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Abstract Filoviruses, including Ebola, Marburg, Sudan, and Taï Forest viruses, are zoonotic pathogens that can cause severe viral hemorrhagic fever and death. Developing vaccines that provide durable, broad immunity against multiple filoviruses is a high global health priority. In this Phase 1 trial, we enrolled 60 healthy U.S. adults and evaluated the safety, reactogenicity and immunogenicity of homologous and heterologous MVA-BN®-Filo and Ad26.ZEBOV prime-boost schedules followed in select arms by MVA-BN®-Filo boost at 1 year (NCT02891980). We found that all vaccine regimens had acceptable safety and reactogenicity. The heterologous prime-boost strategy elicited superior Ebola binding and neutralizing antibody, antibody-dependent cellular cytotoxicity (ADCC), and cellular responses compared to homologous prime-boost. The MVA-BN®-Filo boost administered at 1 year resulted in robust humoral and cellular responses that persisted through 6-month follow-up. Overall, our data demonstrated that a heterologous Ad26.ZEBOV/MVA-BN®-Filo prime-boost was safe and immunogenic and established immunologic memory primed to respond after re-exposure. Clinicaltrials.gov, NCT02891980, registered September 1, 2016.

Abstract Tuberculosis remains an international health threat partly because of limited protection from pulmonary tuberculosis provided by standard intradermal vaccination with Bacillus of Calmette and Guérin (BCG); this may reflect the inability of intradermal vaccination to optimally induce pulmonary immunity. In contrast, respiratory Mycobacterium tuberculosis infection usually results in the immune-mediated bacillary containment of latent tuberculosis infection (LTBI). Here we present RNA-Seq-based assessments of systemic and pulmonary immune cells from LTBI participants and recipients of intradermal and oral BCG. LTBI individuals uniquely display ongoing immune activation and robust CD4 T cell recall responses in blood and lung. Intradermal BCG is associated with robust systemic immunity but only limited pulmonary immunity. Conversely, oral BCG induces limited systemic immunity but distinct pulmonary responses including enhanced inflammasome activation potentially associated with mucosal-associated invariant T cells. Further, IL-9 is identified as a component of systemic immunity in LTBI and intradermal BCG, and pulmonary immunity following oral BCG.

Abstract Current seasonal and pre-pandemic influenza vaccines induce short-lived predominantly strain-specific and limited heterosubtypic responses. To better understand how vaccine adjuvants AS03 and MF59 may provide improved antibody responses to vaccination, we interrogated serum from subjects who received 2 doses of inactivated monovalent influenza A/Indonesia/05/2005 vaccine with or without AS03 or MF59 using hemagglutinin (HA) microarrays (NCT01317758 and NCT01317745). The arrays were designed to reflect both full-length and globular head HA derived from 17 influenza A subtypes (H1 to H16 and H18) and influenza B strains. We observed significantly increased strain-specific and broad homo- and heterosubtypic antibody responses with both AS03 and MF59 adjuvanted vaccination with AS03 achieving a higher titer and breadth of IgG responses relative to MF59. The adjuvanted vaccine was also associated with the elicitation of stalk-directed antibody. We established good correlation of the array antibody responses to H5 antigens with standard HA inhibition and microneutralization titers.

IntroductionOver the last decade, the field of systems vaccinology has emerged, in which high throughput transcriptomics and other omics assays are used to probe changes of the innate and adaptive immune system in response to vaccination. The goal of this study was to benchmark key technical and analytical parameters of RNA sequencing (RNA-seq) in the context of a multi-site, double-blind randomized vaccine clinical trial.MethodsWe collected longitudinal peripheral blood mononuclear cell (PBMC) samples from 10 subjects before and after vaccination with a live attenuated Francisella tularensis vaccine and performed RNA-Seq at two different sites using aliquots from the same sample to generate two replicate datasets (5 time points for 50 samples each). We evaluated the impact of (i) filtering lowly-expressed genes, (ii) using external RNA controls, (iii) fold change and false discovery rate (FDR) filtering, (iv) read length, and (v) sequencing depth on differential expressed genes (DEGs) concordance between replicate datasets. Using synthetic mRNA spike-ins, we developed a method for empirically establishing minimal read-count thresholds for maintaining fold change accuracy on a per-experiment basis. We defined a reference PBMC transcriptome by pooling sequence data and established the impact of sequencing depth and gene filtering on transcriptome representation. Lastly, we modeled statistical power to detect DEGs for a range of sample sizes, effect sizes, and sequencing depths.Results and DiscussionOur results showed that (i) filtering lowly-expressed genes is recommended to improve fold-change accuracy and inter-site agreement, if possible guided by mRNA spike-ins (ii) read length did not have a major impact on DEG detection, (iii) applying fold-change cutoffs for DEG detection reduced inter-set agreement and should be used with caution, if at all, (iv) reduction in sequencing depth had a minimal impact on statistical power but reduced the identifiable fraction of the PBMC transcriptome, (v) after sample size, effect size (i.e. the magnitude of fold change) was the most important driver of statistical power to detect DEG. The results from this study provide RNA sequencing benchmarks and guidelines for planning future similar vaccine studies.

