High resolution metabolite imaging in the hippocampus following neonatal exposure to the environmental toxin BMAA using ToF-SIMS

Simultaneous Multiplexed Imaging of Biomolecules in Transgenic Mouse Brain Tissues Using Mass Spectrometry Imaging: A Multi-omic Approach

The importance of multi-omic-based approaches to better understand diverse pathological mechanisms including neurodegenerative diseases has emerged. Spatial information can be of great help in understanding how biomolecules interact pathologically and in elucidating target biomarkers for developing therapeutics. While various analytical methods have been attempted for imaging-based biomolecule analysis, a multi-omic approach to imaging remains challenging due to the different characteristics of biomolecules. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a powerful tool due to its sensitivity, chemical specificity, and high spatial resolution in visualizing chemical information in cells and tissues. In this paper, we suggest a new strategy to simultaneously obtain the spatial information of various kinds of biomolecules that includes both labeled and label-free approaches using ToF-SIMS. The enzyme-assisted labeling strategy for the targets of interest enables the sensitive and specific imaging of large molecules such as peptides, proteins, and mRNA, a task that has been, to date, difficult for any MS analysis. Together with the strength of the analytical performance of ToF-SIMS in the label-free tissue imaging of small biomolecules, the proposed strategy allows one to simultaneously obtain integrated information of spatial distribution of metabolites, lipids, peptides, proteins, and mRNA at a high resolution in a single measurement. As part of the suggested strategy, we present a sample preparation method suitable for MS imaging. Because a comprehensive method to examine the spatial distribution of multiple biomolecules in tissues has remained elusive, our strategy can be a useful tool to support the understanding of the interactions of biomolecules in tissues as well as pathological mechanisms.

Two-Dimensional and Three-Dimensional Time-of-Flight Secondary Ion Mass Spectrometry Image Feature Extraction Using a Spatially Aware Convolutional Autoencoder

Feature extraction algorithms are an important class of unsupervised methods used to reduce data dimensionality. They have been applied extensively for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging─commonly, matrix factorization (MF) techniques such as principal component analysis have been used. A limitation of MF is the assumption of linearity, which is generally not accurate for ToF-SIMS data. Recently, nonlinear autoencoders have been shown to outperform MF techniques for ToF-SIMS image feature extraction. However, another limitation of most feature extraction methods (including autoencoders) that is particularly important for hyperspectral data is that they do not consider spatial information. To address this limitation, we describe the application of the convolutional autoencoder (CNNAE) to hyperspectral ToF-SIMS imaging data. The CNNAE is an artificial neural network developed specifically for hyperspectral data that uses convolutional layers for image encoding, thereby explicitly incorporating pixel neighborhood information. We compared the performance of the CNNAE with other common feature extraction algorithms for two biological ToF-SIMS imaging data sets. We investigated the extracted features and used the dimensionality-reduced data to train additional ML algorithms. By converting two-dimensional convolutional layers to three-dimensional (3D), we also showed how the CNNAE can be extended to 3D ToF-SIMS images. In general, the CNNAE produced features with significantly higher contrast and autocorrelation than other techniques. Furthermore, histologically recognizable features in the data were more accurately represented. The extension of the CNNAE to 3D data also provided an important proof of principle for the analysis of more complex 3D data sets.

Systematic and state-of the science review of the role of environmental factors in Amyotrophic Lateral Sclerosis (ALS) or Lou Gehrig's Disease

