Real-time tracking of Yersinia pestis infection dynamics using a near-infrared fluorescent protein labeling system

ABSTRACT Live imaging is essential for elucidating dynamic infection processes. Here, we developed a near-infrared fluorescent protein (NIR-FP)-based labeling strategy that enables integrated visualization of bacterial behavior in both cellular and animal infection models. Using Yersinia pestis as a model pathogen, we constructed stable fluorescent strains by either chromosomal insertion of the gene encoding NIR-FP miRFP670nano3 under the control of a strong endogenous promoter to obtain Yp-nano3, or by introducing a plasmid expressing the same reporter to obtain Yp-p-nano3. Both labeled strains exhibited a strong correlation between fluorescence intensity and bacterial counts, with Yp-nano3 exhibiting significantly higher brightness at the same bacterial count. Importantly, the labeled strains showed no measurable reduction in virulence under the tested experimental conditions, supporting their use in physiologically relevant infection studies. In cellular infection assays, sustained and robust fluorescence from the labeled bacteria enables continuous monitoring of pathogen–host cell interactions for up to 12 h. In a murine bubonic plague model, fluorescence signals were detectable in the inguinal lymph nodes (ILN) as early as 1 day post-infection with Yp-nano3 and increased progressively until the mice died. In contrast, mice infected with a highly attenuated Δpla mutant carrying the same NIR-FP label showed no detectable fluorescence in ILN throughout the infection. These results show that NIR-FP labeling, combined with in vivo imaging, provides a powerful approach for real-time tracking of the dissemination of Y. pestis in lymph nodes and for assessing bacterial virulence. Together, this work establishes an NIR-FP labeling platform suitable for real-time analysis of bacterial infection dynamics and host-pathogen interactions. IMPORTANCE Live imaging techniques, such as bioluminescence imaging and fluorescence imaging, have been widely used to study infection dynamics. However, bioluminescence imaging is strongly limited by its dependence on exogenous substrate administration and its inability to explore direct interactions between pathogen and host cells. To overcome these limitations, we established an NIR-FP labeling platform that enables visualization of pathogen–host interactions at both cellular and animal levels, using Y. pestis as a model pathogen. This labeling method offers high stability and a strong linear relationship between fluorescence intensity and bacterial count, allowing real-time tracking of bacterial dissemination to lymph nodes and subsequent proliferation in vivo . Together, these attributes offer a novel and robust tool for investigating infection dynamics and underlying pathogenic mechanisms.