Ribosomal profiling is an emerging experimental technology to measure protein synthesis by sequencing short mRNA fragments undergoing translation in ribosomes. Applied on the genome wide scale, this is a powerful tool to profile global protein synthesis within cell populations of interest. Such information can be utilized for biomarker discovery and detection of treatment-responsive genes. However, analysis of ribosomal profiling data requires careful preprocessing to reduce the impact of artifacts and dedicated statistical methods for visualizing and modeling the high-dimensional discrete read count data. Here we present Ribosomal Profiling Reports (RP-REP), a new open-source cloud-enabled software that allows users to execute start-to-end gene-level ribosomal profiling and RNA-Seq analysis on a pre-configured Amazon Virtual Machine Image (AMI) hosted on AWS or on the user’s own Ubuntu Linux server. The software works with FASTQ files stored locally, on AWS S3, or at the Sequence Read Archive (SRA). RP-REP automatically executes a series of customizable steps including filtering of contaminant RNA, enrichment of true ribosomal footprints, reference alignment and gene translation quantification, gene body coverage, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially translated genes, and generation of heatmaps, co-translated gene clusters, enriched pathways, and other custom visualizations. RP-REP provides functionality to contrast RNA-SEQ and ribosomal profiling results, and calculates translational efficiency per gene. The software outputs a PDF report and publication-ready table and figure files. As a use case, we provide RP-REP results for a dengue virus study that tested cytosol and endoplasmic reticulum cellular fractions of human Huh7 cells pre-infection and at 6 h, 12 h, 24 h, and 40 h post-infection. Case study results, Ubuntu installation scripts, and the most recent RP-REP source code are accessible at GitHub. The cloud-ready AMI is available at AWS (AMI ID: RPREP RSEQREP (Ribosome Profiling and RNA-Seq Reports) v2.1 (ami-00b92f52d763145d3)).

The immune response to live-attenuated Francisella tularensis vaccine and its host evasion mechanisms are incompletely understood. Using RNA-Seq and LC–MS on samples collected pre-vaccination and at days 1, 2, 7, and 14 post-vaccination, we identified differentially expressed genes in PBMCs, metabolites in serum, enriched pathways, and metabolites that correlated with T cell and B cell responses, or gene expression modules. While an early activation of interferon α/β signaling was observed, several innate immune signaling pathways including TLR, TNF, NF-κB, and NOD-like receptor signaling and key inflammatory cytokines such as Il-1α, Il-1β, and TNF typically activated following infection were suppressed. The NF-κB pathway was the most impacted and the likely route of attack. Plasma cells, immunoglobulin, and B cell signatures were evident by day 7. MHC I antigen presentation was more actively up-regulated first followed by MHC II which coincided with the emergence of humoral immune signatures. Metabolomics analysis showed that glycolysis and TCA cycle-related metabolites were perturbed including a decline in pyruvate. Correlation networks that provide hypotheses on the interplay between changes in innate immune, T cell, and B cell gene expression signatures and metabolites are provided. Results demonstrate the utility of transcriptomics and metabolomics for better understanding molecular mechanisms of vaccine response and potential host–pathogen interactions.

