Photonfluxostat: A method for light-limited batch cultivation of cyanobacteria at different, yet constant, growth rates

Use of Quartz Sand Columns to Study Far-Red Light Photoacclimation (FaRLiP) in Cyanobacteria

Some cyanobacteria can perform far-red light photoacclimation (FaRLiP), which allows them to use far-red light (FRL) for oxygenic photosynthesis. Most of the cyanobacteria able to use FRL were discovered in low visible-light (VL; λ = 400-700 nm) environments that are also enriched in FRL (λ = 700-800 nm). However, these cyanobacteria grow faster in VL than in FRL in laboratory conditions, indicating that FRL is not their preferred light source when VL is available. Therefore, it is interesting to understand why such strains were primarily found in FRL-enriched but not VL-enriched environments. To this aim, we established a terrestrial model system with quartz sand to study the distribution and photoacclimation of cyanobacterial strains. A FaRLiP-performing cyanobacterium, Leptolyngbya sp. JSC-1, and a VL-utilizing model cyanobacterium, Synechocystis sp. PCC 6803, were compared in this study. We found that, although Leptolyngbya sp. JSC-1 can grow well in both VL and FRL, Synechocystis sp. PCC 6803 grows much faster than Leptolyngbya sp. JSC-1 in VL. In addition, the growth was higher in liquid cocultures than in monocultures of Leptolyngbya sp. JSC-1 or Synechocystis sp. PCC 6803. In an artificial terrestrial model system, Leptolyngbya sp. JSC-1 has an advantage when growing in coculture at greater depths by performing FaRLiP. Therefore, strong competition for VL and slower growth rate are possible reasons why FRL-utilizing cyanobacteria are found in environments with low VL intensities. This model system provides a valuable tool for future studies of cyanobacterial ecological niches and interactions in a terrestrial environment. IMPORTANCE This study uses sand columns to establish a terrestrial model system for the investigation of the distribution and acclimation of cyanobacteria to far-red light. Previous studies of this group of cyanobacteria required direct in situ samplings. The variability of conditions and abundances of the cyanobacteria in natural settings impeded detailed analyses and comparisons. Therefore, we established this model system under controlled conditions in the laboratory. In this system, the distribution and acclimation of two cyanobacteria were similar to the situation observed in natural environments, which validates that it can be used to study fundamental questions. Using this approach, we made the unanticipated observation that two cyanobacteria grow faster in coculture than in axenic cultures. This laboratory-based model system can provide a valuable new tool for comparing cyanobacterial strains (e.g., mutants and wild type), exploring interactions between cyanobacterial strains and interactions with other bacteria, and characterizing ecological niches of cyanobacteria.

Channeling Anabolic Side Products toward the Production of Nonessential Metabolites: Stable Malate Production in Synechocystis sp. PCC6803

Powered by (sun)light to oxidize water, cyanobacteria can directly convert atmospheric CO₂ into valuable carbon-based compounds and meanwhile release O₂ to the atmosphere. As such, cyanobacteria are promising candidates to be developed as microbial cell factories for the production of chemicals. Nevertheless, similar to other microbial cell factories, engineered cyanobacteria may suffer from production instability. The alignment of product formation with microbial fitness is a valid strategy to tackle this issue. We have described previously the "FRUITS" algorithm for the identification of metabolites suitable to be coupled to growth (i.e., side products in anabolic reactions) in the model cyanobacterium Synechocystis. sp PCC6803. However, the list of candidate metabolites identified using this algorithm can be somewhat limiting, due to the inherent structure of metabolic networks. Here, we aim at broadening the spectrum of candidate compounds beyond the ones predicted by FRUITS, through the conversion of a growth-coupled metabolite to downstream metabolites via thermodynamically favored conversions. We showcase the feasibility of this approach for malate production using fumarate as the growth-coupled substrate in Synechocystis mutants. A final titer of ∼1.2 mM was achieved for malate during photoautotrophic batch cultivations. Under prolonged continuous cultivation, the most efficient malate-producing strain can maintain its productivity for at least 45 generations, sharply contrasting with other producing Synechocystis strains engineered with classical approaches. Our study also opens a new possibility for extending the stable production concept to derivatives of growth-coupled metabolites, increasing the list of suitable target compounds.

