Culturing Synechocystis sp. Strain PCC 6803 with N2 and CO2 in a Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance Costs

A desiccated dual-species subaerial biofilm reprograms its metabolism and affects water dynamics in limestone

Understanding the impact of sessile communities on underlying materials is of paramount importance in stone conservation. Up until now, the critical role of subaerial biofilms (SABs) whether they are protective or deteriorative remains unclear, especially under desiccation. The interest in desiccated SABs is raised by the prediction of an increase in drought events in the next decades that will affect the Mediterranean regions' rich stone heritage as never before. Thus, the main goal of this research is to study the effects of desiccation on both the biofilms' eco-physiology and its impacts on the lithic substrate. To this end, we used a dual-species model system composed of a phototroph and a chemotroph to simulate biofilm behavior on stone heritage. We found that drought altered the phototroph-chemotroph balance and enriched the biofilm matrix with proteins and DNA. Desiccated SABs underwent a shift in metabolism to fermentation and a decrease in oxidative stress. Additionally, desiccated SABs changed the water-related dynamics (adsorption, evaporation, and wetting properties) in limestone. Water absorption experiments showed that desiccated SABs protected the stone from rapid water uptake, while a thermographic survey indicated a delay in water evaporation. Spilling-drop tests revealed a change in the wettability of the stone-SAB interface, which affected the water transport properties of the stone. Finally, desiccated SABs reduced stone swelling in the presence of water vapor. The biodeteriorative and bioprotective implications of desiccated SABs on the stone were ultimately assessed.

Carotenoid metabolism: New insights and synthetic approaches

Carotenoids are well-known isoprenoid pigments naturally produced by plants, algae, photosynthetic bacteria as well as by several heterotrophic microorganisms. In plants, they are synthesized in plastids where they play essential roles in light-harvesting and in protecting the photosynthetic apparatus from reactive oxygen species (ROS). Carotenoids are also precursors of bioactive metabolites called apocarotenoids, including vitamin A and the phytohormones abscisic acid (ABA) and strigolactones (SLs). Genetic engineering of carotenogenesis made possible the enhancement of the nutritional value of many crops. New metabolic engineering approaches have recently been developed to modulate carotenoid content, including the employment of CRISPR technologies for single-base editing and the integration of exogenous genes into specific "safe harbors" in the genome. In addition, recent studies revealed the option of synthetic conversion of leaf chloroplasts into chromoplasts, thus increasing carotenoid storage capacity and boosting the nutritional value of green plant tissues. Moreover, transient gene expression through viral vectors allowed the accumulation of carotenoids outside the plastid. Furthermore, the utilization of engineered microorganisms allowed efficient mass production of carotenoids, making it convenient for industrial practices. Interestingly, manipulation of carotenoid biosynthesis can also influence plant architecture, and positively impact growth and yield, making it an important target for crop improvements beyond biofortification. Here, we briefly describe carotenoid biosynthesis and highlight the latest advances and discoveries related to synthetic carotenoid metabolism in plants and microorganisms.

Quantifying the propagation of parametric uncertainty on flux balance analysis

Flux balance analysis (FBA) and associated techniques operating on stoichiometric genome-scale metabolic models play a central role in quantifying metabolic flows and constraining feasible phenotypes. At the heart of these methods lie two important assumptions: (i) the biomass precursors and energy requirements neither change in response to growth conditions nor environmental/genetic perturbations, and (ii) metabolite production and consumption rates are equal at all times (i.e., steady-state). Despite the stringency of these two assumptions, FBA has been shown to be surprisingly robust at predicting cellular phenotypes. In this paper, we formally assess the impact of these two assumptions on FBA results by quantifying how uncertainty in biomass reaction coefficients, and departures from steady-state due to temporal fluctuations could propagate to FBA results. In the first case, conditional sampling of parameter space is required to re-weigh the biomass reaction so as the molecular weight remains equal to 1 g mmol^-1, and in the second case, metabolite (and elemental) pool conservation must be imposed under temporally varying conditions. Results confirm the importance of enforcing the aforementioned constraints and explain the robustness of FBA biomass yield predictions.