Francisella tularensis (F. tularensis) is an intracellular pathogen that causes a potentially debilitating febrile illness known as tularemia. F. tularensis can be spread by aerosol transmission and cause fatal pneumonic tularemia. If untreated, mortality rates can be as high as 30%. To study the host responses to a live-attenuated tularemia vaccine, peripheral blood mononuclear cell (PBMC) samples were assayed from 10 subjects collected pre- and post-vaccination, using both the 2D-DIGE/MALDI-MS/MS and LC-MS/MS approaches. Protein expression related to antigen processing and presentation, inflammation (PPARγ nuclear receptor), phagocytosis, and gram-negative bacterial infection was enriched at Day 7 and/or Day 14. Protein candidates that could be used to predict human immune responses were identified by evaluating the correlation between proteome changes and humoral and cellular immune responses. Consistent with the proteomics data, parallel transcriptomics data showed that MHC class I and class II-related signals important for protein processing and antigen presentation were up-regulated, further confirming the proteomic results. These findings provide new biological insights that can be built upon in future clinical studies, using live attenuated strains as immunogens, including their potential use as surrogates of protection.

Tularemia is a highly infectious and contagious disease caused by the bacterium Francisella tularensis. To better understand human response to a live-attenuated tularemia vaccine and the biological pathways altered post-vaccination, healthy adults were vaccinated, and plasma was collected pre- and post-vaccination for longitudinal lipidomics studies. Using tandem mass spectrometry, we fully characterized individual lipid species within predominant lipid classes to identify changes in the plasma lipidome during the vaccine response. Separately, we targeted oxylipins, a subset of lipid mediators involved in inflammatory pathways. We identified 14 differentially abundant lipid species from eight lipid classes. These included 5-hydroxyeicosatetraenoic acid (5-HETE) which is indicative of lipoxygenase activity and, subsequently, inflammation. Results suggest that 5-HETE was metabolized to a dihydroxyeicosatrienoic acid (DHET) by day 7 post-vaccination, shedding light on the kinetics of the 5-HETE-mediated inflammatory response. In addition to 5-HETE and DHET, we observed pronounced changes in 34:1 phosphatidylinositol, anandamide, oleamide, ceramides, 16:1 cholesteryl ester, and other glycerophospholipids; several of these changes in abundance were correlated with serum cytokines and T cell activation. These data provide new insights into alterations in plasma lipidome post-tularemia vaccination, potentially identifying key mediators and pathways involved in vaccine response and efficacy.

Background: Vaccinia is known to induce antibody and cellular responses. Plasmablast, circulating follicular helper T (cTFH) cells, cytokine-expressing CD4 T cells, and memory B cells were compared between subcutaneous (SC) and needle-free jet injection (JI) recipients of non-replicating modified vaccinia Ankara (MVA) vaccine. Methods: Vaccinia-naïve adults received MVA SC or by JI on Days 1 and 29. Vaccinia-specific antibodies were quantified by plaque reduction neutralization test (PRNT) and enzyme-linked immunosorbent assay. Plasmablast, cTFH, and cytokine-expressing CD4 T cells were assessed on Days 1, 8, 15, 29, 36, 43 (cTFH and CD4+ only) and 57. Memory B cells were measured on Days 1 and 57. Results: Of the 36 enrolled subjects, only 22 received both vaccinations and had evaluable specimens after the second vaccine. Plasmablasts peaked one week after each vaccine. Day 15 plasmablasts correlated with peak PRNT titers. cTFH peaked on Days 8 and 36 and correlated with Day 36 plasmablasts. CD4+ peaked at Day 29 and one-third produced ≥2 cytokines. Day 57 memory B cells ranged from 0.1% to 0.17% of IgG-secreting B cells. Conclusions: This study provides insights into the cellular responses to non-replicating MVA, currently used as a vector for a variety of novel vaccines.

