Resolving the Complexity of Spatial Lipidomics Using MALDI TIMS Imaging Mass Spectrometry.

Protein glycosylation can be vital for changing the function or physiochemical properties of a protein. Abnormal glycosylation can lead to protein malfunction, resulting in severe diseases. Therefore, it is important to develop techniques for characterization of such modifications in proteins at a sensitivity level comparable with state-of-the-art proteomics. Whereas techniques exist for characterization of high abundance glycoproteins, no single method is presently capable of providing information on both site occupancy and glycan structure on a single band excised from an electrophoretic gel. We present a new technique that allows characterization of low amounts of glycoproteins separated by gel electrophoresis. The method takes advantage of sequential specific and nonspecific enzymatic treatment followed by selective purification and characterization of the glycopeptides using graphite powder microcolumns in combination with mass spectrometry. The method is faster and more sensitive than previous approaches and is compatible with proteomic studies.

Mass spectrometry-based tissue profiling and imaging are technologies that allow identification and visualization of protein signals directly on thin sections cut from fresh frozen tissue specimens. These technologies were utilized to evaluate protein expression profiles in the normal mouse prostate during development (1-5 weeks of age), at sexual maturation (6 weeks of age), and in adult prostate (at 10, 15, or 40 weeks of age). The evolution of protein expression during normal prostate development and maturation were subsequently compared with 15-week prostate tumors derived from genetically engineered mice carrying the Large T antigen gene under regulation of the prostate-specific probasin promoter (LPB-Tag mouse model for prostate cancer). This approach identified proteins differentially expressed at specific time points during prostate development. Furthermore expression of some of these proteins, for example probasin and spermine-binding protein, were associated with prostate maturation, and prostate tumor formation resulted in their loss of expression. Cyclophilin A, a protein found in other cancers, was differentially alpha-acetylated on the N terminus, and both isoforms appeared during normal prostate and prostate tumor development. Imaging mass spectrometry localized the protein signals to specific prostatic lobes or regions. Thus, tissue profiling and imaging can be utilized to analyze the ontogeny of protein expression during prostate morphogenesis and tumorigenesis and identify proteins that could potentially serve as biomarkers for prostate cancer.

Imaging mass spectrometry (IMS) enables the spatially targeted molecular assessment of biological tissues at cellular resolutions. New developments and technologies are essential for uncovering the molecular drivers of native physiological function and disease. Instrumentation must maximize spatial resolution, throughput, sensitivity, and specificity, because tissue imaging experiments consist of thousands to millions of pixels. Here, we report the development and application of a matrix-assisted laser desorption/ionization (MALDI) trapped ion-mobility spectrometry (TIMS) imaging platform. This prototype MALDI timsTOF instrument is capable of 10 μm spatial resolutions and 20 pixels/s throughput molecular imaging. The MALDI source utilizes a Bruker SmartBeam 3-D laser system that can generate a square burn pattern of <10 × 10 μm at the sample surface. General image performance was assessed using murine kidney and brain tissues and demonstrate that high-spatial-resolution imaging data can be generated rapidly with mass measurement errors <5 ppm and ∼40 000 resolving power. Initial TIMS-based imaging experiments were performed on whole-body mouse pup tissue demonstrating the separation of closely isobaric [PC(32:0) + Na]+ and [PC(34:3) + H]+ (3 mDa mass difference) in the gas phase. We have shown that the MALDI timsTOF platform can maintain reasonable data acquisition rates (>2 pixels/s) while providing the specificity necessary to differentiate components in complex mixtures of lipid adducts. The combination of high-spatial-resolution and throughput imaging capabilities with high-performance TIMS separations provides a uniquely tunable platform to address many challenges associated with advanced molecular imaging applications.