A Systematic Survey of the Light/Dark-dependent Protein Degradation Events in a Model Cyanobacterium

Light is essential for photosynthetic organisms and is involved in the regulation of protein synthesis and degradation. The significance of light-regulated protein degradation is exemplified by the well-established light-induced degradation and repair of the photosystem II reaction center D1 protein in higher plants and cyanobacteria. However, systematic studies of light-regulated protein degradation events in photosynthetic organisms are lacking. Thus, we conducted a large-scale survey of protein degradation under light or dark conditions in the model cyanobacterium Synechocystis sp. PCC 6803 (hereafter referred to as Synechocystis) using the isobaric labeling-based quantitative proteomics technique. The results revealed that 79 proteins showed light-regulated degradation, including proteins involved in photosystem II structure or function, quinone binding, and NADH dehydrogenase. Among these, 25 proteins were strongly dependent on light for degradation. Moreover, the light-dependent degradation of several proteins was sensitive to photosynthetic electron transport inhibitors (DCMU and DBMIB), suggesting that they are influenced by the redox state of the plastoquinone (PQ) pool. Together, our study comprehensively cataloged light-regulated protein degradation events, and the results serve as an important resource for future studies aimed at understanding light-regulated processes and protein quality control mechanisms in cyanobacteria.

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Light-/dark-regulated protein degradation events in a model Cyanobacterium were identified.

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Seventy-nine proteins displayed light-regulated degradation.

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Thirty-one proteins displayed dark-regulated degradation.

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Multiple light-regulated protein degradation events were regulated by the redox state of the plastoquinone pool.

Slow Protein Turnover Explains Limited Protein-Level Response to Diurnal Transcriptional Oscillations in Cyanobacteria

Metabolically engineered cyanobacteria have the potential to mitigate anthropogenic CO₂ emissions by converting CO₂ into renewable fuels and chemicals. Yet, better understanding of metabolic regulation in cyanobacteria is required to develop more productive strains that can make industrial scale-up economically feasible. The aim of this study was to find the cause for the previously reported inconsistency between oscillating transcription and constant protein levels under day-night growth conditions. To determine whether translational regulation counteracts transcriptional changes, Synechocystis sp. PCC 6803 was cultivated in an artificial day-night setting and the level of transcription, translation and protein was measured across the genome at different time points using mRNA sequencing, ribosome profiling and quantitative proteomics. Furthermore, the effect of protein turnover on the amplitude of protein oscillations was investigated through in silico simulations using a protein mass balance model. Our experimental analysis revealed that protein oscillations were not dampened by translational regulation, as evidenced by high correlation between translational and transcriptional oscillations (r = 0.88) and unchanged protein levels. Instead, model simulations showed that these observations can be attributed to a slow protein turnover, which reduces the effect of protein synthesis oscillations on the protein level. In conclusion, these results suggest that cyanobacteria have evolved to govern diurnal metabolic shifts through allosteric regulatory mechanisms in order to avoid the energy burden of replacing the proteome on a daily basis. Identification and manipulation of such mechanisms could be part of a metabolic engineering strategy for overproduction of chemicals.

Computational Analysis of Dynamic Light Exposure of Unicellular Algal Cells in a Flat-Panel Photobioreactor to Support Light-Induced CO2 Bioprocess Development

Cyanobacterial cell factories trace a vibrant pathway to climate change neutrality and sustainable development owing to their ability to turn carbon dioxide-rich waste into a broad portfolio of renewable compounds, which are deemed valuable in green chemistry cross-sectorial applications. Cell factory design requires to define the optimal operational and cultivation conditions. The paramount parameter in biomass cultivation in photobioreactors is the light intensity since it impacts cellular physiology and productivity. Our modeling framework provides a basis for the predictive control of light-limited, light-saturated, and light-inhibited growth of the Synechocystis sp. PCC 6803 model organism in a flat-panel photobioreactor. The model here presented couples computational fluid dynamics, light transmission, kinetic modeling, and the reconstruction of single cell trajectories in differently irradiated areas of the photobioreactor to relate key physiological parameters to the multi-faceted processes occurring in the cultivation environment. Furthermore, our analysis highlights the need for properly constraining the model with decisive qualitative and quantitative data related to light calibration and light measurements both at the inlet and outlet of the photobioreactor in order to boost the accuracy and extrapolation capabilities of the model.