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.

Biochemical profiling of three indigenous Dunaliella isolates with main focus on fatty acid composition towards potential biotechnological application

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Biochemical composition of native isolates determined their potential application.

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The isolates tend to store energy and carbon mainly in lipid, not carbohydrate, form.

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The fatty acid profile of the isolates show appropriate n3:n6 and health lipid indices.

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Dunaliella sp. ABRIINW-B1 and -G2/1 are the proper options for nutraceutical purposes.

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Dunaliella sp. ABRIINW-I1 well suits pharmaceutical and aquaculture application.

This study describes the biochemical composition of three isolates, Dunaliella sp. ABRIINW-B1, -G2/1 and -I1 towards the biotechnological potential. Dunaliella sp. ABRIINW- G2/1 and -I1 had a remarkable protein content (∼40% dry weight). Dunaliella sp. ABRIINW-I1 contained a pigment fraction of 3.2% largely composed of chlorophyll a (1.9%) and carotenoid (1.1%). Dunaliella sp. ABRIINW-B1, -G2/1 and -I1 produced respectively 42, 36 and 47% lipid content. The occurrence of high lipid and low carbohydrate (4–7%) in the isolates demonstrated their cell tendency to store energy and carbon mainly in lipid form. The lipid profile of the isolates expressed adequate n3:n6 ratio and health indices. The biochemical analysis revealed that Dunaliella sp. ABRIINW-B1 and -G2/1 have potential applications in the food and freshwater aquafeed sector. While Dunaliella sp. ABRIINW-I1 owing to appropriate pigment, protein, and lipid level containing very-long-chain polyunsaturated fatty acids showed a great promise in nutritional, pharmaceutical and marine aquafeed industries.

Pooled CRISPRi screening of the cyanobacterium Synechocystis sp PCC 6803 for enhanced industrial phenotypes

Cyanobacteria are model organisms for photosynthesis and are attractive for biotechnology applications. To aid investigation of genotype-phenotype relationships in cyanobacteria, we develop an inducible CRISPRi gene repression library in Synechocystis sp. PCC 6803, where we aim to target all genes for repression. We track the growth of all library members in multiple conditions and estimate gene fitness. The library reveals several clones with increased growth rates, and these have a common upregulation of genes related to cyclic electron flow. We challenge the library with 0.1 M L-lactate and find that repression of peroxiredoxin bcp2 increases growth rate by 49%. Transforming the library into an L-lactate-secreting Synechocystis strain and sorting top lactate producers enriches clones with sgRNAs targeting nutrient assimilation, central carbon metabolism, and cyclic electron flow. In many examples, productivity can be enhanced by repression of essential genes, which are difficult to access by transposon insertion.

Exploiting Day- and Night-Time Metabolism of Synechocystis sp. PCC 6803 for Fitness-Coupled Fumarate Production around the Clock

Cyanobacterial cell factories are widely researched for the sustainable production of compounds directly from CO2. Their application, however, has been limited for two reasons. First, traditional approaches have been shown to lead to unstable cell factories that lose their production capability when scaled to industrial levels. Second, the alternative approaches developed so far are mostly limited to growing conditions, which are not always the case in industry, where nongrowth periods tend to occur (e.g., darkness). We tackled both by generalizing the concept of growth-coupled production to fitness coupling. The feasibility of this new approach is demonstrated for the production of fumarate by constructing the first stable dual-strategy cell factory. We exploited circadian metabolism using both systems and synthetic biology tools, resulting in the obligatorily coupling of fumarate to either biomass or energy production. Resorting to laboratory evolution experiments, we show that this engineering approach is more stable than conventional methods.

Optimal proteome allocation strategies for phototrophic growth in a light-limited chemostat

BACKGROUND

Cyanobacteria and other phototrophic microorganisms allow to couple the light-driven assimilation of atmospheric [Formula: see text] 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.

