A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of Streptococcus pyogenes.

Streptococcus pyogenes is responsible for a range of diseases in humans contributing significantly to morbidity and mortality. Among more than 200 serotypes of S. pyogenes, serotype M1 strains hold the greatest clinical relevance due to their high prevalence in severe human infections. To enhance our understanding of pathogenesis and discovery of potential therapeutic approaches, we have developed the first genome-scale metabolic model (GEM) for a serotype M1 S. pyogenes strain, which we name iYH543. The curation of iYH543 involved cross-referencing a draft GEM of S. pyogenes serotype M1 from the AGORA2 database with gene essentiality and autotrophy data obtained from transposon mutagenesis-based and growth screens. We achieved a 92.6% (503/543 genes) accuracy in predicting gene essentiality and a 95% (19/20 amino acids) accuracy in predicting amino acid auxotrophy. Additionally, Biolog Phenotype microarrays were employed to examine the growth phenotypes of S. pyogenes, which further contributed to the refinement of iYH543. Notably, iYH543 demonstrated 88% accuracy (168/190 carbon sources) in predicting growth on various sole carbon sources. Discrepancies observed between iYH543 and the actual behavior of living S. pyogenes highlighted areas of uncertainty in the current understanding of S. pyogenes metabolism. iYH543 offers novel insights and hypotheses that can guide future research efforts and ultimately inform novel therapeutic strategies.IMPORTANCEGenome-scale models (GEMs) play a crucial role in investigating bacterial metabolism, predicting the effects of inhibiting specific metabolic genes and pathways, and aiding in the identification of potential drug targets. Here, we have developed the first GEM for the S. pyogenes highly virulent serotype, M1, which we name iYH543. The iYH543 achieved high accuracy in predicting gene essentiality. We also show that the knowledge obtained by substituting actual measurement values for iYH543 helps us gain insights that connect metabolism and virulence. iYH543 will serve as a useful tool for rational drug design targeting S. pyogenes metabolism and computational screening to investigate the interplay between inhibiting virulence factor synthesis and growth.

Engineering Escherichia coli for efficient glutathione production.

Glutathione is a tripeptide of excellent value in the pharmaceutical, food, and cosmetic industries that is currently produced during yeast fermentation. In this case, glutathione accumulates intracellularly, which hinders high production. Here, we engineered Escherichia coli for the efficient production of glutathione. A total of 4.3 g/L glutathione was produced by overexpressing gshA and gshB, which encode cysteine glutamate ligase and glutathione synthetase, respectively, and most of the glutathione was excreted into the culture medium. Further improvements were achieved by inhibiting degradation (Δggt and ΔpepT); deleting gor (Δgor), which encodes glutathione oxide reductase; attenuating glutathione uptake (ΔyliABCD); and enhancing cysteine production (PompF-cysE). The engineered strain KG06 produced 19.6 g/L glutathione after 48 h of fed-batch fermentation with continuous addition of ammonium sulfate as the sulfur source. We also found that continuous feeding of glycine had a crucial role for effective glutathione production. The results of metabolic flux and metabolomic analyses suggested that the conversion of O-acetylserine to cysteine is the rate-limiting step in glutathione production by KG06. The use of sodium thiosulfate largely overcame this limitation, increasing the glutathione titer to 22.0 g/L, which is, to our knowledge, the highest titer reported to date in the literature. This study is the first report of glutathione fermentation without adding cysteine in E. coli. Our findings provide a great potential of E. coli fermentation process for the industrial production of glutathione.

Coupling and uncoupling growth and product formation for producing chemicals.

