Deterministic Ratchet for Sub-micrometer (Bio)particle Separation

Resolving the heterogeneity of particle populations by size is important when the particle size is a signature of abnormal biological properties leading to disease. Accessing size heterogeneity in the sub-micrometer regime is particularly important to resolve populations of subcellular species or di...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2018-04, Vol.90 (7), p.4370-4379
Main Authors: Kim, Daihyun, Luo, Jinghui, Arriaga, Edgar A, Ros, Alexandra
Format: Article
Language:English
Subjects:
Animals
Beads
Biological properties
Chemistry
Heterogeneity
Liposomes
Liposomes - chemistry
Liposomes - isolation & purification
Liver
Mathematical models
Mice
Microfluidic Analytical Techniques
Migration
Mitochondria
Mitochondria, Liver - chemistry
Organelles
Organelles - chemistry
Particle Size
Populations
Separation
Surface Properties
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Summary:Resolving the heterogeneity of particle populations by size is important when the particle size is a signature of abnormal biological properties leading to disease. Accessing size heterogeneity in the sub-micrometer regime is particularly important to resolve populations of subcellular species or diagnostically relevant bioparticles. Here, we demonstrate a ratchet migration mechanism capable of separating sub-micrometer sized species by size and apply it to biological particles. The phenomenon is based on a deterministic ratchet effect, is realized in a microfluidic device, and exhibits fast migration allowing separation in tens of seconds. We characterize this phenomenon extensively with the aid of a numerical model allowing one to predict the speed and resolution of this method. We further demonstrate the deterministic ratchet migration with two sub-micrometer sized beads as model system experimentally as well as size-heterogeneous mouse liver mitochondria and liposomes as model system for other organelles. We demonstrate excellent agreement between experimentally observed migration and the numerical model.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.7b03774