Exploring the low photosynthetic efficiency of cyanobacteria in blue light using a mutant lacking phycobilisomes

The ubiquitous chlorophyll a (Chl a) pigment absorbs both blue and red light. Yet, in contrast to green algae and higher plants, most cyanobacteria have much lower photosynthetic rates in blue than in red light. A plausible but not yet well-supported hypothesis is that blue light results in limited energy transfer to photosystem II (PSII), because cyanobacteria invest most Chl a in photosystem I (PSI), whereas their phycobilisomes (PBS) are mostly associated with PSII but do not absorb blue photons. In this paper, we compare the photosynthetic performance in blue and orange-red light of wildtype Synechocystis sp. PCC 6803 and a PBS-deficient mutant. Our results show that the wildtype had much lower biomass, Chl a content, PSI:PSII ratio and O₂ production rate per PSII in blue light than in orange-red light, whereas the PBS-deficient mutant had a low biomass, Chl a content, PSI:PSII ratio, and O₂ production rate per PSII in both light colors. More specifically, the wildtype displayed a similar low photosynthetic efficiency in blue light as the PBS-deficient mutant in both light colors. Our results demonstrate that the absorption of light energy by PBS and subsequent transfer to PSII are crucial for efficient photosynthesis in cyanobacteria, which may explain both the low photosynthetic efficiency of PBS-containing cyanobacteria and the evolutionary success of chlorophyll-based light-harvesting antennae in environments dominated by blue light.

Quantitative insights into the cyanobacterial cell economy

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.

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.

Targeted Repression of Essential Genes To Arrest Growth and Increase Carbon Partitioning and Biofuel Titers in Cyanobacteria

Photoautotrophic production of fuels and chemicals by cyanobacteria typically gives lower volumetric productivities and titers than heterotrophic production. Cyanobacteria cultures become light limited above an optimal cell density, so that this substrate is not supplied to all cells sufficiently. Here, we investigate genetic strategies for a two-phase cultivation, where biofuel-producing Synechocystis cultures are limited to an optimal cell density through inducible CRISPR interference (CRISPRi) repression of cell growth. Fixed CO₂ is diverted to ethanol or n-butanol. Among the most successful strategies was partial repression of citrate synthase gltA. Strong repression (>90%) of gltA at low culture densities increased carbon partitioning to n-butanol 5-fold relative to a nonrepression strain, but sacrificed volumetric productivity due to severe growth restriction. CO₂ fixation continued for at least 3 days after growth was arrested. By targeting sgRNAs to different regions of the gltA gene, we could modulate GltA expression and carbon partitioning between growth and product to increase both specific and volumetric productivity. These growth arrest strategies can be useful for improving performance of other photoautotrophic processes.

Light-optimized growth of cyanobacterial cultures: Growth phases and productivity of biomass and secreted molecules in light-limited batch growth

Cyanobacteria are photosynthetic microorganisms whose metabolism can be modified through genetic engineering for production of a wide variety of molecules directly from CO2, light, and nutrients. Diverse molecules have been produced in small quantities by engineered cyanobacteria to demonstrate the feasibility of photosynthetic biorefineries. Consequently, there is interest in engineering these microorganisms to increase titer and productivity to meet industrial metrics. Unfortunately, differing experimental conditions and cultivation techniques confound comparisons of strains and metabolic engineering strategies. In this work, we discuss the factors governing photoautotrophic growth and demonstrate nutritionally replete conditions in which a model cyanobacterium can be grown to stationary phase with light as the sole limiting substrate. We introduce a mathematical framework for understanding the dynamics of growth and product secretion in light-limited cyanobacterial cultures. Using this framework, we demonstrate how cyanobacterial growth in differing experimental systems can be easily scaled by the volumetric photon delivery rate using the model organisms Synechococcus sp. strain PCC7002 and Synechococcus elongatus strain UTEX2973. We use this framework to predict scaled up growth and product secretion in 1L photobioreactors of two strains of Synechococcus PCC7002 engineered for production of l-lactate or L-lysine. The analytical framework developed in this work serves as a guide for future metabolic engineering studies of cyanobacteria to allow better comparison of experiments performed in different experimental systems and to further investigate the dynamics of growth and product secretion.

