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Challenges and solutions to developing an automated high‐throughput/high‐content screening platform for the ‘neglected’ schistosome parasite
Author(s) -
Caffrey Conor,
Chen Steven,
Suzuki Brian,
Singh Rahul,
Arkin Michelle
Publication year - 2016
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.30.1_supplement.lb475
Subject(s) - parasite hosting , computer science , identification (biology) , drug discovery , instrumentation (computer programming) , throughput , scalability , interface (matter) , computational biology , biology , bioinformatics , ecology , database , world wide web , operating system , bubble , maximum bubble pressure method , wireless
Automated high‐throughput (HT) and/or high‐content (HC) screening platforms are now well‐established in early drug discovery, including for many parasitic organisms causing ‘neglected tropical diseases.’ However, for the helminth (worm) parasites responsible for a range of globally prevalent and debilitating infections, such systems are still in their infancy. Using the schistosome, a flatworm parasite that infects over 200 million people, as a particularly challenging example, we developed an HTS/HCS platform to quantify the parasite's responses to chemical insult. I will highlight the hurdles encountered to standardize the preparation and handling of the parasite, and how we interfaced the parasite with an automated instrumentation environment. I will then discuss the approaches taken regarding image acquisition, object segmentation and tracking, and feature extraction. We tested the platform with seven anti‐schistosomal drugs to measure a range of static and dynamic parasite responses as a function of time and concentration. We designed a user interface to visualize and interrogate the data, which are maintained in a customized database. We combined the high‐dimensional data into a single metric output suitable for primary first‐pass screening: data from screening campaigns of high‐value small molecule collections will be presented. The new platform increases throughput, improves rigor and will support the identification of drugs, drug targets and mechanisms of action. Support or Funding Information Supported by NIH R01AI089896 and R21AI107390.