Predicting the physiological effects of multiple drugs using electronic health record.

Various computational models have been developed to understand the physiological effects of drug-drug interactions, which can contribute to more effective drug treatments. However, they mostly focus on interactions of only two drugs, and do not consider the patient information. To address this challenge, we use publicly available electronic health record (EHR), MIMIC-IV, to develop machine learning models that predict the physiological effects of two or more drugs.

Overcoming Bacteriophage Contamination in Bioprocessing: Strategies and Applications.

Bacteriophage contamination has a devastating impact on the viability of bacterial hosts and can significantly reduce the productivity of bioprocesses in biotechnological industries. The consequences range from widespread fermentation failure to substantial economic losses, highlighting the urgent need for effective countermeasures. Conventional prevention methods, which focus primarily on the physical removal of bacteriophages from equipment, bioprocess units, and the environment, have proven ineffective in preventing phage entry and contamination.

Inverted Alu repeats: friends or foes in the human transcriptome.

Alu elements are highly abundant primate-specific short interspersed nuclear elements that account for ~10% of the human genome. Due to their preferential location in gene-rich regions, especially in introns and 3' UTRs, Alu elements can exert regulatory effects on the expression of both host and neighboring genes. When two Alu elements with inverse orientations are positioned in close proximity, their transcription results in the generation of distinct double-stranded RNAs (dsRNAs), known as inverted Alu repeats (IRAlus).

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.

Alternative polyadenylation determines the functional landscape of inverted Alu repeats.

Inverted Alu repeats (IRAlus) are abundantly found in the transcriptome, especially in introns and 3' untranslated regions (UTRs). Yet, the biological significance of IRAlus embedded in 3' UTRs remains largely unknown. Here, we find that 3' UTR IRAlus silences genes involved in essential signaling pathways.

Predicting the effects of cultivation condition on gene regulation in by using deep learning.

Cell's physiology is affected by cultivation conditions at varying degrees, including carbon sources and inorganic nutrients in growth medium, and the presence or absence of aeration. When examining the effects of cultivation conditions on the cell, the cell's transcriptional response is often examined first among other phenotypes (e.g.

Efficient production of an antitumor precursor actinocin and other medicinal molecules from kynurenine pathway in Escherichia coli.

Kynurenine pathway has a potential to convert L-tryptophan into multiple medicinal molecules. This study aims to explore the biosynthetic potential of kynurenine pathway for the efficient production of actinocin, an antitumor precursor selected as a proof-of-concept target molecule. Kynurenine pathway is first constructed in Escherichia coli by testing various combinations of biosynthetic genes from four different organisms.

Mitochondrial nucleic acids in innate immunity and beyond.

Mitochondria participate in a wide range of cellular processes. One essential function of mitochondria is to be a platform for antiviral signaling proteins during the innate immune response to viral infection. Recently, studies have revealed that mitochondrion-derived DNAs and RNAs are recognized as non-self molecules and act as immunogenic ligands.

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.

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.

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.

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.

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.

Resveratrol Attenuates the Mitochondrial RNA-Mediated Cellular Response to Immunogenic Stress.

Human mitochondria contain a circular genome that encodes 13 subunits of the oxidative phosphorylation system. In addition to their role as powerhouses of the cells, mitochondria are also involved in innate immunity as the mitochondrial genome generates long double-stranded RNAs (dsRNAs) that can activate the dsRNA-sensing pattern recognition receptors. Recent evidence shows that these mitochondrial dsRNAs (mt-dsRNAs) are closely associated with the pathogenesis of human diseases that accompany inflammation and aberrant immune activation, such as Huntington's disease, osteoarthritis, and autoimmune Sjögren's syndrome.

Targeted and high-throughput gene knockdown in diverse bacteria using synthetic sRNAs.

