Intelligent Image-Activated Cell Sorting.

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.

Boosting the Brightness of Raman Tags Using Cyanostar Macrocycles.

Raman probes have received growing attention for their potential use in super-multiplex biological imaging and flow cytometry applications that cannot be achieved using fluorescent probes. However, obtaining strong Raman scattering signals from small Raman probes has posed a challenge that holds back their practical implementation. Here, we present new types of Raman-active nanoparticles (Rdots) that incorporate ionophore macrocycles, known as cyanostars, to act as ion-driven and structure-directing spacers to address this problem. These macrocycle-enhanced Rdots (MERdots) exhibit sharper and higher electronic absorption peaks than Rdots. When combined with resonant broadband time-domain Raman spectroscopy, these MERdots show a ∼3-fold increase in Raman intensity compared to conventional Rdots under the same particle concentration. Additionally, the detection limit on the concentration of MERdots is improved by a factor of 2.5 compared to that of Rdots and a factor of 430 compared to that of Raman dye molecules in solution. The compact size of MERdots (26 nm in diameter) and their increased Raman signal intensity, along with the broadband capabilities of time-domain resonant Raman spectroscopy, make them promising candidates for a wide range of biological applications.

Label-free multiphoton imaging flow cytometry.

Label-free imaging flow cytometry is a powerful tool for biological and medical research as it overcomes technical challenges in conventional fluorescence-based imaging flow cytometry that predominantly relies on fluorescent labeling. To date, two distinct types of label-free imaging flow cytometry have been developed, namely optofluidic time-stretch quantitative phase imaging flow cytometry and stimulated Raman scattering (SRS) imaging flow cytometry. Unfortunately, these two methods are incapable of probing some important molecules such as starch and collagen. Here, we present another type of label-free imaging flow cytometry, namely multiphoton imaging flow cytometry, for visualizing starch and collagen in live cells with high throughput. Our multiphoton imaging flow cytometer is based on nonlinear optical imaging whose image contrast is provided by two optical nonlinear effects: four-wave mixing (FWM) and second-harmonic generation (SHG). It is composed of a microfluidic chip with an acoustic focuser, a lab-made laser scanning SHG-FWM microscope, and a high-speed image acquisition circuit to simultaneously acquire FWM and SHG images of flowing cells. As a result, it acquires FWM and SHG images (100 × 100 pixels) with a spatial resolution of 500 nm and a field of view of 50 µm × 50 µm at a high event rate of four to five events per second, corresponding to a high throughput of 560-700 kb/s, where the event is defined by the passage of a cell or a cell-like particle. To show the utility of our multiphoton imaging flow cytometer, we used it to characterize Chromochloris zofingiensis (NIES-2175), a unicellular green alga that has recently attracted attention from the industrial sector for its ability to efficiently produce valuable materials for bioplastics, food, and biofuel. Our statistical image analysis found that starch was distributed at the center of the cells at the early cell cycle stage and became delocalized at the later stage. Multiphoton imaging flow cytometry is expected to be an effective tool for statistical high-content studies of biological functions and optimizing the evolution of highly productive cell strains.

Intelligent sort-timing prediction for image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) has enabled high-throughput image-based sorting of single cells with artificial intelligence (AI) algorithms. This AI-on-a-chip technology combines fluorescence microscopy, AI-based image processing, sort-timing prediction, and cell sorting. Sort-timing prediction is particularly essential due to the latency on the order of milliseconds between image acquisition and sort actuation, during which image processing is performed. The long latency amplifies the effects of the fluctuations in the flow speed of cells, leading to fluctuation and uncertainty in the arrival time of cells at the sort point on the microfluidic chip. To compensate for this fluctuation, iIACS measures the flow speed of each cell upstream, predicts the arrival timing of the cell at the sort point, and activates the actuation of the cell sorter appropriately. Here, we propose and demonstrate a machine learning technique to increase the accuracy of the sort-timing prediction that would allow for the improvement of sort event rate, yield, and purity. Specifically, we trained an algorithm to predict the sort timing for morphologically heterogeneous budding yeast cells. The algorithm we developed used cell morphology, position, and flow speed as inputs for prediction and achieved 41.5% lower prediction error compared to the previously employed method based solely on flow speed. As a result, our technique would allow for an increase in the sort event rate of iIACS by a factor of ~2.

