• BMB Reports
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• v.54 no.10
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• pp.497-504
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• 2021

EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2- BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC.

• Animal Bioscience
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• v.34 no.9
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• pp.1439-1450
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• 2021

Objective: With the rapid development of proteomics sequencing and RNA sequencing technology, multi-omics analysis has become a current research hotspot. Our previous study indicated that Xinjiang brown cattle have better meat quality than Kazakh cattle. In this study, Xinjiang brown cattle and Kazakh cattle were used as the research objects. Methods: Proteome sequencing and RNA sequencing technology were used to analyze the proteome and transcriptome of the longissimus dorsi muscle of the two breeds of adult steers (n = 3). Results: In this project, 22,677 transcripts and 1,874 proteins were identified through quantitative analysis of the transcriptome and proteome. By comparing the identified transcriptome and proteome, we found that 1,737 genes were identified at both the transcriptome and proteome levels. The results of the study revealed 12 differentially expressed genes and proteins: troponin I1, crystallin alpha B, cysteine, and glycine rich protein 3, phosphotriesterase-related, myosin-binding protein H, glutathione s-transferase mu 3, myosin light chain 3, nidogen 2, dihydropyrimidinase like 2, glutamate-oxaloacetic transaminase 1, receptor accessory protein 5, and aspartoacylase. We performed functional enrichment of these differentially expressed genes and proteins. The Kyoto encyclopedia of genes and genomes results showed that these differentially expressed genes and proteins are enriched in the fatty acid degradation and histidine metabolism signaling pathways. We performed parallel reaction monitoring (PRM) verification of the differentially expressed proteins, and the PRM results were consistent with the sequencing results. Conclusion: Our study provided and identified the differentially expressed genes and proteins. In addition, identifying functional genes and proteins with important breeding value will provide genetic resources and technical support for the breeding and industrialization of new genetically modified beef cattle breeds.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.547-554
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• 2021

Cancer patients can have different kinds of cancer driver genes, and identification of these patient-specific cancer driver genes is an important step in the development of personalized cancer treatment and drug development. Several bioinformatic methods have been proposed for this purpose, but there is room for improvement in terms of accuracy. In this paper, we propose NPD (Network based Patient-specific Driver gene identification) for identifying patient-specific cancer driver genes. NPD consists of three steps, constructing a patient-specific gene network, applying the modified PageRank algorithm to assign scores to genes, and identifying cancer driver genes through a score comparison method. We applied NPD on six cancer types of TCGA data, and found that NPD showed generally higher F1 score compared to existing patient-specific cancer driver gene identification methods.

• Biomedical Science Letters
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• v.29 no.1
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• pp.11-25
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• 2023

In hepatocellular carcinoma (HCC), chromosome 4 open-reading frame 47 (C4orf47) has not been so far investigated for its prognostic value or association with infiltrating immune cells. We performed bioinformatics analysis on HCC data and analyzed the data using online databases such as TIMER, UALCAN, Kaplan-Meier plotter, LinkedOmics, and GEPIA2. We found that C4orf47 expression in HCC was higher compared to normal tissues. High C4orf47 expression was associated with a worse prognosis in HCC. The correlation between C4orf47 and infiltrating immune cells is positively associated with CD4+T cells, B cells, neutrophils, macrophages, and dendritic cells in HCC. Moreover, high C4orf47 expression was correlated with a poor prognosis of infiltrating immune cells. Analysis of C4orf47 gene co-expression networks revealed that 12501 genes were positively correlated with C4orf47, whereas 7200 genes were negatively correlated. The positively related genes of C4orf47 are associated with a high hazard ratio in different types of cancer, including HCC. Regarding the biological functions of C4orf47 gene, it mainly regulates RNA metabolic process, DNA replication, and cell cycle. The C4orf47 gene may play a prognostic role by regulating the global transcriptome process in HCC. Our findings demonstrate that high C4orf47 expression correlates with poor prognosis and tumor-infiltrating immune cells in HCC. We suggest that C4orf47 is a novel prognostic biomarker and potential immune therapeutic target for HCC.