Synthetic sRNAs allow knockdown of target genes at translational level, but have been restricted to a limited number of bacteria. Here, we report the development of a broad-host-range synthetic sRNA (BHR-sRNA) platform employing the RoxS scaffold and the Hfq chaperone from Bacillus subtilis. BHR-sRNA is tested in 16 bacterial species including commensal, probiotic, pathogenic, and industrial bacteria, with >50% of target gene knockdown achieved in 12 bacterial species.

A contribution of metabolic engineering to addressing medical problems: Metabolic flux analysis.

Metabolic engineering has served as a systematic discipline for industrial biotechnology as it has offered systematic tools and methods for strain development and bioprocess optimization. Because these metabolic engineering tools and methods are concerned with the biological network of a cell with emphasis on metabolic network, they have also been applied to a range of medical problems where better understanding of metabolism has also been perceived to be important. Metabolic flux analysis (MFA) is a unique systematic approach initially developed in the metabolic engineering community, and has proved its usefulness and potential when addressing a range of medical problems.

Multi-targeted therapy resistance via drug-induced secretome fucosylation.

Cancer secretome is a reservoir for aberrant glycosylation. How therapies alter this post- translational cancer hallmark and the consequences thereof remain elusive. Here, we show that an elevated secretome fucosylation is a pan-cancer signature of both response and resistance to multiple targeted therapies.

Analysis of mitochondrial double-stranded RNAs in human cells.

Human mitochondrial genome is transcribed bidirectionally, generating long complementary RNAs that can form double-stranded RNAs (mt-dsRNAs). When released to the cytosol, these mt-dsRNAs can activate antiviral signaling. Here, we present a detailed protocol for the analysis of mt-dsRNA expression.

Recent development of machine learning models for the prediction of drug-drug interactions.

Polypharmacy, the co-administration of multiple drugs, has become an area of concern as the elderly population grows and an unexpected infection, such as COVID-19 pandemic, keeps emerging. However, it is very costly and time-consuming to experimentally examine the pharmacological effects of polypharmacy. To address this challenge, machine learning models that predict drug-drug interactions (DDIs) have actively been developed in recent years.

Factors affecting the competitiveness of bacterial fermentation.

Sustainable production of chemicals and materials from renewable non-food biomass using biorefineries has become increasingly important in an effort toward the vision of 'net zero carbon' that has recently been pledged by countries around the world. Systems metabolic engineering has allowed the efficient development of microbial strains overproducing an increasing number of chemicals and materials, some of which have been translated to industrial-scale production. Fermentation is one of the key processes determining the overall economics of bioprocesses, but has recently been attracting less research attention.

Systems metabolic engineering of Corynebacterium glutamicum for the efficient production of β-alanine.

β-Alanine is an important β-amino acid with a growing demand in a wide range of applications in chemical and food industries. However, current industrial production of β-alanine relies on chemical synthesis, which usually involves harmful raw materials and harsh production conditions. Thus, there has been increasing demand for more sustainable, yet efficient production process of β-alanine.

Double-stranded RNA induction asa potential dynamic biomarkerfor DNA-demethylating agents.

Hypomethylating agents (HMAs), such as azacitidine and decitabine, induce cancer cell death by demethylating DNAs to promote the expression of tumor-suppressor genes. HMAs also reactivate the transcription of endogenous double-stranded RNAs (dsRNAs) that trigger the innate immune response and subsequent apoptosis via viral mimicry. However, the expression patterns of endogenous dsRNAs and their relevance in the efficacy of HMAs remain largely uninvestigated.

Designing Microbial Cell Factories for the Production of Chemicals.

The sustainable production of chemicals from renewable, nonedible biomass has emerged as an essential alternative to address pressing environmental issues arising from our heavy dependence on fossil resources. Microbial cell factories are engineered microorganisms harboring biosynthetic pathways streamlined to produce chemicals of interests from renewable carbon sources. The biosynthetic pathways for the production of chemicals can be defined into three categories with reference to the microbial host selected for engineering: native-existing pathways, nonnative-existing pathways, and nonnative-created pathways.