Yamaguchi Daiki, Oki Keita, Kaya Yuki, Sakairi Yoshiaki, Morita Yuji, Kamoshida Go
Department of Infection Control Science, Meiji Pharmaceutical University, Kiyose-shi, Tokyo, Japan.
Microbiol Immunol. 2025 Jul;69(7):377-383. doi: 10.1111/1348-0421.13225. Epub 2025 May 6.
The analysis of bacterial infections using animal models has primarily relied on the average evaluation of many individuals at specific time points. Consequently, tracking temporal changes in an infection within the same individual is challenging. InVivo imaging techniques enable the longitudinal assessment of infection in the same individual while reducing the number of animals required. Understanding the dynamics of bacterial infections over time is crucial for elucidating disease mechanisms and developing effective treatment strategies. In this review, we summarize the In Vivo imaging techniques used to detect bacterial colonization in deep tissues in animal models of bacterial infection, along with efforts to enhance their sensitivity. In particular, we introduce a recently developed In Vivo imaging system that employs near-infrared luminescence to achieve high sensitivity and versatility. Furthermore, we discuss strategies for further improving its sensitivity.
利用动物模型分析细菌感染主要依赖于在特定时间点对许多个体进行平均评估。因此，追踪同一个体内感染的时间变化具有挑战性。体内成像技术能够在减少所需动物数量的同时，对同一个体内的感染进行纵向评估。了解细菌感染随时间的动态变化对于阐明疾病机制和制定有效的治疗策略至关重要。在本综述中，我们总结了用于在细菌感染动物模型中检测深部组织细菌定植的体内成像技术，以及提高其灵敏度的相关努力。特别是，我们介绍了一种最近开发的体内成像系统，该系统利用近红外发光实现高灵敏度和多功能性。此外，我们还讨论了进一步提高其灵敏度的策略。
