OR19-06 State-of-the-art MALDI Mass Spectrometry Imaging Reveals Unique Spatial Lipid Signatures in Human and Mouse Ovarian Compartments
Authors: Pascuali Natalia , Tobias Fernando , Valyi-Nagy Klara , Salih Sana , Veiga-Lopez Almudena 
Published: October 2023

Abstract
Disclosure: N. Pascuali: None. F. Tobias: None. K. Valyi-Nagy: None. S. Salih: None. A. Veiga-Lopez: None.
The incidence of infertility has been consistently increasing over the past few decades, with a high proportion of these cases caused by ovarian-related dysfunction. Metabolic disorders such as hyper- or dyslipidemia have been associated with subfertility (e.g., follicular fluid dyslipidemia is associated with lower IVF success). Lipids play a critical role in the structure and function of ovarian tissue. However, while several studies have investigated transcript- and protein-level alterations in ovarian pathologies, less is known about alterations in the lipid landscape. The first step in determining if ovarian disorders are associated with ovarian dyslipidemia - and thus use lipids as potential biomarkers of ovarian pathology - is to understand the physiological distribution of ovarian lipids. Matrix-Assisted Laser Desorption Ionization Time-Of-Flight (MALDI-TOF) mass spectrometry imaging (MSI) enables label-free in situ analysis of molecules such as lipids and metabolites directly within tissue sections. We aimed to begin mapping the distribution of lipids in human and mouse ovaries using high spatial resolution MALDI MSI. To this end, and after informed consent, two fresh ovarian biopsies from a 26-year-old patient were frozen, cryosectioned into 10-μm sections, and mounted onto ITO-coated slides. A set of 21-day-old mouse ovaries (n=10) were gelatin-embedded and cryosectioned. Slides were sprayed with 1,5-diaminonaphthalene as the matrix. MALDI MSI was performed using a Bruker RapifleX MALDI Tissuetyper (20-μm resolution) in the negative ion mode. Data were processed using the SCiLS Lab software. We identified for the first time in human ovaries over 100 lipid species, with most of them displaying distinct spatial distributions. Specifically, we detected 3 lipids specific to theca cells (m/z: 701.6; 1050.8; 1263.9), 6 lipids specific to granulosa cells (m/z: 279.3; 697.5; 861.7; 883.7; 911.7; 1448.0), 3 lipids specific to the stromal region (m/z 392.1; 753.5; 835.7), and one specific to luteal cells (m/z: 615.3). As for mouse ovaries, we detected 5 lipids specific to follicular cells (theca or granulosa) (m/z: 327.1: 343.2; 552.6; 632.6; 703.5), 5 lipids specific to stromal cells (m/z: 715.6; 729.6; 743.6; 771.7; 799.6), 5 lipids specific to oocytes (m/z: 778.5; 863.7; 1063.8; 1225.7; 1336.0) and 7 lipids specific to the ovarian cortex (m/z: 721.5; 748.5; 776.6; 792.6; 810.6; 869.6; 885.7). To our knowledge, this is the first evaluation of the human ovarian lipidome and characterization of region- or cell-layer-specific lipids. This approach has allowed us to demonstrate that compartments as small as oocytes (∼70 μm in diameter) have a unique lipid signature. Harnessing the unique specificity of the lipid signature per ovarian region and/or cell layer in this study could help pave the way to develop novel biomarkers of ovarian dysfunction.
Presentation Date: Saturday, June 17, 2023