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

Cell-cycle-dependent mRNA localization in P-bodies

Understanding the dynamics of RNA targeting to membraneless organelles is essential to disentangle their functions. Here, we investigate how P-bodies (PBs) evolve during cell-cycle progression in HEK293 cells. PB purification across the cell cycle uncovers widespread changes in their RNA content, partly uncoupled from cell-cycle-dependent changes in RNA expression. Single-molecule fluorescence in situ hybridization (FISH) shows various mRNA localization patterns in PBs peaking in G1, S, or G2, with examples illustrating the timely capture of mRNAs in PBs when their encoded protein becomes dispensable. Rather than directly reflecting absence of translation, cyclic mRNA localization in PBs can be controlled by RBPs, such as HuR in G2, and by RNA features. Indeed, while PB mRNAs are AU rich at all cell-cycle phases, they are specifically longer in G1, possibly related to post-mitotic PB reassembly. Altogether, our study supports a model where PBs are more than a default location for excess untranslated mRNAs.

Cell cycle visualization tools to study cardiomyocyte proliferation in real-time

Cardiomyocytes in the adult human heart are quiescent and those lost following heart injury are not replaced by proliferating survivors. Considerable effort has been made to understand the mechanisms underlying cardiomyocyte cell cycle exit and re-entry, with view to discovering therapeutics that could stimulate cardiomyocyte proliferation and heart regeneration. The advent of large compound libraries and robotic liquid handling platforms has enabled the screening of thousands of conditions in a single experiment but success of these screens depends on the appropriateness and quality of the model used. Quantification of (human) cardiomyocyte proliferation in high throughput has remained problematic because conventional antibody-based staining is costly, technically challenging and does not discriminate between cardiomyocyte division and failure in karyokinesis or cytokinesis. Live cell imaging has provided alternatives that facilitate high-throughput screening but these have other limitations. Here, we (i) review the cell cycle features of cardiomyocytes, (ii) discuss various cell cycle fluorescent reporter systems, and (iii) speculate on what could improve their predictive value in the context of cardiomyocyte proliferation. Finally, we consider how these new methods can be used in combination with state-of-the-art three-dimensional human cardiac organoid platforms to identify pro-proliferative signalling pathways that could stimulate regeneration of the human heart.

High-contrast imaging of cellular non-repetitive drug-resistant genes via in situ dead Cas12a-labeled PCR

In situ imaging of genes of pathogenic bacteria can profile cellular heterogeneity, such as the emergence of drug resistance. Fluorescence in situ hybridization (FISH) serves as a classic approach to image mRNAs inside cells, but it remains challenging to elucidate genomic DNAs and relies on multiple fluorescently labeled probes. Herein, we present a dead Cas12a (dCas12a)-labeled polymerase chain reaction (CasPCR) assay for high-contrast imaging of cellular drug-resistant genes. We employed a syncretic dCas12a-green fluorescent protein (dCas12a-GFP) to tag the amplicons, thereby enabling high-contrast imaging and avoiding multiple fluorescently labeled probes. The CasPCR assay can quantify quinolone-resistant Salmonella enterica in mixed populations and identify them isolated from poultry farms.

Spatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives

Overlaying omics data onto spatial biological dimensions has been a promising technology to provide high-resolution insights into the interactome and cellular heterogeneity relative to the organization of the molecular microenvironment of tissue samples in normal and disease states. Spatial omics can be categorized into three major modalities: (a) next-generation sequencing-based assays, (b) imaging-based spatially resolved transcriptomics approaches including in situ hybridization/in situ sequencing, and (c) imaging-based spatial proteomics. These modalities allow assessment of transcripts and proteins at a cellular level, generating large and computationally challenging datasets. The lack of standardized computational pipelines to analyze and integrate these nonuniform structured data has made it necessary to apply artificial intelligence and machine learning strategies to best visualize and translate their complexity. In this review, we summarize the currently available techniques and computational strategies, highlight their advantages and limitations, and discuss their future prospects in the scientific field.

Multiplexing Imaging of Closely Located Single-Nucleotide Mutations in Single Cells via Encoded in situ PCR

Mutation accumulation in RNAs results in closely located single-nucleotide mutations (SNMs), which is highly associated with the drug resistance of pathogens. Imaging of SNMs in single cells has significance for understanding the heterogeneity of RNAs that are related to drug resistance, but the direct "see" closely located SNMs remains challenging. Herein, we designed an encoded ligation-mediated in situ polymerase chain reaction method (termed enPCR), which enabled the visualization of multiple closely located SNMs in bacterial RNAs. Unlike conventional ligation-based probes that can only discriminate a single SNM, this method can simultaneously image different SNMs at closely located sites with single-cell resolution using modular anchoring probes and encoded PCR primers. We tested the capacity of the method to detect closely located SNMs related to quinolone resistance in the gyrA gene of Salmonella enterica (S. enterica), and found that the simultaneous detection of the closely located SNMs can more precisely indicate the resistance of the S. enterica to quinolone compared to the detection of one SNM. The multiplexing imaging assay for SNMs can serve to reveal the relationship between complex cellular genotypes and phenotypes.

