• 한국정보과학회논문지:데이타베이스
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• 제30권6호
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• pp.573-584
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• 2003

최근 유전체학과 단백질체학 분야에서 생성되는 방대한 분량의 데이타로부터 생물학적 의미를 추출해내기 위한 생물정보학적인 도구들에 대한 필요성이 크게 대두되고 있다. 본 논문에서는 세포 신호전달 경로에 관한 정보를 효율적으로 표현, 저장함은 물론 저장된 데이타로부터 생물학적 의미를 추출할 수 있도록 하기 위한 다양한 요구 조건들을 생물학자의 관점에서 분석하고, 이들 요구조건을 체계적으로 반영하여 설계한 ROSPath 데이타베이스 시스템을 제안한다. ROSPath 데이타 모델에서는 향후의 확장성을 고려하여 불완전한 지식의 표현이 가능하도록 하며 인터넷상에서 기존의 다른 생화학 데이타베이스를 공유할 수 있는 연결성을 제공한다. 또한, 객체지향 모델을 이용하여 계층적인 구성을 제공함으로써 효율적인 검색을 지원한다. ROSPath 데이타 모델은 두 가지 주요 데이타 요소인 ‘바이오 개체’와 ‘상호작용’으로 정의된다. 바이오 개체는 세포 신호전달 경로에 관여하는 단백질과 단백질 상태 등과 같은 개개의 생화학적인 개체를 의미하고, 상호작용은 단백질 상태 전이나 화학 반응, 단백질-단백질 상호작용 등과 같은 바이오 개체들 간의 다양한 관계 및 신호전달과정을 설명한다. 제안된 ROSPath 데이타 모델을 이용하여 구성되는 복잡한 정보 네트워크는 다양한 생화학 프로세스들을 기술하고 분석하는 데에 활용할 수 있다.

• Genomics & Informatics
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• 제12권4호
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• pp.181-186
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• 2014

Genome-wide association studies have proven the highly polygenic architecture of complex diseases or traits; therefore, single-locus-based methods are usually unable to detect all involved loci, especially when individual loci exert small effects. Moreover, the majority of associated single-nucleotide polymorphisms resides in non-coding regions, making it difficult to understand their phenotypic contribution. In this work, we studied epistatic interactions associated with three common diseases using Korea Association Resource (KARE) data: type 2 diabetes mellitus (DM), hypertension (HT), and coronary artery disease (CAD). We showed that epistatic single-nucleotide polymorphisms (SNPs) were enriched in enhancers, as well as in DNase I footprints (the Encyclopedia of DNA Elements [ENCODE] Project Consortium 2012), which suggested that the disruption of the regulatory regions where transcription factors bind may be involved in the disease mechanism. Accordingly, to identify the genes affected by the SNPs, we employed whole-genome multiple-cell-type enhancer data which discovered using DNase I profiles and Cap Analysis Gene Expression (CAGE). Assigned genes were significantly enriched in known disease associated gene sets, which were explored based on the literature, suggesting that this approach is useful for detecting relevant affected genes. In our knowledge-based epistatic network, the three diseases share many associated genes and are also closely related with each other through many epistatic interactions. These findings elucidate the genetic basis of the close relationship between DM, HT, and CAD.

• Genes and Genomics
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• 제40권12호
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• pp.1279-1285
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• 2018

Interdigitating dendritic cell sarcoma (IDCS) is an aggressive neoplasm and is an extremely rare disease, with a challenging diagnosis. Etiology of IDCS is also unknown and most studies with only case reports. In our case, immunohistochemistry showed that the tumor cells were positive for S100, CD45, and CD68, but negative for CD1a and CD21. This study aimed to investigate the causative factors of IDCS by sequencing the protein-coding regions of IDCS. We performed whole-exome sequencing with genomic DNA from blood and sarcoma tissue of the IDCS patient using the Illumina Hiseq 2500 platform. After that, we conducted Sanger sequencing for validation of sarcoma-specific variants and gene ontology analysis using DAVID bioinformatics resources. Through comparing sequencing data of sarcoma with normal blood, we obtained 15 nonsynonymous single nucleotide polymorphisms (SNPs) as sarcoma-specific variants. Although the 15 SNPs were not validated by Sanger sequencing due to tumor heterogeneity and low sensitivity of Sanger sequencing, we examined the function of the genes in which each SNP is located. Based on previous studies and gene ontology database, we found that POLQ encoding DNA polymerase theta enzyme and FNIP1 encoding tumor suppressor folliculin-interacting protein might have contributed to the IDCS. Our study provides potential causative genetic factors of IDCS and plays a role in advancing the understanding of IDCS pathogenesis.

• Genomics & Informatics
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• 제13권4호
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• pp.132-136
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• 2015

Studies of cancer heterogeneity have received considerable attention recently, because the presence or absence of resistant sub-clones may determine whether or not certain therapeutic treatments are effective. Previously, we have reported G64, a co-regulated gene module composed of 64 different genes, can differentiate tumor intra- or inter-subpopulations in lung adenocarcinomas (LADCs). Here, we investigated whether the G64 module genes were also expressed distinctively in different subpopulations of other cancers. RNA sequencing-based transcriptome data derived from 22 cancers, except LADC, were downloaded from The Cancer Genome Atlas (TCGA). Interestingly, the 22 cancers also expressed the G64 genes in a correlated manner, as observed previously in an LADC study. Considering that gene expression levels were continuous among different tumor samples, tumor subpopulations were investigated using extreme expressional ranges of G64-i.e., tumor subpopulation with the lowest 15% of G64 expression, tumor subpopulation with the highest 15% of G64 expression, and tumor subpopulation with intermediate expression. In each of the 22 cancers, we examined whether patient survival was different among the three different subgroups and found that G64 could differentiate tumor subpopulations in six other cancers, including sarcoma, kidney, brain, liver, and esophageal cancers.

