ai_agent_IP

ai_agent

maintenance

instantTrialDurationMinutes

isBiopharma

enableNewMyJoveSectionDesign

educationFeatures

seoMetaApi

ai_copilot_institution_blacklist

ai_chat_institution_blacklist

freeAccessWindow

ssoRoleCapture

scheduledMaintenanceBanner

joveLabsFeatures

disable_autoplay_for_bots

extended_trial_duration

5 minutes

Work in the Braselmann lab is supported by the National Institutes of Health (R35GM150823 to E.B.), the Luce Foundation (E.B.), and the Department of Chemistry at Georgetown University (Espenscheid fellowship to L.K.S.). This work was part of lab course CHEM 4505 at Georgetown University. All students enrolled in CHEM 4505 participated in data collection, analysis, and development of this manuscript and are listed as co-authors. All authors thank Sanuja Mohanaraj and Dr. Rodrigo Maillard for support during development of this manuscript. The authors also thank Emerson Boggs and Dr. Clayton Hazelett for their technical feedback.
DATA AVAILABILITY
All datasets and analysis files will be made available in a repository (a publicly available Box folder with reference to this manuscript) upon publication.

<ol><li>Bertrand, E., Chartrand, P., Schaefer, M., Shenoy, S. M., Singer, R. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Localization+of+ASH1+mRNA+Particles+in+Living+Yeast%5BTitle%5D)+AND+%22Molecular+Cell%22%5BJournal%5D)">Localization of ASH1 mRNA Particles in Living Yeast.</a> Molecular Cell. 2 (4), 437-445 (1998).</li>
<li>Johansson, H. E., Liljas, L., Uhlenbeck, O. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((RNA+Recognition+by+the+MS2+Phage+Coat+Protein%5BTitle%5D)+AND+%22Seminars+in+Virology%22%5BJournal%5D)">RNA Recognition by the MS2 Phage Coat Protein.</a> Seminars in Virology. 8 (3), 176-185 (1997).</li>
<li>Braselmann, E., Rathbun, C., Richards, E. M., Palmer, A. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Illuminating+RNA+Biology%3A+Tools+for+Imaging+RNA+in+Live+Mammalian+Cells%5BTitle%5D)+AND+%22Cell+Chemical+Biology%22%5BJournal%5D)">Illuminating RNA Biology: Tools for Imaging RNA in Live Mammalian Cells.</a> Cell Chemical Biology. 27 (8), 891-903 (2020).</li>
<li>Paige, J. S., Wu, K. Y., Jaffrey, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((RNA+Mimics+of+Green+Fluorescent+Protein%5BTitle%5D)+AND+%22Science%22%5BJournal%5D)">RNA Mimics of Green Fluorescent Protein.</a> Science. 333 (6042), 642-646 (2011).</li>
<li>Filonov, G. S., Moon, J. D., Svensen, N., Jaffrey, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Broccoli%3A+Rapid+Selection+of+an+RNA+Mimic+of+Green+Fluorescent+Protein+by+Fluorescence-Based+Selection+and+Directed+Evolution%5BTitle%5D)+AND+%22Journal+of+the+American+Chemical+Society%22%5BJournal%5D)">Broccoli: Rapid Selection of an RNA Mimic of Green Fluorescent Protein by Fluorescence-Based Selection and Directed Evolution.</a> Journal of the American Chemical Society. 136 (46), 16299-16308 (2014).</li>
<li>Song, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Imaging+RNA+polymerase+III+transcription+using+a+photostable+RNA%E2%80%93fluorophore+complex%5BTitle%5D)+AND+%22Nature+Chemical+Biology%22%5BJournal%5D)">Imaging RNA polymerase III transcription using a photostable RNA–fluorophore complex.</a> Nature Chemical Biology. 13 (11), 1187-1194 (2017).</li>
<li>Dolgosheina, E. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((RNA+Mango+Aptamer-Fluorophore%3A+A+Bright%2C+High-Affinity+Complex+for+RNA+Labeling+and+Tracking%5BTitle%5D)+AND+%22ACS+Chemical+Biology%22%5BJournal%5D)">RNA Mango Aptamer-Fluorophore: A Bright, High-Affinity Complex for RNA Labeling and Tracking.</a> ACS Chemical Biology. 9 (10), 2412-2420 (2014).</li>
<li>Chen, X., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Visualizing+RNA+dynamics+in+live+cells+with+bright+and+stable+fluorescent+RNAs%5BTitle%5D)+AND+%22Nature+Biotechnology%22%5BJournal%5D)">Visualizing RNA dynamics in live cells with bright and stable fluorescent RNAs.</a> Nature Biotechnology. 37 (11), 1287-1293 (2019).</li>
<li>Sunbul, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Super-resolution+RNA+imaging+using+a+rhodamine-binding+aptamer+with+fast+exchange+kinetics%5BTitle%5D)+AND+%22Nature+Biotechnology%22%5BJournal%5D)">Super-resolution RNA imaging using a rhodamine-binding aptamer with fast exchange kinetics.</a> Nature Biotechnology. 39 (6), 686-690 (2021).</li>
<li>Chen, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+molecular+beacon-based+approach+for+live-cell+imaging+of+RNA+transcripts+with+minimal+target+engineering+at+the+single-molecule+level%5BTitle%5D)+AND+%22Scientific+Reports%22%5BJournal%5D)">A molecular beacon-based approach for live-cell imaging of RNA transcripts with minimal target engineering at the single-molecule level.</a> Scientific Reports. 7 (1), 1550(2017).</li>