The etiology of sporadic amyotrophic lateral sclerosis (ALS) is still unclear. We evaluate environmental factors suspected to be associated with ALS for their potential linkage to disease causality and to model geographic distributions of susceptible populations and expected cases worldwide. A PRISMA systematic literature review was performed 2021. Bradford Hill criteria were used to identify and rank environmental factors and a secondary review of ALS diagnoses in population studies and ALS case or cohort studies was conducted. Prevalence rate projection informed estimates of impacted regions and populations. Among 1710 papers identified, 258 met the inclusion criteria, of which 173 responded to at least one of nine Bradford Hill criteria among 83 literature-identified ALS environmental factors. Environmental determinants of ALS in order of decreasing significance were β-N-methylamino-L-alanine (BMAA), formaldehyde, selenium, and heavy metals including manganese, mercury, zinc, and copper. Murine animal models were the most common methodology for exploring environmental factors. Another line of investigation of 62 population exposure studies implicated the same group of environmental agents (mean odds ratios): BMAA (2.32), formaldehyde (1.54), heavy metals (2.99), manganese (3.85), mercury (2.74), and zinc (2.78). An age-adjusted incidence model estimated current total ALS cases globally at ~85,000 people compared to only ~1600 cases projected from the reported ALS incidence in the literature. Modeling with the prevalence microscope equation forecasted an increase in U.S. ALS cases from 16,707 confirmed in 2015 to ~22,650 projected for 2040. Two orthogonal methods employed implicate BMAA, formaldehyde, manganese, mercury, and zinc as environmental factors with strong ALS associations. ALS cases likely are significantly underreported globally, and high vulnerability exists in regions with large aging populations. Recent studies on other diseases with environmental determinants suggest the need to consider additional potential triggers and mechanisms, including exposures to microbial agents and epigenetic modifications.

Applications of multivariate analysis and unsupervised machine learning to ToF-SIMS images of organic, bioorganic, and biological systems

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging offers a powerful, label-free method for exploring organic, bioorganic, and biological systems. The technique is capable of very high spatial resolution, while also producing an enormous amount of information about the chemical and molecular composition of a surface. However, this information is inherently complex, making interpretation and analysis of the vast amount of data produced by a single ToF-SIMS experiment a considerable challenge. Much research over the past few decades has focused on the application and development of multivariate analysis (MVA) and machine learning (ML) techniques that find meaningful patterns and relationships in these datasets. Here, we review the unsupervised algorithms—that is, algorithms that do not require ground truth labels—that have been applied to ToF-SIMS images, as well as other algorithms and approaches that have been used in the broader family of mass spectrometry imaging (MSI) techniques. We first give a nontechnical overview of several commonly used classes of unsupervised algorithms, such as matrix factorization, clustering, and nonlinear dimensionality reduction. We then review the application of unsupervised algorithms to various organic, bioorganic, and biological systems including cells and tissues, organic films, residues and coatings, and spatially structured systems such as polymer microarrays. We then cover several novel algorithms employed for other MSI techniques that have received little attention from ToF-SIMS imaging researchers. We conclude with a brief outline of potential future directions for the application of MVA and ML algorithms to ToF-SIMS images.

Cell and Tissue Imaging by TOF-SIMS and MALDI-TOF: An Overview for Biological and Pharmaceutical Analysis

The potential of mass spectrometry imaging (MSI) has been demonstrated in cell and tissue research since 1970. MSI can reveal the spatial distribution of a wide range of atomic and molecular ions detected from biological sample surfaces, it is a powerful and valuable technique used to monitor and detect diverse chemical and biological compounds, such as drugs, lipids, proteins, and DNA. MSI techniques, notably matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) and time of flight secondary ion mass spectrometry (TOF-SIMS), witnessed a dramatic upsurge in studying and investigating biological samples especially, cells and tissue sections. This advancement is attributed to the submicron lateral resolution, the high sensitivity, the good precision, and the accurate chemical specificity, which make these techniques suitable for decoding and understanding complex mechanisms of certain diseases, as well as monitoring the spatial distribution of specific elements, and compounds. While the application of both techniques for the analysis of cells and tissues is thoroughly discussed, a briefing of MALDI-TOF and TOF-SIMS basis and the adequate sampling before analysis are briefly covered. The importance of MALDI-TOF and TOF-SIMS as diagnostic tools and robust analytical techniques in the medicinal, pharmaceutical, and toxicology fields is highlighted through representative published studies.

