Engineered polymer nanoparticles as artificial chaperones facilitating the selective refolding of denatured enzymes.

Molecular chaperones assist in protein refolding by selectively binding to proteins in their nonnative states. Despite progress in creating artificial chaperones, these designs often have a limited range of substrates they can work with. In this paper, we present molecularly imprinted flexible polymer nanoparticles (nanoMIPs) designed as customizable biomimetic chaperones. We used model proteins such as cytochrome c, laccase, and lipase to screen polymeric monomers and identify the most effective formulations, offering tunable charge and hydrophobic properties. Utilizing a dispersed phase imprinting approach, we employed magnetic beads modified with destabilized whole-protein as solid-phase templates. This process involves medium exchange facilitated by magnetic pulldowns, resulting in the synthesis of nanoMIPs featuring imprinted sites that effectively mimic chaperone cavities. These nanoMIPs were able to selectively refold denatured enzymes, achieving up to 86.7% recovery of their activity, significantly outperforming control samples. Mechanistic studies confirmed that nanoMIPs preferentially bind denatured rather than native enzymes, mimicking natural chaperone interactions. Multifaceted analyses support the functionality of nanoMIPs, which emulate the protective roles of chaperones by selectively engaging with denatured proteins to inhibit aggregation and facilitate refolding. This approach shows promise for widespread use in protein recovery within biocatalysis and biomedicine.

Computational prediction of interactions between Paxlovid and prescription drugs.

Pfizer's Paxlovid has recently been approved for the emergency use authorization (EUA) from the US Food and Drug Administration (FDA) for the treatment of mild-to-moderate COVID-19. Drug interactions can be a serious medical problem for COVID-19 patients with underlying medical conditions, such as hypertension and diabetes, who have likely been taking other drugs. Here, we use deep learning to predict potential drug-drug interactions between Paxlovid components (nirmatrelvir and ritonavir) and 2,248 prescription drugs for treating various diseases.

Biohybrid CO2 electrolysis for the direct synthesis of polyesters from CO2.

Converting anthropogenic CO2 to value-added products using renewable energy has received much attention to achieve a sustainable carbon cycle. CO2 electrolysis has been extensively investigated, but the products have been limited to some C1-3 products. Here, we report the integration of CO2 electrolysis with microbial fermentation to directly produce poly-3-hydroxybutyrate (PHB), a microbial polyester, from gaseous CO2 on a gram scale. This biohybrid system comprises electrochemical conversion of CO2 to formate on Sn catalysts deposited on a gas diffusion electrode (GDE) and subsequent conversion of formate to PHB by Cupriavidus necator cells in a fermenter. The electrolyzer and the electrolyte solution were optimized for this biohybrid system. In particular, the electrolyte solution containing formate was continuously circulated through both the CO2 electrolyzer and the fermenter, resulting in the efficient accumulation of PHB in C. necator cells, reaching a PHB content of 83% of dry cell weight and producing 1.38 g PHB using 4 cm2 Sn GDE. This biohybrid system was further modified to enable continuous PHB production operated at a steady state by adding fresh cells and removing PHB. The strategies employed for developing this biohybrid system will be useful for establishing other biohybrid systems producing chemicals and materials directly from gaseous CO2.

An operator-based expression toolkit for Bacillus subtilis enables fine-tuning of gene expression and biosynthetic pathway regulation.

SignificanceA gene regulatory system is an important tool for the engineering of biosynthetic pathways of organisms. Here, we report the development of an inducible-ON/OFF regulatory system using a malO operator as a key element. We identified and modulated sequence, position, numbers, and spacing distance of malO operators, generating a series of activating or repressive promoters with tunable strength. The stringency and robustness are both guaranteed in this system, a maximal induction factor of 790-fold was achieved, and nine proteins from different organisms were expressed with high yields. This system can be utilized as a gene switch, promoter enhancer, or metabolic valve in synthetic biology applications. This operator-based engineering strategy can be employed for developing similar regulatory systems in different microorganisms.

Complete microbial synthesis of crocetin and crocins from glycerol in Escherichia coli.

