A computational framework to study sub-cellular RNA localization

Bento: a toolkit for subcellular analysis of spatial transcriptomics data

The spatial organization of molecules in a cell is essential for their functions. While current methods focus on discerning tissue architecture, cell-cell interactions, and spatial expression patterns, they are limited to the multicellular scale. We present Bento, a Python toolkit that takes advantage of single-molecule information to enable spatial analysis at the subcellular scale. Bento ingests molecular coordinates and segmentation boundaries to perform three analyses: defining subcellular domains, annotating localization patterns, and quantifying gene-gene colocalization. We demonstrate MERFISH, seqFISH + , Molecular Cartography, and Xenium datasets. Bento is part of the open-source Scverse ecosystem, enabling integration with other single-cell analysis tools.

The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma

Finding effective therapeutic targets to treat NRAS-mutated melanoma remains a challenge. Long non-coding RNAs (lncRNAs) recently emerged as essential regulators of tumorigenesis. Using a discovery approach combining experimental models and unbiased computational analysis complemented by validation in patient biospecimens, we identified a nuclear-enriched lncRNA (AC004540.4) that is upregulated in NRAS/MAPK-dependent melanoma, and that we named T-RECS. Considering potential innovative treatment strategies, we designed antisense oligonucleotides (ASOs) to target T-RECS. T-RECS ASOs reduced the growth of melanoma cells and induced apoptotic cell death, while having minimal impact on normal primary melanocytes. Mechanistically, treatment with T-RECS ASOs downregulated the activity of pro-survival kinases and reduced the protein stability of hnRNPA2/B1, a pro-oncogenic regulator of MAPK signaling. Using patient- and cell line- derived tumor xenograft mouse models, we demonstrated that systemic treatment with T-RECS ASOs significantly suppressed the growth of melanoma tumors, with no noticeable toxicity. ASO-mediated T-RECS inhibition represents a promising RNA-targeting approach to improve the outcome of MAPK pathway-activated melanoma.

A systematic evaluation of computation methods for cell segmentation

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including training data and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, which substantially reduces the time and effort for training cell segmentation models.

The therapeutically actionable long non-coding RNA 'T-RECS' is essential to cancer cells' survival in NRAS/MAPK-driven melanoma

Finding effective therapeutic targets to treat NRAS-mutated melanoma remains a challenge. Long non-coding RNAs (lncRNAs) recently emerged as essential regulators of tumorigenesis. Using a discovery approach combining experimental models and unbiased computational analysis complemented by validation in patient biospecimens, we identified a nuclear-enriched lncRNA (AC004540.4) that is upregulated in NRAS/MAPK-dependent melanoma, and that we named T-RECS. Considering potential innovative treatment strategies, we designed antisense oligonucleotides (ASOs) to target T-RECS. T-RECS ASOs reduced the growth of melanoma cells and induced apoptotic cell death, while having minimal impacton normal primary melanocytes. Mechanistically, treatment with T-RECS ASOs downregulated the activity of pro-survival kinases and reduced the protein stability of hnRNPA2/B1, a pro-oncogenic regulator of MAPK signaling. Using patient- and cell line- derived tumor xenograft mouse models, we demonstrated that systemic treatment with T-RECS ASOs significantly suppressed the growth of melanoma tumors, with no noticeable toxicity. ASO-mediated T-RECS inhibition represents a promising RNA-targeting approach to improve the outcome of MAPK pathway-activated melanoma.

Pairwise biosynthesis of ion channels stabilizes excitability and mitigates arrhythmias

Coordinated expression of ion channels is crucial for cardiac rhythms, neural signaling, and cell cycle progression. Perturbation of this balance results in many disorders including cardiac arrhythmias. Prior work revealed association of mRNAs encoding cardiac NaV1.5 (SCN5A) and hERG1 (KCNH2), but the functional significance of this association was not established. Here, we provide a more comprehensive picture of KCNH2, SCN5A, CACNA1C, and KCNQ1 transcripts collectively copurifying with nascent hERG1, NaV1.5, CaV1.2, or KCNQ1 channel proteins. Single-molecule fluorescence in situ hybridization (smFISH) combined with immunofluorescence reveals that the channel proteins are synthesized predominantly as heterotypic pairs from discrete molecules of mRNA, not as larger cotranslational complexes. Puromycin disrupted colocalization of mRNA with its encoded protein, as expected, but remarkably also pairwise mRNA association, suggesting that transcript association relies on intact translational machinery or the presence of the nascent protein. Targeted depletion of KCHN2 by specific shRNA resulted in concomitant reduction of all associated mRNAs, with a corresponding reduction in the encoded channel currents. This co-knockdown effect, originally described for KCNH2 and SCN5A, thus appears to be a general phenomenon among transcripts encoding functionally related proteins. In multielectrode array recordings, proarrhythmic behavior arose when IKr was reduced by the selective blocker dofetilide at IC50 concentrations, but not when equivalent reductions were mediated by shRNA, suggesting that co-knockdown mitigates proarrhythmic behavior expected from the selective reduction of a single channel species. We propose that coordinated, cotranslational association of functionally related ion channel mRNAs confers electrical stability by co-regulating complementary ion channels in macromolecular complexes.

RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies

RNA localization is essential for regulating spatial translation, where RNAs are trafficked to their target locations via various biological mechanisms. In this review, we discuss RNA localization in the context of molecular mechanisms, experimental techniques and machine learning-based prediction tools. Three main types of molecular mechanisms that control the localization of RNA to distinct cellular compartments are reviewed, including directed transport, protection from mRNA degradation, as well as diffusion and local entrapment. Advances in experimental methods, both image and sequence based, provide substantial data resources, which allow for the design of powerful machine learning models to predict RNA localizations. We review the publicly available predictive tools to serve as a guide for users and inspire developers to build more effective prediction models. Finally, we provide an overview of multimodal learning, which may provide a new avenue for the prediction of RNA localization.

Subcellular spatially resolved gene neighborhood networks in single cells

Image-based spatial omics methods such as fluorescence in situ hybridization (FISH) generate molecular profiles of single cells at single-molecule resolution. Current spatial transcriptomics methods focus on the distribution of single genes. However, the spatial proximity of RNA transcripts can play an important role in cellular function. We demonstrate a spatially resolved gene neighborhood network (spaGNN) pipeline for the analysis of subcellular gene proximity relationships. In spaGNN, machine-learning-based clustering of subcellular spatial transcriptomics data yields subcellular density classes of multiplexed transcript features. The nearest-neighbor analysis produces heterogeneous gene proximity maps in distinct subcellular regions. We illustrate the cell-type-distinguishing capability of spaGNN using multiplexed error-robust FISH data of fibroblast and U2-OS cells and sequential FISH data of mesenchymal stem cells (MSCs), revealing tissue-source-specific MSC transcriptomics and spatial distribution characteristics. Overall, the spaGNN approach expands the spatial features that can be used for cell-type classification tasks.

Transcripts of the Prostate Cancer-Associated Gene ANO7 Are Retained in the Nuclei of Prostatic Epithelial Cells

Prostate cancer affects millions of men globally. The prostate cancer-associated gene ANO7 is downregulated in advanced prostate cancer, whereas benign tissue and low-grade cancer display varying expression levels. In this study, we assess the spatial correlation between ANO7 mRNA and protein using fluorescent in situ hybridization and immunohistochemistry for the detection of mRNA and protein in parallel sections of tissue microarrays prepared from radical prostatectomy samples. We show that ANO7 mRNA and protein expression correlate in prostate tissue. Furthermore, we show that ANO7 mRNA is enriched in the nuclei of the luminal cells at 89% in benign ducts and low-grade cancer, and at 78% in high-grade cancer. The nuclear enrichment of ANO7 mRNA was validated in prostate cancer cell lines 22Rv1 and MDA PCa 2b using droplet digital polymerase chain reaction (ddPCR) on RNA isolated from nuclear and cytoplasmic fractions of the cells. The nuclear enrichment of ANO7 mRNA was compared to the nuclearly-enriched lncRNA MALAT1, confirming the surprisingly high nuclear retention of ANO7 mRNA. ANO7 has been suggested to be used as a diagnostic marker and a target for immunotherapy, but a full comprehension of its role in prostate cancer progression is currently lacking. Our results contribute to a better understanding of the dynamics of ANO7 expression in prostatic tissue.

