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<p><i>Caenorhabditis elegans</i> (<i>C. elegans)</i> is a key model organism in human disease research. However, conventional automated monitoring systems face notable limitations including poor image quality from insufficient illumination and target misidentification caused by complex backgrounds, which severely impede reliable high-throughput experiments. To address these issues, we developed an integrated hardware-software high-throughput <i>C. elegans</i> lifespan monitoring system. At the hardware level, collimated illumination technology ensures uniform lighting for high-quality imaging, while a stepper motor-driven linear rail combined with industrial cameras enables stable and automated patrol imaging of large-scale Petri dishes. On the software side, the system optimizes target detection through iterative image processing, adopts a two-stage detection algorithm that reduces the miss rate from 1.75% to 0.8%, and integrates a dedicated viability assessment algorithm for accurate distinction between live and dead worms. Validated with adult <i>C. elegans</i> using manual counting as the gold standard, the system achieves over 95% live-count accuracy. It processes a single batch of 36 Petri dishes in 36–60&#xa0;min, boosting throughput to 4–5 times that of manual operation. Long-term 30-day monitoring validation confirms extremely high consistency with manual results, with a Pearson correlation coefficient of 0.999 for live counts. This system is providing a robust tool for aging mechanism research and anti-aging drug screening.</p>

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High-throughput adult Caenorhabditis elegans viability monitoring system

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月26日

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  • Qizhao Lin,
  • Jinfang Weng,
  • Zhishuang Cheng,
  • Jian Guo,
  • Renhui Zhang,
  • Jiachen Zhang

摘要

Caenorhabditis elegans (C. elegans) is a key model organism in human disease research. However, conventional automated monitoring systems face notable limitations including poor image quality from insufficient illumination and target misidentification caused by complex backgrounds, which severely impede reliable high-throughput experiments. To address these issues, we developed an integrated hardware-software high-throughput C. elegans lifespan monitoring system. At the hardware level, collimated illumination technology ensures uniform lighting for high-quality imaging, while a stepper motor-driven linear rail combined with industrial cameras enables stable and automated patrol imaging of large-scale Petri dishes. On the software side, the system optimizes target detection through iterative image processing, adopts a two-stage detection algorithm that reduces the miss rate from 1.75% to 0.8%, and integrates a dedicated viability assessment algorithm for accurate distinction between live and dead worms. Validated with adult C. elegans using manual counting as the gold standard, the system achieves over 95% live-count accuracy. It processes a single batch of 36 Petri dishes in 36–60 min, boosting throughput to 4–5 times that of manual operation. Long-term 30-day monitoring validation confirms extremely high consistency with manual results, with a Pearson correlation coefficient of 0.999 for live counts. This system is providing a robust tool for aging mechanism research and anti-aging drug screening.