Innovation in drug toxicology: Application of mass spectrometry imaging technology

Mass spectrometry imaging (MSI) is a powerful molecular imaging technology that can obtain qualitative, quantitative, and location information by simultaneously detecting and mapping endogenous or exogenous molecules in biological tissue slices without specific chemical labeling or complex sample pretreatment. This article reviews the progress made in MSI and its application in drug toxicology research, including the tissue distribution of toxic drugs and their metabolites, the target organs (liver, kidney, lung, eye, and central nervous system) of toxic drugs, the discovery of toxicity-associated biomarkers, and explanations of the mechanisms of drug toxicity when MSI is combined with the cutting-edge omics methodologies. The unique advantages and broad prospects of this technology have been fully demonstrated to further promote its wider use in the field of pharmaceutical toxicology.

Understanding mass spectrometry images: complexity to clarity with machine learning

The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the complexity and size of MSI data sets. Advances in this area have been particularly appealing for MSI of biological samples, which typically produce highly complicated data with often subtle relationships between features. There are many different machine learning approaches that have been applied to MSI data over the past two decades. In this review, we focus on a subset of non-linear machine learning techniques that have mostly only been applied in the past 5 years. Specifically, we review the use of the self-organizing map (SOM), SOM with relational perspective mapping (SOM-RPM), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). While not their only functionality, we have grouped these techniques based on their ability to produce what we refer to as similarity maps. Similarity maps are color representations of hyperspectral data, in which spectral similarity between pixels-that is, their distance in high-dimensional space-is represented by relative color similarity. In discussing these techniques, we describe, briefly, their associated algorithms and functionalities, and also outline applications in MSI research with a strong focus on biological sample types. The aim of this review is therefore to introduce this relatively recent paradigm for visualizing and exploring hyperspectral MSI, while also providing a comparison between each technique discussed.

Strong intramolecular hydrogen bonding in protonated β-methylaminoalanine: A vibrational spectroscopic and computational study

The gas-phase structure of protonated β-methylaminoalanine was investigated using infrared multiple photon dissociation spectroscopy in the C-H, N-H, O-H stretching region (2700-3800 cm^-1) and the fingerprint region (1000-1900 cm^-1). Calculations using density functional theory methods show that the lowest energy structures prefer protonation of the secondary amine. Formation of hydrogen bonds between the primary and secondary amine, and the secondary amine and carboxylic oxygen further stabilize the lowest energy structure. The infrared spectrum of the lowest energy structure originating with harmonic density functional theory has features that generally match the positions of the experimental spectra; however, the overall agreement with the experimental spectrum is poor. Molecular dynamics calculations were used to generate a gas-phase infrared spectrum. With these calculations a reasonable match with the experimental spectrum, especially in the high-energy region, was obtained. The results of the molecular dynamics simulation support the density functional theory calculations, with protonation of the secondary amine and the formation of a hydrogen bond between the protonated secondary amine and the primary amine. This work shows the importance of accounting for anharmonic effects in systems with very strong intramolecular hydrogen bonding.

Spatial and molecular changes of mouse brain metabolism in response to immunomodulatory treatment with teriflunomide as visualized by MALDI-MSI

Multiple sclerosis (MS) is an immune-mediated neurodegenerative disease of the central nervous system (CNS). One of the most promising recent medications for MS is teriflunomide. Its primary mechanism of action is linked to effects on the peripheral immune system by inhibiting dihydroorotate dehydrogenase (DHODH)-catalyzed de novo pyrimidine synthesis and reducing the expansion of lymphocytes in the peripheral immune system. Some in vitro studies suggested, however, that it can also have a direct effect on the CNS compartment. This potential alternative mode of action depends on the drug's capacity to traverse the blood-brain barrier (BBB) and to exert an effect on the complex network of brain biochemical pathways. In this paper, we demonstrate the application of high-resolution/high-accuracy matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry for molecular imaging of the mouse brain coronal sections from animals treated with teriflunomide. Specifically, in order to assess the effect of teriflunomide on the mouse CNS compartment, we investigated the feasibility of teriflunomide to traverse the BBB. Secondly, we systematically evaluated the spatial and semi-quantitative brain metabolic profiles of 24 different endogenous compounds after 4-day teriflunomide administration. Even though the drug was not detected in the examined cerebral sections (despite the high detection sensitivity of the developed method), in-depth study of the endogenous metabolic compartment revealed noticeable alterations as a result of teriflunomide administration compared to the control animals. The observed differences, particularly for purine and pyrimidine nucleotides as well as for glutathione and carbohydrate metabolism intermediates, shed some light on the potential impact of teriflunomide on the mouse brain metabolic networks. Graphical Abstract.

