High-Throughput Raman Flow Cytometry and Beyond Gala de Pablo, Julia; Lindley, Matthew; Hiramatsu, Kotaro ...
Accounts of chemical research,
05/2021, Letnik:
54, Številka:
9
Journal Article
Recenzirano
Conspectus 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.
The interrogation of single cells has revolutionised biology and medicine by providing crucial unparalleled insights into cell-to-cell heterogeneity. Flow cytometry (including fluorescence-activated ...cell sorting) is one of the most versatile and high-throughput approaches for single-cell analysis by detecting multiple fluorescence parameters of individual cells in aqueous suspension as they flow past through a focus of excitation lasers. However, this approach relies on the expression of cell surface and intracellular biomarkers, which inevitably lacks spatial and temporal phenotypes and activities of cells, such as secreted proteins, extracellular metabolite production, and proliferation. Droplet microfluidics has recently emerged as a powerful tool for the encapsulation and manipulation of thousands to millions of individual cells within pico-litre microdroplets. Integrating flow cytometry with microdroplet architectures surrounded by aqueous solutions (
e.g.
, water-in-oil-in-water (W/O/W) double emulsion and hydrogel droplets) opens avenues for new cellular assays linking cell phenotypes to genotypes at the single-cell level. In this review, we discuss the capabilities and applications of droplet flow cytometry (DFC). This unique technique uses standard commercially available flow cytometry instruments to characterise or select individual microdroplets containing single cells of interest. We explore current challenges associated with DFC and present our visions for future development.
This work reviews recent advances in the integration of emulsion microdroplets and flow cytometry technologies, so-called droplet flow cytometry (DFC), for high-throughput single-cell analysis.
Abstract
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 (~10
6
) 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.
We present a Fourier-transform coherent anti-Stokes Raman scattering (FT-CARS) spectroscopy technique that achieves broadband CARS measurements at an ultrahigh scan rate of more than 20,000 spectra/s ...- more than 20 times higher than that of previous broadband coherent Raman scattering spectroscopy techniques. This is made possible by an integration of a FT-CARS system and a rapid-scanning retro-reflective optical path length scanner. To demonstrate the technique's strength, we use it to perform broadband CARS spectroscopy of the transient mixing dynamics of toluene and benzene in the fingerprint region (200-1500 cm(-1)) with spectral resolution of 10 cm(-1) at a record high scan rate of 24,000 spectra/s. Our rapid-scanning FT-CARS technique holds great promise for studying chemical dynamics and wide-field label-free biomedical imaging.
Abstract
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.
Hydrogel droplets encapsulating cells and molecules provide a unique platform in biochemistry, biology, and medicine, including single-cell and single-molecule analysis, directed molecular evolution, ...and detection of cellular secretions. The ability to prepare hydrogel droplets with high monodispersity can lead to synchronization of populations, more controlled biomaterials, and more quantitative assays. Here, we present an inertial microfluidic device for passive, continuous, and high-throughput sorting of hydrogel droplets by size. The sorting is achieved due to size-dependent lateral inertial equilibrium positions: hydrogel droplets of different sizes have different equilibrium positions under the combined effects of shear-gradient lift and wall-effect lift forces. We apply this separation technique to isolate smaller hydrogel droplets containing microalgal colonies from larger empty droplets. We found that hydrogel droplets containing microalga Euglena gracilis (E. gracilis) shrink as cells grow and divide, while empty hydrogel droplets retain their size. Cell-laden hydrogel droplets were collected with up to 93.6% purity, and enrichment factor up to 5.51. After sorting, we were able to recover cells from hydrogel droplets without significantly affecting cell viability.
AI on a chip Isozaki, Akihiro; Harmon, Jeffrey; Zhou, Yuqi ...
Lab on a chip,
08/2020, Letnik:
2, Številka:
17
Journal Article
Recenzirano
Artificial intelligence (AI) has dramatically changed the landscape of science, industry, defence, and medicine in the last several years. Supported by considerably enhanced computational power and ...cloud storage, the field of AI has shifted from mostly theoretical studies in the discipline of computer science to diverse real-life applications such as drug design, material discovery, speech recognition, self-driving cars, advertising, finance, medical imaging, and astronomical observation, where AI-produced outcomes have been proven to be comparable or even superior to the performance of human experts. In these applications, what is essentially important for the development of AI is the data needed for machine learning. Despite its prominent importance, the very first process of the AI development, namely data collection and data preparation, is typically the most laborious task and is often a limiting factor of constructing functional AI algorithms. Lab-on-a-chip technology, in particular microfluidics, is a powerful platform for both the construction and implementation of AI in a large-scale, cost-effective, high-throughput, automated, and multiplexed manner, thereby overcoming the above bottleneck. On this platform, high-throughput imaging is a critical tool as it can generate high-content information (
e.g.
, size, shape, structure, composition, interaction) of objects on a large scale. High-throughput imaging can also be paired with sorting and DNA/RNA sequencing to conduct a massive survey of phenotype-genotype relations whose data is too complex to analyze with traditional computational tools, but is analyzable with the power of AI. In addition to its function as a data provider, lab-on-a-chip technology can also be employed to implement the developed AI for accurate identification, characterization, classification, and prediction of objects in mixed, heterogeneous, or unknown samples. In this review article, motivated by the excellent synergy between AI and lab-on-a-chip technology, we outline fundamental elements, recent advances, future challenges, and emerging opportunities of AI with lab-on-a-chip technology or "AI on a chip" for short.
The excellent synergy between artificial intelligence and lab-on-a-chip technology is described with applications.
By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as ...cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually freezing the motion of flowing cells on the image sensor to effectively achieve 1000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells s
without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.
This editorial serves as an overview of worldwide biophotonics research. Specifically, it lays out its advantages, optical technologies, current research trends, interdisciplinary nature, and growth ...factor in an informative manner. It aims to help biophotonics researchers recognize their important roles in the development and application of optical technologies to studies in biology, medicine, pharmaceutical science, environmental science, and agriculture as well as to provide newcomers interested in starting biophotonics research with the significance, merits, and future perspective of the field. Biophotonics is highly interdisciplinary by nature and acts as a gold mine of ideas, discoveries, and innovations. The future of biophotonics is bright and welcomes interested newcomers.
PDF
