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1.
Opt Lett ; 46(17): 4320-4323, 2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-34470004

RESUMO

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.

2.
J Phys Chem Lett ; 12(32): 7859-7865, 2021 Aug 19.
Artigo em Inglês | MEDLINE | ID: mdl-34382803

RESUMO

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.


Assuntos
Corantes Fluorescentes/química , Rodaminas/química , Análise Espectral Raman/métodos , Fluorescência , Limite de Detecção , Estudo de Prova de Conceito , Espectrometria de Fluorescência , Vibração
3.
Nat Commun ; 12(1): 3062, 2021 05 24.
Artigo em Inglês | MEDLINE | ID: mdl-34031409

RESUMO

Raman optical activity (ROA) is effective for studying the conformational structure and behavior of chiral molecules in aqueous solutions and is advantageous over X-ray crystallography and nuclear magnetic resonance spectroscopy in sample preparation and cost performance. However, ROA signals are inherently minuscule; 3-5 orders of magnitude weaker than spontaneous Raman scattering due to the weak chiral light-matter interaction. Localized surface plasmon resonance on metallic nanoparticles has been employed to enhance ROA signals, but suffers from detrimental spectral artifacts due to its photothermal heat generation and inability to efficiently transfer and enhance optical chirality from the far field to the near field. Here we demonstrate all-dielectric chiral-field-enhanced ROA by devising a silicon nanodisk array and exploiting its dark mode to overcome these limitations. Specifically, we use it with pairs of chemical and biological enantiomers to show >100x enhanced chiral light-molecule interaction with negligible artifacts for ROA measurements.

4.
Environ Sci Technol ; 55(12): 7880-7889, 2021 06 15.
Artigo em Inglês | MEDLINE | ID: mdl-33913704

RESUMO

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.


Assuntos
Euglena gracilis , Metais Pesados , Microalgas , Biodegradação Ambiental , Citometria de Fluxo
5.
Acc Chem Res ; 54(9): 2132-2143, 2021 05 04.
Artigo em Inglês | MEDLINE | ID: mdl-33788539

RESUMO

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.


Assuntos
Citometria de Fluxo , Ensaios de Triagem em Larga Escala , Humanos , Análise Espectral Raman
6.
Nat Commun ; 11(1): 4772, 2020 09 24.
Artigo em Inglês | MEDLINE | ID: mdl-32973145

RESUMO

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for vibrational spectroscopy as it provides several orders of magnitude higher sensitivity than inherently weak spontaneous Raman scattering by exciting localized surface plasmon resonance (LSPR) on metal substrates. However, SERS can be unreliable for biomedical use since it sacrifices reproducibility, uniformity, biocompatibility, and durability due to its strong dependence on "hot spots", large photothermal heat generation, and easy oxidization. Here, we demonstrate the design, fabrication, and use of a metal-free (i.e., LSPR-free), topologically tailored nanostructure composed of porous carbon nanowires in an array as a SERS substrate to overcome all these problems. Specifically, it offers not only high signal enhancement (~106) due to its strong broadband charge-transfer resonance, but also extraordinarily high reproducibility due to the absence of hot spots, high durability due to no oxidization, and high compatibility to biomolecules due to its fluorescence quenching capability.


Assuntos
Carbono/química , Nanofios/química , Análise Espectral Raman/métodos , Fluorescência , Porosidade , Reprodutibilidade dos Testes , Ressonância de Plasmônio de Superfície/métodos , Propriedades de Superfície
7.
Nat Commun ; 11(1): 3452, 2020 07 10.
Artigo em Inglês | MEDLINE | ID: mdl-32651381

RESUMO

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.


Assuntos
Separação Celular/métodos , Análise Espectral Raman/métodos , Animais , Humanos
8.
Lab Chip ; 20(13): 2263-2273, 2020 06 30.
Artigo em Inglês | MEDLINE | ID: mdl-32459276

RESUMO

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology.


Assuntos
Redes Neurais de Computação , Software , Algoritmos , Separação Celular , Citometria de Fluxo
9.
Biomed Opt Express ; 11(4): 1752-1759, 2020 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-32341845

RESUMO

Microalga-based biomaterial production has attracted attention as a new source of drugs, foods, and biofuels. For enhancing the production efficiency, it is essential to understand its differences between heterogeneous microalgal subpopulations. However, existing techniques are not adequate to address the need due to the lack of single-cell resolution or the inability to perform large-scale analysis and detect small molecules. Here we demonstrated large-scale single-cell analysis of Euglena gracilis (a unicellular microalgal species that produces paramylon as a potential drug for HIV and colon cancer) with our recently developed high-throughput broadband Raman flow cytometer at a throughput of >1,000 cells/s. Specifically, we characterized the intracellular content of paramylon from single-cell Raman spectra of 10,000 E. gracilis cells cultured under five different conditions and found that paramylon contents in E. gracilis cells cultured in an identical condition is given by a log-normal distribution, which is a good model for describing the number of chemicals in a reaction network. The capability of characterizing distribution functions in a label-free manner is an important basis for isolating specific cell populations for synthetic biology via directed evolution based on the intracellular content of metabolites.

