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.

From sustainable feedstocks to microbial foods.

Climate change-induced alterations in weather patterns, such as frequent and severe heatwaves, cold waves, droughts, floods, heavy rain and storms, are reducing crop yields and agricultural productivity. At the same time, greenhouse gases arising from food production and supply account for almost 30% of anthropogenic emissions. This vicious circle is producing a global food crisis. Sustainable food resources and production systems are needed now, and microbial foods are one possible solution. In this Perspective, we highlight the most promising technologies, and carbon and energy sources, for microbial food production.

Metabolic engineering and fermentation of microorganisms for carotenoids production.

Carotenoids are natural pigments that exhibit a wide range of red, orange, and yellow colors and are extensively used in the food, nutraceuticals, cosmetics, and aquaculture industries. While advances in systems metabolic engineering have established a foundation for constructing carotenoid-producing microbial cell factories at a laboratory scale, translating these technologies to industrial scales remains a big challenge. Moreover, there is a need to devise cost-effective methods for downstream processing and purification of carotenoids. In this review, we discuss recent strategies in metabolic engineering, such as metabolic flux optimization, enzyme assembly, and storage capacity engineering, aimed at constructing high-performance carotenoid-producing microbial strains. We also review recent approaches for cost-effective downstream processing and purification of carotenoids.

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data.

BACKGROUND: Oncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to the large number of metabolites in a cell and the presence of multiple genes associated with cancer development. RESULTS: Here we report the development of a computational workflow that predicts metabolite-gene-pathway sets. Metabolite-gene-pathway sets present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate metabolite-gene-pathway sets. A GEM is a computational model that predicts reaction fluxes at a genome scale and can be constructed in a cell-specific manner by using omics data. The computational workflow is first validated by comparing the resulting metabolite-gene pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from acute myeloid leukemia and renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the metabolite-gene-pathway sets predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting metabolite-gene-pathway sets is also discussed. CONCLUSIONS: Validation of the metabolite-gene-pathway set-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting metabolite-gene-pathway sets will help identify novel oncometabolites and also suggest cancer treatment strategies.

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.

Observing growth and interfacial dynamics of nanocrystalline ice in thin amorphous ice films.

Ice crystals at low temperatures exhibit structural polymorphs including hexagonal ice, cubic ice, or a hetero-crystalline mixture of the two phases. Despite the significant implications of structure-dependent roles of ice, mechanisms behind the growths of each polymorph have been difficult to access quantitatively. Using in-situ cryo-electron microscopy and computational ice-dynamics simulations, we directly observe crystalline ice growth in an amorphous ice film of nanoscale thickness, which exhibits three-dimensional ice nucleation and subsequent two-dimensional ice growth. We reveal that nanoscale ice crystals exhibit polymorph-dependent growth kinetics, while hetero-crystalline ice exhibits anisotropic growth, with accelerated growth occurring at the prismatic planes. Fast-growing facets are associated with low-density interfaces that possess higher surface energy, driving tetrahedral ordering of interfacial H2O molecules and accelerating ice growth. These findings, based on nanoscale observations, improve our understanding on early stages of ice formation and mechanistic roles of the ice interface.

Enhanced Photocatalytic Oxygen Evolution Using Copper-Coordinated Perylene Diimide Nanorod Assemblies.

A crystalline supramolecular photocatalyst is prepared through metal-induced self-assembly of perylene diimide with imidazole groups at the imide position (PDI-Hm). Exploiting the metal-coordination ability of imidazole, a crystalline assembly of copper-coordinated PDI-Hm (CuPDI-Hm) in a nanorod shape is prepared which displays an outstanding photocatalytic oxygen evolution rate of 25,900 µmol g-1 h-1 without additional co-catalysts. The imidazole-copper coordination, along with π-π stacking of PDI frameworks, guides the arrangement of PDI-Hm molecules to form highly crystalline assemblies. The coordination of copper also modulates the size of the CuPDI-Hm supramolecular assembly by regulating the nucleation and growth processes. Furthermore, the imidazole-copper coordination constructs the electric field within the PDI-Hm assembly, hindering the recombination of photo-induced charges to enhance the photoelectric/photocatalytic activity when compared to Cu-free PDI-Hm assemblies. Small CuPDI-Hm assembly exhibits higher photocatalytic activity due to their larger surface area and reduced light scattering. Together, the Cu-imidazole coordination presents a facile way for fabricating size-controlled crystalline PDI assemblies with built-in electric field enhancing photoelectric and photocatalytic activities substantially.

Functional annotation of enzyme-encoding genes using deep learning with transformer layers.

