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<p>Zebrafish (<i>Danio rerio</i>) larvae are optically transparent, small vertebrates that serve as an ideal model for in vivo high-throughput screening. However, automated high-throughput manipulation, imaging, and analysis of live zebrafish larvae remain considerable challenges. Moreover, it is critical to avoid damage to these delicate organisms because even minor injury can impair normal physiological function. To address these challenges, we developed a high-throughput manipulation platform that enables the loading of zebrafish larvae into glass tubes, enabling accurate localization and controlled rotation at a throughput of one fish every 15 s. The platform uses hydrodynamic methods, including a siphon-based system, as the primary driving mechanism to enable adaptive loading and unloading of zebrafish larvae while substantially reducing fluid pressure and minimizing potential flow-induced damage. In addition, the platform integrates machine vision to support automated control and data acquisition throughout the entire workflow. We developed a comprehensive suite of algorithms for automated image segmentation of zebrafish larval videos and three-dimensional (3D) reconstruction of their transparent structures and internal organs. Two distinct 3D reconstruction algorithm pipelines were designed: one is a computationally efficient, lightweight approach optimized for execution on conventional personal computers; the other is a high-speed rendering-based algorithm that requires large-memory computational resources to achieve reconstructions at the original image resolution. Notably, both approaches operate without requiring any additional user-defined parameter tuning. Finally, we demonstrate the platform’s capability by evaluating drug-induced inhibition of zebrafish melanogenesis. This automated platform expands the utility of zebrafish as a versatile, high-throughput model system, facilitating research across diverse fields, including developmental biology, disease modeling, and pharmaceutical and toxicological evaluation.</p>

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High-throughput automated manipulation and imaging analysis of zebrafish larvae

  • 期刊论文

  • 发表日期：

    2026年6月20日

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  • Yangning Li,
  • Shang Wu,
  • Xuanyu Zhang,
  • Haina Ji,
  • Yi Wang,
  • Yuan Sun,
  • Lu Zhao,
  • Yong He

摘要

Zebrafish (Danio rerio) larvae are optically transparent, small vertebrates that serve as an ideal model for in vivo high-throughput screening. However, automated high-throughput manipulation, imaging, and analysis of live zebrafish larvae remain considerable challenges. Moreover, it is critical to avoid damage to these delicate organisms because even minor injury can impair normal physiological function. To address these challenges, we developed a high-throughput manipulation platform that enables the loading of zebrafish larvae into glass tubes, enabling accurate localization and controlled rotation at a throughput of one fish every 15 s. The platform uses hydrodynamic methods, including a siphon-based system, as the primary driving mechanism to enable adaptive loading and unloading of zebrafish larvae while substantially reducing fluid pressure and minimizing potential flow-induced damage. In addition, the platform integrates machine vision to support automated control and data acquisition throughout the entire workflow. We developed a comprehensive suite of algorithms for automated image segmentation of zebrafish larval videos and three-dimensional (3D) reconstruction of their transparent structures and internal organs. Two distinct 3D reconstruction algorithm pipelines were designed: one is a computationally efficient, lightweight approach optimized for execution on conventional personal computers; the other is a high-speed rendering-based algorithm that requires large-memory computational resources to achieve reconstructions at the original image resolution. Notably, both approaches operate without requiring any additional user-defined parameter tuning. Finally, we demonstrate the platform’s capability by evaluating drug-induced inhibition of zebrafish melanogenesis. This automated platform expands the utility of zebrafish as a versatile, high-throughput model system, facilitating research across diverse fields, including developmental biology, disease modeling, and pharmaceutical and toxicological evaluation.