Atomistic simulations for investigation of substrate and salt effects on lipid in-source fragmentation in secondary ion mass spectrometry: A follow-up study.

In-source fragmentation (ISF) poses a significant challenge in secondary ion mass spectrometry (SIMS). These fragment ions increase the spectral complexity and can lead to incorrect annotation of fragments as intact species. The presence of salt that is ubiquitous in biological samples can influence the fragmentation and ionization of analytes in a significant manner, but their influences on SIMS have not been well characterized. To elucidate the effect of substrates and salt on ISF in SIMS, we have employed experimental SIMS in combination with atomistic simulations of a sphingolipid on a gold surface with various NaCl concentrations as a model system. Our results revealed that a combination of bond dissociation energy and binding energy between N-palmitoyl-sphingomyelin and a gold surface is a good predictor of fragment ion intensities in the absence of salt. However, ion-fragment interactions play a significant role in determining fragment yields in the presence of salt. Additionally, the charge distribution on fragment species may be a major contributor to the varying effects of salt on fragmentation. This study demonstrates that atomistic modeling can help predict ionization potential when salts are present, providing insights for more accurate interpretations of complex biological spectra.

Mass spectrometry imaging of metals in tissues and cells: Methods and biological applications.

BACKGROUND: Metals are pervasive throughout biological processes, where they play essential structural and catalytic roles. Metals can also exhibit deleterious effects on human health. Powerful analytical techniques, such as mass spectrometry imaging (MSI), are required to map metals due to their low concentrations within biological tissue. SCOPE OF REVIEW: This Mini Review focuses on key MSI technology that can image metal distributions in situ, describing considerations for each technique (e.g., resolution, sensitivity, etc.). We highlight recent work using MSI for mapping trace metals in tissues, detecting metal-based drugs, and simultaneously imaging metals and biomolecules. MAJOR CONCLUSIONS: MSI has enabled significant advances in locating bioactive metals at high spatial resolution and correlating their distributions with that of biomolecules. The use of metal-based immunochemistry has enabled simultaneous high-throughput protein and biomolecule imaging. GENERAL SIGNIFICANCE: The techniques and examples described herein can be applied to many biological questions concerning the important biological roles of metals, metal toxicity, and localization of metal-based drugs.

Applying Multimodal Mass Spectrometry to Image Tumors Undergoing Ferroptosis Following In Vivo Treatment with a Ferroptosis Inducer.

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. One region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.

Depth Correction of 3D NanoSIMS Images Shows Intracellular Lipid and Cholesterol Distributions while Capturing the Effects of Differential Sputter Rate.

Knowledge of the distributions of drugs, metabolites, and drug carriers within cells is a prerequisite for the development of effective disease treatments. Intracellular component distribution may be imaged with high sensitivity and spatial resolution by using a NanoSIMS in the depth profiling mode. Depth correction strategies that capture the effects of differential sputtering without requiring additional measurements could enable producing accurate 3D NanoSIMS depth profiling images of intracellular component distributions. Here we describe an approach for depth correcting 3D NanoSIMS depth profiling images of cells that accounts for differential sputter rates. Our approach uses the secondary ion and secondary electron depth profiling images to reconstruct the cell's morphology at every raster plane. These cell morphology reconstructions are used to adjust the z-positions and heights of the voxels in the component-specific 3D NanoSIMS images. We validated this strategy using AFM topography data and reconstructions created from depth profiling images acquired with focused ion beam-secondary electron microscopy. Good agreement was found for the shapes and relative heights of the reconstructed morphologies. Application of this depth correction strategy to 3D NanoSIMS depth profiling images of a metabolically labeled cell better resolved the transport vesicles, organelles, and organellar membranes containing 18O-cholesterol and 15N-sphingolipids. Accurate 3D NanoSIMS images of intracellular component distributions may now be produced without requiring correlated analyses with separate instruments or the assumption of a constant sputter rate. This will allow visualization of the subcellular distributions of lipids, metabolites, drugs, and nanoparticles in 3D, information pivotal to understanding and treating disease.

Depth correction of 3D NanoSIMS images using secondary electron pixel intensities.