10.
Anal Chem ; 91(24): 15563-15569, 2019 12 17.
Artigo em Inglês | MEDLINE | ID: mdl-31774654

RESUMO

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.

11.
Opt Lett ; 44(21): 5282-5285, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31674988

RESUMO

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.

13.
Nat Protoc ; 14(8): 2370-2415, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31278398

RESUMO

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs real-time intelligent image-based sorting of single cells with high throughput. iIACS extends beyond the capabilities of fluorescence-activated cell sorting (FACS) from fluorescence intensity profiles of cells to multidimensional images, thereby enabling high-content sorting of cells or cell clusters with unique spatial chemical and morphological traits. Therefore, iIACS serves as an integral part of holistic single-cell analysis by enabling direct links between population-level analysis (flow cytometry), cell-level analysis (microscopy), and gene-level analysis (sequencing). Specifically, iIACS is based on a seamless integration of high-throughput cell microscopy (e.g., multicolor fluorescence imaging, bright-field imaging), cell focusing, cell sorting, and deep learning on a hybrid software-hardware data management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision making, and actuation. Here, we provide a practical guide to iIACS that describes how to design, build, characterize, and use an iIACS machine. The guide includes the consideration of several important design parameters, such as throughput, sensitivity, dynamic range, image quality, sort purity, and sort yield; the development and integration of optical, microfluidic, electrical, computational, and mechanical components; and the characterization and practical usage of the integrated system. Assuming that all components are readily available, a team of several researchers experienced in optics, electronics, digital signal processing, microfluidics, mechatronics, and flow cytometry can complete this protocol in ~3 months.


Assuntos
Citometria de Fluxo/métodos , Processamento de Imagem Assistida por Computador/métodos , Redes Neurais de Computação , Análise de Célula Única/métodos , Células Cultivadas , Humanos , Dispositivos Lab-On-A-Chip , Microalgas/citologia , Processamento de Sinais Assistido por Computador , Software
14.
Sci Adv ; 5(1): eaau0241, 2019 01.
Artigo em Inglês | MEDLINE | ID: mdl-30746443

RESUMO

Flow cytometry is an indispensable tool in biology for counting and analyzing single cells in large heterogeneous populations. However, it predominantly relies on fluorescent labeling to differentiate cells and, hence, comes with several fundamental drawbacks. Here, we present a high-throughput Raman flow cytometer on a microfluidic chip that chemically probes single live cells in a label-free manner. It is based on a rapid-scan Fourier-transform coherent anti-Stokes Raman scattering spectrometer as an optical interrogator, enabling us to obtain the broadband molecular vibrational spectrum of every single cell in the fingerprint region (400 to 1600 cm-1) with a record-high throughput of ~2000 events/s. As a practical application of the method not feasible with conventional flow cytometry, we demonstrate high-throughput label-free single-cell analysis of the astaxanthin productivity and photosynthetic dynamics of Haematococcus lacustris.


Assuntos
Citometria de Fluxo/métodos , Análise Espectral Raman/métodos , Dióxido de Carbono/metabolismo , Isótopos de Carbono/metabolismo , Clorofíceas/metabolismo , Citometria de Fluxo/instrumentação , Análise de Fourier , Ensaios de Triagem em Larga Escala/instrumentação , Ensaios de Triagem em Larga Escala/métodos , Dispositivos Lab-On-A-Chip , Fotossíntese , Reprodutibilidade dos Testes , Análise de Célula Única/instrumentação , Análise de Célula Única/métodos , Análise Espectral Raman/instrumentação , Vibração , Xantofilas/metabolismo
15.
Cell ; 175(1): 266-276.e13, 2018 09 20.
Artigo em Inglês | MEDLINE | ID: mdl-30166209

RESUMO

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.


Assuntos
Citometria de Fluxo/métodos , Ensaios de Triagem em Larga Escala/métodos , Processamento de Imagem Assistida por Computador/métodos , Animais , Aprendizado Profundo , Humanos
16.
Opt Lett ; 43(16): 4057-4060, 2018 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-30106951

RESUMO

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.

17.
Opt Lett ; 42(21): 4335-4338, 2017 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-29088157

RESUMO

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.

18.
J Chem Phys ; 143(12): 121102, 2015 Sep 28.
Artigo em Inglês | MEDLINE | ID: mdl-26428989

RESUMO

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.


Assuntos
Dicroísmo Circular/métodos , Simulação por Computador , Desenho de Equipamento , Modelos Químicos , Processos Fotoquímicos , Compostos de Rutênio/química
19.
Opt Lett ; 40(17): 4170-3, 2015 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-26368739

RESUMO

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.


Assuntos
Fenômenos Ópticos , Análise Espectral Raman/métodos , Monoterpenos Bicíclicos , Compostos Bicíclicos com Pontes/química , Monoterpenos/química
20.
Opt Express ; 21(11): 13515-21, 2013 Jun 03.
Artigo em Inglês | MEDLINE | ID: mdl-23736604

RESUMO

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.

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