Microbial fermentation employs two strategies: growth- and nongrowth-coupled productions. Stoichiometric metabolic models with flux balance analysis enable pathway engineering to couple target synthesis with growth, yielding numerous successful results. Growth-coupled engineering also contributes to improving bottleneck flux through subsequent adaptive evolution. However, because growth-coupled production inevitably shares resources between biomass and target syntheses, the cost-effective production of bulk chemicals mandates a nongrowth-coupled approach. In such processes, understanding how and when to transition the metabolic state from growth to production modes becomes crucial, as does maintaining cellular activity during the nongrowing state to achieve high productivity. In this paper, we review recent technologies for growth-coupled and nongrowth-coupled production, considering their advantages and disadvantages.

Metabolome analysis of metabolic burden in Escherichia coli caused by overexpression of green fluorescent protein and delta-rhodopsin.

Overexpression of proteins by introducing a DNA vector is among the most important tools for the metabolic engineering of microorganisms such as Escherichia coli. Protein overexpression imposes a burden on metabolism because metabolic pathways must supply building blocks for protein and DNA synthesis. Different E. coli strains have distinct metabolic capacities. In this study, two proteins were overexpressed in four E. coli strains (MG1655(DE3), W3110(DE3), BL21star(DE3), and Rosetta(DE3)), and their effects on metabolic burden were investigated. Metabolomic analysis showed that E. coli strains overexpressing green fluorescent protein had decreased levels of several metabolites, with a positive correlation between the number of reduced metabolites and green fluorescent protein expression levels. Moreover, nucleic acid-related metabolites decreased, indicating a metabolic burden in the E. coli strains, and the growth rate and protein expression levels were improved by supplementation with the five nucleosides. In contrast, two strains overexpressing delta rhodopsin, a microbial membrane rhodopsin from Haloterrigena turkmenica, led to a metabolic burden and decrease in the amino acids Ala, Val, Leu, Ile, Thr, Phe, Asp, and Trp, which are the most frequent amino acids in the delta rhodopsin protein sequence. The metabolic burden caused by protein overexpression was influenced by the metabolic capacity of the host strains and the sequences of the overexpressed proteins. Detailed characterization of the effects of protein expression on the metabolic state of engineered cells using metabolomics will provide insights into improving the production of target compounds.

Effects of n-butanol production on metabolism and the photosystem in Synecococcus elongatus PCC 7942 based on metabolic flux and target proteome analyses.

Although n-butanol (BuOH) is an ideal fuel because of its superior physical properties, it has toxicity to microbes. Previously, a Synechococcus elongatus PCC 7942 derivative strain that produces BuOH from CO2 was developed by introducing six heterologous genes (BUOH-SE strain). To identify the bottleneck in BuOH production, the effects of BuOH production and its toxicity on central metabolism and the photosystem were investigated. Parental (WT) and BUOH-SE strains were cultured under autotrophic conditions. Consistent with the results of a previous study, BuOH production was observed only in the BUOH-SE strain. Isotopically non-stationary 13C-metabolic flux analysis revealed that the CO2 fixation rate was much larger than the BuOH production rate in the BUOH-SE strain (1.70 vs 0.03 mmol gDCW-1 h-1), implying that the carbon flow for BuOH biosynthesis was less affected by the entire flux distribution. No large difference was observed in the flux of metabolism between the WT and BUOH-SE strains. Contrastingly, in the photosystem, the chlorophyll content and maximum O2 evolution rate per dry cell weight of the BUOH-SE strain were decreased to 81% and 43% of the WT strain, respectively. Target proteome analysis revealed that the amounts of some proteins related to antennae (ApcA, ApcD, ApcE, and CpcC), photosystem II (PsbB, PsbU, and Psb28-2), and cytochrome b6f complex (PetB and PetC) in photosystems decreased in the BUOH-SE strain. The activation of photosynthesis would be a novel approach for further enhancing BuOH production in S. elongatus PCC 7942.

Multicolor optogenetics for regulating flux ratio of three glycolytic pathways using EL222 and CcaSR in Escherichia coli.

