Longitudinal monitoring of individual infection progression in Drosophila melanogaster

Bryan A Ramirez-Corona; Anna C Love; Srikiran Chandrasekaran; Jennifer A Prescher; Zeba Wunderlich

doi:10.1016/j.isci.2022.105378

Longitudinal monitoring of individual infection progression in Drosophila melanogaster

iScience. 2022 Oct 17;25(11):105378. doi: 10.1016/j.isci.2022.105378. eCollection 2022 Nov 18.

Authors

Bryan A Ramirez-Corona¹, Anna C Love², Srikiran Chandrasekaran³, Jennifer A Prescher^{2

4

5}, Zeba Wunderlich^{1

6

7}

Affiliations

¹ Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA92697, USA.
² Department of Chemistry, University of California, Irvine, Irvine, CA92697, USA.
³ Center for Complex Biological Sciences, University of California, Irvine, Irvine, CA92697, USA.
⁴ Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA92697, USA.
⁵ Department of Pharmaceutical Sciences, University of California, Irvine, Irvine, CA92697, USA.
⁶ Department of Biology, Boston University, Boston, MA02215, USA.
⁷ Biological Design Center, Boston University, Boston, MA02215, USA.

Abstract

The innate immune system is critical for infection survival. Drosophila melanogaster is a key model for understanding the evolution and dynamics of innate immunity. Current toolsets for fly infection studies are limited in throughput and, because of their destructive nature, cannot generate longitudinal measurements in individual animals. We report a bioluminescent imaging strategy enabling non-invasive characterization of pathogen load. By using Escherichia coli expressing the ilux operon, we demonstrate that photon flux from autobioluminescent bacteria can be used to monitor pathogen loads in individual, living flies. Because animal sacrifice is not necessary to estimate pathogen load, stochastic responses to infection can be characterized in individuals over time. The high temporal resolution of bioluminescence imaging enables visualization of the dynamics of microbial clearance on the hours time-scale. This non-invasive imaging strategy provides a simple and scalable platform to observe changes in pathogen load in vivo over time.

Keywords: Microbiology; Optical imaging.