Subventricular zone lipidomic architecture loss in Huntington's disease

The human subventricular zone (SVZ) has a defined cytological and neurochemical architecture, with four constituent laminae that act in concert to support its neurogenic activity. Lipidomic specialisation has previously been demonstrated in the neurologically normal human SVZ, with enrichment of functionally important lipid classes in each lamina. The SVZ is also responsive to neurodegenerative disorders, where thickening of the niche and enhanced proliferation of resident cells were observed in Huntington's disease (HD) brains. In this study, we hypothesised lipidomic changes in the HD SVZ. Using matrix-assisted laser desorption/ionisation (MALDI) imaging mass spectrometry, this analysis shows differences in the lipidomic architecture in the post-mortem Vonsattel grade III cases. Relative to matched, neurologically normal specimens (N = 4), the lipidomic signature of the HD SVZ (N = 4) was characterized by loss of sulfatides and triglycerides in the myelin layer, with an ectopic and focal accumulation of sphingomyelins and ceramide-1-phosphate observed in this lamina. A striking loss of lipidomic patterning was also observed in the ependymal layer, where the local abundance of phosphatidylinositols was significantly reduced in HD. This comprehensive spatially resolved lipidomic analysis of the human HD SVZ identifies alterations in lipid architecture that may shed light on the mechanisms of SVZ responses to neurodegeneration in HD. Open Science: This manuscript was awarded with the Open Materials Badge. For more information see: https://cos.io/our-services/open-science-badges/.

The environmental neurotoxin β-N-methylamino-L-alanine inhibits melatonin synthesis in primary pinealocytes and a rat model

The environmental neurotoxin β-N-methylamino-L-alanine (BMAA) is a glutamate receptor agonist that can induce oxidative stress and has been implicated as a possible risk factor for neurodegenerative disease. Detection of BMAA in mussels, crustaceans, and fish illustrates that the sources of human exposure to this toxin are more abundant than previously anticipated. The aim of this study was to determine uptake of BMAA in the pineal gland and subsequent effects on melatonin production in primary pinealocyte cultures and a rat model. Autoradiographic imaging of 10-day-old male rats revealed a high and selective uptake in the pineal gland at 30 minutes to 24 hours after ¹⁴ C-L-BMAA administration (0.68 mg/kg). Primary pinealocyte cultures exposed to 0.05-3 mmol/L BMAA showed a 57%-93% decrease in melatonin synthesis in vitro. Both the metabotropic glutamate receptor 3 (mGluR3) antagonist Ly341495 and the protein kinase C (PKC) activator phorbol-12-myristate-13-acetate prevented the decrease in melatonin secretion, suggesting that BMAA inhibits melatonin synthesis by mGluR3 activation and PKC inhibition. Serum analysis revealed a 45% decrease in melatonin concentration in neonatal rats assessed 2 weeks after BMAA administration (460 mg/kg) and confirmed an inhibition of melatonin synthesis in vivo. Given that melatonin is a most important neuroprotective molecule in the brain, the etiology of BMAA-induced neurodegeneration may include mechanisms beyond direct excitotoxicity and oxidative stress.

