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Lipids are involved in a wide range of biological processes and can be broadly classified into five categories based on their structural diversity: fatty acids, triacylglycerols (TAGs), phospholipids, sterol lipids, and sphingolipids1. The fundamental functions of lipids are to provide energy sources for biological processes (i.e., TAGs) and form cellular membranes (i.e., phospholipids and cholesterol). However, additional roles of lipids have been noted in development and diseases, and have been extensively studied in the biomedical field. For instance, reports have shown that fatty acids of different lengths may have unique therapeutic roles. Short fatty acid chains can be involved in defense mechanisms against autoimmune diseases, medium-length fatty acid chains produce metabolites that can mitigate seizures, and long fatty acid chains generate metabolites that can be used to treat metabolic disorders2. In the nervous system, glia-derived cholesterol and phospholipids have been shown to be vital for synaptogenesis3,4. Other types of lipids have shown promise in medical applications, including sphingolipids utilized in drug delivery systems and saccharolipids used to support the immune system5,6. The numerous roles and potential therapeutic applications of lipids in the biomedical field have made lipidomics—the study of the pathways and interactions of cellular lipids—a critical and increasingly important field.
Lipidomics makes use of analytical chemistry to study the lipidome on a large scale. The main experimental methods utilized in lipidomics are based on mass spectrometry (MS) coupled with various chromatography and ion-mobility techniques7,8. The use of MS in the area is advantageous due to its high specificity and sensitivity, speed of acquisition, and unique capabilities to (1) detect lipids and lipid metabolites occurring even at low and transient levels, (2) detect hundreds of different lipid compounds in a single experiment, (3) identify previously unknown lipids, and (4) distinguish between lipid isomers. Among the developments in MS, including desorption electrospray ionization (DESI), MALDI, and secondary ion mass spectrometry (SIMS), MALDI MSI has emerged as a powerful imaging technique that complements conventional MS-based approaches by providing unique information on the spatial distribution of lipids within tissue compartments9,10.
The typical workflow of lipidomics consists of sample preparation, data acquisition using mass-spectrometry technology, and data analysis11. The study of lipids and metabolites in samples has led to the emergence of techniques to understand the physiological and pathological conditions of metabolic processes in organisms. While understanding biological interactions is important, the sensitivity of lipids and metabolites makes them difficult to image and identify without dyes or other modification. Changes in metabolite levels or distribution may lead to phenotypic changes. One tool used for metabolomic profiling is MALDI MSI, a label-free, in situ imaging technique capable of detecting hundreds of molecules simultaneously. MALDI imaging allows for the visualization of metabolites and lipids in samples while preserving their integrity and spatial distribution. Previous technology for lipid profiling involved the use of radioactive chemicals to individually map lipids, while MALDI imaging forgoes this and allows for the detection of a range of lipids simultaneously.
Lipid metabolism and homeostasis play important functions in cell physiology, such as the maintenance and development of the nervous system. One essential aspect of nervous system lipid metabolism is the lipid shuttling between neurons and glial cells, which is mediated by molecular carrier lipoproteins, including very-low-density lipoprotein (VLDL), low-density lipoproteins (LDL), and high-density lipoproteins (HDL)12. Lipoproteins contain apolipoproteins (Apo), such as ApoB and ApoD, which function as structural blocks of lipid cargo and as ligands for lipoprotein receptors. The neuron-glia crosstalk of lipids involves multiple players such as glia-derived ApoD, ApoE, and ApoJ, and their neuronal LDL receptors (LDLRs)13,14. In Drosophila, apolipophorin, a member of the ApoB family, is a major hemolymph lipid carrier15. Apolipophorin has two closely related lipophorin receptors (LpRs), LpR1 and LpR2, which are homologs of mammalian LDLR15,16. In previous studies, the astrocyte-secreted lipocalin Glial Lazarillo (GLaz), a Drosophila homolog of human ApoD, and its neuronal receptor LpR1 were discovered to cooperatively mediate neuron-glia lipid shuttling, thus regulating dendrite morphogenesis17. Therefore, it was speculated that the loss of LpR1 would cause a decrease in overall lipid content in the Drosophila brain. MALDI MSI would be a suitable tool for profiling the lipid contents in small tissues of LpR1−/− mutant and wild-type Drosophila brains, as demonstrated in this study.
Despite the growing popularity of MALDI MSI, the instrument's high cost and experimental complexity often impede its implementation in individual laboratories. Thus, most MALDI MSI studies are conducted using shared core facilities. As with other applications of MALDI MSI, a careful sample preparation process for lipidomics is critical to achieve reliable results. However, because sample slide preparation is typically performed in individual research laboratories, there is a possibility of variation in MALDI MSI acquisition. To combat this, this paper aims to provide a detailed protocol for the sample preparation of small biological samples prior to MALDI MSI measurement using lipid analysis of a large group of adult Drosophila brains in positive ion mode as an example11,17. However, some phospholipid classes and the majority of small metabolites are favorably detected by MALDI imaging in negative ion mode, which was described previously11. Therefore, with these two example studies, we hope to provide detailed sample preparation protocols of various combinations: free-standing large tissue versus embedded small tissue, thaw-mounting versus warm-slide mounting, and positive ion mode versus negative ion mode.