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Guo Y, Kowalczyk GJ, Lee REC. Label and quantify mRNA molecules in live cell experiments using SunRISER and dNEMO. STAR Protoc 2022; 3:101630. [PMID: 36035802 PMCID: PMC9405536 DOI: 10.1016/j.xpro.2022.101630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Visualization of mRNA molecules in single cells has revealed their core mechanisms as well as sources of cell-to-cell and spatiotemporal heterogeneity. Here, we describe a protocol to label, visualize, and quantify mRNA molecules by time-lapse imaging with the capability of resolving mRNA molecules over durations of hours to days. We provide links to mRNA-labeling plasmids as well as free software for a semi-automated image analysis pipeline. For complete details on the use and execution of this protocol, please refer to Guo and Lee (2022) and Kowalczyk et al. (2021). SunRISER is a toolbox optimized for single mRNA live-cell imaging experiments Rapid detection of labeled single mRNA molecules in fluorescence microscopy images Automated single-cell segmentation and mRNA quantification
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
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Affiliation(s)
- Yue Guo
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA.
| | - Gabriel J Kowalczyk
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Robin E C Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA; Center for Systems Immunology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15260, USA.
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Guo Y, Lee RE. Long-term imaging of individual mRNA molecules in living cells. CELL REPORTS METHODS 2022; 2:100226. [PMID: 35784652 PMCID: PMC9243547 DOI: 10.1016/j.crmeth.2022.100226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 03/10/2022] [Accepted: 05/04/2022] [Indexed: 12/04/2022]
Abstract
Single-cell imaging of individual mRNAs has revealed core mechanisms of the central dogma. However, most approaches require cell fixation or have limited sensitivity for live-cell applications. Here, we describe SunRISER (SunTag-based reporter for imaging signal-enriched mRNA), a computationally and experimentally optimized approach for unambiguous detection of single mRNA molecules in living cells. When viewed by epifluorescence microscopy, SunRISER-labeled mRNAs show strong signal to background and resistance to photobleaching, which together enable long-term mRNA imaging studies. SunRISER variants, using 8× and 10× stem-loop arrays, demonstrate effective mRNA detection while significantly reducing alterations to target mRNA sequences. We characterize SunRISER to observe mRNA inheritance during mitosis and find that stressors enhance diversity among post-mitotic sister cells. Taken together, SunRISER enables a glimpse into living cells to observe aspects of the central dogma and the role of mRNAs in rare and dynamical trafficking events.
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Affiliation(s)
- Yue Guo
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Robin E.C. Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Center for Systems Immunology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
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Cruz JA, Mokashi CS, Kowalczyk GJ, Guo Y, Zhang Q, Gupta S, Schipper DL, Smeal SW, Lee REC. A variable-gain stochastic pooling motif mediates information transfer from receptor assemblies into NF-κB. SCIENCE ADVANCES 2021; 7:7/30/eabi9410. [PMID: 34301608 PMCID: PMC8302133 DOI: 10.1126/sciadv.abi9410] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/04/2021] [Indexed: 06/13/2023]
Abstract
A myriad of inflammatory cytokines regulate signaling pathways to maintain cellular homeostasis. The IκB kinase (IKK) complex is an integration hub for cytokines that govern nuclear factor κB (NF-κB) signaling. In response to inflammation, IKK is activated through recruitment to receptor-associated protein assemblies. How and what information IKK complexes transmit about the milieu are open questions. Here, we track dynamics of IKK complexes and nuclear NF-κB to identify upstream signaling features that determine same-cell responses. Experiments and modeling of single complexes reveal their size, number, and timing relays cytokine-specific control over shared signaling mechanisms with feedback regulation that is independent of transcription. Our results provide evidence for variable-gain stochastic pooling, a noise-reducing motif that enables cytokine-specific regulation and parsimonious information transfer. We propose that emergent properties of stochastic pooling are general principles of receptor signaling that have evolved for constructive information transmission in noisy molecular environments.
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Affiliation(s)
- J Agustin Cruz
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Chaitanya S Mokashi
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Gabriel J Kowalczyk
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Yue Guo
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Qiuhong Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Sanjana Gupta
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - David L Schipper
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Steven W Smeal
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Robin E C Lee
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
- Center for Systems Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
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