Earticle

본 연구는 소의 부위별 근육에 특이하게 발현하는 유전자 마커를 발굴하여 소고기의 부위를 과학적으로 판명할 수 있는 기술을 개발하고자 실시하였다. 이러한 연구 목표 아래 먼저 사태(Beef shank), 등심(Longissimus dorsi), 양지(Deep pectoral), 홍두깨 (Semitendinosus) 부위의 근육조직에서 MSC(myogenic satellite cell, 근육줄기세포)를 순수 분리하고 이를 MFC(myotube-formed cell; 근관이 형성된 세포)로 분화시키거나 ALC(adipocyte-like cell; 지방세포와 유사한 세포)로 이형분화 시킨 후 3가지의 세포로부터 각각의 RNA를 추출하였다. 이렇게 추출한 RNA는 24,000개의 bovine oligo-nucelotide(70 mer)가 집적된 microarray를 이용해 4개의 조직 중 1개의 조직에서만 MSC의 분화(MFC) 또는 이형분화 과정에서 mRNA의 발현이 증감을 보이는 유전자 135개를 먼저 발굴하였다. 135개의 유전자에 대해 microarray 분석에 사용한 동일한 RNA를 이용하여 real-time PCR 기술로 검증한 결과 총 29개의 유전자가 microarray 분석 결과와 유사함을 보였다. 29개의 유전자를 다시 4개 부위의 생체 조직에서 추출한 RNA를 이용해 real-time PCR 방법으로 분석한 결과 TS(thymi- dlyate synthase), TE(tropoelastin), RAD52(similar RAD52 motif- containing protein 1), unknown gene), MLC2(myosin light 2, regulatory cardiac, slow), TXNIP(thioredoxin-interating protein) 6개의 유전자만이 다른 부위에 비해 사태 부위에서 현저한 발현의 차이를 나타냈다. 결론적으로 본 연구를 통해 소 부위별 근육을 구분할 수 있는 과학적 기술의 토대를 확립하였다.

Myogenic satellite cells(MSCs) are mononuclear, multipotent progenitors of adult skeletal muscle possessing a capacity of forming adipocyte-like cells(ALC). To identify the skeletal muscle type-specific myogenic and adipogenic genes during MSCs differentiation, total RNA was extracted from bovine MSCs, myotube-formed cell(MFC), and ALC from each of Beef shank, Longissimus dorsi, Deep pectoral, and Semitendinosus. DNA microarray analysis(24,000 oligo chip) comparing MSCs with MFC and ALC, respectively, revealed 135 differentially expressed genes(>4 fold) among four cuts. Real-time PCR confirmed expression of 29 genes. Furthermore, the whole tissue sample RNAs analysis showed 6 differentially expressed genes in Beef shank. Among which, 1 gene in MSCs, 4 in MFC, and 1 in ALCs were highly expressed. This study will provide an insight for better understanding the molecular mechanism of differentiation of skeletal muscle type-specific MSCs. The identified genes may be used as marker to distinguish skeletal muscle types.

Pathogen detection is an important issue due to the threats posed by severe communicable diseases. Here, to achieve multiple detection of 11 selected pathogens, we constructed a 16S rDNA chip. Although 7 target pathogens were specifically detected using PCR labeling method, some target species or subtypes were difficult to discriminate due to nonspecific binding. Therefore, a pattern-mapping statistical model was established using an artificial neural network algorithm. The pattern-mapping tool combined with the DNA chip resulted in successful detection of all target pathogens. In addition, to reduce the intrinsic bias and extended time and effort induced by PCR or labeling reaction, we suggested direct detection method using 16S rRNA as target. The bacterial total RNAs from cell lysate were hybridized to constructed 16S rDNA-based chip and detected using 7 fluorescent-labeled detector probes. The direct detection combined with the DNA chip resulted in more specific detection of all target pathogens than that of PCR labeling method. Collectively, our novel pattern-mapping tool and 16S rRNA direct detection combined with a 16S rDNA-based chip are a simple and effective method for detecting multiple pathogens.

