Rational Design of High-Efficiency Synthetic Small Regulatory RNAs and Their Application in Robust Genetic Circuit Performance Through Tight Control of Leaky Gene Expression.

Synthetic sRNAs show promise as tools for targeted and programmable gene expression manipulation. However, the design of high-efficiency synthetic sRNAs is a challenging task that necessitates careful consideration of multiple factors. Therefore, this study aims to investigate rational design strategies that significantly and robustly enhance the efficiency of synthetic sRNAs. This is achieved by optimizing the following parameters: the sRNA scaffold, mRNA binding affinity, Hfq protein expression level, and mRNA secondary structure. By utilizing optimized synthetic sRNAs within a positive feedback circuit, we effectively addressed the issue of gene expression leakage─an enduring challenge in synthetic biology that undermines the reliability of genetic circuits in bacteria. Our designed synthetic sRNAs successfully prevented gene expression leakage, thus averting unintended circuit activation caused by initial expression noise, even in the absence of signal molecules. This result shows that high-efficiency synthetic sRNAs not only enable precise gene knockdown for metabolic engineering but also ensure the robust performance of synthetic circuits. The strategies developed here hold significant promise for broad applications across diverse biotechnological fields, establishing synthetic sRNAs as pivotal tools in advancing synthetic biology and gene regulation.

Autoinhibited Protein Database: a curated database of autoinhibitory domains and their autoinhibition mechanisms.

Autoinhibition, a crucial allosteric self-regulation mechanism in cell signaling, ensures signal propagation exclusively in the presence of specific molecular inputs. The heightened focus on autoinhibited proteins stems from their implication in human diseases, positioning them as potential causal factors or therapeutic targets. However, the absence of a comprehensive knowledgebase impedes a thorough understanding of their roles and applications in drug discovery. Addressing this gap, we introduce Autoinhibited Protein Database (AiPD), a curated database standardizing information on autoinhibited proteins. AiPD encompasses details on autoinhibitory domains (AIDs), their targets, regulatory mechanisms, experimental validation methods, and implications in diseases, including associated mutations and post-translational modifications. AiPD comprises 698 AIDs from 532 experimentally characterized autoinhibited proteins and 2695 AIDs from their 2096 homologs, which were retrieved from 864 published articles. AiPD also includes 42 520 AIDs of computationally predicted autoinhibited proteins. In addition, AiPD facilitates users in investigating potential AIDs within a query sequence through comparisons with documented autoinhibited proteins. As the inaugural autoinhibited protein repository, AiPD significantly aids researchers studying autoinhibition mechanisms and their alterations in human diseases. It is equally valuable for developing computational models, analyzing allosteric protein regulation, predicting new drug targets, and understanding intervention mechanisms AiPD serves as a valuable resource for diverse researchers, contributing to the understanding and manipulation of autoinhibition in cellular processes. Database URL: http://ssbio.cau.ac.kr/databases/AiPD.

Engineered T Cell Receptor for Cancer Immunotherapy.

Among the therapeutic strategies in cancer immunotherapy-such as immune-modulating antibodies, cancer vaccines, or adoptive T cell transfer-T cells have been an attractive target due to their cytotoxicity toward tumor cells and the tumor antigen-specific binding of their receptors. Leveraging the unique properties of T cells, chimeric antigen receptor-T cells and T cell receptor (TCR)-T cells were developed through genetic modification of their receptors, enhancing the specificity and effectiveness of T cell therapy. Adoptive cell transfer of chimeric antigen receptor-T cells has been successful for the treatment of hematological malignancies. To expand T cell therapy to solid tumors, T cells are modified to express defined TCR targeting tumor associated antigen, which is called TCR-T therapy. This review discusses anti-tumor T cell therapies, with a focus on engineered TCR-T cell therapy. We outline the characteristics of TCR-T cell therapy and its clinical application to non-hematological malignancies.

Corydalis ternata Nakai Alleviates Cognitive Decline in Alzheimer's Disease by Reducing ß-Amyloid and Neuroinflammation.

