IDEAS home Printed from https://ideas.repec.org/a/plo/ppat00/1006678.html
   My bibliography  Save this article

Single-cell analysis identifies cellular markers of the HIV permissive cell

Author

Listed:
  • Sylvie Rato
  • Antonio Rausell
  • Miguel Muñoz
  • Amalio Telenti
  • Angela Ciuffi

Abstract

Cellular permissiveness to HIV infection is highly heterogeneous across individuals. Heterogeneity is also found across CD4+ T cells from the same individual, where only a fraction of cells gets infected. To explore the basis of permissiveness, we performed single-cell RNA-seq analysis of non-infected CD4+ T cells from high and low permissive individuals. Transcriptional heterogeneity translated in a continuum of cell states, driven by T-cell receptor-mediated cell activation and was strongly linked to permissiveness. Proteins expressed at the cell surface and displaying the highest correlation with T cell activation were tested as biomarkers of cellular permissiveness to HIV. FACS sorting using antibodies against several biomarkers of permissiveness led to an increase of HIV cellular infection rates. Top candidate biomarkers included CD25, a canonical activation marker. The combination of CD25 high expression with other candidate biomarkers led to the identification of CD298, CD63 and CD317 as the best biomarkers for permissiveness. CD25highCD298highCD63highCD317high cell population showed an enrichment of HIV-infection of up to 28 fold as compared to the unsorted cell population. The purified hyper-permissive cell subpopulation was characterized by a downregulation of interferon-induced genes and several known restriction factors. Single-cell RNA-seq analysis coupled with functional characterization of cell biomarkers provides signatures of the “HIV-permissive cell”.Author summary: CD4+ T cells are the main target of human immunodeficiency virus (HIV) infection. However, CD4+ T cells are not equally permissive to infection, varying between individuals and across cells isolated from the same individual. We explored cellular heterogeneity by analyzing the transcriptome profile of CD4+ T cells at single-cell level. Results identified T-cell receptor-mediated activation as the major determinant of CD4+ T cell heterogeneity. We identified cell surface proteins that highly correlated with T cell activation and HIV permissiveness. Activated CD4+ T cells expressing CD25, CD298, CD63 and CD317 were highly enriched for HIV permissiveness. The single-cell analysis approach used in this study allowed for the identification of the most HIV-permissive cell.