DNA microarray is a multiplex technology used in molecular biology and biomedicine. It consists of an arrayed series of thousands of microscopic spots of DNA oligonucleotides, called features, of which the result should be analyzed by computational methods. Analyzing microarray data using intelligent computing methods has attracted many researchers in recent years. Several approaches have been proposed, in which machine learning based approaches play an important role for biomedical research such as gene expression interpretation, classification and prediction for cancer diagnosis, etc. In this paper, we present an application of the feedforward neural network (SLFN) trained by the singular value decomposition (SVD) approach for DNA microarray classification. The classifier of the single hidden-layer feedforward neural network (SLFN) has the activation function of the hidden units to be ‘tansig’. Experimental results show that the SVD trained feedforward neural network is simple in both training procedure and network structure; it has low computational complexity and can produce better performance with compact network architecture.

Quantitative analysis of DNA microarray is one of important issues in mRNA expression profiling and estimation for infectious doses of pathogens1). Here, we newly introduced an artificial standard probe strategy for quantitative data analysis of pathogen detection oligonucleotide chip as a model system improved from our previous report2). The artificial standard probe was designed to have below 85% similarity with any bacteria in order not to occur non-specific hybridizations with other targets. Based on fluorescence intensities of artificial standard spots, we successfully demonstrated that raw fluorescence intensities of specific probe spots could be corrected to have quantitative correlations with target concentrations. Therefore, our suggested rtificial standard probe strategy may be used for correction of chip-to-chip variation and making possible quantitative analysis of one-color oligonucleotide microarray experiment.

DNA microarray technology enables a significant expansion of the molecular identification and characterization of multiple species in food safety, medical, agricultural and public health. In this study, we focused on development of species identification DNA microarray chips for pathogens. Three food-borne pathogens were selected for a random genomic DNA fragment-based chip, Staphylococcus aureus, Salmonella enterica and Bacillus cereus. At first we followed probe development protocols, the strategy of a random genomic DNA fragment, and constructed the proto-type DNA microarrays which have about 50 probes of each strain. It was validated and optimized for the detection of significant strains. To discriminate significant probes in the proto-type DNA microarray, we have successfully tested seven food-borne pathogens such as, Escherichia coli O157, Enterobacter sakazakii, Listeria monocytogenes, Yersinia enterocolitica, Alicyclobacillus acidocaldarius, Alicyclobacillus acidoterrestris, and Alicyclobacillus cycloheptanicus including E. coli as a non-pathogen. Finally, we have completed the probe contents after removing the probes cross-talked with other non-specific species, and successfully developed a specific DNA microarray which can be used to detect 3 specific target pathogens and discriminate non-specific pathogens.

It has been needed to develop rapid, sensitive, and accurate techniques for detection and diagnosis of pathogenic bacteria, especially in food safety and hygiene. Thus, there have been many attempts to apply the DNA microarray as one of pathogenic bacteria detection methods. To employ DNA microarray for food safety, target DNA must be prepared by extraction from food matrix, amplified by polymerase chain reaction (PCR), and labeled using fluorescent dye. It is not easy to directly extract the DNA from food and takes a long time for target DNA preparation. In the present work, we established the 16S rDNA-based oligonucleotide microarray detection system using RNAs from food bacteria. Also, we constructed the simple pathogenic bacteria RNAs extraction and treatment from various food matrixes. Using this technique, we confirmed the detection of pathogenic bacteria from diverse food matrixes such as grain, meat, milk, egg, and vegetable. Although background signal was raised, it was successful to detect a model pathogenic bacterium. Therefore, we expect that this technique for direct detection of pathogenic bacteria from many food matrixes is functional.

DNA 마이크로어레이는 바이오칩의 발전에서 가장 주목받으며 발전하고 있는 분야로서 이에 대한 연구가 점차 확장하고 있다. DNA나 RNA 등 유전자의 매우 느린 확산속도를 극복하기 위하여 마이크로플루딕 바이오칩이 DNA마이크로어레이에 적용되는 최근의 학술적인 사례들을 연구, 비교 하였다. DNA 마이크로어레이에 적용된 미세유체바이오칩은 상당수가 효율적인 hybridization을 달성하기 위한 믹싱 시스템이 많이 보고되었으며, 이 총설에서는 그에 대한 분석을 수행하여 유전자 hybridization 강화를 이룬 시스템에 대한 최근 동향을 가늠할 수 있게 하였다. 특별히 PDMS를 이용한 마이크로 펌프의 적용 등, 앞으로의 미세유체 DNA 마이크로어레이 발전가능성과 모델링의 한계점 등을 정리 분석해 보았다.