RASP: Optimal Single Puncta Detection in Complex Cellular Backgrounds

Super-resolution and single-molecule microscopies have been increasingly applied to complex biological systems. A major challenge of these approaches is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false-positive puncta that other analysis methods detect and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art methods in precision and speed using image gradients to separate Gaussian-shaped objects from the background. We demonstrate RASP's power by showing that it can extract spatial correlations between microglia, neurons, and α-synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments, with sensitivity down to the level of the single protein. Python and MATLAB codes, enabling users to perform this RASP analysis on their own data, are provided as Supporting Information and links to third-party repositories.

Designing a Hybrid Chain Reaction Probe for Multiplex Transcripts Assay with High-Level Imaging

The hybrid chain reaction (HCR), an isothermal and enzyme-free amplification strategy, has found extensive use in fluorescent in situ hybridization (FISH) assays. However, the existing HCRs are limited, being time-consuming processes and low-efficiency imaging due to weak signal, significantly restricting their application in transcriptomic assays. To address the limitations, we developed nine orthogonal HCR hairpin-pair (hp) probes in this study to enable efficient signal amplification for multiplex assays. To enhance the efficiency and imaging quality of multiplex assays using these HCR probes, we employed two strategies. First, we coupled fluorescent molecules to HCR hairpins via disulfide bonds, facilitating easy removal through chemical cleavage. As a result, the workflow was greatly simplified. Second, we combined HCR with in situ rolling circle amplification (ISRCA), creating ISRCA-HCR, which achieved a 17-fold signal amplification. ISRCA-HCR demonstrated a high-level imaging capability for spatial cell type assays. This study shows the application for cell typing based on the developed HCR probes, enabling accurate and high-level signal amplification for multiplex FISH imaging. This provides an effective research tool for transcriptome and spatial cell type analysis.

Spatial omics: An innovative frontier in aging research

Disentangling the impact of aging on health and disease has become critical as population aging progresses rapidly. Studying aging at the molecular level is complicated by the diverse aging profiles and dynamics. However, the examination of cellular states within aging tissues in situ is hampered by the lack of high-resolution spatial data. Emerging spatial omics technologies facilitate molecular and spatial analysis of tissues, providing direct access to precise information on various functional regions and serving as a favorable tool for unraveling the heterogeneity of aging. In this review, we summarize the recent advances in spatial omics application in multi-organ aging research, which has enhanced the understanding of aging mechanisms from multiple standpoints. We also discuss the main challenges in spatial omics research to date, the opportunities for further developing the technology, and the potential applications of spatial omics in aging and aging-related diseases.

Following the Birth, Life, and Death of mRNAs in Single Cells

Recent advances in single-molecule imaging of mRNAs in fixed and living cells have enabled the lives of mRNAs to be studied with unprecedented spatial and temporal detail. These approaches have moved beyond simply being able to observe specific events and have begun to allow an understanding of how regulation is coupled between steps in the mRNA life cycle. Additionally, these methodologies are now being applied in multicellular systems and animals to provide more nuanced insights into the physiological regulation of RNA metabolism.

An automated single-molecule FRET platform for high-content, multiwell plate screening of biomolecular conformations and dynamics

Single-molecule FRET (smFRET) has become a versatile tool for probing the structure and functional dynamics of biomolecular systems, and is extensively used to address questions ranging from biomolecular folding to drug discovery. Confocal smFRET measurements are amongst the widely used smFRET assays and are typically performed in a single-well format. Thus, sampling of many experimental parameters is laborious and time consuming. To address this challenge, we extend here the capabilities of confocal smFRET beyond single-well measurements by integrating a multiwell plate functionality to allow for continuous and automated smFRET measurements. We demonstrate the broad applicability of the multiwell plate assay towards DNA hairpin dynamics, protein folding, competitive and cooperative protein-DNA interactions, and drug-discovery, revealing insights that would be very difficult to achieve with conventional single-well format measurements. For the adaptation into existing instrumentations, we provide a detailed guide and open-source acquisition and analysis software.

