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Сучасна б!отехнолог1я ензимпв е перспективною галуззю, яка швидко розвиваеться i потребуе hobíthíx дослщжень щодо умов б1осинтезу ензим!в. Оптим1зац1я складу поживного середовища залежно в!д потреб м1кроорган1зм!в та ф1зико-х1м1чн1 фактори напряму впивають на зростання ефективност! б!осинтезу ам1лол1тичних ензим!в, а саме на б1осинтетичну спроможшсть штаму Streptomyces reci fensis var. lyticus 2P-15. Модулювання бшсинтетично! активност! штам!в продуцент!в ам!лол!тичних ензим!в уможливггь значно збшыпити !х економ!чний вих!д. Мета. Метою роботи е оптим!зац1я бшсинтетично! спроможност! штаму Streptomyces recifensis var. lyticus 2P-15 за умов синтезу ам!лол!тичних ензим!в та дослщження динам!ки впливу ф!зикох!м!чних х!м!чних фактор!в на оптим!зац1ю. Методи. Об'ект дослщження - штам Streptomyces reci fensis var. lyticus 2P-15, одержаний шляхом тристушнеао! селекцп продуценту. Для виконання дослщжень було застосовано симплексметод добору складу середовища. За бшсинтетичну спроможшсть штаму приймали сшввщношення ам!лол!тично! активност! до р!вня накопичення б!омаси. Для визначення ам!лол!тично! активност! використовували фотоколометричний метод. Р!вень накопичення б!омаси визначали вагомим методом. Резулътати. Встановлено, що в результат! оптим!зац!1 складу симплексного поживного середовища методом математичного моделювання бшсинтетична емшсть зросла на 3,63 пор!вняно з контрольним вар!антом. Дослщжено також, що оптимальна концентращя такого компонента живильного середовища, як глутамат натр!ю CgHgNC^Na ^O становила 1,5%, що шдвищувало ам!лол!тичну актившсть на 2,63 та зб!лыпувало накопичення бшмаси. Окремо сл!д зазначити отримаш резулътати дослщження оптимальних концентращй !он!в важчих метал!в, що додавалися до оптим!зованого вар!анту поживного середовища, що дозволяють продовжувати дослщження в цьому аспект! i використовувати !они Со, Mo, Cd у склад! поживного середовища. За отриманих результат!в спостершалося шдвищення ам!лол!тично! активност! в найкращому вщгуку у 3,54 рази. Отримаш резулътати мають теоретичне i практичне значения для подальших дослщжень бютехнолог!! ензим!в. Висновки. Перспективою подальших дослщжень оптим!зац!1 бшсинтезу актином!цет!в симплексметодом !нших аспект!в його регуляцп буде тдвищення бшсинтетично! спроможност! дослщжуваного штаму, що позитивно вплине на економ!чну ефектившсть виробництва ам!лол!тичних ензимних препарат!в шляхом отримання м!кробного синтезу.

Fungal biotechnology can drive sustainability, offering eco-friendly solutions for energy, healthcare, nutraceuticals, and environmental challenges.The genomic and metabolic adaptability of fungi enables the efficient production of biofuels, enzymes, nutraceuticals, and other high-value bioproducts.Biosynthetic gene clusters in fungi support the discovery and production of essential secondary metabolites for pharmaceuticals and industry.Artificial intelligence-driven design–build–test–learn cycles accelerate fungal strain optimization, enhancing metabolic engineering and improving bioprocess efficiency. Fungal biotechnology plays a vital role in advancing sustainability by offering innovative solutions for resource efficiency, environmental protection, and health improvements. Fungal systems are highly adaptable compared with other biotechnologies, with unique genomic and metabolic functions that enable the large-scale production of valuable compounds. This review emphasizes how fungal biotechnology contributes to global sustainability goals, particularly through artificial intelligence (AI)-driven methods that accelerate strain optimization and metabolic engineering. Engineered Aspergillus strains, with enhanced enzyme production, and Neurospora, a model organism, demonstrate significant potential for industrial applications. These advancements offer cost-effective and resource-efficient solutions, underscoring the importance of interdisciplinary collaboration in fungal biology, genomics, enzymes, and computational approaches to scale fungal biotechnology for sustainable outcomes. Fungal biotechnology plays a vital role in advancing sustainability by offering innovative solutions for resource efficiency, environmental protection, and health improvements. Fungal systems are highly adaptable compared with other biotechnologies, with unique genomic and metabolic functions that enable the large-scale production of valuable compounds. This review emphasizes how fungal biotechnology contributes to global sustainability goals, particularly through artificial intelligence (AI)-driven methods that accelerate strain optimization and metabolic engineering. Engineered Aspergillus strains, with enhanced enzyme production, and Neurospora, a model organism, demonstrate significant potential for industrial applications. These advancements offer cost-effective and resource-efficient solutions, underscoring the importance of interdisciplinary collaboration in fungal biology, genomics, enzymes, and computational approaches to scale fungal biotechnology for sustainable outcomes.

