Health trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome.

2.50
Hdl Handle:
http://hdl.handle.net/10033/592857
Title:
Health trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome.
Authors:
Lough, Graham; Kyriazakis, Ilias; Bergmann, Silke; Lengeling, Andreas; Doeschl-Wilson, Andrea B
Abstract:
Resistance and tolerance are two alternative strategies hosts can adopt to survive infections. Both strategies may be genetically controlled. To date, the relative contribution of resistance and tolerance to infection outcome is poorly understood. Here, we use a bioluminescent Listeria monocytogenes (Lm) infection challenge model to study the genetic determination and dynamic contributions of host resistance and tolerance to listeriosis in four genetically diverse mouse strains. Using conventional statistical analyses, we detect significant genetic variation in both resistance and tolerance, but cannot capture the time-dependent relative importance of either host strategy. We overcome these limitations through the development of novel statistical tools to analyse individual infection trajectories portraying simultaneous changes in infection severity and health. Based on these tools, early expression of resistance followed by expression of tolerance emerge as important hallmarks for surviving Lm infections. Our trajectory analysis further reveals that survivors and non-survivors follow distinct infection paths (which are also genetically determined) and provides new survival thresholds as objective endpoints in infection experiments. Future studies may use trajectories as novel traits for mapping and identifying genes that control infection dynamics and outcome. A Matlab script for user-friendly trajectory analysis is provided.
Affiliation:
Helmholtz Centre for Infection Research, Inhoffenstr.7, 28124 Braunschweig, Germany.
Citation:
Health trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome. 2015, 282 (1819): Proc. Biol. Sci.
Journal:
Proceedings. Biological sciences / The Royal Society
Issue Date:
22-Nov-2015
URI:
http://hdl.handle.net/10033/592857
DOI:
10.1098/rspb.2015.2151
PubMed ID:
26582028
Type:
Article
Language:
en
ISSN:
1471-2954
Appears in Collections:
publications of the department infection genetics (INFG)

Full metadata record

DC FieldValue Language
dc.contributor.authorLough, Grahamen
dc.contributor.authorKyriazakis, Iliasen
dc.contributor.authorBergmann, Silkeen
dc.contributor.authorLengeling, Andreasen
dc.contributor.authorDoeschl-Wilson, Andrea Ben
dc.date.accessioned2016-01-05T15:08:50Zen
dc.date.available2016-01-05T15:08:50Zen
dc.date.issued2015-11-22en
dc.identifier.citationHealth trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome. 2015, 282 (1819): Proc. Biol. Sci.en
dc.identifier.issn1471-2954en
dc.identifier.pmid26582028en
dc.identifier.doi10.1098/rspb.2015.2151en
dc.identifier.urihttp://hdl.handle.net/10033/592857en
dc.description.abstractResistance and tolerance are two alternative strategies hosts can adopt to survive infections. Both strategies may be genetically controlled. To date, the relative contribution of resistance and tolerance to infection outcome is poorly understood. Here, we use a bioluminescent Listeria monocytogenes (Lm) infection challenge model to study the genetic determination and dynamic contributions of host resistance and tolerance to listeriosis in four genetically diverse mouse strains. Using conventional statistical analyses, we detect significant genetic variation in both resistance and tolerance, but cannot capture the time-dependent relative importance of either host strategy. We overcome these limitations through the development of novel statistical tools to analyse individual infection trajectories portraying simultaneous changes in infection severity and health. Based on these tools, early expression of resistance followed by expression of tolerance emerge as important hallmarks for surviving Lm infections. Our trajectory analysis further reveals that survivors and non-survivors follow distinct infection paths (which are also genetically determined) and provides new survival thresholds as objective endpoints in infection experiments. Future studies may use trajectories as novel traits for mapping and identifying genes that control infection dynamics and outcome. A Matlab script for user-friendly trajectory analysis is provided.en
dc.language.isoenen
dc.titleHealth trajectories reveal the dynamic contributions of host genetic resistance and tolerance to infection outcome.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Centre for Infection Research, Inhoffenstr.7, 28124 Braunschweig, Germany.en
dc.identifier.journalProceedings. Biological sciences / The Royal Societyen

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