High-Throughput Raman Flow Cytometry and Beyond.

Flow cytometry is a powerful tool with applications in diverse fields such as microbiology, immunology, virology, cancer biology, stem cell biology, and metabolic engineering. It rapidly counts and characterizes large heterogeneous populations of cells in suspension (e.g., blood cells, stem cells, cancer cells, and microorganisms) and dissociated solid tissues (e.g., lymph nodes, spleen, and solid tumors) with typical throughputs of 1,000-100,000 events per second (eps). By measuring cell size, cell granularity, and the expression of cell surface and intracellular molecules, it provides systematic insights into biological processes. Flow cytometers may also include cell sorting capabilities to enable subsequent additional analysis of the sorted sample (e.g., electron microscopy and DNA/RNA sequencing), cloning, and directed evolution. Unfortunately, traditional flow cytometry has several critical limitations as it mainly relies on fluorescent labeling for cellular phenotyping, which is an indirect measure of intracellular molecules and surface antigens. Furthermore, it often requires time-consuming preparation protocols and is incompatible with cell therapy. To overcome these difficulties, a different type of flow cytometry based on direct measurements of intracellular molecules by Raman spectroscopy, or "Raman flow cytometry" for short, has emerged. Raman flow cytometry obtains a chemical fingerprint of the cell in a nondestructive manner, allowing for single-cell metabolic phenotyping. However, its slow signal acquisition due to the weak light-molecule interaction of spontaneous Raman scattering prevents the throughput necessary to interrogate large cell populations in reasonable time frames, resulting in throughputs of about 1 eps. The remedy to this throughput limit lies in coherent Raman scattering methods such as stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS), which offer a significantly enhanced light-sample interaction and hence enable high-throughput Raman flow cytometry, Raman imaging flow cytometry, and even Raman image-activated cell sorting (RIACS). In this Account, we outline recent advances, technical challenges, and emerging opportunities of coherent Raman flow cytometry. First, we review the principles of various types of SRS and CARS and introduce several techniques of coherent Raman flow cytometry such as CARS, multiplex CARS, Fourier-transform CARS, SRS, SRS imaging flow cytometry, and RIACS. Next, we discuss a unique set of applications enabled by coherent Raman flow cytometry, from microbiology and lipid biology to cancer detection and cell therapy. Finally, we describe future opportunities and challenges of coherent Raman flow cytometry including increasing sensitivity and throughput, integration with droplet microfluidics, utilizing machine learning techniques, or achieving in vivo flow cytometry. This Account summarizes the growing field of high-throughput Raman flow cytometry and the bright future it can bring.

Highly sensitive Fourier-transform coherent anti-Stokes Raman scattering spectroscopy via genetic algorithm pulse shaping.

We report highly sensitive Fourier-transform coherent anti-Stokes Raman scattering spectroscopy enabled by genetic algorithm (GA) pulse shaping for adaptive dispersion compensation. We show that the non-resonant four-wave mixing signal from water can be used as a fitness indicator for successful GA training. This method allows GA adaptation to sample measurement conditions and offers significantly improved performance compared to training using second-harmonic generation from a nonlinear crystal in place of the sample. Results include a 3× improvement to peak signal-to-noise ratio for 2-propanol measurement, as well as a 10× improvement to peak intensities from the high-throughput measurement of polystyrene microbeads under flow.

Morphological Indicator for Directed Evolution of Euglena gracilis with a High Heavy Metal Removal Efficiency.

In the past few decades, microalgae-based bioremediation methods for treating heavy metal (HM)-polluted wastewater have attracted much attention by virtue of their environment friendliness, cost efficiency, and sustainability. However, their HM removal efficiency is far from practical use. Directed evolution is expected to be effective for developing microalgae with a much higher HM removal efficiency, but there is no non-invasive or label-free indicator to identify them. Here, we present an intelligent cellular morphological indicator for identifying the HM removal efficiency of Euglena gracilis in a non-invasive and label-free manner. Specifically, we show a strong monotonic correlation (Spearman's ρ = -0.82, P = 2.1 × 10-5) between a morphological meta-feature recognized via our machine learning algorithms and the Cu2+ removal efficiency of 19 E. gracilis clones. Our findings firmly suggest that the morphology of E. gracilis cells can serve as an effective HM removal efficiency indicator and hence have great potential, when combined with a high-throughput image-activated cell sorter, for directed-evolution-based development of E. gracilis with an extremely high HM removal efficiency for practical wastewater treatment worldwide.