Single Cell Neurometabolomics

Metabolomics, the characterization of metabolites and their changes within biological systems, has seen great technological and methodological progress over the past decade. Most metabolomic experiments involve the characterization of the small-molecule content of fluids or tissue homogenates. While these microliter and larger volume metabolomic measurements can characterize hundreds to thousands of compounds, the coverage of molecular content decreases as sample sizes are reduced to the nanoliter and even to the picoliter volume range. Recent progress has enabled the ability to characterize the major molecules found within specific individual cells. Especially within the brain, a myriad of cell types are colocalized, and oftentimes only a subset of these cells undergo changes in both healthy and pathological states. Here we highlight recent progress in mass spectrometry-based approaches used for single cell metabolomics, emphasizing their application to neuroscience research. Single cell studies can be directed to measuring differences between members of populations of similar cells (e.g., oligodendrocytes), as well as characterizing differences between cell types (e.g., neurons and astrocytes), and are especially useful for measuring changes occurring during different behavior states, exposure to diets and drugs, neuronal activity, and disease. When combined with other omics approaches such as transcriptomics, and with morphological and physiological measurements, single cell metabolomics aids fundamental neurochemical studies, has great potential in pharmaceutical development, and should improve the diagnosis and treatment of brain diseases.

A critical review of the postulated role of the non-essential amino acid, β-N-methylamino-L-alanine, in neurodegenerative disease in humans

The compound BMAA (β-N-methylamino-L-alanine) has been postulated to play a significant role in four serious neurological human diseases: Amyotrophic Lateral Sclerosis/Parkinsonism Dementia Complex (ALS/PDC) found on Guam, and ALS, Parkinsonism, and dementia that occur globally. ALS/PDC with symptoms of all three diseases first came to the attention of the scientific community during and after World War II. It was initially associated with cycad flour used for food because BMAA is a product of symbiotic cycad root-dwelling cyanobacteria. Human consumption of flying foxes that fed on cycad seeds was later suggested as a source of BMAA on Guam and a cause of ALS/PDC. Subsequently, the hypothesis was expanded to include a causative role for BMAA in other neurodegenerative diseases including Alzheimer's disease (AD) through exposures attributed to proximity to freshwaters and/or consumption of seafood due to its purported production by most species of cyanobacteria. The hypothesis that BMAA is the critical factor in the genesis of these neurodegenerative diseases received considerable attention in the medical, scientific, and public arenas. This review examines the history of ALS/PDC and the BMAA-human disease hypotheses; similarities and differences between ALS/PDC and the other diseases with similar symptomologies; the relationship of ALS/PDC to other similar diseases, studies of BMAA-mediated effects in lab animals, inconsistencies and data gaps in the hypothesis; and other compounds and agents that were suggested as the cause of ALS/PDC on Guam. The review concludes that the hypothesis of a causal BMAA neurodegenerative disease relationship is not supported by existing data.

Assessment of non-derivatized β-N-methylamino-l-alanine (BMAA) neurotoxin in free form in urine of patients with nonspecific neurological symptoms

The beta-N-methylamino-l-alanine (BMAA) is a non-proteinogenic amino acid discussed to be produced by cyanobacteria forming harmful blooms. Since BMAA is suspected etiological agent in neurodegenerative diseases, there is a need to study and validate whether and in what concentrations can BMAA be present in human tissues. The aim of the present study was to validate analytical and extraction procedures for quantification of non-derivatized BMAA in the urine using liquid chromatography and commercial ELISA Kit. The study was focused on BMAA in different forms - dissolved, protein associated and total. The validated protocol included SPE followed by HILIC MS/MS for analyses of non-derivatized free form of BMAA with a limit of quantification 20 ng/mL. The methods for other BMAA forms (i.e. protein-associated and total) were also assessed but high matrix interferences did not allow their implementation. The method was used for analyses of free BMAA in 23 urine samples from healthy volunteers and psychiatric patients suffering from nonspecific neurological symptoms. Traces of BMAA were suspectedly detected in a single urine sample but they were not unequivocally proved according to all conservative analytical criteria. BMAA was also not confirmed in a repeatedly collected sample from the same person. The evaluated commercial BMAA ELISA Kit (Abraxis) was not suitable for determination of BMAA in extracted urine samples because of systematically highly false positive results. In agreement with recent findings, analyses of BMAA appear to methodologically challenging, and further research on BMAA in human tissues (or its precursors with potency to form BMAA under natural conditions or - eventually - during sample processing) is needed to clarify its potential ethiological role in neurodegenerative diseases.

