SIMS Imaging Research Articles

Multi-color two-laser super-resolution structured illumination microscopy for the visualization of multi-organelle in living cells.

In this study, we introduced a novel dual-laser multi-color imaging system. Integrated with a multi-channel filter wheel, this system compared three spectral decontamination algorithms (nonnegative matrix factorization [NMF], RCAN, and PICASSO) showcasing its efficacy in achieving four-color imaging with only two laser sources. Combined with a reliable image reconstruction algorithm, the spatial resolution of four channels super-resolution four-color images reached 130, 125, 133, and 132 nm, respectively. Lipid droplets, mitochondria, lysosomes, and nuclei from the mouse hepatocytes (AML12), human neuroblastoma cells (SH-SY5Y), mouse hippocampal neuronal cells (HT-22), and immortalized murine bone marrow-derived macrophages were imaged. At the same time, the chromatin condensation, nuclear contraction, DNA fragmentation, apoptotic body formation, as well as the fusion of Mito and Lyso involved in mitochondrial autophagy were observed in HT-22 and SH-SY5Y cells suffering oxidative stress. Our multi-color SIM imaging system establishes a powerful platform for dynamic organelle studies and other high-resolution investigations in live cells.

Hydrogen trapping and embrittlement of titanium- and vanadium carbide-containing steels after high-temperature hydrogen charging

This work studies the effect of TiC and VC precipitate sizes on hydrogen trapping and embrittlement. Two experimental ferritic HSLA steels containing either TiC or VC carbides for precipitation strengthening are annealed in nitrogen and hydrogen gas. This results in a hydrogen uptake of up to 0.91 and 0.44 wppm in the TiC and VC steels, respectively. TEM and TDS analysis indicate that semi-coherent TiC particles trap hydrogen in misfit dislocations with an activation energy of 43 kJ/mol. Coherent VC particles are suggested to trap hydrogen in interface carbon vacancies, with an energy between 53 and 72 kJ/mol. Carbon vacancies are the likely trapping site in incoherent precipitates, where SIMS imaging confirms that incoherent TiC precipitates trap preferentially near the interface, whereas incoherent VC precipitates trap throughout their bulk. Neither alloy is embrittled in SSRT tests after hydrogen absorption, which shows that these precipitates can be used as both a hydrogen sink and a strengthening mechanism in steels.Graphical abstract

Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data.

Convolutional neural network (CNN)-based methods have shown excellent performance in denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the focus of existing studies. However, Swin Transformer, an alternative and recently proposed deep learning-based image restoration architecture, has not been fully investigated for denoising SR-SIM images. Furthermore, it has not been fully explored how well transfer learning strategies work for denoising SR-SIM images with different noise characteristics and recorded cell structures for these different types of deep learning-based methods. Currently, the scarcity of publicly available SR-SIM datasets limits the exploration of the performance and generalization capabilities of deep learning methods. In this work, we present SwinT-fairSIM, a novel method based on the Swin Transformer for restoring SR-SIM images with a low signal-to-noise ratio. The experimental results show that SwinT-fairSIM outperforms previous CNN-based denoising methods. Furthermore, as a second contribution, two types of transfer learning-namely, direct transfer and fine-tuning-were benchmarked in combination with SwinT-fairSIM and CNN-based methods for denoising SR-SIM data. Direct transfer did not prove to be a viable strategy, but fine-tuning produced results comparable to conventional training from scratch while saving computational time and potentially reducing the amount of training data required. As a third contribution, we publish four datasets of raw SIM images and already reconstructed SR-SIM images. These datasets cover two different types of cell structures, tubulin filaments and vesicle structures. Different noise levels are available for the tubulin filaments. The SwinT-fairSIM method is well suited for denoising SR-SIM images. By fine-tuning, already trained models can be easily adapted to different noise characteristics and cell structures. Furthermore, the provided datasets are structured in a way that the research community can readily use them for research on denoising, super-resolution, and transfer learning strategies.