Ultrafast Simultaneous Raman-Fluorescence Spectroscopy.

Raman and fluorescence spectroscopies offer complementary approaches in bioanalytical chemistry, particularly in microbiological assays. The former method is used to detect lipids, metabolites, and nonspecific proteins and nucleic acids in a label-free manner, while the latter is used to investigate targeted proteins, nucleic acids, and their interactions via labeling or transfection. Despite their complementarity, these regimes are seldom used in conjunction due to fluorescent signals overwhelming inherently weak Raman signals by more than several orders of magnitude. Here we report a multimodal spectrometer that simultaneously performs Raman and fluorescence spectroscopies at high speed. It is made possible by Fourier-transform-coherent anti-Stokes Raman scattering (FT-CARS) and Fourier-transform-two-photon excitation (FT-TPE) measurements powered by a femtosecond pulse laser coupled to a homemade rapid-scan Michelson interferometer, operating at 24 000 spectra per second. As a proof-of-principle demonstration, we validate the ultrafast fluoRaman spectrometer by measuring coumarin dyes in organic solvents. To show its potential for applications that require rapid fluoRaman spectroscopy, we also demonstrate fluoRaman flow cytometry of Haematococcus pluvialis cells under varying culture conditions with a high throughput of ∼10 events per second to perform large-scale single-cell analysis of their metabolic stress response.

Sagnac-enhanced impulsive stimulated Raman scattering for highly sensitive low-frequency Raman spectroscopy.

The "fingerprint" (500-1800 cm-1) and "high-frequency" (2400-4000 cm-1) regions in Raman spectroscopy are commonly used for label-free chemical analysis, while the "low-frequency" region (<200 cm-1) is often overlooked, despite containing rich information. This is largely due to the challenge of measuring weak Raman signals that are obscured by strong Rayleigh scattering. Here we propose and experimentally demonstrate Sagnac-enhanced impulsive stimulated Raman scattering (SE-ISRS), a filter-free method for time-domain Raman spectroscopy that overcomes the challenge and provides low-frequency Raman spectra at all probe frequencies. Using SE-ISRS for simultaneous low-frequency and fingerprint region measurements, we demonstrate a >5× enhancement of the signal-to-noise ratio compared to conventional ISRS spectroscopy.

Microfluidic single-particle chemical analyzer with dual-comb coherent Raman spectroscopy.

Label-free particle analysis is a powerful tool in chemical, pharmaceutical, and cosmetic industries as well as in basic sciences, but its throughput is significantly lower than that of fluorescence-based counterparts. Here we present a label-free single-particle analyzer based on broadband dual-comb coherent Raman scattering spectroscopy operating at a spectroscopic scan rate of 10 kHz. As a proof-of-concept demonstration, we perform broadband coherent anti-Stokes Raman scattering measurements of polystyrene microparticles flowing on an acoustofluidic chip at a high throughput of >1000 particles per second. This high-throughput label-free particle analyzer has the potential for high-precision statistical analysis of a large number of microparticles including biological cells.

Rapid-scan Fourier-transform coherent anti-Stokes Raman scattering spectroscopy with heterodyne detection.

High-speed Raman spectroscopy has become increasingly important for analyzing chemical dynamics in real time. To address the need, rapid-scan Fourier-transform coherent anti-Stokes Raman scattering (FT-CARS) spectroscopy has been developed to realize broadband CARS measurements at a scan rate of more than 20,000 scans/s. However, the detection sensitivity of FT-CARS spectroscopy is inherently low due to the limited number of photons detected during each scan. In this Letter, we show our experimental demonstration of enhanced sensitivity in rapid-scan FT-CARS spectroscopy by heterodyne detection. Specifically, we implemented heterodyne detection by superposing the CARS electric field with an external local oscillator (LO) for their interference. The CARS signal was amplified by simply increasing the power of the LO without the need for increasing the incident power onto the sample. Consequently, we achieved enhancement in signal intensity and the signal-to-noise ratio by factors of 39 and 5, respectively, compared to FT-CARS spectroscopy with homodyne detection. The sensitivity-improved rapid-scan FT-CARS spectroscopy is expected to enable the sensitive real-time observation of chemical dynamics in a broad range of settings, such as combustion engines and live biological cells.