• Biomedical Science Letters
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• v.28 no.4
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• pp.260-275
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• 2022

Sterile alpha motif (SAM) domains bind to various proteins, lipids, and RNAs. However, these domains have not yet been analyzed as prognostic biomarkers. In this study, SAM domain containing 13 (SAMD13), a member of the SAM domain, was evaluated to identify a novel prognostic biomarker in various human cancers, including hepatocellular carcinoma (HCC). Moreover, we identified a correlation between SAMD13 expression and immune cell infiltration in HCC. We performed bioinformatics analysis using online databases, such as Tumor Immune Estimation Resource, UALCAN, Kaplan-Meier plotter, LinkedOmics, and Gene Expression Profiling Interactive Analysis2. SAMD13 expression in HCC samples was significantly higher than that in normal liver tissue; additionally, SAMD13 was higher in primary tumors, various stages of cancer and grades of tumor, and status of nodal metastasis. Higher SAMD13 expression was also associated with poorer prognosis. SAMD13 expression positively correlated with CD8+ T cells, CD4+ T cells, B cells, neutrophils, macrophages, and dendritic cells. In the analysis of SAMD13 co-expression networks, positively related genes of SAMD13 were associated with a high hazard ratio in different types of cancer, including HCC. In biological function of SAMD13, SAMD13 mainly include spliceosome, ribosome biogenesis in eukaryote, ribosome, etc. These results suggest that SAMD13 may serve as a novel prognostic biomarker for HCC diagnosis and provide novel insights into tumor immunology in HCC.

• Microbiology and Biotechnology Letters
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• v.52 no.2
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• pp.141-151
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• 2024

Isochrysis sp. is a sea microalga that has become a species of interest because of the extreme lipid content and rapid growth rate of this organism indicating its potential for efficient biofuel production. Using genome sequencing/genome-scale modeling for the prediction of Isochrysis sp. metabolic utilities there is high scope for the identification of essential pathways for the extraction of byproducts of interest at a higher rate. In our work, we design and present iIsochr964, a genome-scale metabolic model of Isochrysis sp. including 4315 reactions, 934 genes, and 1879 metabolites, which are distributed among fourteen compartments. For model validation, experimental culture, and isolation of Isochrysis sp. were performed and biomass values were used for validation of the genome-scale model. OptFlux was instrumental in uncovering several novel metabolites that influence the organism's metabolism by increasing the flux of interacting metabolites, such as Malonyl-CoA, EPA, Protein and others. iIsochr964 provides a compelling resource of metabolic understanding to revolutionize its industrial applications, thereby fostering sustainable development and allowing estimations and simulations of the organism metabolism under varying physiological, chemical, and genetic conditions. It is also useful in principle to provide a systemic view of Isochrysis sp. metabolism, efficiently guiding research and granting context to omics data.

• The Korean Journal of Physiology and Pharmacology
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• v.21 no.5
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• pp.531-546
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• 2017

Activation of Toll-like receptor-4 (TLR-4) in articular chondrocytes increases the catabolic compartment and leads to matrix degradation during the development of osteoarthritis. In this study, we determined the proteomic and genomic alterations in human chondrocytes during lipopolysaccharide (LPS)-induced inflammation to elucidate the underlying mechanisms and consequences of TLR-4 activation. Human chondrocytes were cultured with LPS for 12, 24, and 36 h to induce TLR-4 activation. The TLR-4-induced inflammatory response was confirmed by real-time PCR analysis of increased interleukin-1 beta ($IL-1{\beta}$), interleukin-6 (IL-6), and tumor necrosis factor alpha ($TNF-{\alpha}$) expression levels. In TLR-4-activated chondrocytes, proteomic changes were determined by two-dimensional electrophoresis and matrix-assisted laser desorption/ionization-mass spectroscopy analysis, and genomic changes were determined by microarray and gene ontology analyses. Proteomics analysis identified 26 proteins with significantly altered expression levels; these proteins were related to the cytoskeleton and oxidative stress responses. Gene ontology analysis indicated that LPS treatment altered specific functional pathways including 'chemotaxis', 'hematopoietic organ development', 'positive regulation of cell proliferation', and 'regulation of cytokine biosynthetic process'. Nine of the 26 identified proteins displayed the same increased expression patterns in both proteomics and genomics analyses. Western blot analysis confirmed the LPS-induced increases in expression levels of lamin A/C and annexins 4/5/6. In conclusion, this study identified the time-dependent genomic, proteomic, and functional pathway alterations that occur in chondrocytes during LPS-induced TLR-4 activation. These results provide valuable new insights into the underlying mechanisms that control the development and progression of osteoarthritis.