Abstract While design and high-throughput build approaches in biotechnology have increasingly gained attention over the past decade, approaches to test strain performance in high-throughput have received less discussion in the literature. Here, we describe how fermentation characterization can be used to improve the overall efficiency of high-throughput DBTAL (design-build-test-analyze-learn) cycles in an industrial context. Fermentation characterization comprises an in-depth study of strain performance in a bioreactor setting and involves semi-frequent sampling and analytical measurement of substrates, cell densities and viabilities, and (by)products. We describe how fermentation characterization can be used to (1) improve (high-throughput) strain design approaches; (2) enable the development of bench-scale fermentation processes compatible with a wide diversity of strains; and (3) inform the development of high-throughput plate-based strain testing procedures for improved performance at larger scales.

N‑Acetyl‑d‑neuraminic acid (Neu5Ac) is the crucial compound for the chemical synthesis of antiflu medicine Zanamivir. Chemoenzymatic synthesis of Neu5Ac involves N-acetyl-d-glucosamine 2-epimerase (AGE)-catalyzed epimerization of N-acetyl-d-glucosamine (GlcNAc) to N-acetyl-d-mannosamine (ManNAc), and aldolase-catalyzed condensation between ManNAc and pyruvate. Host optimization plays an important role in the whole-cell biotransformation of value-added compounds. In this study, via single-plasmid biotransformation system, we showed that the AGE gene BT0453, cloned from human gut microorganism Bacteroides thetaiotaomicron VPI-5482, showed the highest biotransformation yield among the AGE genes tested; and there is no clear Neu5Ac yield difference between the BT0453 coupled with one aldolase coding nanA gene and two nanA genes. Next, Escherichia coli chromosomal genes involved in substrate degradation, product exportation and pH change were deleted via recombineering and CRISPR/Cas9. With the final E. coli BL21(DE3) ΔnanA Δnag ΔpoxB as host, a significant 16.5% yield improvement was obtained. Furthermore, precursor (pyruvate) feeding resulted in 3.2% yield improvement, reaching 66.8% molar biotransformation. The result highlights the importance of host optimization, and set the stage for further metabolic engineering of whole-cell biotransformation of Neu5Ac.

With the ongoing journey of automation advancements and a trend towards miniaturization, the choice of actuator plays a crucial role. Over recent years, soft actuators have demonstrated their usefulness in various applications, especially where light weight and high strain are required. Dielectric elastomer actuators (DEAs) are a class of soft actuators that provide high-strain actuation possibilities in applications like biomedicine, logistics, or consumer electronics. A variety of work featuring DEAs for actuation has been carried out in recent years, but a single work detailing the design conception, fabrication, modeling and experimental validation is lacking, especially in the context of achieving high strains with the integration of multiple electrodes and their interaction. This work discusses these issues with an equibiaxial DEA, enabling optimized equibiaxial strain patterns due to full use of the available actuation area. The developed DEA can achieve an equibiaxial strain of 12.75% for actuation at 60 V μm−1 over an active area of 7 cm2 which is an improvement of 1.3 times compared to traditional dot actuators. These properties position the device as a promising alternative for various applications like cell cultures or microassembly and provide an advantage of optimized use of passive regions within the actuator.

Endangered species can achieve population growth through utilization. is an endangered species, which can be used in gardens and street trees. To avoid population degradation caused by long-term nursery cultivation, we need to introduce high-quality wild sources of germplasm for hybridization. In the past, when the selection of strains was carried out, attention was often paid to the performance of different traits of each strain. The strains with advantages in many more traits were selected as the target. In this paper, we proposed that excellent strains should be selected based on the needs of managers. We constructed a complex index composed of insect resistance and growth amount, which was concerned by plantation managers, for the selection of excellent strains. Its availability was confirmed as well. We cultivated 16 wild-sourced strains in a homogeneous garden and carried out experiments for 3 years. We measured 28 functional traits. Through collinearity diagnostics, 15 functional traits in 4 dimensions (morphology, leaf economy, stoichiometry and reproduction) were selected for analysis and construction of complex index. The influence of environmental factors on traits was excluded by comparing the trait matrix calculated based on Euclidean distance with the geographical distance matrix. Excellent strains (No. 15 from Dazeshan) selected based on the key complex index may not be outstanding in each trait, but have a more balanced performance among the trade-offs of trait combinations. We also explored the visualization of this key complex index by correlating with leaf carbon content (its ecologically relevant trait), so as to realize rapid and early selection of strains by using LCC (an easily measurable trait). To construct key complex index, appropriate functional traits should be selected according to the needs of managers or different species. The measurable traits with clear ecological links with complex index should be selected as \"agents\" to realize visualization of complex index.

