• Molecular & Cellular Toxicology
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• 제4권3호
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• pp.260-266
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• 2008

Recently, there has been scientific discussion on the utility of -omics techniques such as genomics, proteomics, and metabolomics within toxicological research and mechanism-based risk assessment. Toxicogenomics is a novel approach integrating the expression analysis of genes (genomic) or proteins (proteomic) with traditional toxicological methods. Since 1999, the toxicogenomic approach has been extensively applied for regulatory purposes in order to understand the potential toxic mechanisms that result from chemical compound exposures. Therefore, this article's purpose was to consider the utility of toxicogenomic profiles for improved risk assessment, explore the current limitations in applying toxicogenomics to regulation, and finally, to rationalize possible avenues to resolve some of the major challenges. Based on many recent works, the significant impact toxicogenomic techniques would have on human health risk assessment is better identification of toxicity pathways or mode-of-actions (MOAs). In addition, the application of toxicogenomics in risk assessment and regulation has proven to be cost effective in terms of screening unknown toxicants prior to more extensive and costly experimental evaluation. However, to maximize the utility of these techniques in regulation, researchers and regulators must resolve many parallel challenges with regard to data collection, integration, and interpretation. Furthermore, standard guidance has to be prepared for researchers and assessors on the scientifically appropriate use of toxicogenomic profiles in risk assessment. The National Institute of Toxicological Research (NITR) looks forward to an ongoing role as leader in addressing the challenges associated with the scientifically sound use of toxicogenomics data in risk assessment.

• 한국축산식품학회지
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• 제40권1호
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• pp.1-10
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• 2020

Various processing methods have a great impact on the physiochemical and nutritional properties of meat that are of health concern. Hence, the postmortem processing of meat by different methods is likely to intensify the potential effects on protein oxidation. The influence of meat protein oxidation on the modulation of the systemic redox status and underlying mechanism is well known. However, the effects of processed meat proteins isolated from different sources on gut microbiota, oxidative stress biomarkers, and metabolomic markers associated with metabolic syndromes are of growing interest. The application of advanced methodological approaches based on OMICS, and mass spectrometric technologies has enabled to better understand the molecular basis of the effect of processed meat oxidation on human health and the aging process. Animal studies indicate the involvement of dietary proteins isolated from different sources on health disorders, which emphasizes the impact of processed meat protein on the richness of bacterial taxa such as (Mucispirillum, Oscillibacter), accompanied by increased expression of lipogenic genes. This review explores the most recent evidences on meat processing techniques, meat protein oxidation, underlying mechanisms, and their potential effects on nutritional value, gut microbiota composition and possible implications on human health.

• Genomics & Informatics
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• 제17권4호
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.

• BMB Reports
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• 제41권8호
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• pp.609-614
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• 2008

The concentrations and catalytic activities of enzymes control metabolic rates. Previous studies have focused on enzyme concentrations because there are no genome-wide techniques used for the measurement of enzyme activity. We propose a method for evaluating the significance of enzyme activity by integrating metabolic network topologies and genome-wide microarray gene expression profiles. We quantified the enzymatic activity of reactions and report the 388 significant reactions in five perturbation datasets. For the 388 enzymatic reactions, we identified 70 that were significantly regulated (P-value < 0.001). Thirty-one of these reactions were part of anaerobic metabolism, 23 were part of low-pH aerobic metabolism, 8 were part of high-pH anaerobic metabolism, 3 were part of low-pH aerobic reactions, and 5 were part of high-pH anaerobic metabolism.

• BMB Reports
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• 제53권6호
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• pp.299-310
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• 2020

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.

• 식물병연구
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• 제21권3호
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• pp.161-179
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• 2015

식물은 다양한 병원성 미생물에 대하여 효과적인 방어 기제를 발전시켜 왔다. 최근 유전체와 다중 오믹스 기술의 발전은 우리에게 미생물 인자에 의한 식물 면역을 폭넓게 이해할 수 있는 단초를 제공해 주었다. 하지만 아직까지는 이러한 기술을 병 방제 전략에 이용한 적은 많지 않다. 그래서 본 리뷰에서 식물 면역의 기본 개념을 소개하고 최근 얻어진 결과들을 소개하였다. 덧붙여 이미 논문에서 발표된 진균, 세균, 바이러스 유래 결정인자에 의한 생물적 방제 가능한 방법에 대해 기술하였다. 특히 미생물 결정인자인 chitin, glucan, LPS/EPS, 미생물분자패턴, 항생제, 식물유사호르몬, AHLs, harpin, 비타민, 휘발성물질에 대한 결과를 자세하게 기술하였다. 이 리뷰를 통하여 많은 과학자들과 농민들이 미생물 결정인자 기반의 생물적 방제에 대한 지식이 폭넓어지고, 다양한 미생물 결정 인자가 앞으로 농업현장의 종합적인 병방제 전략의 하나로 자리매김하기를 바란다.

