An integrated eco-evolutionary framework to predict population-level responses of climate-sensitive pathogens
Campbell, Amy M. (Centre for Environment, Fisheries and Aquaculture Science)
Hauton, Chris (University of Southampton. School of Ocean and Earth Science)
Baker-Austin, Craig (Centre for Environment, Fisheries and Aquaculture Science)
van Aerle, Ronny (Centre for Environment, Fisheries and Aquaculture Science)
Martinez-Urtaza, Jaime (Universitat Autònoma de Barcelona. Departament de Genètica i de Microbiologia)

Date:	2023
Abstract:	It is critical to gain insight into how climate change impacts evolutionary responses within climate-sensitive pathogen populations, such as increased resilience, opportunistic responses and the emergence of dominant variants from highly variable genomic backgrounds and subsequent global dispersal. This review proposes a framework to support such analysis, by combining genomic evolutionary analysis with climate time-series data in a novel spatiotemporal dataframe for use within machine learning applications, to understand past and future evolutionary pathogen responses to climate change. Recommendations are presented to increase the feasibility of interdisciplinary applications, including the importance of robust spatiotemporal metadata accompanying genome submission to databases. Such workflows will inform accessible public health tools and early-warning systems, to aid decision-making and mitigate future human health threats.
Grants:	Agencia Estatal de Investigación PID2021-127107NB-I00
Note:	Altres ajuts: acords transformatius de la UAB
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Published in:	Current opinion in biotechnology, Vol. 80 (April 2023) , art. 102898, ISSN 1879-0429

DOI: 10.1016/j.copbio.2023.102898

9 p, 1.9 MB

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