The Fluctuating Cell-Specific Light Environment and Its Effects on Cyanobacterial Physiology

Impact of irradiance and inorganic carbon availability on heterologous sucrose production in Synechococcus elongatus PCC 7942

Cyanobacteria have been proposed as a potential alternative carbohydrate feedstock and multiple species have been successfully engineered to secrete fermentable sugars. To date, the most productive cyanobacterial strains are those designed to secrete sucrose, yet there exist considerable differences in reported productivities across different model species and laboratories. In this study, we investigate how cultivation conditions (specifically, irradiance, CO2, and cultivator type) affect the productivity of sucrose-secreting Synechococcus elongatus PCC 7942. We find that S. elongatus produces the highest sucrose yield in irradiances far greater than what is often experimentally utilized, and that high light intensities are tolerated by S. elongatus, especially under higher density cultivation where turbidity may attenuate the effective light experienced in the culture. By increasing light and inorganic carbon availability, S. elongatus cscB/sps produced a total of 3.8 g L-1 of sucrose and the highest productivity within that period being 47.8 mg L-1 h-1. This study provides quantitative description of the impact of culture conditions on cyanobacteria-derived sucrose that may assist to standardize cross-laboratory comparisons and demonstrates a significant capacity to improve productivity via optimizing cultivation conditions.

CRISPR interference screens reveal growth-robustness tradeoffs in Synechocystis sp. PCC 6803 across growth conditions

Barcoded mutant libraries are a powerful tool for elucidating gene function in microbes, particularly when screened in multiple growth conditions. Here, we screened a pooled CRISPR interference library of the model cyanobacterium Synechocystis sp. PCC 6803 in 11 bioreactor-controlled conditions, spanning multiple light regimes and carbon sources. This gene repression library contained 21,705 individual mutants with high redundancy over all open reading frames and noncoding RNAs. Comparison of the derived gene fitness scores revealed multiple instances of gene repression being beneficial in 1 condition while generally detrimental in others, particularly for genes within light harvesting and conversion, such as antennae components at high light and PSII subunits during photoheterotrophy. Suboptimal regulation of such genes likely represents a tradeoff of reduced growth speed for enhanced robustness to perturbation. The extensive data set assigns condition-specific importance to many previously unannotated genes and suggests additional functions for central metabolic enzymes. Phosphoribulokinase, glyceraldehyde-3-phosphate dehydrogenase, and the small protein CP12 were critical for mixotrophy and photoheterotrophy, which implicates the ternary complex as important for redirecting metabolic flux in these conditions in addition to inactivation of the Calvin cycle in the dark. To predict the potency of sgRNA sequences, we applied machine learning on sgRNA sequences and gene repression data, which showed the importance of C enrichment and T depletion proximal to the PAM site. Fitness data for all genes in all conditions are compiled in an interactive web application.

Characterizing compensatory mechanisms in the absence of photoprotective qE in Chlamydomonas reinhardtii

Rapid fluctuations in the quantity and quality of natural light expose photosynthetic organisms to conditions when the capacity to utilize absorbed quanta is insufficient. These conditions can result in the production of reactive oxygen species and photooxidative damage. Non-photochemical quenching (NPQ) and alternative electron transport are the two most prominent mechanisms which synergistically function to minimize the overreduction of photosystems. In the green alga Chlamydomonas reinhardtii, the stress-related light-harvesting complex (LHCSR) is a required component for the rapid induction and relaxation of NPQ in the light-harvesting antenna. Here, we use simultaneous chlorophyll fluorescence and oxygen exchange measurements to characterize the acclimation of the Chlamydomonas LHCSR-less mutant (npq4lhcsr1) to saturating light conditions. We demonstrate that, in the absence of NPQ, Chlamydomonas does not acclimate to sinusoidal light through increased light-dependent oxygen consumption. We also show that the npq4lhcsr1 mutant has an increased sink capacity downstream of PSI and this energy flow is likely facilitated by cyclic electron transport. Furthermore, we show that the timing of additions of mitochondrial inhibitors has a major influence on plastid/mitochondrial coupling experiments.