A model of optimal protein allocation during phototrophic growth

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.

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.

Challenges in the Application of Synthetic Biology Toward Synthesis of Commodity Products by Cyanobacteria via "Direct Conversion"

Cyanobacterial direct conversion of CO₂ to several commodity chemicals has been recognized as a potential contributor to support the much-needed sustainable development of human societies. However, the feasibility of this "green conversion" hinders on our ability to overcome the hurdles presented by the natural evolvability of microbes. The latter may result in the genetic instability of engineered cyanobacterial strains leading to impaired productivity. This challenge is general to any "cell factory" approach in which the cells grow for multiple generations, and based on several studies carried out in different microbial hosts, we could identify that three distinct strategies have been proposed to tackle it. These are (1) to reduce microbial evolvability by decreasing the native mutation rate, (2) to align product formation with cell growth/fitness, and, paradoxically, (3) to efficiently reallocate cellular resources to product formation by uncoupling it from growth. The implementation of either of these strategies requires an advanced synthetic biology toolkit. Here, we review the existing methods available for cyanobacteria and identify areas of focus in which specific developments are still needed. Furthermore, we discuss how potentially stabilizing strategies may be used in combination leading to further increases of productivity while ensuring the stability of the cyanobacterial-based direct conversion process.

Natural changes in light interact with circadian regulation at promoters to control gene expression in cyanobacteria

The circadian clock interacts with other regulatory pathways to tune physiology to predictable daily changes and unexpected environmental fluctuations. However, the complexity of circadian clocks in higher organisms has prevented a clear understanding of how natural environmental conditions affect circadian clocks and their physiological outputs. Here, we dissect the interaction between circadian regulation and responses to fluctuating light in the cyanobacterium Synechococcus elongatus. We demonstrate that natural changes in light intensity substantially affect the expression of hundreds of circadian-clock-controlled genes, many of which are involved in key steps of metabolism. These changes in expression arise from circadian and light-responsive control of RNA polymerase recruitment to promoters by a network of transcription factors including RpaA and RpaB. Using phenomenological modeling constrained by our data, we reveal simple principles that underlie the small number of stereotyped responses of dusk circadian genes to changes in light.

Living things face daily, predictable challenges due to the regular day and night cycle imposed by the Earth’s rotation. Many of them have evolved an internal ‘circadian’ clock to anticipate daily changes in the environment. However, nature can also change in unpredictable ways, and in order to survive, organisms must account for both the time of day stipulated by their clocks and changes in their present environment. For example, cyanobacteria depend on the sun for survival and must cope with light variations throughout the day and the absence of light at nighttime.

Circadian clocks are made up of specific genes and their proteins. Most of what we know about how these clocks control the behavior of an organism comes from experiments performed under constant conditions. Previous research has shown that under such circumstances, the circadian clock of cyanobacteria periodically turns on a set of genes every 24 hours via a protein called RpaA. However, to understand how cyanobacteria use this clock, we must know how it works in a fluctuating environment.

To test this, Piechura, Amarnath and O’Shea measured the activation of genes in cyanobacteria that had been exposed to changes in light mimicking those in nature. Compared to constant conditions, fluctuating light drastically changed the timing of activation of circadian genes. When light decreased – as it would in nature during sunset or if a cloud blocks the sun – the circadian genes were activated.

Changes in light did not change the ‘ticking’ of the clock, but did affect the ability of RpaA to turn on circadian genes. Moreover, the activity of a second protein called RpaB increased when light decreased and the genes were activated. Thus, cyanobacteria switch on circadian genes as the sun is setting or during unexpected shade, likely through RpaA and RpaB, to help them survive without light.

This study shows that circadian clocks activate genes differently in the real world compared to unnatural, constant conditions. This may prompt scientists to think carefully about how an organism’s natural environment can affect its inner workings. A next step will be to see how else light affects circadian gene levels. A deeper understanding of how cyanobacteria control their genes in a natural environment will be useful for scientists who engineer these organisms to produce biofuels from sunlight.