Spatially Resolved Molecular Analysis of Host Response to Medical Device Implantation Using the 3D OrbiSIMS Highlights a Critical Role for Lipids.

A key goal for implanted medical devices is that they do not elicit a detrimental immune response. Macrophages play critical roles in the modulation of the host immune response and are the cells responsible for persistent inflammatory reactions to implanted biomaterials. Two novel immune-instructive polymers that stimulate pro- or anti-inflammatory responses from macrophages in vitro are investigated. These also modulate in vivo foreign body responses (FBR) when implanted subcutaneously in mice. Immunofluorescent staining of tissue abutting the polymer reveals responses consistent with pro- or anti-inflammatory responses previously described for these polymers. Three Dimensional OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) analysis to spatially characterize the metabolites in the tissue surrounding the implant, providing molecular histology insight into the metabolite response in the host is applied. For the pro-inflammatory polymer, monoacylglycerols (MG) and diacylglycerols (DG) are observed at increased intensity, while for the anti-inflammatory coating, the number of phospholipid species detected decreased, and pyridine and pyrimidine levels are elevated. Small molecule signatures from single-cell studies of M2 macrophages in vitro correlate with the in vivo observations, suggesting potential for prediction. Metabolite characterization by the 3D OrbiSIMS is shown to provide insight into the mechanism of bio-instructive materials as medical devices and to inform on the FBR to biomaterials.

Label-free Chemical Characterization of Polarized Immune Cells in vitro and Host Response to Implanted Bio-instructive Polymers in vivo Using 3D OrbiSIMS.

The Three-dimensional OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) is a secondary ion mass spectrometry instrument, a combination of a Time of Flight (ToF) instrument with an Orbitrap analyzer. The 3D OrbiSIMS technique is a powerful tool for metabolic profiling in biological samples. This can be achieved at subcellular spatial resolution, high sensitivity, and high mass-resolving power coupled with MS/MS analysis. Characterizing the metabolic signature of macrophage subsets within tissue sections offers great potential to understand the response of the human immune system to implanted biomaterials. Here, we describe a protocol for direct analysis of individual cells after in vitro differentiation of naïve monocytes into M1 and M2 phenotypes using cytokines. As a first step in vivo, we investigate explanted silicon catheter sections as a medical device in a rodent model of foreign body response. Protocols are presented to allow the host response to different immune instructive materials to be compared. The first demonstration of this capability illustrates the great potential of direct cell and tissue section analysis for in situ metabolite profiling to probe functional phenotypes using molecular signatures. Details of the in vitro cell approach, materials, sample preparation, and explant handling are presented, in addition to the data acquisition approaches and the data analysis pipelines required to achieve useful interpretation of these complex spectra. This method is useful for in situ characterization of both in vitro single cells and ex vivo tissue sections. This will aid the understanding of the immune response to medical implants by informing the design of immune-instructive biomaterials with positive interactions. It can also be used to investigate a broad range of other clinically relevant therapeutics and immune dysregulations. Graphical overview.

Untargeted Metabolomic Characterization of Glioblastoma Intra-Tumor Heterogeneity Using OrbiSIMS.

Glioblastoma (GBM) is an incurable brain cancer with a median survival of less than two years from diagnosis. The standard treatment of GBM is multimodality therapy comprising surgical resection, radiation, and chemotherapy. However, prognosis remains poor, and there is an urgent need for effective anticancer drugs. Since different regions of a single GBM contain multiple cancer subpopulations ("intra-tumor heterogeneity"), this likely accounts for therapy failure as certain cancer cells can escape from immune surveillance and therapeutic threats. Here, we present metabolomic data generated using the Orbitrap secondary ion mass spectrometry (OrbiSIMS) technique to investigate brain tumor metabolism within its highly heterogeneous tumor microenvironment. Our results demonstrate that an OrbiSIMS-based untargeted metabolomics method was able to discriminate morphologically distinct regions (viable, necrotic, and non-cancerous) within single tumors from formalin-fixed paraffin-embedded tissue archives. Specifically, cancer cells from necrotic regions were separated from viable GBM cells based on a set of metabolites including cytosine, phosphate, purine, xanthine, and 8-hydroxy-7-methylguanine. Moreover, we mapped ubiquitous metabolites across necrotic and viable regions into metabolic pathways, which allowed for the discovery of tryptophan metabolism that was likely essential for GBM cellular survival. In summary, this study first demonstrated the capability of OrbiSIMS for in situ investigation of GBM intra-tumor heterogeneity, and the acquired information can potentially help improve our understanding of cancer metabolism and develop new therapies that can effectively target multiple subpopulations within a tumor.

Time resolved growth of (N)-polycyclic aromatic hydrocarbons in engine deposits uncovered with OrbiSIMS depth profiling.

Carbonaceous deposits are ubiquitous, being formed on surfaces in engines, fuel systems and on catalysts operating at high temperatures for hydrocarbon transformations. In internal combustion engines, their formation negatively affects worldwide vehicle emissions and fuel economy, leading to premature deaths and environmental damage. Deposit composition and formation pathways are poorly understood due to their insolubility and the intrinsic complexity of their layered carbonaceous matrix. Here, we apply the in situ high mass resolving power capabilities of 3D Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) argon cluster depth profiling on 16 lab grown deposits and evidence common molecular distributions in deposit depth and in positions relative to the combustion chamber. We observe the products of the growth of both planar and curved polycyclic aromatic hydrocarbons to form small fullerenes over time in the engine and propose possible formation pathways which explain the molecular distributions observed. These include alkyl scission, cyclisation of aliphatic side chains and hydrogen abstraction C2H2 addition to form larger aromatic structures. We apply this pathway to previously unidentified nitrogen containing structures in deposits including quinolines and carbazoles. For the first time, 3D OrbiSIMS results were compared and validated with data from atmospheric pressure matrix assisted laser desorption ionization MS. The comprehensive characterization provided will help the development of a new generation of chemical additives to reduce deposits, and thus improve vehicle emissions and global air quality.

