• Bulletin of the Korean Chemical Society
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• 제35권7호
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• pp.2197-2200
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• 2014

• Asian-Australasian Journal of Animal Sciences
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• 제26권1호
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• pp.19-29
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• 2013

Marbling (intramuscular fat) is an important trait that affects meat quality and is a casual factor determining the price of beef in the Korean beef market. It is a complex trait and has many biological pathways related to muscle and fat. There is a need to identify functional modules or genes related to marbling traits and investigate their relationships through a weighted gene co-expression network analysis based on the system level. Therefore, we investigated the co-expression relationships of genes related to the 'marbling score' trait and systemically analyzed the network topology in Hanwoo (Korean cattle). As a result, we determined 3 modules (gene groups) that showed statistically significant results for marbling score. In particular, one module (denoted as red) has a statistically significant result for marbling score (p = 0.008) and intramuscular fat (p = 0.02) and water capacity (p = 0.006). From functional enrichment and relationship analysis of the red module, the pathway hub genes (IL6, CHRNE, RB1, INHBA and NPPA) have a direct interaction relationship and share the biological functions related to fat or muscle, such as adipogenesis or muscle growth. This is the first gene network study with m.logissimus in Hanwoo to observe co-expression patterns in divergent marbling phenotypes. It may provide insights into the functional mechanisms of the marbling trait.

• 한국균학회소식:학술대회논문집
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• 한국균학회 2014년도 춘계학술대회 및 임시총회
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• pp.27-28
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• 2014

Beauveria bassiana (Cordycipitaceae, Hypocreales, Ascomycota) is an anamorphic fungus having a potential to be used as a biological control agent because it parasitizes a wide range of arthropod hosts including termites, aphids, beetles and many other insects. A number of bioactive secondary metabolites (SMs) have been isolated from B. bassiana and functionally verified. Among them, beauvericin and bassianolide are cyclic depsipeptides with antibiotic and insecticidal effects belonging to the enniatin family. Non-ribosomal peptide synthetases (NRPSs) play a crucial role in the synthesis of these secondary metabolites. NRPSs are modularly organized multienzyme complexes in which each module is responsible for the elongation of proteinogenic and non-protein amino acids, as well as carboxyl and hydroxyacids. A minimum of three domains are necessary for one NRPS elongation module: an adenylation (A) domain for substrate recognition and activation; a tholation (T) domain that tethers the growing peptide chain and the incoming aminoacyl unit; and a condensation (C) domain to catalyze peptide bond formation. Some of the optional domains include epimerization (E), heterocyclization (Cy) and oxidation (Ox) domains, which may modify the enzyme-bound precursors or intermediates. In the present study, we analyzed genomes of B. bassiana and its allied species in Hypocreales to verify the distribution of NRPS-encoding genes involving biosynthesis of beauvericin and bassianolide, and to unveil the evolutionary processes of the gene clusters. Initially, we retrieved completely or partially assembled genomic sequences of fungal species belonging to Hypocreales from public databases. SM biosynthesizing genes were predicted from the selected genomes using antiSMASH program. Adenylation (A) domains were extracted from the predicted NRPS, NRPS-like and NRPS-PKS hybrid genes, and used them to construct a phylogenetic tree. Based on the preliminary results of SM biosynthetic gene prediction in B. bassiana, we analyzed the conserved gene orders of beauvericin and bassianolide biosynthetic gene clusters among the hypocrealean fungi. Reciprocal best blast hit (RBH) approach was performed to identify the regions orthologous to the biosynthetic gene cluster in the selected fungal genomes. A clear recombination pattern was recognized in the inferred A-domain tree in which A-domains in the 1st and 2nd modules of beauvericin and bassianolide synthetases were grouped in CYCLO and EAS clades, respectively, suggesting that two modules of each synthetase have evolved independently. In addition, inferred topologies were congruent with the species phylogeny of Cordycipitaceae, indicating that the gene fusion event have occurred before the species divergence. Beauvericin and bassianolide synthetases turned out to possess identical domain organization as C-A-T-C-A-NM-T-T-C. We also predicted precursors of beauvericin and bassianolide synthetases based on the extracted signature residues in A-domain core motifs. The result showed that the A-domains in the 1st module of both synthetases select D-2-hydroxyisovalerate (D-Hiv), while A-domains in the 2nd modules specifically activate L-phenylalanine (Phe) in beauvericin synthetase and leucine (Leu) in bassianolide synthetase. antiSMASH ver. 2.0 predicted 15 genes in the beauvericin biosynthetic gene cluster of the B. bassiana genome dispersed across a total length of approximately 50kb. The beauvericin biosynthetic gene cluster contains beauvericin synthetase as well as kivr gene encoding NADPH-dependent ketoisovalerate reductase which is necessary to convert 2-ketoisovalarate to D-Hiv and a gene encoding a putative Gal4-like transcriptional regulator. Our syntenic comparison showed that species in Cordycipitaceae have almost conserved beauvericin biosynthetic gene cluster although the gene order and direction were sometimes variable. It is intriguing that there is no region orthologous to beauvericin synthetase gene in Cordyceps militaris genome. It is likely that beauvericin synthetase was present in common ancestor of Cordycipitaceae but selective gene loss has occurred in several species including C. militaris. Putative bassianolide biosynthetic gene cluster consisted of 16 genes including bassianolide synthetase, cytochrome P450 monooxygenase, and putative Gal4-like transcriptional regulator genes. Our synteny analysis found that only B. bassiana possessed a bassianolide synthetase gene among the studied fungi. This result is consistent with the groupings in A-domain tree in which bassianolide synthetase gene found in B. bassiana was not grouped with NRPS genes predicted in other species. We hypothesized that bassianolide biosynthesizing cluster genes in B. bassiana are possibly acquired by horizontal gene transfer (HGT) from distantly related fungi. The present study showed that B. bassiana is the only species capable of producing both beauvericin and bassianolide. This property led to B. bassiana infect multiple hosts and to be a potential biological control agent against agricultural pests.

