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Longitudinal monitoring of individual infection progression in Drosophila melanogaster

Bryan A. Ramirez-Corona, View ORCID ProfileAnna C. Love, View ORCID ProfileSrikiran Chandrasekaran, View ORCID ProfileJennifer A. Prescher, View ORCID ProfileZeba Wunderlich
doi: https://doi.org/10.1101/2021.08.17.456698
Bryan A. Ramirez-Corona
1Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, United States
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Anna C. Love
2Department of Chemistry, University of California, Irvine, Irvine, CA, United States
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Srikiran Chandrasekaran
3Center for Complex Biological Sciences, University of California, Irvine, CA, USA
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Jennifer A. Prescher
2Department of Chemistry, University of California, Irvine, Irvine, CA, United States
4Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA, United States
5Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA, United States
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Zeba Wunderlich
1Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, United States
6Department of Biology, Boston University, Boston, MA, United States
7Biological Design Center, Boston University, Boston, MA, United States
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  • For correspondence: zeba@bu.edu
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Abstract

The innate immune system is critical for host survival of infection. Infection models in organisms like Drosophila melanogaster are key for understanding evolution and dynamics of innate immunity. However, current toolsets for fly infection studies are limited in their ability to resolve changes in pathogen load on the hours time-scale, along with stochastic responses to infection in individuals. Here we report a novel bioluminescent imaging strategy enabling non-invasive characterization of pathogen load over time. We demonstrate that photon flux from autobioluminescent reporter bacteria can be used to estimate pathogen count. Escherichia coli expressing the ilux operon were imaged in whole, living flies at relevant concentrations for immune study. Because animal sacrifice was not necessary to estimate pathogen load, stochastic responses to infection were characterized in individuals for the first time. The high temporal resolution of bioluminescence imaging also enabled visualization of the fine dynamics of microbial clearance on the hours time-scale. Overall, this non-invasive imaging strategy provides a simple and scalable platform to observe changes in pathogen load in vivo over time.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted August 17, 2021.
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Longitudinal monitoring of individual infection progression in Drosophila melanogaster
Bryan A. Ramirez-Corona, Anna C. Love, Srikiran Chandrasekaran, Jennifer A. Prescher, Zeba Wunderlich
bioRxiv 2021.08.17.456698; doi: https://doi.org/10.1101/2021.08.17.456698
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Longitudinal monitoring of individual infection progression in Drosophila melanogaster
Bryan A. Ramirez-Corona, Anna C. Love, Srikiran Chandrasekaran, Jennifer A. Prescher, Zeba Wunderlich
bioRxiv 2021.08.17.456698; doi: https://doi.org/10.1101/2021.08.17.456698

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