Byeong-Chul Kang

Detection and Genotyping of Mycobacterium Species from Clinical Isolates and Specimens by Oligonucleotide Array

ABSTRACT Identification of pathogenic Mycobacterium species is important for a successful diagnosis of mycobacteriosis. The purpose of this study was to develop an oligonucleotide array which could detect and differentiate mycobacteria to the species level by using the internal transcribed spacer (ITS) sequence. Using a genus-specific probe and 20 species-specific probes including two M. avium-intracellulare complex (MAC)-specific probes, we have developed an ITS-based oligonucleotide array for the rapid and reliable detection and discrimination of M. tuberculosis, MAC, M. fortuitum, M. chelonae, M. abscessus, M. kansasii, M. gordonae, M. scrofulaceum, M. szulgai, M. vaccae, M. xenopi, M. terrae, M. flavescens, M. smegmatis, M. malmoense, M. simiae, M. marinum, M. ulcerans, M. gastri, and M. leprae. All mycobacteria were hybridized with a genus-specific probe (PAN-03) for detection of the genus Mycobacterium. Mycobacterial species were expected to show a unique hybridization pattern with species-specific probes, except for M. marinum and M. ulcerans, which were not differentiated by ITS-based probe. Among the species-specific probes, two kinds of species-specific probes were designed for MAC in which there were many subspecies. The performance of the oligonucleotide array assay was demonstrated by using 46 reference strains, 149 clinical isolates, and 155 clinical specimens. The complete procedure (DNA extraction, PCR, DNA hybridization, and scanning) was carried out in 4.5 h. Our results indicated that the oligonucleotide array is useful for the identification and discrimination of mycobacteria from clinical isolates and specimens in an ordinary clinical laboratory.

Experimental and Numerical Investigation on Impact Performance of Carbon Reinforced Aluminum Laminates

It is known that fiber metal laminates (FML) as one of hybrid materials with thin metal sheets and fiber/epoxy layers have the characteristics of the excellent damage tolerance, fatigue and impact properties with a relatively low density. Therefore, the mechanical components using FML can contribute the enhanced safety level of the sound construction toward the whole body. In this study, the impact performance of carbon reinforced aluminum laminates (CARAL) is investigated by experiments and numerical simulations. Drop weight tests are carried out with the weight of 4.7 kg at the speed of 1 and 2 m/s, respectively. Dynamic non-linear transient analyses are also accomplished using a finite element analysis software, ABAQUS. The experiment results and numerical results are compared with impact load-time histories. Also, energy-time histories are applied to investigate the impact performance of CARAL.

Antimicrobial peptides in the centipede Scolopendra subspinipes mutilans

The centipede Scolopendra subspinipes mutilans is an environmentally beneficial and medically important arthropod species. Although this species is increasingly applied as a reliable source of new antimicrobial peptides, the transcriptome of this species is a prerequisite for more rational selection of antimicrobial peptides. In this report, we isolated total RNA from the whole body of adult centipedes, S. subspinipes mutilans, that were nonimmunized and immunized against Escherichia coli, and we generated a total of 77,063 pooled contigs and singletons using high-throughput sequencing. To screen putative antimicrobial peptides, in silico analyses of the S. subspinipes mutilans transcriptome were performed based on the physicochemical evidence of length, charge, isoelectric point, and in vitro and in vivo aggregation scores together with the existence of continuous antimicrobial peptide stretches. Moreover, we excluded some transcripts that showed similarity with both previously known antimicrobial peptides and the human proteome, had a proteolytic cleavage site, and had downregulated expression compared with the nonimmunized sample. As a result, we selected 17 transcripts and tested their antimicrobial activity with a radial diffusion assay. Among them, ten synthetic peptides experimentally showed antimicrobial activity against microbes and no toxicity to mouse erythrocytes. Our results provide not only a useful set of antimicrobial peptide candidates and an efficient strategy for novel antimicrobial peptide development but also the transcriptome data of a big centipede as a valuable resource.

Genome sequence of pacific abalone (Haliotis discus hannai): the first draft genome in family Haliotidae

Abstract Background: Abalones are large marine snails in the family Haliotidae and the genus Haliotis belonging to the class Gastropoda of the phylum Mollusca. The family Haliotidae contains only one genus, Haliotis, and this single genus is known to contain several species of abalone. With 18 additional subspecies, the most comprehensive treatment of Haliotidae considers 56 species valid [1]. Abalone is an economically important fishery and aquaculture animal that is considered a highly prized seafood delicacy. The total global supply of abalone has increased 5-fold since the 1970s and farm production increased explosively from 50 mt to 103 464 mt in the past 40 years. Additionally, researchers have recently focused on abalone given their reported tumor suppression effect. However, despite the valuable features of this marine animal, no genomic information is available for the Haliotidae family and related research is still limited. To construct the H. discus hannai genome, a total of 580-G base pairs using Illumina and Pacbio platforms were generated with 322-fold coverage based on the 1.8-Gb estimated genome size of H. discus hannai using flow cytometry. The final genome assembly consisted of 1.86 Gb with 35 450 scaffolds (>2 kb). GC content level was 40.51%, and the N50 length of assembled scaffolds was 211 kb. We identified 29 449 genes using Evidence Modeler based on the gene information from ab initio prediction, protein homology with known genes, and transcriptome evidence of RNA-seq. Here we present the first Haliotidae genome, H. discus hannai, with sequencing data, assembly, and gene annotation information. This will be helpful for resolving the lack of genomic information in the Haliotidae family as well as providing more opportunities for understanding gastropod evolution.

