Paola
Agüi-Gonzalez
ab,
Sebastian
Jähne
ab and
Nhu T. N.
Phan
*ab
aCenter for Biostructural Imaging of Neurodegeneration, University Medical Center Göttingen, von-Siebold-Straße 3a, 37075 Göttingen, Germany. E-mail: thi.phan@med.uni-goettingen.de
bDepartment of Neuro- and Sensory Physiology, University Medical Center Göttingen, Humboldtallee 23, 37073 Göttingen, Germany
First published on 9th May 2019
Secondary ion mass spectrometry (SIMS) has been increasingly recognized as a powerful technique for visualizing molecular architectures in the fields of neurobiology and cell biology. There are two main platforms of SIMS, namely ToF-SIMS and nanoscale SIMS (nanoSIMS), which are capable of imaging different types of biomolecules with resolution at the single cell and organelle level, respectively. In this review, we focus on the fundamental aspects of SIMS, as well as on the current ongoing instrumental developments of this technology. Selective applications of SIMS in neurobiological and cell biological research are provided to demonstrate its strengths, limitations, and future potential in the field. We add several examples of correlative imaging techniques that combine SIMS with other technologies, while highlighting the current trend for comprehensive and specific bio-imaging.
Given the high complexity and heterogeneity of the cells in the brain, spatial information on the molecular organization is essential for the understanding of and insights into cellular processes. A particular cellular mechanism or a disease is not caused by a simple change of a single molecule, but most likely is the result of a complex interaction of various key biomolecules such as lipids, proteins, peptides, and metabolites. SIMS provides advantages in that multiple molecules can be analyzed with high throughput to obtain comprehensive data of the molecular composition and distribution inside cells and organs, often with subcellular or organelle level spatial resolution, and therefore it is an excellent approach for the study of brain and cell biology.
In this review, we provide a fundamental overview of SIMS and updates on recent technological advances in this field. We also introduce the relevant applications of SIMS in neurological and cell biological research, particularly for single cell imaging, three-dimensional imaging, pharmaceuticals, and neurodegenerative diseases and pathology. In addition, correlative imaging approaches combining SIMS and other optical and non-optical imaging modalities will be presented as the current trends in mass spectrometry imaging in an effort to obtain a comprehensive understanding of complex biological questions.
To obtain an ion image, the focused primary ion beam scans the sample surface spot by spot or pixel by pixel. A mass spectrum is then obtained for each pixel. By recording the positions of the beam while scanning, a color map of the signal intensity for each ion can be constructed across the scanned area, providing a so-called ion image. These ion images show the distribution of the ions on the surface. In addition, a three dimensional (3D) reconstruction from a series of consecutive two dimensional (2D) ion images can be performed allowing the visualization of the molecular distribution underneath the sample surface. Alternatively, depth profiling is the method of choice to observe the molecular compositional change across the sample depth. The depth resolution in SIMS is typically in a range of 1–10 nm.1
Second, the sensitivity for the molecules of interest depends on several factors, particularly the abundance of the molecules in the analyzed volume and their ionization probability (typically lower than ∼10−4).11 This is a critical element especially for biological imaging at subcellular resolution, where the amount of analytes can become too low for detection. In this case, gaining better spatial resolution is a compromise with limit of detection. In addition, the properties of the target analyte and its chemical and morphological environment also heavily affect the sensitivity. The limit of detection obtained by SIMS is in the range of parts per million (ppm) to parts per billion (ppb).12
Lastly, the success of SIMS analysis is also heavily dependent on the sample preparation. It is essential to preserve the native states of the biological samples in order to obtain reliable information about the spatial distribution of the biomolecules. The common sample preparation methods for SIMS imaging are typically called frozen-hydrated, freeze-dried, and chemical fixation.13,14 Freeze-drying is the most widely used method due to its simplicity; however, there is a risk of molecular rearrangement of the subcellular structure. The samples are plunged into liquid nitrogen (77 K) or liquid propane (85 K) quickly to avoid the formation of ice crystals which may cause ultrastructural damage. The samples are then inserted into a high vacuum (∼10−5 