Background Adaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation. Results Here, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45  ±  0.12 mmol EtOH g CDW −1  h −1 and a growth rate of 0.15 ± 0.01 h −1 in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements. Conclusions The established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products.

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi‐level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi‐level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low‐complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing. We present a heuristic algorithmic method, which we call GDLS (Genetic Design through Local Search), that is capable of handling large models and allows for a much larger number of genetic manipulations in the final design, with runtime scaling only linearly‐as compared to exponentially for globally‐optimal search‐with the total number of manipulations. GDLS employs a local search approach with multiple search paths to find a set of locally optimal strategies. GDLS implements reductions that simplify flux‐balance analysis (FBA) models without changing their properties and gene‐protein‐reaction (GPR) mappings that describe the mapping from genes to reactions. We assessed the performance of GDLS on genetic designs for acetate and succinate production using the most recent genome‐scale metabolic model of Escherichia coli, iAF1260. Compared with globally‐optimal search using mixed‐integer linear programming (MILP), GDLS achieves over an order of magnitude improvement incomputational time for solutions that yield equal or comparable values for the desired flux with as few as three manipulations. We compared GDLS against the evolutionary algorithm and simulated annealing metaheuristics implemented by OptFlux and found favorable performance for GDLS. In particular, we found that the OptFlux meta‐heuristics were unable to identify genetic designs that required two or more manipulations to be simultaneously implemented to have an effect on the desired flux.

As an alternative to chemical building blocks derived from algal biomass, the excretion of glycolate has been proposed. This process has been observed in green algae such as Chlamydomonas reinhardtii as a product of the photorespiratory pathway. Photorespiration generally occurs at low CO 2 and high O 2 concentrations, through the key enzyme RubisCO initiating the pathway via oxygenation of 1.5-ribulose-bisphosphate. In wild-type strains, photorespiration is usually suppressed in favour of carboxylation due to the cellular carbon concentrating mechanisms (CCMs) controlling the internal CO 2 concentration. Additionally, newly produced glycolate is directly metabolized in the C2 cycle. Therefore, both the CCMs and the C2 cycle are the key elements which limit the glycolate production in wild-type cells. Using conventional crossing techniques, we have developed Chlamydomonas reinhardtii double mutants deficient in these two key pathways to direct carbon flux to glycolate excretion. Under aeration with ambient air, the double mutant D6 showed a significant and stable glycolate production when compared to the non-producing wild type. Interestingly, this mutant can act as a carbon sink by fixing atmospheric CO 2 into glycolate without requiring any additional CO 2 supply. Thus, the double-mutant strain D6 can be used as a photocatalyst to produce chemical building blocks and as a future platform for algal-based biotechnology. Key Points • Chlamydomonas reinhardtii cia5 gyd double mutants were developed by sexual crossing • The double mutation eliminates the need for an inhibitor in glycolate production • The strain D6 produces significant amounts of glycolate with ambient air only

Unpredictable web temperature distributions in the dryer and strain deviations in the cross-machine (CMD) and machine (MD) directions could hamper the manufacture of smooth functional layers on polymer-based webs through the roll-to-roll (R2R) continuous process system. However, research on this topic is limited. In this study, we developed a structural analysis model using the temperature distribution of the web as a boundary condition to analyze the drying mechanism of the dryer used in an R2R system. Based on the results of this model, we then applied structural modifications to the flow channel and hole density of the aluminum plate of the dryer. The model successfully predicted the temperature and strain distributions of the web inside the dryer in the CMD and MD by forming a tension according to the speed difference of the driven rolls at both ends of the span. Our structural improvements significantly reduced the temperature deviation of the moving web inside the dryer by up to 74% and decreased the strain deviation by up to 46%. The findings can help prevent web unevenness during the drying process of the R2R system, which is essential to minimize the formation of defects on functional layers built over polymer-based webs.