Molecular and cellular dynamics in the skin, the lymph nodes and the blood of the immune response to intradermal injection of Modified Vaccinia Ankara vaccine
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ABSTRACT:
ORGANISM(S): Macaca fascicularis
SUBMITTER: Frédéric Martinon
PROVIDER: E-MTAB-5907 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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2020-04-10 | E-MTAB-8973 | biostudies-arrayexpress
Project description:HIV-1 sexual transmission occurs mainly via mucosal semen exposures. In the female reproductive tract (FRT), seminal plasma (SP) induces physiological modifications, including inflammation. An effective HIV-1 vaccine should elicit mucosal immunity. However, modifications of vaccine responses by the local environment remain to be characterized. Using a modified vaccinia virus Ankara (MVA) as a vaccine model, we characterized the impact of HIV-1+ SP intravaginal exposure on the local immune responses of nonhuman primates. Multiple HIV-1+ SP exposures did not impact the anti-MVA antibody responses. However, SP exposures revealed an anti-MVA responses mediated by CD4+ T cells, which was not observed in the control group. Multi-parameter approaches clearly identified the cervix as the most impacted compartment in the FRT. The frequency and the quality of specific anti-MVA CD8+ T cell responses increased in the FRT exposed to SP. Furthermore SP exposures induced a local cell recruitment of antigen presenting cells, especially CD11c+ cells and CD8+ T cell recruitment in the FRT draining lymph nodes. CD11c+ cell recruitment was associated with upregulation of inflammation-related gene expression after SP exposures in the cervix. We thus highlight the fact that physiological conditions, such as SP exposures, should be taken into consideration to test and to improve vaccine efficacy against HIV-1 and other sexually transmitted infections.
2019-02-12 | E-MTAB-7639 | biostudies-arrayexpress
Project description:The female reproductive tract is one of the major mucosal invasion site of HIV-1. This site has been neglected in previous HIV-1 vaccine studies. Immune responses in the female reproductive tract after systemic vaccination remain to be characterized. Using a modified vaccinia virus Ankara (MVA) as a vaccine model, we characterized specific immune responses in all compartments of the female reproductive tract (FRT) of non-human primates after systemic vaccination. Memory T cells were preferentially found in the lower tract (vagina and cervix), whereas antigen-presenting cells and innate lymphoid cells were mainly located in the upper tract (uterus and fallopian tubes). This compartmentalisation of immune cells in the FRT was supported by transcriptomic analyses and correlation network. Polyfunctional MVA-specific CD8+ T cells were detected in the blood, lymph nodes, vagina, cervix, uterus and fallopian tubes. Anti-MVA IgG and IgA were detected in cervicovaginal fluid after a second vaccine dose. Systemic vaccination with an MVA vector thus elicits cellular and antibody responses in the female reproductive tract.
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2013-03-01 | E-GEOD-37312 | biostudies-arrayexpress
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2012-02-15 | E-GEOD-35816 | biostudies-arrayexpress
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2013-11-04 | E-GEOD-33687 | biostudies-arrayexpress
Project description:Using whole-blood transcriptional profiling, we investigated differences in the host response to vaccination and challenge in a rhesus macaque AIDS vaccine trial. Samples were collected from animals prior to and after vaccination with live irradiated vaccine cells secreting the modified endoplasmic reticulum chaperone gp96-Ig loaded with SIV peptides, either alone or in combination with a SIV-gp120 protein boost. Additional samples were collected following multiple low-dose rectal challenge with SIVmac251. Animals in the boosted group had a 73% reduced risk of infection. Surprisingly, few changes in gene expression were observed during the vaccination phase. Focusing on post-challenge comparisons, in particular for protected animals, we identified a host response signature of protection comprised of strong interferon signaling after the first challenge, which then largely abated after further challenges. We also identified a host response signature, comprised of early macrophage-mediated inflammatory responses, in animals with undetectable viral load five days after the first challenge, but which had unusually high viral titers after subsequent challenges. Statistical analysis showed that prime-boost vaccination significantly lowered the probability of infection in a time-consistent manner throughout several challenges. Given that humoral responses in the prime-boost group were highly significant pre-challenge correlates of protection, the strong innate signaling after the first challenge suggests that interferon signaling enhances vaccine-induced antibody responses and is an important contributor to protection from infection during repeated low-dose exposure to SIV. 36 Indian-origin outbred, young adult, male and female rhesus macaques divided into thre vaccination groups of 12 animals each. Groups were balanced for Mamu-A*01 (three in each group), Mamu-B*08 (one in each group), and for susceptible