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Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis

Vaccination is the most successful and cost-effective method to prevent infectious diseases. However, many vaccine antigens have poor in vivo immunogenic potential and need adjuvants to enhance immune response. The application of systems biology to immunity and vaccinology has yielded crucial insigh...

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Autores principales: Costa, Valerio, Righelli, Dario, Russo, Francesco, De Berardinis, Piergiuseppe, Angelini, Claudia, D’Apice, Luciana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372510/
https://www.ncbi.nlm.nih.gov/pubmed/28245601
http://dx.doi.org/10.3390/ijms18030494
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author Costa, Valerio
Righelli, Dario
Russo, Francesco
De Berardinis, Piergiuseppe
Angelini, Claudia
D’Apice, Luciana
author_facet Costa, Valerio
Righelli, Dario
Russo, Francesco
De Berardinis, Piergiuseppe
Angelini, Claudia
D’Apice, Luciana
author_sort Costa, Valerio
collection PubMed
description Vaccination is the most successful and cost-effective method to prevent infectious diseases. However, many vaccine antigens have poor in vivo immunogenic potential and need adjuvants to enhance immune response. The application of systems biology to immunity and vaccinology has yielded crucial insights about how vaccines and adjuvants work. We have previously characterized two safe and powerful delivery systems derived from non-pathogenic prokaryotic organisms: E2 and fd filamentous bacteriophage systems. They elicit an in vivo immune response inducing CD8+ T-cell responses, even in absence of adjuvants or stimuli for dendritic cells’ maturation. Nonetheless, a systematic and comparative analysis of the complex gene expression network underlying such activation is missing. Therefore, we compared the transcriptomes of ex vivo isolated bone marrow-derived dendritic cells exposed to these antigen delivery systems. Significant differences emerged, especially for genes involved in innate immunity, co-stimulation, and cytokine production. Results indicate that E2 drives polarization toward the Th2 phenotype, mainly mediated by Irf4, Ccl17, and Ccr4 over-expression. Conversely, fd-scαDEC-205 triggers Th1 T cells’ polarization through the induction of Il12b, Il12rb, Il6, and other molecules involved in its signal transduction. The data analysis was performed using RNASeqGUI, hence, addressing the increasing need of transparency and reproducibility of computational analysis.
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spelling pubmed-53725102017-04-10 Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis Costa, Valerio Righelli, Dario Russo, Francesco De Berardinis, Piergiuseppe Angelini, Claudia D’Apice, Luciana Int J Mol Sci Article Vaccination is the most successful and cost-effective method to prevent infectious diseases. However, many vaccine antigens have poor in vivo immunogenic potential and need adjuvants to enhance immune response. The application of systems biology to immunity and vaccinology has yielded crucial insights about how vaccines and adjuvants work. We have previously characterized two safe and powerful delivery systems derived from non-pathogenic prokaryotic organisms: E2 and fd filamentous bacteriophage systems. They elicit an in vivo immune response inducing CD8+ T-cell responses, even in absence of adjuvants or stimuli for dendritic cells’ maturation. Nonetheless, a systematic and comparative analysis of the complex gene expression network underlying such activation is missing. Therefore, we compared the transcriptomes of ex vivo isolated bone marrow-derived dendritic cells exposed to these antigen delivery systems. Significant differences emerged, especially for genes involved in innate immunity, co-stimulation, and cytokine production. Results indicate that E2 drives polarization toward the Th2 phenotype, mainly mediated by Irf4, Ccl17, and Ccr4 over-expression. Conversely, fd-scαDEC-205 triggers Th1 T cells’ polarization through the induction of Il12b, Il12rb, Il6, and other molecules involved in its signal transduction. The data analysis was performed using RNASeqGUI, hence, addressing the increasing need of transparency and reproducibility of computational analysis. MDPI 2017-02-24 /pmc/articles/PMC5372510/ /pubmed/28245601 http://dx.doi.org/10.3390/ijms18030494 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Costa, Valerio
Righelli, Dario
Russo, Francesco
De Berardinis, Piergiuseppe
Angelini, Claudia
D’Apice, Luciana
Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title_full Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title_fullStr Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title_full_unstemmed Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title_short Distinct Antigen Delivery Systems Induce Dendritic Cells’ Divergent Transcriptional Response: New Insights from a Comparative and Reproducible Computational Analysis
title_sort distinct antigen delivery systems induce dendritic cells’ divergent transcriptional response: new insights from a comparative and reproducible computational analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372510/
https://www.ncbi.nlm.nih.gov/pubmed/28245601
http://dx.doi.org/10.3390/ijms18030494
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