Cycling between growth and production phases increases cyanobacteria bioproduction of lactate

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

Cyanobacteria hold great potential to revolutionize conventional industries and farming practices with their light-driven chemical production. To fully exploit their photosynthetic capacity and enhance product yield, it is crucial to investigate their intricate interplay with the environment including the light intensity and spectrum. Mathematical models provide valuable insights for optimizing strategies in this pursuit. In this study, we present an ordinary differential equation-based model for the cyanobacterium Synechocystis sp. PCC 6803 to assess its performance under various light sources, including monochromatic light. Our model can reproduce a variety of physiologically measured quantities, e.g. experimentally reported partitioning of electrons through four main pathways, O2 evolution, and the rate of carbon fixation for ambient and saturated CO2. By capturing the interactions between different components of a photosynthetic system, our model helps in understanding the underlying mechanisms driving system behavior. Our model qualitatively reproduces fluorescence emitted under various light regimes, replicating Pulse-amplitude modulation (PAM) fluorometry experiments with saturating pulses. Using our model, we test four hypothesized mechanisms of cyanobacterial state transitions for ensemble of parameter sets and found no physiological benefit of a model assuming phycobilisome detachment. Moreover, we evaluate metabolic control for biotechnological production under diverse light colors and irradiances. We suggest gene targets for overexpression under different illuminations to increase the yield. By offering a comprehensive computational model of cyanobacterial photosynthesis, our work enhances the basic understanding of light-dependent cyanobacterial behavior and sets the first wavelength-dependent framework to systematically test their producing capacity for biocatalysis.

Phenotypic heterogeneity follows a growth-viability tradeoff in response to amino acid identity

In their natural environments, microorganisms mainly operate at suboptimal growth conditions with fluctuations in nutrient abundance. The resulting cellular adaptation is subject to conflicting tasks: growth or survival maximisation. Here, we study this adaptation by systematically measuring the impact of a nitrogen downshift to 24 nitrogen sources on cellular metabolism at the single-cell level. Saccharomyces lineages grown in rich media and exposed to a nitrogen downshift gradually differentiate to form two subpopulations of different cell sizes where one favours growth while the other favours viability with an extended chronological lifespan. This differentiation is asymmetrical with daughter cells representing the new differentiated state with increased viability. We characterise the metabolic response of the subpopulations using RNA sequencing, metabolic biosensors and a transcription factor-tagged GFP library coupled to high-throughput microscopy, imaging more than 800,000 cells. We find that the subpopulation with increased viability is associated with a dormant quiescent state displaying differences in MAPK signalling. Depending on the identity of the nitrogen source present, differentiation into the quiescent state can be actively maintained, attenuated, or aborted. These results establish amino acids as important signalling molecules for the formation of genetically identical subpopulations, involved in chronological lifespan and growth rate determination.

CRISPR Tools for Engineering Prokaryotic Systems: Recent Advances and New Applications

In the past decades, the broad selection of CRISPR-Cas systems has revolutionized biotechnology by enabling multimodal genetic manipulation in diverse organisms. Rooted in a molecular engineering perspective, we recapitulate the different CRISPR components and how they can be designed for specific genetic engineering applications. We first introduce the repertoire of Cas proteins and tethered effectors used to program new biological functions through gene editing and gene regulation. We review current guide RNA (gRNA) design strategies and computational tools and how CRISPR-based genetic circuits can be constructed through regulated gRNA expression. Then, we present recent advances in CRISPR-based biosensing, bioproduction, and biotherapeutics across in vitro and in vivo prokaryotic systems. Finally, we discuss forthcoming applications in prokaryotic CRISPR technology that will transform synthetic biology principles in the near future.