• Bioinformatics and Biosystems
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• 제2권1호
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• pp.24-27
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• 2007

Human cell regulatory mechanism is one of suspicious problems among biologists. Here we tried to uncover the human breast cancer cell regulatory mechanism from gene expression data (Marc J. Van de vijver, et. al., 2002) using a module network algorithm which is suggested by Segal, et. al.(2003) Finally, we derived a module network which consists of 50 modules and 10 tree depths. Moreover, to validate this candidate network, we applied a GO enrichment test and known transcription factor-target relationships from Transfac(R) (V. Matys, et. al, 2006) and HPRD database (Peri, S. et al., 2003).

• 한국미생물·생명공학회지
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• 제44권3호
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• pp.391-399
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• 2016

Melithiazol은 점액세균 Melitangium lichenicola, Archangium gephyra, Myxococcus stipitatus에 의해 생산되는 항진균 물질이다. M. lichenicola의 melithiazol 생합성 유전자는 이미 알려져 있지만, A. gephyra와 M. stipitatus의 melithiazol 생합성 유전자들은 아직까지 밝혀져 있지 않다. 본 연구에서는 유전체 서열 분석과 돌연변이 분석을 통해 M. stipitatus DSM 14675 균주로부터 37.3 kb 크기의 melithiazol 생합성 유전자군을 발견하였다. 이 유전자군은 9개(MYSTI_04973−MYSTI_04965)의 유전자로 구성되어 있는데, 4개의 polyketide synthase 모듈과 3개의 non-ribosomal peptide synthase 모듈, 그리고 fumarylacetoacetate hydrolase, S-adenosylmethionine-dependent methyltransferase, nitrilase를 암호화하는 것으로 분석되었다. 플라스미드 삽입 돌연변이를 통해 MYSTI_04972 유전자 또는 MYSTI_04973를 불활성화시켰을 때 melithiazol 생산능이 상실되었다. MYSTI_04972부터 MYSTI_04965까지의 8개 유전자가 암호화하는 melithiazol 생합성 모듈의 구성은 M. lichenicola Me l46에서와 유사하였다. 하지만 첫 번째 유전자(MYSTI_04973)에 의해 암호화되는 로딩 모듈의 구성은 M. lichenicola Me l46과 달랐는데, 이러한 차이는 M. stipitatus 균주들이 어떻게 M. lichenicola Me l46과는 다른 구조의 melithiazol 유도체들을 생산하는지 설명해준다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• Journal of Microbiology and Biotechnology
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• 제16권5호
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• pp.764-770
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• 2006