HT-smFISH: a cost-effective and flexible workflow for high-throughput single-molecule RNA imaging

The ability to visualize RNA in its native subcellular environment by using single-molecule fluorescence in situ hybridization (smFISH) has reshaped our understanding of gene expression and cellular functions. A major hindrance of smFISH is the difficulty to perform systematic experiments in medium- or high-throughput formats, principally because of the high cost of generating the individual fluorescent probe sets. Here, we present high-throughput smFISH (HT-smFISH), a simple and cost-efficient method for imaging hundreds to thousands of single endogenous RNA molecules in 96-well plates. HT-smFISH uses RNA probes transcribed in vitro from a large pool of unlabeled oligonucleotides. This allows the generation of individual probes for many RNA species, replacing commercial DNA probe sets. HT-smFISH thus reduces costs per targeted RNA compared with many smFISH methods and is easily scalable and flexible in design. We provide a protocol that combines oligo pool design, probe set generation, optimized hybridization conditions and guidelines for image acquisition and analysis. The pipeline requires knowledge of standard molecular biology tools, cell culture and fluorescence microscopy. It is achievable in ~20 d. In brief, HT-smFISH is tailored for medium- to high-throughput screens that image RNAs at single-molecule sensitivity.

Visualizing and Quantifying mRNA Localization at the Invasive Front of 3D Cancer Spheroids

Localization of mRNAs at the front of migrating cells is a widely used mechanism that functionally supports efficient cell movement. It is observed in single cells on two-dimensional surfaces, as well as in multicellular three-dimensional (3D) structures and in tissue in vivo. 3D multicellular cultures can reveal how the topology of the extracellular matrix and cell-cell contacts influence subcellular mRNA distributions. Here we describe a method for mRNA imaging in an inducible system of collective cancer cell invasion. MDA-MB-231 cancer cell spheroids are embedded in Matrigel, induced to invade, and processed to image mRNAs with single-molecule sensitivity. An analysis algorithm is used to quantify and compare mRNA distributions at the front of invasive leader cells. The approach can be easily adapted and applied to analyze RNA distributions in additional settings where cells polarize along a linear axis.

RNA velocity unraveled

We perform a thorough analysis of RNA velocity methods, with a view towards understanding the suitability of the various assumptions underlying popular implementations. In addition to providing a self-contained exposition of the underlying mathematics, we undertake simulations and perform controlled experiments on biological datasets to assess workflow sensitivity to parameter choices and underlying biology. Finally, we argue for a more rigorous approach to RNA velocity, and present a framework for Markovian analysis that points to directions for improvement and mitigation of current problems.

Single-cell sequencing data are snapshots of biological processes, making it challenging to infer dynamic relationships between cell types. RNA velocity attempts to bypass this challenge by treating the unspliced RNA content as a proxy for spliced RNA content in the near future, and using this “extrapolation” to build directional relationships. However, the method, as implemented in several software packages, is not yet reliable enough to be actionable, in part due to the large number of arbitrary, user-set hyperparameters, as well as fundamental incompatibilities between the biophysics of transcription in the living cell and the models used throughout the velocity workflows. In this study, we review these issues, and use existing results from the fields of stochastic modeling and fluorescence transcriptomics to develop an alternative theoretical framework. We show that our framework can facilitate the development and inference of physically consistent models for sequencing data, as well as the unification of single-cell analyses to self-consistently treat variation due to cell type dynamics and identities, the stochasticity inherent to single-molecule processes, and the uncertainty introduced by sequencing experiments.

Analysis of the Expression and Subcellular Distribution of eEF1A1 and eEF1A2 mRNAs during Neurodevelopment

Neurodevelopment is accompanied by a precise change in the expression of the translation elongation factor 1A variants from eEF1A1 to eEF1A2. These are paralogue genes that encode 92% identical proteins in mammals. The switch in the expression of eEF1A variants has been well studied in mouse motor neurons, which solely express eEF1A2 by four weeks of postnatal development. However, changes in the subcellular localization of eEF1A variants during neurodevelopment have not been studied in detail in other neuronal types because antibodies lack perfect specificity, and immunofluorescence has a low sensitivity. In hippocampal neurons, eEF1A is related to synaptic plasticity and memory consolidation, and decreased eEF1A expression is observed in the hippocampus of Alzheimer's patients. However, the specific variant involved in these functions is unknown. To distinguish eEF1A1 from eEF1A2 expression, we have designed single-molecule fluorescence in-situ hybridization probes to detect either eEF1A1 or eEF1A2 mRNAs in cultured primary hippocampal neurons and brain tissues. We have developed a computational framework, ARLIN (analysis of RNA localization in neurons), to analyze and compare the subcellular distribution of eEF1A1 and eEF1A2 mRNAs at specific developmental stages and in mature neurons. We found that eEF1A1 and eEF1A2 mRNAs differ in expression and subcellular localization over neurodevelopment, and eEF1A1 mRNAs localize in dendrites and synapses during dendritogenesis and synaptogenesis. Interestingly, mature hippocampal neurons coexpress both variant mRNAs, and eEF1A1 remains the predominant variant in dendrites.

