• Journal of Microbiology and Biotechnology
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• v.19 no.12
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• pp.1497-1505
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• 2009

The thermophile Bacillus fordii MH602 was screened for stereospecifically hydrolyzing DL-5-substituted hydantoins to L-$\alpha$-amino acids. Since the reaction occurs at higher temperature, the advantages for enhancement of substrate solubility and for racemization of DL-5-substituted hydantoins during the conversion were achieved. The hydantoin metabolism gene cluster from thermophile is firstly reported in this paper. The genes involved in hydantoin utilization (hyu) were isolated on an 8.2-kb DNA fragment by restriction site-dependent PCR, and six ORFs were identified by DNA sequence analysis. The hyu gene cluster contained four genes with novel cluster organization characteristics: the hydantoinase gene hyuH, putative transport protein gene hyuP, hyperprotein gene hyuHP, and L-carbamoylase gene hyuC. The hyuH and hyuC genes were heterogeneously expressed in E. coli. The results indicated that hyuH and hyuC are involved in the conversion of DL-5-substituted hydantoins to an N-carbamyl intermediate that is subsequently converted to L-$\alpha$-amino acids. Hydantoinase and carbamoylase from B. fordii MH602 compared respectively with reported hydantoinase and carbamoylase showed the highest identities of 71% and 39%. The novel cluster organization characteristics and the difference of the key enzymes between thermopile B. fordii MH602 and other mesophiles were presumed to be related to the evolutionary origins of concerned metabolism.

• Korean Journal of Biological Psychiatry
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• v.20 no.4
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• pp.129-135
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• 2013

Aggression can be defined as 'behavior intended to harm another' which can be seen both from humans and animals. However, trying to understand aggression in a simplistic view may make it difficult to develop an integrated approach. So, we tried to explain aggression in a multidisciplinary approach, affected by various factors such as neuroanatomical structures, neurotransmitter, genes, and sex hormone. Parallel with animal models, human aggression can be understood with two phenomena, offensive aggression and defensive aggression. Neurobiological model of aggression give a chance to explain aggression with an imbalance between prefrontal regulatory influences and hyper-reactivity of the subcortical areas involved in affective evaluation, finally in an aspect of brain organization. Serotonin and GABA usually inhibit aggression and norepinephrine while glutamate and dopamine precipitate aggressive behavior. As there is no one gene which has been identified as a cause of aggression, functions between gene to gene interaction and gene to environment interaction are being magnified. Contributions of sex hormone to aggression, especially molecular biologic interaction of testosterone and regulation of estrogen receptor have been emphasized during the research on aggression. This multidisciplinary approach on aggression with types, neurochemical bases, and animal models can bring integrated interpretation on aggression.

• Journal of Plant Biotechnology
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• v.46 no.4
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• pp.255-273
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• 2019

Orchids are indispensable to the floriculture industry due to their unique floral organization. The flowers have two outer whorls of tepals including a lip (labellum), and two inner whorls, pollinia and gynostemiun (column). The floral organization and development is controlled at the molecular level, mainly by the MADS-box gene family, comprising homeotic genes divided into type I and type II groups. The type I group has four sub-groups, Mα, Mβ, Mγ, and Mδ, playing roles in seed, embryo, and female reproductive organ development; the type II group genes form classes A, B, C, D, and E, which are a part of the MIKC^C subgroup with specific roles in florigenesis and organization. The coordinated functioning of these classes regulates the development of various floral whorls. The availability of genome and transcriptome sequence data for Phalaenopsis equestris offers an opportunity to validate the ABCDE model of flower development. Hence, this study sought to characterize the MADS-box gene family and elucidate of the ABCDE model. A total of 48 identified MADS-box proteins, including 20 type I [Mα (12), Mγ (8)] and 28 type II [MIKC^C (27), MIKC*(1)] members, were characterized for physico-chemical features and domains and motifs organization. The exon-intron distribution and the upstream cis-regulatory elements in the promoter regions of MADS-box genes were also analysed. The discrete pace of duplication events in type I and type II genes suggested differential evolutionary constraints between groups. The correlation of spatio-temporal expression pattern with the presence of specific cis-regulatory elements and putative protein-protein interaction within the different classes of MADS-box gene family endorse the ABCDE model of floral development.

• Genomics & Informatics
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• v.9 no.4
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• pp.173-180
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• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.

• The Korea Genome Conference
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• 2006.09a
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• pp.53-53
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• 2006

• Proceedings of the Korean Society of Crop Science Conference
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• 2006.11a
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• pp.22-22
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• 2006

• The Korea Genome Conference
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• 2002.08a
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• pp.50.1-50.1
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• 2002

• The Korea Genome Conference
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• 2004.07a
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• pp.38.2-38.2
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• 2004

• The Korea Genome Conference
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• 2004.07a
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• pp.39.1-39.1
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• 2004

• The Korea Genome Conference
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• 2004.07a
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• pp.56-56
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• 2004