• Genomics & Informatics
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• v.19 no.2
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• pp.16.1-16.14
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• 2021

Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1497-1505
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• 2022

Recently, the concept of personalized nutrition has been developed, which states that food components do not always lead to the same metabolic responses, but vary from person to person. Although this concept has been studied based on individual genetic backgrounds, researchers have recently explored its potential role in the gut microbiome. The gut microbiota physiologically communicates with humans by forming a bidirectional relationship with the micronutrients, macronutrients, and phytochemicals consumed by the host. Furthermore, the gut microbiota can vary from person to person and can be easily shifted by diet. Therefore, several recent studies have reported the application of personalized nutrition to intestinal microflora. This review provides an overview of the interaction of diet with the gut microbiome and the latest evidence in understanding the inter-individual differences in dietary responsiveness according to individual baseline gut microbiota and microbiome-associated dietary intervention in diseases. The diversity of the gut microbiota and the presence of specific microorganisms can be attributed to physiological differences following dietary intervention. The difference in individual responsiveness based on the gut microbiota has the potential to become an important research approach for personalized nutrition and health management, although further well-designed large-scale studies are warranted.

• The Korean Journal of Food & Health Convergence
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• v.9 no.2
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• pp.1-6
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• 2023

As oil palm trees are an important economic source in many countries, particularly in Southeast Asia and Africa, the study of Ganoderma boninense is crucial for the sustainability of the oil palm industry. This study aims to understand the biology and ecology of the fungus, its pathogenesis, and the impact it has on oil palm trees. This knowledge can be used to develop management strategies to mitigate the damage caused by the fungus, such as the use of resistant varieties, chemical and biological control methods, and cultural practices. This study is to ensure the long-term productivity and sustainability of the oil palm industry. The main method of recent academic studies on this pathogen is molecular biology, with a focus on genetic analysis and functional genomics. Researchers have used techniques such as PCR, DNA sequencing, and transcriptomics to identify genes and pathways involved in pathogenesis and better understand the fungus's interactions with its host plant. Other methods used in recent studies include biochemical analysis, microscopy, and phytohormonal assays to investigate the biochemistry and physiology of the interaction between G. boninense and oil palm. This study is intended to provide implications from a new perspective by organizing and integrating studies on Ganoderma boninense.

• Journal of the Korean Society of International Agriculture
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• v.23 no.5
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• pp.503-506
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• 2011

In order to analyze the resistant gene to Xanthomonas oryzae pv. oryzae in Korean native rices. Six Korean native rice varieties were crossed with IR-BB 101 contains Xa1 resistant gene and inoculated Japanese isolates IA(T7174). Cheonggunbyeo has Xa1 resistant gene only, and Yukseongjaerae, Agukdo, Heukpi and Icheon7ilchal have Xa1 and another one dominant gene. Ginggaragshare has Xa1 and another two dominant genes and two of those genes concerned complementary interaction against Japanese isolates IA(T7174).

• Journal of Microbiology and Biotechnology
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• v.34 no.4
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• pp.795-803
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• 2024

Microorganisms usually coexist as a multifaceted polymicrobial community in the natural habitats and at mucosal sites of the human body. Two opportunistic human pathogens, Pseudomonas aeruginosa and Staphylococcus aureus commonly coexist in the bacterial infections for hospitalized and/or immunocompromised patients. Here, we observed that autolysis of the P. aeruginosa quorum-sensing (QS) mutant (lasRmvfR) was suppressed by the presence of the S. aureus cells in vitro. The QS mutant still displayed killing against S. aureus cells, suggesting the link between the S. aureus-killing activity and the autolysis suppression. Independent screens of the P. aeruginosa transposon mutants defective in the S. aureus-killing and the S. aureus transposon mutants devoid of the autolysis suppression revealed the genetic link between both phenotypes, suggesting that the iron-dependent metabolism involving S. aureus exoproteins might be central to both phenotypes. The autolysis was suppressed by iron treatment as well. These results suggest that the interaction between P. aeruginosa and S. aureus might be governed by mechanisms that necessitate the QS circuitry as well as the metabolism involving the extracellular iron resources during the polymicrobial infections in the human airway.

• International Journal of Stem Cells
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• v.17 no.1
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• pp.91-98
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• 2024

The development of in vitro models is essential in modern science due to the need for experiments using human material and the reduction in the number of laboratory animals. The complexity of the interactions that occur in living organisms requires improvements in the monolayer cultures. In the work presented here, neuroepithelial stem (NES) cells were differentiated into peripheral-like neurons (PLN) and the phenotype of the cells was confirmed at the genetic and protein levels. Then RNA-seq method was used to investigate how stimulation with pro-inflammatory factors such as LPS and IFN𝛾 affects the expression of genes involved in the immune response in human fibroblast-like synoviocytes (HFLS). HFLS were then cultured on semi-permeable membrane inserts, and after 24 hours of pro-inflammatory stimulation, the levels of cytokines secretion into the medium were checked. Inserts with stimulated HFLS were introduced into the PLN culture, and by measuring secreted ATP, an increase in cell activity was found in the system. The method used mimics the condition that occurs in the joint during inflammation, as observed in the development of diseases such as rheumatoid arthritis (RA) or osteoarthritis (OA). In addition, the system used can be easily modified to simulate the interaction of peripheral neurons with other cell types.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6673-6680
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• 2013

