Back to Search Start Over

Impedance-Based Microfluidic Assay for Automated Antischistosomal Drug Screening.

Authors :
Chawla K
Modena MM
Ravaynia PS
Lombardo FC
Leonhardt M
Panic G
Bürgel SC
Keiser J
Hierlemann A
Source :
ACS sensors [ACS Sens] 2018 Dec 28; Vol. 3 (12), pp. 2613-2620. Date of Electronic Publication: 2018 Nov 28.
Publication Year :
2018

Abstract

Schistosomiasis is a neglected tropical disease, caused by parasitic worms, which affects almost 200 million people worldwide. For over 40 years, chemotherapeutic treatment has relied on the administration of praziquantel, an efficacious drug against schistosomiasis. However, concerns about developing drug resistance require the discovery of novel drug compounds. Currently, the drug-screening process is mostly based on the visual evaluation of drug effects on worm larvae in vitro by a trained operator. This manual process is extremely labor-intensive, has limited throughput, and may be affected by subjectivity of the operator evaluation. In this paper, we introduce a microfluidic platform with integrated electrodes for the automated detection of worm larvae viability using an impedance-based approach. The microfluidic analysis unit consists of two sets of electrodes and a channel of variable geometry to enable counting and size detection of single parasite larvae and the collective evaluation of the motility of the larvae as an unbiased estimator for their viability. The current platform also allows for multiplexing of the analysis units resulting in increased throughput. We used our platform to record size and motility variations of Schistosoma mansoni larvae exposed to different concentrations of mefloquine, a drug with established in vitro antischistosomal properties. The developed platform demonstrates the potential of integrated microfluidic platforms for high-throughput antischistosomal drug screening.

Details

Language :
English
ISSN :
2379-3694
Volume :
3
Issue :
12
Database :
MEDLINE
Journal :
ACS sensors
Publication Type :
Academic Journal
Accession number :
30426744
Full Text :
https://doi.org/10.1021/acssensors.8b01027