<li>Raj, A., Van Den Bogaard, P., Rifkin, S. A., Van Oudenaarden, A., Tyagi, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Imaging+individual+mRNA+molecules+using+multiple+singly+labeled+probes%5BTitle%5D)+AND+%22Nature+Methods%22%5BJournal%5D)">Imaging individual mRNA molecules using multiple singly labeled probes.</a> Nature Methods. 5 (10), 877-879 (2008).</li>
<li>Bratu, D. P., Cha, B. -J., Mhlanga, M. M., Kramer, F. R., Tyagi, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Visualizing+the+distribution+and+transport+of+mRNAs+in+living+cells%5BTitle%5D)+AND+%22Proceedings+of+the+National+Academy+of+Sciences%22%5BJournal%5D)">Visualizing the distribution and transport of mRNAs in living cells.</a> Proceedings of the National Academy of Sciences. 100 (23), 13308-13313 (2003).</li>
<li>Zuo, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Imaging+the+dynamics+of+messenger+RNA+with+a+bright+and+stable+green+fluorescent+RNA%5BTitle%5D)+AND+%22Nature+Chemical+Biology%22%5BJournal%5D)">Imaging the dynamics of messenger RNA with a bright and stable green fluorescent RNA.</a> Nature Chemical Biology. 20 (10), 1272-1281 (2024).</li>
<li>Grün, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Super-Resolved+Protein+Imaging+Using+Bifunctional+Light-Up+Aptamers%5BTitle%5D)+AND+%22Angewandte+Chemie+International+Edition%22%5BJournal%5D)">Super-Resolved Protein Imaging Using Bifunctional Light-Up Aptamers.</a> Angewandte Chemie International Edition. 63 (51), e202412810(2024).</li>
<li>Braselmann, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+multicolor+riboswitch-based+platform+for+imaging+of+RNA+in+live+mammalian+cells%5BTitle%5D)+AND+%22Nature+Chemical+Biology%22%5BJournal%5D)">A multicolor riboswitch-based platform for imaging of RNA in live mammalian cells.</a> Nature Chemical Biology. 14 (10), 964-971 (2018).</li>
<li>Sarfraz, N., Moscoso, E., Oertel, T., Lee, H. J., Ranjit, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Visualizing+orthogonal+RNAs+simultaneously+in+live+mammalian+cells+by+fluorescence+lifetime+imaging+microscopy+%28FLIM%29%5BTitle%5D)+AND+%22Nature+Communications%22%5BJournal%5D)">Visualizing orthogonal RNAs simultaneously in live mammalian cells by fluorescence lifetime imaging microscopy (FLIM).</a> Nature Communications. 14 (1), 867(2023).</li>
<li>Sarfraz, N., Shafik, L. K., Stickelman, Z. R., Shankar, U., Moscoso, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluating+Riboglow-FLIM+probes+for+RNA+sensing%5BTitle%5D)+AND+%22RSC+Chemical+Biology%22%5BJournal%5D)">Evaluating Riboglow-FLIM probes for RNA sensing.</a> RSC Chemical Biology. 5 (2), 109-116 (2024).</li>
<li>Sarfraz, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Establishing+Riboglow-FLIM+to+visualize+noncoding+RNAs+inside+live+zebrafish+embryos%5BTitle%5D)+AND+%22Biophysical+Reports%22%5BJournal%5D)">Establishing Riboglow-FLIM to visualize noncoding RNAs inside live zebrafish embryos.</a> Biophysical Reports. 3 (4), 100132(2023).</li>
<li>Datta, R., Heaster, T. M., Sharick, J. T., Gillette, A. A., Skala, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fluorescence+lifetime+imaging+microscopy%3A+fundamentals+and+advances+in+instrumentation%2C+analysis%2C+and+applications%5BTitle%5D)+AND+%22Journal+of+Biomedical+Optics%22%5BJournal%5D)">Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.</a> Journal of Biomedical Optics. 25 (07), 1(2020).</li>
<li>Stickelman, Z., Sarfraz, N., Rice, M. K., Lambeck, B. J., Milkovich, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Expanding+the+Riboglow-FLIM+Toolbox+with+Different+Fluorescence+Lifetime-Producing+RNA+Tags%5BTitle%5D)+AND+%22Biochemistry%22%5BJournal%5D)">Expanding the Riboglow-FLIM Toolbox with Different Fluorescence Lifetime-Producing RNA Tags.</a> Biochemistry. 64 (11), 2429-2438 (2025).</li>
<li>Shafik, L. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluating+Linker+Architecture+in+RNA-Detecting+Riboglow+Probes+and+Effects+on+Fluorescence+Turn-On%5BTitle%5D)+AND+%22ACS+Chemical+Biology%22%5BJournal%5D)">Evaluating Linker Architecture in RNA-Detecting Riboglow Probes and Effects on Fluorescence Turn-On.</a> ACS Chemical Biology. 21 (2), 371-379 (2026).</li>
<li>Cialek, C. A., Galindo, G., Koch, A. L., Saxton, M. N., Stasevich, T. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Bead+Loading+Proteins+and+Nucleic+Acids+into+Adherent+Human+Cells%5BTitle%5D)+AND+%22Journal+of+Visualized+Experiments%22%5BJournal%5D)">Bead Loading Proteins and Nucleic Acids into Adherent Human Cells.</a> Journal of Visualized Experiments. (172), e62559(2021).</li>
<li>Sarfraz, N., Braselmann, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Practical+guide+to+fluorescence+lifetime+imaging+microscopy%5BTitle%5D)+AND+%22Molecular+Biology+of+the+Cell%22%5BJournal%5D)">Practical guide to fluorescence lifetime imaging microscopy.</a> Molecular Biology of the Cell. 36 (6), tp1(2025).</li>
</ol>

The authors have no conflicts of interest to disclose.