Illuminating RNA biology through imaging

RNA processing plays a central role in accurately transmitting genetic information into functional RNA and protein regulators. To fully appreciate the RNA life-cycle, tools to observe RNA with high spatial and temporal resolution are critical. Here we review recent advances in RNA imaging and highlight how they will propel the field of RNA biology. We discuss current trends in RNA imaging and their potential to elucidate unanswered questions in RNA biology.

FISH-quant v2: a scalable and modular tool for smFISH image analysis

Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image data sets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.

Computational Methods for Single-Cell Imaging and Omics Data Integration

Integrating single cell omics and single cell imaging allows for a more effective characterisation of the underlying mechanisms that drive a phenotype at the tissue level, creating a comprehensive profile at the cellular level. Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques such as MRI, CT, and PET. These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring at the tissue level. Single cell imaging can act as an intermediary between these levels. Meanwhile new technologies continue to arrive that can be used to interrogate the genome of single cells and its related omics datasets. As these two areas, single cell imaging and single cell omics, each advance independently with the development of novel techniques, the opportunity to integrate these data types becomes more and more attractive. This review outlines some of the technologies and methods currently available for generating, processing, and analysing single-cell omics- and imaging data, and how they could be integrated to further our understanding of complex biological phenomena like ageing. We include an emphasis on machine learning algorithms because of their ability to identify complex patterns in large multidimensional data.

Regulation and outcomes of localized RNA translation

Spatial segregation of mRNAs in the cytoplasm of cells is a well-known biological phenomenon that is widely observed in diverse species spanning different kingdoms of life. In mammalian cells, localization of mRNAs has been documented and studied quite extensively in highly polarized cells, most notably in neurons, where localized mRNAs function to direct protein production at sites that are quite distant from the soma. Recent studies have strikingly revealed that a large proportion of the cellular transcriptome exhibits polarized distributions even in cells that lack an obvious need for long-range transport, such as fibroblasts or epithelial cells. This review focuses on emerging concepts regarding the functional outcomes of mRNA targeting in the cytoplasm of such cells. We also discuss regulatory mechanisms controlling these events, with an emphasis on the role of cell mechanics and the organization of the cytoskeleton. This article is categorized under: Translation > Regulation RNA Export and Localization > RNA Localization.

Prediction of RNA subcellular localization: Learning from heterogeneous data sources

RNA subcellular localization has recently emerged as a widespread phenomenon, which may apply to the majority of RNAs. The two main sources of data for characterization of RNA localization are sequence features and microscopy images, such as obtained from single-molecule fluorescent in situ hybridization-based techniques. Although such imaging data are ideal for characterization of RNA distribution, these techniques remain costly, time-consuming, and technically challenging. Given these limitations, imaging data exist only for a limited number of RNAs. We argue that the field of RNA localization would greatly benefit from complementary techniques able to characterize location of RNA. Here we discuss the importance of RNA localization and the current methodology in the field, followed by an introduction on prediction of location of molecules. We then suggest a machine learning approach based on the integration between imaging localization data and sequence-based data to assist in characterization of RNA localization on a transcriptome level.

Improved Methods for Single-Molecule Fluorescence In Situ Hybridization and Immunofluorescence in Caenorhabditis elegans Embryos

