Kok Hao Chen

Evaluation of fluorophores for optimal performance in localization-based super-resolution imaging

One approach to super-resolution fluorescence imaging uses sequential activation and localization of individual fluorophores to achieve high spatial resolution. Essential to this technique is the choice of fluorescent probes; the properties of the probes, including photons per switching event, on-off duty cycle, photostability and number of switching cycles, largely dictate the quality of super-resolution images. Although many probes have been reported, a systematic characterization of the properties of these probes and their impact on super-resolution image quality has been described in only a few cases. Here we quantitatively characterized the switching properties of 26 organic dyes and directly related these properties to the quality of super-resolution images. This analysis provides guidelines for characterization of super-resolution probes and a resource for selecting probes based on performance. Our evaluation identified several photoswitchable dyes with good to excellent performance in four independent spectral ranges, with which we demonstrated low–cross-talk, four-color super-resolution imaging.

Spatially resolved, highly multiplexed RNA profiling in single cells

Multiplexed RNA imaging in single cells The basis of cellular function is where and when proteins are expressed and in what quantities. Single-molecule fluorescence in situ hybridization (smFISH) experiments quantify the copy number and location of mRNA molecules; however, the numbers of RNA species that can be simultaneously measured by smFISH has been limited. Using combinatorial labeling with error-robust encoding schemes, Chen et al. simultaneously imaged 100 to 1000 RNA species in a single cell. Such large-scale detection allows regulatory interactions to be analyzed at the transcriptome scale. Science, this issue p. 10.1126/science.aaa6090 A single-molecule imaging method allows simultaneous measurement of 1000 RNA species in single cells. INTRODUCTION The copy number and intracellular localization of RNA are important regulators of gene expression. Measurement of these properties at the transcriptome scale in single cells will give answers to many questions related to gene expression and regulation. Single-molecule RNA imaging approaches, such as single-molecule fluorescence in situ hybridization (smFISH), are powerful tools for counting and mapping RNA; however, the number of RNA species that can be simultaneously imaged in individual cells has been limited. This makes it challenging to perform transcriptomic analysis of single cells in a spatially resolved manner. Here, we report multiplexed error-robust FISH (MERFISH), a single-molecule imaging method that allows thousands of RNA species to be imaged in single cells by using combinatorial FISH labeling with encoding schemes capable of detecting and/or correcting errors. RATIONALE We labeled each cellular RNA with a set of encoding probes, which contain targeting sequences that bind the RNA and readout sequences that bind fluorescently labeled readout probes. Each RNA species is encoded with a particular combination of readout sequences. We used successive rounds of hybridization and imaging, each with a different readout probe, to identify the readout sequences bound to each RNA and to decode the RNA. In principle, combinatorial labeling allows the number of detectable RNA species to grow exponentially with the number of imaging rounds, but the detection errors also increase exponentially. To combat such accumulating errors, we exploited error-robust encoding schemes used in digital electronics, such as the extended Hamming code, in the design of our encoding probes but modified these schemes in order to account for the error properties in FISH measurements. We assigned each RNA a binary word in our modified Hamming code and encoded the RNA with a combination of readout sequences according to this binary word. RESULTS We first imaged 140 RNA species in human fibroblast cells using MERFISH with 16 rounds of hybridization and a modified Hamming code capable of both error detection and correction. We obtained ~80% detection efficiency and observed excellent correlation of RNA copy numbers determined with MERFISH with both bulk RNA sequencing data and conventional smFISH measurements of individual genes. Next, we used an alternative MERFISH encoding scheme, which is capable of detecting but not correcting errors, to image 1001 RNA species in individual cells using only 14 rounds of hybridization. The observed RNA copy numbers again correlate well with bulk sequencing data. However, the detection efficiency is only one-third that of the error-correcting encoding scheme. We performed correlation analysis of the 104 to 106 pairs of measured genes and identified many covarying gene groups that share common regulatory elements. Such grouping allowed us to hypothesize potential functions of ~100 unannotated or partially annotated genes of unknown functions. We further analyzed correlations in the spatial distributions of different RNA species and identified groups of RNAs with different distribution patterns in the cell. DISCUSSION This highly multiplexed imaging approach enables analyses based on the variation and correlation of copy numbers and spatial distributions of a large number of RNA species within single cells. Such analyses should facilitate the delineation of regulatory networks and in situ identification of cell types. We envision that this approach will allow spatially resolved transcriptomes to be determined for single cells. MERFISH for transcriptome imaging. Numerous RNA species can be identified, counted, and localized in a single cell by using MERFISH, a single-molecule imaging approach that uses combinatorial labeling and sequential imaging with encoding schemes capable of detection and/or correction of errors. This highly multiplexed measurement of individual RNAs can be used to compute the gene expression profile and noise, covariation in expression among different genes, and spatial distribution of RNAs within single cells. Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here, we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 to 1000 distinct RNA species in hundreds of individual cells. Correlation analysis of the ~104 to 106 pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins.

