Department of Infectious Diseases, Virology, University of Heidelberg, Germany; German Center for Infection Research, partner site Heidelberg, Germany.
J Mol Biol. 2018 Aug 17;430(17):2612-2625. doi: 10.1016/j.jmb.2018.06.018. Epub 2018 Jun 24.
A comprehensive understanding of host-pathogen interactions requires quantitative assessment of molecular events across a wide range of spatiotemporal scales and organizational complexities. Due to recent technical developments, this is currently only achievable with microscopy. This article is providing a general perspective on the importance of microscopy in infectious disease research, with a focus on new imaging modalities that promise to have a major impact in biomedical research in the years to come. Every major technological breakthrough in light microscopy depends on, and is supported by, advancements in computing and information technologies. Bioimage acquisition and analysis based on machine learning will pave the way toward more robust, automated and objective implementation of new imaging modalities and in biomedical research in general. The combination of novel imaging technologies with machine learning and near-physiological model systems promises to accelerate discoveries and breakthroughs in our understanding of infectious diseases, from basic research all the way to clinical applications.
要全面了解宿主-病原体相互作用，需要定量评估广泛的时空尺度和组织复杂性下的分子事件。由于最近的技术发展，这目前只能通过显微镜来实现。本文提供了在传染病研究中显微镜的重要性的总体观点，重点介绍了新的成像方式，这些方式有望在未来几年对生物医学研究产生重大影响。 每一个在光学显微镜方面的重大技术突破都取决于计算和信息技术的进步，并得到了它们的支持。基于机器学习的生物图像采集和分析将为更强大、自动化和客观地实施新的成像方式以及更广泛的生物医学研究铺平道路。新型成像技术与机器学习和近乎生理的模型系统相结合，有望加速我们对传染病的理解，从基础研究到临床应用。
