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Lin L, Frelinger J, Jiang W, Finak G, Seshadri C, Bart PA, Pantaleo G, McElrath J, DeRosa S, Gottardo R. Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data. Cytometry A 2015; 87:675-82. [PMID: 25908275 PMCID: PMC4482785 DOI: 10.1002/cyto.a.22623] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Revised: 10/24/2014] [Accepted: 12/10/2014] [Indexed: 11/08/2022]
Abstract
An important aspect of immune monitoring for vaccine development, clinical trials, and research is the detection, measurement, and comparison of antigen-specific T-cells from subject samples under different conditions. Antigen-specific T-cells compose a very small fraction of total T-cells. Developments in cytometry technology over the past five years have enabled the measurement of single-cells in a multivariate and high-throughput manner. This growth in both dimensionality and quantity of data continues to pose a challenge for effective identification and visualization of rare cell subsets, such as antigen-specific T-cells. Dimension reduction and feature extraction play pivotal role in both identifying and visualizing cell populations of interest in large, multi-dimensional cytometry datasets. However, the automated identification and visualization of rare, high-dimensional cell subsets remains challenging. Here we demonstrate how a systematic and integrated approach combining targeted feature extraction with dimension reduction can be used to identify and visualize biological differences in rare, antigen-specific cell populations. By using OpenCyto to perform semi-automated gating and features extraction of flow cytometry data, followed by dimensionality reduction with t-SNE we are able to identify polyfunctional subpopulations of antigen-specific T-cells and visualize treatment-specific differences between them.
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Affiliation(s)
- Lin Lin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jacob Frelinger
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Wenxin Jiang
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Greg Finak
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Chetan Seshadri
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington
| | | | | | - Julie McElrath
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Steve DeRosa
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Raphael Gottardo
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
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Lin L, Finak G, Ushey K, Seshadri C, Hawn TR, Frahm N, Scriba TJ, Mahomed H, Hanekom W, Bart PA, Pantaleo G, Tomaras GD, Rerks-Ngarm S, Kaewkungwal J, Nitayaphan S, Pitisuttithum P, Michael NL, Kim JH, Robb ML, O'Connell RJ, Karasavvas N, Gilbert P, C De Rosa S, McElrath MJ, Gottardo R. COMPASS identifies T-cell subsets correlated with clinical outcomes. Nat Biotechnol 2015; 33:610-6. [PMID: 26006008 PMCID: PMC4569006 DOI: 10.1038/nbt.3187] [Citation(s) in RCA: 209] [Impact Index Per Article: 23.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Accepted: 03/04/2015] [Indexed: 11/09/2022]
Abstract
Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software.
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Affiliation(s)
- Lin Lin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Greg Finak
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Kevin Ushey
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Chetan Seshadri
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA
| | - Thomas R Hawn
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA
| | - Nicole Frahm
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Thomas J Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and School of Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Hassan Mahomed
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and School of Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - Willem Hanekom
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and School of Child and Adolescent Health, University of Cape Town, Cape Town, South Africa
| | | | | | - Georgia D Tomaras
- Duke Human Vaccine Institute, Duke University Medical Center, Durham, North Carolina, USA
| | | | - Jaranit Kaewkungwal
- Data Management Unit, Faculty of Tropical Medicine, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Sorachai Nitayaphan
- Thai Component, Armed Forces Research Institute of Medical Sciences, Bangkok, Ratchathewi, Bangkok, Thailand
| | - Punnee Pitisuttithum
- Vaccine Trials Center, Faculty of Tropical Medicine, Mahidol University, Ratchathewi, Bangkok, Thailand
| | - Nelson L Michael
- US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | - Jerome H Kim
- US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, Maryland, USA
| | - Merlin L Robb
- US Army Military HIV Research Program, Walter Reed Army Institute of Research; Henry M. Jackson Foundation, Bethesda, Maryland, USA
| | - Robert J O'Connell
- US Army Medical Component, Armed Forces Research Institute of Medical Sciences, Ratchathewi, Bangkok, Thailand
| | - Nicos Karasavvas
- US Army Medical Component, Armed Forces Research Institute of Medical Sciences, Ratchathewi, Bangkok, Thailand
| | - Peter Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Stephen C De Rosa
- 1] Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. [2] Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA
| | - M Juliana McElrath
- 1] Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. [2] Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, USA. [3] Department of Laboratory Medicine, University of Washington, Seattle, Washington, USA
| | - Raphael Gottardo
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
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