Recently, microfluidic biochips for DNA microarray are providing a number of advantages such as, reduction in reagent volume, high-throughput parallel sample screening, automation of processing, and reduction in hybridization time. Particularly, the enhancement of target:probe hybridization by decrease of hybridization time is an important aspect highlighting the advantage of microfluidic DNA microarray platform. Fundamental issues to overcome extremely slow diffusion-limited hybridization are based on physical, electrical or fluidic dynamical mixing technology. So far, there have been some reports on the enhancement of the hybridization with the microfluidic platforms. In this review, their principle, performance, and outreaching of the technology are overviewed and discussed for the implementation into many bio-applications.

Aiming at the characteristics of high dimension and small samples in microarray data, this paper proposes a selective ensemble method to classify microarray data. Firstly, kruskal-wallis test is used to filter irrelevant genes with classification task and to obtain a set of genes, and then a reduced training set is produced from original training set according to gene subset obtained. Secondly, multiple gene subsets are generated by using neighborhood rough set model with different radius and used to construct training subsets on above reduced training set. Thirdly, every constructed training subset is used to train a classifier by using SVM algorithm, and then multiple classifiers are produced as base classifiers. Finally, a set of base classifiers are selected by using teaching-learning-based optimization and build an ensemble classifier by weighted voting. Five benchmarks tumor microarray datasets are applied to evaluate performance of our proposed method. Experimental results indicate our proposed method is very effective and efficient for classifying microarray data, and it improves not only classification accuracy, but also decrease memory costs and computation times.

독소루비신 생합성 유전자의 발현을 촉진시키는 유전자인 dnrI와 다나루비신으로부터 독소루비신으로의 생전환에 관여하는 유전자인 doxA를 ermE* 프로모터가 포함된 pSE34에 도입하였을 때 각각 5.5배, 2.5배의 독소루비신 생산성 증가가 이루어졌다. 독소루비신 생합성 유전자군의 발현패턴 분석을 위한 DNA microarray system을 구축하였고, 고생산 균주의 독소루비신 생합성 유전자 발현 패턴을 DNA microarray를 통해 확인하였다. 독소루비신 생합성 유전자군의 세포성장에 따른 발현패턴을 분석한 결과, 독소 루비신 생산성 증가에 따라 생합성 유전자의 발현도 증가함을 확인할 수 있었고, pSE34를 통해 도입해준 doxA, dnrI 유전자의 경우 전체 생합성 유전자의 평균보다 높은 수준의 발현량을 보여줌으로써, ermE* 프로모터에 의해 발현이 극대화되었음을 확인할 수 있었다. 독소루비신 내성 유전자의 경우 다른 독소루비신 생합성 유전자들에 비해 발현정도가 크게 증가했고, DnrI에 의해 조절을 받는 다른 유전자들의 발현 수준과 비교하였을 때 TDP-daunosamine을 생합성의 첫 번째 단계에 관여하는 dnmL 유전자는 그 발현양의 증가가 크지 않았다. 따라서 DNA microarray 시스템 분석 결과, 독소루비신 생산성 극대화를 위해서는 dnrI, doxA, drrA, drrB, drrC, dnmL 등의 유전자들의 안정적 발현이 매우 중요하고도 핵심적인 인자임이 확인되었다.

Doxorubicin is an anthracycline-family polyketide compound with a very potent anti-cancer activity, typically produced by Streptomyces peucetius. To understand the potential target biosynthetic genes critical for the doxorubicin overproduction, a doxorubicin-specific DNA microarray chip was fabricated and applied to reveal the growth-phase-dependent expression profiles of biosynthetic genes from two doxorubicin-overproducing strains along with the wild-type strain. Two doxorubicinoverproducing S. peucetius strains were generated via over-expression of a dnrI (a doxorubicin-specific positive regulatory gene) and a doxA (a gene involved in the conversion from daunorubicin to doxorubicin) using a streptomycetes high expression vector containing a strong ermE* promoter. Each doxorubicin-overproducing strain was quantitatively compared with the wild-type doxorubicin producer based on the growth-phase-dependent doxorubicin productivity as well as doxorubicin biosynthetic gene expression profiles. The doxorubicin-specific DNA microarray chip data revealed the early-and-steady expressions of the doxorubicin-specific regulatory gene (dnrI), the doxorubicin resistance genes (drrA, drrB, drrC), and the doxorubicin deoxysugar biosynthetic gene (dnmL) are critical for the doxorubicin overproduction in S. peucetius. These results provide that the relationship between the growth-phase-dependent doxorubicin productivity and the doxorubicin biosynthetic gene expression profiles should lead us a rational design of molecular genetic strain improvement strategy.