Objective: Insulin resistance (IR) is an established risk factor for colorectal cancer (CRC). Given that CRC and IR physiologically overlap and the calpain-10 gene (CAPN10) is a candidate for IR, we explored the association between CAPN10 and CRC risk. Methods: Blood samples of 400 case-control pairs were genotyped, and the lifestyle and dietary habits of these pairs were recorded and collected. Unconditional logistic regression (LR) was used to assess the effects of CAPN10 SNP43 and SNP19, and environmental factors. Both generalized multifactor dimensionality reduction (GMDR) and the classification and regression tree (CART) were used to test gene-environment interactions for CRC risk. Results: The GA+AA genotype of SNP43 and the Del/Ins+Ins/Ins genotype of SNP19 were marginally related to CRC risk (GA+AA: OR = 1.35, 95% CI = 0.92-1.99; Del/Ins+Ins/Ins: OR = 1.31, 95% CI = 0.84-2.04). Notably, a high-order interaction was consistently identified by GMDR and CART analyses. In GMDR, the four-factor interaction model of SNP43, SNP19, red meat consumption, and smoked meat consumption was the best model, with a maximum cross-validation consistency of 10/10 and testing balance accuracy of 0.61 (P < 0.01). In LR, subjects with high red and smoked meat consumption and two risk genotypes had a 6.17-fold CRC risk (95% CI = 2.44-15.6) relative to that of subjects with low red and smoked meat consumption and null risk genotypes. In CART, individuals with high smoked and red meat consumption, SNP19 Del/Ins+Ins/Ins, and SNP43 GA+AA had higher CRC risk (OR = 4.56, 95%CI = 1.94-10.75) than those with low smoked and red meat consumption. Conclusions: Though the single loci of CAPN10 SNP43 and SNP19 are not enough to significantly increase the CRC susceptibility, the combination of SNP43, SNP19, red meat consumption, and smoked meat consumption is associated with elevated risk.

• Journal of Forest and Environmental Science
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• v.24 no.1
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• pp.41-46
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• 2008

Progeny tests of Abies holophylla were established with 32 open-pollinated families at Hwaseong and Gangneung in 1994. Growth characteristics (height, DBH and volume index) were measured at the age of 15, showing that Gangneung site showed in general better performance than Hwaseong site. Analysis of variance (ANOVA) of the growth characteristics showed that there was a significant difference among families in Gangneung but not in Hwaseong, and Hwaseong site showed that DBH and volume index were statistically different among replications. At Gangneung site, family ${\times}$ replication interaction was significant in DBH and volume index. Based on the combined analysis of both sites, all characteristics except height showed highly significant differences between sites and among families. On the other hand, family ${\times}$ replication interaction was not significant, implying that growth pattern of families could be similar at Gangneung and Hwaseong. Individual heritabilities ($hi^2$) at Gangneung were 0.485 in height, 0.611 in DBH and 0.538 in volume index, and the values of $hi^2$ at Hwaseong were 0.121 in height, 0.054 in DBH and 0.080 in volume index, respectively. Based on both sites, $hi^2$ was estimated as 0.204 in height, 0.326 in DBH and 0.238 in volume index. Individual heritabilities (0.054~0.611) were lower than family heritabilities (0.089~0.723) for all growth characteristics. Realized gain was estimated to be 2.5% in height, 9.2% in DBH and 23.6% in volume. When inferior families (about 50% of all families) are genetically thinned from a seed orchard, genetic gain would be 9.55% in height, 17.0% in DBH and 46.8% in volume.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.333-345
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• 2017

The potato tuber is known as a rich source of essential nutrients, used throughout the world. Although potato-breeding programs share some priorities, the major objective is to increase the genetic potential for yield through breeding or to eliminate hazards that reduce yield. Glycoalkaloids, which are considered a serious hazard to human health, accumulate naturally in potatoes during growth, harvesting, transportation, and storage. Here, we used the AMMI (additive main effects and multiplicative interaction) and GGE (Genotype main effect and genotype by environment interaction) biplot model, to evaluate tuber yield stability and glycoalkaloid content in six potato cultivars across three locations during 2012/2013. The environment on tuber yield had the greatest effect and accounted for 33.0% of the total sum squares; genotypes accounted for 3.8% and $G{\times}E$ interaction accounted for 11.1% which is the nest highest contribution. Conversely, the genotype on glycoalkaloid had the greatest effect and accounted for 82.4% of the total sum squares), whereas environment and $G{\times}E$ effects on this trait accounted for only 0.4% and 3.7%, respectively. Furthermore, potato genotype 'Superior', which covers most of the cultivated area, exhibited high yield performance with stability. 'Goun', which showed lower glycoalkaloid content, was the most suitable and desirable genotype. Results showed that, while tuber yield was more affected by the environment, glycoalkaloid content was more dependent on genotype. Further, the use of the AMMI and GGE biplot model generated more interactive visuals, facilitated the identification of superior genotypes, and suggested decisions on a variety of recommendations for specific environments.