• Genomics & Informatics
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• v.5 no.1
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• pp.10-18
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• 2007

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

• Bulletin of the Korean Chemical Society
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• v.30 no.12
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• pp.2993-2998
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• 2009

An enzyme-linked immunosorbent assay (ELISA)-on-a-chip (EOC) biosensor combined with cell concentration technology based on immuno-magnetic separation (IMS) was investigated for use as a potential tool for early screening of Listeria monocytogenes (L. monocytogenes) in food products. The target analyte is a well-known pathogenic foodborne microorganism and outbreaks of the food poisoning typically occur due to contamination of normal food products. Thus, the aim of this study was to develop a rapid and reliable sensor that could be utilized on a daily basis to test food products for the presence of this pathogenic microorganism. The sensor was optimized to provide a high detection capability (e.g., 5.9 ${\times}\;10^3$ cells/mL) and, to eventually minimize cultivation time. The cell density was condensed using IMS prior to analysis. Since the concentration rate of IMS was greater than 100-fold, this combination resulted in a detection limit of 54 cells/mL. The EOC-IMS coupled analytical system was then applied to a real sample test of fish intestines. The system was able to detect L. monocytogenes at a concentration of 2.4 CFU/g after pre-enrichment for 6 h from the onset of cell cultivation. This may allow us to monitor the target analyte at a concentration less than 1 CFU/g within a 9 h-cultivation provided a doubling time of 40 min is typically maintained. Based on this estimation, the EOC-IMS system can screen and detect the presence of this microorganism in food products almost within working hours.

• Animal Bioscience
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• v.36 no.9
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• pp.1336-1349
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• 2023

Objective: The study was conducted to screen differentially expressed miRNAs in sows at early pregnancy by high-throughput sequencing and explore its mechanism of action on embryo implantation. Methods: The blood serum of pregnant and non-pregnant Landrace×Yorkshire sows were collected 14 days after artificial insemination, and exosomal miRNAs were purified for high throughput miRNA sequencing. The expression patterns of 10 differentially expressed (DE) miRNAs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The qRT-PCR quantified the abundance of serum exosomal miR-192 in pregnant and control sows, and the diagnostic power was assessed by receiver operating characteristic (ROC) analysis. The target genes of DE miRNAs were predicted with bioinformatics software, and the functional and pathway enrichment analysis was performed on gene ontology and the Kyoto encyclopedia of genes and genomes terms. Furthermore, a luciferase reporter system was used to identify the target relation between miR-192 and integrin alpha 4 (ITGA4), a gene influencing embryo implantation in pigs. Finally, the expression levels of miRNAs and the target gene ITGA4 were analyzed by qRT-PCR, and western blot, with the proliferation of BeWo cells detected by cell counting kit-8 (CCK-8). Results: A total of 221 known miRNAs were detected in the libraries of the pregnant and non-pregnant sows, of which 55 were up-regulated and 67 were down-regulated in the pregnant individuals compared with the non-pregnant controls. From these, the expression patterns of 10 DE miRNAs were validated. The qRT-PCR analysis further confirmed a significantly higher expression of miR-192 in the serum exosomes extracted from pregnant sows, when compared to controls. The ROC analysis revealed that miR-192 provided excellent diagnostic accuracy for pregnancy (area under the ROC curve [AUC]=0.843; p>0.001). The dual-luciferase reporter assay indicated that miR-192 directly targeted ITGA4. The protein expression of ITGA4 was reduced in cells that overexpressed miR-192. Overexpression of miR-192 resulted in the decreased proliferation of BeWo cells and regulated the expression of cell cycle-related genes. Conclusion: Serum exosomal miR-192 could serve as a potential biomarker for early pregnancy in pigs. miR-192 targeted ITGA4 gene directly, and miR-192 can regulate cellular proliferation.

• Toxicological Research
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• v.32 no.4
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• Genomics & Informatics
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• v.21 no.2
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• pp.22.1-22.15
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• 2023

Kidney renal clear cell carcinoma (KIRC) is one of the most aggressive cancer type of the urinary system. Metastatic KIRC patients have poor prognosis and limited therapeutic options. Ankyrin 3 (ANK3) is a scaffold protein that plays important roles in maintaining physiological function of the kidney and its alteration is implicated in many cancers. In this study, we investigated differential expression of ANK3 in KIRC using GEPIA2, UALCAN, and HPA databases. Survival analysis was performed by GEPIA2, Kaplan-Meier plotter, and OS-kirc databases. Genetic alterations of ANK3 in KIRC were assessed using cBioPortal database. Interaction network and functional enrichment analyses of ANK3-correlated genes in KIRC were performed using GeneMANIA and Shiny GO, respectively. Finally, the TIMER2.0 database was used to assess correlation between ANK3 expression and immune infiltration in KIRC. We found that ANK3 expression was significantly decreased in KIRC compared to normal tissues. The KIRC patients with low ANK3 expression had poorer survival outcomes than those with high ANK3 expression. ANK3 mutations were found in 2.4% of KIRC patients and were frequently co-mutated with several genes with a prognostic significance. ANK3-correlated genes were significantly enriched in various biological processes, mainly involved in peroxisome proliferator-activated receptor (PPAR) signaling pathway, in which positive correlations of ANK3 with PPARA and PPARG expressions were confirmed. Expression of ANK3 in KIRC was significantly correlated with infiltration level of B cell, CD8+ T cell, macrophage, and neutrophil. These findings suggested that ANK3 could serve as a prognostic biomarker and promising therapeutic target for KIRC.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.290-295
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• 2019

Salmonella spp. are frequently associated with food and are among the most important foodborne pathogens. The recent Salmonella out breaks in Korea was associated with chocolate mousse cakes served with school meals during September 2018. The objective of this research was to compare the 3M Molecular Detection Assay 2 - Salmonella and the Korean Standard Method of Salmonella in artificially inoculated mousse (chocolate and cheese) and tiramisu cakes. Mousse (chocolate and cheese) and tiramisu cakes were artificially inoculated with S. Typhimurium. Twenty five gram of sample was enriched with 225 mL buffered peptone water for incubation at $37^{\circ}C$ for 24 h. After enrichment, the cultures were analyzed by using the 3M Molecular Detection Assay 2 - Salmonella and the Korean Standard Method. Most of the inoculated samples showed similar results except the chocolate mousse cakes, in which real-time PCR was unable to detect S. Typhimurium even after $10^4CFU/25g$ of inoculation. However, S. Typhimurium inoculated at a concentration of $10^0CFU/25g$ was detected by using 3M Molecular Detection Assay 2 - Salmonella. In chocolate mousse, detection of S. Typhimurium using real-time PCR was partially successful when dark chocolate was added at less than 15%. Negative results in real-time PCR and 3M Molecular Detection Assay 2 - Salmonella were confirmed by gel electrophoresis. The data indicated that dark chocolate could inhibit amplification of the target gene in the PCR reactions. In conclusion, the 3M Molecular Detection Assay 2 - Salmonella was better than the Korean Standard Method (real-time PCR) for the detection of S. Typhimurium in chocolate mousse cakes and chocolate mousse.