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Background Imprinted genes are epigenetically regulated in normal tissues to follow monoallelic expression according to the parent of origin of each allele. Some of these patterns are dysregulated in cancer. Results We developed a novel computational multi-omic pipeline to evaluate monoallelic and biallelic expression patterns based on matched RNA-seq expression data, whole-exome sequencing information, and copy number data. We analyzed allelic expression of the entire genes, individual isoforms, and each exon of 59,283 autosomal protein-coding and ncRNA genes, with a focus on 94 genes previously reported to be imprinted. We analyzed 108 cell lines from 9 different tumor histologies using molecular data from the DepMap Portal for the Cancer Cell Line Encyclopedia. Allelic expression patterns of imprinted genes and isoforms in tumor cells were variable. We also identified additional genes and isoforms with predominantly monoallelic expression due to a variety of potential mechanisms. We provide a novel public dataset of transcriptome-wide allelic expression patterns in cell lines from diverse tumor categories, which can serve as a resource for future cancer studies. We examined associations of in vitro cell line response to antitumor agents and repurposed drugs with allelic patterns and overall levels of isoform expression of imprinted genes and of additional genes with predominantly monoallelic expression. Drug response was associated with isoform expression patterns of multiple imprinted genes including CPA4, DGCR6, DNMT1, GNAS, GRB10, H19, NAA60, OSBPL5, PHACTR2, and ZFAT, predominantly monoallelically expressed MAP2K5 and BCLAF1, and additional predominantly monoallelically expressed genes. Multiple associations may be related to mechanisms of drug activity, including associations between the response to the DNA damaging agents and allelic expression of ZFAT, CDC27, and BCLAF1 isoforms , and the response to inhibitors of multiple signaling pathways with expression patterns of GNAS isoforms. Conclusions Tumor cells have a range of monoallelic and biallelic expression patterns in both imprinted and non-imprinted genes and are likely affected by the complex interplay among changes in allelic expression, sequence variants, copy number changes, and expression changes of biologically important genes. Multiple isoform-specific patterns of allelic expression were associated with drug response, indicating complex mechanisms of cancer chemoresistance.

Vaccine 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. We 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. Both 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. Using this cell-based systems approach, novel mechanisms of action for AS03-adjuvanted pandemic influenza vaccination were observed. ClinicalTrials.gov NCT01573312.

Extensive genetic diversity plays a role in immune evasion, and antibody responses can be strain-specific or broadly reactive depending on the epitope. Controlled human malaria infection (CHMI) allows investigation of immune responses to variant parasite proteins after a single infection with a known strain. We designed a novel diversity-reflecting peptide microarray containing 638,817 unique peptides representing 22,655 variants of 227 proteins from 23 P genome assemblies and 379 field isolates. Using this array, we probed sera from 38 malaria naïve adults before and 28 days after CHMI with one of two genetically distinct strains, NF54 (n = 21) or 7G8 (n = 17). We examined fold-increase in antibody response (intensity) and cross-reactivity to protein variants (breadth). ABCPred was used to predict linear epitopes for all 227 proteins. We used MEME to identify enriched motifs in regions of high intensity or breadth, which were presumed to be potential epitopes. While the two CHMI groups had similar intensity of responses to all proteins on the array, 20 proteins on the array had differential breadth of responses and participants infected with 7G8 strain had a higher breadth of responses to 17 of them. Of 543 ABCPred-predicted epitopes, 66 overlapped with MEME-identified epitopes, six of which were highly cross-reactive with >95% of peptide variants serorecognized by at least one CHMI group. Overall, we found most antibody responses to be comparable after infection with the NF54 strain or 7G8 strain, but we saw notable differences for ~10% of proteins on the array. While many MEME-identified epitopes from highly cross-reactive proteins were asparagine rich, an epitope from PF3D7_1033200 (ETRAMP10.2) was not. Highly cross-reactive responses to ETRAMP10.2 could be further characterized and ETRAMP10.2 could be considered for inclusion in a next generation vaccine.

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.

Over 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. We collected longitudinal peripheral blood mononuclear cell (PBMC) samples from 10 subjects before and after vaccination with a live attenuated 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. Our 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.

[This corrects the article DOI: 10.3389/fimmu.2022.1093242.].

Transcriptomic signatures were identified in human peripheral blood mononuclear cells (PBMCs) and breast milk lymphocyte (BML) cells induced by trivalent inactivated influenza vaccine (TIV) or live attenuated influenza vaccine (LAIV) administered after delivery. We performed an RNA-Seq analysis on blood and breast milk samples from a subset of subjects enrolled in a randomized, double-blind controlled study in breastfeeding women who received either intranasal LAIV and intramuscular placebo, or intramuscular TIV and intranasal placebo (LAIV, n  = 10 and TIV, n  = 6). Differentially expressed genes, gene clusters, and enriched pathways were identified. We observed increased innate immune signaling responses in BML but not in PBMC at Day 28 for the LAIV group. We hypothesize that breastfeeding extended the innate response to LAIV via mucosal immunity. An association between an increased IgG antibody response in TIV vs. LAIV identified in the parent study using ELISA corresponded to IGHG1 immunoglobulin gene expression in Day 28 PBMCs.

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)).

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.

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.