For the past two decades, Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) imaging has successfully answered various research questions, because it can visualize the spatial distribution of small molecules (< 2000 Da) in 2D with a spatial resolution comparable to that of a light microscope. Dr. Sebastiaan Van Nuffel is presenting various examples of the ongoing research in his group using ToF-SIMS imaging as an invited speaker.

ToF-SIMS imaging is used to simultaneously investigate the elemental composition, the metabolome and the lipidome of tissue sections as well as their interaction with non-native compounds such as drugs or toxins. Although ToF-SIMS allows for label-free detection, ambiguity always remains with regards to structural identification of compounds given the secondary ions of the different compounds present in the sample are all formed together after the impact of the primary ion. Consequently, a typical ToF-SIMS mass spectrum can be considered a summation of the spectra of the individual compounds present and spatial colocation does not necessarily mean that these mass peaks all originate from one compound. Luckily, the creation of ToF-SIMS instruments with MS/MS capabilities makes unambiguous identification finally possible. Regardless, the data generated is very complex, especially in the case of biological systems, and its integration with multivariate analysis techniques for image segmentation and more advanced machine learning approaches for biomarker discovery will be covered as well. In addition, it is difficult to detect large molecules such as intact proteins with a typical ToF-SIMS instrument. It is therefore necessary to integrate ToF-SIMS with other techniques such immunohistochemistry in order to establish a spatially resolved multi-omics atlas. However, there are several issues still hampering its widespread application. In order to become truly competitive with immunofluorescence microscopy, the same field of view needs to be achieved at a similar throughput rate. Ongoing research efforts developing SIMS-IHC methods in combination with novel stigmatic SIMS imaging instrumentation will be discussed.

Finally, as it can observe inorganic and organic compounds with micrometric resolution, ToF-SIMS is also eminently suited for other research than biological and clinical applications such as the investigation of cultural heritage and in particular old paintings. The implications of this research line concerning art authentication in a forensic context will be outlined.

Apolipoprotein E4 (ApoE4) is the strongest risk gene for late-onset Alzheimer’s disease. Growing clinical evidence revealed that dysfunction of systematic metabolism in the brain occurs even twenty years before the onset of evident AD pathological features [1]. Therefore, a better understanding of ApoE4-related pathophysiological mechanisms early and before the onset of Alzheimer’s disease is essential for drug development. Metabolomics is a widely used tool for researching neurodegenerative disease’s related metabolism alteration. However, screening the whole profile of metabolites remains challenging due to the various classes of metabolites that might need different extraction and analysis methodologies[2].

The aim of this study is to investigate the potential mechanism of the risk gene ApoE4 in H4 neuroglioma cells. Metabolomics of ApoE4-carried and wild-type H4 cells was performed by applying a novel workflow composed of OrbiSIMS as a screening tool, followed by targeted LC-MS metabolomics for further confirming polar molecules. Proteins affected by ApoE4 were identified by performing LC-MS-based proteomics.

The data obtained using OrbiSIMS allowed a non-biased overview of metabolic alteration under ApoE4-carried cells. In total, 192 putatively annotated metabolites were detected in our study. PLS-DA (Partial least squares discriminant analysis) was used to identify differential metabolites between two groups. Significant features were selected for pathway and enrichment analysis by filtering with VIP (variable importance for projection) >1 plus FDR (false discovery rate) adjusted p-value < 0.05. Pathway enrichment analysis showed that glycerophospholipid metabolism was inhibited by ApoE4. The alanine, aspartate, and glutamate metabolism was also found to be affected by ApoE4-mediated metabolism disruption. To validate this, we applied polar-targeted metabolomics of LC-MS to exploit these polar compounds, which revealed that the metabolism of taurine and hypotaurine might also be involved in the ApoE4 risk mechanism.

Aside from the metabolomics application of the OrbiSIMS analysis, the chemical filtering (SIMS-MFP) approach [3] allowed us to filter out peptide-related peaks from the OrbiSIMS dataset based on elemental composition. An analysis of the resulting peptide data-sets indicated modification of proteins involved in ApoE4. These suggested differences were then confirmed via proteomics analysis that suggests the nitrogen compound metabolic process, RNA splicing process and translation have been associated with ApoE4-related AD development.

Finally, our metabolomics results by using OrbiSIMS as a screening tool have elucidated the glycerophospholipid dysfunction of H4 neuroglioma cells in the presence of ApoE4, discovering two new potential amino acid pathways that may be involved in Alzheimer’s disease. In addition, SIMS-MFP-aided chemical filtering on the OrbiSIMS dataset and proteomics analysis found the dysfunction of nitrogen compound metabolism and RNA splicing process involved in the risk effect of ApoE4 on Alzheimer’s disease pathology. It suggests that the early monitoring or interference of these molecular functions associated with ApoE4 will help us promote the development of Alzheimer’s disease drugs and prevent the progression of Alzheimer’s disease.