Torr) where water is sublimed slowly to prevent molecular rearrangement. Frozen-hydrated sample preparation provides the safest method for the preservation of the morphology and localization of the cellular components. However, a more laborious and complicated instrumental setup at near liquid nitrogen temperature is needed and there is a high risk of ice condensation on the sample surface which can restrict its applications in biology. On the other hand, chemical fixation and embedding in resin is routinely used, especially for nanoSIMS. Glutaraldehyde is the gold standard for protein fixation while osmium tetroxide is common for lipids.15 It should be noted that the addition of fixative chemicals might introduce artifacts in the analysis due to the fact that the fixation involves chemical modification of the sample constituents. The selection of suitable fixatives should therefore be considered carefully. Other less common methods, namely freeze-fracture, etching, and trehalose vitrification have also been proposed in the literature.2,13,14
Another SIMS platform, nanoSIMS, employs a magnetic sector mass analyzer and a high energy and highly focussed ion beam. In the magnetic sector, the secondary ions travel in a circular path under the influence of a magnetic field. The radius of the path is different based on the m/z of the ions (Fig. 1C). By varying the magnetic field, the detectable mass range, although narrow, can be adjusted. High mass resolution of about 10000 can be obtained.19 NanoSIMS typically allows parallel detection of up to 7 different secondary ions, although more secondary ions can be detected using magnetic switching. The most significant feature of nanoSIMS is the coaxial configuration between the primary and secondary ion beams (Fig. 1C), which improves the focus of the primary ion beam, decreases aberrations, and increases the transmission efficiency of secondary ions (∼80%).20 In addition, the instrument can be equipped with both O− and Cs+ primary ion beams which are highly focused and energetic, so both positive and negative ions can be imaged. A spatial resolution of ∼50 nm can be achieved;21 however, to obtain sufficient signals of the secondary ions from biological samples (e.g. lipids), a lateral resolution of ∼100 nm is more commonly used.15 On the other hand, owing to the intense fragmentation that occurs, only elements and small ions are observed in nanoSIMS from the larger parent molecules. The technique is suitable for the analysis of the chemical organization of the entire sample (such as 31P, 32S, 12C14N, etc.). To study specific target biomolecules, labeling the biomolecules of interest with less abundant isotopic compounds is needed. A technique, known as multi-isotope imaging mass spectrometry (MIMS), was first applied by the Lechene group to track the protein turnover in cells and tissues.12
Other noticeable configurations have been developed and applied in biological SIMS such as Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR)-SIMS which offers an outstanding mass resolution (m/Δm 67500 at m/z 750),22 and hybrid quadrupole orthogonal ToF for matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI) combined with SIMS (QSTAR XL-QqTOF) which allows the detection of very large molecules up to m/z 40000.23 However, the spatial resolution is sufficient for only tissue imaging, perhaps not for cellular imaging.
Fig. 2 Examples of recent developments in SIMS. (A and B) Parallel imaging tandem MS (MS1, MS2) on a TRIFT nanoTOF. (A) Schematic of a TRIFT nanoTOF. (B) An example of MS1 and MS2 imaging of a fatty acid (16:0) at m/z 255 in a zebra finch brain section using a TRIFT nanoTOF. Reproduced from ref. 25 with permission. (C and D). 3D Orbi-SIMS for MSn imaging with high speed and high mass resolution. (C) Schematic of 3D OrbiSIMS. (D) Molecular maps of neurotransmitters GABA, dopamine, and serotonin in the cornu ammonis region of mouse hippocampus obtained by 3D OrbiSIMS. Reproduced from ref. 27 with permission. (E and F) Laser-SNMS postionization for improving the secondary ion yield. (E) Schematic of a laser-SNMS. (F) Mass spectra of a guanine surface analyzed with a 20 keV C60+ (left) and Arn+ GCIB (right), with and without laser-SNMS postionization (first and second row, respectively). Laser-SNMS clearly increases the intensity of the detected ions. Reproduced from ref. 29 with permission. |
Another new development in this field is 3D Orbi-SIMS which couples a ToF and Orbitrap mass analyzer (Fig. 2C). This configuration combines the best features of both analyzers, particularly the high speed of analysis, high spatial resolution of a ToF analyzer (∼2 μm for biomolecules), and high mass-resolving power of an Orbitrap (>240000 at m/z 200).27 Orbi-SIMS was employed to map the distribution of the neurotransmitters GABA, dopamine, and serotonin (Fig. 2D) in the cornu ammonis region of mouse hippocampus. Additionally, 29 sulfoglycosphingolipids and 45 glycerolphospholipids in different layers of the hippocampus were imaged and identified by tandem SIMS. In addition, the metabolic profile of single rat alveolar macrophages treated with the drug amiodarone was examined. The exponential increase in the abundance of cholesterol and several phospholipids was found to be related to the accumulation of the drug.27