BACKGROUND: Crocin, a glycosylated apocarotenoid pigment predominantly found in saffron, has garnered significant interest in the field of biotechnology for its bioactive properties. Traditional production of crocins and their aglycone, crocetin, typically involves extraction from crocin-producing plants. This study aimed to develop an alternative biosynthetic method for these compounds by engineering the metabolic pathways of zeaxanthin, crocetin, and crocin in Escherichia coli strains. RESULTS: Employing a series of genetic modifications and the strategic overexpression of key enzymes, we successfully established a complete microbial pathway for synthesizing crocetin and four glycosylated derivatives of crocetin, utilizing glycerol as the primary carbon source. The overexpression of zeaxanthin cleavage dioxygenase and a novel variant of crocetin dialdehyde dehydrogenase resulted in a notable yield of crocetin (34.77 ± 1.03 mg/L). Further optimization involved the overexpression of new types of crocetin and crocin-2 glycosyltransferases, facilitating the production of crocin-1 (6.29 ± 0.19 mg/L), crocin-2 (5.29 ± 0.24 mg/L), crocin-3 (1.48 ± 0.10 mg/L), and crocin-4 (2.72 ± 0.13 mg/L). CONCLUSIONS: This investigation introduces a pioneering and integrated microbial synthesis method for generating crocin and its derivatives, employing glycerol as a sustainable carbon feedstock. The substantial yields achieved highlight the commercial potential of microbial-derived crocins as an eco-friendly alternative to plant extraction methods. The development of these microbial processes not only broadens the scope for crocin production but also suggests significant implications for the exploitation of bioengineered compounds in pharmaceutical and food industries.

Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individual bacterial cell in its native state.

Polyhydroxyalkanoates (PHAs) are biodegradable polyesters that are intracellularly accumulated as distinct insoluble granules by various microorganisms. PHAs have attracted much attention as sustainable substitutes for petroleum-based plastics. However, the formation of PHA granules and their characteristics, such as localization, volume, weight, and density of granules, in an individual live bacterial cell are not well understood. Here, we report the results of three-dimensional (3D) quantitative label-free analysis of PHA granules in individual live bacterial cells through measuring the refractive index distributions by optical diffraction tomography (ODT). The formation and growth of PHA granules in the cells of Cupriavidus necator, the best-studied native PHA producer, and recombinant Escherichia coli harboring C. necator poly(3-hydroxybutyrate) (PHB) biosynthesis pathway are comparatively examined. Through the statistical ODT analyses of the bacterial cells, the distinctive characteristics for density and localization of PHB granules in vivo could be observed. The PHB granules in recombinant E. coli show higher density and localization polarity compared with those of C. necator, indicating that polymer chains are more densely packed and granules tend to be located at the cell poles, respectively. The cells were investigated in more detail through real-time 3D analyses, showing how differently PHA granules are processed in relation to the cell division process in native and nonnative PHA-producing strains. We also show that PHA granule-associated protein PhaM of C. necator plays a key role in making these differences between C. necator and recombinant E. coli strains. This study provides spatiotemporal insights into PHA accumulation inside the native and recombinant bacterial cells.

Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay.

The COVID-19 pandemic caused by SARS-CoV-2 is an unprecedentedly significant health threat, prompting the need for rapidly developing antiviral drugs for the treatment. Drug repurposing is currently one of the most tangible options for rapidly developing drugs for emerging and reemerging viruses. In general, drug repurposing starts with virtual screening of approved drugs employing various computational methods. However, the actual hit rate of virtual screening is very low, and most of the predicted compounds are false positives. Here, we developed a strategy for virtual screening with much reduced false positives through incorporating predocking filtering based on shape similarity and postdocking filtering based on interaction similarity. We applied this advanced virtual screening approach to repurpose 6,218 approved and clinical trial drugs for COVID-19. All 6,218 compounds were screened against main protease and RNA-dependent RNA polymerase of SARS-CoV-2, resulting in 15 and 23 potential repurposed drugs, respectively. Among them, seven compounds can inhibit SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, show anti-SARS-CoV-2 activities in human lung cells, Calu-3. Notably, the activity of omipalisib is 200-fold higher than that of remdesivir in Calu-3. Furthermore, three drug combinations, omipalisib/remdesivir, tipifarnib/omipalisib, and tipifarnib/remdesivir, show strong synergistic effects in inhibiting SARS-CoV-2. Such drug combination therapy improves antiviral efficacy in SARS-CoV-2 infection and reduces the risk of each drug's toxicity. The drug repurposing strategy reported here will be useful for rapidly developing drugs for treating COVID-19 and other viruses.

