• Communications for Statistical Applications and Methods
• /
• v.29 no.6
• /
• pp.655-664
• /
• 2022

On the motivation by an integrative study of multi-omics data, we are interested in estimating the structure of the sparse cross correlation matrix of two high-dimensional random vectors. We rewrite the problem as a multiple testing problem and propose a new method to estimate the sparse structure of the cross correlation matrix. To do so, we test the correlation coefficients simultaneously and threshold the correlation coefficients by controlling FRD at a predetermined level α. Further, we apply the proposed method and an alternative adaptive thresholding procedure by Cai and Liu (2016) to the integrative analysis of the protein expression data (X) and the mRNA expression data (Y) in TCGA breast cancer cohort. By varying the FDR level α, we show that the new procedure is consistently more efficient in estimating the sparse structure of cross correlation matrix than the alternative one.

• BMB Reports
• /
• v.56 no.1
• /
• pp.43-48
• /
• 2023

Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids.

• Mass Spectrometry Letters
• /
• v.9 no.1
• /
• pp.24-29
• /
• 2018

DC23, a triazolothione resorcinol analogue, is known to inhibit heat shock protein 90 and pyruvate dehydrogenase kinase which are up-regulated in cancer and diabetes, respectively. This study was performed to elucidate the metabolism of DC23 in human liver microsomes (HLMs). HLMs incubated with DC23 in the presence of uridine 5'-diphosphoglucuronic acid (UDPGA) and/or ${\beta}$-nicotinamide adenine dinucleotide phosphate (NADPH) resulted in the formation of four metabolites, M1-M4. M1 was identified as DC23-N-Oxide, on the basis of LC-MS/MS analysis. DC23 was further metabolized to its glucuronide conjugates (M2, M3, and M4). In vitro metabolic stability studies conducted with DC23 in HLMs revealed significant glucuronide conjugation with a $t_{1/2}$ value of 1.3 min. The inhibitory potency of DC23 on five human cytochrome P450s was also investigated in HLMs. In these experiments, DC23 inhibited CYP2C9-mediated tolbutamide hydroxylase activity with an $IC_{50}$ value of $8.7{\mu}M$, which could have implications for drug interactions.

• Molecules and Cells
• /
• v.44 no.3
• /
• pp.127-135
• /
• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• Journal of Applied Biological Chemistry
• /
• v.59 no.4
• /
• pp.361-364
• /
• 2016

We developed a spectrophotometric assay method for polyethoxylated ascorbic acidusing 3-ethyl ascorbic acid as standard material. The analytical method was validated by linearity, accuracy, precision, and stability. The coefficient of variation of the precision of the assay was less than 3.4 %. The linearity of the calibration curves in the desired concentration range is good ($r^2$>0.998). 3-Ethyl ascorbic acid and polyethoxylated ascorbic acid were stable in stock solution at room temperature for up to at least 6 h. The developed assay could be used for the content analysis of polyethoxylated ascorbic acid in samples.

• Food Science and Industry
• /
• v.50 no.1
• /
• pp.16-25
• /
• 2017

There is no doubt that accumulation of big data using multi-omics technologies will be useful to solve human's long-standing problems such as development of personalized diet and medicine, overcoming diseases, and longevity. However, in the food industry, big data based on omics is scarcely accumulated. In particular, comprehensive analysis of molecular lipid metabolites directly associated with food quality, such as taste, flavor, and texture has been very limited. Moreover, most of food lipidomics studies are applied to analyze lipid components and discriminate authenticity and freshness of limited foods including vegetable and fish oil. However, if lipid big data through food lipidomics research of various foods and materials can be accumulated, lipidomics can be used in the optimization of food processing, production, delivery system, food safety, and storage as well as functional food.

