Pooled CRISPR screening of high-content cellular phenotypes using ghost cytometry.

Recent advancements in image-based pooled CRISPR screening have facilitated the mapping of diverse genotype-phenotype associations within mammalian cells. However, the rapid enrichment of cells based on morphological information continues to pose a challenge, constraining the capacity for large-scale gene perturbation screening across diverse high-content cellular phenotypes. In this study, we demonstrate the applicability of multimodal ghost cytometry-based cell sorting, including both fluorescent and label-free high-content phenotypes, for rapid pooled CRISPR screening within vast cell populations. Using the high-content cell sorter operating in fluorescence mode, we successfully executed kinase-specific CRISPR screening targeting genes influencing the nuclear translocation of RelA. Furthermore, using the multiparametric, label-free mode, we performed large-scale screening to identify genes involved in macrophage polarization. Notably, the label-free platform can enrich target phenotypes without requiring invasive staining, preserving untouched cells for downstream assays and expanding the potential for screening cellular phenotypes even when suitable markers are absent.

Label-free enrichment of human pluripotent stem cell-derived early retinal progenitor cells for cell-based regenerative therapies.

Pluripotent stem cell-based therapy for retinal degenerative diseases is a promising approach to restoring visual function. A clinical study using retinal organoid (RO) sheets was recently conducted in patients with retinitis pigmentosa. However, the graft preparation currently requires advanced skills to identify and excise suitable segments from the transplantable area of the limited number of suitable ROs. This remains a challenge for consistent clinical implementations. Herein, we enabled the enrichment of wild-type (non-reporter) retinal progenitor cells (RPCs) from dissociated ROs using a label-free ghost cytometry (LF-GC)-based sorting system, where a machine-based classifier was trained in advance with another RPC reporter line. The sorted cells reproducibly formed retinal spheroids large enough for transplantation and developed mature photoreceptors in the retinal degeneration rats. This method of enriching early RPCs with no specific surface antigens and without any reporters or chemical labeling is promising for robust preparation of graft tissues during cell-based therapy.

Label-free cell detection of acute leukemia using ghost cytometry.

Early diagnosis and prompt initiation of appropriate treatment are critical for improving the prognosis of acute leukemia. Acute leukemia is diagnosed by microscopic morphological examination of bone marrow smears and flow cytometric immunophenotyping of bone marrow cells stained with fluorophore-conjugated antibodies. However, these diagnostic processes require trained professionals and are time and resource-intensive. Here, we present a novel diagnostic approach using ghost cytometry, a recently developed high-content flow cytometric approach, which enables machine vision-based, stain-free, high-speed analysis of cells, leveraging their detailed morphological information. We demonstrate that ghost cytometry can detect leukemic cells from the bone marrow cells of patients diagnosed with acute lymphoblastic leukemia and acute myeloid leukemia without relying on biological staining. The approach presented here holds promise as a precise, simple, swift, and cost-effective diagnostic method for acute leukemia in clinical practice.

High-Throughput 3D Imaging Flow Cytometry of Suspended Adherent 3D Cell Cultures.

3D cell cultures are indispensable in recapitulating in vivo environments. Among the many 3D culture methods, culturing adherent cells on hydrogel beads to form spheroid-like structures is a powerful strategy for maintaining high cell viability and functions in the adherent states. However, high-throughput, scalable technologies for 3D imaging of individual cells cultured on the hydrogel scaffolds are lacking. This study reports the development of a high throughput, scalable 3D imaging flow cytometry platform for analyzing spheroid models. This platform is realized by integrating a single objective fluorescence light-sheet microscopy with a microfluidic device that combines hydrodynamic and acoustofluidic focusing techniques. This integration enabled unprecedentedly high-throughput and scalable optofluidic 3D imaging, processing 1310 spheroids consisting of 28 117 cells min-1 . The large dataset obtained enables precise quantification and comparison of the nuclear morphology of adhering and suspended cells, revealing that the adhering cells have smaller nuclei with less rounded surfaces. This platform's high throughput, robustness, and precision for analyzing the morphology of subcellular structures in 3D culture models hold promising potential for various biomedical analyses, including image-based phenotypic screening of drugs with spheroids or organoids.

Identification of In-Droplet Multicellular Communities by Light-Induced Combinatorial DNA Barcoding.