Riboglow-FLIM provides a framework for quantitative RNA imaging by taking advantage of fluorescence lifetime readouts. Successful application of this protocol depends critically on careful control of photon acquisition, decay fitting, and unbiased sampling. Photon counts must be balanced to ensure sufficient statistics for reliable n-exponential reconvolution while avoiding detector saturation, pileup effects, and photobleaching that artificially decrease extracted lifetimes. In practice, insufficient photon numbers most often result in failed fits, especially when using small ROIs in cell imaging such as attempting to resolve small cellular compartments, whereas excessive photon flux compresses decay curves due to binning limitations of TCSPC detection. Selecting appropriate dwell times, frame numbers, and laser power based on experimental goals is therefore essential. Dwell time and frame number together determine the total photon budget by controlling how long each pixel is sampled and how many times the field of view is revisited, respectively, whereas laser power sets the excitation rate and therefore photon yield per dwell period, with direct consequences for signal-to-noise, photobleaching, and pileup. Equally important is avoiding overfitting of decay curves by minimizing model parameters and confirming random residuals, as overparameterization systematically biases lifetime values downward. The choice of lifetime metric is an important analytical consideration, as amplitude weighted (&#964;AvAmp) and intensity weighted (&#964;AvInt) averages reflect&#160;different aspects of multiexponential decay and are not interchangeable. Consistent with prior guidance, &#964;AvAmp is used here because it more directly represents the fractional contributions of lifetime components and is better suited for resolving heterogeneous biological environments23. Accurate determination of the instrument response function (IRF) is required for reliable reconvolution fitting, especially when resolving short lifetime components. A calculated IRF is used to maintain experimental fitting consistency over time&#160;yet may introduce systematic error if it deviates from the true instrument response. Periodic measurement of the IRF using a potassium iodide standard should be conducted to verify agreement between measured and calculated IRFs. For cellular experiments, unbiased sampling requires assessment of cell health and probe loading prior to lifetime extraction, as post hoc exclusion based on lifetime outcomes introduces selection bias. Bead-loading introduces additional variability in cell viability, and only cells exhibiting normal morphology and stable fluorescence signal as determined by brightfield or confocal imaging should be included in analysis. Irregular structures such as rounding, blebbing, or dim cells should be excluded22. In our experience, imaging is best completed within approximately 3 h of bead loading to minimize cellular stress, which can alter fluorescence lifetime measurements over time.
Decay curve fitting represents the most common troubleshooting challenge in Riboglow-FLIM experiments. Failed fits can be identified by nonphysical parameters such as negative fit amplitudes (an &#60; 0 in FLIM analysis fits), poor overlap between fitted and measured decays, or structured residuals. In many cases, fitting quality can be improved by adjusting the temporal fit boundaries to exclude low-signal or late-time noise while preserving the linear region of the decay on a logarithmic scale. Although this approach slightly reduces lifetime resolution, it minimally affects extracted average lifetimes and allows otherwise usable datasets to be retained. When fitting failures persist despite sufficient photon counts and boundary optimization, exclusion of the acquisition is warranted. For large scale cellular studies, protocol modifications such as preselecting cells by confocal imaging and automating multipoint FLIM acquisitions can substantially increase throughput, though these approaches require stable focus control using the microscope&#8217;s perfect focus system to minimize Z-drift during extended imaging sessions. This protocol is demonstrated on a Nikon Ti2 Eclipse AX system with PicoQuant TCSPC hardware, but general acquisition and analysis principles are transferable to other FLIM platforms such as Leica SP8 or Abberior STEDYCON systems provided that equivalent control over photon counting, timing resolution, and detector configuration is maintained. While SymPhoTime 64 is used here for analysis, exported FLIM datasets are compatible with other analysis software packages that support TCSPC-based formats, and users may adapt workflows accordingly.
Several limitations of the method should be considered when designing experiments. First, regions of interest defined during confocal imaging cannot be directly transferred into FLIM analysis software and must instead be redrawn manually for each FLIM dataset, introducing additional analysis time and potential user-dependent variability. Additionally, current FLIM processing workflows require individual analysis of Z-stack slices since volumetric lifetime fitting is not currently supported in SymPhoTime 64, increasing analysis time and fragmenting photon statistics across slices. This fragmentation reduces the effective photon count per measurement and can lower fitting precision in dim regions or small compartments. This limitation becomes impactful in 3D cellular imaging where reduced photon counts per slice and increased system complexity decrease lifetime resolution. Since multiple ROIs are often extracted from the same cell across slices, these measurements are not fully independent, which reduces the effective biological repeats and should be considered in statistical interpretation. Consistent with this constraint, small sample sizes in 3D experiments may obscure biologically meaningful lifetime differences that are apparent in single-cell or 2D analyses due to reduced photon counts in defined ROIs. Additionally, very small or dim subcellular localizations are difficult to fit reliably when spatial resolution or photon density is insufficient, further emphasizing the tradeoff between spatial detail and lifetime precision as sample complexity increases.
Despite these limitations, this protocol addresses an unmet need by providing a detailed and standardized workflow for implementation of Riboglow-FLIM across sample types. While Riboglow has been previously applied using intensity-based measurements, Riboglow-FLIM enables a quantitative and environment-sensitive readout that is largely independent of probe concentration and RNA expression level. Fluorescence lifetime has been reported in prior studies to offer advantages over intensity-based approaches, including reduced sensitivity to probe concentration, photobleaching, and optical path differences. Importantly, no standardized protocol for Riboglow-FLIM acquisition and analysis has previously been published, and the detailed workflow presented here establishes a set of experimental considerations for unbiased data collection, fitting discipline, and interpretation across in vitro, cellular, and 3D systems.
The availability of a validated Riboglow-FLIM protocol expands the experimental toolkit for studying RNA dynamics, localization, and regulation in live cells. This approach is well suited for experiments requiring quantitative comparison across subcellular compartments, time points, or experimental conditions, as well as for multiplexed RNA imaging using orthogonal lifetime signatures. Beyond fundamental RNA biology, this protocol is readily applicable to studies of RNA processing, transport, stress response, and transcriptional regulation in increasingly complex biological models. As FLIM instrumentation and analysis software continue&#160;to evolve, the methodology established here provides a foundation for extending lifetime-based RNA imaging into higher dimensional and in vivo systems.