RNA-Seq is increasingly being used to measure human RNA expression on a genome-wide scale. Expression profiles can be interrogated to identify and functionally characterize treatment-responsive genes. Ultimately, such controlled studies promise to reveal insights into molecular mechanisms of treatment effects, identify biomarkers, and realize personalized medicine. RNA-Seq Reports (RSEQREP) is a new open-source cloud-enabled framework that allows users to execute start-to-end gene-level RNA-Seq analysis on a preconfigured RSEQREP Amazon Virtual Machine Image (AMI) hosted by AWS or on their own Ubuntu Linux machine via a Docker container or installation script. The framework works with unstranded, stranded, and paired-end sequence FASTQ files stored locally, on Amazon Simple Storage Service (S3), or at the Sequence Read Archive (SRA). RSEQREP automatically executes a series of customizable steps including reference alignment, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially expressed genes, heatmaps, co-expressed gene clusters, enriched pathways, and a series of custom visualizations. The framework outputs a file collection that includes a dynamically generated PDF report using R, knitr, and LaTeX, as well as publication-ready table and figure files. A user-friendly configuration file handles sample metadata entry, processing, analysis, and reporting options. The configuration supports time series RNA-Seq experimental designs with at least one pre- and one post-treatment sample for each subject, as well as multiple treatment groups and specimen types. All RSEQREP analyses components are built using open-source R code and R/Bioconductor packages allowing for further customization. As a use case, we provide RSEQREP results for a trivalent influenza vaccine (TIV) RNA-Seq study that collected 1 pre-TIV and 10 post-TIV vaccination samples (days 1-10) for 5 subjects and two specimen types (peripheral blood mononuclear cells and B-cells).

Background: Tularemia is a potential biological weapon due to its high infectivity and ease of dissemination. This study aimed to characterize the innate and adaptive responses induced by two different lots of a live attenuated tularemia vaccine and compare them to other well-characterized viral vaccine immune responses. Methods: Microarray analyses were performed on human peripheral blood mononuclear cells (PBMCs) to determine changes in transcriptional activity that correlated with changes detected by cellular phenotyping, cytokine signaling, and serological assays. Transcriptional profiles after tularemia vaccination were compared with yellow fever [YF-17D], inactivated [TIV], and live attenuated [LAIV] influenza. Results: Tularemia vaccine lots produced strong innate immune responses by Day 2 after vaccination, with an increase in monocytes, NK cells, and cytokine signaling. T cell responses peaked at Day 14. Changes in gene expression, including upregulation of STAT1, GBP1, and IFIT2, predicted tularemia-specific antibody responses. Changes in CCL20 expression positively correlated with peak CD8+ T cell responses, but negatively correlated with peak CD4+ T cell activation. Tularemia vaccines elicited gene expression signatures similar to other replicating vaccines, inducing early upregulation of interferon-inducible genes. Conclusions: A systems vaccinology approach identified that tularemia vaccines induce a strong innate immune response early after vaccination, similar to the response seen after well-studied viral vaccines, and produce unique transcriptional signatures that are strongly correlated to the induction of T cell and antibody responses.

Ribosomal profiling is an emerging experimental technology to measure protein synthesis by sequencing short mRNA fragments undergoing translation in ribosomes. Applied on the genome wide scale, this is a powerful tool to profile global protein synthesis within cell populations of interest. Such information can be utilized for biomarker discovery and detection of treatment-responsive genes. However, analysis of ribosomal profiling data requires careful preprocessing to reduce the impact of artifacts and dedicated statistical methods for visualizing and modeling the high-dimensional discrete read count data. Here we present Ribosomal Profiling Reports (RP-REP), a new open-source cloud-enabled software that allows users to execute start-to-end gene-level ribosomal profiling and RNA-Seq analysis on a pre-configured Amazon Virtual Machine Image (AMI) hosted on AWS or on the user’s own Ubuntu Linux server. The software works with FASTQ files stored locally, on AWS S3, or at the Sequence Read Archive (SRA). RP-REP automatically executes a series of customizable steps including filtering of contaminant RNA, enrichment of true ribosomal footprints, reference alignment and gene translation quantification, gene body coverage, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially translated genes, and generation of heatmaps, co-translated gene clusters, enriched pathways, and other custom visualizations. RP-REP provides functionality to contrast RNA-SEQ and ribosomal profiling results, and calculates translational efficiency per gene. The software outputs a PDF report and publication-ready table and figure files. As a use case, we provide RP-REP results for a dengue virus study that tested cytosol and endoplasmic reticulum cellular fractions of human Huh7 cells pre-infection and at 6 h, 12 h, 24 h, and 40 h post-infection. Case study results, Ubuntu installation scripts, and the most recent RP-REP source code are accessible at GitHub. The cloud-ready AMI is available at AWS (AMI ID: RPREP RSEQREP (Ribosome Profiling and RNA-Seq Reports) v2.1 (ami-00b92f52d763145d3)).

