Enhancing Sensitivity of Atmospheric Pressure Laser Ablation Carbon Fiber Ionization Mass Spectrometry Imaging for Endogenous Metabolites Using a Polydopamine/Covalent Organic Framework Composite

Abstract The spatial distribution of endogenous small-molecule metabolites is pivotal for understanding living processes, disease mechanisms, and therapeutic principles. However, achieving high-sensitivity spatial metabolomic profiling remains challenging for atmospheric pressure mass spectrometry imaging (AP-MSI) due to low desorption/ionization efficiency, leading to the systematic omission of low-abundance yet biologically vital metabolites from spatial maps. Here, we developed a high-sensitivity MSI platform that integrated a polydopamine/covalent organic framework (PDA/COF) composite substrate with atmospheric pressure laser ablation carbon fiber ionization (LACFI) technology for spatial mapping of endogenous small-molecule metabolites in biological tissues. This substrate employed a polydopamine (PDA) interlayer to guide the ordered assembly of a COF on the substrate. The resulting PDA/COF composite substrate exhibited uniform surface coverage, strong stability, and excellent light absorption, collectively improving the laser desorption/ionization efficiency of metabolites. Moreover, the substrate was simple, easy to use, and cost-effective. Our platform demonstrated a significantly enhanced sensitivity, achieving an improvement of more than 2-fold based on the slope of the linear calibration curve for analysis of metabolites compared with MALDI, DESI, LACFI using copper-coated, graphene oxide, and COF substrate. It also exhibited excellent linear response, wide dynamic range, and broad metabolite coverage. The platform was further applied to map the metabolomes of normal, para-cancerous, and cancerous liver tissues and, through heatmap analysis, clearly revealed the spatial distribution patterns of metabolites such as NAD+ and adenine across these tissue types. This method provides a straightforward, efficient, and robust AP-MSI platform for highly sensitive and comprehensive spatial metabolomics.