Visualization of gene products in Caenorhabditis elegans has provided insights into the molecular and biological functions of many novel genes in their native contexts. Single-molecule fluorescence in situ hybridization (smFISH) and immunofluorescence (IF) enable the visualization of the abundance and localization of mRNAs and proteins, respectively, allowing researchers to ultimately elucidate the localization, dynamics, and functions of the corresponding genes. Whereas both smFISH and immunofluorescence have been foundational techniques in molecular biology, each protocol poses challenges for use in the C. elegans embryo. smFISH protocols suffer from high initial costs and can photobleach rapidly, and immunofluorescence requires technically challenging permeabilization steps and slide preparation. Most importantly, published smFISH and IF protocols have predominantly been mutually exclusive, preventing the exploration of relationships between an mRNA and a relevant protein in the same sample. Here, we describe protocols to perform immunofluorescence and smFISH in C. elegans embryos either in sequence or simultaneously. We also outline the steps to perform smFISH or immunofluorescence alone, including several improvements and optimizations to existing approaches. These protocols feature improved fixation and permeabilization steps to preserve cellular morphology while maintaining probe and antibody accessibility in the embryo, a streamlined, in-tube approach for antibody staining that negates freeze-cracking, a validated method to perform the cost-reducing single molecule inexpensive FISH (smiFISH) adaptation, slide preparation using empirically determined optimal antifade products, and straightforward quantification and data analysis methods. Finally, we discuss tricks and tips to help the reader optimize and troubleshoot individual steps in each protocol. Together, these protocols simplify existing workflows for single-molecule RNA and protein detection. Moreover, simultaneous, high-resolution imaging of proteins and RNAs of interest will permit analysis, quantification, and comparison of protein and RNA distributions, furthering our understanding of the relationship between RNAs and their protein products or cellular markers in early development. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Sequential immunofluorescence and single-molecule fluorescence in situ hybridization Alternate Protocol: Abbreviated protocol for simultaneous immunofluorescence and single-molecule fluorescence in situ hybridization Basic Protocol 2: Simplified immunofluorescence in C. elegans embryos Basic Protocol 3: Single-molecule fluorescence in situ hybridization or single-molecule inexpensive fluorescence in situ hybridization.

Interrogating RNA and protein spatial subcellular distribution in smFISH data with DypFISH

Advances in single-cell RNA sequencing have allowed for the identification of cellular subtypes on the basis of quantification of the number of transcripts in each cell. However, cells might also differ in the spatial distribution of molecules, including RNAs. Here, we present DypFISH, an approach to quantitatively investigate the subcellular localization of RNA and protein. We introduce a range of analytical techniques to interrogate single-molecule RNA fluorescence in situ hybridization (smFISH) data in combination with protein immunolabeling. DypFISH is suited to study patterns of clustering of molecules, the association of mRNA-protein subcellular localization with microtubule organizing center orientation, and interdependence of mRNA-protein spatial distributions. We showcase how our analytical tools can achieve biological insights by utilizing cell micropatterning to constrain cellular architecture, which leads to reduction in subcellular mRNA distribution variation, allowing for the characterization of their localization patterns. Furthermore, we show that our method can be applied to physiological systems such as skeletal muscle fibers.

Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis

Cellular and subcellular spatial colocalization of structures and molecules in biological specimens is an important indicator of their co-compartmentalization and interaction. Presently, colocalization in biomedical images is addressed with visual inspection and quantified by co-occurrence and correlation coefficients. However, such measures alone cannot capture the complexity of the interactions, which does not limit itself to signal intensity. On top of the previously developed density distribution maps (DDMs), here, we present a method for advancing current colocalization analysis by introducing co-density distribution maps (cDDMs), which, uniquely, provide information about molecules absolute and relative position and local abundance. We exemplify the benefits of our method by developing cDDMs-integrated pipelines for the analysis of molecules pairs co-distribution in three different real-case image datasets. First, cDDMs are shown to be indicators of colocalization and degree, able to increase the reliability of correlation coefficients currently used to detect the presence of colocalization. In addition, they provide a simultaneously visual and quantitative support, which opens for new investigation paths and biomedical considerations. Finally, thanks to the coDDMaker software we developed, cDDMs become an enabling tool for the quasi real time monitoring of experiments and a potential improvement for a large number of biomedical studies.

RNA transport from transcription to localized translation: a single molecule perspective

Transport of mRNAs is an important step of gene expression, which brings the genetic message from the DNA in the nucleus to a precise cytoplasmic location in a regulated fashion. Perturbation of this process can lead to pathologies such as developmental and neurological disorders. In this review, we discuss recent advances in the field of mRNA transport made using single molecule fluorescent imaging approaches. We present an overview of these approaches in fixed and live cells and their input in understanding the key steps of mRNA journey: transport across the nucleoplasm, export through the nuclear pores and delivery to its final cytoplasmic location. This review puts a particular emphasis on the coupling of mRNA transport with translation, such as localization-dependent translational regulation and translation-dependent mRNA localization. We also highlight the recently discovered translation factories, and how cellular and viral RNAs can hijack membrane transport systems to travel in the cytoplasm.