Optogenetics is an attractive synthetic biology tool for controlling the metabolic flux distribution. Here, we demonstrated optogenetic flux ratio control of glycolytic pathways consisting of the Embden-Meyerhof-Parnas (EMP), pentose phosphate (PP), and Entner-Doudoroff (ED) pathways by illuminating multicolor lights using blue light-responsive EL222 and green/red light-responsive CcaSR in Escherichia coli. EL222 forms a dimer and binds to a particular DNA sequence under blue light; therefore, target gene expression can be reduced or induced by inserting a recognition sequence into its promoter regions. First, a flux ratio between the PP and ED pathways was controlled by blue light using EL222. After blocking the EMP pathway, the EL222-recognition sequence was inserted between the -35 and -10 regions of gnd to repress the PP flux and was also inserted upstream of the -35 region of edd to induce ED flux. After adjusting light intensity, the PP:ED flux ratios were 60:39% and 29:70% under dark and blue light conditions, respectively. Finally, a CcaSR-based pgi expression system was implemented to control the flux ratio between the EMP and PP + ED pathways by illuminating green/red light. The EMP:PP:ED flux ratios were 80:9:11%, 14:35:51%, and 33:5:62% under green, red, and red and blue light, respectively.

Effect of light fluctuations on photosynthesis and metabolic flux in Synechocystis sp. PCC 6803.

In nature, photosynthetic organisms are exposed to fluctuating light, and their physiological systems must adapt to this fluctuation. To maintain homeostasis, these organisms have a light fluctuation photoprotective mechanism, which functions in both photosystems and metabolism. Although the photoprotective mechanisms functioning in the photosystem have been studied, it is unclear how metabolism responds to light fluctuations within a few seconds. In the present study, we investigated the metabolic response of Synechocystis sp. PCC 6803 to light fluctuations using 13 C-metabolic flux analysis. The light intensity and duty ratio were adjusted such that the total number of photons or the light intensity during the low-light phase was equal. Light fluctuations affected cell growth and photosynthetic activity under the experimental conditions. However, metabolic flux distributions and cofactor production rates were not affected by the light fluctuations. Furthermore, the estimated ATP and NADPH production rates in the photosystems suggest that NADPH-consuming electron dissipation occurs under fluctuating light conditions. Although we focused on the water-water cycle as the electron dissipation path, no growth effect was observed in an flv3-disrupted strain under fluctuating light, suggesting that another path contributes to electron dissipation under these conditions.

Functional evaluation of non-oxidative glycolysis in Escherichia coli in the stationary phase under microaerobic conditions.

In microbial bioproduction, CO2 emissions via pyruvate dehydrogenase in the Embden-Meyerhof pathway, which converts glucose to acetyl-CoA, is one of the challenges for enhancing carbon yield. The synthetic non-oxidative glycolysis (NOG) pathway transforms glucose into three acetyl-CoA molecules without CO2 emission, making it an attractive module for metabolic engineering. Because the NOG pathway generates no ATP and NADH, it is expected to use a resting cell reaction. Therefore, it is important to characterize the feasibility of the NOG pathway during stationary phase. Here, we experimentally evaluated the in vivo metabolic flow of the NOG pathway in Escherichia coli. An engineered strain was constructed by introducing phosphoketolase from Bifidobacterium adolescentis into E. coli and by deleting competitive reactions. When the strain was cultured in magnesium-starved medium under microaerobic conditions, the carbon yield of acetate, an end-product of the NOG pathway, was six times higher than that of the control strain harboring an empty vector. Based on the mass balance constraints, the NOG flux was estimated to be between 2.89 and 4.64 mmol g-1 h-1, suggesting that the engineered cells can convert glucose through the NOG pathway with enough activity for bioconversion. Furthermore, to expand the application potential of NOG pathway-implemented strains, the theoretical maximum yields of various useful compounds were calculated using flux balance analysis. This suggests that the theoretical maximum yields of not only acetate but also lactam compounds can be increased by introducing the NOG pathway. This information will help in future applications of the NOG pathway.

