Mass spectrometry coupled to imaging techniques: the better the view the greater the challenge

Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.

Fatty Acid Unsaturation Degree of Plasma Exosomes in Colorectal Cancer Patients: A Promising Biomarker

Even though colorectal cancer (CRC) is one of the most preventable cancers, it is currently one of the deadliest. Worryingly, incidence in people <50 years has increased unexpectedly, and for unknown causes, despite the successful implementation of screening programs in the population aged >50 years. Thus, there is a need to improve early diagnosis detection strategies by identifying more precise biomarkers. In this scenario, the analysis of exosomes is given considerable attention. Previously, we demonstrated the exosome lipidome was able to classify CRC cell lines according to their malignancy. Herein, we investigated the use of the lipidome of plasma extracellular vesicles as a potential source of non-invasive biomarkers for CRC. A plasma exosome-enriched fraction was analyzed from patients undergoing colonoscopic procedure. Patients were divided into a healthy group and four pathological groups (patients with hyperplastic polyps; adenomatous polyps; invasive neoplasia (CRC patients); or hereditary non-polyposis CRC. The results showed a shift from 34:1- to 38:4-containing species in the pathological groups. We demonstrate that the ratio Σ34:1-containing species/Σ38:4-containing species has the potential to discriminate between healthy and pathological patients. Altogether, the results reinforce the utility of plasma exosome lipid fingerprint to provide new non-invasive biomarkers in a clinical context.

A Drastic Shift in Lipid Adducts in Colon Cancer Detected by MALDI-IMS Exposes Alterations in Specific K+ Channels

Even though colorectal cancer (CRC) is one of the most preventable cancers, it is one of the deadliest, and recent data show that the incidence in people <50 years has unexpectedly increased. While new techniques for CRC molecular classification are emerging, no molecular feature is as yet firmly associated with prognosis. Imaging mass spectrometry (IMS) lipidomic analyses have demonstrated the specificity of the lipid fingerprint in differentiating pathological from healthy tissues. During IMS lipidomic analysis, the formation of ionic adducts is common. Of particular interest is the [Na⁺]/[K⁺] adduct ratio, which already functions as a biomarker for homeostatic alterations. Herein, we show a drastic shift of the [Na⁺]/[K⁺] adduct ratio in adenomatous colon mucosa compared to healthy mucosa, suggesting a robust increase in K⁺ levels. Interrogating public databases, a strong association was found between poor diagnosis and voltage-gated potassium channel subunit beta-2 (KCNAB2) overexpression. We found this overexpression in three CRC molecular subtypes defined by the CRC Subtyping Consortium, making KCNAB2 an interesting pharmacological target. Consistently, its pharmacological inhibition resulted in a dramatic halt in commercial CRC cell proliferation. Identification of potential pharmacologic targets using lipid adduct information emphasizes the great potential of IMS lipidomic techniques in the clinical field.

The Lipidome Fingerprint of Longevity

Lipids were determinants in the appearance and evolution of life. Recent studies disclose the existence of a link between lipids and animal longevity. Findings from both comparative studies and genetics and nutritional interventions in invertebrates, vertebrates, and exceptionally long-lived animal species—humans included—demonstrate that both the cell membrane fatty acid profile and lipidome are a species-specific optimized evolutionary adaptation and traits associated with longevity. All these emerging observations point to lipids as a key target to study the molecular mechanisms underlying differences in longevity and suggest the existence of a lipidome profile of long life.