Intracellular mRNA transport and localized translation

Fine-tuning cellular physiology in response to intracellular and environmental cues requires precise temporal and spatial control of gene expression. High-resolution imaging technologies to detect mRNAs and their translation state have revealed that all living organisms localize mRNAs in subcellular compartments and create translation hotspots, enabling cells to tune gene expression locally. Therefore, mRNA localization is a conserved and integral part of gene expression regulation from prokaryotic to eukaryotic cells. In this Review, we discuss the mechanisms of mRNA transport and local mRNA translation across the kingdoms of life and at organellar, subcellular and multicellular resolution. We also discuss the properties of messenger ribonucleoprotein and higher order RNA granules and how they may influence mRNA transport and local protein synthesis. Finally, we summarize the technological developments that allow us to study mRNA localization and local translation through the simultaneous detection of mRNAs and proteins in single cells, mRNA and nascent protein single-molecule imaging, and bulk RNA and protein detection methods.

A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport

Local translation allows for a spatial control of gene expression. Here, we use high-throughput smFISH to screen centrosomal protein-coding genes, and we describe 8 human mRNAs accumulating at centrosomes. These mRNAs localize at different stages during cell cycle with a remarkable choreography, indicating a finely regulated translational program at centrosomes. Interestingly, drug treatments and reporter analyses reveal a common translation-dependent localization mechanism requiring the nascent protein. Using ASPM and NUMA1 as models, single mRNA and polysome imaging reveals active movements of endogenous polysomes towards the centrosome at the onset of mitosis, when these mRNAs start localizing. ASPM polysomes associate with microtubules and localize by either motor-driven transport or microtubule pulling. Remarkably, the Drosophila orthologs of the human centrosomal mRNAs also localize to centrosomes and also require translation. These data identify a conserved family of centrosomal mRNAs that localize by active polysome transport mediated by nascent proteins.

Centrosomes function as microtubule organizing centers where several mRNAs accumulate. By employing high-throughput single molecule FISH screening, the authors discover that 8 human mRNAs localize to centrosomes with unique cell cycle dependent patterns using an active polysome targeting mechanism.

Density Distribution Maps: A Novel Tool for Subcellular Distribution Analysis and Quantitative Biomedical Imaging

Subcellular spatial location is an essential descriptor of molecules biological function. Presently, super-resolution microscopy techniques enable quantification of subcellular objects distribution in fluorescence images, but they rely on instrumentation, tools and expertise not constituting a default for most of laboratories. We propose a method that allows resolving subcellular structures location by reinforcing each single pixel position with the information from surroundings. Although designed for entry-level laboratory equipment with common resolution powers, our method is independent from imaging device resolution, and thus can benefit also super-resolution microscopy. The approach permits to generate density distribution maps (DDMs) informative of both objects’ absolute location and self-relative displacement, thus practically reducing location uncertainty and increasing the accuracy of signal mapping. This work proves the capability of the DDMs to: (a) improve the informativeness of spatial distributions; (b) empower subcellular molecules distributions analysis; (c) extend their applicability beyond mere spatial object mapping. Finally, the possibility of enhancing or even disclosing latent distributions can concretely speed-up routine, large-scale and follow-up experiments, besides representing a benefit for all spatial distribution studies, independently of the image acquisition resolution. DDMaker, a Software endowed with a user-friendly Graphical User Interface (GUI), is also provided to support users in DDMs creation.

Detecting Differences of Fluorescent Markers Distribution in Single Cell Microscopy: Textural or Pointillist Feature Space?

We consider the detection of change in spatial distribution of fluorescent markers inside cells imaged by single cell microscopy. Such problems are important in bioimaging since the density of these markers can reflect the healthy or pathological state of cells, the spatial organization of DNA, or cell cycle stage. With the new super-resolved microscopes and associated microfluidic devices, bio-markers can be detected in single cells individually or collectively as a texture depending on the quality of the microscope impulse response. In this work, we propose, via numerical simulations, to address detection of changes in spatial density or in spatial clustering with an individual (pointillist) or collective (textural) approach by comparing their performances according to the size of the impulse response of the microscope. Pointillist approaches show good performances for small impulse response sizes only, while all textural approaches are found to overcome pointillist approaches with small as well as with large impulse response sizes. These results are validated with real fluorescence microscopy images with conventional resolution. This, a priori non-intuitive result in the perspective of the quest of super-resolution, demonstrates that, for difference detection tasks in single cell microscopy, super-resolved microscopes may not be mandatory and that lower cost, sub-resolved, microscopes can be sufficient.