Actinorhodin (ACT) and Doxorubicin (DOX) belong to a structural family of type II polyketide compounds generated by a high G+C Gram-positive soil bacterium, Streptomyces species. Here we report the identification of a couple of previously-unknown down-regulator genes via comparative transcriptome profiles using S. coelicolor cDNA microarrays. Using interspecies DNA microarray analysis, we found several putative transcriptional down-regulator genes involved in antibiotic biosynthesis. To show the biological significance of the transcriptomics-driven potential down-regulator genes in Streptomyces species, these genes were functionally expressed both in ACT-producing S. coelicolor and DOX-producing S. peucetius. Further analysis revealed that the expression of these putative transcriptional down-regulators inhibited both actinorhodin and undecylprodigiosin production in S. coelicolor. Overexpression of these genes also inhibited the biosynthesis of DOX in S. peucetius. Real-time RT-PCR confirmed that the differences of antibiotic productivity in S. coelicolor were due to the differential expression levels of antibiotic pathway-specific regulatory genes including actII-orf4 and redD/Z. Therefore, we concluded that the interspecies DNA microarray analysis reported here successfully identified a couple of novel global down-regulators of antibiotic biosynthesis in Streptomyces species.

We describe here a novel method for the surface immobilization of DNA oligonucleotides using a gold nanoparticle as a mediator. The outer surface of gold nanoparticle is electrostatically attached to amine-modified DNA and, subsequently the gold-DNA complex is easily immobilized on the amine or aldehyde activated glasses through covalent bond or electrostatic force. Based on optimization of gold-DNA concentration and linker effect experiments, sensitivity and specificity of the gold-DNA complex system were tested through hybridization reaction with two kinds of capture probes consisting of different sequences. As a result of the gold-DNA complex system, the surfaces reveal high immobilization efficiency and hybridization intensity for amine-modified DNAs compared with conventional immobilization method. Furthermore, as we use gold nanoparticle as a mediator, it is possible to do silver enhancement enabling us to monitor the capture probe status just after immobilization washing step.

In order to obtain reliable results from DNA microarray system, one of the key issues is the strategy for efficient immobilization of capture probe DNAs. The conventional immobilization methods, however, have not been regarded as good enough in several points such as capture probe capacity, spot homogeneity, and data consistency with repeated experiments. Therefore, we developed a novel strategy for DNA immobilization on slide glass utilizing gold nanoparticle as an immobilization mediator. Prior to spotting, the capture probe DNA molecules were mixed with relavent gold nanoparticles followed by the conventional immobilization processes on aldehyde- or amine-activated slide glass. Through the investigation of the DNA chips prepared by the strategy, we found out that it offers following key major advantages. First, the gold nanoparticles provide the capture probe DNAs with three dimensional surfaces leading to the increased surface area for DNA immobilization, which results in higher probe capacity and consequently higher signal intensity after final hybridization step. Second, since the gold nanoparticle-DNA complex was more uniformly dispersed on the slide glass, more highly uniformed spots could be obtained. Finally, with this strategy, we were able to check the spot quality immediately after the spotting by just performing silver enhancement on the spotted gold nanoparticles, which can be detected by the naked eye. Since this strategy is very simple and effective for DNA immobilization, it has enormous potentials in the area of DNA microarray.

Droplet-based microfluidic systems have emerged as a powerful platform for performing high-throughput biological experimentation. Fluorescence polarization(FP) measurements have been used to probe many biological reactions such as receptor-ligand binding, DNA hybridization, DNA-protein binding, peptide-protein binding, immunoassays and enzymatic degradation. FP detection is particularly advantageous since it is truly homogeneous assay format, allows for real-time (kinetic) measurements and is insensitive to concentration variations. For these reasons, we report herein the use of FP detection in a droplet-based microfluidic system.