Engineering highly productive cyanobacteria towards carbon negative emissions technologies

Cyanobacteria are a diverse and ecologically important group of photosynthetic prokaryotes that contribute significantly to the global carbon cycle through the capture of CO2 as biomass. Cyanobacterial biotechnology could play a key role in a sustainable bioeconomy through negative emissions technologies (NETs), such as carbon sequestration or bioproduction. However, the primary issues of low productivities and high infrastructure costs currently limit the commercialisation of such applications. The isolation of several fast-growing strains and recent advancements in molecular biology tools now offer promising new avenues for improving yields, including metabolic engineering approaches guided by high-throughput screening and metabolic models. Furthermore, emerging research on engineering coculture communities could help to develop more robust culturing systems to support broader NET applications.

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 isoprene production in cyanobacteria - Insights into the effects of light, temperature, and isoprene on Synechocystis sp. PCC 6803

Engineering cyanobacteria for the production of isoprene and other terpenoids has gained increasing attention in the field of biotechnology. Several studies have addressed optimization of isoprene synthesis in cyanobacteria via enzyme and pathway engineering. However, only little attention has been paid to the optimization of cultivation conditions. In this study, an isoprene-producing strain of Synechocystis sp. PCC 6803 and two control strains were grown under a variety of cultivation conditions. Isoprene production, as quantified by modified membrane inlet mass spectrometer (MIMS) and interpreted using Flux Balance Analysis (FBA), increased under violet light and at elevated temperature. Increase of thermotolerance in the isoprene producer was attributed to the physical presence of isoprene, similar to plants. The results demonstrate a beneficial effect of isoprene on cell survival at higher temperatures. This increased thermotolerance opens new possibilities for sustainable bio-production of isoprene and other products.

Assessing and reducing phenotypic instability in cyanobacteria

Cyanobacteria have promising potential as sustainable cell factories. However, one challenge that is still largely unreported in scaling-up cyanobacteria bioproduction is phenotypic instability, where the emergence and selection of nonproducing cells leading to loss in production has longer evolutionary timescales to take place in industrial-scale bioreactors. Quantifying phenotypic instability early on in strain development allows researchers to make informed decisions on whether to proceed with scalable designs, or if present, devise countermeasures to reduce instability. One particularly effective strategy to mitigate instability is the use of genome-scale metabolic models to design growth-coupled production strains. In silico studies have predicted that creating certain cofactor imbalances or removing recycling reactions in cyanobacteria can be exploited to stably produce a wide variety of metabolites.

Cyanobacteria as whole-cell factories: current status and future prospectives

Cyanobacteria as phototrophic microorganisms bear great potential to produce chemicals from sustainable resources such as light and CO₂. Most studies focus on either strain engineering or tackling metabolic constraints. Recently gained knowledge on internal electron and carbon fluxes and their regulation provides new opportunities to efficiently channel cellular resources toward product formation. Concomitantly, novel photobioreactor concepts are developed to ensure sufficient light supply. This review summarizes the newest developments in the field of cyanobacterial engineering to finally establish photosynthesis-based production processes. A holistic approach tackling genetic, metabolic, and biochemical engineering in parallel is considered essential to turn their application into an ecoefficient and economically feasible option for a future green bioeconomy.

Recent Advances in CRISPR-Cas Technologies for Synthetic Biology

With developments in synthetic biology, "engineering biology" has emerged through standardization and platformization based on hierarchical, orthogonal, and modularized biological systems. Genome engineering is necessary to manufacture and design synthetic cells with desired functions by using bioparts obtained from sequence databases. Among various tools, the CRISPR-Cas system is modularly composed of guide RNA and Cas nuclease; therefore, it is convenient for editing the genome freely. Recently, various strategies have been developed to accurately edit the genome at a single nucleotide level. Furthermore, CRISPR-Cas technology has been extended to molecular diagnostics for nucleic acids and detection of pathogens, including disease-causing viruses. Moreover, CRISPR technology, which can precisely control the expression of specific genes in cells, is evolving to find the target of metabolic biotechnology. In this review, we summarize the status of various CRISPR technologies that can be applied to synthetic biology and discuss the development of synthetic biology combined with CRISPR technology in microbiology.

