Article ; Online: Utilizing gnotobiotic models to inform the role of the microbiome in vaccine response heterogeneity.
Current opinion in HIV and AIDS
2018 Volume 13, Issue 1, Page(s) 1–8
Abstract: Purpose of review: Gnotobiotic models have the potential to provide substantial insight into how the microbiome shapes its host's response to vaccines. This review aims to summarize literature about the role of the microbiome in shaping the immune ... ...
Abstract | Purpose of review: Gnotobiotic models have the potential to provide substantial insight into how the microbiome shapes its host's response to vaccines. This review aims to summarize literature about the role of the microbiome in shaping the immune system and vaccine response heterogeneity, summarize gnotobiotic and other murine models that help us understand the immune system and vaccine response, and suggest novel ways that these models could be used to further understand vaccine response heterogeneity. Recent findings: Clinical data have suggested that numerous vaccines' effectiveness are regulated by the microbiome and often correlate with the abundance of specific taxa. Gnotobiotic and other animal models are beginning to illuminate the complex effects induced by the presence of particular microbial groups and communities. Such models have identified microbial groups that improve vaccine response to rotavirus vaccine and identified pathways by which the microbiome influences response to influenza and other vaccines. Summary: By applying a range of vaccines across gnotobiotic mouse models, researchers may be able to identify the effects of single microorganisms as well as interacting communities of microorganisms on the immune response. |
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MeSH term(s) | Animals ; Biological Variation, Population ; Germ-Free Life ; Influenza Vaccines/administration & dosage ; Influenza Vaccines/immunology ; Mice ; Microbiota/immunology ; Rotavirus Vaccines/administration & dosage ; Rotavirus Vaccines/immunology |
Chemical Substances | Influenza Vaccines ; Rotavirus Vaccines |
Language | English |
Publishing date | 2018-01 |
Publishing country | United States |
Document type | Journal Article ; Review |
ZDB-ID | 2502511-9 |
ISSN | 1746-6318 ; 1746-630X |
ISSN (online) | 1746-6318 |
ISSN | 1746-630X |
DOI | 10.1097/COH.0000000000000422 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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