and resistant TRIM5α alleles. There were no Mamu-B*17+ animals. The prime group (PG) received Gp96 SIV Ig vaccine 292 cells that were transfected with plasmids encoding gp96-Ig, SIVmac251 rev-tat-nef, Gag and gp160 (35). They were injected intraperitoneally with 107 irradiated gp96SIVIg vaccine cells in HBSS, which secrete 10 μg of gp96SIVIg per 24 h. For the prime-boost group (PBG), 100 g of rSIVgp120 protein was added to the vaccine cells. The control group received 292-gp96 Ig cells not transfected with SIV antigens. After a 32-week vaccination phase, which consisted of priming in weeks 0, 6, and 25 and (for the PBG only) additional boosts in weeks 6 and 25, all animals were subject to up to seven weekly low-dose intrarectal challenges starting at 33-week with SIVmac251 at a dosage of 120 TCID50. Whenever an animal had detectable viral load (>50 copies/ml of plasma) at 5 days post challenge, it was considered viremic, further challenges were suspended, and only viral load screening continued on a weekly basis. Whole blood samples (preserved in PAXgene tubes) were collected 2 weeks prior to the first prime, 1 week after the first prime, 2 weeks before and 1 week after the third prime, 1 week before the first challenge, for newly infected animals five days into the corresponding study week and from viremic animals four days into the study week (also denoted as challenge 2 and challenge 3). Total RNA was isolated from Paxgene tubes using Paxgene Blood RNeasy Mini Kits (Qiagen) following the manufacturer’s protocol. RNA quality was assessed on an Agilent 2100 Bioanalyzer using the nanochip format, and only intact RNA was used for microarray analyses.
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Project description:Expression profiling by NanoString nCounter gene expression system Inflammatory response genes play an important role during acute HIV and SIV infection. Using an SIV macaque model for AIDS and CNS disease, we measured mRNA expression of 92 genes before and at multiple time points during acute SIV infection in three tissues: Peripheral blood mononuclear cells, mesenteric lymph nodes (MLN) and peripheral blood mononuclear cells (PBMC). Studying the overall changes of mRNA expressions over time or analyzing the correlation between the gene measurements and SIV RNA in plasma can result in limited interpretations. This is due to several reasons including but not limited to: 1) lack of prior information on how cells react to changes in gene expressions; and 2) biological responses typically involve many genes working together. To approach this problem, we combine multiple preprocessing methods with two multivariate analysis methods, namely principal component analysis and partial least square regression, to create a multiplexed set of 12 “judges”. Each of the judges simultaneously observes all the variables and emphasizes a unique type of gene expression response that could be significant, for example, depending on whether the cell responds to the absolute or relative size of gene expression changes. By incorporating multiple potential biological models of response, it is possible to identify genes that are consistently ranked as high “contributing” genes in different scenarios, i.e., genes that have a higher weight when we classify the data based on different classification schemes. We then use statistical analysis to verify that the consistently high-ranking genes are also statistically significant. We also investigate whether genes are tissue-specific, identify clusters of genes that co-vary together and study their correlation with regard to other gene clusters. The multiplex component analysis method introduced in this paper is a powerful tool to analyze complex gene datasets, identify significant genes, and generate testable hypotheses. In this study we inoculated 20 pig-tailed macaques with two SIV strains (SIV/17E-Fr and the swarm SIV/DeltaB670), and mock-inoculated 4 animals for control. Infected animals were sacrificed at 4 time points, as following: 6 animals sacrificed at 4 days, 6 at 7 days, 6 at 14 days and 2 at 21 days post-infection. Animals were perfused before necropsy to decrease blood contamination in the tissues. Organs were then culled, and RNA was extraction for NanosString analysis using a set of 92 probes specifically generated for macaque genes. Data were then analyzed by multiple preprocessing methods with two multivariate analysis methods. The following files contains raw data for the listed samples, respectively; GAMA Nanostring RAW MLN.xlsx - all MLN samples GAMA Nanostring RAW PBMC.xlsx - all PBMC samples GAMA Nanostring RAW Spleen 1.xls - PT01-04SP, PT71-74SP, PT141-144SP GAMA Nanostring RAW Spleen 2.xls - PT41-44SP, PT75-76SP, PT145-146SP, PT211-212SP GAMA Nanostring RAW Spleen 3.xls - PT45-46SP Please note that, in the associated publication, we describe a multiplexed component analysis to identify genes that highly contribute to inflammation during SIV acute infection. This analysis was done by compiling results generated by different types of data transformations and data normalizations (more than 12 for each tissue) and the relevant algorithms/mathematical processes will be discussed in detail. Therefore, only raw data is presented in this record (i.e. each sample data table contains raw data).
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