DeepTFactor: A deep learning-based tool for the prediction of transcription factors.

A transcription factor (TF) is a sequence-specific DNA-binding protein that modulates the transcription of a set of particular genes, and thus regulates gene expression in the cell. TFs have commonly been predicted by analyzing sequence homology with the DNA-binding domains of TFs already characterized. Thus, TFs that do not show homologies with the reported ones are difficult to predict. Here we report the development of a deep learning-based tool, DeepTFactor, that predicts whether a protein in question is a TF. DeepTFactor uses a convolutional neural network to extract features of a protein. It showed high performance in predicting TFs of both eukaryotic and prokaryotic origins, resulting in F1 scores of 0.8154 and 0.8000, respectively. Analysis of the gradients of prediction score with respect to input suggested that DeepTFactor detects DNA-binding domains and other latent features for TF prediction. DeepTFactor predicted 332 candidate TFs in Escherichia coli K-12 MG1655. Among them, 84 candidate TFs belong to the y-ome, which is a collection of genes that lack experimental evidence of function. We experimentally validated the results of DeepTFactor prediction by further characterizing genome-wide binding sites of three predicted TFs, YqhC, YiaU, and YahB. Furthermore, we made available the list of 4,674,808 TFs predicted from 73,873,012 protein sequences in 48,346 genomes. DeepTFactor will serve as a useful tool for predicting TFs, which is necessary for understanding the regulatory systems of organisms of interest. We provide DeepTFactor as a stand-alone program, available at https://bitbucket.org/kaistsystemsbiology/deeptfactor.

Energy, Exergetic, and Thermoeconomic Analyses of Hydrogen-Fueled 1-kW Proton-Exchange Membrane Fuel Cell.

Exergy analysis evaluates the efficiency of system components by quantifying the rate of entropy generation. In general, the exergy destruction rate or irreversibility rate was directly obtained through the exergy balance equation. However, this method cannot determine the origin of the component's entropy generation rate, which is a very important factor in system design and improvement. In this study, a thorough energy, exergy, and thermoeconomic analysis of a proton-exchange membrane fuel cell (PEMFC) was performed, providing the heat transfer rate, entropy generation rate, and cost loss rate of each component. The irreversibility rate of each component was obtained by the Gouy-Stodola theorem. Detailed and extensive exergy and thermoeconomic analyses of the PEMFC system determined that water cooling units experience the greatest heat transfer among the components in the studied PEMFC system, resulting in the greatest irreversibility and, thus, the greatest monetary flow loss.

Can microbes be harnessed to reduce atmospheric loads of greenhouse gases?

Reducing atmospheric loads of greenhouse gases (GHGs), especially CO2 and CH4 , has been considered the key to alleviating global crises we are facing, such as climate change, sea level elevation and ocean acidification. To this end, development of strategies and technologies for carbon capture, sequestration and utilization (CCSU) is urgently needed. Although physicochemical methods have been the most actively studied in the early stages of developing CCSU technologies, there have recently been growing interests in developing microbe-based CCSU processes. In this article, we discuss advantages of microbe-based CCSU technologies over physicochemical approaches and even plant-based approaches. Next, various parts of the global carbon cycle where microorganisms can contribute, such as sequestering atmospheric GHGs, facilitating the carbon cycle, and slowing down the depletion of carbon reservoirs are described, emphasizing the impacts of microbes on the carbon cycle. Strategies to upgrade microbes and increase their performance in assimilating GHGs or converting GHGs to value-added chemicals are also provided. Moreover, several examples of exploiting microbes to address environmental crises are discussed. Finally, we discuss things to overcome in microbe-based CCSU technologies and provide future perspectives.

Metabolic engineering of Corynebacterium glutamicum for the high-level production of valerolactam, a nylon-5 monomer.

