Reaction-based chemical shift engineering unlocks interference-free detection window for in vivo proton magnetic resonance spectroscopy

Résumé fourni par la source

Proton magnetic resonance spectroscopy (¹H MRS) enables non-invasive in vivo detection of metabolites and biochemical alterations, providing critical information for neurological disease diagnosis and metabolic monitoring. However, conventional ¹H MRS is restricted to endogenous metabolites with resonance signals clustered in the 1–5 ppm region, resulting in severe spectral overlap that fundamentally limits specific identification of target biomolecules. While reaction-responsive molecular probes are widely used in optical imaging, their integration with ¹H MRS to resolve spectral congestion remains underexplored. We develop a reaction-based chemical shift engineering strategy for ¹H MRS. Target-specific chemical reactions generate well-resolved resonance peaks beyond 5 ppm, thereby circumventing interference from endogenous metabolites and water signals. As a proof of concept, we engineered a molecular probe FS for selective detection of norepinephrine (NE), a key neurotransmitter implicated in depression. We elucidated the reaction mechanism via theoretical simulation, and validated its performance in aqueous solutions, PC12 cells, and fluoxetine-treated live rats on a 7.0 T magnetic resonance system. The probe FS undergoes specific cascade nucleophilic substitution with NE to produce 4-hydroxybutanal, which yields a characteristic aldehyde proton resonance at ~ 9.7 ppm, fully separated from endogenous spectral signals. The probe exhibited favorable selectivity, anti-interference capacity and pH stability in vitro. Furthermore, FS successfully detected endogenous NE secretion in PC12 cells and enabled in vivo monitoring of pharmacologically elevated NE in rat brains. This work establishes a generalizable strategy to expand the metabolic detection scope of ¹H MRS via analyte-specific chemical reactions, holding significant translational potential for disease diagnosis, dynamic metabolic monitoring and preclinical drug evaluation.

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