As discussed above, the use of a GCIB in SIMS offers an advantage of reducing fragmentation during the ionization; however, this is accompanied by a decrease of the secondary ion yield. Laser secondary neutral mass spectrometry (Laser-SNMS) has been developed as an effective postionization approach to increase the secondary ion production (Fig. 2E).28 The technique applies a laser beam just before the extraction lens to ionize the neutral species which are co-sputtered with the secondary ions from the sample surface. To adjust the degree of fragmentation and the energy of the sputtered neutral species, the laser power density and the laser pulse delay time can be adjusted. A guanine surface was analyzed with both a 20 keV C60+ and Arn+ GCIB with and without laser-SNMS postionization (Fig. 2F) and the postionization efficiency was even higher when accompanied by a GCIB primary ion source.29,30
Recently, the correlation of the molecular distribution obtained by SIMS imaging and the cellular structures or the localization of specific proteins has been investigated. A main drawback of SIMS is the difficulty in the identification of cellular organelles and protein localization. Several labeling tags for specific proteins utilizing heavy metals such as lanthanides31 and colloidal gold conjugated to antibodies32 have been developed with the goal of imaging specific proteins with SIMS. However, these tags exhibit several disadvantages, especially that their large size causes low labeling precision. Targeted imaging of specific cellular proteins by nanoSIMS has been demonstrated using newly developed labeling probes containing fluorine33 and boron.34 For example, boron probes were used to label proteins of interest which then could be visualized by both nanoSIMS and fluorescence microscopy. Successful imaging of the synaptic protein syntaxin 1 and mitochondrial marker TOM-70 in mammalian cells was carried out. The probes were shown to be well suited for imaging of target proteins with subcellular resolution due to their high selectivity, high sensitivity of detection, and high spatial precision of labeling. In addition, they could be applied for different proteins using different labeling methods. The probes could also be applied for cluster SIMS, allowing the study of lipid–protein domains and their functional relations.
One of the first significant applications of SIMS in single cell imaging was the imaging of mating Tetrahymena thermophila to visualize the distribution of membrane lipids.35 During mating, the membranes of two complementary Tetrahymena cells form a fusion pore allowing the transportation of micronuclei between the cells. It was found that low curvature lipids, such as phosphatidylcholine (PC), decreased significantly, whereas high curvature lipids, such as 2-amino ethylphosphonolipids, were dominant at the fusion site. Based on the study, it is implied that the heterogeneous distribution of membrane lipids could play a key role in regulating membrane fusion for cellular processes.
A more recent example was the imaging and characterization of membrane lipids of single neurons in the sea slug Aplysia californica using TOF-SIMS and a 20 keV C60+ primary ion gun.36 The major lipid species of the neuronal membrane including PC (16:0e/18:1), vitamin E, and cholesterol were detected and their molecular structures were identified by tandem MS directly on the sample surface. The localization of vitamin E was found to be highly correlated with the pigment carotenoids. Vitamin E was also previously detected by SIMS on Aplysia neurons.37 This could imply the biological function of vitamin E in neuronal activity.
Silver nanoparticles (Ag NPs) have been widely used for therapeutics and biomedical purposes; however, their cytotoxicity is not fully known.38 The effects of Ag NPs on the lipid composition of macrophage cells were investigated by ToF-SIMS.39 To increase the sensitivity towards biomolecules, matrix enhanced SIMS is a method in which a matrix 2,5-dihydroxybenzoic acid was deposited on top of the sample surface before freeze drying. It was found that cells exposed to Ag NPs exhibit a significant change in the lipid composition at the cell surface; specifically there was a significant increase in the abundance of monoacylglycerols (MAGs), diacylglycerols (DAGs), and cholesterol. The change was more dramatic as the concentration of Ag NPs was elevated (Fig. 3A). In addition, cholesterol and DAGs were shown to migrate to the surroundings of the cells which indicated cell death.