Four-carbon dicarboxylic acid production through the reductive branch of the open cyanobacterial tricarboxylic acid cycle in Synechocystis sp. PCC 6803

Succinate, fumarate, and malate are valuable four-carbon (C4) dicarboxylic acids used for producing plastics and food additives. C4 dicarboxylic acid is biologically produced by heterotrophic organisms. However, current biological production requires organic carbon sources that compete with food uses. Herein, we report C4 dicarboxylic acid production from CO₂ using metabolically engineered Synechocystis sp. PCC 6803. Overexpression of citH, encoding malate dehydrogenase (MDH), resulted in the enhanced production of succinate, fumarate, and malate. citH overexpression increased the reductive branch of the open cyanobacterial tricarboxylic acid (TCA) cycle flux. Furthermore, product stripping by medium exchanges increased the C4 dicarboxylic acid levels; product inhibition and acidification of the media were the limiting factors for succinate production. Our results demonstrate that MDH is a key regulator that activates the reductive branch of the open cyanobacterial TCA cycle. The study findings suggest that cyanobacteria can act as a biocatalyst for converting CO₂ to carboxylic acids.

Modifying the Cyanobacterial Metabolism as a Key to Efficient Biopolymer Production in Photosynthetic Microorganisms

Cyanobacteria are photoautotrophic bacteria commonly found in the natural environment. Due to the ecological benefits associated with the assimilation of carbon dioxide from the atmosphere and utilization of light energy, they are attractive hosts in a growing number of biotechnological processes. Biopolymer production is arguably one of the most critical areas where the transition from fossil-derived chemistry to renewable chemistry is needed. Cyanobacteria can produce several polymeric compounds with high applicability such as glycogen, polyhydroxyalkanoates, or extracellular polymeric substances. These important biopolymers are synthesized using precursors derived from central carbon metabolism, including the tricarboxylic acid cycle. Due to their unique metabolic properties, i.e., light harvesting and carbon fixation, the molecular and genetic aspects of polymer biosynthesis and their relationship with central carbon metabolism are somehow different from those found in heterotrophic microorganisms. A greater understanding of the processes involved in cyanobacterial metabolism is still required to produce these molecules more efficiently. This review presents the current state of the art in the engineering of cyanobacterial metabolism for the efficient production of these biopolymers.

Simultaneous increases in the levels of compatible solutes by cost-effective cultivation of Synechocystis sp. PCC 6803

Synechocystis sp. PCC 6803, a cyanobacterium widely used for basic research, is often cultivated in a synthetic medium, BG-11, in the presence of 4-(2-hydroxyethyl)-1-piperazine ethanesulfonic acid (HEPES) or 2-[[1,3-dihydroxy-2-(hydroxymethyl)propan-2-yl]amino]ethanesulfonic acid buffer. Owing to the high cost of HEPES buffer (96.9% of the total cost of BG-11 medium), the biotechnological application of BG-11 is limited. In this study, we cultured Synechocystis sp. PCC 6803 cells in BG-11 medium without HEPES buffer and examined the effects on the primary metabolism. Synechocystis sp. PCC 6803 cells could grow in BG-11 medium without HEPES buffer after adjusting for nitrogen sources and light intensity; the production rate reached 0.54 g cell dry weight·L^-1 ·day^-1 , exceeding that of commercial cyanobacteria and Synechocystis sp. PCC 6803 cells cultivated under other conditions. The exclusion of HEPES buffer markedly altered the metabolites in the central carbon metabolism; particularly, the levels of compatible solutes, such as sucrose, glucosylglycerol, and glutamate were increased. Although the accumulation of sucrose and glucosylglycerol under high salt conditions is antagonistic to each other, these metabolites accumulated simultaneously in cells grown in the cost-effective medium. Because these metabolites are used in industrial feedstocks, our results reveal the importance of medium composition for the production of metabolites using cyanobacteria.

A comprehensive time-course metabolite profiling of the model cyanobacterium Synechocystis sp. PCC 6803 under diurnal light:dark cycles

Cyanobacteria are a model photoautotroph and a chassis for the sustainable production of fuels and chemicals. Knowledge of photoautotrophic metabolism in the natural environment of day/night cycles is lacking, yet has implications for improved yield from plants, algae and cyanobacteria. Here, a thorough approach to characterizing diverse metabolites-including carbohydrates, lipids, amino acids, pigments, cofactors, nucleic acids and polysaccharides-in the model cyanobacterium Synechocystis sp. PCC 6803 (S. 6803) under sinusoidal diurnal light:dark cycles was developed and applied. A custom photobioreactor and multi-platform mass spectrometry workflow enabled metabolite profiling every 30-120 min across a 24-h diurnal sinusoidal LD ('sinLD') cycle peaking at 1600 μmol photons m^-2 sec^-1 . We report widespread oscillations across the sinLD cycle with 90%, 94% and 40% of the identified polar/semi-polar, non-polar and polymeric metabolites displaying statistically significant oscillations, respectively. Microbial growth displayed distinct lag, biomass accumulation and cell division phases of growth. During the lag phase, amino acids and nucleic acids accumulated to high levels per cell followed by decreased levels during the biomass accumulation phase, presumably due to protein and DNA synthesis. Insoluble carbohydrates displayed sharp oscillations per cell at the day-to-night transition. Potential bottlenecks in central carbon metabolism are highlighted. Together, this report provides a comprehensive view of photosynthetic metabolite behavior with high temporal resolution, offering insight into the impact of growth synchronization to light cycles via circadian rhythms. Incorporation into computational modeling and metabolic engineering efforts promises to improve industrially relevant strain design.

