CEEPC/IPM/CMSC - Abstrakt prezentace

(CEEPC/IPM/CMSC 2022 - FrO-19)
Characterization of glycosphingolipids in iPSC-derived cerebral organoids and its application in neurodegenerative disorders

Durga Jha 1, Tereza Váňová 2,3, Dáša Bohačiaková 2,3, Zdeněk Spáčil 1 *

  1. RECETOX, Faculty of Science, Masaryk University, Brno, Czech Republic
  2. Dept. of Histology and Embryology, Faculty of Medicine, Masaryk University, Brno, Czech Republic
  3. International Clinical Research Center (ICRC), St. Anne’s University Hospital, Brno, Czech Republic

Abstrakt

Gangliosides are sialylated glycosphingolipids, highly abundant in the neuronal lipid membrane. Utilizing 3D cerebral models, like cerebral organoids (COs), can provide an opportunity to understand the role of these lipids in aging and neurodegenerative diseases. The study aimed to develop a novel UHPLC/ SRM method for identifying eight sub-classes of gangliosides with information on the composition of fatty acid composition and the sphingoid bases for each sub-class. The method was applied to understand the effect of known risk factors of Alzheimer's disease on these lipids, such as apolipoprotein E and secretases. More than 70 gangliosides were identified in the cerebral organoids. In the organoids, fatty acids were characterized by a prevalence of chain lengths in sizes from C14 to C22. Overall the profiles of different chain length lipids were similar within the same sub-class of gangliosides.
Interestingly the C16 and C18 fatty acids were present in the highest concentrations in the organoids, in contrast to C18 and C20, which are more abundant in an aging human brain. There was a global upregulation in the level of gangliosides in the presence of ApoE4. A similar effect was observed in the treatment of these organoids with secretases. This method can be helpful for the analysis of healthy and neuropathological changes associated with aging and neurodegenerative diseases in the cerebral organoids.

* Korespondující autor: spacil@recetox.muni.cz

Poděkování:

This work was supported by GAMU project No. MUNI/G/1131/2017 and MUNI/A/1382/2019, AZV project No. NV19-08-00472 and NU21-08-00373, MEYS, LM2018121, Horizon2020, 857560 and MEYS, 02.1.01/0.0/0.0/18_046/0015975, GACR no. 18-25429Y, GA20-15728S, and 21-21510S, and Project INBIO (No. CZ.02.1.01/0.0/0.0/16_026/0008451).


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