Multicolor Super‐Resolution Fluorescence Imaging via Multi‐Parameter Fluorophore Detection

Understanding the complexity of the cellular environment will benefit from the ability to unambiguously resolve multiple cellular components, simultaneously and with nanometer-scale spatial resolution. Multicolor super-resolution fluorescence microscopy techniques have been developed to achieve this goal, yet challenges remain in terms of the number of targets that can be simultaneously imaged and the crosstalk between color channels. Herein, we demonstrate multicolor stochastic optical reconstruction microscopy (STORM) based on a multi-parameter detection strategy, which uses both the fluorescence activation wavelength and the emission color to discriminate between photo-activatable fluorescent probes. First, we obtained two-color super-resolution images using the near-infrared cyanine dye Alexa 750 in conjunction with a red cyanine dye Alexa 647, and quantified color crosstalk levels and image registration accuracy. Combinatorial pairing of these two switchable dyes with fluorophores which enhance photo-activation enabled multi-parameter detection of six different probes. Using this approach, we obtained six-color super-resolution fluorescence images of a model sample. The combination of multiple fluorescence detection parameters for improved fluorophore discrimination promises to substantially enhance our ability to visualize multiple cellular targets with sub-diffraction-limit resolution.

Reference component analysis of single-cell transcriptomes elucidates cellular heterogeneity in human colorectal tumors

Intratumoral heterogeneity is a major obstacle to cancer treatment and a significant confounding factor in bulk-tumor profiling. We performed an unbiased analysis of transcriptional heterogeneity in colorectal tumors and their microenvironments using single-cell RNA–seq from 11 primary colorectal tumors and matched normal mucosa. To robustly cluster single-cell transcriptomes, we developed reference component analysis (RCA), an algorithm that substantially improves clustering accuracy. Using RCA, we identified two distinct subtypes of cancer-associated fibroblasts (CAFs). Additionally, epithelial–mesenchymal transition (EMT)-related genes were found to be upregulated only in the CAF subpopulation of tumor samples. Notably, colorectal tumors previously assigned to a single subtype on the basis of bulk transcriptomics could be divided into subgroups with divergent survival probability by using single-cell signatures, thus underscoring the prognostic value of our approach. Overall, our results demonstrate that unbiased single-cell RNA–seq profiling of tumor and matched normal samples provides a unique opportunity to characterize aberrant cell states within a tumor.

High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization

Significance Image-based approaches to single-cell transcriptomics offer the ability to quantify not only the copy number of RNAs within cells but also the intracellular RNA location and the spatial organization of cells within cultures or tissues. Here we report advances in multiplexed error-robust fluorescence in situ hybridization (MERFISH) that increase the measurement throughput by two orders of magnitude and allow gene expression profiling of ∼40,000 human cells in a single 18-h measurement. This drastic increase in throughput should facilitate the identification and study of rare populations of cells as well as the characterization of transcriptionally distinct cell types within large tissue regions. Image-based approaches to single-cell transcriptomics, in which RNA species are identified and counted in situ via imaging, have emerged as a powerful complement to single-cell methods based on RNA sequencing of dissociated cells. These image-based approaches naturally preserve the native spatial context of RNAs within a cell and the organization of cells within tissue, which are important for addressing many biological questions. However, the throughput of these image-based approaches is relatively low. Here we report advances that lead to a drastic increase in the measurement throughput of multiplexed error-robust fluorescence in situ hybridization (MERFISH), an image-based approach to single-cell transcriptomics. In MERFISH, RNAs are identified via a combinatorial labeling approach that encodes RNA species with error-robust barcodes followed by sequential rounds of single-molecule fluorescence in situ hybridization (smFISH) to read out these barcodes. Here we increase the throughput of MERFISH by two orders of magnitude through a combination of improvements, including using chemical cleavage instead of photobleaching to remove fluorescent signals between consecutive rounds of smFISH imaging, increasing the imaging field of view, and using multicolor imaging. With these improvements, we performed RNA profiling in more than 100,000 human cells, with as many as 40,000 cells measured in a single 18-h measurement. This throughput should substantially extend the range of biological questions that can be addressed by MERFISH.

