Many biological questions are essentially spatial: why do leaf margin and leaf base differ in metabolites? Why do tumor and paratumor metabolic profiles differ? Why do neurons and glial regions differ in metabolism? Traditional metabolomics homogenizes tissue, flattening these differences. Spatial metabolomics uses MSI to preserve structure and directly present metabolic spatial heterogeneity, enabling researchers to ask 'the mechanism behind distribution differences'.
The application notes of the Neo-Source MSI DPI list 'metabolomics: spatial distribution changes of metabolites' as the primary application area, and state that photochemical post-ionization extends the detectable lipids, terpenoids, flavonoids, amino acids and glycosides and other secondary metabolites to more than a hundred in both positive and negative ion modes, with overall signal enhanced by 1–3 orders of magnitude.
In published DPI cases, mouse brain section imaging showed simultaneous imaging of neurotransmitters (GABA, creatine, glutamine, glutamate, adenosine) and various neutral GalCer lipids, guiding neuroscience, pharmacology and neurochemistry research; in plants, samples such as sage, Ginkgo, tea leaf, tomato, tobacco and petals all presented rich metabolite spatial distribution, e.g., theanine signal in tea leaf increased by 14.5x and caffeine by 61x, with significant differences between vein and blade regions.
These cases jointly show: spatial metabolomics can depict metabolic partitions within organs, reveal chemical heterogeneity of different microstructures in plants, and also be used for spatially specific toxicity research of pollutants (e.g., carbamazepine (CBZ) and its transformation products enriched at the leaf margin in tomato, at a concentration 2.3x that of the inner region) (Environ. Sci. Technol., 2024).
The success of spatial metabolomics largely depends on whether it can 'see comprehensively and clearly'. The Neo-Source MSI DPI has no polarity bias, covering polar/weakly-polar/non-polar organics; low ion suppression allows complex samples to be analyzed directly; matrix-free avoids the low-mass region being covered by matrix peaks. MSI LDPI further pushes the minimum detectable m/z down to 70, specializing in clean spectra of the small-molecule low-mass region.
At the data-interpretation level, spatial metabolomics often uses statistics such as principal component analysis, spatial clustering, boxplots and t-tests to identify differential regions and differential metabolites, and integrates with transcriptomics and metabolic pathways to build a 'ingredient–gene–phenotype' closed loop.
A single metabolite map is insufficient to explain mechanisms; spatial metabolomics is often combined with spatial lipidomics, spatial proteomics and transcriptomics to form multi-omics integrated imaging. The two Neo-Source imaging sources keep the section intact after imaging for continued H&E or IHC, leaving room for multi-omics.
Engineered, DPI is compatible with mainstream mass spectrometers from Agilent, AB SCIEX and Thermo, with 20–200 μm adjustable resolution; LDPI provides 2–3 μm matrix-free ambient imaging. The two complement each other by resolution and polarity coverage, supporting spatial metabolism research from organ scale to single-cell scale.
To obtain detailed specifications, compatible models, or a quotation for the MSI LDPI / DPI full series imaging ion sources, visit the Neo-Source official website, or contact the official team for compatibility advice tailored to your mass spectrometer (Agilent / SCIEX / Thermo and other mainstream MS).