An adaptable platform for in-house hepatitis C serology

Jannie Pedersen, Irène Pegha Moukandja, Stella Ndidi, Anna Louise Sørensen, Ismaël Hervé Koumakpayi, Jean Bernard Lekana-Douki, Marie Louise Vachon, Nina Weis, Gary Kobinger, Hugues Fausther-Bovendo

Research output: Contribution to journalArticlepeer-review


Serology-based diagnosis remains one of the major tools for diagnosis and surveillance of infectious diseases. However, for many neglected diseases no or only few commercial assays are available and often with prices prohibiting large scale testing in low and middle-income countries (LMICs). We developed an adaptable enzyme-linked immunoassay (ELISA) using hepatitis C virus (HCV) as a proof-of-concept application. By combining the maltose-binding-protein with a multiepitope HCV protein, we were able to obtain a high concentration of protein suitable for downstream applications. Following optimization, the assay was verified using previously tested human samples from Canada, Denmark and Gabon in parallel with the use of a commercial protein. Sensitivity and specificity were calculated to 98 % and 97 % respectively, after accounting for non-specific binding and assay optimization. This study provides a thorough description of the development, and validation of a multiepitope ELISA-based diagnostic assay against HCV, which could be implemented at low cost. The described methodology can be readily adapted to develop novel ELISA-based diagnostic assays for other infectious pathogens with well-described immunogenic epitopes. This method could improve the diagnosis of neglected diseases for which affordable diagnostic assays are lacking.

Original languageEnglish (US)
Article number114586
JournalJournal of Virological Methods
StatePublished - Oct 2022
Externally publishedYes


  • Hepatitis C virus
  • Maltose binding protein
  • Non-specific binding

ASJC Scopus subject areas

  • Virology


Dive into the research topics of 'An adaptable platform for in-house hepatitis C serology'. Together they form a unique fingerprint.

Cite this