In recent years, advancements in understanding the role of RNAs in cellular function have created a growing need to visualize RNAs in live cells, particularly in disease states. However, the absence of naturally fluorescent RNAs necessitates engineered labeling systems, often combined with exogenous fluorogenic probes. As a result, a wide range of RNA imaging approaches have been developed to enable visualization of RNA localization, dynamics, and interactions in living systems.
One major class of RNA imaging methods relies on genetically encoded tags. Fluorophore-aptamer systems and protein-based tagging strategies, such as the MS2 bacteriophage coat protein (MCP) system, remain widely used1,2. In the MS2 system, RNA stem loops are bound by bacteriophage coat proteins fused to fluorescent proteins to track transcripts in live cells. While useful, this approach requires relatively large RNA tags and production of additional protein components, which can perturb native RNA behavior1,2,3. Fluorophore aptamer systems, including Spinach4 and subsequent variants such as Broccoli5, Corn6, Mango7, and Pepper8, enable direct fluorescence activation upon ligand binding and offer reduced tag size. However, these systems can suffer from limited signal intensity, background fluorescence, and challenges with multiplexing in complex cellular environments3.
Alternative strategies include fluorophore-quencher systems and hybridization-based approaches. Fluorophore-quencher systems, including RhoBAST, produce fluorescence upon disruption of quenching following RNA binding, but can exhibit background signal and sensitivity to probe concentration3,9. Hybridization-based RNA imaging methods, such as smFISH and molecular beacons, provide high specificity but require probe delivery and are often limited in long term live cell imaging due to binding kinetics and off target interactions10,11,12. Collectively, these approaches highlight key challenges in live-cell RNA imaging3,13,14. Despite these advances, there is a lack of standardized workflows for quantitative fluorescence lifetime-based RNA imaging in complex biological systems.
Riboglow attempts to overcome many of these limitations. Riboglow is a genetically encoded RNA tagging system that combines a short riboswitch-derived RNA aptamer &#8220;tag&#8221; with a synthetic small-molecule cobalamin (Cbl)-fluorophore &#8220;probe,&#8221; enabling the visualization of live-cell RNAs15. Cbl, a natural quencher, becomes spatially separated from the fluorophore upon tag binding, producing a quantifiable fluorescence &#8220;turn-on&#8221; in intensity15. Expansion of Riboglow into fluorescence lifetime imaging microscopy (FLIM) revealed a readout that is largely independent of fluorophore concentration and excitation intensity, buffering against probe delivery variability and inter-user differences16,17. More importantly, varying the RNA aptamer results in unique fluorescence lifetimes, as visualized via FLIM16. These orthogonal lifetimes enable multiplexed RNA imaging, allowing two RNAs to be visualized with a single fluorophore16. The platform has been validated across diverse mammalian models, including U-2 OS, HeLa, MDA-MB-231, and HOS cells, and with simultaneous visualization of ACTB mRNA and NORAD lncRNA15,16,17. More recently, Riboglow has been used to visualize RNAs in live animal embryos18. Together, these studies establish Riboglow as a compact and versatile system for quantitative multiplexed RNA imaging.
In biological systems, FLIM has been widely applied to study molecular interactions, metabolism, and cellular dynamics in living systems due to its sensitivity to the local molecular environment and relative robustness to experimental variability19. FLIM measures the excited state decay rate from a fluorescent sample, typically using time-correlated single-photon counting (TCSPC). TCSPC measures the time between laser excitation of a sample and the arrival of the emitted photon at the detector, compiling the acquired photon lifetimes into a distribution of photon arrival time for each measurement. Lifetime-based imaging offers an important advantage by reducing dependence on concentrations for fluorogenic parts of the system, including probe loaded into cells, RNA expression level, and optical path variations. However, FLIM experiments are conceptually and technically demanding, requiring careful control of photon acquisition, fitting models, and analysis workflows.
Here, a detailed protocol for Riboglow-FLIM is presented, describing workflows for sample preparation, image acquisition, and quantitative analysis of fluorescence lifetime datasets. The objective of this study is to establish a reproducible workflow for quantitative Riboglow-FLIM imaging across biological systems. Riboglow-FLIM is best suited for quantitative comparisons and requires specialized FLIM hardware and analysis expertise. The protocol is demonstrated in vitro, where RNA-dependent lifetime changes are measured, and in live mammalian cells and 3D cellular systems where FLIM acquisition, region of interest selection, and quantitative lifetime extraction are established using Riboglow probes. This protocol lays the important foundation of establishing FLIM acquisition workflows and principles for quantitative and unbiased FLIM data analysis, enabling future applications for Riboglow-FLIM or other FLIM-based systems. Emphasis is placed on experimental design choices, unbiased data collection, and common challenges encountered during FLIM acquisition and analysis. While demonstration of RNA detection in cells using transfected Riboglow-tagged constructs has been reported previously, none provide a step-by-step acquisition and analysis workflow, especially across 2D and 3D systems. Together, this work provides a resource for implementing Riboglow-FLIM as a tool for live-cell RNA imaging.