RNA-Seq is increasingly being used to measure human RNA expression on a genome-wide scale. Expression profiles can be interrogated to identify and functionally characterize treatment-responsive genes. Ultimately, such controlled studies promise to reveal insights into molecular mechanisms of treatment effects, identify biomarkers, and realize personalized medicine. RNA-Seq Reports (RSEQREP) is a new open-source cloud-enabled framework that allows users to execute start-to-end gene-level RNA-Seq analysis on a preconfigured RSEQREP Amazon Virtual Machine Image (AMI) hosted by AWS or on their own Ubuntu Linux machine. The framework works with unstranded, stranded, and paired-end sequence FASTQ files stored locally, on Amazon Simple Storage Service (S3), or at the Sequence Read Archive (SRA). RSEQREP automatically executes a series of customizable steps including reference alignment, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially expressed genes, heatmaps, co-expressed gene clusters, enriched pathways, and a series of custom visualizations. The framework outputs a file collection that includes a dynamically generated PDF report using R, knitr, and LaTeX, as well as publication-ready table and figure files. A user-friendly configuration file handles sample metadata entry, processing, analysis, and reporting options. The configuration supports time series RNA-Seq experimental designs with at least one pre- and one post-treatment sample for each subject, as well as multiple treatment groups and specimen types. All RSEQREP analyses components are built using open-source R code and R/Bioconductor packages allowing for further customization. As a use case, we provide RSEQREP results for a trivalent influenza vaccine (TIV) RNA-Seq study that collected 1 pre-TIV and 10 post-TIV vaccination samples (days 1-10) for 5 subjects and two specimen types (peripheral blood mononuclear cells and B-cells).

BACKGROUNDVaccine development for influenza A/H5N1 is an important public health priority, but H5N1 vaccines are less immunogenic than seasonal influenza vaccines. Adjuvant System 03 (AS03) markedly enhances immune responses to H5N1 vaccine antigens, but the underlying molecular mechanisms are incompletely understood.OBJECTIVE AND METHODSWe compared the safety (primary endpoint), immunogenicity (secondary), gene expression (tertiary) and cytokine responses (exploratory) between AS03-adjuvanted and unadjuvanted inactivated split-virus H5N1 influenza vaccines. In a double-blinded clinical trial, we randomized twenty adults aged 18-49 to receive two doses of either AS03-adjuvanted (n = 10) or unadjuvanted (n = 10) H5N1 vaccine 28 days apart. We used a systems biology approach to characterize and correlate changes in serum cytokines, antibody titers, and gene expression levels in six immune cell types at 1, 3, 7, and 28 days after the first vaccination.RESULTSBoth vaccines were well-tolerated. Nine of 10 subjects in the adjuvanted group and 0/10 in the unadjuvanted group exhibited seroprotection (hemagglutination inhibition antibody titer > 1:40) at day 56. Within 24 hours of AS03-adjuvanted vaccination, increased serum levels of IL-6 and IP-10 were noted. Interferon signaling and antigen processing and presentation-related gene responses were induced in dendritic cells, monocytes, and neutrophils. Upregulation of MHC class II antigen presentation-related genes was seen in neutrophils. Three days after AS03-adjuvanted vaccine, upregulation of genes involved in cell cycle and division was detected in NK cells and correlated with serum levels of IP-10. Early upregulation of interferon signaling-related genes was also found to predict seroprotection 56 days after first vaccination.CONCLUSIONSUsing this cell-based systems approach, novel mechanisms of action for AS03-adjuvanted pandemic influenza vaccination were observed.TRIAL REGISTRATIONClinicalTrials.gov NCT01573312.

Understanding the microbial content of the air has important scientific, health, and economic implications. While studies have primarily characterized the taxonomic content of air samples by sequencing the 16S or 18S ribosomal RNA gene, direct analysis of the genomic content of airborne microorganisms has not been possible due to the extremely low density of biological material in airborne environments. We developed sampling and amplification methods to enable adequate DNA recovery to allow metagenomic profiling of air samples collected from indoor and outdoor environments. Air samples were collected from a large urban building, a medical center, a house, and a pier. Analyses of metagenomic data generated from these samples reveal airborne communities with a high degree of diversity and different genera abundance profiles. The identities of many of the taxonomic groups and protein families also allows for the identification of the likely sources of the sampled airborne bacteria.