Life in biophotovoltaics systems

As the most suitable potential clean energy power generation technology, biophotovoltaics (BPV) not only inherits the advantages of traditional photovoltaics, such as safety, reliability and no noise, but also solves the disadvantages of high pollution and high energy consumption in the manufacturing process, providing new functions of self-repair and natural degradation. The basic idea of BPV is to collect light energy and generate electric energy by using photosynthetic autotrophs or their parts, and the core is how these biological materials can quickly and low-loss transfer electrons to the anode through mediators after absorbing light energy and generating electrons. In this mini-review, we summarized the biological materials widely used in BPV at present, mainly cyanobacteria, green algae, biological combinations (using multiple microorganisms in the same BPV system) and isolated products (purified thylakoids, chloroplasts, photosystem I, photosystem II), introduced how researchers overcome the shortcomings of low photocurrent output of BPV, pointed out the limitations that affected the development of BPV' biological materials, and put forward reasonable assumptions accordingly.

An ATP-sensitive phosphoketolase regulates carbon fixation in cyanobacteria

Regulation of CO2 fixation in cyanobacteria is important both for the organism and global carbon balance. Here we show that phosphoketolase in Synechococcus elongatus PCC7942 (SeXPK) possesses a distinct ATP-sensing mechanism, where a drop in ATP level allows SeXPK to divert precursors of the RuBisCO substrate away from the Calvin-Benson-Bassham cycle. Deleting the SeXPK gene increased CO2 fixation particularly during light-dark transitions. In high-density cultures, the Δxpk strain showed a 60% increase in carbon fixation and unexpectedly resulted in sucrose secretion without any pathway engineering. Using cryo-EM analysis, we discovered that these functions were enabled by a unique allosteric regulatory site involving two subunits jointly binding two ATP, which constantly suppresses the activity of SeXPK until the ATP level drops. This magnesium-independent ATP allosteric site is present in many species across all three domains of life, where it may also play important regulatory functions.

Fertilization and seasonality influence on the photochemical performance of tree legumes in forest plantation for area recovery in the Amazon

N-fixing leguminous species can reach atmospheric dinitrogen gas (N₂), having an advantage under N-limited degraded environments. These N-fixers are constantly used as facilitative species. Chlorophyll a fluorescence (ChF) acknowledges how different species take up and use light energy during photosynthesis. These techniques assess stress and performance responses to photosynthesis and are used for the selection of species with potential for reforestation. Six Fabaceae species were selected for this study: three nonfixing species (Cenostigma tocantinum, Senna reticulata and Dipteryx odorata) and three N-fixing species (Clitoria fairchildiana, Inga edulis and Acacia spp.). Variations in chlorophyll fluorescence under high vs. low water and nutrient conditions were studied. Multivariate analysis was performed to detect the effects of seasonality and fertilization on dark-adapted ChF two years after the experiment was established. The correlation among ChF variables and growth, photosynthesis and foliar nutrient concentrations was evaluated. Under high water- and nutrient-availability conditions, plants exhibited an enhanced performance index on absorption basis values correlated with electron transport fluxes. Under drought and nutrient-poor conditions, most species exhibit increased energy dissipation as photoprotection. High interspecific variation was found; therefore, species-specific responses should be considered in future ChF studies. Corroborating the ability to colonize high-light environments, N-fixers showed an increased performance index correlated with electron transport and Zn and N foliar concentrations. Negative correlations were found between photosynthesis and trapped fluxes. Diameter growth was positively correlated with electron transport fluxes. Given the different responses among species, ChF is an effective technique to screen for seasonality, fertilization and species effects and should be considered for use during forest restoration. Finally, the addition of fertilization treatments may facilitate tropical forest restoration due to the importance of nutrients in physiological processes. N-fixers showed high photochemical performance and tolerance to abiotic stress in degraded areas and therefore should be included to support ecosystem biomass restoration.

