Unveiling Mucorales infections: A cutting-edge longitudinal imaging approach for real-time infection and host-response monitoring in Galleria mellonella and mouse models.
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صداهایی که در نامشان «Natural»، «Neural» یا «Online» دیده میشود معمولاً طبیعیترند. انتخاب صدا به صداهای نصبشده در ویندوز و مرورگر شما بستگی دارد.
چکیده اصلی
Mucormycosis, a disease encompassing life-threatening fungal infections by members of the Mucorales group, is characterized by significant heterogeneity, poor clinical outcomes, and globally rising incidences. Although showing clear outbreak potential, the disease remains poorly understood. Mucorales infections are characterized by rapid progression and extensive tissue destruction, often requiring disfiguring surgical interventions. Moreover, intrinsic resistance and high drug tolerance limit antifungal effectiveness, contributing to the disease's high mortality. To overcome the challenges associated with these infections, a deeper understanding of mucormycosis is urgently needed. Valuable translational insights traditionally derive from in vivo host models. However, current systems are limited by single-endpoint invasive analysis, offering only a narrow view of infection progression and treatment effects. To address these critical shortcomings and enhance experimental models, bioluminescent Mucor lusitanicus reporter strains were generated to establish models that allow for real-time, longitudinal monitoring of infection in individual animals. Codon optimization, targeted integration of the firefly luciferase gene, and control of expression using highly active promoters resulted in the successful establishment of two mucormycosis models: Galleria mellonella larvae as an intermediate infection model and a translational mouse model. In the murine model, the integration of micro-CT imaging further enhanced the characterization of host-pathogen interactions by enabling noninvasive assessment of tissue responses over time. Overall, our approach enables enhanced temporal resolution for quantitative assessment of fungal burden and host responses. Using M. lusitanicus as a model organism, this methodology establishes a foundation and technical expertise for application toward clinically relevant Mucorales infection and antifungal research.
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