<table><tbody><tr><td>15 mL centrifuge tube</td><td>Abdos</td><td>P10402</td><td>Used for cell culture and to construct the bead loader</td></tr><tr><td>Cbl-3xGly-ATTO590</td><td>N/A</td><td>N/A</td><td>Used for detection of RNA in the Riboglow system, synthesis information available here: https://doi.org/10.1021/acschembio.5c00917</td></tr><tr><td>Cbl-5xGly-ATTO590</td><td>N/A</td><td>N/A</td><td>Used for detection of RNA in the Riboglow system, synthesis information available here: https://doi.org/10.1021/acschembio.5c00918</td></tr><tr><td>Cell detachment media</td><td>Gibco</td><td>12605-28</td><td>Used for cell splitting and transfer</td></tr><tr><td>Cell Imaging Dishes</td><td>Ibidi</td><td>81218-200</td><td>Used for live cell imaging</td></tr><tr><td>Cell Microscopy DMEM</td><td>Gibco</td><td>A1896701</td><td>Used for live cell imaging</td></tr><tr><td>Confocal Microscope System</td><td>Nikon</td><td>&amp;nbsp;AX</td><td>Used for cellular confocal imaging</td></tr><tr><td>DMEM</td><td>Gibco</td><td>1195-092</td><td>Used for mammalian cell culture</td></tr><tr><td>FBS</td><td>Cytiva</td><td>SH30910.03</td><td>Used to serum supplement DMEM</td></tr><tr><td>Fluorescence lifetime imaging (FLIM) analysis software</td><td>PicoQuant</td><td>SymPhoTime 64, version 2.9, build 5818</td><td>Used for FLIM analysis</td></tr><tr><td>Glass beads</td><td>Millipore Sigma</td><td>G4649</td><td>Used to bead-load Riboglow probes into live cells</td></tr><tr><td>Glass Coverslips</td><td>VWR</td><td>48368 062</td><td>Used for In vitro imaging.</td></tr><tr><td>HEPES</td><td>Sigma</td><td>H3375</td><td>Used to make the RNA buffer.</td></tr><tr><td>High Yield RNA Synthesis Kit</td><td>Thermo Scientific</td><td>K0441</td><td>RNA transcription kit</td></tr><tr><td>Hybrid Photomultiplier Detector</td><td>PicoQuant</td><td>PMA Hybrid Series</td><td>used for times photon detection for fluorescence lifetime measurement.</td></tr><tr><td>KCl</td><td>Fisher Scientific</td><td>BP366</td><td>Used to make the RNA buffer.</td></tr><tr><td>Live Cell Nuclei Stain</td><td>Invitrogen</td><td>R37605</td><td>Used to stain cellular nuclei during live cell imaging</td></tr><tr><td>Mammalian Cell Cryo Tubes</td><td>Fisher Scientific</td><td>12-567-501</td><td>Used for mammalian cell storage</td></tr><tr><td>MgCl&lt;sub&gt;2&lt;/sub&gt;</td><td>Sigma</td><td>M8266</td><td>Used to make the RNA buffer.</td></tr><tr><td>Microcentrifuge Tubes</td><td>Thermo Scientific</td><td>90410</td><td>Used in general in-vitro and cell culture work</td></tr><tr><td>Microscope Base</td><td>Nikon&amp;nbsp;</td><td>Ti2 Eclipse</td><td>Used for in vitro and cellular imaging.</td></tr><tr><td>Microscope Objective</td><td>Nikon</td><td>N Plan Apochromat</td><td>Used for in vitro and cellular imaging.</td></tr><tr><td>Microscope Operation Software/Image Acquisition and Analysis Software</td><td>Nikon</td><td>NIS-Elements, version 6.20.02.&amp;nbsp;</td><td></td></tr><tr><td>Microvolume Spectrophotometer</td><td>Thermo Scientific</td><td>ND-2000</td><td>Used for DNA and RNA concentration and purity determination</td></tr><tr><td>Multichannel Event Timer</td><td>PicoQuant</td><td>MultiHarp 150</td><td>Used for TCSPC to extract fluorescence lifetime from in vitro and cellular samples.</td></tr><tr><td>NaCl</td><td>Fisher Scientific</td><td>BP358</td><td>Used to make the RNA buffer.</td></tr><tr><td>PBS, 1X</td><td>Corning</td><td>21-040-CV</td><td>Used for cell washes and bead removal</td></tr><tr><td>Pulsed Diode Laser and Laser Combining Unit</td><td>PicoQuant</td><td>Sepia PDL 828, PicoQuant LCU</td><td>Used for laser excitation of in vitro and cellular samples.</td></tr><tr><td>RNA Cleanup Kit</td><td>New England Biolabs</td><td>T2050L</td><td>RNA clean-up kit</td></tr><tr><td>RNAse denaturant</td><td>Invitrogen</td><td>AM9780</td><td>Used to prepare an RNAse-free environment</td></tr><tr><td>Tissue Culture Dishes</td><td>Fisher Scientific</td><td>FB012923</td><td>Used for general cell culture and upkeep</td></tr></tbody></table>

characterizing riboglow probes in vitro as the basis for fluorescence lifetime imaging in live mammalian cells and three-dimensional cellular models

