Identification of reactive <i>Borrelia burgdorferi</i> peptides associated with Lyme disease
Serology is the primary method of Lyme disease diagnosis, but this approach has limitations, particularly early in disease. Currently employed antibody detection assays can be improved by the identification of alternative immunodominant epitopes and the selection of optimal diagnostic targets. We employed high-density peptide arrays that enabled precise epitope mapping for a wide range of <i>B. burgdorferi</i> antigens. In combination with machine learning, this approach facilitated the selection of serologic targets early in disease and the identification of serological indicators associated with different manifestations of Lyme disease. This study provides insights into differential antibody responses during infection and outlines a new approach for improved serologic diagnosis of Lyme disease.
Authors
- Cheng Guo (ORCID: https://orcid.org/0000-0002-6602-8810)
- Adriana Marques (ORCID: https://orcid.org/0000-0002-5403-4551)
- Rafal Tokarz (ORCID: https://orcid.org/0000-0001-7108-668X)
- Elizabeth J. Horn (ORCID: https://orcid.org/0000-0001-5928-9652)
- Siu Ping Turk
- Santiago Sánchez-Vicente (ORCID: https://orcid.org/0000-0002-4193-4251)
- Walter Ian Lipkin (ORCID: https://orcid.org/0000-0002-8768-9386)
- Aleah Eschman
Institutions
- National Institutes of Health (US)
- National Institute of Allergy and Infectious Diseases (US)
- Columbia University (US)
Publication Details
- Journal
- mBio
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1128/mbio.02360-24
- Citations
- 7
- Primary Topic
- Vector-borne infectious diseases
- Type
- article
- Field-Weighted Citation Impact
- 3.61
Funders
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases
- Global Lyme Alliance
- Steven and Alexandra Cohen Foundation
- National Institutes of Health
- National Institute of Allergy and Infectious Diseases
- NHLBI Division of Intramural Research