Neurophotonics · 2025
Depth-resolved fiber photometry of amyloid plaque signals in freely behaving Alzheimer's disease mice.
СтатьяНазвание и аннотация: Перевод в очереди
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Byron Nicole, McAlinden Niall, Pisano Filippo, Pisanello Marco, Ferreira Jacques, Montinaro Cinzia, Mathieson Keith, De Vittorio Massimo, Pisanello Ferruccio, Sakata Shuzo
Аннотация
SIGNIFICANCE: Current preclinical evaluation of Alzheimer's disease pathology in mouse models relies on post-mortem analyses, which hinders the development and optimization of therapeutic approaches. Although in vivo methods exist, monitoring amyloid plaque signals across multiple brain regions in freely behaving animals remains a significant challenge.
AIM: We aim to develop an optical approach to address this challenge.
APPROACH: We used flat and tapered optical fibers in an Alzheimer's mouse model.
RESULTS: We first confirmed that conventional flat fiber-based photometry can detect amyloid plaque signals across multiple brain regions under anesthesia after injecting a blood-brain-barrier-permeable tracer, Methoxy-X04. The depth profile of in vivo fluorescent signals is correlated with histological signals. A machine learning approach could distinguish between in vivo fluorescent signals of mice with and without amyloid plaques. Next, after validating the feasibility of depth-resolved fiber photometry ex vivo, we chronically implanted a tapered fiber to monitor amyloid plaque signals in freely behaving mice. After injecting Methoxy-X04, fluorescent signals increased in a depth-specific manner in Alzheimer's mice, but not in their wild-type littermates.
CONCLUSIONS: Our approach expands the capabilities of fiber photometry to monitor molecular pathologies, such as amyloid plaques, even in a freely behaving condition.
AIM: We aim to develop an optical approach to address this challenge.
APPROACH: We used flat and tapered optical fibers in an Alzheimer's mouse model.
RESULTS: We first confirmed that conventional flat fiber-based photometry can detect amyloid plaque signals across multiple brain regions under anesthesia after injecting a blood-brain-barrier-permeable tracer, Methoxy-X04. The depth profile of in vivo fluorescent signals is correlated with histological signals. A machine learning approach could distinguish between in vivo fluorescent signals of mice with and without amyloid plaques. Next, after validating the feasibility of depth-resolved fiber photometry ex vivo, we chronically implanted a tapered fiber to monitor amyloid plaque signals in freely behaving mice. After injecting Methoxy-X04, fluorescent signals increased in a depth-specific manner in Alzheimer's mice, but not in their wild-type littermates.
CONCLUSIONS: Our approach expands the capabilities of fiber photometry to monitor molecular pathologies, such as amyloid plaques, even in a freely behaving condition.