Subcellular ToF-SIMS Imaging of the Snow Alga Sanguina nivaloides by Combining High Mass and High Lateral Resolution Acquisitions
Year: 2024
Type: article
Abstract: ABSTRACT Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging has demonstrated great potential for metabolic imaging, yet achieving sufficiently high lateral and mass resolution to reach the organelle scale remains challenging. We have developed an approach by combining ToF-SIMS imaging acquisitions at high lateral resolution (> 150 nm) and high mass resolution (9,000). The data were then merged and processed using multivariate analysis (MVA), allowing for the precise 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 are provided, especially as we reveal 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 were able to map elements and molecules within their subcellular context, allowing for the molecular fingerprinting of organelles at a resolution of 100 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 contribute to the understanding of key questions such as P homeostasis and other cell physiological processes.
Source: Analytical Chemistry
Institutions: Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CEA Grenoble, Institut de Recherche Interdisciplinaire de Grenoble, Laboratoire Modélisation et Exploration des Matériaux, Université Grenoble Alpes, Centre National de la Recherche Scientifique, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Laboratoire Physiologie Cellulaire & Végétale, Laboratoire d'Électronique des Technologies de l'Information
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4405093201
