Jeffrey R. Moffitt

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.

Characterization and development of photoactivatable fluorescent proteins for single-molecule–based superresolution imaging

Significance Photoactivatable fluorescent proteins (PAFPs) are important probes for superresolution fluorescence microscopy, which allows the spatial organization of proteins in living cells to be probed with sub–diffraction-limit resolution. Here, we compare four properties of PAFPs that are critical for superresolution imaging and report two new PAFPs that exhibit excellent performance in all four properties. Photoactivatable fluorescent proteins (PAFPs) have been widely used for superresolution imaging based on the switching and localization of single molecules. Several properties of PAFPs strongly influence the quality of the superresolution images. These properties include (i) the number of photons emitted per switching cycle, which affects the localization precision of individual molecules; (ii) the ratio of the on- and off-switching rate constants, which limits the achievable localization density; (iii) the dimerization tendency, which could cause undesired aggregation of target proteins; and (iv) the signaling efficiency, which determines the fraction of target–PAFP fusion proteins that is detectable in a cell. Here, we evaluated these properties for 12 commonly used PAFPs fused to both bacterial target proteins, H-NS, HU, and Tar, and mammalian target proteins, Zyxin and Vimentin. Notably, none of the existing PAFPs provided optimal performance in all four criteria, particularly in the signaling efficiency and dimerization tendency. The PAFPs with low dimerization tendencies exhibited low signaling efficiencies, whereas mMaple showed the highest signaling efficiency but also a high dimerization tendency. To address this limitation, we engineered two new PAFPs based on mMaple, which we termed mMaple2 and mMaple3. These proteins exhibited substantially reduced or undetectable dimerization tendencies compared with mMaple but maintained the high signaling efficiency of mMaple. In the meantime, these proteins provided photon numbers and on–off switching rate ratios that are comparable to the best achieved values among PAFPs.

Spatial organization of chromatin domains and compartments in single chromosomes.

Spatial organization inside the nucleus In eukaryotic cells, DNA is packaged into a complex macromolecular structure called chromatin. Wang et al. have developed an imaging method to map the position of multiple regions on individual chromosomes, and the results confirm that chromatin is organized into large contact domains called TADS (topologically associating domains). Unexpectedly, though, folding deviates from the classical fractal-globule model at large length scales. Science, this issue p. 598 Imaging that maps chromatin domains reveals polarized arrangements of chromatin compartments and nonfractal chromosome folding. The spatial organization of chromatin critically affects genome function. Recent chromosome-conformation-capture studies have revealed topologically associating domains (TADs) as a conserved feature of chromatin organization, but how TADs are spatially organized in individual chromosomes remains unknown. Here, we developed an imaging method for mapping the spatial positions of numerous genomic regions along individual chromosomes and traced the positions of TADs in human interphase autosomes and X chromosomes. We observed that chromosome folding deviates from the ideal fractal-globule model at large length scales and that TADs are largely organized into two compartments spatially arranged in a polarized manner in individual chromosomes. Active and inactive X chromosomes adopt different folding and compartmentalization configurations. These results suggest that the spatial organization of chromatin domains can change in response to regulation.

The single-cell chemostat: an agarose-based, microfluidic device for high- throughput, single-cell studies of bacteria and bacterial communities†

Optical microscopy of single bacteria growing on solid agarose support is a powerful method for studying the natural heterogeneity in growth and gene expression. While the material properties of agarose make it an excellent substrate for such studies, the sheer number of exponentially growing cells eventually overwhelms the agarose pad, which fundamentally limits the duration and the throughput of measurements. Here we overcome the limitations of exponential growth by patterning agarose pads on the sub-micron-scale. Linear tracks constrain the growth of bacteria into a high density array of linear micro-colonies. Buffer flow through microfluidic lines washes away excess cells and delivers fresh nutrient buffer. Densely patterned tracks allow us to cultivate and image hundreds of thousands of cells on a single agarose pad over 30-40 generations, which drastically increases single-cell measurement throughput. In addition, we show that patterned agarose can facilitate single-cell measurements within bacterial communities. As a proof-of-principle, we study a community of E. coli auxotrophs that can complement the amino acid deficiencies of one another. We find that the growth rate of colonies of one strain decreases sharply with the distance to colonies of the complementary strain over distances of only a few cell lengths. Because patterned agarose pads maintain cells in a chemostatic environment in which every cell can be imaged, we term our device the single-cell chemostat. High-throughput measurements of single cells growing chemostatically should greatly facilitate the study of a variety of microbial behaviours.

Single–Base Pair Unwinding and Asynchronous RNA Release by the Hepatitis C Virus NS3 Helicase

During RNA unwinding, nucleotides are transiently sequestered, and their release is decoupled from base pair opening. Nonhexameric helicases use adenosine triphosphate (ATP) to unzip base pairs in double-stranded nucleic acids (dsNAs). Studies have suggested that these helicases unzip dsNAs in single–base pair increments, consuming one ATP molecule per base pair, but direct evidence for this mechanism is lacking. We used optical tweezers to follow the unwinding of double-stranded RNA by the hepatitis C virus NS3 helicase. Single–base pair steps by NS3 were observed, along with nascent nucleotide release that was asynchronous with base pair opening. Asynchronous release of nascent nucleotides rationalizes various observations of its dsNA unwinding and may be used to coordinate the translocation speed of NS3 along the RNA during viral replication.