Functional annotation of open reading frames in microbial genomes remains substantially incomplete. Enzymes constitute the most prevalent functional gene class in microbial genomes and can be described by their specific catalytic functions using the Enzyme Commission (EC) number. Consequently, the ability to predict EC numbers could substantially reduce the number of un-annotated genes. Here we present a deep learning model, DeepECtransformer, which utilizes transformer layers as a neural network architecture to predict EC numbers. Using the extensively studied Escherichia coli K-12 MG1655 genome, DeepECtransformer predicted EC numbers for 464 un-annotated genes. We experimentally validated the enzymatic activities predicted for three proteins (YgfF, YciO, and YjdM). Further examination of the neural network's reasoning process revealed that the trained neural network relies on functional motifs of enzymes to predict EC numbers. Thus, DeepECtransformer is a method that facilitates the functional annotation of uncharacterized genes.

Sustainable production and degradation of plastics using microbes.

Plastics are indispensable in everyday life and industry, but the environmental impact of plastic waste on ecosystems and human health is a huge concern. Microbial biotechnology offers sustainable routes to plastic production and waste management. Bacteria and fungi can produce plastics, as well as their constituent monomers, from renewable biomass, such as crops, agricultural residues, wood and organic waste. Bacteria and fungi can also degrade plastics. We review state-of-the-art microbial technologies for sustainable production and degradation of bio-based plastics and highlight the potential contributions of microorganisms to a circular economy for plastics.

Genome-wide identification of overexpression and downregulation gene targets based on the sum of covariances of the outgoing reaction fluxes.

In metabolic engineering, predicting gene overexpression targets remains challenging because both endogenous and heterologous genes in a large metabolic space can be candidates, in contrast to gene knockout targets that are confined to endogenous genes. We report the development of iBridge that identifies positive and negative metabolites exerting positive and negative impacts on product formation, respectively, based on the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Then, "bridge" reactions converting negative metabolites to positive metabolites are identified as overexpression targets, while the opposites as downregulation targets. Using iBridge, overexpression and downregulation targets are suggested for the production of 298 chemicals and validated for 36 chemicals experimentally demonstrated in previous studies. Finally, iBridge is employed to engineer Escherichia coli strains capable of producing 10.3 g/L of D-panthenol, a compound not previously produced, as well as putrescine and 4-hydroxyphenyllactate at enhanced titers, 63.7 and 8.3 g/L, respectively.

Do media coverage of suicides and search frequency on suicides predict the number of tweets seeking others for a suicide pact?

We examined whether media coverage of suicides and frequencies of searching for suicide methods or suicide pacts predicted the number of users posting tweets seeking others for a suicide pact. Analyses of 6,119 tweets containing "suicide pact" posted on Twitter during a 6-month period revealed that the number of users posting tweets seeking others for a suicide pact had a positive association with media coverage of celebrity suicides, but not with that of suicide pact victims, and a greater positive association with the search frequency for suicide methods than for suicide pacts. We found that the search frequency on suicide methods was positively associated with media coverage of celebrity suicides, while that on suicide pacts was more strongly related to media coverage of suicide pacts.

Recent advances in systems metabolic engineering.

Systems metabolic engineering, which integrates metabolic engineering with systems biology, synthetic biology, and evolutionary engineering, has revolutionized the sustainable production of fuels and materials through the creation of efficient microbial cell factories. Recent advancements in systems metabolic engineering targeting different biological components of the host cell have enabled the creation of highly productive microbial cell factories. This article provides a review of the recent tools and strategies used for enzyme-, genetic module-, pathway-, flux-, genome-, and cell-level engineering, supported by illustrative examples. Furthermore, we highlight recent trends in systems metabolic engineering, which involve the application of multiple tools discussed in this review. Finally, the paper addresses the challenges and perspectives of transitioning academic-level metabolic engineering studies to commercial-scale production.

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.

Rh-coordinated histidyl bolaamphiphile assembly: a catalyst for the isomerization of cis-stilbene and cis-alkene.

In this study, we present a colloidal assembly of histidyl bolaamphiphiles whose imidazoles coordinate with rhodium ions (HisC7[Rh]) to exhibit catalytic isomerization activity for cis-stilbene and cis-alkene molecules. The histidyl bolaamphiphiles self-assemble to form a soft scaffold that functions analogously to an apoenzyme. This scaffold exposes multiple histidyl imidazoles and carboxylates on its surface, to which rhodium ions bind, generating catalytically active sites. The Rh coordination with the biochemical functional groups was verified through comprehensive vibrational spectroscopy and calorimetry. The colloidal HisC7[Rh] demonstrated a significant catalytic effect on the isomerization of cis- to trans-stilbene under mild H2 conditions, resulting in 69% yield of trans-stilbene. In contrast, when Rh(cod)2BF4 was employed as a control catalyst, only the hydrogenated products of bibenzyl were obtained. These findings underscore the crucial role of histidyl motifs in exhibiting unique catalytic isomerization activity through the coordination with Rh. The catalytic activity of HisC7[Rh] is governed by several factors, such as rhodium content, solvent composition, temperature, and H2 pressure. Moreover, HisC7[Rh] displayed moderate isomerization activity towards not only stilbene but also unsaturated fatty acid isomers, highlighting its expansive potential as an isomerization catalyst.

