title: Large-scale microfluidics providing high-resolution and high-throughput screening of Caenorhabditis elegans poly-glutamine aggregation model.
abstract: Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ∼4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ∼100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ∼1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.
authors.affiliation: Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Sudip
authors.initials: S
authors.lastname: Mondal
authors.affiliation: Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Evan
authors.initials: E
authors.lastname: Hegarty
authors.affiliation: Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Chris
authors.initials: C
authors.lastname: Martin
authors.affiliation: Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Sertan Kutal
authors.initials: SK
authors.lastname: Gökçe
authors.affiliation: Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.|Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Navid
authors.initials: N
authors.lastname: Ghorashian
authors.affiliation: Department of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.|Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.|Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, Texas 78712, USA.|The Institute for Neuroscience, The University of Texas at Austin, Austin, Texas 78712, USA.
authors.forename: Adela
authors.initials: A
authors.lastname: Ben-Yakar
mesh_terms: D000818:Animals; D001331:Automation; D017173:Caenorhabditis elegans / Q000378:metabolism*; D004195:Disease Models, Animal; D017277:Drug Approval; D004353:Drug Evaluation, Preclinical; D057166:High-Throughput Screening Assays / Q000379:methods*; D021621:Imaging, Three-Dimensional; D044085:Microfluidics / Q000379:methods*; D008954:Models, Biological; D010455:Peptides / Q000737:chemistry*; D066329:Protein Aggregates; D015203:Reproducibility of Results; D014481:United States; D014486:United States Food and Drug Administration
chemical_list: D010455:Peptides; D066329:Protein Aggregates; C097188:polyglutamine