References

1. Frontiers in Cell and Developmental Biology 2021, 9, doi:10.3389/fcell.2021.602887.

2. Nature Methods 2021, 18, 747-756, doi:10.1038/s41592-021-01197-1.

3. Analytical Chemistry 2022, 94, 4703-4711, doi:10.1021/acs.analchem.1c04898.

The viability and adaptability of plants, e.g. to salt stress, relies on the spatial distribution of ions in the liquid medium of the different compartments in the roots, stems, flowers, and leaves. Salinity stress is a major constraint on global plant growth and productivity, impacting various crop plant species, but also roses. According to R. Munns et al. cell exclusion and tolerance of phytotoxic Na⁺ and Cl^- ions are critical to tolerance.[1] Unfortunately, until now spatially highly resolved analysis of ion distribution in hydrated, in situ preserved plant tissue has been challenging using conventional methods.[2] SIMS could bridge the gap, although it needs to address challenges, like vacuum stabilization for high water-content samples.[3]

Although wild roses are not the focus of traditional economic interest, they can hold important ecological and cultural values. In recent decades, Rosa rugosa has displaced the endemic R. spinosissima on the European North Sea coasts of the mainland. Botanists V. Wissemann and A. Kellner suspected the increased site adaptation of R. rugosa due to a stronger tolerance to the salty aerosols of the nearby seawater behind this prime example of man-made fauna biodiversity loss. In classical experiments using gross analytical methods, such as atomic absorption spectrometry of a solution from ashy leaves, they observed reduced accumulation of Na⁺ in leaf tissue of R. rugosa.[4] However such approaches cannot provide sufficient required molecular clues to the different tolerance mechanisms due to their lack of spatial resolution.

In this context, we demonstrated the application potential of SIMS in contributing to the existing knowledge of salinity stress. The complementary combination of mass spectrometry imaging (MSI) and depth profiling, as well as 3D reconstructions provide new insights regarding the different salt tolerance, which only became possible due to the high lateral resolving power. Since SIMS is a high vacuum technique, the high water content and the hydrophobic properties of the leaf cuticle make the sample preparation quite challenging. More over, the very mobile saline ions have to be kept and fixed at their original place. To maintain the leaves in a nearly native state, we employed frozen-hydrated leaf samples from two distinct salt-tolerant rose species, namely R. rugosa and R. spinosissima. These samples were carefully examined following cultivation with artificial sea salt spray solutions.

Both the depth profiles and the cross-sectional ion images qualitatively revealed the lower enrichment of sodium and chloride ions in leaf tissue. Still the cross sectional MSI approach was better suited in delivering spatial localization information. Our MSI approach demonstrated for the first time that R. rugosa exhibits a mechanism that effectively excludes phytotoxic Na⁺ ions from the mesophyll, being essential for fitness. Our findings offer valuable starting points for targeted genomic experiments.

This presentation summarizes our optimized preparational set-up, measurement techniques, and the insights obtained from studying salt tolerance mechanisms in R. rugosa compared to R. spinosissima using SIMS. We also provide valuable insights into common pitfalls and workarounds when employing SIMS in plant physiology research.

Metabolite mass spectrometry imaging has become a valuable tool for localization of plant primary and secondary metabolites within a tissue section. Using Matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS) imaging, the lateral distribution of various compounds in tomato tissues was determined during development and the change in metabolites due to genetic modifications examined. The lateral resolution of commercially available MALDI-MS imaging instruments of at best 10 µm, allows metabolites to be assigned to specific tissues, such as seed, embryo or fruit skin, but not on a (sub)cellular level. In order to overcome this limitation and better understand processes like production, storage, and transport of secondary metabolites in specific cell types an approach employing secondary ion mass spectrometry (SIMS) using an Orbitrap^TM analyzer was evaluated.

SIMS imaging was performed using a recently developed Hybrid SIMS instrument (IONTOF GmbH), which allows high mass resolution imaging of metabolites and other biological molecules at µm lateral resolution by employing an Orbitrap detector (Q Exactive HF, Thermo-Fisher Scientific) and 20 keV Ar gas clusers. The TOF-SIMS part of the instrument can be operated using Bi-clusters, allowing even sub-µm lateral resolution, but usually accompanied by intense molecule fragmentation.

Here we describe the Orbitrap-SIMS analysis of tomato secondary metabolites, like steroidal glycoalkaloids or flavonoids, inorganic ions, and lipids/fatty acids. Using the Argon gas cluster ion beam in combination with the Orbitrap mass analyzer high mass resolution images were acquired, while TOF-SIMS mode with the Bi- ion beam was used to achieve sub-µm lateral resolution at the moderate mass resolution of the TOF analyzer.

We detected and annotated 10s of compounds/ions in both positive and negative ionization mode, including inorganic ions, lipids, fatty acids, primary metabolites and secondary metabolites at single cell resolution.

Furthermore, we explored the possibility to identify characteristic fragment ions of secondary metabolites directly from the Orbitrap-SIMS imaging run. In contrast to MALDI that does not cause metabolite fragmentation, SIMS using the Bi ion beam leads to strong fragmentation, while using the Argon gas cluster ion beam allows the parallel detection of molecular ions, adducts and characteristic fragments. We analyzed the obtained images using correlation analysis of ion distributions and manual identification of co-localized masses as fragments of steroidal glycoalkaloid molecular ions. Thereby we were able to distinguish between differentially localized molecular ions and assign their characteristic fragments accordingly. This allowed the putative metabolite identification directly from imaging data without performing MS/MS analysis or complementary analysis methods, like LC/MS for compound assignment.

We present here mass spectrometry imaging of plant metabolites using Orbitrap-SIMS at (sub)cellular resolution with high mass resolution & metabolite identification partially using inherent fragmentation.