Rubisco is the main entry point of inorganic carbon into the biosphere and a central player in the global carbon system. The relatively low specific activity and tendency to accept O2 as a substrate have made Rubisco an attractive but challenging target for enzyme engineering. We have developed an enzyme engineering and screening platform for Rubisco using the model cyanobacterium Synechocystis sp. PCC 6803. Starting with the Form II Rubisco from Gallionella, we first show that the enzyme can replace the native Form I Rubisco in Synechocystis and that growth rates become sensitive to CO2 and O2 levels. We address the challenge of designing a zero-shot input library of the Gallionella Rubisco, without prior experimental knowledge, by coupling the phylogenetically guided model EV mutation with "in silico evolution". This multisite mutagenesis library of Synechocystis (n = 16) was subjected to competitive growth in different gas feeds coupled to deep sequencing, in order to compare Rubisco variants. We identified an amino acid exchange that increased the thermostability of Gallionella Rubisco and conveyed resilience to otherwise detrimental amino acid exchanges. The platform is a first step toward high-throughput screening of Rubisco variants in Synechocystis and creating optimized enzyme variants to accelerate the Calvin-Benson-Bassham cycle in cyanobacteria and possibly chloroplasts.

Rubisco is the main entry point of inorganic carbon into the biosphere and a central player in the global carbon system. The relatively low specific activity and tendency to accept O2 as a substrate have made Rubisco an attractive but challenging target for enzyme engineering. We have developed an enzyme engineering and screening platform for Rubisco using the model cyanobacterium Synechocystis sp. PCC 6803. Starting with the Form II Rubisco from Gallionella, we first show that the enzyme can replace the native Form I Rubisco in Synechocystis and that growth rates become sensitive to CO2 and O2 levels. We address the challenge of designing a zero-shot input library of the Gallionella Rubisco, without prior experimental knowledge, by coupling the phylogenetically guided model EV mutation with "in silico evolution". This multisite mutagenesis library of Synechocystis (n = 16) was subjected to competitive growth in different gas feeds coupled to deep sequencing, in order to compare Rubisco variants. We identified an amino acid exchange that increased the thermostability of Gallionella Rubisco and conveyed resilience to otherwise detrimental amino acid exchanges. The platform is a first step toward high-throughput screening of Rubisco variants in Synechocystis and creating optimized enzyme variants to accelerate the Calvin-Benson-Bassham cycle in cyanobacteria and possibly chloroplasts.

Plants rely on metabolite regulation of proteins to control their metabolism and adapt to environmental changes, but studying these complex interaction networks remains challenging. The proteome integral solubility alteration (PISA) assay, a high-throughput chemoproteomic technique, was originally developed for mammalian systems to investigate drug targets. PISA detects changes in protein stability upon interaction with small molecules, quantified through LC–MS. Here, we present an adapted PISA protocol for Arabidopsis thaliana chloroplasts to identify potential protein interactions with ascorbate. Chloroplasts are extracted using a linear Percoll gradient, treated with multiple ascorbate concentrations, and subjected to heat-induced protein denaturation. Soluble proteins are extracted via ultracentrifugation, and proteome-wide stability changes are quantified using multiplexed LC–MS. We provide instructions for deconvolution of LC–MS spectra and statistical analysis using freely available software. This protocol enables unbiased screening of protein regulation by small molecules in plants without requiring prior knowledge of interaction partners, chemical probe design, or genetic modifications.

Malonyl-CoA, produced by the first committed step of fatty acid biosynthesis, is a precursor for many valuable bioproducts, making it an important metabolic engineering target. Here, we establish a malonyl-CoA biosensor for the model cyanobacteria Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942. The developed biosensor utilizes FapR, a malonyl-CoA-regulated transcriptional repressor from Bacillus subtilis, and novel FapR-regulated and cyanobacteria-compatible hybrid promoters for expressing Yfp, the biosensor output reporter. A l-rhamnose-inducible promoter P rhaBAD , characterized in combination with ribosome binding sites of varied strengths, was evaluated for titratable FapR expression. Additionally, the placement and quantity of the FapR-recognized operator within the hybrid promoter was evaluated for its effect on biosensor performance. The optimal operator placement was found to differ for the biosensor variants that achieved maximum reporter expression in the two considered model cyanobacteria. Overall, this biosensor provides new opportunities for further development of cyanobacterial cell factories.

