HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME
Single-cell imaging has emerged as a powerful means to study viral replication dynamics and identify sites of virus–host interactions. Multivariate aspects of viral replication cycles yield challenges inherent to handling large, complex imaging datasets. Herein, we describe the design and implementa...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-04-01
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| Series: | Viruses |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4915/14/5/903 |
| _version_ | 1797494640871473152 |
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| author | Edward L. Evans Ginger M. Pocock Gabriel Einsdorf Ryan T. Behrens Ellen T. A. Dobson Marcel Wiedenmann Christian Birkhold Paul Ahlquist Kevin W. Eliceiri Nathan M. Sherer |
| author_facet | Edward L. Evans Ginger M. Pocock Gabriel Einsdorf Ryan T. Behrens Ellen T. A. Dobson Marcel Wiedenmann Christian Birkhold Paul Ahlquist Kevin W. Eliceiri Nathan M. Sherer |
| author_sort | Edward L. Evans |
| collection | DOAJ |
| description | Single-cell imaging has emerged as a powerful means to study viral replication dynamics and identify sites of virus–host interactions. Multivariate aspects of viral replication cycles yield challenges inherent to handling large, complex imaging datasets. Herein, we describe the design and implementation of an automated, imaging-based strategy, “Human Immunodeficiency Virus Red-Green-Blue” (HIV RGB), for deriving comprehensive single-cell measurements of HIV-1 unspliced (US) RNA nuclear export, translation, and bulk changes to viral RNA and protein (HIV-1 Rev and Gag) subcellular distribution over time. Differentially tagged fluorescent viral RNA and protein species are recorded using multicolor long-term (>24 h) time-lapse video microscopy, followed by image processing using a new open-source computational imaging workflow dubbed “Nuclear Ring Segmentation Analysis and Tracking” (NR-SAT) based on ImageJ plugins that have been integrated into the Konstanz Information Miner (KNIME) analytics platform. We describe a typical HIV RGB experimental setup, detail the image acquisition and NR-SAT workflow accompanied by a step-by-step tutorial, and demonstrate a use case wherein we test the effects of perturbing subcellular localization of the Rev protein, which is essential for viral US RNA nuclear export, on the kinetics of HIV-1 late-stage gene regulation. Collectively, HIV RGB represents a powerful platform for single-cell studies of HIV-1 post-transcriptional RNA regulation. Moreover, we discuss how similar NR-SAT-based design principles and open-source tools might be readily adapted to study a broad range of dynamic viral or cellular processes. |
| first_indexed | 2024-03-10T01:37:15Z |
| format | Article |
| id | doaj.art-39386aafa62e4211a1d9f4e662eefe2e |
| institution | Directory Open Access Journal |
| issn | 1999-4915 |
| language | English |
| last_indexed | 2024-03-10T01:37:15Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Viruses |
| spelling | doaj.art-39386aafa62e4211a1d9f4e662eefe2e2023-11-23T13:29:59ZengMDPI AGViruses1999-49152022-04-0114590310.3390/v14050903HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIMEEdward L. Evans0Ginger M. Pocock1Gabriel Einsdorf2Ryan T. Behrens3Ellen T. A. Dobson4Marcel Wiedenmann5Christian Birkhold6Paul Ahlquist7Kevin W. Eliceiri8Nathan M. Sherer9McArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USAMcArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USALaboratory for Optical and Computational Instrumentation, Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI 53706, USAMcArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USALaboratory for Optical and Computational Instrumentation, Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI 53706, USALaboratory for Optical and Computational Instrumentation, Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI 53706, USAKNIME GmbH, 78467 Konstanz, GermanyMcArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USALaboratory for Optical and Computational Instrumentation, Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI 53706, USAMcArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USASingle-cell imaging has emerged as a powerful means to study viral replication dynamics and identify sites of virus–host interactions. Multivariate aspects of viral replication cycles yield challenges inherent to handling large, complex imaging datasets. Herein, we describe the design and implementation of an automated, imaging-based strategy, “Human Immunodeficiency Virus Red-Green-Blue” (HIV RGB), for deriving comprehensive single-cell measurements of HIV-1 unspliced (US) RNA nuclear export, translation, and bulk changes to viral RNA and protein (HIV-1 Rev and Gag) subcellular distribution over time. Differentially tagged fluorescent viral RNA and protein species are recorded using multicolor long-term (>24 h) time-lapse video microscopy, followed by image processing using a new open-source computational imaging workflow dubbed “Nuclear Ring Segmentation Analysis and Tracking” (NR-SAT) based on ImageJ plugins that have been integrated into the Konstanz Information Miner (KNIME) analytics platform. We describe a typical HIV RGB experimental setup, detail the image acquisition and NR-SAT workflow accompanied by a step-by-step tutorial, and demonstrate a use case wherein we test the effects of perturbing subcellular localization of the Rev protein, which is essential for viral US RNA nuclear export, on the kinetics of HIV-1 late-stage gene regulation. Collectively, HIV RGB represents a powerful platform for single-cell studies of HIV-1 post-transcriptional RNA regulation. Moreover, we discuss how similar NR-SAT-based design principles and open-source tools might be readily adapted to study a broad range of dynamic viral or cellular processes.https://www.mdpi.com/1999-4915/14/5/903human immunodeficiency virus type 1retrovirusRevRev response elementGagunspliced RNA |
| spellingShingle | Edward L. Evans Ginger M. Pocock Gabriel Einsdorf Ryan T. Behrens Ellen T. A. Dobson Marcel Wiedenmann Christian Birkhold Paul Ahlquist Kevin W. Eliceiri Nathan M. Sherer HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME Viruses human immunodeficiency virus type 1 retrovirus Rev Rev response element Gag unspliced RNA |
| title | HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME |
| title_full | HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME |
| title_fullStr | HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME |
| title_full_unstemmed | HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME |
| title_short | HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME |
| title_sort | hiv rgb automated single cell analysis of hiv 1 rev dependent rna nuclear export and translation using image processing in knime |
| topic | human immunodeficiency virus type 1 retrovirus Rev Rev response element Gag unspliced RNA |
| url | https://www.mdpi.com/1999-4915/14/5/903 |
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