Valerolactam (VL) is an important precursor chemical for nylon-5 and nylon 6,5. It has been produced by petroleum-based route involving harsh reaction conditions and generating toxic wastes. Here, we report the complete biosynthesis of VL by metabolically engineered Corynebacterium glutamicum overproducing L-lysine. The pathway comprising L-lysine monooxygenase (davB) and 5-aminovaleramide amidohydrolase (davA) from Pseudomonas putida, and ß-alanine CoA transferase (act) from Clostridium propionicum was introduced into the C. glutamicum GA16 strain. To increase the VL flux, competitive pathways predicted from sRNA knockdown target screening were deleted. This engineered C. glutamicum strain produced VL as a major product, but still secreted significant amount of its precursor, 5-aminovaleric acid (5AVA). To circumvent this problem, putative 5AVA transporter genes were screened and engineered in the genome, thereby reuptaking 5AVA excreted. Also, multiple copies of the act gene were integrated into the genome to strengthen the conversion of 5AVA to VL. The final VL10 (pVL1) strain was constructed by enhancing glucose uptake system, which produced 9.68 g/L of VL in flask culture. Fed-batch fermentation of the VL10 (pVL1) strain produced 76.1 g/L of VL from glucose with the yield and productivity of 0.28 g/g and 0.99 g/L/h, respectively, showcasing a high potential for bio-based production of VL from renewable resources.

Improved terephthalic acid production from p-xylene using metabolically engineered Pseudomonas putida.

Terephthalic acid (TPA) is an important commodity chemical used as a monomer of polyethylene terephthalate (PET). Since a large quantity of PET is routinely manufactured and consumed worldwide, the development of sustainable biomanufacturing processes for its monomers (i.e. TPA and ethylene glycol) has recently gained much attention. In a previous study, we reported the development of a metabolically engineered Escherichia coli strain producing 6.7 g/L of TPA from p-xylene (pX) with a productivity and molar conversion yield of 0.278 g/L/h and 96.7 mol%, respectively. Here, we report metabolic engineering of Pseudomonas putida KT2440, a microbial chassis particularly suitable for the synthesis of aromatic compounds, for improved biocatalytic conversion of pX to TPA. To develop a plasmid-free, antibiotic-free, and inducer-free biocatalytic process for cost-competitive TPA production, all heterologous genes required for the synthetic pX-to-TPA bioconversion pathway were integrated into the chromosome of P. putida KT2440 by RecET-based markerless recombineering and overexpressed under the control of constitutive promoters. Next, TPA production was enhanced by integrating multiple copies of the heterologous genes to the ribosomal RNA genes through iteration of recombineering-based random integration and subsequent screening of high-performance strains. Finally, fed-batch fermentation process was optimized to further improve the performance of the engineered P. putida strain. As a result, 38.25 ± 0.11 g/L of TPA was produced from pX with a molar conversion yield of 99.6 ± 0.6%, which is equivalent to conversion of 99.3 ± 0.8 g pX to 154.6 ± 0.5 g TPA. This superior pX-to-TPA biotransformation process based on the engineered P. putida strain will pave the way to the commercial biomanufacturing of TPA in an industrial scale.

Deep learning for metabolic pathway design.

The establishment of a bio-based circular economy is imperative in tackling the climate crisis and advancing sustainable development. In this realm, the creation of microbial cell factories is central to generating a variety of chemicals and materials. The design of metabolic pathways is crucial in shaping these microbial cell factories, especially when it comes to producing chemicals with yet-to-be-discovered biosynthetic routes. To aid in navigating the complexities of chemical and metabolic domains, computer-supported tools for metabolic pathway design have emerged. In this paper, we evaluate how digital strategies can be employed for pathway prediction and enzyme discovery. Additionally, we touch upon the recent strides made in using deep learning techniques for metabolic pathway prediction. These computational tools and strategies streamline the design of metabolic pathways, facilitating the development of microbial cell factories. Leveraging the capabilities of deep learning in metabolic pathway design is profoundly promising, potentially hastening the advent of a bio-based circular economy.

Metabolic engineering of Escherichia coli for the production of an antifouling agent zosteric acid.

