Cargando…
A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers
BACKGROUND: Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing t...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789701/ https://www.ncbi.nlm.nih.gov/pubmed/29378643 http://dx.doi.org/10.1186/s13059-017-1385-x |
_version_ | 1783296337234624512 |
---|---|
author | Martin-Gayo, Enrique Cole, Michael B. Kolb, Kellie E. Ouyang, Zhengyu Cronin, Jacqueline Kazer, Samuel W. Ordovas-Montanes, Jose Lichterfeld, Mathias Walker, Bruce D. Yosef, Nir Shalek, Alex K. Yu, Xu G. |
author_facet | Martin-Gayo, Enrique Cole, Michael B. Kolb, Kellie E. Ouyang, Zhengyu Cronin, Jacqueline Kazer, Samuel W. Ordovas-Montanes, Jose Lichterfeld, Mathias Walker, Bruce D. Yosef, Nir Shalek, Alex K. Yu, Xu G. |
author_sort | Martin-Gayo, Enrique |
collection | PubMed |
description | BACKGROUND: Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection. RESULTS: To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4(+) T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. CONCLUSIONS: Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-017-1385-x) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5789701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57897012018-02-08 A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers Martin-Gayo, Enrique Cole, Michael B. Kolb, Kellie E. Ouyang, Zhengyu Cronin, Jacqueline Kazer, Samuel W. Ordovas-Montanes, Jose Lichterfeld, Mathias Walker, Bruce D. Yosef, Nir Shalek, Alex K. Yu, Xu G. Genome Biol Research BACKGROUND: Human immunity relies on the coordinated responses of many cellular subsets and functional states. Inter-individual variations in cellular composition and communication could thus potentially alter host protection. Here, we explore this hypothesis by applying single-cell RNA-sequencing to examine viral responses among the dendritic cells (DCs) of three elite controllers (ECs) of HIV-1 infection. RESULTS: To overcome the potentially confounding effects of donor-to-donor variability, we present a generally applicable computational framework for identifying reproducible patterns in gene expression across donors who share a unifying classification. Applying it, we discover a highly functional antiviral DC state in ECs whose fractional abundance after in vitro exposure to HIV-1 correlates with higher CD4(+) T cell counts and lower HIV-1 viral loads, and that effectively primes polyfunctional T cell responses in vitro. By integrating information from existing genomic databases into our reproducibility-based analysis, we identify and validate select immunomodulators that increase the fractional abundance of this state in primary peripheral blood mononuclear cells from healthy individuals in vitro. CONCLUSIONS: Overall, our results demonstrate how single-cell approaches can reveal previously unappreciated, yet important, immune behaviors and empower rational frameworks for modulating systems-level immune responses that may prove therapeutically and prophylactically useful. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13059-017-1385-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-01-29 /pmc/articles/PMC5789701/ /pubmed/29378643 http://dx.doi.org/10.1186/s13059-017-1385-x Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Martin-Gayo, Enrique Cole, Michael B. Kolb, Kellie E. Ouyang, Zhengyu Cronin, Jacqueline Kazer, Samuel W. Ordovas-Montanes, Jose Lichterfeld, Mathias Walker, Bruce D. Yosef, Nir Shalek, Alex K. Yu, Xu G. A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title | A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title_full | A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title_fullStr | A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title_full_unstemmed | A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title_short | A Reproducibility-Based Computational Framework Identifies an Inducible, Enhanced Antiviral State in Dendritic Cells from HIV-1 Elite Controllers |
title_sort | reproducibility-based computational framework identifies an inducible, enhanced antiviral state in dendritic cells from hiv-1 elite controllers |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5789701/ https://www.ncbi.nlm.nih.gov/pubmed/29378643 http://dx.doi.org/10.1186/s13059-017-1385-x |
work_keys_str_mv | AT martingayoenrique areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT colemichaelb areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT kolbkelliee areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT ouyangzhengyu areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT croninjacqueline areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT kazersamuelw areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT ordovasmontanesjose areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT lichterfeldmathias areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT walkerbruced areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT yosefnir areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT shalekalexk areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT yuxug areproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT martingayoenrique reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT colemichaelb reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT kolbkelliee reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT ouyangzhengyu reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT croninjacqueline reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT kazersamuelw reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT ordovasmontanesjose reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT lichterfeldmathias reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT walkerbruced reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT yosefnir reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT shalekalexk reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers AT yuxug reproducibilitybasedcomputationalframeworkidentifiesaninducibleenhancedantiviralstateindendriticcellsfromhiv1elitecontrollers |