One strategy for CO2 mitigation is using photosynthetic microorganisms to sequester CO2 under high concentrations, such as in flue gases. While elevated CO2 levels generally promote growth, excessively high levels inhibit growth through uncertain mechanisms. This study investigated the physiology of the cyanobacterium Synechocystis sp. PCC 6803 under very high CO2 concentrations and yet stable pH around 7.5. The growth rate of the wild type (WT) at 200 mu mol photons m(-2) s(-1) and a gas phase containing 30% CO2 was 2.7-fold lower compared to 4% CO2. Using a CRISPR interference mutant library, we identified genes that, when repressed, either enhanced or impaired growth under 30% or 4% CO2. Repression of genes involved in light harvesting (cpc and apc), photochemical electron transfer (cytM, psbJ, and petE), and several genes with little or unknown functions promoted growth under 30% CO2, while repression of key regulators of photosynthesis (pmgA) and CO2 capture and fixation (ccmR, cp12, and yfr1) increased growth inhibition under 30% CO2. Experiments confirmed that WT cells were more susceptible to light inhibition under 30% than under 4% CO2 and that a light-harvesting-impaired Delta cpcG mutant showed improved growth under 30% CO2 compared to the WT. These findings suggest that enhanced fitness under very high CO2 involves modifications in light harvesting, electron transfer, and carbon metabolism, and that the native regulatory machinery is insufficient, and in some cases obstructive, for optimal growth under 30% CO2. This genetic profiling provides potential targets for engineering cyanobacteria with improved photosynthetic efficiency and stress resilience for biotechnological applications. KEY POINTS: center dot Synechocystis growth was inhibited under very high CO2. center dot Inhibition of growth under very high CO2 was light dependent. center dot Repression of photosynthesis genes improved growth under very high CO2.

Ascorbate (Asc) is a major plant metabolite that plays crucial roles in various processes, from reactive oxygen scavenging to epigenetic regulation. However, to what extent and how Asc modulates metabolism is largely unknown. We investigated the consequences of chloroplastic and total cellular Asc deficiencies by studying chloroplastic Asc transporter mutant lines lacking PHOSPHATE TRANSPORTER 4; 4 and the Asc-deficient vtc2-4 mutant of Arabidopsis (Arabidopsis thaliana). Under regular growth conditions, both Asc deficiencies caused minor alterations in photosynthesis, with no apparent signs of oxidative damage. In contrast, metabolomics analysis revealed global and largely overlapping alterations in the metabolome profiles of both Asc-deficient mutants, suggesting that chloroplastic Asc modulates plant metabolism. We observed significant alterations in amino acid metabolism, particularly in arginine metabolism, activation of nucleotide salvage pathways, and changes in secondary metabolism. In addition, proteome-wide analysis of thermostability revealed that Asc may interact with enzymes involved in arginine metabolism, the Calvin–Benson cycle, and several photosynthetic electron transport components. Overall, our results suggest that, independent of oxidative stress, chloroplastic Asc modulates the activity of diverse metabolic pathways in vascular plants and may act as an internal metabolite signal.

Microbial catalysts must partition incoming substrate between the synthesis of biomass and the synthesis of a desired product. Although biomass synthesis generates more catalyst and therefore potentially higher volumetric productivities, the synthesis of product increases specific production rates and product yields. Two-stage bioprocesses can accommodate this tradeoff through temporal separation of the growth and production phases. The biocatalyst first grows to optimal density; it is then switched to a growth-arrested state during which the product is synthesized. However, a substantial reduction in metabolic activity is often observed during cellular growth arrest, even in the presence of sufficient substrate. An ultimate bioengineering goal, therefore, is to create growth-arrested states that retain high metabolic activity. Achieving this goal brings the metabolic engineer to the intersection of microbial physiology, synthetic biology and biochemistry. In this Review, we describe various aspects of the design of microbial catalysts for two-stage bioprocesses for metabolite production, including synthetic biology tools to arrest cell growth using external or internal cues, and metabolic engineering tools to minimize interference from the native metabolic network and enhance substrate uptake and conversion. We highlight recent systems biology studies of nutrient-limited heterotrophs and phototrophs and conclude that the reduction in substrate uptake by cells in growth arrest is the consequence of reduced energy demand as well as imbalances in regulatory metabolites that typically arise during nutrient limitation. On the basis of these studies, we propose strategies for increasing metabolic activity in growth-arrested cells.