• 한국균학회소식:학술대회논문집
• /
• 2018.05a
• /
• pp.33-33
• /
• 2018

Air-borne plant pathogenic fungus Fusarium graminearum and seed-borne plant pathogenic bacterium Burkholderia glumae are cause similar disease symptoms in rice heads. Here we showed that two pathogens frequently co-isolated in rice heads and F. graminearum is resistant to toxoflavin produced by B. glumae while other fungal genera are sensitive to the toxin. We have tried to clarify the resistant mechanism of F. graminearum against toxoflavin and the ecological reason of co-existence of the two pathogens in rice. We found that F. graminearum carries resistance to toxoflavin as accumulating lipid in fungal cells. Co-cultivation of two pathogens resulted in increased conidia and enhanced chemical attraction and attachment of the bacterial cells to the fungal conidia. Bacteria physically attached to fungal conidia, which protected bacterium cells from UV light and allowed disease dispersal. Chemotaxis analysis showed that bacterial cells moved toward the fungal exudation compared to a control. Even enhanced the production of phytotoxic trichothecene by the fungal under presence of toxoflavin and disease severity on rice heads was significantly increased by co-inoculation rather than single inoculation. This study suggested that the undisclosed potentiality of air-born infection of bacteria using the fungal spores for survival and dispersal.

• Mass Spectrometry Letters
• /
• v.8 no.4
• /
• pp.98-104
• /
• 2017

Ginseng (Panax ginseng Meyer) is a well-known health functional food used as a traditional herbal drug in Asian countries owing to its diverse pharmacological effects. Herb-drug interactions may cause unexpected side effects of co-administered drugs by the alteration of pharmacokinetics through effects on cytochrome P450 activity. In this study, we investigated the herb-drug interactions between Korean red ginseng extract (KRG) and five CYP-specific probes in mice. The pharmacokinetics of KRG extract induced-drug interactions were studied by cassette dosing of five CYP substrates for CYP1A, 2B, 2C, 2D, and 3A and the LC-MS/MS analysis of the blood concentration of metabolites of each of the five probes. The linearity, precision, and accuracy of the quantification method of the five metabolites were successfully confirmed. The plasma concentrations of five metabolites after co-administration of different doses of the KRG extract (0, 0.5, 1, and 2 g/kg) were quantified by LC-MS/MS and dose-dependent pharmacokinetic parameters were determined. The pharmacokinetic parameters of the five metabolites were not significantly altered by the dose of the KRG extract. In conclusion, the single co-administration of KRG extract up to 2 g/kg in vivo did not cause any significant herb-drug interactions linked to the modulation of CYP activity.

• Genomics & Informatics
• /
• v.16 no.3
• /
• pp.52-58
• /
• 2018

In this report, we present a case study of how pharmacogenomics and pharmacometabolomics can be useful to characterize safety and pharmacokinetic profiles in early phase new drug development clinical trials. During conducting a first-in-human trial for a new molecular entity, we were able to determine the mechanism of dichotomized variability in plasma drug concentrations, which appeared closely related to adverse drug reactions (ADRs) through integrated omics analysis. The pharmacogenomics screening was performed from whole blood samples using the Affymetrix DMET (Drug-Metabolizing Enzymes and Transporters) Plus microarray, and confirmation of genetic variants was performed using real-time polymerase chain reaction. Metabolomics profiling was performed from plasma samples using liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. A GSTM1 null polymorphism was identified in pharmacogenomics test and the drug concentrations was higher in GSTM1 null subjects than GSTM1 functional subjects. The apparent drug clearance was 13-fold lower in GSTM1 null subjects than GSTM1 functional subjects (p < 0.001). By metabolomics analysis, we identified that the study drug was metabolized by cysteinylglycine conjugation in GSTM functional subjects but those not in GSTM1 null subjects. The incidence rate and the severity of ADRs were higher in the GSTM1 null subjects than the GSTM1 functional subjects. Through the integrated omics analysis, we could understand the mechanism of inter-individual variability in drug exposure and in adverse response. In conclusion, integrated multi-omics analysis can be useful for elucidating the various characteristics of new drug candidates in early phase clinical trials.

• Genomics & Informatics
• /
• v.18 no.1
• /
• pp.8.1-8.10
• /
• 2020

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.