Histology-Compatible MALDI Mass Spectrometry Based Imaging of Neuronal Lipids for Subsequent Immunofluorescent Staining

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) enables acquisition of spatial distribution maps for molecular species in situ. This can provide comprehensive insights on the pathophysiology of different diseases. However, current sample preparation and MALDI-IMS acquisition methods have limitations in preserving molecular and histological tissue morphology, resulting in interfered correspondence of MALDI-IMS data with subsequently acquired immunofluorescent staining results. We here investigated the histology compatibility of MALDI-IMS to image neuronal lipids in rodent brain tissue with subsequent immunohistochemistry and fluorescent staining of histological features. This was achieved by sublimation of a low ionization energy matrix compound, 1,5-diaminonapthalene (1,5-DAN), minimizing the number of low-energy laser shots. This yielded improved lipid spectral quality and speed of data acquisition and reduced matrix cluster formation along with preservation of specific histological information at cellular levels. This gentle, histology-compatible MALDI-IMS protocol also diminished thermal effects and mechanical stress created during nanosecond laser ablation processes that were prominent in subsequent immunofluorescent staining images but not with classical hematoxylin and eosin (H&E) staining on the same tissue section. Furthermore, this methodology proved to be a powerful strategy for investigating β-amyloid (Aβ) plaque-associated neuronal lipids as exemplified by performing high-resolution MALDI-IMS with subsequent fluorescent amyloid staining in a transgenic mouse model of Alzheimer's disease (tgSwe).

MALDI imaging delineates hippocampal glycosphingolipid changes associated with neurotoxin induced proteopathy following neonatal BMAA exposure

The environmental toxin β-N-methylamino-L-alanine (BMAA) has been proposed to contribute to neurodegenerative diseases. We have previously shown that neonatal exposure to BMAA results in dose-dependent cognitive impairments, proteomic alterations and progressive neurodegeneration in the hippocampus of adult rats. A high BMAA dose (460mg/kg) also induced intracellular fibril formation, increased protein ubiquitination and enrichment of proteins important for lipid transport and metabolism. The aim of this study was therefore to elucidate the role of neuronal lipids in BMAA-induced neurodegeneration. By using matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS), we characterized the spatial lipid profile in the hippocampus of six month-old rats that were treated neonatally (postnatal days 9-10) with 460mg/kg BMAA. Multivariate statistical analysis revealed long-term changes in distinct ganglioside species (GM, GD, GT) in the dentate gyrus. These changes could be a consequence of direct effects on ganglioside biosynthesis through the b-series (GM3-GD3-GD2-GD1b-GT1b) and may be linked to astrogliosis. Complementary immunohistochemistry experiments towards GFAP and S100β further verified the role of increased astrocyte activity in BMAA-induced brain damage. This highlights the potential of imaging MS for probing chemical changes associated with neuropathological mechanisms in situ. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Imaging mass spectrometry in drug development and toxicology

During the last decades, imaging mass spectrometry has gained significant relevance in biomedical research. Recent advances in imaging mass spectrometry have paved the way for in situ studies on drug development, metabolism and toxicology. In contrast to whole-body autoradiography that images the localization of radiolabeled compounds, imaging mass spectrometry provides the possibility to simultaneously determine the discrete tissue distribution of the parent compound and its metabolites. In addition, imaging mass spectrometry features high molecular specificity and allows comprehensive, multiplexed detection and localization of hundreds of proteins, peptides and lipids directly in tissues. Toxicologists traditionally screen for adverse findings by histopathological examination. However, studies of the molecular and cellular processes underpinning toxicological and pathologic findings induced by candidate drugs or toxins are important to reach a mechanistic understanding and an effective risk assessment strategy. One of IMS strengths is the ability to directly overlay the molecular information from the mass spectrometric analysis with the tissue section and allow correlative comparisons of molecular and histologic information. Imaging mass spectrometry could therefore be a powerful tool for omics profiling of pharmacological/toxicological effects of drug candidates and toxicants in discrete tissue regions. The aim of the present review is to provide an overview of imaging mass spectrometry, with particular focus on MALDI imaging mass spectrometry, and its use in drug development and toxicology in general.

