• Korean Journal of Microbiology
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• v.43 no.1
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• pp.72-75
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• 2007

Using co-immunoprecipitation, we identified proteins interacting with Streptomyces coelicolor RNase ES, an ortholog of Escherichia coli RNase E that plays a major role in RNA decay and processing. Polyphosphate kinase and a homolog of exoribonuclease polynucleotide phosphorylase, guanosine pentaphosphate synthetase I that use inorganic phophate were co-precipitated with RNase E, indicating a possibility of S. coelicolor RNase ES to form a multiprotein complex called degradosome, which has been shown to be formed by RNase E in E. coli. Polynucleotide phophorylase proteins from these two phylogenetically distantly related bacteria species showed similar RNA cleavage action in vitro. These results imply the ability of RNase ES to form a multiprotein complex that has structurally and functionally similar to that of E. coli degradosome.

• Journal of Microbiology and Biotechnology
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• v.27 no.11
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• pp.1999-2009
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• 2017

The secretion efficiency of a protein in a Sec-type secretion system is mainly determined by an N-terminal signal peptide and its combination with its cognate protein. Five signal peptides, namely, two synthetic Sec-type and three Bacillus licheniformis alpha-amylase-derived signal peptides, were compared for periplasmic expression of the human growth hormone (hGH) in E. coli. Based on in silico predictions on the signal peptides' cleavage efficiencies and their corresponding mRNA secondary structures, a number of amino acid substitutions and silent mutations were considered in the modified signal sequences. The two synthetic signal peptides, specifically designed for hGH secretion in E. coli, differ in their N-terminal positively charged residues and hydrophobic region lengths. According to the mRNA secondary structure predictions, combinations of the protein and each of the five signal sequences could lead to different outcomes, especially when accessibility of the initiator ATG and ribosome binding sites were considered. In the experimental stage, the two synthetic signal peptides displayed complete processing and resulted in efficient secretion of the mature hGH in periplasmic regions, as was demonstrated by protein analysis. The three alpha-amylase-derived signal peptides, however, were processed partially from their precursors. Therefore, to achieve efficient secretion of a protein in a heterologous system, designing a specific signal peptide by using a combined approach of optimizations of the mRNA secondary structure and the signal peptide H-domain and cleavage site is recommended.

• Interdisciplinary Bio Central
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• v.4 no.3
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• pp.6.1-6.12
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• 2012

Parkinson's disease (PD) is a complicated neurodegenerative disorder although it is oftentimes defined by clinical motor symptoms originated from age dependent and progressive loss of dopaminergic neurons in the midbrain. The pathogenesis of PD involves dopaminergic and nondopaminergic neurons in many brain regions and the molecular mechanisms underlying the death of different cell types still remain to be elucidated. There are indications that PD causing disease processes occur in a global scale ranging from DNA to RNA, and proteins. Several PD-associated genes have been reported to play diverse roles in controlling cellular functions in different levels, such as chromatin structure, transcription, processing of mRNA, translational modulation, and posttranslational modification of proteins. The advent of quantitative high throughput screening (HTS) tools makes it possible to monitor systemic changes in DNA, RNA and proteins in PD models. Combined with dopamine neuron isolation or derivation of dopamine neurons from PD patient specific induced pluripotent stem cells (PD iPSCs), HTS techonologies will provide opportunities to draw PD causing sequences of molecular events in pathologically relevant PD samples. Here I discuss previous studies that identified molecular functions in which PD genes are involved, especially those signaling pathways that can be efficiently studied using HTS methodologies. Brief descriptions of quantitative and systemic tools looking at DNA, RNA and proteins will be followed. Finally, I will emphasize the use and potential benefits of PD iPSCs-derived dopaminergic neurons to screen signaling pathways that are initiated by PD linked gene mutations and thus causative for dopaminergic neurodegneration in PD.

• Genomics & Informatics
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• v.19 no.4
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• pp.49.1-49.11
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• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• Animal Bioscience
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• v.37 no.6
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• pp.993-1000
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• 2024

Objective: This study was conducted to investigate the differential expression of the major histocompatibility complex (MHC) gene region in Eimeria-infected broiler. Methods: We profiled gene expression of Eimeria-infected and uninfected ceca of broilers sampled at 4, 7, and 21 days post-infection (dpi) using RNA sequencing. Differentially expressed genes (DEGs) between two sample groups were identified at each time point. DEGs located on chicken chromosome 16 were used for further analysis. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis was conducted for the functional annotation of DEGs. Results: Fourteen significant (false discovery rate <0.1) DEGs were identified at 4 and 7 dpi and categorized into three groups: MHC-Y class I genes, MHC-B region genes, and non-MHC genes. In Eimeria-infected broilers, MHC-Y class I genes were upregulated at 4 dpi but downregulated at 7 dpi. This result implies that MHC-Y class I genes initially activated an immune response, which was then suppressed by Eimeria. Of the MHC-B region genes, the DMB1 gene was upregulated, and TAP-related genes significantly implemented antigen processing for MHC class I at 4 dpi, which was supported by KEGG pathway analysis. Conclusion: This study is the first to investigate MHC gene responses to coccidia infection in chickens using RNA sequencing. MHC-B and MHC-Y genes showed their immune responses in reaction to Eimeria infection. These findings are valuable for understanding chicken MHC gene function.

