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代谢组学在抗击疟疾中的应用

Metabolomics in the fight against malaria.

作者信息

Salinas Jorge L, Kissinger Jessica C, Jones Dean P, Galinski Mary R

机构信息

Division of Infectious Diseases, Emory University School of Medicine, Emory University, Atlanta, GA, USA.

Department of Genetics, Institute of Bioinformatics, Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA, USA.

出版信息

Mem Inst Oswaldo Cruz. 2014 Aug;109(5):589-97. doi: 10.1590/0074-0276140043.

Abstract

Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host's metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC), a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP) malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

摘要

代谢组学利用高分辨率质谱技术提供细胞、组织或体液中数千种代谢物的化学指纹图谱。这种代谢表型分析已成功用于研究各种生物过程和疾病状态。高分辨率代谢组学能够为疟原虫生命周期各阶段宿主 - 寄生虫相互作用的复杂性以及对宿主代谢、发病机制和疾病的下游影响提供新的见解。这些数据可以与使用自上而下的系统生物学方法生成的其他大型数据集整合,并被计算生物学家用于开发和完善与识别新药物靶点或干预策略相关的疟疾发病机制模型。在此,我们聚焦于代谢组学在补充系统生物学方法以寻求抗击疟疾新干预措施方面的前景。我们介绍了疟疾宿主 - 病原体相互作用中心(MaHPIC),这是一个新的系统生物学研究联盟。MaHPIC的一个主要目标是生成与人类和非人类灵长类动物(NHP)疟原虫及其宿主相关的系统生物学数据集,并通过在线关系数据库将这些数据集公开提供。来自世界各地NHP感染和临床疟疾感染的代谢组学数据将构成一种独特的全球资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/31f4/4156452/fa702f8259bd/0074-0276-mioc-109-5-0589-gf01.jpg

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