Live imaging of Aiptasia larvae, a model system for coral and anemone bleaching, using a simple microfluidic device

Coral reefs, and their associated diverse ecosystems, are of enormous ecological importance. In recent years, coral health has been severely impacted by environmental stressors brought on by human activity and climate change, threatening the extinction of several major reef ecosystems. Reef damage is mediated by a process called ‘coral bleaching’ where corals, sea anemones, and other cnidarians lose their photosynthetic algal symbionts (family Symbiodiniaceae) upon stress induction, resulting in drastically decreased host energy harvest and, ultimately, coral death. The mechanism by which this critical cnidarian-algal symbiosis is lost remains poorly understood. The larvae of the sea anemone, Exaiptasia pallida (commonly referred to as ‘Aiptasia’) are an attractive model organism to study this process, but they are large (∼100 mm in length, ∼75 mm in diameter), deformable, and highly motile, complicating long-term imaging and limiting study of this critical endosymbiotic relationship in live organisms. Here, we report ‘Traptasia’, a simple microfluidic device with multiple traps designed to isolate and image individual, live larvae of Aiptasia and their algal symbionts over extended time courses. Using a trap design parameterized via fluid flow simulations and polymer bead loading tests, we trapped Aiptasia larvae containing algal symbionts and demonstrated stable imaging for >10 hours. We visualized algae within Aiptasia larvae and observed algal expulsion under an environmental stressor. To our knowledge, this device is the first to enable time-lapsed, high-throughput live imaging of cnidarian larvae and their algal symbionts and, in further implementation, could provide important insights into the cellular mechanisms of cnidarian bleaching under different environmental stressors. The ‘Traptasia’ device is simple to use, requires minimal external equipment and no specialized training to operate, and can easily be adapted using the trap optimization data presented here to study a variety of large, motile organisms.