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...

Background Cyanobacteria and other phototrophic microorganisms allow to couple the light-driven assimilation of atmospheric $$\text {CO}_{2}$$ CO 2 directly to the synthesis of carbon-based products, and are therefore attractive platforms for microbial cell factories. While most current engineering efforts are performed using small-scale laboratory cultivation, the economic viability of phototrophic cultivation also crucially depends on photobioreactor design and culture parameters, such as the maximal areal and volumetric productivities. Based on recent insights into the cyanobacterial cell physiology and the resulting computational models of cyanobacterial growth, the aim of this study is to investigate the limits of cyanobacterial productivity in continuous culture with light as the limiting nutrient. Results We integrate a coarse-grained model of cyanobacterial growth into a light-limited chemostat and its heterogeneous light gradient induced by self-shading of cells. We show that phototrophic growth in the light-limited chemostat can be described using the concept of an average light intensity. Different from previous models based on phenomenological growth equations, our model provides a mechanistic link between intracellular protein allocation, population growth and the resulting reactor productivity. Our computational framework thereby provides a novel approach to investigate and predict the maximal productivity of phototrophic cultivation, and identifies optimal proteome allocation strategies for developing maximally productive strains. Conclusions Our results have implications for efficient phototrophic cultivation and the design of maximally productive phototrophic cell factories. The model predicts that the use of dense cultures in well-mixed photobioreactors with short light-paths acts as an effective light dilution mechanism and alleviates the detrimental effects of photoinhibition even under very high light intensities. We recover the well-known trade-offs between a reduced light-harvesting apparatus and increased population density. Our results are discussed in the context of recent experimental efforts to increase the yield of phototrophic cultivation.

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Motivation: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even widely separated PTMs to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. Results: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. Availability: The source code is available at https://github.com/marjanfaizi/MSModDetector together with the scripts used for analyses and to generate the figures presented in this study.

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 minimal 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 parametrized 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 minimal growth models have implications for our understanding of the limits of phototrophic growth and bridge a gap between molecular physiology and ecology.

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