Sequential infection experiments for quantifying innate and adaptive immunity during influenza infection

AWC Yan; SG Zaloumis; JA Simpson; JM McCaw

Journal article

Sequential infection experiments for quantifying innate and adaptive immunity during influenza infection

AWC Yan, SG Zaloumis, JA Simpson, JM McCaw

Plos Computational Biology | PUBLIC LIBRARY SCIENCE | Published : 2019

DOI: 10.1371/journal.pcbi.1006568

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Abstract

Laboratory models are often used to understand the interaction of related pathogens via host immunity. For example, recent experiments where ferrets were exposed to two influenza strains within a short period of time have shown how the effects of cross-immunity vary with the time between exposures and the specific strains used. On the other hand, studies of the workings of different arms of the immune response, and their relative importance, typically use experiments involving a single infection. However, inferring the relative importance of different immune components from this type of data is challenging. Using simulations and mathematical modelling, here we investigate whether the sequent..

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University of Melbourne Researchers

Sophie Zaloumis Author

Julie Simpson Author

James McCaw Author

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Grants

Awarded by National Health and Medical Research Council

Funding Acknowledgements

AWCY is supported by an Australian Postgraduate Award (now Australian Government Research Training Program Scholarship), an Albert Shimmins Postgraduate Writing-up Award, and a Wellcome Trust Collaborator Award (UK, grant 200187/Z/15/Z). SGZ is funded by an Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) Fellowship (grant 170100785). JAS is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship (grant 1104975). This research was supported by the ARC (grant DP170103076) and the NHMRC Centre of Research Excellence (grant 1058804). Computational support for this research was provided by Melbourne Bioinformaticsat the University of Melbourne (grant VR0274), and the National eResearch Collaboration Tools and Resources (NeCTAR) Project. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.