Fig. 3 Examples of applications of SIMS in neurobiology and cell biology. (A) ToF-SIMS imaging of macrophage cells without (top) and with Ag NP treatment (bottom). From left to right: SIMS images of total ions, cholesterol (C27H45) at m/z 369.38, a fragment of DAG (C39H71O4) at m/z 603.52, the overlay of cholesterol and the DAG fragment, and a score plot of principle component analysis showing good separation between the cell group exposed to a high level of Ag NPs (500–2000 ng mL−1) and those exposed to no or low amount of Ag NPs (>50 ng mL−1). Cholesterol and DAGs were shown to migrate to the surroundings of the cells when exposed to Ag NPs. Reproduced from ref. 39 with permission. (B) SIM and nanoSIMS imaging of tumor tissue of mice pretreated with a Pt drug containing nanocarriers for cancer treatment. Left: SIM and nanoSIMS images showing the localization of the drug in tumor tissue; the nanoSIMS image of 31P and 195Pt (top row), overlay of the SIM fluorescent image of actin filaments (green), DAPI (blue), and the nanocarrier via Cy5.5 dye (red) and the nanoSIMS ratio image of 15N/14N in hue saturation intensity (HSI) showing the enriched area of the nanocarrier in tissue (bottom row). Right: Schematic of the nanocarrier assembly which contains a polymer structure of oxaliplatin drug, 15N label and Cy5.5 fluorescent label of the nanocarrier, and MMP substrate peptide. Reproduced from ref. 50 with permission. (C) ToF-SIMS imaging of drosophila brain treated with cocaine and methylphenidate to study the lipid structural effects of the drug on brain chemistry. Left: SIMS images of PC (34:1) at m/z 760.58 in control and cocaine treated brain. Right: Relative quantification of lipid change in the fly brains under cocaine and methylphenidate treatments. It is shown that both the abundance and localization of the lipids in the brain significantly changed by drug exposure; however, the change is opposite in cocaine and methylphenidate treatments. Reproduced from ref. 59 with permission. |
One of the first demonstrations was the 3D imaging of single HeLa cells using the J105 SIMS instrument with a 40 keV C60+ beam.40 Frozen hydrated cells were used in order to preserve the intact molecular structure of the cells. Signature ions such as the PC headgroup m/z 184 and DNA base adenine m/z 136 were detected and used to generate a 3D image. Subcellular features were observed, particularly the nucleus and endoplasmic reticulum. A similar instrumental approach was used to visualize the 3D distribution of TiO2 NPs inside single Tetrahymena cells.41 The study showed that TiO2 NPs were incorporated into the cells via the "mouth" of the cells and mainly accumulated in the food vacuoles. In another study, to investigate the organization and interaction between cholesterol and sphingolipids on membrane and subcellular compartments, Yeager et al.42 showed the 3D localization of these lipids in single Madin-Darby canine kidney cells using nanoSIMS and an 8 keV Cs+ gun. The cells were labelled with 18O-cholesterol and 15N-sphingolipids, fixed with glutaraldehyde and osmium tetroxide, and coated with an iridium layer before imaging with transmission electron microscopy (TEM) and nanoSIMS. The TEM imaging helps to visualize the morphology of the cells. The 3D images clearly showed distinguished enriched intracellular regions of cholesterol and sphingolipids, particularly 18O-cholesterol was concentrated in the tubular projections along the analysis depth, whereas 15N-sphingolipids were localized in small pockets which were not overlapping with the 18O-cholesterol area.