Defining Changes in the Spatial Distribution and Composition of Brain Lipids in the Shiverer and Cuprizone Mouse Models of Myelin Disease

Myelin is composed primarily of lipids and diseases affecting myelin are associated with alterations in its lipid composition. However, correlation of the spatial (in situ) distribution of lipids with the disease-associated compositional and morphological changes is not well defined. Herein we applied high resolution matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS), immunohistochemistry (IHC), and liquid chromatography–electrospray ionization–mass spectrometry (LC-ESI-MS) to evaluate brain lipid alterations in the dysmyelinating shiverer (Shi) mouse and cuprizone (Cz) mouse model of reversible demyelination. MALDI-IMS revealed a decrease in the spatial distribution of sulfatide (SHexCer) species, SHexCer (d42:2), and a phosphatidylcholine (PC) species, PC (36:1), in white matter regions like corpus callosum (CC) both in the Shi mouse and Cz mouse model. Changes in these lipid species were restored albeit not entirely upon spontaneous remyelination after demyelination in the Cz mouse model. Lipid distribution changes correlated with the local morphological changes as confirmed by IHC. LC-ESI-MS analyses of CC extracts confirmed the MALDI-IMS derived reductions in SHexCer and PC species. These findings highlight the role of SHexCer and PC in preserving the normal myelin architecture and our experimental approaches provide a morphological basis to define lipid abnormalities relevant to myelin diseases.

Lipidomics Reveals a Tissue-Specific Fingerprint

In biological systems lipids generate membranes and have a key role in cell signaling and energy storage. Therefore, there is a wide diversity of molecular lipid expressed at the compositional level in cell membranes and organelles, as well as in tissues, whose lipid distribution remains unclear. Here, we report a mass spectrometry study of lipid abundance across 7 rat tissues, detecting and quantifying 652 lipid molecular species from the glycerolipid, glycerophospholipid, fatty acyl, sphingolipid, sterol lipid and prenol lipid categories. Our results demonstrate that every tissue analyzed presents a specific lipid distribution and concentration. Thus, glycerophospholipids are the most abundant tissue lipid, they share a similar tissue distribution but differ in particular lipid species between tissues. Sphingolipids are more concentrated in the renal cortex and sterol lipids can be found mainly in both liver and kidney. Both types of white adipose tissue, visceral and subcutaneous, are rich in glycerolipids but differing the amount. Acylcarnitines are mainly in the skeletal muscle, gluteus and soleus, while heart presents higher levels of ubiquinone than other tissues. The present study demonstrates the existence of a rat tissue-specific fingerprint.

Macrophage-Bacteria Interactions-A Lipid-Centric Relationship

Macrophages are professional phagocytes at the front line of immune defenses against foreign bodies and microbial pathogens. Various bacteria, which are responsible for deadly diseases including tuberculosis and salmonellosis, are capable of hijacking this important immune cell type and thrive intracellularly, either in the cytoplasm or in specialized vacuoles. Tight regulation of cellular metabolism is critical in shaping the macrophage polarization states and immune functions. Lipids, besides being the bulk component of biological membranes, serve as energy sources as well as signaling molecules during infection and inflammation. With the advent of systems-scale analyses of genes, transcripts, proteins, and metabolites, in combination with classical biology, it is increasingly evident that macrophages undergo extensive lipid remodeling during activation and infection. Each bacterium species has evolved its own tactics to manipulate host metabolism toward its own advantage. Furthermore, modulation of host lipid metabolism affects disease susceptibility and outcome of infections, highlighting the critical roles of lipids in infectious diseases. Here, we will review the emerging roles of lipids in the complex host-pathogen relationship and discuss recent methodologies employed to probe these versatile metabolites during the infection process. An improved understanding of the lipid-centric nature of infections can lead to the identification of the Achilles' heel of the pathogens and host-directed targets for therapeutic interventions. Currently, lipid-moderating drugs are clinically available for a range of non-communicable diseases, which we anticipate can potentially be tapped into for various infections.