Recently, natural herbs have gained increasing attention owing to their comparatively low toxicity levels and the abundance of historical medical documentation regarding their use. Nevertheless, owing to a lack of knowledge regarding these herbs and their compounds, attempts to find those that could be beneficial for treating diseases have often been ad hoc; thus, there is now a growing demand for an in silico method to identify beneficial herbs. In this study, we present a computational approach for identifying natural herbs specifically effective in treating cognitive decline in Alzheimer's disease (AD) sufferers, which analyzes the similarities between herbal compounds and known drugs targeting AD-related proteins. Our in silico method suggests that Corydalis ternata can improve cognitive decline in AD sufferers. Behavioral tests with an AD mouse model for the confirmation of the in silico prediction reveals that C. ternata significantly alleviated the cognitive decline (memory and motor functions) caused by neurodegeneration. Further pathology analyses reveal that C. ternata decreases the level of Aß plaques, reduces neuroinflammation, and promotes autophagy flux, and thus C. ternata can be clinically effective for preventing mild cognitive impairment during the early stages of AD. These findings highlight the potential utility of our in silico method and the potential clinical application of the identified natural herb in treating and preventing AD.

A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration.

The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3ß), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.

A machine learning-based quantitative model (LogBB_Pred) to predict the blood-brain barrier permeability (logBB value) of drug compounds.

MOTIVATION: Efficient assessment of the blood-brain barrier (BBB) penetration ability of a drug compound is one of the major hurdles in central nervous system drug discovery since experimental methods are costly and time-consuming. To advance and elevate the success rate of neurotherapeutic drug discovery, it is essential to develop an accurate computational quantitative model to determine the absolute logBB value (a logarithmic ratio of the concentration of a drug in the brain to its concentration in the blood) of a drug candidate. RESULTS: Here, we developed a quantitative model (LogBB_Pred) capable of predicting a logBB value of a query compound. The model achieved an R2 of 0.61 on an independent test dataset and outperformed other publicly available quantitative models. When compared with the available qualitative (classification) models that only classified whether a compound is BBB-permeable or not, our model achieved the same accuracy (0.85) with the best qualitative model and far-outperformed other qualitative models (accuracies between 0.64 and 0.70). For further evaluation, our model, quantitative models, and the qualitative models were evaluated on a real-world central nervous system drug screening library. Our model showed an accuracy of 0.97 while the other models showed an accuracy in the range of 0.29-0.83. Consequently, our model can accurately classify BBB-permeable compounds as well as predict the absolute logBB values of drug candidates. AVAILABILITY AND IMPLEMENTATION: Web server is freely available on the web at http://ssbio.cau.ac.kr/software/logbb_pred/. The data used in this study are available to download at http://ssbio.cau.ac.kr/software/logbb_pred/dataset.zip.

Functional small peptides for enhanced protein delivery, solubility, and secretion in microbial biotechnology.

In microbial biotechnology, there is a constant demand for functional peptides to give new functionality to engineered proteins to address problems such as direct delivery of functional proteins into bacterial cells, enhanced protein solubility during the expression of recombinant proteins, and efficient protein secretion from bacteria. To tackle these critical issues, we selected three types of functional small peptides: cell-penetrating peptides (CPPs) enable the delivery of diverse cargoes into bacterial cytoplasm for a variety of purposes, protein-solubilizing peptide tags demonstrate remarkable efficiency in solubilizing recombinant proteins without folding interference, and signal peptides play a key role in enabling the secretion of recombinant proteins from bacterial cells. In this review, we introduced these three functional small peptides that offer effective solutions to address emerging problems in microbial biotechnology. Additionally, we summarized various engineering efforts aimed at enhancing the activity and performance of these peptides, thereby providing valuable insights into their potential for further applications.

Direct measurements of the colloidal Debye force.

Colloids often behave in a manner similar to their counterparts in molecular space and are used as model systems to understand molecular behavior. Here, we study like-charged colloidal attractions between a permanent dipole on an interfacial particle and its induced dipole on a water-immersed particle caused by diffuse layer polarization. We find that the scaling behavior of the measured dipole-induced dipole (D‒I) interaction via optical laser tweezers is in good agreement with that predicted from the molecular Debye interaction. The dipole character propagates to form aggregate chains. Using coarse-grained molecular dynamic simulations, we identify the separate roles of the D‒I attraction and the van der Waals attraction on aggregate formation. The D‒I attraction should be universal in a broad range of soft matter, such as colloids, polymers, clays, and biological materials, motivating researchers to further conduct in-depth research on these materials.