The crustacean cardiac neuromuscular system is a useful model for studying how neural circuits generate behavior, as it is comprised of a simple ganglion containing nine neurons, yet acts as a robust central pattern generator. The crustacean heart is neurogenic, receiving input from neuropeptides. However, the specific effects of neuropeptides on cardiac output is not fully understood, and the large degree of comodulation between multiple neuropeptides makes studying these effects more challenging. To address this challenge, matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) imaging was used to localize neuropeptides within the cardiac ganglion (CG), providing information about the identity and localization of neuropeptides being present. CG extracts were also profiled using liquid chromatography coupled to tandem mass spectrometry (MS/MS) with a data independent acquisition method, resulting in the confirmation of 316 neuropeptides. Two MS imaging (MSI) platforms were compared to provide comprehensive results, including a MALDI-Orbitrap instrument for high mass spectral resolution for accurate identifications and a MALDI TOF/TOF instrument for improved spatial resolution and sensitivity, providing more descriptive MS images. MS images for 235 putative neuropeptides were obtained, with the identification of 145 of these being confirmed by either complementary MS/MS data or accurate mass matching. The MSI studies demonstrate the sensitivity and power of this MALDI-based in situ analytical strategy for unraveling the chemical complexity present in a small nine-cell neuronal system. The results of this study will enable more informative assays of the functions of neuropeptides within this important neural circuit.

Matrix-assisted laser desorption/ionisation (MALDI) imaging mass spectrometry (IMS) allows for the simultaneous detection and imaging of several molecules in brain tissue. However, the detection of glycerolipids such as diacylglycerol (DAG) and triacylglycerol (TAG) in brain tissues is hindered in MALDI-IMS because of the ion suppression effect from excessive ion yields of phosphatidylcholine (PC). In this study, we describe an approach that employs a homogeneously deposited metal nanoparticle layer (or film) for the detection of glycerolipids in rat brain tissue sections using IMS. Surface-assisted laser desorption/ionisation IMS with sputter-deposited Pt film (Pt-SALDI-IMS) for lipid analysis was performed as a solvent-free and organic matrix-free method. Pt-SALDI produced a homogenous layer of nanoparticles over the surface of the rat brain tissue section. Highly selective detection of lipids was possible by MALDI-IMS and Pt-SALDI-IMS; MALDI-IMS detected the dominant ion peak of PC in the tissue section, and there were no ion peaks representing glycerolipids such as DAG and TAG. In contrast, Pt-SALDI-IMS allowed the detection of these glycerolipids, but not PC. Therefore, using a hybrid method combining MALDI and Pt-SALDI (i.e., matrix-enhanced [ME]-Pt-SALDI-IMS), we achieved the simultaneous detection of PC, PE and DAG in rat brain tissue sections, and the sensitivity for the detection of these molecules was better than that of MALDI-IMS or Pt-SALDI alone. The present simple ME-Pt-SALDI approach for the simultaneous detection of PC and DAG using two matrices (sputter-deposited Pt film and DHB matrix) would be useful in imaging analyses of biological tissue sections.

Prostate cancer is often heterogeneous with multiple tumor foci within the same prostate. MALDI (Matrix-Assisted Laser Desorption/Ionization) mass spectrometry imaging (MSI) allows for a comprehensive profiling of the molecular phenotype on the protein, peptide, lipid, and metabolite level across entire tissue slides without prior enrichment of tumor cells. This study aims in a MALDI-based discrimination of cancer areas that are heterogeneous with respect to morphology and molecular features. We established a method for cryopreservation of entire prostates from cancer patients, and build tissue microarrays from individual cancerous prostates representing &amp;gt;30 different areas of the primary tumor as well as multiple lymph node metastases. We analyzed these arrays for ERG fusion by FISH and for peptide signatures by MALDI MSI. In addition, 2 selected tumor areas and 4 different lymph node metastases from one prostate were subjected to paired end next generation sequencing. MALDI identified 5 masses that were specific for epithelial cells. One particular mass was strongly related to presence of ERG fusion. In one prostate, we identified another mass that was present only in 2/35 tissue spots from the primary tumor as well as in 4/10 lymph nodes. Deep sequencing of different tumor areas of this case identified distinct patterns of structural genetic alterations. A cluster analysis showed that all samples were clonally related, and identified the area inside the primary tumor that gave rise to the metastases. In conclusion, these data suggest that MALDI imaging and next generation sequencing allow for identification of genetic and proteome patterns that correspond to metastatic spread of prostate cancer cells. A combination of both techniques is suited to dissect the genetic background of distinct MALDI signatures. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1272. doi:1538-7445.AM2012-1272