Single-Cell Metabolic Profiling of Macrophages Using 3D OrbiSIMS: Correlations with Phenotype.

Macrophages are important immune cells that respond to environmental cues acquiring a range of activation statuses represented by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at each end of their spectrum. Characterizing the metabolic signature (metabolic profiling) of different macrophage subsets is a powerful tool to understand the response of the human immune system to different stimuli. Here, the recently developed 3D OrbiSIMS instrument is applied to yield useful insight into the metabolome from individual cells after in vitro differentiation of macrophages into naïve, M1, and M2 phenotypes using different cytokines. This analysis strategy not only requires more than 6 orders of magnitude less sample than traditional mass spectrometry approaches but also allows the study of cell-to-cell variance. Characteristic metabolites in macrophage subsets are identified using a targeted lipid and data-driven multivariate approach highlighting amino acids and other small molecules. The diamino acids alanylasparagine and lipid sphingomyelin SM(d18/16:0) are uniquely found in M1 macrophages, while pyridine and pyrimidine are observed at increased intensity in M2 macrophages, findings which link to known biological pathways. The first demonstration of this capability illustrates the great potential of direct cell analysis for in situ metabolite profiling with the 3D OrbiSIMS to probe functional phenotype at the single-cell level using molecular signatures and to understand the response of the human body to implanted devices and immune diseases.

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets.

Modern mass spectrometry techniques produce a wealth of spectral data, and although this is an advantage in terms of the richness of the information available, the volume and complexity of data can prevent a thorough interpretation to reach useful conclusions. Application of molecular formula prediction (MFP) to produce annotated lists of ions that have been filtered by their elemental composition and considering structural double bond equivalence are widely used on high resolving power mass spectrometry datasets. However, this has not been applied to secondary ion mass spectrometry data. Here, we apply this data interpretation approach to 3D OrbiSIMS datasets, testing it for a series of increasingly complex samples. In an organic on inorganic sample, we successfully annotated the organic contaminant overlayer separately from the substrate. In a more challenging purely organic human serum sample we filtered out both proteins and lipids based on elemental compositions, 226 different lipids were identified and validated using existing databases, and we assigned amino acid sequences of abundant serum proteins including albumin, fibronectin, and transferrin. Finally, we tested the approach on depth profile data from layered carbonaceous engine deposits and annotated previously unidentified lubricating oil species. Application of an unsupervised machine learning method on filtered ions after performing MFP from this sample uniquely separated depth profiles of species, which were not observed when performing the method on the entire dataset. Overall, the chemical filtering approach using MFP has great potential in enabling full interpretation of complex 3D OrbiSIMS datasets from a plethora of material types.

Elucidating the molecular landscape of the stratum corneum.

SignificanceSkin is recognized as an intricate assembly of molecular components, which facilitate cell signaling, metabolism, and protein synthesis mechanisms in order to offer protection, regulation, and sensation to the body. Our study takes significant steps to characterize in more detail the complex chemistry of the skin, in particular by generating a better understanding of the uppermost layer, the stratum corneum. Using a state-of-the-art 3D OrbiSIMS technique, we were able to observe the depth distribution, in situ, for a wide range of molecular species. This unprecedented molecular characterization of skin provides information that has the potential to benefit research into fundamental processes, such as those associated with skin aging and disease, and the development and delivery of effective topical formulations.

Spatially Resolved Molecular Compositions of Insoluble Multilayer Deposits Responsible for Increased Pollution from Internal Combustion Engines.

Internal combustion engines are used heavily in diverse applications worldwide. Achieving the most efficient operation is key to improving air quality as society moves to a decarbonized energy system. Insoluble deposits that form within internal combustion engine components including fuel injectors and filters negatively impact CO2 and pollutant emissions. Understanding the composition, origins, and formation mechanisms of these complex materials will be key to their mitigation however, previous attempts only afforded nondiagnostic chemical assignments and limited knowledge toward this. Here, we uncover the identity and spatial distribution of molecular species from a gasoline direct injector, diesel injector, and filter deposit in situ using a new hyphenation of secondary ion mass spectrometry and the state-of-the-art Orbitrap mass analyzer (3D OrbiSIMS) and elemental analysis. Through a high mass resolving power and tandem MS we unambiguously uncovered the identity, distribution, and origin of species including alkylbenzyl sulfonates and provide evidence of deposit formation mechanisms including formation of longer chain sulfonates at the gasoline deposit's surface as well as aromatization to form polycyclic aromatic hydrocarbons up to C66H20, which were prevalent in the lower depth of this deposit. Inorganic salts contributed significantly to the diesel injector deposit throughout its depth, suggesting contamination over multiple fueling cycles. Findings will enable several strategies to mitigate these insoluble materials such as implementing stricter worldwide fuel specifications, modifying additives with adverse reactivity, and synthesizing new fuel additives to solubilize deposits in the engine, thereby leading to less polluting vehicles.