Sublimation of DAN Matrix for the Detection and Visualization of Gangliosides in Rat Brain Tissue for MALDI Imaging Mass Spectrometry

Sample preparation is key for optimal detection and visualization of analytes in Matrix-assisted Laser Desorption/Ionization (MALDI) Imaging Mass Spectrometry (IMS) experiments. Determining the appropriate protocol to follow throughout the sample preparation process can be difficult as each step must be optimized to comply with the unique characteristics of the analytes of interest. This process involves not only finding a compatible matrix that can desorb and ionize the molecules of interest efficiently, but also selecting the appropriate matrix deposition technique. For example, a wet matrix deposition technique, which entails dissolving a matrix in solvent, is superior for desorption of most proteins and peptides, whereas dry matrix deposition techniques are particularly effective for ionization of lipids. Sublimation has been reported as a highly efficient method of dry matrix deposition for the detection of lipids in tissue by MALDI IMS due to the homogeneity of matrix crystal deposition and minimal analyte delocalization as compared to many wet deposition methods ^1,2. Broadly, it involves placing a sample and powdered matrix in a vacuum-sealed chamber with the samples pressed against a cold surface. The apparatus is then lowered into a heated bath (sand or oil), resulting in sublimation of the powdered matrix onto the cooled tissue sample surface. Here we describe a sublimation protocol using 1,5-diaminonaphthalene (DAN) matrix for the detection and visualization of gangliosides in the rat brain using MALDI IMS.

Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS

Examination of tissue sections using desorption electrospray ionization (DESI)-MS revealed phospholipid-derived signals that differ between gray matter, white matter, gliomas, meningiomas, and pituitary tumors, allowing their ready discrimination by multivariate statistics. A set of lower mass signals, some corresponding to oncometabolites, including 2-hydroxyglutaric acid and N-acetyl-aspartic acid, was also observed in the DESI mass spectra, and these data further assisted in discrimination between brain parenchyma and gliomas. The combined information from the lipid and metabolite MS profiles recorded by DESI-MS and explored using multivariate statistics allowed successful differentiation of gray matter (n = 223), white matter (n = 66), gliomas (n = 158), meningiomas (n = 111), and pituitary tumors (n = 154) from 58 patients. A linear discriminant model used to distinguish brain parenchyma and gliomas yielded an overall sensitivity of 97.4% and a specificity of 98.5%. Furthermore, a discriminant model was created for tumor types (i.e., glioma, meningioma, and pituitary), which were discriminated with an overall sensitivity of 99.4% and a specificity of 99.7%. Unsupervised multivariate statistics were used to explore the chemical differences between anatomical regions of brain parenchyma and secondary infiltration. Infiltration of gliomas into normal tissue can be detected by DESI-MS. One hurdle to implementation of DESI-MS intraoperatively is the need for tissue freezing and sectioning, which we address by analyzing smeared biopsy tissue. Tissue smears are shown to give the same chemical information as tissue sections, eliminating the need for sectioning before MS analysis. These results lay the foundation for implementation of intraoperative DESI-MS evaluation of tissue smears for rapid diagnosis.

Optimized Protocol To Analyze Changes in the Lipidome of Xenografts after Treatment with 2-Hydroxyoleic Acid

Xenografts are a popular model for the study of the action of new antitumor drugs. However, xenografts are highly heterogeneous structures, and therefore it is sometimes difficult to evaluate the effects of the compounds on tumor metabolism. In this context, imaging mass spectrometry (IMS) may yield the required information, due to its inherent characteristics of sensitivity and spatial resolution. To the best of our knowledge, there is still no clear analysis protocol to properly evaluate the changes between samples due to the treatment. Here we present a protocol for the evaluation of the effect of 2-hydroxyoleic acid (2-OHOA), an antitumor compound, on xenografts lipidome based on IMS. Direct treated/control comparison did not show conclusive results. As we will demonstrate, a more sophisticated protocol was required to evaluate these changes including the following: (1) identification of different areas in the xenograft, (2) classification of these areas (necrotic/viable) to compare similar types of tissues, (3) suppression of the effect of the variation of adduct formation between samples, and (4) normalization of the variables using the standard deviation to eliminate the excessive impact of the stronger peaks in the statistical analysis. In this way, the 36 lipid species that experienced the largest changes between treated and control were identified. Furthermore, incorporation of 2-hydroxyoleic acid to a sphinganine base was also confirmed by MS/MS. Comparison of the changes observed here with previous results obtained with different techniques demonstrates the validity of the protocol.