Development of Automated Exosome Isolation Method Using EGCG-Modified Magnetic Beads: Standardized Protocols for Diverse Biofluids

국문 초록 (Abstract)

엑소좀은 세포 간 신호 전달에 핵심적인 역할을 하는 30–150 nm 크기의 세포외 소포로, 비침습적 액체 생검을 위한 바이오마커로서 큰 잠재력을 지니고 있습니다. 그러나 기존의 엑소좀 분리 기술은 낮은 수율, 높은 비용, 시간 소모 등 여러 한계를 가지고 있습니다.
본 연구에서는 혈장, 혈청, 소변, 타액 등 다양한 생체액에 최적화된 EGCG-변형 자성 비드(EGCG@T)를 활용한 새로운 자동화 엑소좀 분리 방법을 제시합니다. EGCG:T-Fe₃O₄ 비율(0.1:1), 결합 시간, 용출 조건, 추출 완충액 조성 등 주요 조건을 생체액 유형별로 체계적으로 최적화하였습니다. 최종 개발된 프로토콜은 Nextractor® NX-Junior 플랫폼에 통합되어, 엑소좀 분리와 단백질 추출을 단일 단계로 자동화할 수 있었습니다.
Western blot 및 ELISA 분석 결과, EGCG@T 방법은 기존의 PEG 침전법 대비 엑소좀 표지 단백질(CD9, CD63, CD81, TSG101, ALIX)의 회수율이 유의하게 높았으며, 이는 생체액 종류에 따라 다르게 나타났습니다. 특히, CD63 양성 엑소좀은 소변에서 약 2배, 타액에서는 약 1.3배 더 높은 효율로 분리되었습니다.
이러한 결과는 엑소좀이 생체액별로 상이한 물리화학적 특성을 지님에 따라, 효과적인 엑소좀 분리를 위해 생체액 특이적 최적화가 필수적임을 시사합니다. 본 자동화된 고효율 엑소좀 분리 기술은 향후 비침습적 질병 진단 및 모니터링을 위한 액체 생검 기반 임상 응용에 있어 유용한 플랫폼으로 활용될 수 있습니다.

다국어 초록 (Multilingual Abstract)

Exosomes are extracellular vesicles of 30-150 nm that play crucial roles in intercellular communication and hold significant potential as biomarkers for non-invasive liquid biopsy. However, current isolation methods face limitations including time-consumption, low yield, and high cost. This study presents a novel automated exosome isolation method using EGCG-modified magnetic beads (EGCG@T) optimized for diverse biofluids including plasma, serum, urine, and saliva. We systematically investigated optimal conditions for EGCG:T-Fe₃O₄ ratio (0.1:1), binding time, elution parameters, and extraction buffer composition for each biofluid type. The developed protocol was successfully integrated into an automated workflow using the Nextractor® NX-Junior platform, combining exosome isolation and protein extraction into a single step. Western blot and ELISA analyses confirmed that the EGCG@T method yielded significantly higher recovery of exosomal markers (CD9, CD63, CD81, TSG101, ALIX) compared to conventional PEG precipitation, with the efficiency varying depending on the biofluid. Notably, CD63-positive exosomes were isolated with approximately two-fold higher efficiency from urine and 1.3-fold higher from saliva using the EGCG@T method. Our findings demonstrate biofluid-specific optimization is essential for effective exosome isolation, as exosome subpopulations exhibit distinct physicochemical properties across different sample types. This automated, rapid, and efficient exosome isolation method provides a valuable platform for future clinical applications in non-invasive disease diagnosis and monitoring through liquid biopsy.

목차 (Table of Contents)

• CHAPTER 1. INTRODUCTION 1
• CHAPTER 2. MATERIALS AND METHODS 8
• 2.1 EGCG-Modified Magnetic Beads (EGCG@T). 8
• 2.1.1 Synthesis and Characterization of EGCG-Modified Magnetic Beads (EGCG@T) 8
• 2.1.2 Preparation of Magnetic Bead+EGCG. 8
• 2.2 Optimization of Exosome Isolation and Protein Extraction Using EGCG+Bead 9
• 2.2.1 Optimization of Magnetic Bead+EGCG Complex Concentration 9
• 2.2.2 Optimization of Exosome Isolation and Protein Extraction Using EGCG+Bead. 10
• 2.2.3 Exosome Isolation from Multiple Biofluids Using EGCG-Modified Magnetic Beads 11
• 2.2.3.1 Plasma exosome isolation 11
• 2.2.3.2 Serum exosome isolation 11
• 2.2.3.3 Urine exosome isolation. 11
• 2.2.3.4 Saliva exosome isolation. 11
• 2.2.4 Optimization of Protein Extraction Buffer Composition 12
• 2.3 Application of Reagents to the NX-Jr Instrument 12
• 2.3.1 Application of Reagents to the NX-Jr Instrument 12
• 2.3.2 Assessment of Exosome Marker Proteins via Western Blot 13
• 2.3.3 Enzyme-Linked Immunosorbent Assay (ELISA) 13
• CHAPTER 3. RESULTS 15
• 3.1 Surface Morphological Analysis of Magnetic Beads Before and After EGCG Modification. 15
• 3.2 Fourier Transform Infrared Spectroscopy (FT-IR) Analysis of EGCG-Modified Magnetic Beads 16
• 3.3 UVVis Spectral Analysis of EGCG-Modified Magnetic Beads 17
• 3.4 Effect of EGCG Concentration on Surface Morphology, Elemental Composition, and Colloidal Properties of Magnetic Beads 19
• 3.5 Optimization of Magnetic Bead+EGCG Complex Concentration: Comparative Efficiency Analysis 21
• 3.6 Optimization of Exosome Isolation Conditions from Various Biological Specimens. 23
• 3.6.1 Optimization of Exosome Isolation from Urine Samples 23
• 3.6.2 Optimization of Exosome Isolation from Plasma Samples. 25
• 3.6.3 Optimization of Exosome Isolation from Serum Samples 27
• 3.7 Optimization of Protein Extraction Buffer 29
• 3.8 Automated Exosome Isolation: Evaluation of Buffer Systems Using the NX-Jr Platform 31
• 3.8.1 Optimization of Exosome Isolation from Urine Samples 31
• 3.8.2 Optimization of Exosome Isolation from Plasma Samples 33
• 3.8.3 Optimization of Exosome Isolation from Serum Samples 35
• 3.8.4 Optimization of Exosome Isolation from Saliva Samples. 37
• 3.9 Automated Exosome Isolation: Comparative Analysis of Exosomal Marker Expression Profiles in Exosomes Isolated from Urine, Saliva, Plasma, and Serum Using Western Blotting. 40
• 3.10 Comparative Analysis of CD63 Expression in Exosomes Isolated from Urine, Saliva, Plasma, and Serum Samples Using Different Methods 42
• 3.11 Identification of protein biomarkers in isolated blood-derived exosomes 45
• 3.11.1 Identification of previously known proteins in exosomes from the blood of pancreatic cancer patients. 45
• 3.11.2 Proteomic Validation of Exosome Isolation from Pancreatic Cancer Patient Plasma 46
• 3.11.3 Cell Type Deconvolution and Clustering Analysis of Plasma-Derived Exosomal Proteins in Pancreatic Cancer Patients. 47
• 3.11.4 Validation of protein analysis method in acquired exosomes 49
• 3.11.5 Comparison of pancreatic cancer patient blood and blood-derived exosome proteome analysis. 50
• CHAPTER 4. DISCUSSION 53
• CHAPTER 5. CONCLUSION 59
• REFERENCES. 60