Raman optical activity spectroscopy by visible-excited coherent anti-Stokes Raman scattering.

We developed a Raman optical activity (ROA) spectroscopic system with visible-excited coherent anti-Stokes Raman scattering (CARS). A supercontinuum within the visible region was generated with a photonic crystal fiber pumped with both 532 and 1064 nm excitation, generating a multiplexed CARS-ROA spectrum covering the whole fingerprint region. In visible excitation, the CARS-ROA spectrum of (-)-ß-pinene shows a higher contrast ratio of the chirality-induced signal to the achiral background than that of the previously reported near-infrared CARS-ROA spectrum.

Communication: Broadband and ultrasensitive femtosecond time-resolved circular dichroism spectroscopy.

We report the development of broadband and sensitive time-resolved circular dichroism (TRCD) spectroscopy by exploiting optical heterodyne detection. Using this method, transient CD signals of submillidegree level can be detected over the spectral range of 415-730 nm. We also demonstrate that the broadband measurement with the aid of singular value decomposition enables the discrimination of genuine TRCD signals from artificial optical-anisotropy, such as linear birefringence and linear dichroism, induced by photoexcitation.

Fluorescence-Encoded Time-Domain Coherent Raman Spectroscopy in the Visible Range.

Fluorescence-encoded vibrational spectroscopy has attracted increasing attention by virtue of its high sensitivity and high chemical specificity. We recently demonstrated fluorescence-encoded time-domain coherent Raman spectroscopy (FLETCHERS), which enables low-frequency vibrational spectroscopy of low-concentration fluorophores using near-infrared (800-900 nm) light excitation. However, the feasibility of this study was constrained by the scarcity of excitable molecules in the near-infrared range. Consequently, the broader applicability of FLETCHERS has not been investigated. Here we extend the capabilities of FLETCHERS into the visible range by employing a noncollinear optical parametric amplifier as a light source, significantly enhancing its versatility. Specifically, we use the method, which we refer to as visible FLETCHERS (vFLETCHERS), to individually acquire Raman spectra from five visible fluorophores that have absorption peaks in the 600-700 nm region. These results not only confirm the versatility of vFLETCHERS for a wide range of molecules but also allude to its widespread applicability in biological research through highly sensitive supermultiplexed imaging.

Raman optical activity by coherent anti-Stokes Raman scattering spectral interferometry.

We demonstrate a method to measure Raman optical activity (ROA) by using coherent anti-Stokes Raman scattering (CARS) spectral interferometry. An extremely weak chirality-induced CARS field is amplified through the interference with a strong CARS field generated from an external reference and is extracted by the Fourier transformation. In this interferometric coherent Raman optical activity (iCROA), both the sign and the magnitude of optical active non-resonant background susceptibility can be directly determined. Measurement of a CARS-ROA spectrum with less artifact is obtained because a broad offset artifact due to optical rotatory dispersion is clearly distinguished in iCROA.

The marriage of coherent Raman scattering imaging and advanced computational tools.

Coherent Raman scattering microscopy can provide high-contrast tissue and single-cell images based on the inherent molecular vibrations of the sample. However, conventional techniques face a three-way trade-off between Raman spectral bandwidth, imaging speed, and image fidelity. Although currently challenging to address via optical design, this trade-off can be overcome via emerging computational tools such as compressive sensing and machine learning.

Color-scalable flow cytometry with Raman tags.