Strategies that do not require additional characterization to be performed on the sample or the collection of additional secondary ion signals are needed to depth correct 3D SIMS images of cells. Here, we develop a depth correction strategy that uses the pixel intensities in the secondary electron images acquired during negative-ion NanoSIMS depth profiling to reconstruct the sample morphology. This morphology reconstruction was then used to depth correct the 3D SIMS images that show the components of interest in the sample. As a proof of concept, we applied this approach to NanoSIMS depth profiling data that show the 15N-enrichment and 18O-enrichment from 15N-sphingolipids and 18O-cholesterol, respectively, within a metabolically labeled Madin-Darby canine kidney cell. Comparison of the cell morphology reconstruction to the secondary electron images collected with the NanoSIMS revealed that the assumption of a constant sputter rate produced small inaccuracies in sample morphology after approximately 0.66 µm of material was sputtered from the cell. Nonetheless, the resulting 3D renderings of the lipid-specific isotope enrichments better matched the shapes and positions of the subcellular compartments that contained 15N-sphingolipids and 18O-cholesterol than the uncorrected 3D SIMS images. This depth correction of the 3D SIMS images also facilitated the detection of spherical cholesterol-rich compartments that were surrounded by membranes containing cholesterol and sphingolipids. Thus, we expect this approach will facilitate identifying the subcellular structures that are enriched with biomolecules of interest in 3D SIMS images while eliminating the need for correlated analyses or additional secondary ion signals for the depth correction of 3D NanoSIMS images.

Development of an inexpensive Raman-compatible substrate for the construction of a microarray screening platform.

Biomaterial microarrays are being developed to facilitate identifying the extrinsic cues that elicit stem cell fate decisions to self-renew, differentiate and remain quiescent. Raman microspectroscopy, often combined with multivariate analysis techniques such as partial least square-discriminant analysis (PLS-DA), could enable the non-invasive identification of stem cell fate decisions made in response to extrinsic cues presented at specific locations on these microarrays. Because existing biomaterial microarrays are not compatible with Raman microspectroscopy, here, we develop an inexpensive substrate that is compatible with both single-cell Raman spectroscopy and the chemistries that are often used for biomaterial microarray fabrication. Standard deposition techniques were used to fabricate a custom Raman-compatible substrate that supports microarray construction. We validated that spectra from living cells on functionalized polyacrylamide (PA) gels attached to the custom Raman-compatible substrate are comparable to spectra acquired from a more expensive commercially available substrate. We also showed that the spectra acquired from individual living cells on functionalized PA gels attached to our custom substrates were of sufficient quality to enable accurate identification of cell phenotypes using PLS-DA models of the cell spectra. We demonstrated this by using cells from laboratory lines (CHO and transfected CHO cells) as well as adult stem cells that were freshly isolated from mice (long-term and short-term hematopoietic stem cells). The custom Raman-compatible substrate reported herein may be used as an inexpensive substrate for constructing biomaterial microarrays that enable the use of Raman microspectroscopy to non-invasively identify the fate decisions of stem cells in response to extrinsic cues.

Measurement of Absolute Concentration at the Subcellular Scale.

The concentration of a pharmaceutical drug or bioactive metabolite within the target organelle influences the effects elicited by the drug or metabolite. Although the relative concentrations of many compounds of interest within subcellular compartments have been measured, measurements of absolute concentrations in the organelle remain elusive. In this Perspective, we discuss a significant advance in using nano secondary ion mass spectrometry (nanoSIMS) to measure the absolute concentration of a 13C-labeled metabolite within secretory vesicles, as reported by Thomen et al. in the April issue of ACS Nano.

High-Resolution Secondary Ion Mass Spectrometry Analysis of Cell Membranes.

This Feature describes the use a Cameca NanoSIMS instrument for directly imaging specific lipid and protein species in the plasma membranes of mammalian cells with approximately 100 nm-lateral resolution and discusses how these analyses have already begun to transform fundamental concepts in the field of membrane biology. Secondary ion generation is discussed with emphasis on the constraints that affect the detection and identification of membrane components, and then the sample preparation methodologies and data analysis strategies that address these constraints are described.