High throughput microscopy and single cell phenotypic image-based analysis in toxicology and drug discovery

Measuring single cell responses to the universe of chemicals (drugs, natural products, environmental toxicants etc.) is of paramount importance to human health as phenotypic variability in sensing stimuli is a hallmark of biology that is considered during high throughput screening. One of the ways to approach this problem is via high throughput, microscopy-based assays coupled with multi-dimensional single cell analysis methods. Here, we will summarize some of the efforts in this vast and growing field, focusing on phenotypic screens (e.g., Cell Painting), single cell analytics and quality control, with particular attention to environmental toxicology and drug screening. We will discuss advantages and limitations of high throughput assays with various end points and levels of complexity.

The endohyphal microbiome: current progress and challenges for scaling down integrative multi-omic microbiome research

As microbiome research has progressed, it has become clear that most, if not all, eukaryotic organisms are hosts to microbiomes composed of prokaryotes, other eukaryotes, and viruses. Fungi have only recently been considered holobionts with their own microbiomes, as filamentous fungi have been found to harbor bacteria (including cyanobacteria), mycoviruses, other fungi, and whole algal cells within their hyphae. Constituents of this complex endohyphal microbiome have been interrogated using multi-omic approaches. However, a lack of tools, techniques, and standardization for integrative multi-omics for small-scale microbiomes (e.g., intracellular microbiomes) has limited progress towards investigating and understanding the total diversity of the endohyphal microbiome and its functional impacts on fungal hosts. Understanding microbiome impacts on fungal hosts will advance explorations of how "microbiomes within microbiomes" affect broader microbial community dynamics and ecological functions. Progress to date as well as ongoing challenges of performing integrative multi-omics on the endohyphal microbiome is discussed herein. Addressing the challenges associated with the sample extraction, sample preparation, multi-omic data generation, and multi-omic data analysis and integration will help advance current knowledge of the endohyphal microbiome and provide a road map for shrinking microbiome investigations to smaller scales. Video Abstract.

Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise

Introduction: Despite continued technological improvements, measurement errors always reduce or distort the information that any real experiment can provide to quantify cellular dynamics. This problem is particularly serious for cell signaling studies to quantify heterogeneity in single-cell gene regulation, where important RNA and protein copy numbers are themselves subject to the inherently random fluctuations of biochemical reactions. Until now, it has not been clear how measurement noise should be managed in addition to other experiment design variables (e.g., sampling size, measurement times, or perturbation levels) to ensure that collected data will provide useful insights on signaling or gene expression mechanisms of interest. Methods: We propose a computational framework that takes explicit consideration of measurement errors to analyze single-cell observations, and we derive Fisher Information Matrix (FIM)-based criteria to quantify the information value of distorted experiments. Results and Discussion: We apply this framework to analyze multiple models in the context of simulated and experimental single-cell data for a reporter gene controlled by an HIV promoter. We show that the proposed approach quantitatively predicts how different types of measurement distortions affect the accuracy and precision of model identification, and we demonstrate that the effects of these distortions can be mitigated through explicit consideration during model inference. We conclude that this reformulation of the FIM could be used effectively to design single-cell experiments to optimally harvest fluctuation information while mitigating the effects of image distortion.

Identifying mRNAs Residing in Myelinating Oligodendrocyte Processes as a Basis for Understanding Internode Autonomy

In elaborating and maintaining myelin sheaths on multiple axons/segments, oligodendrocytes distribute translation of some proteins, including myelin basic protein (MBP), to sites of myelin sheath assembly, or MSAS. As mRNAs located at these sites are selectively trapped in myelin vesicles during tissue homogenization, we performed a screen to identify some of these mRNAs. To confirm locations, we used real-time quantitative polymerase chain reaction (RT-qPCR), to measure mRNA levels in myelin (M) and 'non-myelin' pellet (P) fractions, and found that five (LPAR1, TRP53INP2, TRAK2, TPPP, and SH3GL3) of thirteen mRNAs were highly enriched in myelin (M/P), suggesting residences in MSAS. Because expression by other cell-types will increase p-values, some MSAS mRNAs might be missed. To identify non-oligodendrocyte expression, we turned to several on-line resources. Although neurons express TRP53INP2, TRAK2 and TPPP mRNAs, these expressions did not invalidate recognitions as MSAS mRNAs. However, neuronal expression likely prevented recognition of KIF1A and MAPK8IP1 mRNAs as MSAS residents and ependymal cell expression likely prevented APOD mRNA assignment to MSAS. Complementary in situ hybridization (ISH) is recommended to confirm residences of mRNAs in MSAS. As both proteins and lipids are synthesized in MSAS, understanding myelination should not only include efforts to identify proteins synthesized in MSAS, but also the lipids.