No abstract

No abstract

No abstract

In this study, we report the development of a dual extraction protocol for RNA and lipids, including phospholipids, endocannabinoids, and arachidonic acid, at high spatial resolution, e.g., brain punches obtained from whole frozen brains corresponding to four brain subregions: dorsal hippocampus, ventral hippocampus, basolateral amygdala, and hypothalamus. This extraction method combined with LC/multiple reaction monitoring for lipid quantifi-cation and quantitative PCR for RNA investigation allows lipidomic and transcriptomic profiling from submilligram amounts of tissue, thus benefiting the time and animal costs for analysis and the data reliability due to prevention of biological variability between animal batches and/or tissue heterogeneity, as compared with profiling in distinct animal batches. Moreover, the method allows a higher extraction efficiency and integrity preservation for RNA, while allowing concurrently quantitative analysis of low and high abundant lipids. The method was applied for brain punches obtained 1 h after kainic acid-induced epileptic seizures in mice (n = 10) compared with controls (n = 10), and enabled the provision of valuable new insights into the subregional lipid and RNA changes with epilepsy, highlighting its potential as a new viable tool in quantitative neurobiology.

Mass spectrometry imaging (MSI) enables the visualization of molecular distributions on complex surfaces. It has been extensively used in the field of biomedical research to investigate healthy and diseased tissues. Most of the MSI studies are conducted in a 2D fashion where only a single slice of the full sample volume is investigated. However, biological processes occur within a tissue volume and would ideally be investigated as a whole to gain a more comprehensive understanding of the spatial and molecular complexity of biological samples such as tissues and cells. Mass spectrometry imaging has therefore been expanded to the 3D realm whereby molecular distributions within a 3D sample can be visualized. The benefit of investigating volumetric data has led to a quick rise in the application of single-sample 3D-MSI investigations. Several experimental and data analysis aspects need to be considered to perform successful 3D-MSI studies. In this review, we discuss these aspects as well as ongoing developments that enable 3D-MSI to be routinely applied to multi-sample studies.