Temperature-independent porous nanocontainers for single-molecule fluorescence studies.

In this work, we demonstrate the capability of using lipid vesicles biofunctionalized with protein channels to perform single-molecule fluorescence measurements over a biologically relevant temperature range. Lipid vesicles can serve as an ideal nanocontainer for single-molecule fluorescence measurements of biomacromolecules. One serious limitation of the vesicle encapsulation method has been that the lipid membrane is practically impermeable to most ions and small molecules, limiting its application to observing reactions in equilibrium with the initial buffer condition. To permeabilize the barrier, Staphylococcus aureus toxin α-hemolysin (aHL) channels have been incorporated into the membrane. These aHL channels have been characterized using single-molecule fluorescence resonance energy transfer signals from vesicle-encapsulated guanine-rich DNA that folds in a G-quadruplex motif as well as from the Rep helicase-DNA system. We show that these aHL channels are permeable to monovalent ions and small molecules, such as ATP, over the biologically relevant temperature range (17-37 °C). Ions can efficiently pass through preformed aHL channels to initiate DNA folding without any detectable delay. With addition of the cholesterol to the membrane, we also report a 35-fold improvement in the aHL channel formation efficiency, making this approach more practical for wider applications. Finally, the temperature-dependent single-molecule enzymatic study inside these nanocontainers is demonstrated by measuring the Rep helicase repetitive shuttling dynamics along a single-stranded DNA at various temperatures. The permeability of the biofriendly nanocontainer over a wide range of temperature would be effectively applied to other surface-based high-throughput measurements and sensors beyond the single-molecule fluorescence measurements.

Wide-field single metal nanoparticle spectroscopy for high throughput localized surface plasmon resonance sensing

Noble metal nanoparticles (mNPs) have a distinct extinction spectrum arising from their ability to support Localized Surface Plasmon Resonance (LSPR). Single-particle biosensing with LSPR is label free and offers a number of advantages, including single molecular sensitivity, multiplex detection, and in vivo quantification of chemical species etc. In this article, we introduce Single-particle LSPR Imaging (SLI), a wide-field spectral imaging method for high throughput LSPR biosensing. The SLI utilizes a transmission grating to generate the diffraction spectra from multiple mNPs, which are captured using a Charge Coupled Device (CCD). With the SLI, we are able to simultaneously image and track the spectral changes of up to 50 mNPs in a single (∼1 s) exposure and yet still retain a reasonable spectral resolution for biosensing. Using the SLI, we could observe spectral shift under different local refractive index environments and demonstrate biosensing using biotin-streptavidin as a model system. To the best of our knowledge, this is the first time a transmission grating based spectral imaging approach has been used for mNPs LSPR sensing. The higher throughput LSPR sensing, offered by SLI, opens up a new possibility of performing label-free, single-molecule experiments in a high-throughput manner.

Evaluation of Fluorophores for Optimal Performance in Localization-Based Super-Resolution Imaging

A variety of approaches have recently been developed to surpass the diffraction-limited resolution of fluorescence microscopy. One such approach relies on the sequential activation and nanoscale localization of single fluorophores, where the high-precision localizations of individual molecules can be used to construct a sub-diffraction-limit image with dramatically improved spatial resolutions. Photoswitchable fluorescent probes have become an essential component in localization-based super-resolution imaging. The properties of these probes, such as the photons per switching event, on/off duty cycle, photostability, and number of switching cycles, determine a probes effectiveness for creating high resolution images. Yet a quantitative characterization of these properties for most fluorophores is lacking, preventing an effective and systematic choice of optimal fluorophores and imaging conditions for attaining high quality super-resolution images. To address this need, we systematically characterize the switching properties of tens of organic dyes and demonstrate how these properties directly impact the quality of a super-resolution image. Our analysis provides a set of guidelines to be followed for evaluating fluorophores and is a resource for probe selection for interested practitioners of single molecule localization-based super-resolution imaging. In addition to our quantitative characterization, we also identify several new dyes suitable for this imaging modality. Using the highest performing dyes from our screen in each of four distinct spectral ranges, we demonstrate low crosstalk, four-color super-resolution imaging and apply these new imaging capabilities to study various cellular structures.