Base editing for reprogramming cyanobacterium Synechococcus elongatus

Cyanobacteria can directly convert carbon dioxide (CO₂) at the atmospheric level to biofuels, value-added chemicals and food products, making them ideal candidates to alleviate global climate change. Despite decades-long pioneering successes, the development of genome-editing tools, especially the CRISPR-Cas-based approaches, seems to lag behind other microbial chassis, slowing down the innovations of cyanobacteria. Here, we adapted and tailored base editing for cyanobacteria based on the CRISPR-Cas system and deamination. We achieved precise and efficient genome editing at a single-nucleotide resolution and demonstrated multiplex base editing in the model cyanobacterium Synechococcus elongatus. By using the base-editing tool, we successfully manipulated the glycogen metabolic pathway via the introduction of premature STOP codons in the relevant genes, building engineered strains with elevated potentials to produce chemicals and food from CO₂. We present here the first report of base editing in the phylum of cyanobacteria, and a paradigm for applying CRISPR-Cas systems in bacteria. We believe that our work will accelerate the metabolic engineering and synthetic biology of cyanobacteria and drive more innovations to alleviate global climate change.

Carbon-negative synthetic biology: challenges and emerging trends of cyanobacterial technology

Global warming and climate instability have spurred interest in using renewable carbon resources for the sustainable production of chemicals. Cyanobacteria are ideal cellular factories for carbon-negative production of chemicals owing to their great potentials for directly utilizing light and CO₂ as sole energy and carbon sources, respectively. However, several challenges in adapting cyanobacterial technology to industry, such as low productivity, poor tolerance, and product harvesting difficulty, remain. Synthetic biology may finally address these challenges. Here, we summarize recent advances in the production of value-added chemicals using cyanobacterial cell factories, particularly in carbon-negative synthetic biology and emerging trends in cyanobacterial applications. We also propose several perspectives on the future development of cyanobacterial technology for commercialization.

Thermodynamic limitations of PHB production from formate and fructose in Cupriavidus necator

The chemolithotroph Cupriavidus necator H16 is known as a natural producer of the bioplastic-polymer PHB, as well as for its metabolic versatility to utilize different substrates, including formate as the sole carbon and energy source. Depending on the entry point of the substrate, this versatility requires adjustment of the thermodynamic landscape to maintain sufficiently high driving forces for biological processes. Here we employed a model of the core metabolism of C. necator H16 to analyze the thermodynamic driving forces and PHB yields from formate for different metabolic engineering strategies. For this, we enumerated elementary flux modes (EFMs) of the network and evaluated their PHB yields as well as thermodynamics via Max-min driving force (MDF) analysis and random sampling of driving forces. A heterologous ATP:citrate lyase reaction was predicted to increase driving force for producing acetyl-CoA. A heterologous phosphoketolase reaction was predicted to increase maximal PHB yields as well as driving forces. These enzymes were then verified experimentally to enhance PHB titers between 60 and 300% in select conditions. The EFM analysis also revealed that PHB production from formate may be limited by low driving forces through citrate lyase and aconitase, as well as cofactor balancing, and identified additional reactions associated with low and high PHB yield. Proteomics analysis of the engineered strains confirmed an increased abundance of aconitase and cofactor balancing. The findings of this study aid in understanding metabolic adaptation. Furthermore, the outlined approach will be useful in designing metabolic engineering strategies in other non-model bacteria.