Logistic Regression-Guided Identification of Cofactor Specificity-Contributing Residues in Enzyme with Sequence Datasets Partitioned by Catalytic Properties.

Changing the substrate/cofactor specificity of an enzyme requires multiple mutations at spatially adjacent positions around the substrate pocket. However, this is challenging when solely based on crystal structure information because enzymes undergo dynamic conformational changes during the reaction process. Herein, we proposed a method for estimating the contribution of each amino acid residue to substrate specificity by deploying a phylogenetic analysis with logistic regression. Since this method can estimate the candidate amino acids for mutation by ranking, it is readable and can be used in protein engineering. We demonstrated our concept using redox cofactor conversion of the Escherichia coli malic enzyme as a model, which still lacks crystal structure elucidation. The use of logistic regression with amino acid sequences classified by cofactor specificity showed that the NADP+-dependent malic enzyme completely switched cofactor specificity to NAD+ dependence without the need for a practical screening step. The model showed that surrounding residues made a greater contribution to cofactor specificity than those in the interior of the substrate pocket. These residues might be difficult to identify from crystal structure observations. We show that a highly accurate and inferential machine learning model was obtained using amino acid sequences of structurally homologous and functionally distinct enzymes as input data.

Conversion of Mevalonate to Isoprenol Using Light Energy in Escherichia coli without Consuming Sugars for ATP Supply.

Bioconversion of key intermediate metabolites such as mevalonate into various useful chemicals is a promising strategy for microbial production. However, the conversion of mevalonate into isoprenoids requires a supply of adenosine triphosphate (ATP). Light-driven ATP regeneration using microbial rhodopsin is an attractive module for improving the intracellular ATP supply. In the present study, we demonstrated the ATP-consuming conversion of mevalonate to isoprenol using rhodopsin-expressing Escherichia coli cells as a whole-cell catalyst in a medium that does not contain energy cosubstrate, such as glucose. Heterologous genes for the synthesis of isoprenol from mevalonate, which requires three ATP molecules for the series of reactions, and a delta-rhodopsin gene derived from Haloterrigena turkmenica were cointroduced into E. coli. To evaluate the conversion efficiency of mevalonate to isoprenol, the cells were suspended in a synthetic medium containing mevalonate as the sole carbon source and incubated under dark or light illumination (100 µmol m-2 s-1). The specific isoprenol production rates were 10.0 ± 0.9 and 20.4 ± 0.7 µmol gDCW-1 h-1 for dark and light conditions, respectively. The conversion was successfully enhanced under the light condition. Furthermore, the conversion efficiency increased with increasing illumination intensity, suggesting that ATP regenerated by the proton motive force generated by rhodopsin using light energy can drive ATP-consuming reactions in the whole-cell catalyst.

Evolutionary approach for improved proton pumping activity of heterologous rhodopsin expressed in Escherichia coli.

A light-driven ATP regeneration system using rhodopsin has been utilized as a method to improve the production of useful substances by microorganisms. To enable the industrial use of this system, the proton pumping rate of rhodopsin needs to be enhanced. Nonetheless, a method for this enhancement has not been established. In this study, we attempted to develop an evolutionary engineering method to improve the proton-pumping activity of rhodopsins. We first introduced random mutations into delta-rhodopsin (dR) from Haloterrigena turkmenica using error-prone PCR to generate approximately 7000 Escherichia coli strains carrying the mutant dR genes. Rhodopsin-expressing E. coli with enhanced proton pumping activity have significantly increased survival rates in prolonged saline water. Considering this, we enriched the mutant E. coli cells with higher proton pumping rates by selecting populations able to survive starvation under 50 µmol m-2 s-1 at 37 °C. As a result, we successfully identified two strains, in which proton pumping activity was enhanced two-fold by heterologous expression in E. coli in comparison to wild-type strains. The combined approach of survival testing using saline water and evolutionary engineering methods used in this study will contribute greatly to the discovery of a novel rhodopsin with improved proton pumping activity. This will facilitate the utilization of rhodopsin in industrial applications.