The High Resolutive Detection of TiO2 Nanoparticles in Human Corneocytes via TEM/NanoSIMS Correlation

Titanium dioxide (TiO2) nanoparticles (NPs) are the subject of numerous studies and controversies on the risks they could pose to the environment and human health. When in contact with biological tissues, NPs can sometimes be challenging to precisely localize within subcellular structures (typically around 0.1 µm) when they exist as isolated NPs, particularly when using the SIMS approach. Indeed, the chemical signals produced by isolated NPs are very low, so they can be confused with background signals. This was the motivation behind our development of a new strategy for correlating TEM/SIMS to detect TiO2 NPs in close proximity to cutaneous corneocytes. For this purpose, we initially developed a new tool for TEM and SIMS image registration based on a non-rigid image-deformation-enabling image overlay. Combining SIMS and TEM data through this overlay enhances NP localization’s precision. Secondly, we developed an algorithm based on the statistical analysis of multiplane SIMS images to denoise them. As a result, background noise was reduced, illuminating the low yet specific signals from isolated NPs. Finally, this new correlative approach enables the precise 3D localization of isolated NPs within the analyzed volume. We consider this method a breakthrough for subcellular-scale NP localization.

Super-resolution reconstruction of structured illumination microscopy based on pixel reassignment

In this work, we report a pixel reassignment based super-resolution reconstruction algorithm for structured illumination microscopy (entitled PR-SIM). PR-SIM provides a twofold theoretical resolution enhancement by reassigning the pixels in raw SIM images with respect to the center of each illumination fringe and applying further deconvolution. By comparing with frequency domain based algorithms, PR-SIM is more immune to fringe distortion and, hence, it is more suited for large-field SIM in that it processes the raw images locally. Meanwhile, the reconstruction speed of PR-SIM can be enhanced by skipping empty regions in the image and further enhanced by employing GPU-base parallel calculation. Overall, we can envisage that the PR-SIM can be extended for other illumination modulation based microscopic techniques.

Visualization of in vitro uptake of nail lacquer ingredients into nail plate by high‐resolution SIMS imaging

Visualization of <i>in vitro</i> uptake of nail lacquer ingredients into nail plate by high‐resolution SIMS imaging

Depth Correction of 3D SIMS Images of Mammalian Cells with Secondary Ion Images Captures the Effects of Differential Sputtering.

Depth Correction of 3D SIMS Images of Mammalian Cells with Secondary Ion Images Captures the Effects of Differential Sputtering.

Keyframe-aided resolution enhancement network for dynamic super-resolution structured illumination microscopy.

Deep learning has been used to reconstruct super-resolution structured illumination microscopy (SR-SIM) images with wide-field or fewer raw images, effectively reducing photobleaching and phototoxicity. However, the dependability of new structures or sample observation is still questioned using these methods. Here, we propose a dynamic SIM imaging strategy: the full raw images are recorded at the beginning to reconstruct the SR image as a keyframe, then only wide-field images are recorded. A deep-learning-based reconstruction algorithm, named KFA-RET, is developed to reconstruct the rest of the SR images for the whole dynamic process. With the structure at the keyframe as a reference and the temporal continuity of biological structures, KFA-RET greatly enhances the quality of reconstructed SR images while reducing photobleaching and phototoxicity. Moreover, KFA-RET has a strong transfer capability for observing new structures that were not included during network training.

Super-resolved SIM imaging revealed hierarchical organization of the ryanodine receptor network in 3 dimensions in rabbit sinoatrial node cells.

The heartbeat is initiated by specialized sinoatrial node cells (SANCs). The rate of the heartbeat is regulated by Ca released from the sarcoplasmic reticulum (SR) via ryanodine receptors (RyRs) interacting with voltage and Ca-dependent membrane ion currents in SANCs. The released Ca takes the form of localized Ca releases (LCRs) that propagate for limited distances in wave-like manner. A computational model of SANCs, previously developed in our laboratory, simulates LCR synchronization mechanism as hierarchical clustering of surface RyRs based on confocal microscopy imaging data obtained in tangential sections of SANCs. The true detailed distribution of RyR clusters in 3D, however, remains unknown. Here, we applied a series of new computational approaches to experimental data obtained by super-resolved structured illumination microscopy in rabbit SANCs, in which RyRs were labeled by specific antibodies. Our approach consists of automated segmentation of RyR clusters with globally optimal detection and segmentation of objects with constant internal intensity distribution, followed by object-based colocalization analysis in 3D. Results are further refined with watershed transformations and computational geometry. Examinations of the images have revealed a hierarchical architecture of RyR network (positions and sizes of submembrane RyR clusters). After constructing a mathematical convex hull around the cell using RyR clusters as nodes, clusters were grouped based on their volume. The distribution of RyR clusters exhibited a wide range of sizes from 0.75 × 10−3 µm3 to 0.50 µm3 and cluster histograms followed a Poisson-like distribution. These new data have been incorporated in a new, realistic 3D model of SANC, in which heterogeneous RyR clusters facilitate LCR propagation. Impairment of the complex, hierarchical structure of RyR clusters may lead to sinus node dysfunction in aging and disease.