A novel semantic framework for toxicogenomics

Complex biological data stored in bioinformatics databases often require additional knowledge to specify and constrain the values held in a particular database. One method of capturing knowledge within bioinformatics applications and databases is the use of ontologies. Existing ontologies can model components of environmental risk and corresponding events, but cannot synthesize them or describe the broader framework of ideas used to conceptualize and study environmental risk. Environmental Risk Ontology (ERO) aims to synthesize and describe a framework for investigating environmental risk. ERO is intended as a metadata framework for data and literature curation and data mining. In this review, we summarize and describe the basic public databases available for toxicogenomics and present a novel approach that uses a semantic knowledge base — which also organizes the literature in a growing, comprehensive bibliographic database — concerning environmental risk and toxicogenomics.

mRNA-centric semantic modeling for finding molecular signature of trace chemical in human blood

The vast quantities of information on toxicogenomics such as genome sequence, genotype, gene expression, phenotype, disease information, etc. are reflected in scientific literature. However, these various and heterogeneous data has to be reconstructed by proper data model to enhance our understanding. This study suggests a semantic modeling to organize heterogeneous data types and introduces techniques and concepts such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers. These concepts were used to represent complex biochemical networks relationship. The semantic modeling tool is used as an example to demonstrate how a domain such as risk assessment is represented and how this representation is utilized for research. In this work, we show focusing on mRNA centric semantic model as a representative. From experimental data, text-mining results and public databases we generate mRNA-centric semantic modeling and demonstrate its use by mining specific molecular networks together. Application of semantic modeling: 1. Common DEGs which are differentially expressed mRNA by VOCs are identified. 2. Diseases and biological processes associated with common DEGs are identified. 3. Finally subjects associated with common disease, biological process and DEGs are identified.

Decision supporting frame to estimate chronic exposure suspicion to VOC chemicals using mixed statistical model

In this paper, we examine the model for a chemical exposure decision support algorithm. Our purpose is to suggest the model frame to describe possibility of exposure with low-dose VOC chemicals for long time under normal circumstances at working place. Forensic rhetoric terms, non-exclusion exposure suspicion (NES) and exclusion exposure suspicion (EES), were defined and various statistical methods were combined basis of Bayesian approach. Decisiontree (DT) methods of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and naïve Bayes model were evaluated to classify 3 VOCs (toluene, xylene, and ehtybenzene) by means of the results of urinary test, gene expression and methylation expression experiments. Overall procedure is conducted by leave-one-out cross-validation that error rate of NES resulted in 11%.

Prediction of VOCs based on functional analysis by decision supporting system

In the industrial age, people are exposed to many hazardous substances in many ways. Generally, exposure is of low doses, but chronic symptoms are associated with many industrial pollutants, and therefore, early prediction of exposure is important. In this study, we intended to determine the reliability of the predictive modeling and biomarkers of a previous study, and to determine the related pathway of that biomarkers. We analyzed the key pathways and biological processes associated with volatile organic compounds (VOCs) from previous data — VOCs biomarker CRCT1, RUNX3, PCDH11X and PCSK6. In the analysis, inflammation and neoplasm were remarkably frequently occurring disease within the VOCs exposed body, and especially, exposure to toluene, presents a great likelihood of nerve disease or nervous system disease. Those diseases were related with the several biological processes, they are cell proliferation, apoptosis, inflammatory response, and nervous system development. This study shows probability that application of decision supporting systems, moreover it is helpful to decide whether VOCs exposure has occurred or not, and to predict negative effects.

Semantic data integration for toxicogenomic laboratory experiment management systems

Mircoarray technology leads rapid screening of differential expressed gene (DEG) from various kinds of chemical exposes. Using toxicogenomics for the risk assessment, various and heterogeneous data are contributed to each step, such as genome sequence, genotype, gene expression, phenotype, disease information etc. Accordingly ontology-based knowledge representations could prove to be successful in providing the semantics for the relationships of the drugs to a wide body of target information, a standardized annotation, integration and exchange of data. To derive actual roles of the DEGs, it is essentially required to construct interactions among DEGs and to link the known information of diseases. We depict reconstruction of semantic relationship among chemical, disease, and DEGs by using omics-data and laboratory experiment raw data in constructed toxicogenomic meta database. Omics- and experimental data are able to be easily uploaded and connected to the already constructed data network. This semantic data integration may represent the chemical-specific marker and target disease by integrated toxicogenomic data including complex expression profiles and experimental raw data. We expect that this system shows early promise in helping bridge the gap between pathophysiological processes and their molecular determinants.

Web-based Research Assistant Tools for Analysis of Microbial Diversity

The study of available genotypes (biodiversity analysis) in bacterial communities is of growing importance in several fields such as ecology, environmental technology, clinical diagnostics, etc. These culture-independent genotyping techniques, especially amplifying 16S rRNA genes, attempt to overcome some shortcomings of conventional cultivation method. Biodiversity analysis based on molecular technique were laborious for base-calling chromatogram, trimming primer sites, correcting strand directions, electing representative operation taxonomic units (OTU), etc. Also, biologists wanted intuitively to confirm results of the above processes. For making up these demands, we developed the web application based on Folder-Process-Filter (FPF) modeling with correspondence to classical Model-View-Controller model. The model of web application leads to keep virtues of simplicity and directness for development and management of the stepwise web interfaces. The web application was developed in Perl and CGI on Linux workstation. It can be freely accessed from http://home.pusan.ac.kr/～genome/tools/rat.htm.