• Molecules and Cells
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• v.44 no.3
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• Parasites, Hosts and Diseases
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• v.58 no.3
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• pp.287-299
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• 2020

Cystic echinococcosis (CE) is a zoonotic infection caused by Echinococcus granulosus larvae. It seriously affects the development of animal husbandry and endangers human health. Due to a poor understanding of the cystic fluid formation pathway, there is currently a lack of innovative methods for the prevention and treatment of CE. In this study, the protoscoleces (PSCs) in the encystation process were analyzed by high-throughput RNA sequencing. A total of 32,401 transcripts and 14,903 cDNAs revealed numbers of new genes and transcripts, stage-specific genes, and differently expressed genes. Genes encoding proteins involved in signaling pathways, such as putative G-protein coupled receptor, tyrosine kinases, and serine/threonine protein kinase, were predominantly up-regulated during the encystation process. Antioxidant enzymes included cytochrome c oxidase, thioredoxin glutathione, and glutathione peroxidase were a high expression level. Intriguingly, KEGG enrichment suggested that differentially up-regulated genes involved in the vasopressin-regulated water reabsorption metabolic pathway may play important roles in the transport of proteins, carbohydrates, and other substances. These results provide valuable information on the mechanism of cystic fluid production during the encystation process, and provide a basis for further studies on the molecular mechanisms of growth and development of PSCs.

• Korean Journal of Environmental Biology
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• v.30 no.2
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• pp.77-89
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• 2012

With the advent of the genomics era powered by DNA sequencing technologies, life science is being transformed significantly and biological research and development have been accelerated. Environmental biology concerns the relationships among living organisms and their natural environment, which constitute the global biogeochemical cycle. As sustainability of the ecosystems depends on biodiversity, examining the structure and dynamics of the biotic constituents and fully grasping their genetic and metabolic capabilities are pivotal. The high-speed high-throughput next-generation sequencing can be applied to barcoding organisms either thriving or endangered and to decoding the whole genome information. Furthermore, diversity and the full gene complement of a microbial community can be elucidated and monitored through metagenomic approaches. With regard to human welfare, microbiomes of various human habitats such as gut, skin, mouth, stomach, and vagina, have been and are being scrutinized. To keep pace with the rapid increase of the sequencing capacity, various bioinformatic algorithms and software tools that even utilize supercomputers and cloud computing are being developed for processing and storage of massive data sets. Environmental genomics will be the major force in understanding the structure and function of ecosystems in nature as well as preserving, remediating, and bioprospecting them.

• Research in Plant Disease
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• v.30 no.2
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• pp.157-164
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• 2024

Jack bean (Canavalia ensiformis) is one of healthy products for fermented or functional food in Korea and is widely distributed and cultivated worldwide. During August 2022, Jack bean plants showing symptoms of yellow flecks, chlorosis, necrotic spots and mosaic were observed in Jangheung-gun, South Korea. By transmission electron microscopy, flexuous filamentous virus particles of approximately 750×13 nm in size were observed in the symptomatic leaf samples. The infection of a Korean isolate of clover yellow vein virus (ClYVV-Ce-JH) was confirmed using double antibody sandwich enzyme-linked sorbent assay, reverse transcription polymerase chain reaction and high-throughput sequencing. The complete genome sequence of ClYVV-Ce-JH consists of 9,549 nucleotides (nt) excluding the poly (A) tail and encodes 3,072 amino acids (aa), with an AUG start and UAG stop codon, containing one open reading frame that is typical of a potyvirus polyprotein. The polyprotein of ClYVV-Ce-JH was divided into ten proteins and each protein's cleavage sites were determined. The coat protein (CP) and polyprotein of ClYVV-Ce-JH were compared at the nt and aa levels with those of the previously reported 14 ClYVV isolates. ClYVV-Ce-JH shared 92.62% to 99.63% and 93.39% to 98.05% at the CP and polyprotein homology. To our knowledge, this is the first report of a Korean isolate of ClYVV from Jack bean plants and the complete genome sequence of a ClYVV Jack bean isolate in the world.