Dual-channel structured illumination super-resolution quantitative fluorescence resonance energy transfer imaging

The Structured illumination (SI)-based super resolution fluorescence resonance energy transfer (SR-FRET) imaging technique, known as SISR-FRET, enables the investigation of molecular structures and functions in cellular organelles by resolving sub-diffraction FRET signals within living cells. The FRET microscopy offers unique advantages for quantitatively detecting dynamic interactions and spatial distribution of biomolecules within living cells. The spatial resolution of conventional FRET microscopy is limited by the diffraction limit, and it can only capture the average behavior of these events within the resolution limits of conventional fluorescence microscopy. The SISR-FRET performs sequential linear reconstruction of the three-channel SIM images followed by FRET quantitative analysis by using a common localization mask-based filtering approach. This two-step process ensures the fidelity of the reconstructed SR-FRET signals while effectively removing false-positive FRET signals caused by SIM artifacts. However, the slow imaging speed resulting from the switching of excitation-emission channels in SISR-FRET imaging limits its application in fast imaging scenarios. To address this issue, this study proposes a dual-channel structured illumination super-resolution quantitative FRET imaging system and method. By incorporating an FRET dual-channel imaging and registration module into the imaging pathway, the spatial switching and channel multiplexing of the SISR-FRET excitation-emission channels are achieved. Combining the image reconstruction algorithm with channel sub-pixel registration correction, the dual-channel SISR-FRET technique enhances the temporal resolution by 3.5 times while preserving the quantitative super-resolution FRET analysis. Experimental results are obtained by using a multi-color SIM system to perform super-resolution imaging of living cells expressing mitochondria outer membrane FRET standard plasmids. These experiments validate the improved spatial and temporal resolution of dual-channel SISR-FRET and the fidelity of FRET quantification analysis. In summary, this research presents a novel dual-channel structured illumination super-resolution FRET imaging system and method. It overcomes the limitations of slow imaging speed in SISR-FRET by realizing the spatial switching and channel multiplexing of excitation-emission channels. The proposed technique enhances the temporal resolution while maintaining quantitative analysis of super-resolution FRET. Experimental validation demonstrates the increased spatial and temporal resolution of dual-channel SISR-FRET and the accuracy of FRET quantification analysis. This advancement contributes to the study of molecular structures and functions in cellular organelles, providing valuable insights into the intricate mechanisms of living cells.

Characterization of trace elements in coal fly ash by extraction, micro-PIXE, TOF-SIMS, and XAFS

Coal fly ash (CFA) contains considerable amounts of potentially hazardous trace elements. Characterization of trace elements in CFA is essential for the safe disposal and recycle of CFA. The objectives of this study were i) to determine and predict the solubility of trace elements in CFA in relation to their chemical and mineralogical properties, and ii) to characterize trace elements using the surface chemical analysis including time-of-flight secondary ion mass spectrometry (TOF-SIMS) and accelerator-based micro particle induced X-ray emission (PIXE) analysis, in combination with X-ray absorption fine structure (XAFS) spectroscopy with a primary focus on As and Cr. The CFA samples from 12 thermal power plants contained B (ave. 203 mg kg−1), F (90 mg kg−1), Cr (63 mg kg−1), As (21 mg kg−1), and Se (3.2 mg kg−1), in which the water soluble fraction relative to the total concentration decreased in the order B (24 %) > Se (23 %) > F (20 %) > As (1.7 %) > Cr(IV) (0.71 %). A regression model indicated that water extractable As and Cr(VI) from CFA increased linearly with increasing SiO2 and CaO in CFA, respectively. The SIMS images showed that B was finely and heterogeneously distributed on CFA, whereas F was distributed homogeneously on CFA. The combined results from micro-PIXE and XAFS revealed that i) As was distributed on about 50-μm particles in the form of As(V) associated with Al and Ca, and ii) Cr was co-located with Fe and Ca on about 50-μm particles and was present as Cr(III). This study demonstrated that the combined results from TOF-SIMS, micro-PIXE, and XAFS techniques enable trace elements in CFA to be better characterized in terms of spatial distribution and chemical speciation.

