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Detection of iron at the subcellular level in order to gain insights into its transport, storage, and therapeutic prospects to prevent cytotoxic effects of excessive iron accumulation is still a challenge. Nanoscale magnetic sector secondary ion mass spectrometry (SIMS) is an excellent candidate for subcellular mapping of elements in cells since it provides high secondary ion collection efficiency and transmission, coupled with high-lateral-resolution capabilities enabled by nanoscale primary ion beams. In this study, we developed correlative methodologies that implement SIMS high-resolution imaging technologies to study accumulation and determine subcellular localization of iron in alveolar macrophages. We employed transmission electron microscopy (TEM) and backscattered electron (BSE) microscopy to obtain structural information and high-resolution analytical tools, NanoSIMS and helium ion microscopy-SIMS (HIM-SIMS) to trace the chemical signature of iron. Chemical information from NanoSIMS was correlated with TEM data, while high-spatial-resolution ion maps from HIM-SIMS analysis were correlated with BSE structural information of the cell. NanoSIMS revealed that iron is accumulating within mitochondria, and both NanoSIMS and HIM-SIMS showed accumulation of iron in electrolucent compartments such as vacuoles, lysosomes, and lipid droplets. This study provides insights into iron metabolism at the subcellular level and has future potential in finding therapeutics to reduce the cytotoxic effects of excessive iron loading.

Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). In this study the effect of heating was examined on a set of 64 small molecule standards and, separately, on human plasma metabolite extracts. The samples, either derivatized or underivatized, were heated at three different temperatures (60, 100, and 250 °C) at different exposure times (30 s, 60 s, and 300 s). All the samples were analyzed by liquid chromatography coupled to electrospray ionization mass spectrometry (LC/MS) and the data processed by XCMS Online ( xcmsonline.scripps.edu ). The results showed that heating at an elevated temperature of 100 °C had an appreciable effect on both the underivatized and derivatized molecules, and heating at 250 °C created substantial changes in the profile. For example, over 40% of the molecular peaks were altered in the plasma metabolite analysis after heating (250 °C, 300s) with a significant formation of degradation and transformation products. The analysis of 64 small molecule standards validated the temperature-induced changes observed on the plasma metabolites, where most of the small molecules degraded at elevated temperatures even after minimal exposure times (30 s). For example, tri- and diorganophosphates (e.g., adenosine triphosphate and adenosine diphosphate) were readily degraded into a mono-organophosphate (e.g., adenosine monophosphate) during heating. Nucleosides and nucleotides (e.g., inosine and inosine monophosphate) were also found to be transformed into purine derivatives (e.g., hypoxanthine). A newly formed transformation product, oleoyl ethyl amide, was identified in both the underivatized and derivatized forms of the plasma extracts and small molecule standard mixture, and was likely generated from oleic acid. Overall these analyses show that small molecules and metabolites undergo significant time-sensitive alterations when exposed to elevated temperatures, especially those conditions that mimic sample preparation and analysis in GC/MS experiments.

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. As a result of this unique integration, we can analyze large profiling datasets and simultaneously obtain structural identifications. Validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometry data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.

An in situ freeze fracture device featuring a spring-loaded trap system has been designed and characterized for time of flight secondary ion mass spectrometry (TOF SIMS) analysis of single cells. The device employs the sandwich assembly, which is typically used in freeze fracture TOF SIMS experiments to prepare frozen, hydrated cells for high-resolution SIMS imaging. The addition of the spring-loaded trap system to the sandwich assembly offers two advances to this sample preparation method. First, mechanizing the fracture by adding a spring standardizes each fracture by removing the need to manually remove the top of the sandwich assembly with a cryogenically cooled knife. A second advance is brought about because the top of the sandwich is not discarded after the sandwich assembly has been fractured. This results in two imaging surfaces effectively doubling the sample size and providing the unique ability to image both sections of a cell bifurcated by the fracture. Here, we report TOF SIMS analysis of freeze fractured rat pheochromocytoma (PC12) cells using a Bi cluster ion source. This work exhibits the ability to obtain single cell chemical images with subcellular lateral resolution from cells preserved in an ice matrix. In addition to preserving the cells, the signal from lipid fragment ions rarely identified in single cells are better observed in the freeze-fractured samples for these experiments. Furthermore, using the accepted argument that K(+) signal indicates a cell that has been fractured though the cytoplasm, we have also identified different fracture planes of cells over the surface. Coupling a mechanized freeze fracture device to high-resolution cluster SIMS imaging will provide the sensitivity and resolution as well as the number of trials required to carry out biologically relevant SIMS experiments.

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) can be utilized to map the distribution of various molecules on a surface with submicrometer resolution. Much of its biological application has been in the study of membrane lipids, such as phospholipids and cholesterol. Cholesterol is a particularly interesting molecule due to its involvement in numerous biological processes. For many studies, the effectiveness of chemical mapping is limited by low signal intensity from various biomolecules. Because of the high energy nature of the SIMS ionization process, many molecules are identified by detection of characteristic fragments. Commonly, fragments of a molecule are identified using standard samples, and those fragments are used to map the location of the molecule. In this work, MS/MS data obtained from a prototype C60(+)/quadrupole time-of-flight mass spectrometer was used in conjunction with indium LMIG imaging to map previously unrecognized cholesterol fragments in single cells. A model system of J774 macrophages doped with cholesterol was used to show that these fragments are derived from cholesterol in cell imaging experiments. Examination of relative quantification experiments reveals that m/z 147 is the most specific diagnostic fragment and offers a 3-fold signal enhancement. These findings greatly increase the prospects for cholesterol mapping experiments in biological samples, particularly with single cell experiments. In addition, these findings demonstrate the wealth of information that is hidden in the traditional TOF-SIMS spectrum.

Mass spectrometric imaging is a powerful tool to interrogate biological complexity. One such technique, time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging, has been successfully utilized for subcellular imaging of cell membrane components. In order for this technique to provide insight into biological processes, it is critical to characterize the figures of merit. Because a SIMS instrument counts individual events, the precision of the measurement is controlled by counting statistics. As the analysis area decreases, the number of molecules available for analysis diminishes. This becomes critical when imaging subcellular features; it limits the information obtainable, resulting in images with only a few counts of interest per pixel. Many features observed in low intensity images are artifacts of counting statistics, making validation of these features crucial to arriving at accurate conclusions. With TOF-SIMS imaging, the experimentally attainable spatial resolution is a function of the molecule of interest, sample matrix, concentration, primary ion, instrument transmission, and spot size of the primary ion beam. A model, based on Poisson statistics, has been developed to validate SIMS imaging data when signal is limited. This model can be used to estimate the effective spatial resolution and limits of detection prior to analysis, making it a powerful tool for tailoring future investigations. In addition, the model allows comparison of pixel-to-pixel intensity and can be used to validate the significance of observed image features. The implications and capabilities of the model are demonstrated by imaging the cell membrane of resting RBL-2H3 mast cells.