Conference Abstract | Volume 8, Abstract ELIC2025152 (Poster 063) | Published:  05 Aug 2025

A comprehensive phylogenomic study of Lassa virus evolution leveraging novel computational approaches

Klaps Joon1,&, Wulff Thomas2, Thielebein Anke2, Wildtraut Robert2, Hinrichs Mette2, Müller Jonas2, Hinzman Jule2, Wozniak David2, Oestereich Lisa2, Okoeguaele Joseph3, Ogbaini-Emovon Ephraim3, Günther Stephan2, Lemey Philippe1, Durrafour Sophie2,*, Kafetzopoulou Liana2,*, Erameh Cyril3,*

* Co-shared last authors

1Rega Institute, KU Leuven, Leuven, Belgium, 2Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany, 3Irrua Specialist Teaching Hospital, Irrua, Edo State, Nigeria

&Corresponding author: Klaps Joon, Rega Institute, KU Leuven, Leuven, Belgium Email: joon.klaps@kuleuven.be

Received: 11 Apr 2025, Accepted: 09 Jul 2025, Published: 05 Aug 2025

Domain: Infectious Disease Epidemiology

This is part of the Proceedings of the ECOWAS 2nd Lassa fever International Conference in Abidjan, September 8 – 11, 2025

Keywords: intrahost evolution, nf-core/viralmetagenome, viral persistence, hybridisation capture sequencing, phylogenomics

©Klaps Joon et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article: Klaps Joon et al., A comprehensive phylogenomic study of Lassa virus evolution leveraging novel computational approaches. Journal of Interventional Epidemiology and Public Health. 2025;8(Conf Proc 5):00207. https://doi.org/10.37432/JIEPH-CONFPRO5-00207

Introduction

Lassa fever (LF), an endemic viral hemorrhagic fever in West Africa, presents a significant public health burden. Understanding Lassa virus (LASV) evolution, particularly at the intrahost level, is crucial for addressing challenges related to disease severity and viral persistence. Our project addresses these gaps by developing and applying novel computational infrastructure and a new hybridization capture-based sequencing library for advanced LASV genomic analysis, especially for samples with low viral loads.

Methods

We will analyze LASV-positive diagnostic samples from the Irrua Specialist Teaching Hospital (ISTH), Nigeria (2018-2022), with associated metadata. To acquire data across the full spectrum of viral loads, we will utilize both metagenomic sequencing and further develop our hybridization capture-based protocol. Deep sequencing will be performed on samples from different bodily fluids at multiple time points. Our analysis will focus on characterizing the genetic composition and intrahost evolution of LASV. These diverse sequencing data are processed within our publicly available computational workflow, viralgenie, a novel bioinformatics pipeline designed to overcome limitations of standard viral sequencing analyses.

Results

This study will deliver a detailed characterization of LASV intrahost populations’ genetic makeup and evolution. We expect to gain insights into how selection pressures, including immune escape, shape LASV evolution within different patient groups and bodily fluids. Preliminary work on sequencing approaches for diverse viral loads is ongoing to support these detailed intrahost analyses.

Conclusion

In conclusion, by combining our enhanced sequencing efforts, including the optimized hybridization capture protocol, with our novel computational approaches and large available patient metadata, we anticipate obtaining an unprecedented comprehensive LASV genomic dataset. This will facilitate insights into Lassa adaptation, immune evasion mechanisms, and their contribution to infection outcome and persistence.

 
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