ArticleBiophysical reports2023
Establishing Riboglow-FLIM to visualize noncoding RNAs inside live zebrafish embryos.
Article in Biophysical reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Expanding the Riboglow-FLIM Toolbox with Different Fluorescence Lifetime-Producing RNA Tags.Biochemistry · 2025Article
- Practical guide to fluorescence lifetime imaging microscopy.Molecular biology of the cell · 2025Review
- Evaluating Riboglow-FLIM probes for RNA sensing.RSC chemical biology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
The central role of RNAs in health and disease calls for robust tools to visualize RNAs in living systems through fluorescence microscopy. Live zebrafish embryos are a popular system to investigate multicellular complexity as disease models. However, RNA visualization approaches in whole organisms are notably underdeveloped. Here, we establish our RNA tagging and imaging platform Riboglow-FLIM for complex cellular imaging applications by systematically evaluating FLIM capabilities. We use adherent mammalian cells as models for RNA visualization. Additional complexity of analyzing RNAs in whole mammalian animals is achieved by injecting these cells into a zebrafish embryo system for cell-by-cell analysis in this model of multicellularity. We first evaluate all variable elements of Riboglow-FLIM quantitatively before assessing optimal use in whole animals. In this way, we demonstrate that a model noncoding RNA can be detected robustly and quantitatively inside live zebrafish embryos using a far-red Cy5-based variant of the Riboglow platform. We can clearly resolve cell-to-cell heterogeneity of different RNA populations by this methodology, promising applicability in diverse fields.
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Registered trials
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