Robust Circadian Oscillations in Growing Cyanobacteria Require Transcriptional Feedback

Keeping in Synch Although it differs from mammalian clocks, the circadian clock of cyanobacteria is a valuable model for understanding how such clocks function. At the heart of the cyanobacterial clock is a posttranslational regulation (PTR) circuit in which the phosphorylation of the clock protein KaiC oscillates. This circuit is apparently sufficient for generating rhythms, but it is connected to a transcriptional-translational (TTR) feedback loop more similar to the one that functions in mammals. This TTR loop is, at least in some conditions, dispensable. To understand the role of the TTR circuit, Teng et al. (p. 737) engineered cyanobacteria so that the circadian behavior of individual cells in a population of growing cells could be monitored. Cells engineered to lack the TTR mechanism had rhythmic clocks but fell out of synch with the other cells in a population over time. The experimental results together with mathematical modeling indicate that the TTR mechanism is important to allow cells to robustly stay in rhythm with one another in the absence of synchronizing external cues. The cyanobacterial clock uses one circuit for rhythms and a second circuit for intercellular synchronous oscillations. The remarkably stable circadian oscillations of single cyanobacteria enable a population of growing cells to maintain synchrony for weeks. The cyanobacterial pacemaker is a posttranslational regulation (PTR) circuit that generates circadian oscillations in the phosphorylation state of the clock protein KaiC. Layered on top of the PTR is transcriptional-translational feedback regulation (TTR), common to all circadian systems, consisting of a negative feedback loop in which KaiC regulates its own production. We found that the PTR circuit is sufficient to generate oscillations in growing cyanobacteria. However, in the absence of TTR, individual oscillators were less stable and synchrony was not maintained in a population of cells. Experimentally constrained mathematical modeling reproduced sustained oscillations in the PTR circuit alone and demonstrated the importance of TTR for oscillator synchrony.

High Degree of Coordination and Division of Labor among Subunits in a Homomeric Ring ATPase

Ring NTPases of the ASCE superfamily perform a variety of cellular functions. An important question about the operation of these molecular machines is how the ring subunits coordinate their chemical and mechanical transitions. Here, we present a comprehensive mechanochemical characterization of a homomeric ring ATPase-the bacteriophage φ29 packaging motor-a homopentamer that translocates double-stranded DNA in cycles composed of alternating dwells and bursts. We use high-resolution optical tweezers to determine the effect of nucleotide analogs on the cycle. We find that ATP hydrolysis occurs sequentially during the burst and that ADP release is interlaced with ATP binding during the dwell, revealing a high degree of coordination among ring subunits. Moreover, we show that the motor displays an unexpected division of labor: although all subunits of the homopentamer bind and hydrolyze ATP during each cycle, only four participate in translocation, whereas the remaining subunit plays an ATP-dependent regulatory role.

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.

Fast compressed sensing analysis for super-resolution imaging using L1-homotopy

In super-resolution imaging techniques based on single-molecule switching and localization, the time to acquire a super-resolution image is limited by the maximum density of fluorescent emitters that can be accurately localized per imaging frame. In order to increase the imaging rate, several methods have been recently developed to analyze images with higher emitter densities. One powerful approach uses methods based on compressed sensing to increase the analyzable emitter density per imaging frame by several-fold compared to other reported approaches. However, the computational cost of this approach, which uses interior point methods, is high, and analysis of a typical 40 µm x 40 µm field-of-view super-resolution movie requires thousands of hours on a high-end desktop personal computer. Here, we demonstrate an alternative compressed-sensing algorithm, L1-Homotopy (L1H), which can generate super-resolution image reconstructions that are essentially identical to those derived using interior point methods in one to two orders of magnitude less time depending on the emitter density. Moreover, for an experimental data set with varying emitter density, L1H analysis is ~300-fold faster than interior point methods. This drastic reduction in computational time should allow the compressed sensing approach to be routinely applied to super-resolution image analysis.

High-performance multiplexed fluorescence in situ hybridization in culture and tissue with matrix imprinting and clearing

Significance Multiplexed single-molecule FISH allows spatially resolved gene-expression profiling in single cells. However, because of off-target binding of FISH probes and cellular autofluorescence, background can become limiting in multiplexed single-molecule FISH measurements, especially when tissue samples are imaged or when the degree of multiplexing is increased. Here we report a sample clearing approach for FISH that substantially reduced these background sources by anchoring RNAs to a polymer matrix and then removing proteins and lipids. This approach allows measurements with higher detection efficiency and sensitivity across more color channels in both cell culture and tissue with no detectable loss in RNA. We anticipate that this clearing approach will greatly facilitate applications of multiplexed FISH measurements in a wide variety of biological systems. Highly multiplexed single-molecule FISH has emerged as a promising approach to spatially resolved single-cell transcriptomics because of its ability to directly image and profile numerous RNA species in their native cellular context. However, background—from off-target binding of FISH probes and cellular autofluorescence—can become limiting in a number of important applications, such as increasing the degree of multiplexing, imaging shorter RNAs, and imaging tissue samples. Here, we developed a sample clearing approach for FISH measurements. We identified off-target binding of FISH probes to cellular components other than RNA, such as proteins, as a major source of background. To remove this source of background, we embedded samples in polyacrylamide, anchored RNAs to this polyacrylamide matrix, and cleared cellular proteins and lipids, which are also sources of autofluorescence. To demonstrate the efficacy of this approach, we measured the copy number of 130 RNA species in cleared samples using multiplexed error-robust FISH (MERFISH). We observed a reduction both in the background because of off-target probe binding and in the cellular autofluorescence without detectable loss in RNA. This process led to an improved detection efficiency and detection limit of MERFISH, and an increased measurement throughput via extension of MERFISH into four color channels. We further demonstrated MERFISH measurements of complex tissue samples from the mouse brain using this matrix-imprinting and -clearing approach. We envision that this method will improve the performance of a wide range of in situ hybridization-based techniques in both cell culture and tissues.