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Updated: Jun 11, 2025
Sample Preparation for Endopeptidomic Analysis in Human Cerebrospinal Fluid
Published on: December 4, 2017
Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer
Christian Mirian1,2, Ole Østergaard2, Maria Thastrup1
1Department of Paediatrics and Adolescent Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark.
Insights
Optimizing proteome analysis of pediatric cerebrospinal fluid (CSF) enables deeper biomarker discovery. This enhanced workflow maximizes protein identification from limited samples, aiding pediatric central nervous system malignancy research.
Area of Science:
- Proteomics
- Biomarker Discovery
- Pediatric Oncology
Background:
- Cerebrospinal fluid (CSF) is crucial for pediatric central nervous system malignancy biomarkers.
- Challenges include wide protein concentration ranges, age-related differences, and limited sample volume.
- Pediatric CSF samples are often scarce and prioritized for clinical use.
Purpose of the Study:
- To optimize a proteome analysis workflow for pediatric CSF.
- To maximize protein identification from limited CSF volumes for research.
- To enhance biomarker discovery for pediatric central nervous system malignancies.
Main Methods:
- Sequential ultracentrifugation to enrich extracellular vesicles (EVs).
- Optimization of CSF input volume, digestion, gradient length, and data acquisition.
- Application of protein aggregation capture (PAC) digestion and data-independent acquisition (DIA).
Main Results:
- Quantification of 1351 proteins from 400 μL raw CSF with EV enrichment.
- Increased protein identification to 2103 using a spectral library.
- The optimized workflow identified 2989 unique proteins from 400 μL CSF, a 340% increase over raw CSF analysis.
Conclusions:
- An optimized proteomic workflow significantly increases protein identification in pediatric CSF.
- This method maximizes information from limited CSF samples, supporting biomarker discovery.
- The enhanced workflow aids research into pediatric central nervous system malignancies.
Abstract:
The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.