Metabolic pathway design for growth-associated phenylalanine production using synthetically designed mutualism.

Combination of growth-associated pathway engineering based on flux balance analysis (FBA) and adaptive laboratory evolution (ALE) is a powerful approach to enhance the production of useful compounds. However, the feasibility of such growth-associated pathway designs depends on the type of target compound. In the present study, FBA predicted a set of gene deletions (pykA, pykF, ppc, zwf, and adhE) that leads to growth-associated phenylalanine production in Escherichia coli. The knockout strain is theoretically enforced to produce phenylalanine only at high growth yields, and could not be applied to the ALE experiment because of a severe growth defect. To overcome this challenge, we propose a novel approach for ALE based on mutualistic co-culture for coupling growth and production, regardless of the growth rate. We designed a synthetic mutualism of a phenylalanine-producing leucine-auxotrophic strain (KF strain) and a leucine-producing phenylalanine-auxotrophic strain (KL strain) and performed an ALE experiment for approximately 160 generations. The evolved KF strain (KF-E strain) grew in a synthetic medium (with glucose as the main carbon source) supplemented with leucine, while severe growth defects were observed in the parental KF strain. The phenylalanine yield of the KF-E strain was 2.3 times higher than that of the KF strain.

Constitutive expression of the global regulator AbrB restores the growth defect of a genome-reduced Bacillus subtilis strain and improves its metabolite production.

Partial bacterial genome reduction by genome engineering can improve the productivity of various metabolites, possibly via deletion of non-essential genome regions involved in undesirable metabolic pathways competing with pathways for the desired end products. However, such reduction may cause growth defects. Genome reduction of Bacillus subtilis MGB874 increases the productivity of cellulases and proteases but reduces their growth rate. Here, we show that this growth defect could be restored by silencing redundant or less important genes affecting exponential growth by manipulating the global transcription factor AbrB. Comparative transcriptome analysis revealed that AbrB-regulated genes were upregulated and those involved in central metabolic pathway and synthetic pathways of amino acids and purine/pyrimidine nucleotides were downregulated in MGB874 compared with the wild-type strain, which we speculated were the cause of the growth defects. By constitutively expressing high levels of AbrB, AbrB regulon genes were repressed, while glycolytic flux increased, thereby restoring the growth rate to wild-type levels. This manipulation also enhanced the productivity of metabolites including γ-polyglutamic acid. This study provides the first evidence that undesired features induced by genome reduction can be relieved, at least partly, by manipulating a global transcription regulation system. A similar strategy could be applied to other genome engineering-based challenges aiming toward efficient material production in bacteria.

Metabolic pathway engineering for the non-growth-associated succinate production in Escherichia coli based on flux solution space.

Non-growth-associated bio-production using microorganisms has the potential to achieve a higher target yield than growth-associated production since the latter approach does not waste the substrate for cell growth. We previously proposed a metabolic pathway engineering method (SSDesign) for non-growth-associated target production based on metabolic flux solution space using elementary mode analysis. SSDesign predicts gene knockout combinations for enforcing cells to produce a target compound under non-growing conditions. For succinate production from glucose in Escherichia coli, gene knockouts of pykA-pykF-sfcA-maeB-zwf and pykA-pykF-sfcA-pntAB-sthA were predicted as candidates. In the present study, to verify the predictions of SSDesign, succinate productivities of these multiple knockout strains were evaluated in the stationary phase under microaerobic conditions. Succinate yields of the BW25113ΔpykAΔpykFΔsfcAΔmaeBΔzwf and BW25113ΔpykAΔpykFΔsfcAΔpntABΔsthA strains were 0.48 and 0.52 mol/mol, respectively, and were higher than that of wild type strain (0.20 mol/mol). The succinate yield of BW25113ΔpykAΔpykFΔsfcAΔpntABΔsthA strain was further improved to 0.66 mol/mol by overexpression of phosphoenolpyruvate carboxylase as a potential bottleneck step in the metabolic pathway.

