A High-Throughput Method for Quantifying Drosophila Fecundity

Author:

Gomez Andreana1,Gonzalez Sergio23,Oke Ashwini45ORCID,Luo Jiayu23,Duong Johnny B.36,Esquerra Raymond M.36,Zimmerman Thomas367ORCID,Capponi Sara37ORCID,Fung Jennifer C.458ORCID,Nystul Todd G.1458ORCID

Affiliation:

1. Department of Anatomy, University of California, San Francisco, CA 94143, USA

2. Department of Biology, San Francisco State University, San Francisco, CA 94132, USA

3. Center for Cellular Construction, San Francisco, CA 94158, USA

4. OB/GYN Department, University of California, San Francisco, CA 94143, USA

5. Center for Reproductive Sciences, University of California, San Francisco, CA 94143, USA

6. Department of Chemistry and Biochemistry, San Francisco State University, San Francisco, CA 94132, USA

7. IBM Almaden Research Center, San Jose, CA 95120, USA

8. San Francisco EaRTH Center, University of California, San Francisco, CA 94143, USA

Abstract

The fruit fly, Drosophila melanogaster, is an experimentally tractable model system that has recently emerged as a powerful “new approach methodology” (NAM) for chemical safety testing. As oogenesis is well conserved at the molecular and cellular level, measurements of Drosophila fecundity can be useful for identifying chemicals that affect reproductive health across species. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another, the RoboCam, a low-cost, custom-built robotic camera to capture images of the wells automatically, and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth). In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high-throughput egg-laying assays that require exposing flies to multiple different media conditions.

Funder

Bloomington Drosophila Stock Center

National Institute of General Medical Sciences

CALEPA

National Institute of Environmental Health Sciences

National Institute of Child Health and Human Development

National Science Foundation

Publisher

MDPI AG

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