• Journal of Plant Biotechnology
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• v.37 no.1
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• pp.12-24
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• 2010

Plant metabolomics is a research field for identifying all of the metabolites found in a certain plant cell, tissue, organ, or whole plant in a given time and conditions and for studying changes in metabolic profiling as time goes or conditions change. Metabolomics is one of the most recently developed omics for holistic approach to biology and is a kind of systems biology. Metabolomics or metabolite fingerprinting techniques usually involves collecting spectra of crude solvent extracts without purification and separation of pure compounds or not in standardized conditions. Therefore, that requires a high degree of reproducibility, which can be achieved by using a standardized method for sample preparation and data acquisition and analysis. In plant biology, metabolomics is applied for various research fields including rapid discrimination between plant species, cultivar and GM plants, metabolic evaluation of commercial food stocks and medicinal herbs, understanding various physiological, stress responses, and determination of gene functions. Recently, plant metabolomics is applied for characterization of gene function often in combination with transcriptomics by analyzing tagged mutants of the model plants of Arabidopsis and rice. The use of plant metabolomics combined by transcriptomics in functional genomics will be the challenge for the coming year. This review paper attempted to introduce current status and prospects of plant metabolomics research.

• 한국균학회소식:학술대회논문집
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• 2015.11a
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• pp.11-11
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• 2015

A total of sixty-six samples of Nuruk, a fermention starter used to make the Korean traditional rice wine, Makgeolli, were collected from central and southern regions of Korea in 2013 and 2014. We classified two groups of the Nuruk samples, "commercial" and "home-made", according to the manufacturing procedure and purpose of use. Commercial Nuruks were made in a controlled environment where the temperature and humidity are fixed and the final product is supplied to Makgeolli manufacturers. Home-made Nuruks were made under uncontrolled conditions in the naturally opened environment and were intended for use in the production of small amounts of home-brewed Makgeolli. We obtained more than five hundred isolates including filamentous fungi and yeasts from the Nuruk samples followed by identification of fungal species. Also we stored glycerol stocks of each single isolate at $-70^{\circ}C$. We identified the species of each isolate based on the sequences of ITS regions amplified with two different universal primer pairs. We also performed morphological characterization of the filamentous fungi and yeast species through observations under the microscope. We investigated the major fungal species of commercial and home-made Nuruks by counting the colony forming units (CFU) and analyzing the occurrence tendency of fungal species. While commercial Nuruks contained mostly high CFU of yeasts, home-made Nuruks showed relatively high occurrence of filamentous fungi. One of the representative Nuruk manufacturers used both domestic wheat bran and imported ones, mainly from US, as raw material. Depending on the source of ingredient, the fungal diversity was somewhat different. Another commercial Nuruk sample was collected twice, once in 2013 and again in 2014, and showed different diversity of fungal species in each year. Nuruks obtained from the southern regions of Korea and Jeju island showed high frequency of yeast such as Saccharomycopsis fibuligera and Pichia species as well as unique filamentous fungus, Monascus species. S. fibuligera was easily found in many Nuruk samples with high CFU. The major filamentous fungi were Aspergillus, Lichtheimia, Mucor and Penicillium species. In order to further our understanding of the isolates and their potential industrial applications, we assayed three enzymes, alpha amylase, glucoamylase and acid protease from 140 isolates out of about five hundred isolates and selected about 10 excellent strains with high enzyme activities. With these fungal isolates, we will perform omics analyses including genomics, transcriptomics, metabolic pathway analyses, and metabolomics followed by whole genome sequencing of unique isolates associated with the basic research of Nuruk and that also has applications in the Makgeolli making process.

• Journal of Life Science
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• v.28 no.10
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• pp.1244-1253
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• 2018

Rumen microbiome consists of a wide variety of microorganisms, such as bacteria, archaea, protozoa, fungi, and viruses, that are in a symbiotic relationship in a strict anaerobic environment in the rumen. These rumen microbiome, a vital maker, play a significant role in feed fermentation within the rumen and produce different volatile fatty acids (VFAs). VFAs are essential for energy metabolism and protein synthesis of the host animal, even though emission of methane gas after feed fermentation is considered a negative indicator of loss of dietary energy of the host animal. To improve rumen microbial efficiency, a variety of approaches, such as feed formulation, the addition of natural feed additives, dietary feed-microbes, etc., have taken to increase ruminant performance. Recently with the application of high-throughput sequencing or next-generation sequencing technologies, especially for metagenomics and metatranscriptomics of rumen microbiomes, our understanding of rumen microbial diversity and function has significantly increased. The metaproteome and metabolome provide deeper insights into the complicated microbial network of the rumen ecosystem and its response to different ruminant diets to improve efficiency in animal production. This review summarized some recent advances of rumen microbiome techniques, especially "meta-omics," viz. metagenomic, metatranscriptomic, metaproteomic, and metabolomic techniques to increase feed fermentation and utilization in ruminants.