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

Safieddine, Adham; Coleno, Emeline; Lionneton, Frédéric; Traboulsi, Abdel-Meneem; Salloum, Soha; Lecellier, Charles-Henri; Gostan, Thierry; Georget, Virginie; Hassen‐Khodja, Cédric; Imbert, Arthur; Mueller, Florian; Walter, Thomas; Peter, Matthias; Bertrand, Édouard

doi:10.1038/s41596-022-00750-2

Cited by 25 publications

(16 citation statements)

References 59 publications

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“…In each cell, both approaches detect similar patterns for the number and spatial locations of mRNA within the nuclei (Fig 5B-G). For our particular choice of image processing algorithm ([66, 76, 32]) and intensity threshold for spot detection (see Methods) and a two-pixel (x,y,z) Euclidean distance threshold for co-localization detection, after analyzing 155 cells in steady-state conditions, we found that 34.8% of mRNA spots (12,231 out of 35,151 total) were detected in both channels (e.g., spots denoted by white triangles in Fig 5A). However, many spots (27.7%, 9,750 spots) are detected only using smiFISH (e.g., those denoted with magenta triangles) and 37.5% (13,170 spots) are only detected using the MS2-MCP labels (e.g., green triangles).…”

Section: Resultsmentioning

confidence: 99%

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

Forero²,

Aguilera³

et al. 2021

Preprint

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Measurement error is a complicating factor that could reduce or distort the information contained in an experiment. This problem becomes even more serious in the context of experiments to measure single-cell gene expression heterogeneity, in which important quantities such as RNA and protein copy numbers are themselves subjected to the inherent randomness of biochemical reactions. Yet, it is not clear how measurement noise should be managed, in addition to other experiment design variables such as sampling size and frequency, in order to ensure that the collected data provides useful insights on the gene expression mechanism of interest. To address these experiment design challenges, we propose a model-centric framework that makes explicit use of measurement error modeling and Fisher Information Matrix-based criteria to decide between experimental methods. This unified approach not only allows us to see how different noise characteristics affect uncertainty in parameter estimation, but also enables a systematic approach to designing hybrid experiments that combine different measurement methods.

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Section: Resultsmentioning

confidence: 99%

“…In this study, we employed Python to implement an image processing pipeline comprising three steps: cell segmentation, spot detection, and data management (as previously described in [66]). Nuclear segmentation on the DAPI channel (405nm) was carried out using Cellpose ([76]) with a 70-pixel diameter as an input parameter.…”

Section: Methodsmentioning

confidence: 99%

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

Forero²,

Aguilera³

et al. 2021

Preprint

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“…26 Hence, implementing multiwell readouts in smFRET experiments should lend itself a powerful approach to probe many different conditions in a fully automated manner within a single continuous experiment under controlled conditions. Fluorescence microscopy experiments for large-scale screening, for example, of single-molecule fluorescence in situ hybridization (smFISH), RNA interference or organoids, have been automated already in many applications based on 96-well or larger multiwell plates [27][28][29] . However, this powerful platform has not yet been transferred to a format suitable for applications in smFRET experiments.…”

Section: Introductionmentioning

confidence: 99%

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

Hartmann

Sreenivasa

Schenkel

et al. 2023

Preprint

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Single-molecule FRET (smFRET) has become a widely used tool for probing the structure, dynamics, and functional mechanisms of biomolecular systems, and is extensively used to address questions ranging from biomolecular folding to drug discovery. Investigations by smFRET often require sampling of a large parameter space, for example, by varying one or more constituent molecular components in ten or more steps to reliably extract distances, kinetic rates, and other quantitative parameters. Confocal smFRET measurements, for example, which are amongst the widely used smFRET assays, are typically performed in a single-well format and measurements are conducted in a manual manner, making sampling of many experimental parameters 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 into a confocal microscope to allow for continuous and automated smFRET measurements. We show that the multiwell plate assay is on par with conventional single-well smFRET measurements in terms of accuracy and precision yet enables probing tens to hundreds of conditions in a fully automized manner. We demonstrate the broad applicability of the multiwell plate assay towards DNA hairpin dynamics, protein folding, and competitive and cooperative protein–DNA interactions, revealing new insights that would be hard if not impossible to achieve with conventional single-well format measurements. The higher sampling density afforded by the multiwell plate format increases the accuracy of data analysis by at least 10-fold. We further showcase that the assay provides access to smFRET-based screening of drug–protein interactions. For the adaptation into existing instrumentations, we provide a detailed guide and open-source acquisition and analysis software. Taken together, the automated multiwell plate assay developed here opens up new possibilities to acquire high-content smFRET datasets for in-depth single-molecule analysis of biomolecular conformations, interactions, and dynamics.

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“…Several FISH imaging methods have been developed, such as single-molecule FISH (smFISH), , branched DNA (bDNA) FISH, , and hybrid chain reaction (HCR). , These methods share the goal of amplifying signals by recruiting multiple fluorescent molecules to a specific RNA molecule. For example, early methods like smFISH employed 10–50 fluorescent molecules tethered to individual mRNA molecules of a target gene, resulting in dim signals due to limited fluorescent molecule binding.…”

Section: Introductionmentioning

confidence: 99%

“…As a spatial transcriptomic technique, multiplex FISH profiles transcript molecules at the single-cell level, allowing exploration of tissue organization's molecular signatures. 3−6 Several FISH imaging methods have been developed, such as single-molecule FISH (smFISH), 7,8 branched DNA (bDNA) FISH, 5,9 and hybrid chain reaction (HCR). 10,11 These methods share the goal of amplifying signals by recruiting multiple fluorescent molecules to a specific RNA molecule.…”

Section: Introductionmentioning

confidence: 99%

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

Cao,

Qin,

Wang

et al. 2023

ACS Nano

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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.

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

Cited by 25 publications

References 59 publications

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

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

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

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

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