Mass Spectrometry Imaging (MSI) has evolved as an exciting technology that can be used to map lipids on tissue surfaces, with many research, industrial and clinical applications. A wide variety of lipids can be spatially localised in both positive and negative modes (e.g. highlighted in cancer, skin and brain) and ionisation approaches such as Matrix-Assisted Laser Desorption/Ionisation (MALDI), Secondary Ion Mass Spectrometry (SIMS) and Desorption Electrospray Ionisation (DESI) bring different strengths and weaknesses, including mass ranges and resolution, fragmentation profiles and spatial resolution. This chapter explores the technical differences of the ionisation types applied to lipid MSI, and offers insight into appropriate choices for spatially profiling specific lipid classes. Novel approaches to enhance ionisation through derivatisation, matrix chemistry and nanomaterials offer the potential to reveal a greater proportion of the lipidome. MSI offers opportunities to profile lipid classes, but in the absence of chromatography cannot yet confidently assign stereochemistry, a weakness that may be addressed using ion mobility. Advances in integrating ion mobility and improvements in handling the large datasets generated, in combination with current methodologies, offer exciting future opportunities to decipher the complex lipid patterns in health and disease.

Molecular imaging of atherosclerosis by Magnetic Resonance Imaging (MRI) has been impaired by a lack of validation of the specific substrate responsible for the molecular imaging signal. We therefore aimed to investigate the additive value of mass spectrometry imaging (MSI) of atherosclerosis-affine Gadofluorine P for molecular MRI of atherosclerotic plaques. Atherosclerotic Ldlr−/− mice were investigated by high-field MRI (7 T) at different time points following injection of atherosclerosis-affine Gadofluorine P as well as at different stages of atherosclerosis formation (4, 8, 16 and 20 weeks of HFD). At each imaging time point mice were immediately sacrificed after imaging and aortas were excised for mass spectrometry imaging: Matrix Assisted Laser Desorption Ionization (MALDI) Imaging and Laser Ablation – Inductively Coupled Plasma – Mass Spectrometry (LA-ICP-MS) imaging. Mass spectrometry imaging allowed to visualize the localization and measure the concentration of the MR imaging probe Gadofluorine P in plaque tissue ex vivo with high spatial resolution and thus adds novel and more target specific information to molecular MR imaging of atherosclerosis.

Simple SummaryFor the effective treatment of lung cancer patients, correct tumor subtyping is of utmost importance, but it is often challenging in clinical routine. Using artificial intelligence and combining information from digital microscopy and matrix-assisted laser desorption/ionization mass spectrometry imaging data have the potential to support the pathologist’s decision-making process. We present a classification algorithm to distinguish between adenocarcinoma and squamous cell carcinoma of the lung based on the automatic detection of tumor areas in whole tissue sections and the determination of the tumor subtype with high accuracy.Artificial intelligence (AI) has shown potential for facilitating the detection and classification of tumors. In patients with non-small cell lung cancer, distinguishing between the most common subtypes, adenocarcinoma (ADC) and squamous cell carcinoma (SqCC), is crucial for the development of an effective treatment plan. This task, however, may still present challenges in clinical routine. We propose a two-modality, AI-based classification algorithm to detect and subtype tumor areas, which combines information from matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) data and digital microscopy whole slide images (WSIs) of lung tissue sections. The method consists of first detecting areas with high tumor cell content by performing a segmentation of the hematoxylin and eosin-stained (H&E-stained) WSIs, and subsequently classifying the tumor areas based on the corresponding MALDI MSI data. We trained the algorithm on six tissue microarrays (TMAs) with tumor samples from N = 232 patients and used 14 additional whole sections for validation and model selection. Classification accuracy was evaluated on a test dataset with another 16 whole sections. The algorithm accurately detected and classified tumor areas, yielding a test accuracy of 94.7% on spectrum level, and correctly classified 15 of 16 test sections. When an additional quality control criterion was introduced, a 100% test accuracy was achieved on sections that passed the quality control (14 of 16). The presented method provides a step further towards the inclusion of AI and MALDI MSI data into clinical routine and has the potential to reduce the pathologist’s work load. A careful analysis of the results revealed specific challenges to be considered when training neural networks on data from lung cancer tissue.