Optogenetic reprogramming of carbon metabolism using light-powering microbial proton pump systems.

In microbial fermentative production, ATP regeneration, while crucial for cellular processes, conflicts with efficient target chemical production because ATP regeneration exhausts essential carbon sources also required for target chemical biosynthesis. To wrestle with this dilemma, we harnessed the power of microbial rhodopsins with light-driven proton pumping activity to supplement with ATP, thereby facilitating the bioproduction of various chemicals. We first demonstrated a photo-driven ATP supply and redistribution of metabolic carbon flows to target chemical synthesis by installing already-known delta rhodopsin (dR) in Escherichia coli. In addition, we identified novel rhodopsins with higher proton pumping activities than dR, and created an engineered cell for in vivo self-supply of the rhodopsin-activator, all-trans-retinal. Our concept exploiting the light-powering ATP supplier offers a potential increase in carbon use efficiency for microbial productions through metabolic reprogramming.

Acceleration of target production in co-culture by enhancing intermediate consumption through adaptive laboratory evolution.

Co-culture is a promising way to alleviate metabolic burden by dividing the metabolic pathways into several modules and sharing the conversion processes with multiple strains. Since an intermediate is passed from the donor to the recipient via the extracellular environment, it is inevitably diluted. Therefore, enhancing the intermediate consumption rate is important for increasing target productivity. In the present study, we demonstrated the enhancement of mevalonate consumption in Escherichia coli by adaptive laboratory evolution and applied the evolved strain to isoprenol production in an E. coli (upstream: glucose to mevalonate)-E. coli (downstream: mevalonate to isoprenol) co-culture. An engineered mevalonate auxotroph strain was repeatedly sub-cultured in a synthetic medium supplemented with mevalonate, where the mevalonate concentration was decreased stepwise from 100 to 20 µM. In five parallel evolution experiments, all growth rates gradually increased, resulting in five evolved strains. Whole-genome re-sequencing and reverse engineering identified three mutations involved in enhancing mevalonate consumption. After introducing nudF gene for producing isoprenol, the isoprenol-producing parental and evolved strains were respectively co-cultured with a mevalonate-producing strain. At an inoculation ratio of 1:3 (upstream:downstream), isoprenol production using the evolved strain was 3.3 times higher than that using the parental strain.

Recent advances in metabolic engineering-integration of in silico design and experimental analysis of metabolic pathways.

Microorganisms are widely used to produce valuable compounds. Because thousands of metabolic reactions occur simultaneously and many metabolic reactions are related to target production and cell growth, the development of a rational design method for metabolic pathway modification to optimize target production is needed. In this paper, recent advances in metabolic engineering are reviewed, specifically considering computational pathway modification design and experimental evaluation of metabolic fluxes by 13C-metabolic flux analysis. Computational tools for seeking effective gene deletion targets and recruiting heterologous genes are described in flux balance analysis approaches. A kinetic model and adaptive laboratory evolution were applied to identify and eliminate the rate-limiting step in metabolic pathways. Data science-based approaches for process monitoring and control are described to maximize the performance of engineered cells in bioreactors.

Reactor control system in bacterial co-culture based on fluorescent proteins using an Arduino-based home-made device.