Specific binding of VegT mRNA localization signal to membranes in Xenopus oocytes

We have studied the interaction of a VegT mRNA localization signal sequence with the membranes of the mitochondrial cloud in Xenopus oocytes, and the binding of the VegT mRNA signal sequence to the lipid raft regions of the vesicles bounded by ordered and disordered phospholipid bilayers. RNA preference for the membranes of the mitochondrial cloud was confirmed using microscopy of a fluorescence resonance energy transfer from RNA molecules to membranes. Our studies show that VegT mRNA has a higher affinity for ordered regions of lipid bilayers. This conclusion is supported by the dissociation constant measurements for RNA-liposome complex and the visualization of the FRET signal between giant vesicles and RNA. Our data indicate that these affinities are sensitive and distinct to the location of the localization elements within the VegT mRNA localization signal structure. Therefore, specific binding of VegT mRNA localization signal sequence to membranes can be responsible for polarized distribution of VegT mRNA in Xenopus oocytes. We suggest that the mechanism of this binding can involve the interaction of the localization elements within the VegT mRNA signal sequence with lipid raft regions of the mitochondrial cloud membranes, thereby utilizing localization elements as novel lipid raft-binding RNA motifs.

A Dual Protein-mRNA Localization Screen Reveals Compartmentalized Translation and Widespread Co-translational RNA Targeting

Local translation allows spatial control of gene expression. Here, we performed a dual protein-mRNA localization screen, using smFISH on 523 human cell lines expressing GFP-tagged genes. 32 mRNAs displayed specific cytoplasmic localizations with local translation at unexpected locations, including cytoplasmic protrusions, cell edges, endosomes, Golgi, the nuclear envelope, and centrosomes, the latter being cell-cycle-dependent. Automated classification of mRNA localization patterns revealed a high degree of intercellular heterogeneity. Surprisingly, mRNA localization frequently required ongoing translation, indicating widespread co-translational RNA targeting. Interestingly, while P-body accumulation was frequent (15 mRNAs), four mRNAs accumulated in foci that were distinct structures. These foci lacked the mature protein, but nascent polypeptide imaging showed that they were specialized translation factories. For β-catenin, foci formation was regulated by Wnt, relied on APC-dependent polysome aggregation, and led to nascent protein degradation. Thus, translation factories uniquely regulate nascent protein metabolism and create a fine granular compartmentalization of translation.

mRNA localization is linked to translation regulation in the Caenorhabditis elegans germ lineage

Caenorhabditis elegans early embryos generate cell-specific transcriptomes despite lacking active transcription, thereby presenting an opportunity to study mechanisms of post-transcriptional regulatory control. We observed that some cell-specific mRNAs accumulate non-homogenously within cells, localizing to membranes, P granules (associated with progenitor germ cells in the P lineage) and P-bodies (associated with RNA processing). The subcellular distribution of transcripts differed in their dependence on 3'UTRs and RNA binding proteins, suggesting diverse regulatory mechanisms. Notably, we found strong but imperfect correlations between low translational status and P granule localization within the progenitor germ lineage. By uncoupling translation from mRNA localization, we untangled a long-standing question: Are mRNAs directed to P granules to be translationally repressed, or do they accumulate there as a consequence of this repression? We found that translational repression preceded P granule localization and could occur independently of it. Further, disruption of translation was sufficient to send homogenously distributed mRNAs to P granules. These results implicate transcriptional repression as a means to deliver essential maternal transcripts to the progenitor germ lineage for later translation.

Challenges and Strategies in Ascribing Functions to Long Noncoding RNAs

Long noncoding RNAs (lncRNAs) are involved in many physiological and pathological processes, such as development, aging, immunity, and cancer. Mechanistically, lncRNAs exert their functions through interaction with proteins, genomic DNA, and other RNA, leading to transcriptional and post-transcriptional regulation of gene expression, either in cis or in trans; it is often difficult to distinguish between these two regulatory mechanisms. A variety of approaches, including RNA interference, antisense oligonucleotides, CRISPR-based methods, and genetically engineered mouse models, have yielded abundant information about lncRNA functions and underlying mechanisms, albeit with many discrepancies. In this review, we elaborate on the challenges in ascribing functions to lncRNAs based on the features of lncRNAs, including the genomic location, copy number, domain structure, subcellular localization, stability, evolution, and expression pattern. We also describe a framework for the investigation of lncRNA functions and mechanisms of action. Rigorous characterization of cancer-implicated lncRNAs is critical for the identification of bona fide anticancer targets.