• Journal of Microbiology and Biotechnology
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• v.27 no.9
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• pp.1566-1575
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• 2017

MicroRNAs (miRNAs) are abundant in bovine milk and milk derived from other livestock, and they have functional roles in infants and in the secretion process of mammary glands. However, few studies have evaluated miRNAs in dairy processes, such as during cheese making and ripening. Thus, we investigated the characteristics of milk-derived miRNAs during the manufacturing and ripening of Camembert cheese as well as the microbiota present using the quantitative reverse transcription polymer chain reaction (RT-qPCR) and 16S rRNA pyrosequencing, respectively. Pyrosequencing showed that the cheese microbiota changed dramatically during cheese processing, including during the pasteurization, starter culture, and ripening stages. Our results indicated that the RNA contents per $200mg/200{\mu}l$ of the sample increased significantly during cheese-making and ripening. The inner cheese fractions had higher RNA contents than the surfaces after 12 and 22 days of ripening in a time-dependent manner (21.9 and 13.2 times higher in the inner and surface fractions than raw milk, respectively). We performed a comparative analysis of the miRNAs in each fraction by RT-qPCR. Large amounts of miRNAs (miR-93, miR-106a, miR-130, miR-155, miR-181a, and miR-223) correlated with immune responses and mammary glands were present in aged cheese, with the exception of miR-223, which was not present on the surface. Considerable amounts of miRNAs were also detected in whey, which is usually disposed of during the cheese-making process. Unexpectedly, there were no significant correlations between immune-related miRNAs and the microbial populations during cheese processing. Taken together, these results show that various functional miRNAs are present in cheese during its manufacture and that they are dramatically increased in amount in ripened Camembert cheese, with differences according to depth.

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.198.1-198
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• 2000

No Abstract, See Full Text

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.23 no.1
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• pp.94-110
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• 2010

Objective : This study was performed to evaluate the effect of immune reaction inductive substances such as phorbol-myristate-acetate(PMA), lipopolysaccharide(LPS), dermato-phagoides pteronyssus crude extract(DPE), dinitrochloro-benzene(DNCB) and Cryptotympana pustulata(CP), the Cryptotympana pustulata extracting substance at simultaneously on the translocation of nuclear factor-kappa B(NF-${\kappa}B$) towards to the nucleus and the mRNA expression patterns of various cytokine genes in Human acute monocytic leukemia cell line(THP-1 cells), monocytes of human. Experiment : To analyze cytokine genes expression patterns, the RT-PCR method was used, measuring tumor necrosis factor(TNF)-$\alpha$ that had been secreted during cell culture in the ELISA method. The morphological change in the cell observed during THP-1 cell culture was observed using a scanning electron microscope (SEM) and the quantitative distribution in the cell NF-${\kappa}B$ was analyzed through immunocytochemistry and a confocal microscopy. Result : CP showed different influences onto the mRNA expression patterns of cytokine genes with PMA, LPS. DPE and DNCB according to the types of immune inductive substances in the THP-1 cells. The expressions of inter-leukin(IL)-10, interferon(INF)-$\gamma$, TNF-$\alpha$ and monocyte chemoattractantant protein(MCP)-1 induced by PMA were suppressed by CP while the expression of transforming growth factor(TGF)-$\beta$ was promoted. Regarding the secretion pattern of TNF-$\alpha$ according to PMA processing, its secretion amount was increased by CP concurrent processing, in case of processing CP onto PMA and LPS, We discovered that the secretion amount of TNF-$\alpha$ was increased. Upon processing PMA and LPS on the THP-1 cell strain at the same time or either additionally processing CP thereon, the movement increase towards the nucleus from the NF-${\kappa}B$ cell cytoplasm, a transcription factor was able to be observed. Conclusion : In this study, Cryptotympana pustulata extracting substance was confirmed that it had an influence on expression patterns of cytokine genes according to the actions of a variety kinds of immune reaction inductive substances processed on the monocyte THP-1 cell of humans. Therefore, additional studies as for the immune adjusting function of Cryptotympana pustulata are considered to be able to offer important materials for curing immune abnormal diseases such as atopy dermatitis afterward.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• Journal of Computing Science and Engineering
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• v.4 no.4
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• pp.350-367
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• 2010

Microarray technology is an interdisciplinary technique that promises a revolutionary progress toward better health and improved quality of life. The paper focuses on the development of an efficient software package, equipped with already well-known methods; also some new methods are proposed that will allow the processing and analysis of thousands of genes on microarray images. The microarray analysis software package (called SmartArray), newly proposed in this paper verifies, through microarray analysis, dramatic changes in the mRNA, protein, and activity level in the rat retina during light deprivation, which have been demonstrated in previous biological experiments. The analysis results demonstrate that SmartArray can successfully find many changes in gene expression levels in each subarray and classify them according to their significance.