Rapid photoacclimation during episodic deep mixing augments the biological carbon pump

Episodic deep mixing events are one component of the biological carbon pump that physically transports organic carbon into the mesopelagic. Episodic deep mixing also disrupts summertime thermal stratification thereby changing the light field and nutrient concentrations available for phytoplankton growth. Phytoplankton survival and growth below the mixed layer following restratification depends on how rapidly cells can employ a variety of photoacclimation processes in response to the environmental changes. To compare the relative timescales of summertime episodic deep mixing events with the timescales of phytoplankton photoacclimation processes, we first analyzed autonomous float data to survey the frequency and magnitude of deep mixing events in the western North Atlantic Ocean. Next, we simulated a sustained deep mixing event in the laboratory and measured rates of acclimation processes ranging from light harvesting to growth in a model diatom and green alga. In both algae increases in chlorophyll (Chl) were coupled to growth, but growth of the green alga lagged the diatom by about a day. In float profiles, significant increases in Chl and phytoplankton carbon (C _phyto) were detected below the mixed layer following episodic deep mixing events. These events pose a previously unrecognized source of new production below the mixed layer that can significantly boost the amount of carbon available for export to the deep ocean.

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.

A Chlorophyte Alga Utilizes Alternative Electron Transport for Primary Photoprotection

The green alga Desmodesmus armatus is an emerging biofuel platform that produces high amounts of lipids and biomass in mass culture. We observed D. armatus in light-limiting, excess-light, and sinusoidal-light environments to investigate its photoacclimation behaviors and the mechanisms by which it dissipates excess energy. Chlorophyll a/b ratios and the functional absorption cross section of PSII suggested a constitutively small light-harvesting antenna size relative to other green algae. In situ and ex situ measurements of photo-physiology revealed that nonphotochemical quenching is not a significant contributor to photoprotection; however, cells do not suffer substantial photoinhibition despite its near absence. We performed membrane inlet mass spectrometry analysis to show that D. armatus has a very high capacity for alternative electron transport (AET) measured as light-dependent oxygen consumption. Up to 90% of electrons generated at PSII can be dissipated by AET in a water-water cycle during growth in rapidly fluctuating light environments, like those found in industrial-scale photobioreactors. This work highlights the diversity of photoprotective mechanisms present in algal systems, indicating that nonphotochemical quenching is not necessarily required for effective photoprotection in some algae, and suggests that engineering AET may be an attractive target for increasing the biomass productivity of some strains.

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.

Fluctuating light experiments and semi-automated plant phenotyping enabled by self-built growth racks and simple upgrades to the IMAGING-PAM

BACKGROUND

Over the last years, several plant science labs have started to employ fluctuating growth light conditions to simulate natural light regimes more closely. Many plant mutants reveal quantifiable effects under fluctuating light despite being indistinguishable from wild-type plants under standard constant light. Moreover, many subtle plant phenotypes become intensified and thus can be studied in more detail. This observation has caused a paradigm shift within the photosynthesis research community and an increasing number of scientists are interested in using fluctuating light growth conditions. However, high installation costs for commercial controllable LED setups as well as costly phenotyping equipment can make it hard for small academic groups to compete in this emerging field.

RESULTS

We show a simple do-it-yourself approach to enable fluctuating light growth experiments. Our results using previously published fluctuating light sensitive mutants, stn7 and pgr5, confirm that our low-cost setup yields similar results as top-prized commercial growth regimes. Moreover, we show how we increased the throughput of our Walz IMAGING-PAM, also found in many other departments around the world. We have designed a Python and R-based open source toolkit that allows for semi-automated sample segmentation and data analysis thereby reducing the processing bottleneck of large experimental datasets. We provide detailed instructions on how to build and functionally test each setup.

CONCLUSIONS

With material costs well below USD$1000, it is possible to setup a fluctuating light rack including a constant light control shelf for comparison. This allows more scientists to perform experiments closer to natural light conditions and contribute to an emerging research field. A small addition to the IMAGING-PAM hardware not only increases sample throughput but also enables larger-scale plant phenotyping with automated data analysis.