Development of a sequence-based in silico OspA typing method for Borrelia burgdorferi sensu lato

Author:

Lee Jonathan T.1,Li Zhenghui1,Nunez Lorna D.1,Katzel Daniel2,Perrin Jr. B. Scott2,Raghuraman Varun1,Rajyaguru Urvi1,Llamera Katrina E.1,Andrew Lubomira1,Anderson Annaliesa S.1,Hovius Joppe W.3,Liberator Paul A.1,Simon Raphael1,Hao Li1ORCID

Affiliation:

1. Vaccine Research and Development, Pfizer, Inc., Pearl River, NY, 10965, USA

2. Pfizer Digital, Pfizer, Inc., Pearl River, NY, 10965, USA

3. Amsterdam University Medical Centers (UMC), location Academic Medical Center (AMC), Department of Internal Medicine, Division of Infectious Diseases, Center for Experimental and Molecular Medicine, Amsterdam Institute for Immunology and Infectious Diseases, University of Amsterdam, Amsterdam, Netherlands

Abstract

Lyme disease (LD), caused by spirochete bacteria of the genus Borrelia burgdorferi sensu lato, remains the most common vector-borne disease in the northern hemisphere. Borrelia outer surface protein A (OspA) is an integral surface protein expressed during the tick cycle, and a validated vaccine target. There are at least 20 recognized Borrelia genospecies, that vary in OspA serotype. This study presents a new in silico sequence-based method for OspA typing using next-generation sequence data. Using a compiled database of over 400 Borrelia genomes encompassing the 4 most common disease-causing genospecies, we characterized OspA diversity in a manner that can accommodate existing and new OspA types and then defined boundaries for classification and assignment of OspA types based on the sequence similarity. To accommodate potential novel OspA types, we have developed a new nomenclature: OspA in silico type (IST). Beyond the ISTs that corresponded to existing OspA serotypes 1–8, we identified nine additional ISTs that cover new OspA variants in B. bavariensis (IST9–10), B. garinii (IST11–12), and other Borrelia genospecies (IST13–17). The IST typing scheme and associated OspA variants are available as part of the PubMLST Borrelia spp. database. Compared to traditional OspA serotyping methods, this new computational pipeline provides a more comprehensive and broadly applicable approach for characterization of OspA type and Borrelia genospecies to support vaccine development.

Funder

Pfizer

Publisher

Microbiology Society

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