Food-induced changes of lipids in rat neuronal tissue visualized by ToF-SIMS imaging

Time of flight secondary ion mass spectrometry (ToF-SIMS) was used to image the lipid localization in brain tissue sections from rats fed specially processed cereals (SPC). An IonTof 5 instrument equipped with a Bi cluster ion gun was used to analyze the tissue sections. Data from 15 brain samples from control and cereal-fed rats were recorded and exported to principal components analysis (PCA). The data clearly show changes of certain lipids in the brain following cereal feeding. PCA score plots show a good separation in lipid distribution between the control and the SPC-fed group. The loadings plot reveal that the groups separated mainly due to changes in cholesterol, vitamin E and c18:2, c16:0 fatty acid distribution as well as some short chain monocarboxylic fatty acid compositions. These insights relate to the working mechanism of SPC as a dietary supplement. SPC is thought to activate antisecretory factor (AF), an endogenous protein with regulatory function for inflammation and fluid secretion. These data provide insights into lipid content in brain following SPC feeding and suggest a relation to activating AF.

Transfer of developmental neurotoxin β-N-methylamino-l-alanine (BMAA) via milk to nursed offspring: Studies by mass spectrometry and image analysis

The cyanobacterial non-proteinogenic amino acid β-N-methylamino-l-alanine (BMAA) is proposed to be involved in the etiology of amyotrophic lateral sclerosis/parkinsonism dementia complex. When administered as single doses to neonatal rats, BMAA gives rise to cognitive and neurodegenerative impairments in the adult animal. Here, we employed mass spectrometry (LC-MS/MS) and autoradiographic imaging to examine the mother-to-pup transfer of BMAA in rats. The results show that unchanged BMAA was secreted into the milk and distributed to the suckling pups. The concentration of BMAA in pup stomach milk and the neonatal liver peaked after 8h, while the concentration in the pup brain increased throughout the study period. About 1 and 6% of the BMAA recovered from adult liver and brain were released following hydrolysis, suggesting that this fraction was associated with protein. No association to milk protein was observed. Injection of rat pups with [methyl-(14)C]-l-BMAA or [carboxyl-(14)C]-l-BMAA resulted in highly similar distribution patterns, indicating no or low metabolic elimination of the methylamino- or carboxyl groups. In conclusion, BMAA is transported as a free amino acid to rat milk and suckling pups. The results strengthen the proposal that mothers' milk could be a source of exposure for BMAA in human infants.

Mass spectrometric profiling of lipids in intestinal tissue from rats fed cereals processed for medical conditions

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used for lipid profiling of intestine tissue sections from rats fed specially processed cereals and rats fed ordinary feed as a control. This cereal is known to increase the activity of antisecretory factor in plasma and the exact mechanism for the activation process at the cellular level is unclear. ToF-SIMS has been used to track food induced changes in lipid content in intestinal tissue sections to gain insight into the possible mechanisms involved. Data from 20 intestine sections belonging to four different rats from each group of control and specially processed cereals-fed rats were obtained using the stage scan macroraster with a lateral resolution of 5 μm. Data were subsequently subjected to orthogonal partial least squares discriminant analysis. The data clearly show that changes of certain lipids are induced by the specially processed cereal feed. Scores plots show a well-defined separation between the two groups. The corresponding loading plots reveal that the groups separate mainly due to changes of vitamin E, phosphocholine, and phosphosphingolipid fragments, and that for the c18:2 fatty acid. The observed changes in lipids might give insight into the working mechanisms of antisecretory factor in the body, and this has been successfully used to understand the working mechanism of specially processed cereal-induced antisecretory factor activation in intestine.

