Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales

PeerJ

article

Kathrin Näpflin¹  Emily A. O’Connor²  Lutz Becks³  Staffan Bensch²  Vincenzo A. Ellis²  Nina Hafer-Hahmann⁴  Karin C. Harding⁶  Sara K. Lindén⁸  Morten T. Olsen⁹  Jacob Roved²  Timothy B. Sackton^1,10  Allison J. Shultz^1,11  Vignesh Venkatakrishnan⁸  Elin Videvall²  Helena Westerdahl²  Jamie C. Winternitz⁴  Scott V. Edwards¹ 

[1] Department of Organismic and Evolutionary Biology and Museum of Comparative Zoology, Harvard University;Molecular Ecology and Evolution Lab, Department of Biology, Lund University;Aquatic Ecology and Evolution, Limnological Institute University Konstanz;Department of Evolutionary Ecology, Max Planck Institute for Evolutionary Biology;EAWAG, Swiss Federal Institute of Aquatic Science and Technology;Department of Biological and Environmental Sciences, University of Gothenburg;Gothenburg Centre for Advanced Studies in Science and Technology, Chalmers University of Technology and University of Gothenburg;Department of Medical Chemistry and Cell Biology, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg;Section for Evolutionary Genomics, Natural History Museum of Denmark, Department of Biology, University of Copenhagen;Informatics Group, Harvard University;Ornithology Department;Center for Conservation Genomics, Smithsonian Conservation Biology Institute, National Zoological Park;Department of Animal Behaviour, Bielefeld University

关键词: Plasmodium;    MHC;    Immunotoxins;    Mucus;    Natural selection;    GWAS;    Infectious diseases;    Anthropogenic stressors;    Co-evolution;    Epidemiological surveillance;   

DOI  :  10.7717/peerj.8013

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

【 授权许可】

CC BY