Inside Back Cover: Bioorthogonal Lanthanide Molecular Probes for Near‐Infrared Fluorescence and Mass Spectrometry Imaging (Angew. Chem. Int. Ed. 43/2022)

The concept of “killing two birds with one stone” is illustrated in the image. Clickable lanthanide molecular probes are drawn as arrowheads and the two imaging methods NIRF and SIMS are shown as two eagles, the silhouettes of which are composed of elements from the near-infrared fluorescence and mass spectrometry images, respectively. Dual-modal NIRF-SIMS imaging has been achieved with these clickable lanthanide molecular probes, as reported by Yao Zhao, Xing Chen, Jun-Long Zhang et al. in their Research Article (e202208707).

MRI-Guided Intraluminal HDR Brachytherapy for Inoperable Malignant Biliary Tract Obstruction

Aim: Malignant biliary tract obstruction (MBTO) leads to abdominal pain, jaundice, poor quality of life and portends a poor prognosis. Management of MBTO is a significant therapeutic challenge given that treatment with chemotherapy or radiotherapy has limited utility and percutaneous biliary drainage or stent insertion provides only transient symptomatic relief. Intraluminal HDR brachytherapy via catheters inserted percutaneously at the time of stent insertion can be effective in the management of inoperable MBTO. Here, we describe the workflow developed within our department for simulation and treatment using an intraluminal brachytherapy technique. Process: Delivery of bile duct brachytherapy requires the participation of multiple disciplines including interventional radiology (IR), medical physics, radiation oncology (RO) and radiation therapy with careful coordination of numerous tasks. A drain/stent and 1-2 treatment catheters are inserted into the patient's bile ducts by IR before the CT and MR simulation (sim). During the CT sim, multiple surview and low dose helical scans are acquired to verify the treatment catheter position and adjustments are made by the RO as needed. Once the position is finalized, a planning CT scan is done with IV contrast and the patient in voluntary breath hold. Then, the CT and MR sim images are fused. The CT is used to digitize the brachytherapy source path, while the MR is used for target and organs at risk delineation. Treatment is delivered 1-2 days after sim, with 15-25 Gy in 3-5 fractions using an Ir-192 HDR source. Radiographs are taken to confirm catheter position prior to each treatment. Benefits/Challenges: Brachytherapy can be used to treat the tumor at the same time as placement of a stent/drain, thus providing both symptom management and disease control. Although the patient is admitted for the IR procedure, the actual brachytherapy treatment is done on an outpatient basis with no anesthesia, thus treatment does not require significant time or resources in the brachytherapy suite. Patients often present with biliary obstruction emergently and stent/drain placement is booked urgently in IR with little notice to the radiotherapy department. The tight time line makes it difficult to facilitate communication between the multidisciplinary team, prepare staff, assemble supplies, and coordinate subsequent appointments. The CT sim process continues to evolve as new issues are identified with each patient. Variations in catheter/stent placement is a potential challenge and 2/8 patients have required reinsertion of angio-sheath by IR after problems were discovered during the CT sim. MR sim is not always possible depending on nature of inserted material (i.e. metallic stent or drainage sheath). Treatment catheters must be secured in place and covered with a dressing between appointments to prevent damage, change in position or obstruction. Patient education and cooperation is crucial to ensure proper care. Impact/Outcomes: In April 2021, our institution became the first in Canada to offer MRI-guided brachytherapy treatment for patients with inoperable MBTO. As of Jan 2022, 8 patients have been treated using this protocol. With each subsequent case, the time required for treatment delivery has decreased from 1 hour to 30 minutes per fraction and sim processes optimized. This treatment option has potential to improve the quality of life in patients with minimal therapeutic options.

A Reliable Approach for Revealing Molecular Targets in Secondary Ion Mass Spectrometry.

Nano secondary ion mass spectrometry (nanoSIMS) imaging is a rapidly growing field in biological sciences, which enables investigators to describe the chemical composition of cells and tissues with high resolution. One of the major challenges of nanoSIMS is to identify specific molecules or organelles, as these are not immediately recognizable in nanoSIMS and need to be revealed by SIMS-compatible probes. Few laboratories have generated such probes, and none are commercially available. To address this, we performed a systematic study of probes initially developed for electron microscopy. Relying on nanoscale SIMS, we found that antibodies coupled to 6 nm gold particles are surprisingly efficient in terms of labeling specificity while offering a reliable detection threshold. These tools enabled accurate visualization and sample analysis and were easily employed in correlating SIMS with other imaging approaches, such as fluorescence microscopy. We conclude that antibodies conjugated to moderately sized gold particles are promising tools for SIMS imaging.

