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Biology subjects

Goba, A.

Publications and source records attributed to Goba, A..

2 recordsLinked to original sources

Predicting the evolution of Lassa Virus endemic area and population at risk over the next decades

Lassa fever is listed among the diseases that pose the greatest risks to public health by the World Health Organization. This severe viral hemorrhagic fever is caused by Lassa virus, a zoonotic pathogen that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate change, transformations in land use, and human population growth could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. We project that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in areas suitable for Lassa virus may grow from about 100 million to 700 million by 2070. By analysing geotagged viral genomes, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades. Our results highlight how the endemic area of Lassa virus may expand well beyond West Africa in the next decades due to human impact on the environment, putting hundreds of million more people at risk of infection.

microbiology↗

Capturing diverse microbial sequence with comprehensive and scalable probe design

Metagenomic sequencing has the potential to transform microbial detection and characteri zation, but new tools are needed to improve its sensitivity. We developed CATCH (Compact Aggregation of Targets for Comprehensive Hybridization), a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs compact probe sets that achieve full coverage of known sequence diversity and that scale well with this diversity. To illustrate applications of CATCH, we focused on capturing viral genomes. We designed, synthesized, and validated multiple probe sets, including one that targets whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriched unique viral content on average 18x and allowed us to assemble genomes that we could not otherwise recover, while accurately preserving within-sample diversity. We used this approach to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of viral infections in samples with unknown content. Together, this work demonstrates a path toward more sensitive, cost-effective metagenomic sequencing.

genomics↗