• Genomics & Informatics
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• 제21권2호
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• pp.21.1-21.14
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• 2023

Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as "Uncharacterized." Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

• Biomolecules & Therapeutics
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• 제18권1호
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• pp.39-47
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• 2010

Brain-derived neurotrophic factor (BDNF) is a neurotrophic factor involved in neuronal differentiation, plasticity, survival and regeneration. BDNF draws massive attention mainly due to the potential as a therapeutic target in neurological diseases such as depression and Alzheimer's disease. In a primary screening for the natural compounds enhancing BDNF release from cultured rat primary cortical neuron, we found that compounds such as baicalein, tanshinone IIa, cinnamic acid, epiberberine, genistein and wogonin among many others increased BDNF release. All the compounds at $0.1{\mu}M$ of concentration barely showed stimulatory effect on BDNF induction, however, their combination (mixture 1; baicalein, tanshinone IIa and cinnamic acid, mixture 2; epiberberine, genistein and wogonin) showed synergistic increase in BDNF release as well as mRNA and protein expression. The level of BDNF expression was comparable to the maximum BDNF stimulation attainable by a positive control oroxylin A ($20{\mu}M$) without cell toxicity as determined by MTT analysis. Both mixtures synergistically increased the phosphorylation of extracellular signal-regulated kinase (ERK) as well as cAMP response element binding protein (CREB), an immediate and essential regulator of BDNF expression. Similar to these results, mixture of these compounds synergistically inhibited the up-regulation of inducible nitric oxide synthase (iNOS) induced by lipopolysaccharide treatments in rat primary astrocytes. These results suggest that the combinatorial treatment of natural compounds in lower concentration might be a useful strategy to obtain sufficient BDNF stimulation in neurological disease condition such as depression, while minimizing potential side effects and toxicity of higher concentration of a single compound.

• Asian-Australasian Journal of Animal Sciences
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• 제30권8호
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• pp.1183-1189
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• 2017

Objective: Owing to the public availability of complete genome sequences, including avian species, massive bioinformatics analyses may be conducted for computational gene prediction and the identification of gene regulatory networks through various informatics tools. However, to evaluate the biofunctional activity of a predicted target gene, in vivo and in vitro functional genomic analyses should be a prerequisite. Methods: Due to a lack of quail genomic sequence information, we first identified the partial genomic structure and sequences of the quail SH3 domain containing ring finger 2 (SH3RF2) gene. Subsequently, SH3RF2 was knocked out using clustered regularly interspaced short palindromic repeat/Cas9 technology and single cell-derived SH3RF2 mutant sublines were established to study the biofunctional activity of SH3RF2 in quail myoblast (QM7) cells during muscle differentiation. Results: Through a T7 endonuclease I assay and genotyping analysis, we established an SH3RF2 knockout (KO) QM7#4 subline with 61 and 155 nucleotide deletion mutations in SH3RF2. After the induction of myotube differentiation, the expression profiles were analyzed and compared between regular QM7 and SH3RF2 KO QM7#4 cells by global RNA sequencing and bioinformatics analysis. Conclusion: We did not detect any statistically significant role of SH3RF2 during myotube differentiation in QM7 myoblast cells. However, additional experiments are necessary to examine the biofunctional activity of SH3RF2 in cell proliferation and muscle growth.

• Tuberculosis and Respiratory Diseases
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• 제87권1호
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• pp.52-64
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• 2024

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.

• Journal of Genetic Medicine
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• 제17권1호
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• pp.11-15
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• 2020

Purpose: The objective of this study was to analyze the results of several noninvasive prenatal tests (NIPTs) from a single center and confirm their efficacy and reliability. In addition, we aimed to confirm the changes in the number of invasive tests performed after introducing NIPT. Materials and Methods: NIPT data from a large single center from March 2014 to November 2018 were analyzed. Karyotyping was confirmed based on chorionic villus sampling, amniocentesis, or postnatal cord/peripheral blood sampling. Data on maternal age, gestational age, fetal fraction, and ultrasonographic results were analyzed. As the secondary outcome, the number of amniocentesis cases before and after the introduction of NIPT was compared. Results: Overall, 1,591 single pregnancy cases that underwent NIPT were enrolled. The mean maternal age was 36.05 (22-45) years. The average gestational age and fetal fraction were 12⁺¹ (9⁺³ to 27⁺¹) weeks and 10.95% (3.6% to 31.3%), respectively. A total of 1,544 cases (97.0%) were reported to have negative NIPT results and 40 (2.5%) had positive NIPT results. The sensitivity and specificity of the overall abnormalities in NIPT were 96.29% and 99.36%, respectively. The positive predictive value (PPV) and negative predictive value were 72.22% and 99.93% respectively. The mean number of amniocentesis cases were 21.7 per month (21.7±3.9), which significantly decreased from 31.5 per month (31.5±4.8) before conducting NIPT as a screening test. Conclusion: NIPT is currently a useful, powerful, and safe screening test. In particular, trisomy 21 is highly specific due to its high PPV. NIPT can reduce the potential risks of procedure-related miscarriages during invasive testing.

• Journal of Pharmaceutical Investigation
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• 제30권3호
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• pp.191-199
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• 2000

Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.