BACKGROUND: Co-culture, fermentation with more than two microbial strains, is a potential flexible method for optimizing the metabolic conversion process in bio-production. However, maintaining an ideal population throughout the fermentation process remains a challenge. METHODS AND RESULTS: In this study, we developed a proportional control system for controlling the population ratio of Escherichia coli strains to a set value during continuous co-culture. Two E. coli strains were distinguished by expressing different fluorescent proteins, and their population ratio was determined by culture fluorescence. Furthermore, different types of amino acid auxotrophs were provided to each strain, and among these, growth was controlled by the amino acid concentrations in the feed medium. An Arduino-based device was developed using light-emitting diodes and cadmium sulfide light sensors for the in-line monitoring of culture fluorescence. Two E. coli strains of methionine auxotroph green fluorescent protein (GFP) expressing (met-GFP) strain and arginine auxotroph red fluorescent protein (RFP) expressing (arg-RFP) strain were co-cultured using a jar-fermenter. The amounts of methionine and arginine in the feed medium were altered to guide the population ratio to a set value. During the continuous culture, the population ratio between the met-GFP and arg-RFP strains was successfully maintained at approximately the setpoint values. CONCLUSION: This study demonstrated the development of a home-made device for controlling the reactor of E. coli based on fluorescent proteins using inexpensive parts.

Proteome analysis of response to different spectral light irradiation in Synechocystis sp. PCC 6803.

In cyanobacteria, it is known that the excitation ratios of photosystem (PS) I and PSII changes with the wavelength of irradiated light due to mobile phycobilisome (PBS) and spillover, affecting the photosynthetic ATP/NADPH synthesis ratio and metabolic flux state. However, the mechanisms by which these changes are controlled have not been well studied. In this study, we performed a targeted proteomic analysis of Synechocystis sp. PCC 6803 under different spectral light conditions to clarify the regulation mechanisms of mobile PBS, spillover and metabolisms under different light qualities at the protein level. The results showed an increase in the amount of proteins mainly involved in CO2 fixation under Red1 light conditions with a high specific growth rate, suggesting that the rate of intracellular metabolism is controlled by the rate of carbon uptake, not by changes in the amount of each enzyme. Correlation analysis between protein levels and PSI/PSII excitation ratios revealed that PsbQUY showed high correlations and significantly increased under Blue and Red2 light conditions, where the PSI/PSII excitation ratio was higher due to spillover. In the strains lacking the genes encoding these proteins, a decrease in the PSI/PSII excitation ratio was observed, suggesting that PsbQUY contribute to spillover occurrence. SIGNIFICANCE: In cyanobacteria, the photosynthetic apparatus's responses, such as state transition [mobile PBS and spillover], occur due to the intensity and wavelength of irradiated light, resulting in changes in photosynthetic electron transport and metabolic flux states. Previous studies have analyzed the response of Synechocystis sp. PCC 6803 to light intensity from various directions, but only spectroscopic analysis of the photosynthetic apparatus has been done on the response to changes in the wavelength of irradiated light. This study analyzed the response mechanisms of mobile PBS, spillover, photosynthetic, and metabolic systems in Synechocystis sp. PCC 6803 under six different spectral light conditions by a targeted proteomic analysis. As a result, many proteins were successfully quantified, and the metabolic enzymes and photosynthetic apparatus were analyzed using an integrated approach. Principal component and correlation analyses and volcano plots revealed that the PSII subunits PsbQ, PsbU, and PsbY have a strong correlation with the PSI/PSII excitation ratio and contribute to spillover occurrence. Thus, statistical analysis based on proteome data revealed that PsbQ, PsbU, and PsbY are involved in spillover, as revealed by spectroscopic analysis.

Soft-sensor development for monitoring the lysine fermentation process.

Monitoring cell growth and target production in working fermentors is important for stabilizing high level production. In this study, we developed a novel soft sensor for estimating the concentration of a target product (lysine), substrate (sucrose), and bacterial cell in commercially working fermentors using machine learning combined with available on-line process data. The lysine concentration was accurately estimated in both linear and nonlinear models; however, the nonlinear models were also suitable for estimating the concentrations of sucrose and bacterial cells. Data enhancement by time interpolation improved the model prediction accuracy and eliminated unnecessary fluctuations. Furthermore, the soft sensor developed based on the dataset of the same process parameters in multiple fermentor tanks successfully estimated the fermentation behavior of each tank. Machine learning-based soft sensors may represent a novel monitoring system for digital transformation in the field of biotechnological processes.