Suggested Citation

  • Sylvie Rato & Antonio Rausell & Miguel Muñoz & Amalio Telenti & Angela Ciuffi, 2017. "Single-cell analysis identifies cellular markers of the HIV permissive cell," PLOS Pathogens, Public Library of Science, vol. 13(10), pages 1-23, October.
    • Handle: RePEc:plo:ppat00:1006678
    DOI: 10.1371/journal.ppat.1006678
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1006678
    Download Restriction: no
    File URL: https://journals.plos.org/plospathogens/article/file?id=10.1371/journal.ppat.1006678&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.ppat.1006678?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stuart J. D. Neil & Trinity Zang & Paul D. Bieniasz, 2008. "Tetherin inhibits retrovirus release and is antagonized by HIV-1 Vpu," Nature, Nature, vol. 451(7177), pages 425-430, January.
    2. Amir Giladi & Ido Amit, 2017. "Immunology, one cell at a time," Nature, Nature, vol. 547(7661), pages 27-29, July.
    3. Alex K. Shalek & Rahul Satija & Joe Shuga & John J. Trombetta & Dave Gennert & Diana Lu & Peilin Chen & Rona S. Gertner & Jellert T. Gaublomme & Nir Yosef & Schraga Schwartz & Brian Fowler & Suzanne W, 2014. "Single-cell RNA-seq reveals dynamic paracrine control of cellular variation," Nature, Nature, vol. 510(7505), pages 363-369, June.
    4. Alex K. Shalek & Rahul Satija & Xian Adiconis & Rona S. Gertner & Jellert T. Gaublomme & Raktima Raychowdhury & Schraga Schwartz & Nir Yosef & Christine Malboeuf & Diana Lu & John J. Trombetta & Dave , 2013. "Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells," Nature, Nature, vol. 498(7453), pages 236-240, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yael Korem & Pablo Szekely & Yuval Hart & Hila Sheftel & Jean Hausser & Avi Mayo & Michael E Rothenberg & Tomer Kalisky & Uri Alon, 2015. "Geometry of the Gene Expression Space of Individual Cells," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-27, July.
    2. Rohith Palli & Mukta G Palshikar & Juilee Thakar, 2019. "Executable pathway analysis using ensemble discrete-state modeling for large-scale data," PLOS Computational Biology, Public Library of Science, vol. 15(9), pages 1-21, September.
    3. Nathaniel D Bachtel & Gisele Umviligihozo & Suzanne Pickering & Talia M Mota & Hua Liang & Gregory Q Del Prete & Pramita Chatterjee & Guinevere Q Lee & Rasmi Thomas & Mark A Brockman & Stuart Neil & M, 2018. "HLA-C downregulation by HIV-1 adapts to host HLA genotype," PLOS Pathogens, Public Library of Science, vol. 14(9), pages 1-25, September.
    4. Marco Del Giudice & Stefano Bo & Silvia Grigolon & Carla Bosia, 2018. "On the role of extrinsic noise in microRNA-mediated bimodal gene expression," PLOS Computational Biology, Public Library of Science, vol. 14(4), pages 1-26, April.
    5. Seungjae Lee & Yen-Chung Chen & Austin E. Gillen & J. Matthew Taliaferro & Bart Deplancke & Hongjie Li & Eric C. Lai, 2022. "Diverse cell-specific patterns of alternative polyadenylation in Drosophila," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    6. Md Tauhidul Islam & Jen-Yeu Wang & Hongyi Ren & Xiaomeng Li & Masoud Badiei Khuzani & Shengtian Sang & Lequan Yu & Liyue Shen & Wei Zhao & Lei Xing, 2022. "Leveraging data-driven self-consistency for high-fidelity gene expression recovery," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    7. Angélique Richard & Loïs Boullu & Ulysse Herbach & Arnaud Bonnafoux & Valérie Morin & Elodie Vallin & Anissa Guillemin & Nan Papili Gao & Rudiyanto Gunawan & Jérémie Cosette & Ophélie Arnaud & Jean-Ja, 2016. "Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process," PLOS Biology, Public Library of Science, vol. 14(12), pages 1-35, December.
    8. Qi Liu & Charles A Herring & Quanhu Sheng & Jie Ping & Alan J Simmons & Bob Chen & Amrita Banerjee & Wei Li & Guoqiang Gu & Robert J Coffey & Yu Shyr & Ken S Lau, 2018. "Quantitative assessment of cell population diversity in single-cell landscapes," PLOS Biology, Public Library of Science, vol. 16(10), pages 1-29, October.
    9. Kerry L. Hilligan & Sivaranjani Namasivayam & Chad S. Clancy & Paul J. Baker & Samuel I. Old & Victoria Peluf & Eduardo P. Amaral & Sandra D. Oland & Danielle O’Mard & Julie Laux & Melanie Cohen & Nic, 2023. "Bacterial-induced or passively administered interferon gamma conditions the lung for early control of SARS-CoV-2," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    10. Chieh Lin & Jun Ding & Ziv Bar-Joseph, 2020. "Inferring TF activation order in time series scRNA-Seq studies," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-19, February.
    11. Andrew McDavid & Lucas Dennis & Patrick Danaher & Greg Finak & Michael Krouse & Alice Wang & Philippa Webster & Joseph Beechem & Raphael Gottardo, 2014. "Modeling Bi-modality Improves Characterization of Cell Cycle on Gene Expression in Single Cells," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-10, July.
    12. Angeles Arzalluz-Luque & Pedro Salguero & Sonia Tarazona & Ana Conesa, 2022. "acorde unravels functionally interpretable networks of isoform co-usage from single cell data," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    13. Manikandan Narayanan & Andrew J Martins & John S Tsang, 2016. "Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-33, July.
    14. Shengfei Tang & Yanmei Shi & Qi Zhang, 2023. "Bias-Corrected Inference of High-Dimensional Generalized Linear Models," Mathematics, MDPI, vol. 11(4), pages 1-14, February.
    15. Peizhuo Wang & Xiao Wen & Han Li & Peng Lang & Shuya Li & Yipin Lei & Hantao Shu & Lin Gao & Dan Zhao & Jianyang Zeng, 2023. "Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    16. Ziye Xu & Tianyu Zhang & Hongyu Chen & Yuyi Zhu & Yuexiao Lv & Shunji Zhang & Jiaye Chen & Haide Chen & Lili Yang & Weiqin Jiang & Shengyu Ni & Fangru Lu & Zhaolun Wang & Hao Yang & Ling Dong & Feng C, 2023. "High-throughput single nucleus total RNA sequencing of formalin-fixed paraffin-embedded tissues by snRandom-seq," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    17. Irene Robles-Rebollo & Sergi Cuartero & Adria Canellas-Socias & Sarah Wells & Mohammad M. Karimi & Elisabetta Mereu & Alexandra G. Chivu & Holger Heyn & Chad Whilding & Dirk Dormann & Samuel Marguerat, 2022. "Cohesin couples transcriptional bursting probabilities of inducible enhancers and promoters," Nature Communications, Nature, vol. 13(1), pages 1-16, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:ppat00:1006678. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plospathogens (email available below). General contact details of provider: https://journals.plos.org/plospathogens .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.