High-speed 3D imaging flow cytometry with optofluidic spatial transformation.

Three-dimensional (3D) fluorescence imaging is important to accurately capture and understand biological structures and phenomena. However, because of its slow acquisition speed, it was difficult to implement 3D fluorescence imaging for imaging flow cytometry. Especially, modern flow cytometers operate at a flow velocity of 1-10 m/s, and no 3D fluorescence imaging technique was able to capture cells at such high velocity. Here, we present a high-speed 3D fluorescence imaging technique in which a set of optical cross sections of a cell is captured within a single frame of a camera by combining strobe light-sheet excitation and optofluidic spatial transformation. Using this technique, we demonstrated 3D fluorescence imaging of cells flowing at a velocity of over 10 m/s, which is the fastest to our knowledge. Such technology can allow integration of 3D imaging with flow systems of common flow cytometers and cell sorters.

Reduced acoustic resonator dimensions improve focusing efficiency of bacteria and submicron particles.

In this study, we demonstrate an acoustofluidic device that enables single-file focusing of submicron particles and bacteria using a two-dimensional (2D) acoustic standing wave. The device consists of a 100 µm × 100 µm square channel that supports 2D particle focusing in the channel center at an actuation frequency of 7.39 MHz. This higher actuation frequency compared with conventional bulk acoustic systems enables radiation-force-dominant motion of submicron particles and overcomes the classical size limitation (≈2 µm) of acoustic focusing. We present acoustic radiation force-based focusing of particles with diameters less than 0.5 µm at a flow rate of 12 µL min-1, and 1.33 µm particles at flow rates up to 80 µL min-1. The device focused 0.25 µm particles by the 2D acoustic radiation force while undergoing a channel cross-section centered, single-vortex acoustic streaming. A suspension of bacteria was also investigated to evaluate the biological relevance of the device, which demonstrated the alignment of bacteria in the channel at a flow rate of up to 20 µL min-1. The developed acoustofluidic device can align submicron particles within a narrow flow stream in a highly robust manner, validating its use as a flow-through focusing chamber to perform high-throughput and accurate flow cytometry of submicron objects.

In silico-labeled ghost cytometry.

Characterization and isolation of a large population of cells are indispensable procedures in biological sciences. Flow cytometry is one of the standards that offers a method to characterize and isolate cells at high throughput. When performing flow cytometry, cells are molecularly stained with fluorescent labels to adopt biomolecular specificity which is essential for characterizing cells. However, molecular staining is costly and its chemical toxicity can cause side effects to the cells which becomes a critical issue when the cells are used downstream as medical products or for further analysis. Here, we introduce a high-throughput stain-free flow cytometry called in silico-labeled ghost cytometry which characterizes and sorts cells using machine-predicted labels. Instead of detecting molecular stains, we use machine learning to derive the molecular labels from compressive data obtained with diffractive and scattering imaging methods. By directly using the compressive 'imaging' data, our system can accurately assign the designated label to each cell in real time and perform sorting based on this judgment. With this method, we were able to distinguish different cell states, cell types derived from human induced pluripotent stem (iPS) cells, and subtypes of peripheral white blood cells using only stain-free modalities. Our method will find applications in cell manufacturing for regenerative medicine as well as in cell-based medical diagnostic assays in which fluorescence labeling of the cells is undesirable.

Ghost cytometry.

Ghost imaging is a technique used to produce an object's image without using a spatially resolving detector. Here we develop a technique we term "ghost cytometry," an image-free ultrafast fluorescence "imaging" cytometry based on a single-pixel detector. Spatial information obtained from the motion of cells relative to a static randomly patterned optical structure is compressively converted into signals that arrive sequentially at a single-pixel detector. Combinatorial use of the temporal waveform with the intensity distribution of the random pattern allows us to computationally reconstruct cell morphology. More importantly, we show that applying machine-learning methods directly on the compressed waveforms without image reconstruction enables efficient image-free morphology-based cytometry. Despite a compact and inexpensive instrumentation, image-free ghost cytometry achieves accurate and high-throughput cell classification and selective sorting on the basis of cell morphology without a specific biomarker, both of which have been challenging to accomplish using conventional flow cytometers.

High-throughput label-free image cytometry and image-based classification of live Euglena gracilis.

We demonstrate high-throughput label-free single-cell image cytometry and image-based classification of Euglena gracilis (a microalgal species) under different culture conditions. We perform it with our high-throughput optofluidic image cytometer composed of a time-stretch microscope with 780-nm resolution and 75-Hz line rate, and an inertial-focusing microfluidic device. By analyzing a large number of single-cell images from the image cytometer, we identify differences in morphological and intracellular phenotypes between E. gracilis cell groups and statistically classify them under various culture conditions including nitrogen deficiency for lipid induction. Our method holds promise for real-time evaluation of culture techniques for E. gracilis and possibly other microalgae in a non-invasive manner.

High-throughput optofluidic particle profiling with morphological and chemical specificity.

We present a method for high-throughput optofluidic particle analysis that provides both the morphological and chemical profiles of individual particles in a large heterogeneous population. This method is based on an integration of a time-stretch optical microscope with a submicrometer spatial resolution of 780 nm and a three-color fluorescence analyzer on top of an inertial-focusing microfluidic device. The integrated system can perform image- and fluorescence-based screening of particles with a high throughput of 10,000 particles/s, exceeding previously demonstrated imaging particle analyzers in terms of specificity without sacrificing throughput.