Development of microfluidic tools for studying individual zooplanktons

Abstract

Zooplanktons are the foundation of aquatic food chains and extensively used as aquaculture live feeds. Exploration and utilization of zooplankton diversity would expand our understanding of aquatic ecosystems and benefit the aquaculture industry. Nonetheless, current methods for isolating and studying diversity of individual zooplanktons remain slow and labor intensive. The objective of this study was to develop a microfluidic device and image analysis software for studying and isolating individual zooplanktons. We built a microfluidic chip from acrylic/PDMS sheets and used a water dipping system to control zooplankton flow. Image analysis software, based on Python OpenCV, automatically measured size and color of individual zooplanktons. A solenoid valve, coupled to a microcontroller, allowed experimenters to manually isolate selected zooplanktons. Our device flows a single stream of tested zooplankton, Moina macrocopa, across our chip and allowed isolation of individual zooplankton. Size and grayscale color of individual zooplankton measured by our automated software are well-correlated with manual measurement. Our device can isolate M. macrocopa by size and color with 75-85% and 80-85% specificity, respectively. Moreover, our device can separate M. macrocopa from Branchinella thailandensis population with 93-97% specificity. We also demonstrated isolation of M. macrocopa enriched with fluorescent bacteria from non-enriched M. macrocopa with 79-81% specificity.

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