Effects of rosiglitazone, an antidiabetic drug, on Kv3.1 channels.

Rosiglitazone is a thiazolidinedione-class antidiabetic drug that reduces blood glucose and glycated hemoglobin levels. We here investigated the interaction of rosiglitazone with Kv3.1 expressed in Chinese hamster ovary cells using the whole-cell patch-clamp technique. Rosiglitazone rapidly and reversibly inhibited Kv3.1 currents in a concentration-dependent manner (IC50 = 29.8 µM) and accelerated the decay of Kv3.1 currents without modifying the activation kinetics. The rosiglitazone-mediated inhibition of Kv3.1 channels increased steeply in a sigmoidal pattern over the voltage range of -20 to +30 mV, whereas it was voltage-independent in the voltage range above +30 mV, where the channels were fully activated. The deactivation of Kv3.1 current, measured along with tail currents, was also slowed by the drug. In addition, the steady-state inactivation curve of Kv3.1 by rosiglitazone shifts to a negative potential without significant change in the slope value. All the results with the use dependence of the rosiglitazone-mediated blockade suggest that rosiglitazone acts on Kv3.1 channels as an open channel blocker.

Retardation of Capillary Force between Janus Particles at the Oil-Water Interface.

Interactions among colloidal particles govern the hierarchical microstructure and its physical properties. Here, optical laser tweezers and Monte Carlo simulations are used to evaluate the effects of azimuthal rotation of Janus particles at the oil-water interface on interparticle interactions. We find that the capillary-induced attractive force between two Janus particles at the interface can be relaxed by azimuthal rotation around the critical separation region, at which the capillary force is ∼0.053 pN. Force relaxation leads to a decrease in capillary force around the critical separation region, resulting in a slight increase in the scaling exponent, compared to the theoretical prediction.

Inflammatory Cytokine: An Attractive Target for Cancer Treatment.

The relationship between inflammation and cancer has attracted attention for a long time. The inflammatory tumor microenvironment consists of inflammatory cells, chemokines, cytokines, and signaling pathways. Among them, inflammatory cytokines play an especially pivotal role in cancer development, prognosis, and treatment. Interleukins, tumor necrosis factor-alpha (TNF-α), transforming growth factor-beta (TGF-ß), interferons, and vascular endothelial growth factor (VEGF) are the representative inflammatory cytokines in various cancers, which may promote or inhibit cancer progression. The pro-inflammatory cytokines are associated with advanced cancer stages, resistance to immunotherapy, and poor prognoses, such as in objective response and disease control rates, and progression-free and overall survival. In this review, we selected colorectal, pancreatic, breast, gastric, lung, and prostate cancers, which are well-reported for an association between cancer and inflammatory cytokines. The related cytokines and their effects on each cancer's development and prognosis were summarized. In addition, the treatment strategies targeting inflammatory cytokines in each carcinoma were also described here. By understanding the biological roles of cancer-related inflammatory cytokines, we may modulate the inflammatory tumor microenvironment for potential cancer treatment.

Strategies for Manipulating T Cells in Cancer Immunotherapy.

T cells are attractive targets for the development of immunotherapy to treat cancer due to their biological features, capacity of cytotoxicity, and antigen-specific binding of receptors. Novel strategies that can modulate T cell functions or receptor reactivity provide effective therapies, including checkpoint inhibitor, bispecific antibody, and adoptive transfer of T cells transduced with tumor antigen-specific receptors. T cell-based therapies have presented successful pre-clinical/clinical outcomes despite their common immune-related adverse effects. Ongoing studies will allow us to advance current T cell therapies and develop innovative personalized T cell therapies. This review summarizes immunotherapeutic approaches with a focus on T cells. Anti-cancer T cell therapies are also discussed regarding their biological perspectives, efficacy, toxicity, challenges, and opportunities.

