Image-based systems biology of infection

被引:34
|
作者
Medyukhina, Anna [1 ]
Timme, Sandra [1 ,2 ]
Mokhtari, Zeinab [1 ,2 ]
Figge, Marc Thilo [1 ,2 ]
机构
[1] Hans Knoll Inst HKI, Leibniz Inst Nat Product Res & Infect Biol, HKI Ctr Syst Biol Infect, Appl Syst Biol, Jena, Germany
[2] Univ Jena, Appl Syst Biol, Jena, Germany
关键词
systems biology; image analysis; mathematical modeling; live-cell imaging; infection; host-pathogen interactions; HOST-PATHOGEN INTERACTIONS; FUNGAL MORPHOGENESIS; COMPUTER-SIMULATION; CELL TRAFFICKING; T-CELLS; MICROSCOPY; TRACKING; SPITZENKORPER; FLUORESCENCE; DETERMINES;
D O I
10.1002/cyto.a.22638
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The successful treatment of infectious diseases requires interdisciplinary studies of all aspects of infection processes. The overarching combination of experimental research and theoretical analysis in a systems biology approach can unravel mechanisms of complex interactions between pathogens and the human immune system. Taking into account spatial information is especially important in the context of infection, since the migratory behavior and spatial interactions of cells are often decisive for the outcome of the immune response. Spatial information is provided by image and video data that are acquired in microscopy experiments and that are at the heart of an image-based systems biology approach. This review demonstrates how image-based systems biology improves our understanding of infection processes. We discuss the three main steps of this approachimaging, quantitative characterization, and modelingand consider the application of these steps in the context of studying infection processes. After summarizing the most relevant microscopy and image analysis approaches, we discuss ways to quantify infection processes, and address a number of modeling techniques that exploit image-derived data to simulate host-pathogen interactions in silico. (c) 2015 International Society for Advancement of Cytometry
引用
收藏
页码:462 / 470
页数:9
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