One critical aspect of mass spectrometry imaging (MSI) is the need to confidently identify detected analytes. While orthogonal tandem MS (e.g., LC-MS2) experiments from sample extracts can assist in annotating ions, the spatial information about these molecules is lost. Accordingly, this could cause mislead conclusions, especially in cases where isobaric species exhibit different distributions within a sample. In this Technical Note, we employed a multimodal imaging approach, using matrix assisted laser desorption/ionization (MALDI)-MSI and liquid extraction surface analysis (LESA)-MS2I, to confidently annotate and localize a broad range of metabolites involved in a tripartite symbiosis system of moss, cyanobacteria, and fungus. We found that the combination of these two imaging modalities generated very congruent ion images, providing the link between highly accurate structural information onfered by LESA and high spatial resolution attainable by MALDI. These results demonstrate how this combined methodology could be very useful in differentiating metabolite routes in complex systems.

Ozone coupled with tandem mass spectrometry (MS/MS) is a traditional tool for assigning double bond positions in lipids.1 However, only a handful of studies utilizing ozone for double bond determination have been reported for bacterial lipids.2 Most MS-based double bond localization methods used in bacterial lipidomics focused on low-molecular-weight phospholipids, but were not applied to complex glycolipids, such as lipid A.2, 3 Here, we present a simple approach to identify double bond positions in fatty acyl chains in intact lipid A using ozone treatment followed by matrix-assisted laser desorption/ionization (MALDI) analysis. The ozone gas reacts selectively with the lipid A double bond without forming any side products. The MALDI analysis induces in-source fragmentation of the resulting lipid A ozonide derivatives, forming product ions diagnostic to the lipid A double bond location. Lipid A is one of the bacterial virulence factors contributing to pathogenicity of bacterial infections in mammals and plants. It is a glucosamine-based saccharolipid acylated by fatty acid chains. Lipid A can bind to Toll-like receptor-4 myeloid differentiation factor 2 complex (TLR-4/MD2) and initiate immune responses during infection.4 The binding of lipid A to TLR-4/MD2 greatly depends on the number, the length, and the degree of unsaturation of its fatty acyl chains. Since these attributes differ greatly between individual bacterial species, detailed characterizations of lipid A fatty acyl chains are essential for investigation of its structure–activity relationship. Conventionally, double bond positions of lipid A fatty acid chains have been determined using gas chromatography–mass spectrometry (GC/MS). This process requires a series of chemical reactions: complete hydrolysis of lipid A to release its fatty acid components, conversion of fatty acids to methyl esters, and derivatization with complex reagents such as 4,4-dimethyloxazoline, pyrrolidides, and dimethyl disulfide.5 Although powerful, the GC/MS method results in loss of information regarding the position of each fatty acid in the context of the lipid A structure.5 The ozone treatment was performed on two chemically synthesized monounsaturated lipid A molecules prepared in house: diphosphorylated hexa-acylated lipid A, BECC438s, and monophosphorylated hexa-acylated lipid A, BECC470s (Figure 1). These molecules were chemically synthesized using proprietary methods.6, 7 Also, they can be derived biologically from Yersinia pestis KIM6+ strains using bacterial enzymatic combinatorial chemistry (BECC) as described elsewhere.8, 9 The chemical structures of the lipid A standards were confirmed by highly accurate MS (~1 ppm) and MS/MS (~5 ppm) measurements using a Q Exactive HF orbitrap equipped with a Spectroglyph MALDI source (Spectroglyph, Kennewick, WA, USA, and Thermo Fisher, Waltham, MA, USA) (Figures 1 and 2). The ozone treatment was performed using the same apparatus setup previously used by Bednařík et al10 for on-tissue ozonization prior to MALDI imaging. The lipid A standards were analyzed before and after the ozone treatment, following application of norharmane matrix (10 mg/mL in 1:1 (v/v) acetonitrile–water). The analysis was performed in the negative ion mode using a timsTOF flex MALDI-2 instrument (Bruker, Bremen, Germany). BECC438s (m/z 1878.29; Figure 3A) contains six fatty acid chains (four 3-OH-C14:0, one C16:0, and one C16:1). The ozone gas (O3, 47.98 Da) reacted with the single double bond in the C16:1 chain forming the corresponding ozonide at m/z 1926.27 (1878.29 + 47.98). Subsequently, the MALDI laser induced the ozonide ring decomposition and formation of diagnostic product ions at m/z 1796.18 and m/z 1812.17 indicating that the double bond was located at C-9 (Figures 2 and 3B), as expected. The same strategy was also applied to BECC470s (m/z 1798.32; Figure 3C) leading to the formation of its expected corresponding ozonide (m/z 1846.31; Figure 3D) followed by its laser-induced decomposition to diagnostic ions at m/z 1716.21 and m/z 1732.20. Our future work will focus on utilizing the ozone treatment to analyze different mono- and polyunsaturated lipid A in complex mixtures and from different bacterial species. This will be done mainly through ozonization post fast lipid analysis technique (FLAT) described by Sorensen et al.11 Defining double bond positions in lipid A opens the way for new structure–activity relationship studies and understanding how the number of double bonds and their positions affect the lipid A binding affinity to TLR-4/MD2 and bacterial pathogenicity. Specifically, with this described method, we can now locate double bonds in the fatty acids of lipid A without the loss of position concomitant with hydrolysis required for GC/MS analysis. D.R.G and R.K.E thank the National Institutes of Health for grant R01 AI147314. The peer review history for this article is available at https://www.webofscience.com/api/gateway/wos/peer-review/10.1002/rcm.9854. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