A synthetic cell-free 36-enzyme reaction system for vitamin B12 production.

Adenosylcobalamin (AdoCbl), a biologically active form of vitamin B12 (coenzyme B12), is one of the most complex metal-containing natural compounds and an essential vitamin for animals. However, AdoCbl can only be de novo synthesized by prokaryotes, and its industrial manufacturing to date was limited to bacterial fermentation. Here, we report a method for the synthesis of AdoCbl based on a cell-free reaction system performing a cascade of catalytic reactions from 5-aminolevulinic acid (5-ALA), an inexpensive compound. More than 30 biocatalytic reactions are integrated and optimized to achieve the complete cell-free synthesis of AdoCbl, after overcoming feedback inhibition, the complicated detection, instability of intermediate products, as well as imbalance and competition of cofactors. In the end, this cell-free system produces 417.41 µg/L and 5.78 mg/L of AdoCbl using 5-ALA and the purified intermediate product hydrogenobyrate as substrates, respectively. The strategies of coordinating synthetic modules of complex cell-free system describe here will be generally useful for developing cell-free platforms to produce complex natural compounds with long and complicated biosynthetic pathways.

Protein engineering and iterative multimodule optimization for vitamin B6 production in Escherichia coli.

Vitamin B6 is an essential nutrient with extensive applications in the medicine, food, animal feed, and cosmetics industries. Pyridoxine (PN), the most common commercial form of vitamin B6, is currently chemically synthesized using expensive and toxic chemicals. However, the low catalytic efficiencies of natural enzymes and the tight regulation of the metabolic pathway have hindered PN production by the microbial fermentation process. Here, we report an engineered Escherichia coli strain for PN production. Parallel pathway engineering is performed to decouple PN production and cell growth. Further, protein engineering is rationally designed including the inefficient enzymes PdxA, PdxJ, and the initial enzymes Epd and Dxs. By the iterative multimodule optimization strategy, the final strain produces 1.4 g/L of PN with productivity of 29.16 mg/L/h by fed-batch fermentation. The strategies reported here will be useful for developing microbial strains for the production of vitamins and other bioproducts having inherently low metabolic fluxes.

Systems Analysis of Highly Multiplexed CRISPR-Base Editing in Streptomycetes.

CRISPR tools, especially Cas9n-sgRNA guided cytidine deaminase base editors such as CRISPR-BEST, have dramatically simplified genetic manipulation of streptomycetes. One major advantage of CRISPR base editing technology is the possibility to multiplex experiments in genomically instable species. Here, we demonstrate scaled up Csy4 based multiplexed genome editing using CRISPR-mcBEST in Streptomyces coelicolor. We evaluated the system by simultaneously targeting 9, 18, and finally all 28 predicted specialized metabolite biosynthetic gene clusters in a single experiment. We present important insights into the performance of Csy4 based multiplexed genome editing at different scales. Using multiomics analysis, we investigated the systems wide effects of such extensive editing experiments and revealed great potentials and important bottlenecks of CRISPR-mcBEST. The presented analysis provides crucial data and insights toward the development of multiplexed base editing as a novel paradigm for high throughput engineering of Streptomyces chassis and beyond.

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.

Enhanced production of difficult-to-express proteins through knocking down rnpA gene expression.

Escherichia coli has been employed as a workhorse for the efficient production of recombinant proteins. However, some proteins were found to be difficult to produce in E. coli. The stability of mRNA has been considered as one of the important factors affecting recombinant protein production. Here we report a generally applicable and simple strategy for enhancing mRNA stability, and consequently improving recombinant protein production in E. coli. RNase P, a ribozyme comprising an RNA subunit (RnpB) and a protein subunit (RnpA), is involved in tRNA maturation. Based on the finding that purified RnpA can digest rRNA and mRNA in vitro, it was reasoned that knocking down the level of RnpA might enhance recombinant protein production. For this, the synthetic small regulatory RNA-based knockdown system was applied to reduce the expression level of RnpA. The developed RnpA knockdown system allowed successful overexpression of 23 different recombinant proteins of various origins and sizes, including Cas9 protein, antibody fragment, and spider silk protein. Notably, a 284.9-kDa ultra-high molecular weight, highly repetitive glycine-rich spider silk protein, which is one of the most difficult proteins to produce, could be produced to 1.38 g L-1 , about two-fold higher than the highest value previously achieved, by a fed-batch culture of recombinant E. coli strain employing the RnpA knockdown system. The RnpA-knockdown strategy reported here will be generally useful for the production of recombinant proteins including those that have been difficult to produce.

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.