We herein introduce the development of a novel multiplexed single-nucleotide polymorphisms (SNPs) genotyping method based on amplification of separated ligation-dependent probe (ASLP) and RecA assisted hybridization (RAH) technology. In the ASLP technique, allele-specific ligation reaction was first performed between annealed allele-specific oligonucleotide (ASO) probe and locus-specific oligonucleotide (LSO) probe containing the unique regions of homology to target genomic DNA. The ASO probe covering up to SNP site is modified with universal forward primer site at the 5’ end while the LSO probe is extended with universal separation (US) site and poly A tail at the 3’ end. The two probes would be ligated when they are hybridized to a correctly matching sequence at a specific SNP locus. The separation probe that consists of universal reverse primer site labeled with biotin at its 5’ end and complimentary sequence of US site at its 3’ end was then applied to the resulting ligated product. During the following extension reaction of the separation probe, the ligated probes were dissociated from target genomic DNA as a form of double-stranded DNA (dsDNA) with the strand extended from the separation probe. By using streptavidin-coated magnetic beads, the dsDNA containing ligated probes could be simply separated from the reaction mixture including genomic DNA and unligated probes. PCR amplification of the purified ligation products was then carried out using a primer pair of Cy3-labeled universal forward primer and universal reverse primer, followed by RAH of the PCR products on DNA microarrays. Using this strategy we successfully genotyped fifteen SNPs markers for the cultivar identification of pepper in a single tube reaction within 3 hours.

For oligonucleotide microarray, target gene is generally amplified by polymerase chain reaction (PCR) and purified. In the present work, we suggest fast and non-labeling direct 16S rRNA detection of pathogenic bacteria without amplification and purification of target gene. Because 16S rRNA has many copies in all living bacteria, we successfully used 16S rRNA as a target for microarray. For simple and fast direct detection of pathogens, we used our previously constructed 16S rDNA-based oligonucleotide microarray detection system. The bacterial total RNAs from cell lysis were hybridized to a specific 16S rRNA probes and detected using fluorescent-labeled detector probe without labeling reactions of target RNAs. We found that hybridization specificity and sensitivity were enhanced using the fragmented RNAs. We also investigated the limit of detection (LOD) using Vibrio vulnificus.

Genomics-guided technologies including cDNA microarrays have been successfully applied for the identification of gene expression alterations in various Streptomyces strains. To detect global changes in mRNA abundance associated with overproduction of anti-cancer doxorubicin, reverse engineering strategy via comparative transcriptome analyses in cultures of the wild-type and industrial mutant strains of S. peucetius were conducted using interspecies S. coelicolor cDNA microarrays. Among 160 S. coelicolor potential candidate genes showing at least a two-fold change in transcription profile, a SCO3579 (whiB-like gene named wblA) inhibited the biosynthesis of doxorubicin in S. peucetius as well as the production of antibiotics in S. coelicolor, suggesting that wblA and its homologs act globally among streptomycetes as down-regulators of antibiotic biosynthesis. In addition, one of tetR-family transcriptional regulatory genes was also identified to encode a global antibiotic regulator. Gene disruption of S. coelicolor revealed that this tetR-family regulatory gene down-regulates antibiotic biosynthesis through pathway-specific regulators even in the presence of the wblA transcript, implying that it might encode a wblA-bypassing antibiotic down-regulator. To isolate and manipulate a wblA homolog in a doxorubicin-overproducing S. peucetius industrial stain, a total genomic DNA library from a S. peucetius industrial mutant was constructed and screened using a S. coelicolor wblA as a probe, resulting in isolation of a wblA ortholog (wblA-spe) showing 95% amino acid identity to a S. coelicolor wblA. Gene disruption of wblA-spe from the S. peucetius industrial mutant resulted in additional increase of doxorubicin production, implying that doxorubicin productivity in the S. peucetius industrial mutant strain could be further improved via rational comparative transcriptomics-guided target gene manipulation.

Doxorubicin(DXR) and daunorubicin(DNR) are anthracycline antibiotics produced by Streptomyces peucetius and widely used as cancer chemotherapeutic agents. Although DXR/DNR regulators have been mainly studied, other factors, such as regulations in central metabolic pathway and carbohydrate metabolism, are known to be important for improving their productivity. To study the correlations between those pathways and DXR/DNR productivity, we selected 268 genes involved in glycolysis, fermentation, citric acid cycle, butanoate metabolism, and etc, and searched for their sequences from the S. peucetius genome by comparing gene sequences of S. coelicolor. Those genes were amplified by PCR and arrayed on the glass slides. We monitored gene expression changes of those genes in two different conditions, R2YE and NDYE media. The analyzed data suggested that the expression levels of genes in alanine and glutamate pathways might be important in DXR/DNR productivity.