Although emerging as an attractive imaging modality, several existing challenges in 3D imaging restrict its widespread applications in the biological field. The main challenge is the accurate reconstruction of 2D images into a 3D image. This occurs in the data treatment step which originally does not account for the topography and matrix effects existing in the samples, and the uneven ionization of biological and organic materials and inorganic or metallic substrates. As a result, a distortion is observed in the generated 3D image, especially near the samples/substrate interface. Data reshaping is necessary in order to include all these factors. Different reshaping methods have been applied based on the recognition of the sample/substrate interface43 or the correlation of the sample with topographical information, which can be measured before and in parallel with SIMS imaging.44 However, the experimental setup for the correlative imaging also presents difficulty and complication. In addition, challenges in handling very huge data for the treatment of 3D MS data and long experimental time for high resolution imaging are common and typical in this modality. Nonetheless, new technologies and developments have been continued to improve and implement 3D imaging with the hope of further expanding the technique to the biological and medical fields. Detailed discussion on the challenges and perspectives of 3D imaging can be found in selected literature.45,46
Another example is the study of the localization of the antibiotics ampicillin (AMP) and tetracycline (TET) in single Gram-negative bacteria Escherichia coli (E. coli). This was carried out with 3D ToF-SIMS and a C60+ primary ion beam.49 A spatial resolution of ∼300 nm was achieved. The cells were analyzed using the freeze-drying approach. There was a nonlinear relationship between the detected signal of the antibiotics and their amount exposed to the E. coli. The SIMS image showed the localization of the antibiotics within individual bacteria. AMP was mainly found within the first 400 nm subsurface layer of the cells, which was the periplasmic location where the main targets of AMP, the penicillin binding proteins, were found. On the other hand, TET was observed beyond the 400 nm subsurface layer. In addition, the study showed a low susceptibility of TET in the E. coli expressing the TET-specific efflux pump, which was consistent with a result measured by an antimicrobial activity assay showing that the TET-efflux pump contributed to the reduction of TET susceptibility in E. coli.
In drug delivery technology, a nanocarrier is designed to contain a platinum drug for cancer treatment.50 It contains a polymer backbone coupled with a fluorescence dye Cy5.5 and labeled with 15N, and a substrate peptide for matrix metalloproteinase (MMP) (Fig. 3B). The nanocarrier is designed to specifically target tumors by moving to the environment where the tumor associated proteases, MMP, are located. The proteases then cleave the substrate peptide of the carrier inducing the nanocarrier to undergo a morphological change. This leads to a microscale arrangement of the nanoparticles locking them in the tumor environment. The Pt drug subsequently dissociated from the carrier and bound to its target, the DNA, in the nucleus. To evaluate the distribution of the nanocarrier and the drug in tumor tissue, a combination of nanoSIMS and structured illumination microscopy (SIM) was utilized. Live fluorescence microscopy was performed to track the fluorophore of the nanocarrier injected into mice for up to 5 days. SIM microscopy also enabled identification of subcellular organelles with respect to the localization of the nanocarriers. Additionally, nanoSIMS imaging allowed the simultaneous detection of the distribution of the nanocarrier and Pt drug in correlation to endogenous ions such as 31P, a typical ion found in DNA and nucleus (Fig. 3B). The data showed that a much stronger signal of the drug was obtained in the tissue containing the nanocarrier compared to the control. Moreover, the Pt drug was found to accumulate in the nucleus and to not co-localize with the nanocarrier, meaning that the Pt drug effectively dissociated from the nanocarriers and reached the DNA target in the nucleus. More applications of SIMS in pharmaceutical analysis can be found in selected review literature.51,52
A method using ToF-SIMS and 25 keV Bi3+ has been developed to detect amyloid-β (Aβ), a characteristic protein aggregate in Alzheimer's's disease (AD), in transgenic mouse brain by the use of antibody conjugated liposomes, namely immunoliposomes.53 The liposome, about 200 nm in size, consists of a lipid bilayer with 100000 lipid molecules that allowed significant amplification of the protein signal. The liposome was coupled to an antibody, 6E10, which binds to only a specific protein, Aβ. To distinguish the signal of the immunoliposome from that of the endogenous lipids, the liposome was made with deuterated lipids. Specific binding of the immunoliposomes to the Aβ aggregate was first confirmed using a quartz crystal microbalance with dissipation, QCM-D, monitoring and fluorescence microscopy on a model surface of Aβ and AD mouse brain tissue. The mouse brain was incubated with the immunoliposomes and imaged with ToF-SIMS after being fixed and freeze dried. The SIMS images showed a clear signal of the deuterated lipids representing Aβ aggregates which were found to localize in the cortex and hippocampus. The localization was in good agreement with the results obtained by fluorescence microscopy imaging. The method is promising for the study of the structural relationship between Aβ aggregates and endogenous lipids; however, further improvements in sample preparation are needed in order to preserve the distribution of lipids.