A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism

Phototrophic organisms such as cyanobacteria utilize the sun's energy to convert atmospheric carbon dioxide into organic carbon, resulting in diurnal variations in the cell's metabolism. Flux balance analysis is a widely accepted constraint-based optimization tool for analyzing growth and metabolism, but it is generally used in a time-invariant manner with no provisions for sequestering different biomass components at different time periods. Here we present CycleSyn, a periodic model of Synechocystis sp. PCC 6803 metabolism that spans a 12-hr light/12-hr dark cycle by segmenting it into 12 Time Point Models (TPMs) with a uniform duration of two hours. The developed framework allows for the flow of metabolites across TPMs while inventorying metabolite levels and only allowing for the utilization of currently or previously produced compounds. The 12 TPMs allow for the incorporation of time-dependent constraints that capture the cyclic nature of cellular processes. Imposing bounds on reactions informed by temporally-segmented transcriptomic data enables simulation of phototrophic growth as a single linear programming (LP) problem. The solution provides the time varying reaction fluxes over a 24-hour cycle and the accumulation/consumption of metabolites. The diurnal rhythm of metabolic gene expression driven by the circadian clock and its metabolic consequences is explored. Predicted flux and metabolite pools are in line with published studies regarding the temporal organization of phototrophic growth in Synechocystis PCC 6803 paving the way for constructing time-resolved genome-scale models (GSMs) for organisms with a circadian clock. In addition, the metabolic reorganization that would be required to enable Synechocystis PCC 6803 to temporally separate photosynthesis from oxygen-sensitive nitrogen fixation is also explored using the developed model formalism.

Analysis of the light intensity dependence of the growth of Synechocystis and of the light distribution in a photobioreactor energized by 635 nm light

Synechocystis gathered momentum in modelling studies and biotechnological applications owing to multiple factors like fast growth, ability to fix carbon dioxide into valuable products, and the relative ease of genetic manipulation. Synechocystis physiology and metabolism, and consequently, the productivity of Synechocystis-based photobioreactors (PBRs), are heavily light modulated. Here, we set up a turbidostat-controlled lab-scale cultivation system in order to study the influence of varying orange–red light intensities on Synechocystis growth characteristics and photosynthetic activity. Synechocystis growth and photosynthetic activity were found to raise as supplied light intensity increased up to 500 μmol photons m⁻² s⁻¹ and to enter the photoinhibition state only at 800 μmol photons m⁻² s⁻¹. Interestingly, reverting the light to a non-photo-inhibiting intensity unveiled Synechocystis to be able to promptly recover. Furthermore, our characterization displayed a clear correlation between variations in growth rate and cell size, extending a phenomenon previously observed in other cyanobacteria. Further, we applied a modelling approach to simulate the effects produced by varying the incident light intensity on its local distribution within the PBR vessel. Our model simulations suggested that the photosynthetic activity of Synechocystis could be enhanced by finely regulating the intensity of the light incident on the PBR in order to prevent cells from experiencing light-induced stress and induce their exploitation of areas of different local light intensity formed in the vessel. In the latter case, the heterogeneous distribution of the local light intensity would allow Synechocystis for an optimized usage of light.

Alignment of microbial fitness with engineered product formation: obligatory coupling between acetate production and photoautotrophic growth

BACKGROUND

Microbial bioengineering has the potential to become a key contributor to the future development of human society by providing sustainable, novel, and cost-effective production pipelines. However, the sustained productivity of genetically engineered strains is often a challenge, as spontaneous non-producing mutants tend to grow faster and take over the population. Novel strategies to prevent this issue of strain instability are urgently needed.

