Wheelock Craig E, Wheelock Asa M, Kawashima Shuichi, Diez Diego, Kanehisa Minoru, van Erk Marjan, Kleemann Robert, Haeggström Jesper Z, Goto Susumu
Department of Medical Biochemistry and Biophysics, Division of Physiological Chemistry II, Karolinska Institutet, Stockholm, Sweden.
Mol Biosyst. 2009 Jun;5(6):588-602. doi: 10.1039/b902356a. Epub 2009 Apr 27.
Systems biology aims to understand the nonlinear interactions of multiple biomolecular components that characterize a living organism. One important aspect of systems biology approaches is to identify the biological pathways or networks that connect the differing elements of a system, and examine how they evolve with temporal and environmental changes. The utility of this method becomes clear when applied to multifactorial diseases with complex etiologies, such as inflammatory-related diseases, herein exemplified by atherosclerosis. In this paper, the initial studies in this discipline are reviewed and examined within the context of the development of the field. In addition, several different software tools are briefly described and a novel application for the KEGG database suite called KegArray is presented. This tool is designed for mapping the results of high-throughput omics studies, including transcriptomics, proteomics and metabolomics data, onto interactive KEGG metabolic pathways. The utility of KegArray is demonstrated using a combined transcriptomics and lipidomics dataset from a published study designed to examine the potential of cholesterol in the diet to influence the inflammatory component in the development of atherosclerosis. These data were mapped onto the KEGG PATHWAY database, with a low cholesterol diet affecting 60 distinct biochemical pathways and a high cholesterol exposure affecting 76 biochemical pathways. A total of 77 pathways were differentially affected between low and high cholesterol diets. The KEGG pathways "Biosynthesis of unsaturated fatty acids" and "Sphingolipid metabolism" evidenced multiple changes in gene/lipid levels between low and high cholesterol treatment, and are discussed in detail. Taken together, this paper provides a brief introduction to systems biology and the applications of pathway mapping to the study of cardiovascular disease, as well as a summary of available tools. Current limitations and future visions of this emerging field are discussed, with the conclusion that combining knowledge from biological pathways and high-throughput omics data will move clinical medicine one step further to individualize medical diagnosis and treatment.
系统生物学旨在理解构成生物体的多种生物分子成分之间的非线性相互作用。系统生物学方法的一个重要方面是识别连接系统中不同元素的生物途径或网络，并研究它们如何随时间和环境变化而演变。当应用于病因复杂的多因素疾病，如炎症相关疾病（本文以动脉粥样硬化为例）时，这种方法的实用性就变得显而易见。本文在该领域发展的背景下，对这一学科的初步研究进行了综述和审视。此外，简要描述了几种不同的软件工具，并介绍了KEGG数据库套件的一种新应用——KegArray。该工具旨在将高通量组学研究的结果，包括转录组学、蛋白质组学和代谢组学数据，映射到交互式KEGG代谢途径上。利用一项已发表研究中的转录组学和脂质组学联合数据集，证明了KegArray的实用性，该研究旨在探讨饮食中的胆固醇影响动脉粥样硬化发展中炎症成分的潜力。这些数据被映射到KEGG PATHWAY数据库上，低胆固醇饮食影响60条不同的生化途径，高胆固醇暴露影响76条生化途径。低胆固醇饮食和高胆固醇饮食之间共有77条途径受到不同影响。KEGG途径“不饱和脂肪酸的生物合成”和“鞘脂代谢”在低胆固醇和高胆固醇治疗之间的基因/脂质水平上有多处变化，并进行了详细讨论。综上所述，本文简要介绍了系统生物学以及途径映射在心血管疾病研究中的应用，还总结了可用工具。讨论了这一新兴领域目前的局限性和未来展望，得出的结论是，将生物途径知识与高通量组学数据相结合将使临床医学在个性化医疗诊断和治疗方面更进一步。