Sustainable citric acid production from CO2 in an engineered cyanobacterium

Citric acid is one of the most widely used organic acids in the world, with applications ranging from acidity regulation in food and beverages to metal chelation in hydrometallurgical processes. Most of its production is currently derived from fermentative processes, using plant-derived carbon feedstocks. While these are currently dominant, there is an increasing need to develop closed-loop production systems that reduce process carbon footprint. In this work, we demonstrate for the first time that an engineered marine cyanobacterium Synechococcus sp. PCC 7002 can be used as a sustainable chassis for the photosynthetic conversion of CO₂ to citric acid. Decreased citric acid cycle flux, through the use of a theophylline-responsive riboswitch, was combined with improved flux through citrate synthase and enhanced citric acid excretion, resulting in a significant improvement to citric acid production. While allowing citrate production, this strategy induces a growth defect which can be overcome by glutamate supplementation or by fine-tuning aconitase levels, resulting in an increase in production relative to WT of over 100-fold. This work represents a first step toward sustainable production of a commodity organic acid from CO₂.

Reprogramming Microbial CO2-Metabolizing Chassis With CRISPR-Cas Systems

Global warming is approaching an alarming level due to the anthropogenic emission of carbon dioxide (CO2). To overcome the challenge, the reliance on fossil fuels needs to be alleviated, and a significant amount of CO2 needs to be sequestrated from the atmosphere. In this endeavor, carbon-neutral and carbon-negative biotechnologies are promising ways. Especially, carbon-negative bioprocesses, based on the microbial CO2-metabolizing chassis, possess unique advantages in fixing CO2 directly for the production of fuels and value-added chemicals. In order to fully uncover the potential of CO2-metabolizing chassis, synthetic biology tools, such as CRISPR-Cas systems, have been developed and applied to engineer these microorganisms, revolutionizing carbon-negative biotechnology. Herein, we review the recent advances in the adaption of CRISPR-Cas systems, including CRISPR-Cas based genome editing and CRISPR interference/activation, in cyanobacteria, acetogens, and methanogens. We also envision future innovations via the implementation of rising CRISPR-Cas systems, such as base editing, prime editing, and transposon-mediated genome editing.

CRISPR-Based Approaches for Gene Regulation in Non-Model Bacteria

CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) have become ubiquitous approaches to control gene expression in bacteria due to their simple design and effectiveness. By regulating transcription of a target gene(s), CRISPRi/a can dynamically engineer cellular metabolism, implement transcriptional regulation circuitry, or elucidate genotype-phenotype relationships from smaller targeted libraries up to whole genome-wide libraries. While CRISPRi/a has been primarily established in the model bacteria Escherichia coli and Bacillus subtilis, a growing numbering of studies have demonstrated the extension of these tools to other species of bacteria (here broadly referred to as non-model bacteria). In this mini-review, we discuss the challenges that contribute to the slower creation of CRISPRi/a tools in diverse, non-model bacteria and summarize the current state of these approaches across bacterial phyla. We find that despite the potential difficulties in establishing novel CRISPRi/a in non-model microbes, over 190 recent examples across eight bacterial phyla have been reported in the literature. Most studies have focused on tool development or used these CRISPRi/a approaches to interrogate gene function, with fewer examples applying CRISPRi/a gene regulation for metabolic engineering or high-throughput screens and selections. To date, most CRISPRi/a reports have been developed for common strains of non-model bacterial species, suggesting barriers remain to establish these genetic tools in undomesticated bacteria. More efficient and generalizable methods will help realize the immense potential of programmable CRISPR-based transcriptional control in diverse bacteria.

New synthetic biology tools for metabolic control

In industrial bioprocesses, microbial metabolism dictates the product yields, and therefore, our capacity to control it has an enormous potential to help us move towards a bio-based economy. The rapid development of multiomics data has accelerated our systematic understanding of complex metabolic regulatory mechanisms, which allow us to develop tools to manipulate them. In the last few years, machine learning-based metabolic modeling, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) derived synthetic biology tools, and synthetic genetic circuits have been widely used to control the metabolism of microorganisms, manipulate gene expression, and build synthetic pathways for bioproduction. This review describes the latest developments for metabolic control, and focuses on the trends and challenges of metabolic engineering strategies.