Region-Specific Proteomic Profiling of Brain Interstitial Fluid via a Micro-invasive Sampling Platform

Abstract

Interstitial fluid (ISF) within the brain parenchyma contains secreted factors related to brain function, metabolism, and neurodegenerative disorders. Cerebrospinal fluid (CSF) is commonly sampled due to its accessibility in well-defined spaces, but it does not fully capture the diversity of the brain secreted proteome. The brain is remarkably heterogeneous on a millimeter scale or smaller, and the secreted proteome likely reflects that heterogeneity. Traditional methods like cerebral microdialysis suffer from recovery loss and tissue damage due to semipermeable membranes and large probe sizes. This study develops a micro-invasive, membrane-free platform for ISF sampling, enabling mass spectrometry analysis of small sample volumes with high spatial resolution and minimal tissue damage. Also, this platform collects samples within approximately 15 minutes, representing a major reduction in sampling time compared to microdialysis. We analyzed proteomic profiles of ISF from the nucleus accumbens and substantia nigra, revealing significant differences in protein abundance and composition indicative of their biological functions. We also compared ISF with CSF and found significantly more proteins associated with brain-specific functions, such as synaptic transmission and vesicle-mediated transport. This novel ISF sampling method can enhance clinical liquid biopsy techniques for brain diseases and provides insights into distinct molecular profiles of different brain regions.

Supplementary files

Article information

Article type
Paper
Submitted
13 Jan 2026
Accepted
30 Mar 2026
First published
13 Apr 2026
This article is Open Access
Creative Commons BY license

Lab Chip, 2026, Accepted Manuscript

Region-Specific Proteomic Profiling of Brain Interstitial Fluid via a Micro-invasive Sampling Platform

Q. Cao, H. D. Jackson, A. J. Duncan, Y. Cui, H. O. Higginbotham, S. Lesnik, Y. Jo, J. Yu, F. White and M. J. Cima, Lab Chip, 2026, Accepted Manuscript , DOI: 10.1039/D6LC00038J

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