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.
Depth-resolved fiber photometry of amyloid plaque signals in freely behaving Alzheimer’s disease mice
Pisanello, Marco;Montinaro, Cinzia;De Vittorio, Massimo;Pisanello, Ferruccio;
2025-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