The Calvin Benson cycle in phototrophic and chemolithoautotrophic bacteria has ecological and biotechnological importance, which has motivated study of its regulation. I review recent advances in our understanding of how the Calvin Benson cycle is regulated in bacteria and the technologies used to elucidate regulation and modify it, and highlight differences between and photoautotrophic and chemolithoautotrophic models. Systems biology studies have shown that in oxygenic phototrophic bacteria, Calvin Benson cycle enzymes are extensively regulated at post-transcriptional and post-translational levels, with multiple enzyme activities connected to cellular redox status through thioredoxin. In chemolithoautotrophic bacteria, regulation is primarily at the transcriptional level, with effector metabolites transducing cell status, though new methods should now allow facile, proteome-wide exploration of biochemical regulation in these models. A biotechnological objective is to enhance CO2 fixation in the cycle and partition that carbon to a product of interest. Flux control of CO2 fixation is distributed over multiple enzymes, and attempts to modulate gene Calvin cycle gene expression show a robust homeostatic regulation of growth rate, though the synthesis rates of products can be significantly increased. Therefore, de-regulation of cycle enzymes through protein engineering may be necessary to increase fluxes. Non-canonical Calvin Benson cycles, if implemented with synthetic biology, could have reduced energy demand and enzyme loading, thus increasing the attractiveness of these bacteria for industrial applications.

The "knallgas" bacterium Cupriavidus necator is attracting interest due to its extremely versatile metabolism. C. necator can use hydrogen or formic acid as an energy source, fixes CO₂ via the Calvin-Benson-Bassham (CBB) cycle, and grows on organic acids and sugars. Its tripartite genome is notable for its size and duplications of key genes (CBB cycle, hydrogenases, and nitrate reductases). Little is known about which of these isoenzymes and their cofactors are actually utilized for growth on different substrates. Here, we investigated the energy metabolism of C. necator H16 by growing a barcoded transposon knockout library on succinate, fructose, hydrogen (H₂/CO₂), and formic acid. The fitness contribution of each gene was determined from enrichment or depletion of the corresponding mutants. Fitness analysis revealed that (i) some, but not all, molybdenum cofactor biosynthesis genes were essential for growth on formate and nitrate respiration. (ii) Soluble formate dehydrogenase (FDH) was the dominant enzyme for formate oxidation, not membrane-bound FDH. (iii) For hydrogenases, both soluble and membrane-bound enzymes were utilized for lithoautotrophic growth. (iv) Of the six terminal respiratory complexes in C. necator H16, only some are utilized, and utilization depends on the energy source. (v) Deletion of hydrogenase-related genes boosted heterotrophic growth, and we show that the relief from associated protein cost is responsible for this phenomenon. This study evaluates the contribution of each of C. necator's genes to fitness in biotechnologically relevant growth regimes. Our results illustrate the genomic redundancy of this generalist bacterium and inspire future engineering strategies.

IMPORTANCE The soil bacterium Cupriavidus necator can grow on gas mixtures of CO₂, H₂, and O₂. It also consumes formic acid as carbon and energy source and various other substrates. This metabolic flexibility comes at a price, for example, a comparatively large genome (6.6 Mb) and a significant background expression of lowly utilized genes. In this study, we mutated every non-essential gene in C. necator using barcoded transposons in order to determine their effect on fitness. We grew the mutant library in various trophic conditions including hydrogen and formate as the sole energy source. Fitness analysis revealed which of the various energy-generating iso-enzymes are actually utilized in which condition. For example, only a few of the six terminal respiratory complexes are used, and utilization depends on the substrate. We also show that the protein cost for the various lowly utilized enzymes represents a significant growth disadvantage in specific conditions, offering a route to rational engineering of the genome. All fitness data are available in an interactive app at https://m-jahn.shinyapps.io/ShinyLib/.

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.