Identification of malaria parasite-infected red blood cell surface aptamers by inertial microfluidic SELEX (I-SELEX)
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Author(s)
Birch, Christina M.
Hou, Han Wei
Han, Jongyoon
Niles, Jacquin
Date Issued
July 2015
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Birch, Christina M., Han Wei Hou, Jongyoon Han, and Jacquin C. Niles. “Identification of Malaria Parasite-Infected Red Blood Cell Surface Aptamers by Inertial Microfluidic SELEX (I-SELEX).” Scientific Reports 5 (July 1, 2015): 11347.
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Final published version
Abstract
Plasmodium falciparum malaria parasites invade and remodel human red blood cells (RBCs) by trafficking parasite-synthesized proteins to the RBC surface. While these proteins mediate interactions with host cells that contribute to disease pathogenesis, the infected RBC surface proteome remains poorly characterized. Here we use a novel strategy (I-SELEX) to discover high affinity aptamers that selectively recognize distinct epitopes uniquely present on parasite-infected RBCs. Based on inertial focusing in spiral microfluidic channels, I-SELEX enables stringent partitioning of cells (efficiency ≥ 10[superscript 6]) from unbound oligonucleotides at high volume throughput (~2 × 10[superscript 6] cells min[superscript −1]). Using an RBC model displaying a single, non-native antigen and live malaria parasite-infected RBCs as targets, we establish suitability of this strategy for de novo aptamer selections. We demonstrate recovery of a diverse set of aptamers that recognize distinct, surface-displayed epitopes on parasite-infected RBCs with nanomolar affinity, including an aptamer against the protein responsible for placental sequestration, var2CSA. These findings validate I-SELEX as a broadly applicable aptamer discovery platform that enables identification of new reagents for mapping the parasite-infected RBC surface proteome at higher molecular resolution to potentially contribute to malaria diagnostics, therapeutics and vaccine efforts.
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/srep11347
