2026. 08.19 (수) ~ 2026. 08.21 (금)
창원컨벤션센터(CECO)
| | 한국질량분석학회 여름학술대회 및 총회 Brief Oral Presentaionof Selected Posters | |
| 제목 | Glycome-Based Multi-Omics Profiling Reveals a Molecular Framework for Brain Organoid Maturation |
|---|---|
| 작성자 | 정수민 (충남대학교 분석과학기술대학원) |
| 발표구분 | 포스터발표 |
| 발표분야 | 4. Medical / Pharmaceutical Science |
| 발표자 |
정수민 (분석과학기술대학원) |
| 주저자 | 정수민 (분석과학기술대학원) |
| 교신저자 |
안현주 (분석과학기술대학원) |
| 저자 |
정수민 (분석과학기술대학원) 백주희 (분석과학기술대학원) 오명진 (분석과학기술대학원) 안현주 (분석과학기술대학원) |
|
Brain organoids are promising preclinical models that recapitulate key structural and functional features of the human brain, but their reliable application requires objective evaluation of developmental state. Current evaluation mainly relies on morphological, transcriptomic, and proteomic analyses, whereas glycosylation, a key regulator of neural differentiation and synaptic maturation, remains comparatively underexplored. This study applied glycome-based multi-omics analyses to brain organoids collected at sequential stages over a four-month culture period, using nanoLC-Q-TOF-MS for N-glycomic profiling and nanoLC-Orbitrap-MS for proteomic and N-glycoproteomic analyses. N-glycomic profiling revealed a progressive increase in glycan diversity, reflecting gradual acquisition of glycan features characteristic of brain tissue. Proteomic analysis supported this maturation, with enrichment shifting from proliferative processes to neuronal and synaptic function over time. N-glycoproteomic analysis linked these changes to specific glycoproteins for integrated interpretation. Notably, the immunogenic glycans Neu5Gc and alpha-Gal, not present in normal human tissue, increased with prolonged culture, suggesting incorporation of exogenous glycans from culture media. Collectively, these findings establish a molecular framework for evaluating brain organoid maturation through integrated glycomic, glycoproteomic, and proteomic analyses. Furthermore, the identification of immunogenic glycans highlights the importance of glycosylation-based quality assessment in disease modeling and preclinical applications. |
|