Environmental neurotoxin interaction with proteins: Dose-dependent increase of free and protein-associated BMAA (β-N-methylamino-L-alanine) in neonatal rat brain

β-Methylamino-L-alanine (BMAA) is implicated in the aetiology of neurodegenerative disorders. Neonatal exposure to BMAA induces cognitive impairments and progressive neurodegenerative changes including intracellular fibril formation in the hippocampus of adult rats. It is unclear why the neonatal hippocampus is especially vulnerable and the critical cellular perturbations preceding BMAA-induced toxicity remains to be elucidated. The aim of this study was to compare the level of free and protein-associated BMAA in neonatal rat brain and peripheral tissues after different exposures to BMAA. Ultra-high performance liquid chromatography-tandem mass spectrometry analysis revealed that BMAA passed the neonatal blood-brain barrier and was distributed to all studied brain areas. BMAA was also associated to proteins in the brain, especially in the hippocampus. The level in the brain was, however, considerably lower compared to the liver that is not a target organ for BMAA. In contrast to the liver there was a significantly increased level of protein-association of BMAA in the hippocampus and other brain areas following repeated administration suggesting that the degradation of BMAA-associated proteins may be lower in neonatal brain than in the liver. Additional evidence is needed in support of a role for protein misincorporation in the neonatal hippocampus for long-term effects of BMAA.

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web - even when larger than 50 GB. Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.

Precise Anatomic Localization of Accumulated Lipids in Mfp2 Deficient Murine Brains Through Automated Registration of SIMS Images to the Allen Brain Atlas

Mass spectrometry imaging (MSI) is a powerful tool for the molecular characterization of specific tissue regions. Histochemical staining provides anatomic information complementary to MSI data. The combination of both modalities has been proven to be beneficial. However, direct comparison of histology based and mass spectrometry-based molecular images can become problematic because of potential tissue damages or changes caused by different sample preparation. Curated atlases such as the Allen Brain Atlas (ABA) offer a collection of highly detailed and standardized anatomic information. Direct comparison of MSI brain data to the ABA allows for conclusions to be drawn on precise anatomic localization of the molecular signal. Here we applied secondary ion mass spectrometry imaging at high spatial resolution to study brains of knock-out mouse models with impaired peroxisomal β-oxidation. Murine models were lacking D-multifunctional protein (MFP2), which is involved in degradation of very long chain fatty acids. SIMS imaging revealed deposits of fatty acids within distinct brain regions. Manual comparison of the MSI data with the histologic stains did not allow for an unequivocal anatomic identification of the fatty acids rich regions. We further employed an automated pipeline for co-registration of the SIMS data to the ABA. The registration enabled precise anatomic annotation of the brain structures with the revealed lipid deposits. The precise anatomic localization allowed for a deeper insight into the pathology of Mfp2 deficient mouse models.

Dietary uptake of omega-3 fatty acids in mouse tissue studied by time-of-flight secondary ion mass spectrometry (TOF-SIMS)

Dietary intake of omega-3 fatty acids is associated with considerable health benefits, including the prevention of metabolic disorders such as cardiovascular disease and type 2 diabetes. Furthermore, incorporation of the main omega-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), at the systemic level has been found to be more efficient when these fatty acids are supplied in the form of marine phospholipids compared to triglycerides. In this work, the uptake of omega-3 fatty acids and their incorporation in specific lipids were studied in adipose, skeletal muscle, and liver tissues of mice given high-fat diets with or without omega-3 supplements in the form of phospholipids or triglycerides using time-of-flight secondary ion mass spectrometry (TOF-SIMS). The results demonstrate significant uptake of EPA and DHA, and the incorporation of these fatty acids in specific lipid molecules, in all three tissue types in response to the dietary omega-3 supplements. Moreover, the results indicate reduced concentrations of arachidonic acid (AA) and depletion of lipids containing AA in tissue samples from mice given supplementary omega-3, as compared to the control mice. The effect on the lipid composition, in particular the DHA uptake and AA depletion, was found to be significantly stronger when the omega-3 supplement was supplied in the form of phospholipids, as compared to triglycerides. TOF-SIMS was found to be a useful technique for screening the lipid composition and simultaneously obtaining the spatial distributions of various lipid classes on tissue surfaces.

Brain region mapping using global metabolomics

Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed both water-soluble and lipid metabolite patterns across brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric acid, and sialic acid, whose physiological roles in brain metabolism are poorly understood. This study helps define regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.