• 한국자기공명학회논문지
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• 제22권4호
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• pp.91-100
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• 2018

Benzisothiazolinone (BIT) is the preservative that is widely used in industrial and household products. In this study, zebrafish (Danio rerio) was exposed to BIT at different concentrations (control, 0.5 g/L, 1.0 g/L and 2.0 g/L) for 72 hours. The techniques of nuclear magnetic resonance (NMR) spectroscopy were applied to analyze the effects of BIT on zebrafish. The advantages of NMR are the minimal sample preparation and high reproducibility of experimental results. With the multivariate statistical analysis, dimethylamine, N-acetylaspartate, glycine and histidine were identified as an important metabolite in differentiating between the control and BIT-exposed group. This study will improve the understanding the metabolite changes in the zebrafish in response to BIT exposure.

• 생명과학회지
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• 제28권10호
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• pp.1244-1253
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• 2018

반추위 속에는 박테리아, 고세균, 프로토조아, 곰팡이 및 바이러스와 같은 다양한 미생물들이 편성의 혐기조건에서 공생하고 있다. 사료의 발효에 중요한 역할을 하고 있는 반추위 미생물은 위내 발효과정에서 에너지 손실에 영향을 주는 메탄의 발생을 제외하면 에너지와 단백질 대사에 필수적인 다양한 휘발성 지방산을 생산한다. 반추위내 미생물의 이용효율을 개선시키기 위해 사료배합비조절, 천연사료첨가제, 생균제첨가 등의 다양한 접근방법들이 사용되고 있다. 최근에 반추위 군집에 대한 메타유전체 또는 메타전사체와 같은 차세대 유전체 해독기술 또는 차세대 시퀀싱 기술의 적용으로 반추위 미생물의 다양성 및 기능에 대한 이해가 크게 증가하였다. 특히 메타단백질체와 메타대사체는 반추위 생태계의 복잡한 미생물네트워크에 대한 더 깊은 통찰력을 제공할 뿐만 아니라, 다양한 반추가축용 사료에 대한 반응을 제공함으로서 생산효율을 개선시키는데 기여하였다. 본 논문에서는 반추위내 사료의 발효와 이용을 향상시키기 위한 메타오믹스 기술, 즉, 메타유전체, 메타전사체, 메타단백질체 및 메타대사체의 최신 응용기술을 요약하고자 한다.

• Journal of Plant Biotechnology
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• 제37권1호
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• pp.12-24
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• 2010

식물 대사체 (plant metabolomics) 연구는 식물 세포 및 조직에 존재하는 모든 대사산물의 시간적, 공간적 변화를 추적 조사함으로써 식물의 복잡한 생리 현상을 총체적으로 이해하는 연구이다. 이와 같은 식물 대사체 연구는 최근 개발이 이루어지고 있는 여러 오믹스 연구 분야의 하나로 시스템생물학의 한 분야이다. 식물 대사체 연구는 시료로부터 순수 화합물 또는 복합물을 정제하거나 또는 정제가 이루어지지 않은 혼합액으로부터 대사체 스펙트럼 정보를 확보하여 분석이 이루어지므로 추출액 제조 및 얻어진 대사체 데이터의 분석과정의 표준화가 필수적으로 이루어져야 한다. 이는 대사체 분석 결과의 해상도 및 재현성의 확보의 핵심 요소 이다. 식물 대사체 연구는 기능유전체학의 연구 수단은 물론 식물의 종, 품종, 더 나아가 GM 식물의 식별, 대사조절 기작 규명, 유용물질 생산, 식물의 외부 환경 스트레스 요인에 대한 다양한 생리적 반응 이해 등 다양한 연구 분야에서 활용이 이루어지고 있다. 최근 식물 대사체 연구는 모델식물(벼, 애기장대)의 유전체 정보와 연계하여 돌연변이주의 분석을 통해 유전자의 기능 정의 수단으로 활용되고 있다. 따라서 향후 유전체 정보와 대사체 정보의 연계를 통해 복잡한 대사경로 규명이나 다양한 생리 현상 해석 연구가 더욱 활발하게 진행될 것으로 전망된다.

• Journal of Ginseng Research
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• 제48권2호
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• pp.149-162
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• 2024

Ginseng, the roots of Panax species, is an important medicinal herb used as a tonic. As ginsenosides are key bioactive components of ginseng, holistic chemical profiling of them has provided many insights into understanding ginseng. Mass spectrometry has been a major methodology for profiling, which has been applied to realize numerous goals in ginseng research, such as the discrimination of different species, geographical origins, and ages, and the monitoring of processing and biotransformation. This review summarizes the various applications of ginsenoside profiling in ginseng research over the last three decades that have contributed to expanding our understanding of ginseng. However, we also note that most of the studies overlooked a crucial factor that influences the levels of ginsenosides: genetic variation. To highlight the effects of genetic variation on the chemical contents, we present our results of untargeted and targeted ginsenoside profiling of different genotypes cultivated under identical conditions, in addition to data regarding genome-level genetic diversity. Additionally, we analyze the other limitations of previous studies, such as imperfect variable control, deficient metadata, and lack of additional effort to validate causation. We conclude that the values of ginsenoside profiling studies can be enhanced by overcoming such limitations, as well as by integrating with other -omics techniques.