Meiosis-specific cohesin complexes display essential and distinct roles in mitotic embryonic stem cell chromosomes

BackgroundCohesin is a chromosome-associated SMC–kleisin complex that mediates sister chromatid cohesion, recombination, and most chromosomal processes during mitosis and meiosis. However, it remains unclear whether meiosis-specific cohesin complexes are functionally active in mitotic chromosomes.ResultsThrough high-resolution 3D-structured illumination microscopy (3D-SIM) and functional analyses, we report multiple biological processes associated with the meiosis-specific cohesin components, α-kleisin REC8 and STAG3, and the distinct loss of function of meiotic cohesin during the cell cycle of embryonic stem cells (ESCs). First, we show that STAG3 is required for the efficient localization of REC8 to the nucleus by interacting with REC8. REC8-STAG3-containing cohesin regulates topological properties of chromosomes and maintains sister chromatid cohesion. Second, REC8-cohesin has additional sister chromatid cohesion roles in concert with mitotic RAD21-cohesin on ESC chromosomes. SIM imaging of REC8 and RAD21 co-staining revealed that the two types of α-kleisin subunits exhibited distinct loading patterns along ESC chromosomes. Third, knockdown of REC8 or RAD21-cohesin not only leads to higher rates of premature sister chromatid separation and delayed replication fork progression, which can cause proliferation and developmental defects, but also enhances chromosome compaction by hyperloading of retinoblastoma protein–condensin complexes from the prophase onward.ConclusionsOur findings indicate that the delicate balance between mitotic and meiotic cohesins may regulate ESC-specific chromosomal organization and the mitotic program.

Validation of Deep Learning-based Augmentation for Reduced 18F-FDG Dose for PET/MRI in Children and Young Adults with Lymphoma.

To investigate if a deep learning convolutional neural network (CNN) could enable low-dose fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/MRI for correct treatment response assessment of children and young adults with lymphoma. In this secondary analysis of prospectively collected data (ClinicalTrials.gov identifier: NCT01542879), 20 patients with lymphoma (mean age, 16.4 years ± 6.4 [standard deviation]) underwent 18F-FDG PET/MRI between July 2015 and August 2019 at baseline and after induction chemotherapy. Full-dose 18F-FDG PET data (3 MBq/kg) were simulated to lower 18F-FDG doses based on the percentage of coincidence events (representing simulated 75%, 50%, 25%, 12.5%, and 6.25% 18F-FDG dose [hereafter referred to as 75%Sim, 50%Sim, 25%Sim, 12.5%Sim, and 6.25%Sim, respectively]). A U.S. Food and Drug Administration-approved CNN was used to augment input simulated low-dose scans to full-dose scans. For each follow-up scan after induction chemotherapy, the standardized uptake value (SUV) response score was calculated as the maximum SUV (SUVmax) of the tumor normalized to the mean liver SUV; tumor response was classified as adequate or inadequate. Sensitivity and specificity in the detection of correct response status were computed using full-dose PET as the reference standard. With decreasing simulated radiotracer doses, tumor SUVmax increased. A dose below 75%Sim of the full dose led to erroneous upstaging of adequate responders to inadequate responders (43% [six of 14 patients] for 75%Sim; 93% [13 of 14 patients] for 50%Sim; and 100% [14 of 14 patients] below 50%Sim; P < .05 for all). CNN-enhanced low-dose PET/MRI scans at 75%Sim and 50%Sim enabled correct response assessments for all patients. Use of the CNN augmentation for assessing adequate and inadequate responses resulted in identical sensitivities (100%) and specificities (100%) between the assessment of 100% full-dose PET, augmented 75%Sim, and augmented 50%Sim images. CNN enhancement of PET/MRI scans may enable 50% 18F-FDG dose reduction with correct treatment response assessment of children and young adults with lymphoma.Keywords: Pediatrics, PET/MRI, Computer Applications Detection/Diagnosis, Lymphoma, Tumor Response, Whole-Body Imaging, Technology AssessmentClinical trial registration no: NCT01542879 Supplemental material is available for this article. © RSNA, 2021.

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.

Differential Proximity of Perisynaptic Astrocytic Best1 at the Excitatory and Inhibitory Tripartite Synapses in APP/PS1 and MAOB-KO Mice Revealed by Lattice Structured Illumination Microscopy.