Modified in situ Hybridization Chain Reaction Using Short Hairpin DNAs

The visualization of multiple gene expressions in well-preserved tissues is crucial for the elucidation of physiological and pathological processes. In situ hybridization chain reaction (HCR) is a method to visualize specific mRNAs in diverse organisms by applying a HCR that is an isothermal enzyme-free nucleotide polymerization method using hairpin DNAs. Although in situ HCR is a versatile method, this method is not widely used by researchers because of their higher cost than conventional in situ hybridization (ISH). Here, we redesigned hairpin DNAs so that their lengths were half the length of commonly used hairpin DNAs. We also optimized the conjugated fluorophores and linkers. Modified in situ HCR showed sufficient fluorescent signals to detect various mRNAs such as Penk, Oxtr, Vglut2, Drd1, Drd2, and Moxd1 in mouse neural tissues with a high signal-to-noise ratio. The sensitivity of modified in situ HCR in detecting the Oxtr mRNA was better than that of fluorescent ISH using tyramide signal amplification. Notably, the modified in situ HCR does not require proteinase K treatment so that it enables the preservation of morphological structures and antigenicity. The modified in situ HCR simultaneously detected the distributions of c-Fos immunoreactivity and Vglut2 mRNA, and detected multiple mRNAs with a high signal-noise ratio at subcellular resolution in mouse brains. These results suggest that the modified in situ HCR using short hairpin DNAs is cost-effective and useful for the visualization of multiple mRNAs and proteins.

Expansion microscopy of C. elegans

We recently developed expansion microscopy (ExM), which achieves nanoscale-precise imaging of specimens at ~70 nm resolution (with ~4.5x linear expansion) by isotropic swelling of chemically processed, hydrogel-embedded tissue. ExM of C. elegans is challenged by its cuticle, which is stiff and impermeable to antibodies. Here we present a strategy, expansion of C. elegans (ExCel), to expand fixed, intact C. elegans. ExCel enables simultaneous readout of fluorescent proteins, RNA, DNA location, and anatomical structures at resolutions of ~65-75 nm (3.3-3.8x linear expansion). We also developed epitope-preserving ExCel, which enables imaging of endogenous proteins stained by antibodies, and iterative ExCel, which enables imaging of fluorescent proteins after 20x linear expansion. We demonstrate the utility of the ExCel toolbox for mapping synaptic proteins, for identifying previously unreported proteins at cell junctions, and for gene expression analysis in multiple individual neurons of the same animal.

New Generations of MS2 Variants and MCP Fusions to Detect Single mRNAs in Living Eukaryotic Cells

Live imaging of single RNA from birth to death brought important advances in our understanding of the spatiotemporal regulation of gene expression. These studies have provided a comprehensive understanding of RNA metabolism by describing the process step by step. Most of these studies used for live imaging a genetically encoded RNA-tagging system fused to fluorescent proteins. One of the best characterized RNA-tagging systems is derived from the bacteriophage MS2 and it allows single RNA imaging in real-time and live cells. This system has been successfully used to track the different steps of mRNA processing in many living organisms. The recent development of optimized MS2 and MCP variants now allows the labeling of endogenous RNAs and their imaging without modifying their behavior. In this chapter, we discuss the improvements in detecting single mRNAs with different variants of MCP and fluorescent proteins that we tested in yeast and mammalian cells. Moreover, we describe protocols using MS2-MCP systems improved for real-time imaging of single mRNAs and transcription dynamics in S. cerevisiae and mammalian cells, respectively.

RDI Calculator: An Analysis Tool to Assess RNA Distributions in Cells

Localization of RNAs to various subcellular destinations has emerged as a widely used mechanism that regulates a large proportion of transcripts in polarized cells. A number of methodologies have been developed that allow detection and imaging of RNAs at single-molecule resolution. However, methodologies to quantitatively describe RNA distributions are limited. Such approaches usually rely on the identification of cytoplasmic and nuclear boundaries which are used as reference points. Here, we describe an automated, interactive image analysis program that facilitates the accurate generation of cellular outlines from single cells and the subsequent calculation of metrics that quantify how a population of RNA molecules is distributed in the cell cytoplasm. We apply this analysis to mRNAs in mouse and human cells to demonstrate how these metrics can highlight differences in the distribution patterns of distinct RNA species. We further discuss considerations for the practical use of this tool. This program provides a way to facilitate and expedite the analysis of subcellular RNA localization for mechanistic and functional studies.