Gut bacteria-derived sphingolipids alter innate immune responses to oral cholera vaccine antigens - fecal lipidomics
Ontology highlight
ABSTRACT:
INSTRUMENT(S): QTRAP 5500
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Ana A. Weil
PROVIDER: MSV000099936 | MassIVE | Mon Nov 17 17:46:00 GMT 2025
REPOSITORIES: MassIVE
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Project description:Introduction: Systems vaccinology is a novel approach to predict immune response in vaccines. We have used a systems biology approach to identify early gene ‘signatures’ that predicted viral load control after analytical therapy interruption (ATI) in HIV-1 infected patients vaccinated with a dendritic cell-based (DC) HIV-1 vaccine. Methods: Frozen post-vaccination PBMC samples from participants of a previously published DC vaccine (DCV2) clinical trial were used for the study. mRNA and miRNA were extracted and gene expression was determined by microarray method. Differential gene expression analysis was performed on both mRNA and miRNA between responders (> 1 log10 copies/mL drop of VL after 12 weeks of ATI) and non-responders (<= 1 log10 copies/mL drop in VL at week 12 of ATI). Gene set enrichment analysis (GSEA) was carried out with the hallmark gene sets of the Broad Institute on the mRNA data. After the stand-alone analyses of mRNA and miRNA we performed an additional GSEA with gene sets defined by the genes regulated by significantly differentially expressed miRNAs. Statistical analysis was done using R and the GSEA software of the Broad Institute. Results: There were 15 responders and 20 non-responders. No differentially expressed mRNAs were observed between responders and non-responders. As compared with non-responders, responders showed an up-regulation of gene sets corresponding to TNF- alpha signaling via the NFkB pathway, inflammatory response, coagulation, the complement system, Il6 and Il2 JAK-STAT signaling, or reactive oxygen-species pathways were up-regulated, and a down-regulation of gene sets corresponding to E2F targets, oxidative phosphorylation, or interferon alpha response. We found 9 differentially expressed miRNAs between responders and non-responders: miR-32-3p, miR-185-3p, miR-223-3p, miR-500b-3p, miR-550a-3p, miR-1183, miR-1184, miR-4455, and miR-8063. Twelve Broad hallmark gene sets that were significantly deregulated in the GSEA showed significant overlap with genes regulated by one or more of these miRNAs, 10 of them with genes regulated by miR-223-3p. We also observed that the expression of genes regulated by miR-223-3p, miR-1183 and miR-8063 was significantly down-regulated in responders as compared with non-responders. Conclusions: Deregulation of certain gene sets related to inflammatory processes seems fundamental in viral control during ATI. miR-223-3p may be one of the miRNAs that fine tune part of these processes.
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Project description:Introduction: Systems vaccinology is a novel approach to predict immune response in vaccines. We have used a systems biology approach to identify early gene ‘signatures’ that predicted viral load control after analytical therapy interruption (ATI) in HIV-1 infected patients vaccinated with a dendritic cell-based (DC) HIV-1 vaccine. Methods: Frozen post-vaccination PBMC samples from participants of a previously published DC vaccine (DCV2) clinical trial were used for the study. mRNA and miRNA were extracted and gene expression was determined by microarray method. Differential gene expression analysis was performed on both mRNA and miRNA between responders (> 1 log10 copies/mL drop of VL after 12 weeks of ATI) and non-responders (<= 1 log10 copies/mL drop in VL at week 12 of ATI). Gene set enrichment analysis (GSEA) was carried out with the hallmark gene sets of the Broad Institute on the mRNA data. After the stand-alone analyses of mRNA and miRNA we performed an additional GSEA with gene sets defined by the genes regulated by significantly differentially expressed miRNAs. Statistical analysis was done using R and the GSEA software of the Broad Institute. Results: There were 15 responders and 20 non-responders. No differentially expressed mRNAs were observed between responders and non-responders. As compared with non-responders, responders showed an up-regulation of gene sets corresponding to TNF- alpha signaling via the NFkB pathway, inflammatory response, coagulation, the complement system, Il6 and Il2 JAK-STAT signaling, or reactive oxygen-species pathways were up-regulated, and a down-regulation of gene sets corresponding to E2F targets, oxidative phosphorylation, or interferon alpha response. We found 9 differentially expressed miRNAs between responders and non-responders: miR-32-3p, miR-185-3p, miR-223-3p, miR-500b-3p, miR-550a-3p, miR-1183, miR-1184, miR-4455, and miR-8063. Twelve Broad hallmark gene sets that were significantly deregulated in the GSEA showed significant overlap with genes regulated by one or more of these miRNAs, 10 of them with genes regulated by miR-223-3p. We also observed that the expression of genes regulated by miR-223-3p, miR-1183 and miR-8063 was significantly down-regulated in responders as compared with non-responders. Conclusions: Deregulation of certain gene sets related to inflammatory processes seems fundamental in viral control during ATI. miR-223-3p may be one of the miRNAs that fine tune part of these processes.
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