The fast and univocal identification of different species in mixtures of pollen grains is still a challenge. Apart from microscopic evaluation and Raman spectroscopy, no other techniques are available. Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry was applied to the analysis of extracts of single pollen grains and pollen mixtures. Pollen grains were fixed, treated and covered with matrix directly on the MALDI target. Clearly resolved MALDI ion intensity images could be obtained enabling the identification of single pollen grains in a mixture. Our results demonstrate the potential and the suitability of MALDI imaging mass spectrometry as an additional method for the identification of pollen mixtures.

Here we report the development and optimization of a mass spectrometry imaging (MSI) platform that combines an atmospheric-pressure matrix-assisted laser desorption/ionization platform with plasma postionization (AP-MALDI-PPI) and trapped ion mobility spectrometry (TIMS). We discuss optimal parameters for operating the source, characterize the behavior of a variety of lipid classes in positive- and negative-ion modes, and explore the capabilities for lipid imaging using murine brain tissue. The instrument generates high signal-to-noise for numerous lipid species, with mass spectra sharing many similarities to those obtained using laser postionization (MALDI-2). The system is especially well suited for detecting lipids such as phosphatidylethanolamine (PE), as well as numerous sphingolipid classes and glycerolipids. For the first time, the coupling of plasma-based postionization with ion mobility is presented, and we show the value of ion mobility for the resolution and identification of species within rich spectra that contain numerous isobaric/isomeric signals that are not resolved in the m/z dimension alone, including isomeric PE and demethylated phosphatidylcholine lipids produced by in-source fragmentation. The reported instrument provides a powerful and user-friendly approach for MSI of lipids.

Mass spectrometry imaging (MSI) is a label free technique capable of providing simultaneous identification and localization of biomolecules. A multimodal approach is required that allows for the study of the complexity of biological tissue samples to overcome the limitations of a single MSI technique. Secondary ion mass spectrometry (SIMS) allows for high spatial resolution imaging while matrix-assisted laser desorption (MALDI) offers a significantly wider mass range. The combination of coregistered SIMS and MALDI images results in detailed and unique biomolecular information. In this Technical Note, we describe how gold sputtered/implanted fiducial markers (FM) are created and can be used to ensure a proper overlay and coregistration of the two-dimensional images provided by the two MSI modalities.