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Imaging of native transcription and transcriptional dynamics in vivo using a tagged Argonaute protein.

ABSTRACT: A flexible method to image unmodified transcripts and transcription in vivo would be a valuable tool to understand the regulation and dynamics of transcription. Here, we present a novel approach to follow native transcription, with fluorescence microscopy, in live C. elegans. By using the fluorescently tagged Argonaute protein NRDE-3, programmed by exposure to defined dsRNA to bind to nascent transcripts of the gene of interest, we demonstrate transcript labelling of multiple genes, at the transcription site and in the cytoplasm. This flexible approach does not require genetic manipulation, and can be easily scaled up by relying on whole-genome dsRNA libraries. We apply this method to image the transcriptional dynamics of the heat-shock inducible gene hsp-4 (a member of the hsp70 family), as well as two transcription factors: ttx-3 (a LHX2/9 orthologue) in embryos, and hlh-1 (a MyoD orthologue) in larvae, respectively involved in neuronal and muscle development.

SUBMITTER: Toudji-Zouaz A

PROVIDER: S-EPMC8421136 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Imaging of native transcription and transcriptional dynamics in vivo using a tagged Argonaute protein.

Toudji-Zouaz Amel A Bertrand Vincent V Barrière Antoine A

Nucleic acids research 20210901 15

A flexible method to image unmodified transcripts and transcription in vivo would be a valuable tool to understand the regulation and dynamics of transcription. Here, we present a novel approach to follow native transcription, with fluorescence microscopy, in live C. elegans. By using the fluorescently tagged Argonaute protein NRDE-3, programmed by exposure to defined dsRNA to bind to nascent transcripts of the gene of interest, we demonstrate transcript labelling of multiple genes, at the trans ...[more]

PMID: 34107044

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Project description:BackgroundAssessment of regional myocardial function at native pixel-level resolution can play a crucial role in recognizing the early signs of the decline in regional myocardial function. Extensive data processing in existing techniques limits the effective resolution and accuracy of the generated strain maps. The purpose of this study is to compute myocardial principal strain maps εp1 and εp2 from tagged MRI (tMRI) at the native image resolution using deep-learning local patch convolutional neural network (CNN) models (DeepStrain).MethodsFor network training, validation, and testing, realistic tMRI datasets were generated and consisted of 53,606 cine images simulating the heart, the liver, blood pool, and backgrounds, including ranges of shapes, positions, motion patterns, noise, and strain. In addition, 102 in-vivo image datasets from three healthy subjects, and three Pulmonary Arterial Hypertension patients, were acquired and used to assess the network's in-vivo performance. Four convolutional neural networks were trained for mapping input tagging patterns to corresponding ground-truth principal strains using different cost functions. Strain maps using harmonic phase analysis (HARP) were obtained with various spectral filtering settings for comparison. CNN and HARP strain maps were compared at the pixel level versus the ground-truth and versus the least-loss in-vivo maps using Pearson correlation coefficients (R) and the median error and Inter-Quartile Range (IQR) histograms.ResultsCNN-based local patch DeepStrain maps at a phantom resolution of 1.1mm × 1.1 mm and in-vivo resolution of 2.1mm × 1.6 mm were artifact-free with multiple fold improvement with εp1 ground-truth median error of 0.009(0.007) vs. 0.32(0.385) using HARP and εp2 ground-truth error of 0.016(0.021) vs. 0.181(0.08) using HARP. CNN-based strain maps showed substantially higher agreement with the ground-truth maps with correlation coefficients R > 0.91 for εp1 and εp2 compared to R < 0.21 and R < 0.82 for HARP-generated maps, respectively.ConclusionCNN-generated Eulerian strain mapping permits artifact-free visualization of myocardial function at the native image resolution.

Project description:GFP-tagged proteins are used extensively as biosensors for protein localization and function, but the GFP moiety can interfere with protein properties. An alternative is to indirectly label proteins using intracellular recombinant antibodies (scFvs), but most antibody fragments are insoluble in the reducing environment of the cytosol. From a synthetic hyperstable human scFv library we isolated an anti-tubulin scFv, 2G4, which is soluble in mammalian cells when expressed as a GFP-fusion protein. Here we report the use of this GFP-tagged scFv to label microtubules in fixed and living cells. We found that 2G4-GFP localized uniformly along microtubules and did not disrupt binding of EB1, a protein that binds microtubule ends and serves as a platform for binding by a complex of proteins regulating MT polymerization. TOGp and CLIP-170 also bound microtubule ends in cells expressing 2G4-GFP. Microtubule dynamic instability, measured by tracking 2G4-GFP labeled microtubules, was nearly identical to that measured in cells expressing GFP-?-tubulin. Fluorescence recovery after photobleaching demonstrated that 2G4-GFP turns over rapidly on microtubules, similar to the turnover rates of fluorescently tagged microtubule-associated proteins. These data indicate that 2G4-GFP binds relatively weakly to microtubules, and this conclusion was confirmed in vitro. Purified 2G4 partially co-pelleted with microtubules, but a significant fraction remained in the soluble fraction, while a second anti-tubulin scFv, 2F12, was almost completely co-pelleted with microtubules. In cells, 2G4-GFP localized to most microtubules, but did not co-localize with those composed of detyrosinated ?-tubulin, a post-translational modification associated with non-dynamic, more stable microtubules. Immunoblots probing bacterially expressed tubulins confirmed that 2G4 recognized ?-tubulin and required tubulin's C-terminal tyrosine residue for binding. Thus, a recombinant antibody with weak affinity for its substrate can be used as a specific intracellular biosensor that can differentiate between unmodified and post-translationally modified forms of a protein.

Dataset Information

Imaging of native transcription and transcriptional dynamics in vivo using a tagged Argonaute protein.

Publications

Imaging of native transcription and transcriptional dynamics in vivo using a tagged Argonaute protein.

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