Characterizing Riboglow Probes In Vitro as the Basis for Fluorescence Lifetime Imaging In Live Mammalian Cells and Three-Dimensional Cellular Models

Nearly 80% of the human genome is transcribed into RNA, while less than 2% encode for proteins, indicating that the majority of mammalian transcripts are noncoding and participate in diverse regulatory processes. Therefore, sensing and visualizing RNA molecules in live mammalian cell systems quantitatively are critical to understanding RNA dynamics and interactions, yet remains technically challenging, especially in complex cellular environments. Riboglow is a genetically encoded RNA biosensor in which a short RNA aptamer binds a small-molecule probe, producing a quantifiable fluorescence lifetime turn-on detectable by fluorescence lifetime imaging microscopy (FLIM). Here, we present a detailed workflow for Riboglow-FLIM, including sample preparation, image acquisition, and quantitative analysis of FLIM datasets. The goal of this protocol is to enable quantitative fluorescence lifetime-based RNA detection using Riboglow in controlled and live-cell environments. The protocol is demonstrated in vitro, where RNA dependent lifetime changes are measured, and in live mammalian cells, where FLIM acquisition, region of interest selection, and subcellular analysis are established. Successful implementation requires careful control of experimental and acquisition parameters. Key considerations for reproducible implementation are highlighted. Together, this protocol serves as a practical reference for implementing Riboglow-FLIM and quantitatively assessing RNA visualization in live cells.

