Deterministic Evolution of Aptamers via a Microfluidic-Integrated Robotic Platform Using Complex Exosomes as Targets.

Area of Science:

• Biotechnology
• Biomarker Discovery
• Molecular Diagnostics

Background:

• Exosome (EXO) membrane proteins are valuable biomarkers for liquid biopsy.
• Antibody-based reagents face challenges due to exosome heterogeneity.
• Traditional aptamer selection (SELEX) is complicated by the small size and separation difficulties of exosomes.

Purpose of the Study:

• To develop an automated system for efficient exosome-targeted aptamer selection.
• To overcome the limitations of manual SELEX for nanosized exosomes.
• To create a practical framework for aptamer discovery in liquid biopsy applications.

Main Methods:

• Introduction of DREAMbot: a robotic platform integrating microfluidics for automated aptamer selection.
• Utilized deterministic lateral displacement sorting and lipid-assisted magnetic isolation for exosome purification.
• Executed multiround aptamer selection with minimal human intervention.

Main Results:

• DREAMbot automated the selection and recovery of exosome-binding aptamers.
• The system demonstrated faithful aptamer enrichment, reducing hands-on time compared to manual SELEX.
• Identified aptamers with nanomolar dissociation constants and high specificity for GPC3-positive exosomes from cell cultures and human serum.

Conclusions:

• DREAMbot provides an automated, efficient, and accessible solution for aptamer discovery against exosomes.
• The robotic-microfluidic platform facilitates biomarker identification for liquid biopsy.
• This technology addresses key challenges in exosome-based diagnostics.