective changes in biomass composition, as well as the light-dependent oxygen (O 2 ) evolution. All data are sourced from a single set of experiments [1].…”

“…Among cyanobacteria, the strain Synechosystis sp. PCC 6803 is an established model organism with a broad compendium of published studies that characterize its growth and metabolism under different environmental conditions [1,2].…”

Shedding light on blue-green photosynthesis: A wavelength-dependent mathematical model of photosynthesis in Synechocystis sp. PCC 6803

“…The model has been manually parameterized, integrating physiological data and dynamic observations from numerous groups (pH-ranges: [52], NADPH reduction: [53], O 2 change rates: [25], CO 2 consumption: [33], PQ reduction: [54], PC, PSI, and Fd redox-states: [55], PAM-behavior: [42], electron fluxes: [46], PAM fluorescence: [56]).…”

“…Established cyanobacterial models often describe broad ecosystem behavior or specific cellular characteristics [27]. Worth mentioning here are constrainedbased reconstructions of primary metabolic networks [28,29,30], as well as kinetic models, ranging from simple models of non-photochemical quenching [31] and fluorescence [26] to adapted plant models to study the dynamics of cyanobacterial photosynthesis [32] and models created to study proteome allocation as a function of growth rate [33]. However, none of these models provide a detailed, mechanistic description of oxygenic photosynthesis in Synechocystis sp.…”