Flow cytometry is an indispensable tool in biology and medicine for counting and analyzing cells in large heterogeneous populations. It identifies multiple characteristics of every single cell, typically via fluorescent probes that specifically bind to target molecules on the cell surface or within the cell. However, flow cytometry has a critical limitation: the color barrier. The number of chemical traits that can be simultaneously resolved is typically limited to several due to the spectral overlap between fluorescence signals from different fluorescent probes. Here, we present color-scalable flow cytometry based on coherent Raman flow cytometry with Raman tags to break the color barrier. This is made possible by combining a broadband Fourier-transform coherent anti-Stokes Raman scattering (FT-CARS) flow cytometer, resonance-enhanced cyanine-based Raman tags, and Raman-active dots (Rdots). Specifically, we synthesized 20 cyanine-based Raman tags whose Raman spectra are linearly independent in the fingerprint region (400 to 1,600 cm-1). For highly sensitive detection, we produced Rdots composed of 12 different Raman tags in polymer nanoparticles whose detection limit was as low as 12 nM for a short FT-CARS signal integration time of 420 µs. We performed multiplex flow cytometry of MCF-7 breast cancer cells stained by 12 different Rdots with a high classification accuracy of 98%. Moreover, we demonstrated a large-scale time-course analysis of endocytosis via the multiplex Raman flow cytometer. Our method can theoretically achieve flow cytometry of live cells with >140 colors based on a single excitation laser and a single detector without increasing instrument size, cost, or complexity.

Place & Play SERS: sample collection and preparation-free surface-enhanced Raman spectroscopy.

The ability to perform sensitive, real-time, in situ, multiplex chemical analysis is indispensable for diverse applications such as human health monitoring, food safety testing, forensic analysis, environmental sensing, and homeland security. Surface-enhanced Raman spectroscopy (SERS) is an effective tool to offer the ability by virtue of its high sensitivity and rapid label-free signal detection as well as the availability of portable Raman spectrometers. Unfortunately, the practical utility of SERS is limited because it generally requires sample collection and preparation, namely, collecting a sample from an object of interest and placing the sample on top of a SERS substrate to perform a SERS measurement. In fact, not all analytes can satisfy this requirement because the sample collection and preparation process may be undesirable, laborious, difficult, dangerous, costly, or time-consuming. Here we introduce "Place & Play SERS" based on an ultrathin, flexible, stretchable, adhesive, biointegratable gold-deposited polyvinyl alcohol (PVA) nanomesh substrate that enables placing the substrate on top of an object of interest and performing a SERS measurement of the object by epi-excitation without the need for touching, destroying, and sampling it. Specifically, we characterized the sensitivity of the gold/PVA nanomesh substrate in the Place & Play SERS measurement scheme and then used the scheme to conduct SERS measurements of both wet and dry objects under nearly real-world conditions. To show the practical utility of Place & Play SERS, we demonstrated two examples of its application: food safety testing and forensic analysis. Our results firmly verified the new measurement scheme of SERS and are expected to extend the potential of SERS by opening up untapped applications of sensitive, real-time, in situ multiplex chemical analysis.

Observation of Raman optical activity by heterodyne-detected polarization-resolved coherent anti-Stokes Raman scattering.

We report the first observation of Raman optical activity (ROA) by coherent anti-Stokes Raman scattering. Thanks to the more freedom of polarization configurations in coherent anti-Stokes Raman scattering than in spontaneous Raman spectroscopy, the contrast ratio of the chiral signal to the achiral background has been improved markedly. For (-)-ß-pinene, it is 2 orders of magnitude better than that in the reported spontaneous ROA measurement. This is also the first measurement of ROA signal using a pulsed laser source.

Highly Sensitive Low-Frequency Time-Domain Raman Spectroscopy via Fluorescence Encoding.

Fluorescence-encoded vibrational spectroscopy has become increasingly more popular by virtue of its high chemical specificity and sensitivity. However, current fluorescence-encoded vibrational spectroscopy methods lack sensitivity in the low-frequency region, which if addressed could further enhance their capabilities. Here, we present a method for highly sensitive low-frequency fluorescence-encoded vibrational spectroscopy, termed fluorescence-encoded time-domain coherent Raman spectroscopy (FLETCHERS). By first exciting molecules into vibrationally excited states and then promoting the vibrating molecules to electronic states at varying times, the molecular vibrations can be encoded onto the emitted time-domain fluorescence intensity. We demonstrate the sensitive low-frequency detection capability of FLETCHERS by measuring vibrational spectra in the lower fingerprint region of rhodamine 800 solutions as dilute as 250 nM, which is ∼1000 times more sensitive than conventional vibrational spectroscopy. These results, along with further improvement of the method, open up the prospect of performing single-molecule vibrational spectroscopy in the low-frequency region.