Zosteric acid (ZA) is a Zostera species-derived, sulfated phenolic acid compound with antifouling activity and has gained much attention due to its nontoxic and biodegradable characteristics. However, the yield of Zostera species available for ZA extraction is limited by natural factors, such as season, latitude, light, and temperature. Here we report the development of metabolically engineered Escherichia coli strains capable of producing ZA from glucose and glycerol. First, intracellular availability of the sulfur donor 3'-phosphoadenosine-5'-phosphosulfate (PAPS) was enhanced by knocking out the cysH gene responsible for PAPS consumption and overexpressing the genes required for PAPS biosynthesis. Co-overexpression of the genes encoding tyrosine ammonia-lyase, sulfotransferase 1A1, ATP sulfurylase, and adenosine 5'-phosphosulfate kinase constructed ZA producing strain with enhanced PAPS supply. Second, the feedback-resistant forms of aroG and tyrA genes (encoding 3-deoxy-d-arabinoheptulosonate 7-phosphate synthase and chorismate mutase, respectively) were overexpressed to relieve the feedback regulation of L-tyrosine biosynthesis. Third, the pykA gene involved in phosphoenolpyruvate-consuming reaction, the regulator gene tyrR, the competing pathway gene pheA, and the ptsHIcrr genes essential for the PEP:carbohydrate phosphotransferase system were deleted. Moreover, all genes involved in the shikimate pathway and the talA, tktA, and tktB genes in the pentose phosphate pathway were examined for ZA production. The PTS-independent glucose uptake system, the expression vector system, and the carbon source were also optimized. As a result, the best-performing strain successfully produced 1.52 g L-1 ZA and 1.30 g L-1p-hydroxycinnamic acid from glucose and glycerol in a 700 mL fed-batch bioreactor.

Efforts to install a heterologous Wood-Ljungdahl pathway in Clostridium acetobutylicum enable the identification of the native tetrahydrofolate (THF) cycle and result in early induction of solvents.

Here, we report the construction of a Clostridium acetobutylicum strain ATCC 824 (pCD07239) by heterologous expression of carbonyl branch genes (CD630_0723∼CD630_0729) from Clostridium difficile, aimed at installing a heterologous Wood-Ljungdahl pathway (WLP). As part of this effort, in order to validate the methyl branch of the WLP in the C. acetobutylicum, we performed 13C-tracing analysis on knockdown mutants of four genes responsible for the formation of 5-methyl-tetrahydrofolate (5-methyl-THF) from formate: CA_C3201, CA_C2310, CA_C2083, and CA_C0291. While C. acetobutylicum 824 (pCD07239) could not grow autotrophically, in heterotrophic fermentation, it began producing butanol at the early growth phase (OD600 of 0.80; 0.162 g/L butanol). In contrast, solvent production in the parent strain did not begin until the early stationary phase (OD600 of 7.40). This study offers valuable insights for future research on biobutanol production during the early growth phase.

Metabolic engineering of Mannheimia succiniciproducens for malic acid production using dimethylsulfoxide as an electron acceptor.

Microbial production of various TCA intermediates and related chemicals through the reductive TCA cycle has been of great interest. However, rumen bacteria that naturally possess strong reductive TCA cycle have been rarely studied to produce these chemicals, except for succinic acid, due to their dependence on fumarate reduction to transport electrons for ATP synthesis. In this study, malic acid (MA), a dicarboxylic acid of industrial importance, was selected as a target chemical for mass production using Mannheimia succiniciproducens, a rumen bacterium possessing a strong reductive branch of the TCA cycle. The metabolic pathway was reconstructed by eliminating fumarase to prevent MA conversion to fumarate. The respiration system of M. succiniciproducens was reconstructed by introducing the Actinobacillus succinogenes dimethylsulfoxide (DMSO) reductase to improve cell growth using DMSO as an electron acceptor. Also, the cell membrane was engineered by employing Pseudomonas aeruginosa cis-trans isomerase to enhance MA tolerance. High inoculum fed-batch fermentation of the final engineered strain produced 61 g/L of MA with an overall productivity of 2.27 g/L/h, which is the highest MA productivity reported to date. The systems metabolic engineering strategies reported in this study will be useful for developing anaerobic bioprocesses for the production of various industrially important chemicals.

Glutaric acid production by systems metabolic engineering of an l-lysine-overproducing Corynebacterium glutamicum.

