We demonstrate a high-throughput platform for cellular-resolution in vivo pharmaceutical and genetic screens on zebrafish larvae. The system automatically loads animals from reservoirs or multiwell plates, and positions and orients them for high-speed confocal imaging and laser manipulation of both superficial and deep organs within 19 seconds without damage. We show small-scale test screening of retinal axon guidance mutants and neuronal regeneration assays in combination with femtosecond laser microsurgery.

Performances of the biosensors are often limited by the depletion zones created around the sensing area which impede the effective analyte transport. To overcome this limitation, we propose and demonstrate a nanoplasmonic-nanofluidic sensor enabling targeted delivery of analytes to the sensor surface with dramatic improvements in mass transport efficiency. Our sensing platform is based on extraordinary light transmission effect in suspended plasmonic nanoholes. This scheme allows three-dimensional control of the fluidic flow by connecting separate layers of microfluidic channels through plasmonic/nanofluidic holes. To implement the proposed sensor platform, we also introduce a lift-off free nanofabrication method.

Microarrays allowing simultaneous analysis of thousands of parameters can significantly accelerate screening of large libraries of pharmaceutical compounds and biomolecular interactions. For large-scale studies on diverse biomedical samples, reliable, label-free, and high-content microarrays are needed. In this work, using large-area plasmonic nanohole arrays, we demonstrate for the first time a large-scale label-free microarray technology with over one million sensors on a single microscope slide. A dual-color filter imaging method is introduced to dramatically increase the accuracy, reliability, and signal-to-noise ratio of the sensors in a highly multiplexed manner. We used our technology to quantitatively measure protein-protein interactions. Our platform, which is highly compatible with the current microarray scanning systems can enable a powerful screening technology and facilitate diagnosis and treatment of diseases.

The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widely used to study genetics, developmental biology, and to model various human diseases. In this article, we present a set of novel technologies that significantly increase the throughput and capabilities of previously described vertebrate automated screening technology (VAST). We developed a robust multi-thread system that can simultaneously process multiple animals. System throughput is limited only by the image acquisition speed rather than by the fluidic or mechanical processes. We developed image recognition algorithms that fully automate manipulation of animals, including orienting and positioning regions of interest within the microscope’s field of view. We also identified the optimal capillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.

We introduce a novel sensor scheme combining nano-photonics and nano-fluidics on a single platform through the use of free-standing photonic crystals. By harnessing nano-scale openings, we theoretically and experimentally demonstrate that both fluidics and light can be manipulated at sub-wavelength scales. Compared to the conventional fluidic channels, we actively steer the convective flow through the nanohole openings for effective delivery of the analytes to the sensor surface. We apply our method to detect refractive index changes in aqueous solutions. Bulk measurements indicate that active delivery of the convective flow results in better sensitivities. The sensitivity of the sensor reaches 510 nm/RIU for resonance located around 850 nm with a line-width of approximately 10 nm in solution. Experimental results are matched very well with numerical simulations. We also show that cross-polarization measurements can be employed to further improve the detection limit by increasing the signal-to-noise ratio.