To investigate the effect of traumatic brain injury on the molecular structure of the brain, Tian et al.54 developed a dynamic reactive ionization method for ToF-SIMS with a 20 keV (CO2)3500+ GCIB via treatment of the brain tissue with 1-ethyl-3-[(dimethylamino) propyl] carbodiimide hydrochloride and phospholipase C (EDC/PLC). The EDC/PLC sample treatment was shown to suppress the signal of highly abundant phospholipids, especially PCs, and enhance the signal of high mass cardiolipin (CL) (m/z 1300–1530) and gangliosides (GM1, GD1, and GT1) (m/z > 1500) in the brain. The entire brain sections were imaged to observe the localization of cardiolipin and gangliosides in the EDC/PLC treated brain. It was found that the CLs with longer carbon chains and more double bonds were dominant in the cortex, whereas those with shorter carbon chains and less double bonds localized in the hippocampus. In contrast, the gangliosides with a 18:0 fatty acid distributed equally between the cortex and hippocampus while the ones with a 20:0 fatty acid were localized in the hippocampus at higher abundance. The localization of these lipids was observed within the substructures inside the hippocampus with a spatial resolution of 8 μm. The injured brain section was imaged showing that there was a loss of CLs and GT1 in the injured brain compared to the control. The most significant loss was polyunsaturated CLs in the cornu ammonis of the hippocampus and thalamus. These regions are known to be involved in memory formation, seizure, and neurodegeneration.54 This indicated that there might be a relationship between CLs and cognition.
Cisplatin has been one of the common chemotherapy drugs for cancer treatment; however, the drug leads to various side effects in patients.55 To understand the chemical effects of cisplatin at the cellular level, ToF-SIMS with a 40 keV (CO2)6000+ GCIB was utilized to image freeze-dried PC12 cells treated with cisplatin.56 It was found that cisplatin caused significant changes in the lipid composition of the cell surface – a dramatic decrease in the amount of PCs was noticed, along with their salt adducts with sodium and potassium ions, and cholesterol, but significant elevation of diacylglycerols (DAGs) was observed. The results were explained based on the signal transduction pathways of sphingomyelinases and the induction of apoptosis by cisplatin which are involved in the synthesis and metabolism of membrane lipids.
Cocaine and methylphenidate are both known psychostimulants; however, they exhibit opposite cognitive effects.57,58 While cocaine causes deficits in attention, memory and behavior, methylphenidate shows improvement in attention, focus and learning. The reason behind this was explored by a study of the effects of these drugs on the molecular structure of Drosophila brains using ToF-SIMS imaging.59 Two sets of flies were treated with these drugs in parallel for three days and then embedded, frozen, and cut into thin slices. The frozen hydrated brain sections were then analyzed with SIMS using a 40 keV Ar4000+ GCIB. It was shown that the lipid composition of the fly brains, both the localization and concentration, was altered dramatically after the drug treatments (Fig. 3C). The most noticeable aspect is that these drugs induced opposite trends. For example a significant increase in the abundance of lamellar shaped PCs and a decrease in conical shaped PEs and PIs were observed in the cocaine-treated brain. In contrast, PCs decreased and PEs and PIs elevated considerably in the methylphenidate-treated brain (Fig. 3C). The data suggest that the lipid structure of the brain is involved in the molecular mechanism of the drugs’ effects on the brain and might be involved in cognition.
SIMS analysis has great potential for cell imaging, including localization of pharmaceuticals in cells, and neuro-biological research because it provides comprehensive molecular information about the properties and effects of endogenous and exogenous elements with high spatial resolution.
