Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging has demonstrated great potential for metabolic imaging; however, achieving sufficiently high lateral and mass resolution to reach the organelle scale remains challenging. To address this, we have developed an approach that combines imaging acquisitions close to the highest lateral resolution (<150 nm) and mass resolution (9,000) reachable by ToF-SIMS. The data were then merged and processed using multivariate analysis (MVA), providing the identification and annotation of 85% of the main contributors to the multivariate analysis components at high lateral resolution. Insights into the electron microscopy sample preparation were provided, especially as we revealed that at least three different osmium-containing complexes can be found depending on the specific chemical environment of organelles. In cells of the snow alga Sanguina nivaloides, living in a natural environment limited in nutrients such as phosphorus (P), we mapped elements and molecules within their subcellular context, allowing for the molecular fingerprinting of organelles at a resolution of ∼150 nm, as confirmed by correlative electron microscopy. It was thus possible to highlight that S. nivaloides likely absorbed selectively some inorganic P forms provided by P-rich dust deposited on the snow surface. S. nivaloides cells could maintain phosphorylations in the stroma of the chloroplast, consistently with the preservation of photosynthetic activity. The presented method can thus overcome the current limitations of ToF-SIMS for subcellular imaging and contributes to the understanding of key questions, such as P homeostasis and other cell physiological processes.
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