RESULTS

In this study, we propose a novel strategy applicable to all microbial production systems for which a genome-scale metabolic model is available that aligns the production of native metabolites to the formation of biomass. Based on well-established constraint-based analysis techniques such as OptKnock and FVA, we developed an in silico pipeline-FRUITS-that specifically 'Finds Reactions Usable in Tapping Side-products'. It analyses a metabolic network to identify compounds produced in anabolism that are suitable to be coupled to growth by deletion of their re-utilization pathway(s), and computes their respective biomass and product formation rates. When applied to Synechocystis sp. PCC6803, a model cyanobacterium explored for sustainable bioproduction, a total of nine target metabolites were identified. We tested our approach for one of these compounds, acetate, which is used in a wide range of industrial applications. The model-guided engineered strain shows an obligatory coupling between acetate production and photoautotrophic growth as predicted. Furthermore, the stability of acetate productivity in this strain was confirmed by performing prolonged turbidostat cultivations.

CONCLUSIONS

This work demonstrates a novel approach to stabilize the production of target compounds in cyanobacteria that culminated in the first report of a photoautotrophic growth-coupled cell factory. The method developed is generic and can easily be extended to any other modeled microbial production system.

Light-controlled motility in prokaryotes and the problem of directional light perception

The natural light environment is important to many prokaryotes. Most obviously, phototrophic prokaryotes need to acclimate their photosynthetic apparatus to the prevailing light conditions, and such acclimation is frequently complemented by motility to enable cells to relocate in search of more favorable illumination conditions. Non-phototrophic prokaryotes may also seek to avoid light at damaging intensities and wavelengths, and many prokaryotes with diverse lifestyles could potentially exploit light signals as a rich source of information about their surroundings and a cue for acclimation and behavior. Here we discuss our current understanding of the ways in which bacteria can perceive the intensity, wavelength and direction of illumination, and the signal transduction networks that link light perception to the control of motile behavior. We discuss the problems of light perception at the prokaryotic scale, and the challenge of directional light perception in small bacterial cells. We explain the peculiarities and the common features of light-controlled motility systems in prokaryotes as diverse as cyanobacteria, purple photosynthetic bacteria, chemoheterotrophic bacteria and haloarchaea.

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

Cyanobacteria are an integral part of Earth's biogeochemical cycles and a promising resource for the synthesis of renewable bioproducts from atmospheric CO₂ Growth and metabolism of cyanobacteria are inherently tied to the diurnal rhythm of light availability. As yet, however, insight into the stoichiometric and energetic constraints of cyanobacterial diurnal growth is limited. Here, we develop a computational framework to investigate the optimal allocation of cellular resources during diurnal phototrophic growth using a genome-scale metabolic reconstruction of the cyanobacterium Synechococcus elongatus PCC 7942. We formulate phototrophic growth as an autocatalytic process and solve the resulting time-dependent resource allocation problem using constraint-based analysis. Based on a narrow and well-defined set of parameters, our approach results in an ab initio prediction of growth properties over a full diurnal cycle. The computational model allows us to study the optimality of metabolite partitioning during diurnal growth. The cyclic pattern of glycogen accumulation, an emergent property of the model, has timing characteristics that are in qualitative agreement with experimental findings. The approach presented here provides insight into the time-dependent resource allocation problem of phototrophic diurnal growth and may serve as a general framework to assess the optimality of metabolic strategies that evolved in phototrophic organisms under diurnal conditions.

Determination of the Glycogen Content in Cyanobacteria

Cyanobacteria accumulate glycogen as a major intracellular carbon and energy storage during photosynthesis. Recent developments in research have highlighted complex mechanisms of glycogen metabolism, including the diel cycle of biosynthesis and catabolism, redox regulation, and the involvement of non-coding RNA. At the same time, efforts are being made to redirect carbon from glycogen to desirable products in genetically engineered cyanobacteria to enhance product yields. Several methods are used to determine the glycogen contents in cyanobacteria, with variable accuracies and technical complexities. Here, we provide a detailed protocol for the reliable determination of the glycogen content in cyanobacteria that can be performed in a standard life science laboratory. The protocol entails the selective precipitation of glycogen from the cell lysate and the enzymatic depolymerization of glycogen to generate glucose monomers, which are detected by a glucose oxidase-peroxidase (GOD-POD) enzyme coupled assay. The method has been applied to Synechocystis sp. PCC 6803 and Synechococcus sp. PCC 7002, two model cyanobacterial species that are widely used in metabolic engineering. Moreover, the method successfully showed differences in the glycogen contents between the wildtype and mutants defective in regulatory elements or glycogen biosynthetic genes.