Bestrophin-1 (Best1) is a GABA- and glutamate-permeable, Ca2+-activated Cl- channel, which is mainly expressed in astrocytes and localized at the microdomain or perisynaptic junction of the tripartite synapse. Distribution of Best1 is dramatically changed in pathological conditions such as Alzheimer’s disease. However, it is still unknown whether Best1 is located at the glutamatergic or GABAergic tripartite synapses. Here, we utilized the Lattice structured illumination microscopy (Lattice SIM) to visualize Best1 expression at the perisynaptic junctions of the tripartite synapses in CA1 of mouse hippocampus. We performed co-labeling with antibodies against 1) Best1 and vesicular glutamate transporter-2 (vGLUT2) or 2) Best1 and vesicular GABA transporter (vGAT) to measure the proximity of Best1-containing perisynapse to glutamatergic or GABAergic presynapse, respectively. In addition, we examined two transgenic mouse lines of 1) APP/PS1 mouse showing high astrocytic MAOB activity and cytosolic GABA and 2) MAOB-KO mouse showing low astrocytic GABA. Lattice SIM images were further processed by Imaris, which allowed 3D-rendering and spot identification. We found that astrocytic Best1 was distributed closer to the glutamatergic synapses than GABAergic synapses in the wild-type mice. In APP/PS1 mice, Best1 distribution was significantly changed by moving away from the glutamatergic synapses while moving closer to the GABAergic synapses. On the contrary, in MAOB-KO mice, the Best1 distribution was dramatically changed by moving closer to the glutamatergic synapses and moving far away from the GABAergic synapses. Our findings propose that the proximity of Best1-containing perisynapses to presynapses dynamically changes according to the level of astrocytic cytosolic GABA.

Successive High-Resolution (H2O)n-GCIB and C60-SIMS Imaging Integrates Multi-Omics in Different Cell Types in Breast Cancer Tissue.

The temporo-spatial organization of different cells in the tumor microenvironment (TME) is the key to understanding their complex communication networks and the immune landscape that exists within compromised tissues. Multi-omics profiling of single-interacting cells in the native TME is critical for providing further information regarding the reprograming mechanisms leading to immunosuppression and tumor progression. This requires new technologies for biomolecular profiling of phenotypically heterogeneous cells on the same tissue sample. Here, we developed a new methodology for comprehensive lipidomic and metabolomic profiling of individual cells on frozen-hydrated tissue sections using water gas cluster ion beam secondary ion mass spectrometry ((H2O)n-GCIB-SIMS) (at 1.6 μm beam spot size), followed by profiling cell-type specific lanthanide antibodies on the same tissue section using C60-SIMS (at 1.1 μm beam spot size). We revealed distinct variations of distribution and intensities of >150 key ions (e.g., lipids and important metabolites) in different types of the TME individual cells, such as actively proliferating tumor cells as well as infiltrating immune cells. The demonstrated feasibility of SIMS imaging to integrate the multi-omics profiling in the same tissue section at the single-cell level will lead to new insights into the role of lipid reprogramming and metabolic response in normal regulation or pathogenic discoordination of cell–cell interactions in a variety of tissue microenvironments.

Combining secondary ion mass spectrometry image depth profiling and single particle inductively coupled plasma mass spectrometry to investigate the uptake and biodistribution of gold nanoparticles in Caenorhabditis elegans

Analytical techniques capable of determining the spatial distribution and quantity (mass and/or particle number) of engineered nanomaterials in organisms are essential for characterizing nano-bio interactions and for nanomaterial risk assessments. Here, we combine the use of dynamic secondary ion mass spectrometry (dynamic SIMS) and single particle inductively coupled mass spectrometry (spICP-MS) techniques to determine the biodistribution and quantity of gold nanoparticles (AuNPs) ingested by Caenorhabditis elegans. We report the application of SIMS in image depth profiling mode for visualizing, identifying, and characterizing the biodistribution of AuNPs ingested by nematodes in both the lateral and z (depth) dimensions. In parallel, conventional- and sp-ICP-MS quantified the mean number of AuNPs within the nematode, ranging from 2 to 36 NPs depending on the size of AuNP. The complementary data from both SIMS image depth profiling and spICP-MS provides a complete view of the uptake, translocation, and size distribution of ingested NPs within Caenorhabditis elegans.