Refining Platelet Purification Methods: Enhancing Proteomics for Clinical Applications
Background: Platelet proteomics offers valuable insights for clinical research, yet isolating high-purity platelets remains a challenge. Current methods often lead to contamination or platelet loss, compromising data quality and reproducibility. Objectives: This study aimed to optimize a platelet isolation technique that yields high-purity samples with minimal loss and to identify the most effective mass spectrometry-based proteomic method for analyzing platelet proteins with optimal coverage and sensitivity. Methods: We refined an isolation protocol by adjusting centrifugation time to reduce blood volume requirements while preserving platelet yield and purity. Using this optimized method, we evaluated three proteomic approaches: Label-free Quantification with Data-Independent Acquisition (LFQ-DIA), Label-free Quantification with Data-Dependent Acquisition (LFQ-DDA), and Tandem Mass Tag labeling with DDA (TMT-DDA). Results: LFQ-DIA demonstrated superior protein coverage and sensitivity compared to LFQ-DDA and TMT-DDA. The refined isolation protocol effectively minimized contamination and platelet loss. Additionally, age-related differences in platelet protein composition were observed, highlighting the importance of using age-matched controls in biomarker discovery studies. Conclusions: The optimized platelet isolation protocol provides a cost-effective and reliable method for preparing high-purity samples for proteomics. LFQ-DIA is the most suitable approach for comprehensive platelet protein analysis. Age-related variation in platelet proteomes underscores the need for demographic matching in clinical proteomic research.
Code (0)
등록된 구현이 없습니다.
Tasks
SensitivityTAGSimilar Papers 제목 키워드 기반
Phenome-wide causal proteomics enhance systemic lupus erythematosus flare prediction: A study in Asian populations
Objective: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by unpredictable flares. This study aimed to develop a novel proteomics-based risk prediction model specifically for Asian SLE p…
2kManagementMapping Differential Protein-Protein Interaction Networks using Affinity Purification Mass Spectrometry
Proteins congregate into complexes to perform fundamental cellular functions. Phenotypic outcomes, in health and disease, are often mechanistically driven by the remodeling of protein complexes by protein coding mutation…
Platelet enumeration in dense aggregates
Identifying and counting blood components such as red blood cells, various types of white blood cells, and platelets is a critical task for healthcare practitioners. Deep learning approaches, particularly convolutional n…
Semantic SegmentationDemand Forecasting for Platelet Usage: from Univariate Time Series to Multivariate Models
Platelet products are both expensive and have very short shelf lives. As usage rates for platelets are highly variable, the effective management of platelet demand and supply is very important yet challenging. The primar…
Demand ForecastingManagementregressionTime Series+1Tube into pearls: A membrane-driven pearling instability shapes platelet biogenesis
At the end of the 19th century, Rayleigh and Plateau explained the physical principle behind the fragmentation of a liquid jet into regular droplets commonly observed in everyday life from a faucet. The classical Rayleig…