• Molecules and Cells
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• v.21 no.2
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• pp.308-313
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• 2006

Amygdalin is a cyanogenic glycoside compound which is commonly found in the pits of many fruits and raw nuts. Although amygdalin itself is not toxic, it can release cyanide (CN) after hydrolysis when the pits and nuts are crushed, moistened and incubated, possibly within the gastrointestinal tract. CN reversibly inhibits cellular oxidizing enzymes and cyanide poisoning generates a range of clinical symptoms. As some pits and nuts may contain unusually high levels of amygdalin such that there is a sufficient amount to induce critical CN poisoning in humans, the detection of abnormal content of amygdalin in those pits and nuts can be a life-saving measure. Although there are various methods to detect amygdalin in food extracts, an enzyme immunoassay has not been developed for this purpose. In this study we immunized New Zealand White rabbits with an amygdalin-KLH (keyhole limpet hemocyanin) conjugate and succeeded in raising anti-sera reactive to amygdalin, proving that amygdalin can behave as a hapten in rabbits. Using this polyclonal antibody, we developed a competition enzyme immunoassay for determination of amygdalin concentration in aqueous solutions. This technique was able to effectively detect abnormally high amygdalin content in various seeds and nuts. In conclusion, we proved that enzyme immunoassay can be used to determine the amount of amygdalin in food extracts, which will allow automated analysis with high throughput.

• Genomics & Informatics
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• v.19 no.1
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• pp.6.1-6.10
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• 2021

Vascular endothelial growth factor (VEGF) is expressed at elevated levels by most cancer cells, which can stimulate vascular endothelial cell growth, survival, proliferation as well as trigger angiogenesis modulated by VEGF and VEGFR (a tyrosine kinase receptor) signaling. The angiogenic effects of the VEGF family are thought to be primarily mediated through the interaction of VEGF with VEGFR-2. Targeting this signaling molecule and its receptor is a novel approach for blocking angiogenesis. In recent years virtual high throughput screening has emerged as a widely accepted powerful technique in the identification of novel and diverse leads. The high resolution X-ray structure of VEGF has paved the way to introduce new small molecular inhibitors by structure-based virtual screening. In this study using different alkaloid molecules as potential novel inhibitors of VEGF, we proposed three alkaloid candidates for inhibiting VEGF and VEGFR mediated angiogenesis. As these three alkaloid compounds exhibited high scoring functions, which also highlights their high binding ability, it is evident that these alkaloids can be taken to further drug development pipelines for use as novel lead compounds to design new and effective drugs against cancer.

• The Plant Pathology Journal
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• v.24 no.3
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• pp.245-268
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• 2008

The outcome of plant-pathogen interactions is influenced significantly by endogenous small molecules that coordinate plant defence responses. There is currently tremendous scientific and commercial interest in identifying chemicals whose exogenous application activates plant defences and affords protection from pathogen infection. In this review, we provide a survey of compounds known to induce disease resistance in plants, with particular emphasis on how each compound was originally identified, its putative or demonstrated mechanism of defence induction, and the known biological target(s) of each chemical. Larger polymeric structures and peptides/proteins are also discussed in this context. The quest for novel defence-inducing molecules would be aided by the capability for high-throughput analysis of candidate compounds, and we describe some issues associated with the development of these types of screens. Subsequent characterization of hits can be a formidable challenge, especially in terms of identifying chemical targets in plant cells. A variety of powerful molecular tools are available for this characterization, not only to provide insight into methods of plant defence activation, but also to probe fundamental biological processes. Furthermore, these investigations can reveal molecules with significant commercial potential as crop protectants, although a number of factors must be considered for this potential to be realized. By highlighting recent progress in the application of chemical biology techniques for the modulation of plant-pathogen interactions, we provide some perspective on the exciting opportunities for future progress in this field of research.

• Clinical and Experimental Pediatrics
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• v.65 no.5
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• International Journal of Oral Biology
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• v.45 no.3
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• pp.77-83
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• 2020

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.

• Proceedings of the Korean Society of Life Science Conference
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• 2008.10a
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• pp.75.2-75.2
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• 2008