A complete graphical overview of the experimental workflow can be found in Figure 1. To minimize experimental bias, datasets may be analyzed blinded. As an illustration for this purpose, all sample identities were kept hidden from researchers during data collection and processing. As such, experimental groups are labeled by their assigned identifier (group A, group B, etc.), and their true identities are defined in the text and figure captions.
Following purification of the RNA A Tag, the in vitro fluorescence lifetime of two Riboglow probes, Cbl-3xGly-ATTO590 (3xGly) and Cbl-5xGly-ATTO590 (5xGly), were measured in the presence and absence of the RNA A Tag. Probes 3xGly and 5xGly are identical except for the number of glycine monomeric repeats in their linker segments, three for 3xGly and five for 5xGly (Figure 2D). In vitro fluorescence lifetime was collected and analyzed using methods described above, and overall decay was analyzed without ROI selection (Figure 2E-2G). Following n-exponential reconvolution, τAvAmp values were extracted and plotted by experimental group (Figure 3B). Representative FLIM acquisition windows with normalized false color scales were produced for each group and are shown to align with collected τAvAmp values corresponding to their specific sample type (Figure 3A and 3B). As expected, in vitro lifetime samples containing the RNA A Tag (groups B and C) had significantly higher fluorescence lifetime values than those with no RNA A Tag (groups A and D). Representative decay curves for each experimental group further show that presence of the RNA A Tag increases the extracted lifetime in vitro (Figure 3C). For samples without RNA A Tag, their decay curves are shifted to the left, indicating shorter average lifetime values in comparison to samples with the RNA A Tag.
To investigate fluorescence lifetime in live cells, bead-loading of adherent HeLa cells was performed as described above with Riboglow probes 3xGly and 5xGly (Figure 4A). FLIM analysis was used to determine if the different Riboglow probes produced unique lifetime signals in live cells. Cells were selected for FLIM measurement based on the presence of loaded Riboglow probe and the overall health of the cell. Cells were selected based on confirmed probe loading and normal morphology prior to lifetime analysis, independent of fluorescence lifetime outcome. Collected FLIM data were analyzed using ROIs to limit off-target fluorescence signals (Figure 2H, Figure 4B). Results showed that the cellular fluorescence lifetimes of cells bead-loaded with 3xGly (group E) were significantly lower than those loaded with 5xGly (group F, Figure 4D). This trend can be further visualized through representative decay curves of the two sample groups, where a cell loaded with 3xGly has a left-shifted decay curve in comparison to the cell loaded with 5xGly, indicating a lower average fluorescence lifetime (Figure 4C). These results demonstrate the utility of the described protocols in extracting cellular lifetime of Riboglow probes from 2D cellular images.
We then aimed to resolve Riboglow-FLIM in subcellular compartments. As an example, we chose nuclear versus cytosolic FLIM signals. The lifetime of cell nuclei was collected and compared to cytosolic lifetime to investigate lifetime variations between cellular compartments (Figure 5). Confocal images of cells with blue nuclear stains were collected alongside FLIM images and used to determine nuclear and cytosol ROIs (Figure 2J, Figure 5C). FLIM analysis of cell nuclei and cytosols loaded with 3xGly and 5xGly revealed a significant lifetime difference between the subcellular compartments in both groups (Figure 5F). In alignment with previous observations, the nucleus of cells loaded with Riboglow probe have consistently higher fluorescence lifetimes than the cytosol of the same cell. The nuclear lifetime was, on average, 0.18 ns and 0.13 ns higher than the cytosol for 3xGly and 5xGly, respectively. Importantly, the false color scale acquisition window, decay curves, and extracted τAvAmp values all show the same fluorescence lifetime trend (Figure 5C-Figure 5F). These differences in nuclear versus cytosolic lifetimes were small but consistently detected through our robust data analysis workflow.
To demonstrate FLIM utility in increasingly complex systems, 3D cellular Z-stacks were collected and analyzed. A total of four cells were imaged in three dimensions using Z-stack slices, with the number of slices ranging from 10–15 per cell. For each cellular slice, ROIs were collected of the nucleus and cytosol, and the extracted τAvAmp values for all slices were plotted and analyzed using a paired t-test (Figure 5A and 5B, 5G). The results of all experiments showed that there was no significant difference between the lifetimes of the nucleus and cytosol in these cells. This may be due to reduced photon counts per Z-slice and limited sample size, which can reduce statistical power and lifetime resolution in 3D analysis. These data highlight the importance of sample size and photon counts in FLIM data collection, where multiple cell analyses with higher photon counts per capture reveal lifetime differences that are not visible in single-cell, lower photon experiments (Figure 5F and 5G).
Together, these results demonstrate the utility of the described protocol in collecting and analyzing FLIM data produced by the Riboglow system in several relevant biomolecular contexts.
<img alt="Fluorescence Lifetime Imaging Microscopy diagram; RNA tagging, sample loading, data fitting, analysis." class="xfigimg" src="/files/ftp_upload/71048/71048fig1v2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 1"> 
Figure 1: Overview of experimental workflow. A-B) Sample preparation workflow for in vitro (A) and mammalian cell (B) samples. C) FLIM data acquisition workflow. D) FLIM data processing workflow. Collected data are fit using n-exponential reconvolution, the number of fitting parameters are determined for each acquisition, and the final lifetime value is determined and exported. E-F) FLIM data display. In vitro data (E) is presented as false-color FLIM images or lifetime dot-plots, and cellular data (F) is presented as 2D or 3D cell FLIM images. <a href="https://www.jove.com/files/ftp_upload/71048/71048figlarge1c3.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Molecular structures; lifetime extraction; spectroscopic data analysis; fluorescence microscopy method." class="xfigimg" src="/files/ftp_upload/71048/71048fig2v2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 2"> 
Figure 2: Riboglow platform, linker series, and FLIM fitting workflow. A-B) Cartoon of Riboglow probes and RNA A Tag. C) Illustration of Riboglow probe binding to the RNA aptamer tag (A Tag), which results in increased fluorescence intensity and lifetime upon complex formation. D) Riboglow linker series for this study. Cbl (plum) is covalently coupled to a fluorophore (blue) via a variable chemical linker. 5xGly contains two additional glycine residues, as highlighted in yellow. E-J) FLIM data processing via SymPhoTime 64. E-G) FLIM data is imported into SymPhoTime 64 (E). A clean region of interest (ROI) is selected (F), and decay curves are then fitted using an n-exponential reconvolution model (G). The optimal fit is utilized to obtain the amplitude-weighted average lifetime (τAvAmp). H) 2D cellular FLIM analysis of the quenched 3xGly in U-2 OS cells, showing fitting for n = 3. I) 3D volume rendering of HeLa cells labeled with quenched 5xGly and DAPI. J) Z-stack workflow for nucleus versus cytosol FLIM analysis, demonstrating how corresponding confocal z-slices guide a precise ROI placement for compartment-specific lifetime fitting. <a href="https://www.jove.com/files/ftp_upload/71048/71048figlarge2c3.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="FLIM analysis, peptide group comparison, box plot for lifetime, decay curve, RNA interaction study." class="xfigimg" src="/files/ftp_upload/71048/71048fig3v2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 3"> 
Figure 3: Assessing fluorescence lifetimes of two probe variants in vitro +/- RNA. A) Quantitative visualization of Riboglow probes by fluorescence lifetime imaging microscopy (FLIM) in vitro in the presence or absence of the RNA A Tag. Scale bar = 50 µm. B) Plotted τ AvAmp values for 3xGly and 5xGly in vitro samples, with and without RNA A Tag. Each point represents one FLIM acquisition. Error bars represent mean and SD. One-way ANOVA with post hoc Tukey HSD reveals significant differences in lifetimes (****p &lt; 0.0001). C) Representative in vitro decay curves for 5xGly and 3xGly probes with and without RNA-A. <a href="https://www.jove.com/files/ftp_upload/71048/71048figlarge3c3.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Riboglow probe method; fluorescent microscopy results; intensity decay graph; lifetime comparison." class="xfigimg" src="/files/ftp_upload/71048/71048fig4v2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 4"> 
Figure 4: Fluorescence lifetime imaging of HeLa cells with 3xGly (Group E) and 5xGly (Group F) Riboglow probes. (A) Overview of probe loading process. (B) Cellular acquisition images of Group E (left) and F (right). Scale bar = 10 μm. (C) Fitted lifetime decay curves extracted from Groups E and F and plotted with the IRF. (D) Fluorescence lifetime for Group E (n=18 cells) and Group F (n=18 cells) in HeLa cells with mean and 95% CI error bars shown. Unpaired t-test reveals significant difference in lifetimes between cells loaded with 3xGly and 5xGly,*** p &lt; 0.0005. <a href="https://www.jove.com/files/ftp_upload/71048/71048figlarge4c3.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Time-correlated single photon counting (TCSPC) experiment; diagram, 3D model, decay graphs." class="xfigimg" src="/files/ftp_upload/71048/71048fig5v2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 5"> 
Figure 5: FLIM analysis of subcellular compartments using 3xGly (Group L) and 5xGly (Group M) Riboglow probes. (A) Schematic representation of Z-stack imaging. (B) 3D rendered image of a HeLa cells acquired through confocal Z-stack images. HeLa cells contained a blue nuclear stain (cyan) and were loaded with Riboglow probe (orange). (C) FLIM analysis of bead-loaded HeLa cells. Confocal images (left column) were used as references for ROI selection (middle, right columns). Scale bars = 10 μm. (D-E) Representative fluorescence decay curves extracted from nuclear and cytosolic ROIs of HeLa cells loaded with either (D) 3xGly, or (E) 5xGly. Curves show normalized photon counts versus decay time, and each decay is overlaid with its instrument response function (IRF, black). (F) Dot plot quantifying fluorescence lifetimes from nuclear versus cytosolic ROIs across the two experimental groups. Each point represents a single cellular ROI. One-way ANOVA with post hoc Tukey HSD reveals significant differences in lifetimes between nucleus and cytosol within both groups (****p &lt; 0.0001). (G) Dot plot of fluorescence lifetime Z-stacks of four cells. Each point represents a single ROI taken from one slice of a cellular Z-stack. Multiple ROIs derived from the same cell were treated with caution, as they are not fully independent biological replicates. All ROIs were defined using the confocal image as a reference. Paired t-tests reveal no significant differences in lifetimes between nucleus and cytosol within all cellular Z-stacks (ns p &gt; 0.05). <a href="https://www.jove.com/files/ftp_upload/71048/71048figlarge5c3.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

