An Image-Based Algorithm for Precise and Accurate High Throughput Assessment of Drug Activity against the Human Parasite Trypanosoma cruzi

• Published in: PloS one Vol. 9; no. 2; p. e87188
• Main Authors: Moon, Seunghyun, Siqueira-Neto, Jair L., Moraes, Carolina Borsoi, Yang, Gyongseon, Kang, Myungjoo, Freitas-Junior, Lucio H., Hansen, Michael A. E.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 04.02.2014; Public Library of Science (PLoS)
• Subjects: Algorithms; Animals; Automation; Benznidazole; Biology; Blood & organ donations; Blood transfusions; Cell Nucleus - drug effects; Cell Nucleus - metabolism; Chemical compounds; Computer Science; Cytoplasm; Cytotoxicity; Deoxyribonucleic acid; Disease; DNA; Drug Evaluation, Preclinical; Drugs; Engineering; Health aspects; High-throughput screening; High-Throughput Screening Assays - methods; Humans; Image databases; Image detection; Image Processing, Computer-Assisted; Infection; Infections; Inspection; Laboratories; Mathematical functions; Mathematics; Nifurtimox; Nuclei; Nuclei (cytology); Parameter estimation; Parasites; Parasites - cytology; Parasites - drug effects; Parasitic Sensitivity Tests; Protozoa; Reproducibility of Results; Screening; Statistical analysis; Titration; Toxicity; Tropical diseases; Trypanocidal Agents - analysis; Trypanocidal Agents - pharmacology; Trypanosoma cruzi; Trypanosoma cruzi - cytology; Trypanosoma cruzi - drug effects
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0087188

We present a customized high content (image-based) and high throughput screening algorithm for the quantification of Trypanosoma cruzi infection in host cells. Based solely on DNA staining and single-channel images, the algorithm precisely segments and identifies the nuclei and cytoplasm of mammalian host cells as well as the intracellular parasites infecting the cells. The algorithm outputs statistical parameters including the total number of cells, number of infected cells and the total number of parasites per image, the average number of parasites per infected cell, and the infection ratio (defined as the number of infected cells divided by the total number of cells). Accurate and precise estimation of these parameters allow for both quantification of compound activity against parasites, as well as the compound cytotoxicity, thus eliminating the need for an additional toxicity-assay, hereby reducing screening costs significantly. We validate the performance of the algorithm using two known drugs against T.cruzi: Benznidazole and Nifurtimox. Also, we have checked the performance of the cell detection with manual inspection of the images. Finally, from the titration of the two compounds, we confirm that the algorithm provides the expected half maximal effective concentration (EC50) of the anti-T. cruzi activity.