A microdroplet co-culture system is useful for the parallel assessment of numerous possible cell-cell interactions by generating isolated subcommunities from a pool of heterogeneous cells. However, the integration of single-cell sequencing into such analysis has been limited due to the lack of effective molecular identifiers for each in-droplet subcommunity. Herein, we present a strategy for generating in-droplet subcommunity identifiers using DNA-functionalized microparticles encapsulated within microdroplets. These microparticles serve as initial information carriers, where their combinations act as distinct identifiers for in-droplet subcommunity. Upon optical trigger, DNA barcoding molecules encoding the microparticle information are once released in the microdroplets and then tag cell membranes. The tagged DNA molecules then serve as a second information carrier readable by single-cell sequencing to reconstitute the community in silico in the single-cell RNA sequencing data space.

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.

Droplet Array-Based Platform for Parallel Optical Analysis of Dynamic Extracellular Vesicle Secretion from Single Cells.

Extracellular vesicles (EVs) are essential intercellular communication tools, but the regulatory mechanisms governing heterogeneous EV secretion are still unclear due to the lack of methods for precise analysis. Monitoring the dynamics of secretion from individually isolated cells is crucial because in bulk analysis, secretion activity can be perturbed by cell-cell interactions, and a cell population rarely performs secretion in a magnitude- or duration-synchronized manner. Although various microfluidic techniques have been adopted to evaluate the abundance of single-cell-derived EVs, none can track their secretion dynamics continually for extended periods. Here, we have developed a droplet array-based method that allowed us to optically quantify the EV secretion dynamics of >300 single cells every 2 h for 36 h, which covers the cell doubling time of many cell types. The experimental results clearly show the highly heterogeneous nature of single-cell EV secretion and suggest that cell division facilitates EV secretion, showing the usefulness of this platform for discovering EV regulation machinery.

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.

Implementing machine learning methods for imaging flow cytometry.

In this review, we focus on the applications of machine learning methods for analyzing image data acquired in imaging flow cytometry technologies. We propose that the analysis approaches can be categorized into two groups based on the type of data, raw imaging signals or features explicitly extracted from images, being analyzed by a trained model. We hope that this categorization is helpful for understanding uniqueness, differences and opportunities when the machine learning-based analysis is implemented in recently developed 'imaging' cell sorters.

Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic Characteristics.

Imaging flow cytometry shows significant potential for increasing our understanding of heterogeneous and complex life systems and is useful for biomedical applications. Ghost cytometry is a recently proposed approach for directly analyzing compressively measured signals of cells, thereby relieving a computational bottleneck for real-time data analysis in high-throughput imaging cytometry. In our previous work, we demonstrated that this image-free approach could distinguish cells from two cell lines prepared with the same fluorescence staining method. However, the demonstration using different cell lines could not exclude the possibility that classification was based on non-morphological factors such as the speed of cells in flow, which could be encoded in the compressed signals. In this study, we show that GC can classify cells from the same cell line but with different fluorescence distributions in space, supporting the strength of our image-free approach for accurate morphological cell analysis. © 2020 International Society for Advancement of Cytometry.

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 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.

High purcell factor due to coupling of a single emitter to a dielectric slot waveguide.

We demonstrate an all-dielectric quantum electrodynamical nanowire-slab system with a single emitter that concentrates the extremely intense light at the scale of 10 × 75 nm(2). The quantum dot exhibits a record high 31-fold spontaneous decay rate enhancement, its optical saturation and blinking are strongly suppressed, and 80% of emission couples into a waveguide mode.

Axial plane optical microscopy.

We present axial plane optical microscopy (APOM) that can, in contrast to conventional microscopy, directly image a sample's cross-section parallel to the optical axis of an objective lens without scanning. APOM combined with conventional microscopy simultaneously provides two orthogonal images of a 3D sample. More importantly, APOM uses only a single lens near the sample to achieve selective-plane illumination microscopy, as we demonstrated by three-dimensional (3D) imaging of fluorescent pollens and brain slices. This technique allows fast, high-contrast, and convenient 3D imaging of structures that are hundreds of microns beneath the surfaces of large biological tissues.

Brownian motion of tethered nanowires.