There is increasing industrial demand for five-carbon platform chemicals, particularly glutaric acid, a widely used building block chemical for the synthesis of polyesters and polyamides. Here we report the development of an efficient glutaric acid microbial producer by systems metabolic engineering of an l-lysine-overproducing Corynebacterium glutamicum BE strain. Based on our previous study, an optimal synthetic metabolic pathway comprising Pseudomonas putida l-lysine monooxygenase (davB) and 5-aminovaleramide amidohydrolase (davA) genes and C. glutamicum 4-aminobutyrate aminotransferase (gabT) and succinate-semialdehyde dehydrogenase (gabD) genes, was introduced into the C. glutamicum BE strain. Through system-wide analyses including genome-scale metabolic simulation, comparative transcriptome analysis, and flux response analysis, 11 target genes to be manipulated were identified and expressed at desired levels to increase the supply of direct precursor l-lysine and reduce precursor loss. A glutaric acid exporter encoded by ynfM was discovered and overexpressed to further enhance glutaric acid production. Fermentation conditions, including oxygen transfer rate, batch-phase glucose level, and nutrient feeding strategy, were optimized for the efficient production of glutaric acid. Fed-batch culture of the final engineered strain produced 105.3 g/L of glutaric acid in 69 h without any byproduct. The strategies of metabolic engineering and fermentation optimization described here will be useful for developing engineered microorganisms for the high-level bio-based production of other chemicals of interest to industry.

Media Coverage of Senior and Celebrity Suicides and Its Effects on Copycat Suicides among Seniors.

This study examined whether suicide rates in the elderly population are associated with media coverage of senior or celebrity suicides. Analyzing data from 2012 to 2015, we found that seniors were likely to be more influenced by media coverage of senior suicides than by celebrity suicides. Furthermore, the effects of media coverage of senior suicides were more significant when the reported reason was either health (mental or physical problems) or financial issues, such as poverty than other reasons.

Structural Insights into Polyhydroxyalkanoates Biosynthesis.

Polyhydroxyalkanoates (PHAs) are diverse biopolyesters produced by numerous microorganisms and have attracted much attention as a substitute for petroleum-based polymers. Despite several decades of study, the detailed molecular mechanisms of PHA biosynthesis have remained unknown due to the lack of structural information on the key PHA biosynthetic enzyme PHA synthase. The recently determined crystal structure of PHA synthase, together with the structures of acetyl-coenzyme A (CoA) acetyltransferase and reductase, have changed this situation. Structural and biochemical studies provided important clues for the molecular mechanisms of each enzyme as well as the overall mechanism of PHA biosynthesis from acetyl-CoA. This new information and knowledge is expected to facilitate production of designed novel PHAs and also enhanced production of PHAs.

Light-Driven Ammonia Production by Azotobacter vinelandii Cultured in Medium Containing Colloidal Quantum Dots.

There is an evergrowing demand for environment-friendly processes to synthesize ammonia (NH3) from atmospheric nitrogen (N2). Although diazotrophic N2 fixation represents an undeniably "green" process of NH3 synthesis, the slow reaction rate makes it less suitable for industrially meaningful large-scale production. Here, we report the photoinduced N2 fixation using a hybrid system composed of colloidal quantum dots (QDs) and aerobic N2-fixing bacteria, Azotobacter vinelandii. Compared to the case where A. vinelandii cells are simply mixed with QDs, NH3 production increases significantly when A. vinelandii cells are cultured in the presence of core/shell InP/ZnSe QDs. During the cell culture of A. vinelandii, the cellular uptake of QDs is facilitated in the exponential growth phase. Experimental results as well as theoretical calculations indicate that the photoexcited electrons in QDs within A. vinelandii cells are directly transferred to MoFe protein, the catalytic component of nitrogenase. We also observe that the excess amount of QDs left on the outer surface of A. vinelandii disrupts the cellular membrane, leading to the decrease in NH3 production due to the deactivation of nitrogenase. The successful uptake of QDs in QD-A. vinelandii hybrid with minimal amount of QDs on the outer surface of the bacteria is key to efficient photosensitized NH3 production. The comprehensive understanding of the QD-bacteria interface paves an avenue to novel and efficient nanobiohybrid systems for chemical production.