Automated microinjection for zebrafish xenograft models

Abstract

Zebrafish xenograft models have been increasingly recognized for their ability to predict patient responses to cancer therapeutics, suggesting their potential as diagnostic tools in clinical settings. However, these models require the precise microinjection of cancer cell suspensions in many small and fragile zebrafish larvae. Manual injections are so challenging that, even after months of training, variability in experimental results persists among researchers. This limits the uptake and deployment of zebrafish xenograft models for clinical use and drug discovery. To address this challenge, we have designed, built, and validated an automated microinjection robot. Combined results of injections into the vasculature, perivitelline space, and hindbrain demonstrated an average injection success rate of approximately 60%, with a larvae survival rate exceeding 70%, comparable to manual injections using a traditional micromanipulator. Notably, the full automated mode was twice as fast as manual injections. This automation of the microinjection process significantly reduces the need for extensive personnel training while it enhances reproducibility, efficiency, and accuracy, paving the way for more extensive use of zebrafish xenograft models in drug discovery and patient diagnostics.