Dihydrochalcomycin (GERI-155), produced by Streptomyces sp. KCTC-0041BP isolated from Korean soil, is a 16-membered macrolide antibiotic consisting of two deoxysugar moieties at C-5 and C-20 positions of a branched lactone ring. The cloning and sequencing of a gene cluster for dihydrochalcomycin biosynthesis revealed a 63-kb nucleotide region containing 25 open reading frames (ORFs). The products of all of these 25 ORFs playa role in dihydrochalcomycin biosynthesis and self-resistance against the compounds synthesized. At the core of this cluster lies a 39.6-kb polyketide synthase (PKS) region encoding eight modules in five giant multifunctional protein-coding genes (gerSI-SV). The genes responsible for the biosynthesis of deoxysugar moieties, D-chalcose and D-mycinose, and their modification and attachment were found on either side of this PKS region. The involvement of this gene cluster in dihydrochalcomycin biosynthesis was confirmed by disruption of the dehydratase (DH) domain in module 3 of the PKS gene and by metabolite analysis.

• Genomics & Informatics
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• 제21권3호
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• pp.38.1-38.8
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• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• 한국미생물·생명공학회지
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• 제46권3호
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• pp.300-312
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• 2018

Whole-genome sequencing of the wood-rotting fungus, Flammulina fennae, was carried out to identify carbohydrate-active enzymes (CAZymes). De novo genome assembly (31 kmer) of short reads by next-generation sequencing revealed a total genome length of 32,423,623 base pairs (39% GC). A total of 11,591 gene models in the assembled genome sequence of F. fennae were predicted by ab initio gene prediction using the AUGUSTUS tool. In a genome-wide comparison, 6,715 orthologous groups shared at least one gene with F. fennae and 10,667 (92%) of 11,591 genes for F. fennae proteins had orthologs among the Dikarya. Additionally, F. fennae contained 23 species-specific genes, of which 16 were paralogous. CAZyme identification and annotation revealed 513 CAZymes, including 82 auxiliary activities, 220 glycoside hydrolases, 85 glycosyltransferases, 20 polysaccharide lyases, 57 carbohydrate esterases, and 45 carbohydrate binding-modules in the F. fennae genome. The genome information of F. fennae increases the understanding of this basidiomycete fungus. CAZyme gene information will be useful for detailed studies of lignocellulosic biomass degradation for biotechnological and industrial applications.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권6호
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• pp.347-356
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• 2008

마이크로어레이는 분자 생물학 실험에 있어 중요한 도구로 사용되고 있으며, 마이크로어레이 데이타 분석을 위한 다양한 계산학적 방법이 개발되어 왔다. 그러나, 기존 분석방법은 주어진 조건에 영향을 주는 개별 유전자를 추출하는 데 강한 방면, 유전자 간의 복합작용에 의한 영향을 분석하기 힘들다는 단점을 가지고 있다. 하이퍼망 모델은 생물학적인 네트워크 작용을 모방한 구조이며, 계산과정에서 요소간의 복합작용을 직접 고려하기 때문에 기존 방법에서 다루기 힘들었던 요소간 상호작용 분석이 가능하다는 장점을 가진다. 본 논문에서는 마이크로어레이 데이타를 기반으로 microRNA(miRNA) 프로파일 분석을 위한 하이퍼망 분류 기법을 소개한다. 하이퍼망 분류기는 miRNA 쌍을 기본 요소로 하여 진화 과정을 통해 miRNA 분류 데이타를 학습한다. 학습된 하이퍼망으로부터 유의하다.고 판단되는 miRNA 모듈을 쉽게 추출할 수 있으며, 사용자는 추출된 모듈의 유치미성을 직접 판단할 수 있다. 하이퍼망 분류기는 암 관련 miRNA 발현 데이타 분류 실험을 통해 91.46%의 정확도를 보임으로써 기존 기계학습 방법에 비해 뛰어난 성능을 보여주었으며, 하이퍼망 분석을 통해 생물학적으로 유의한 miRNA 모듈을 찾을 수 있음을 확인하였다.