The antidiabetic drug rosiglitazone blocks Kv1.5 potassium channels in an open state.

An antidiabetic drug, rosiglitazone is a member of the drug class of thiazolidinedione. Although restrictions on use due to the possibility of heart toxicity have been removed, it is still a drug that is concerned about side effects on the heart. We here examined, using Chinese hamster ovary cells, the action of rosiglitazone on Kv1.5 channels, which is a major determinant of the duration of cardiac action potential. Rosiglitazone rapidly and reversibly inhibited Kv1.5 currents in a concentration-dependent manner (IC50 = 18.9 µM) and accelerated the decay of Kv1.5 currents without modifying the activation kinetics. In addition, the deactivation of Kv1.5 current, assayed with tail current, was slowed by the drug. All of the results as well as the use-dependence of the rosiglitazone-mediated blockade indicate that rosiglitazone acts on Kv1.5 channels as an open channel blocker. This study suggests that the cardiac side effects of rosiglitazone might be mediated in part by suppression of Kv1.5 channels, and therefore, raises a concern of using the drug for diabetic therapeutics.

Advanced biotechnology using methyltransferase and its applications in bacteria: a mini review.

Since prokaryotic restriction-modification (RM) systems protect the host by cleaving foreign DNA by restriction endonucleases, it is difficult to introduce engineered plasmid DNAs into newly isolated microorganisms whose RM system is not discovered. The prokaryotes also possess methyltransferases to protect their own DNA from the endonucleases. As those methyltransferases can be utilized to methylate engineered plasmid DNAs before transformation and to enhance the stability within the cells, the study on methyltransferases in newly isolated bacteria is essential for genetic engineering. Here, we introduce the mechanism of the RM system, specifically the methyltransferases and their biotechnological applications. These biotechnological strategies could facilitate plasmid DNA-based genetic engineering in bacteria strains that strongly defend against foreign DNA.

Construction of a tunable promoter library to optimize gene expression in Methylomonas sp. DH-1, a methanotroph, and its application to cadaverine production.

BACKGROUND: As methane is 84 times more potent than carbon dioxide in exacerbating the greenhouse effect, there is an increasing interest in the utilization of methanotrophic bacteria that can convert harmful methane into various value-added compounds. A recently isolated methanotroph, Methylomonas sp. DH-1, is a promising biofactory platform because of its relatively fast growth. However, the lack of genetic engineering tools hampers its wide use in the bioindustry. RESULTS: Through three different approaches, we constructed a tunable promoter library comprising 33 promoters that can be used for the metabolic engineering of Methylomonas sp. DH-1. The library had an expression level of 0.24-410% when compared with the strength of the lac promoter. For practical application of the promoter library, we fine-tuned the expressions of cadA and cadB genes, required for cadaverine synthesis and export, respectively. The strain with PrpmB-cadA and PDnaA-cadB produced the highest cadaverine titre (18.12 ± 1.06 mg/L) in Methylomonas sp. DH-1, which was up to 2.8-fold higher than that obtained from a non-optimized strain. In addition, cell growth and lysine (a precursor of cadaverine) production assays suggested that gene expression optimization through transcription tuning can afford a balance between the growth and precursor supply. CONCLUSIONS: The tunable promoter library provides standard and tunable components for gene expression, thereby facilitating the use of methanotrophs, specifically Methylomonas sp. DH-1, as a sustainable cell factory.

Prevalence of Anemia in Pediatric Patients According to Asthma Control: Propensity Score Analysis.

PURPOSE: To investigate whether the degree of asthma control is associated with anemia in pediatric patients. PATIENTS AND METHODS: A cross-sectional study was performed using a dataset from the Health Insurance Reviews & Assessment Service (HIRA) of South Korea in 2016, which included children and adolescent patients diagnosed with asthma. Binary logistic regression was used to assess the association between asthma control and the prevalence of anemia. RESULTS: A total of 236,429 patients under 18 years old were included in the study, including 233,975 patients with controlled and 2454 with uncontrolled asthma. Binary logistic regression after adjustment for confounding factors showed that patients with uncontrolled asthma had a 2.64-fold higher prevalence of anemia than those with well-controlled asthma (OR = 2.64, 95% CI: 2.16-3.22). While there was no effect of gender on the results, there was a statistically significant association between the prevalence of anemia and asthma control in patients under 13 years old. CONCLUSION: These findings suggest that the prevalence of anemia is inversely correlated with asthma control in pediatric patients. Further studies are necessary to obtain pathophysiological insight into the relationship between severe inflammatory diseases and anemia.