Fig. 4 Correlative imaging of SIMS with other imaging modalities. (A) Correlative SIMS and STED to study the protein turnover in hippocampal neurons. Top row, from left to right: fluorescence microscopy image of the Golgi marker TGN38 (green), synaptic vesicle marker synaptophysin 1 (red), and endoplasmic reticulum marker calnexin (blue) and an overlay of these proteins. Bottom row, from left to right: STED image of calnexin, nanoSIMS ratio image of 15N/14N showing the localization of the turnover, and a chart showing the turnover rate in different organelles. Reproduced from ref. 60 with permission. (B) Correlation of TEM and nanoSIMS imaging to study the distribution of dopamine loading inside single vesicles of PC12 by treatment with 13C-L-DOPA and reserpine. Top row, from left to right: the TEM image, nanoSIMS image of 12C14N, and ratio image of 13C14N/12C14N showing the dopamine enrichment in the vesicles (indicated by red arrows). Bottom row, from left to right: schematic of a dense core vesicle; 3D surface plots of TEM signals and nanoSIMS signal of 13C14N. Reproduced from ref. 63 with permission. (C) Correlation of SIMS and MALDI imaging to visualize the molecular distribution of human cerebellum. From left to right: the SIMS image (red: cholesterol at m/z 386 and green: PC headgroup at m/z 184); MALDI image (green: m/z 3926, blue: m/z 1756 and red: m/z 2817); and tissue stained with H&E (light pink: grey matter, pink: white matter, and purple: granular layer). Reproduced from ref. 68 with permission. |
EM can also be used to obtain elemental information in the energy-dispersive X-ray (EDX) microanalysis mode or electron energy loss spectroscopy (EELS) mode. These EM methods have been combined with nanoSIMS to study neuromelanin granules in the substantia nigra.64 EDX/EELS provided the ultrastructure and general elemental composition, whereas nanoSIMS added information about specific trace elements and isotopes. However, the correlation of SIMS with EM can be challenging, as the sample preparation must be compatible to both techniques. Furthermore, care must be taken to correlate the same regions for analysis. To overcome these problems, an instrument combining both TEM and SIMS has been developed.65 In addition, image fusion techniques have recently been tested and improved for their application in correlative imaging. For example, a Laplacian pyramid fusion method, a method for combining the image information from different sources in order to provide comprehensive visual information with improved clarity and accuracy compared to the individual sources, significantly improved the fusion between nanoSIMS and TEM images.66
Veith and colleagues combined SIMS with fast micro X-ray fluorescence spectroscopy (μ-TRF) to detect CeO2 particles in biological tissue sections.70 μ-TRF allows a fast elemental analysis of big tissues, such as lung tissue. Once a region of interest was defined by μ-TRF, ToF-SIMS was used to analyze the organic and inorganic molecules at higher lateral resolution. Finally, for 3D SIMS imaging, since the sputtering of the sample is not uniform and depends on different parameters, it is not easy to estimate the 3D-volume of analysis by SIMS alone. Thus, SIMS could be combined with AFM, which helped to measure the 3D topography of the sample surface. Combining both techniques, Terlier et al.71 demonstrated an improvement in the accuracy of 3D-reconstruction as well as in the correlation between the chemical information and the physical properties of the sample surface.
Regarding the detection capability, primary ion sources with a higher energy, smaller beam size and softer ionization capable of detecting intact biomolecules in an extended mass range are still a main focus of development. Spatial resolution is expected to not only be sufficient for a single cell but also reach beyond to the single- and sub-organelle level. In addition, methods for improving the ionization efficiency, including improving secondary ion yield and sensitivity, such as the modifications of sample surfaces with reactive reagents are highly desired.
For chemical identification, there have been considerable developments with tandem MS SIMS for elucidating molecular structures in complex biological samples; however, this area is still in the stage of proof of principle. Further effort is needed to improve the spatial resolution and detection mass range, which are the current limitations of the technique, before it will find wide use in bioimaging.
Development of targeted imaging methodologies especially for large biomolecules such as proteins has been a new goal for SIMS imaging. The main challenge for this is the sensitivity and selectivity of detection to obtain both a high signal-to-noise ratio for the molecules of interest and high spatial resolution. Although there have been a few significant studies in the development of effective labeling probes for SIMS, further investigation is desirable to allow simultaneous imaging of different proteins and lipids at subcellular spatial resolution.
Finally, SIMS imaging produces very large datasets which contain a full spectrum of hundreds of peaks for an individual pixel of an entire imaged area. Proper data handling and reliable statistical analysis are in high demand. Development of a standardization method for data treatment, including criteria of sample quantity, data normalization and pre-treatment, statistical analysis, as well as more databases for mass peak assignment have been ongoing and this will contribute to be a major part of the efforts to enable SIMS imaging to become a routine analytical method in neurobiology and cell biology.
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