The goal of this protocol is to enable quantitative fluorescence lifetime measurement of Riboglow probes for reproducible RNA imaging workflows in vitro, in live mammalian cells, and in three-dimensional cellular models. We outline sample preparation, probe delivery, data acquisition, and quantitative analysis workflows for extracting unbiased fluorescence lifetime measurements.

Nearly 80% of the human genome is transcribed into RNA, while less than 2% encode for proteins, indicating that the majority of mammalian transcripts are ...

characterizing-riboglow-probes-vitro-as-basis-for-fluorescence

Research

JoVE Journal

Biochemistry

Here we demonstrate the protocols for performing single-molecule fluorescence microscopy on living bacterial cells to enable functional molecular complexes to be detected, tracked and quantified.

Visualizing Single Molecular Complexes In Vivo Using Advanced Fluorescence Microscopy

By employing a spectrally resolved two-photon microscopy imaging system, pixel-level maps of Förster Resonance Energy Transfer (FRET) efficiencies are obtained for cells expressing membrane receptors hypothesized to form homo-oligomeric complexes.  From the FRET efficiency maps, we are able to estimate stoichiometric information about the oligomer complex under study.

In vivo Quantification of G Protein Coupled Receptor Interactions using Spectrally Resolved Two-photon Microscopy

Fluorescence Lifetime Imaging (FLIM) has emerged as a key technique to image the environment and interaction of specific proteins and dyes in living cells. FLIM of fluorescent molecular rotors allows mapping of viscosity in living cells.

Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells

Time-lapse microscopy of fluorescently labeled autophagy markers allows monitoring of the dynamic autophagy response with high temporal resolution. Using specific autophagy and organelle markers in a combination of 3 different colors, we can follow the contribution of a protein to autophagosome formation in a robust spatial and temporal context.

Live Cell Imaging of Early Autophagy Events: Omegasomes and Beyond

We describe the imaging approaches we use to investigate the distribution and mobility of the transfected fluorescent proteins resident in the endoplasmic reticulum (ER) by means of the confocal imaging of living cells. We also ultrastructurally analyze the effect of their expression on the architecture of this subcellular compartment.

Visualization of Endoplasmic Reticulum Subdomains in Cultured Cells

Ratiometric bimolecular beacons (RBMBs) can be used to image single engineered RNA transcripts in living cells. Here, we describe the preparation and purification of RBMBs, delivery of RBMBs into cells by microporation and fluorescent imaging of single RNA transcripts in real-time.

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

Studies of biomolecules in vivo are crucial for understanding molecular function in a biological context. Here we describe a novel method allowing the internalization of fluorescent biomolecules, such as DNA or proteins, into living microorganisms. Analysis of in vivo data recorded by fluorescence microscopy is also presented and discussed.

Internalization and Observation of Fluorescent Biomolecules in Living Microorganisms via Electroporation

This paper describes the use of a new, fast optical imager for the macroscopic photoluminescence lifetime imaging of long decay emitting samples. The integration, image acquisition, and analysis procedures are described, along with the preparation and characterization of the sensor materials for the imaging and the application of the imager in studying biological samples.

Fluorescence Lifetime Macro Imager for Biomedical Applications

Here, we describe different multicellular spheroid formation methods to perform follow-up multi-parameter live cell microscopy. Using fluorescence lifetime imaging microscopy (FLIM), cellular autofluorescence, staining dyes, and nanoparticles, the approach for analysis of cell metabolism, hypoxia, and cell death in live three-dimensional (3D) cancer and stem cell-derived spheroids is demonstrated.

Production and Multi-Parameter Live Cell Fluorescence Lifetime Imaging Microscopy (FLIM) of Multicellular Spheroids

Here we describe protocols to disrupt mammalian cells by solid-state milling at a cryogenic temperature, produce a cell extract from the resulting cell powder, and isolate protein complexes of interest by affinity capture upon antibody-coupled micron-scale paramagnetic beads.

Protein Complex Affinity Capture from Cryomilled Mammalian Cells

751 Views.  Georgetown University. The goal of this protocol is to enable quantitative fluorescence lifetime measurement of Riboglow probes for reproducible RNA imaging workflows in vitro, in live mammalian cells, and in three-dimensional cellular models. We outline sample preparation, probe delivery, data acquisition, and quantitative analysis workflows for extracting unbiased fluorescence lifetime measurements.

Video: Characterizing Riboglow Probes In Vitro as the Basis for Fluorescence Lifetime Imaging In Live Mammalian Cells and Three-Dimensional Cellular Models

Characterizing Riboglow Probes In Vitro as the Basis for Fluorescence Lifetime Imaging In Live Mammalian Cells and Three-Dimensional Cellular Models

Explore More Videos