Synthetically engineered microbial scavengers for enhanced bioremediation.

Microbial bioremediation has gained attention as a cheap, efficient, and sustainable technology to manage the increasing environmental pollution. Since microorganisms in nature are not evolved to degrade pollutants, there is an increasing demand for developing safer and more efficient pollutant-scavengers for enhanced bioremediation. In this review, we introduce the strategies and technologies developed in the field of synthetic biology and their applications to the construction of microbial scavengers with improved efficiency of biodegradation while minimizing the impact of genetically engineered microbial scavengers on ecosystems. In addition, we discuss recent achievements in the biodegradation of fastidious pollutants, greenhouse gases, and microplastics using engineered microbial scavengers. Using synthetic microbial scavengers and multidisciplinary technologies, toxic pollutants could be more easily eliminated, and the environment could be more efficiently recovered.

Identification of efficient prokaryotic cell-penetrating peptides with applications in bacterial biotechnology.

In bacterial biotechnology, instead of producing functional proteins from plasmids, it is often necessary to deliver functional proteins directly into live cells for genetic manipulation or physiological modification. We constructed a library of cell-penetrating peptides (CPPs) capable of delivering protein cargo into bacteria and developed an efficient delivery method for CPP-conjugated proteins. We screened the library for highly efficient CPPs with no significant cytotoxicity in Escherichia coli and developed a model for predicting the penetration efficiency of a query peptide, enabling the design of new and efficient CPPs. As a proof-of-concept, we used the CPPs for plasmid curing in E. coli and marker gene excision in Methylomonas sp. DH-1. In summary, we demonstrated the utility of CPPs in bacterial engineering. The use of CPPs would facilitate bacterial biotechnology such as genetic engineering, synthetic biology, metabolic engineering, and physiology studies.

Optimized expression of Hfq protein increases Escherichia coli growth.

Escherichia coli is a widely used platform for metabolic engineering due to its fast growth and well-established engineering techniques. However, there has been a demand for faster-growing E. coli for higher production of desired substances. Here, to increase the growth of E. coli cells, we optimized the expression level of Hfq protein, which plays an essential role in stress responses. Six variants of the hfq gene with a different ribosome binding site sequence and thereby a different expression level were constructed. When the Hfq expression level was optimized in DH5α, its growth rate was increased by 12.1% and its cell density was also increased by 4.5%. RNA-seq and network analyses revealed the upregulation of stress response genes and metabolic genes, which increases the tolerance against pH changes. When the same strategy was applied to five other E. coli strains (BL21 (DE3), JM109, TOP10, W3110, and MG1655), all their growth rates were increased by 18-94% but not all their densities were increased (- 12 - + 32%). In conclusion, the Hfq expression optimization can increase cell growth rate and probably their cell densities as well. Since the hfq gene is highly conserved across bacterial species, the same strategy could be applied to other bacterial species to construct faster-growing strains.

Role of Nitric Oxide and Protein S-Nitrosylation in Ischemia-Reperfusion Injury.

Ischemia-reperfusion injury (IRI) is a process in which damage is induced in hypoxic tissue when oxygen supply is resumed after ischemia. During IRI, restoration of reduced nitric oxide (NO) levels may alleviate reperfusion injury in ischemic organs. The protective mechanism of NO is due to anti-inflammatory effects, antioxidant effects, and the regulation of cell signaling pathways. On the other hand, it is generally known that S-nitrosylation (SNO) mediates the detrimental or protective effect of NO depending on the action of the nitrosylated target protein, and this is also applied in the IRI process. In this review, the effect of each change of NO and SNO during the IRI process was investigated.