Brownian motion of slender particles near a boundary is ubiquitous in biological systems and in nanomaterial assembly, but the complex hydrodynamic interaction in those systems is still poorly understood. Here, we report experimental and computational studies of the Brownian motion of silicon nanowires tethered on a substrate. An optical interference method enabled direct observation of microscopic rotations of the slender bodies in three dimensions with high angular and temporal resolutions. This quantitative observation revealed anisotropic and angle-dependent hydrodynamic wall effects: rotational diffusivity in inclined and azimuth directions follows different power laws as a function of the length, ∼ L(-2.5) and ∼ L(-3), respectively, and is more hindered for smaller inclined angles. In parallel, we developed an implicit simulation technique that takes the complex wire-wall hydrodynamic interactions into account efficiently, the result of which agreed well with the experimentally observed angle-dependent diffusion. The demonstrated techniques provide a platform for studying the microrheology of soft condensed matters, such as colloidal and biological systems near interfaces, and exploring the optimal self-assembly conditions of nanostructures.

Explosives detection in a lasing plasmon nanocavity.

Perhaps the most successful application of plasmonics to date has been in sensing, where the interaction of a nanoscale localized field with analytes leads to high-sensitivity detection in real time and in a label-free fashion. However, all previous designs have been based on passively excited surface plasmons, in which sensitivity is intrinsically limited by the low quality factors induced by metal losses. It has recently been proposed theoretically that surface plasmon sensors with active excitation (gain-enhanced) can achieve much higher sensitivities due to the amplification of the surface plasmons. Here, we experimentally demonstrate an active plasmon sensor that is free of metal losses and operating deep below the diffraction limit for visible light. Loss compensation leads to an intense and sharp lasing emission that is ultrasensitive to adsorbed molecules. We validated the efficacy of our sensor to detect explosives in air under normal conditions and have achieved a sub-part-per-billion detection limit, the lowest reported to date for plasmonic sensors with 2,4-dinitrotoluene and ammonium nitrate. The selectivity between 2,4-dinitrotoluene, ammonium nitrate and nitrobenzene is on a par with other state-of-the-art explosives detectors. Our results show that monitoring the change of the lasing intensity is a superior method than monitoring the wavelength shift, as is widely used in passive surface plasmon sensors. We therefore envisage that nanoscopic sensors that make use of plasmonic lasing could become an important tool in security screening and biomolecular diagnostics.

Intracellular delivery of top-down fabricated tunable nano-plasmonic resonators.

Engineered plasmonic structures fabricated using top-down technologies have demonstrated huge enhancements in the optical response of molecules, including Raman scattering. However, providing a sufficient number of such top-down fabricated nanostructures in solution has been a nontrivial task which has limited their potential in intracellular applications. Here we report the development of a protocol for the intracellular delivery of tunable nanoplasmonic resonators fabricated via scalable top-down techniques. This offers excellent possibilities towards the real-time parallel optical detection of intracellular molecular events.

Lipid bilayer-integrated optoelectronic tweezers for nanoparticle manipulations.

Remotely manipulating a large number of microscopic objects is important to soft-condensed matter physics, biophysics, and nanotechnology. Optical tweezers and optoelectronic tweezers have been widely used for this purpose but face critical challenges when applied to nanoscale objects, including severe photoinduced damages, undesired ionic convections, or irreversible particle immobilization on surfaces. We report here the first demonstration of a lipid bilayer-integrated optoelectronic tweezers system for simultaneous manipulation of hundreds of 60 nm gold nanoparticles in an arbitrary pattern. We use a fluid lipid bilayer membrane with a ~5 nm thickness supported by a photoconductive electrode to confine the diffusion of chemically tethered nanoparticles in a two-dimensional space. Application of an external a.c. voltage together with patterned light selectively activates the photoconducting electrode that creates strong electric field localized near the surface. The field strength changes most significantly at the activated electrode surface where the particles tethered to the membrane thus experience the strongest dielectrophoretic forces. This design allows us to efficiently achieve dynamic, reversible, and parallel manipulation of many nanoparticles. Our approach to integrate biomolecular structures with optoelectronic devices offers a new platform enabling the study of thermodynamics in many particle systems and the selective transport of nanoscale objects for broad applications in biosensing and cellular mechanotransductions.