Identification of early gene expression profiles associated with long-lasting antibody responses to the Ebola vaccine Ad26.ZEBOV/MVA-BN-Filo

MVA-based SARS-CoV-2 vaccine candidates encoding different spike protein conformations induce distinct early transcriptional responses which may impact subsequent adaptive immunity

Introduction

Vaccine platforms such as viral vectors and mRNA can accelerate vaccine development in response to newly emerging pathogens, as demonstrated during the COVID-19 pandemic. However, the differential effects of platform and antigen insert on vaccine immunogenicity remain incompletely understood. Innate immune responses induced by viral vector vaccines are suggested to have an adjuvant effect for subsequent adaptive immunity. Integrating data on both innate and adaptive immunity, systems vaccinology approaches can improve the understanding of vaccine-induced immune mechanisms.

Methods

Two vaccine candidates against SARS-CoV-2, both based on the viral vector Modified Vaccinia virus Ankara (MVA) and encoding the native (MVA-SARS-2-S) or prefusion-stabilized spike protein (MVA-SARS-2-ST), were evaluated in phase 1 clinical trials (ClinicalTrials.gov: NCT04569383, NCT04895449). Longitudinal dynamics of innate and early adaptive immune responses induced by vaccination in SARS-CoV-2-naïve individuals were analyzed based on transcriptome and flow cytometry data, in comparison to the licensed ChAd and mRNA vaccines.

Results

Compared to MVA-SARS-2-S, MVA-SARS-2-ST (encoding the prefusion-stabilized spike protein) induced a stronger transcriptional activation early after vaccination, as well as higher virus neutralizing antibodies. Positive correlations were observed between innate and adaptive immune responses induced by a second MVA-SARS-2-ST vaccination. MVA-, ChAd- and mRNA-based vaccines induced distinct immune signatures, with the overall strongest transcriptional activation as well as monocyte and circulating T follicular helper (cTFH) cell responses induced by ChAd.

Discussion

Our findings suggest a potential impact of the spike protein conformation not only on adaptive but also on innate immune responses. As indicated by positive correlations between several immune parameters induced by MVA-SARS-2-ST, the distinct transcriptional activation early after vaccination may be linked to the induction of classical monocytes and activation of cTFH1 cells, which may in turn result in the superior adaptive immunogenicity of MVA-SARS-2-ST, compared to MVA-SARS-2-S. Overall, our data demonstrate that both the vaccine platform and antigen insert can affect innate immune responses and subsequent vaccine immunogenicity in humans.

Urgent considerations for booster vaccination strategies against Ebola virus disease

With two endorsed and prophylactic vaccines against Zaire ebolavirus (referred to hereafter as EBOV), the number of individuals vaccinated against EBOV worldwide is estimated to range between 500 000 and 1 000 000 individuals, increasing with every renewed EBOV threat and vaccination campaign. Therefore, re-exposure of previously vaccinated health-care workers, and possibly community members, could become more frequent. In the absence of long-term data on vaccine efficacy and duration of protection, we urgently need to understand revaccination strategies that could maximise the level of protection. In this Personal View, we highlight the scarcity of available evidence to guide revaccination recommendations for the accumulating groups of previously vaccinated communities or front-line health-care workers that could be redeployed or re-exposed in the next EBOV outbreak(s). This evidence base is crucial to identify optimal target populations and the frequency of booster doses, and guide vaccine interchangeability (especially in settings with limited or unpredictable vaccine supplies), while preventing vaccine mistrust, equity concerns, and exclusion of vulnerable populations. We discuss five priority gaps (to whom, when, and how frequently, to provide booster doses; long-term correlates and thresholds of protection; the effect of vector-directed immunity and viral variant protection; comparative research in mix-and-match schedules; and implementation concerns) that should be urgently tackled to adapt the initial EBOV prophylactic vaccination strategies considering potential booster dose vaccinations.

Machine learning-based analysis of Ebola virus' impact on gene expression in nonhuman primates

Introduction

This study introduces the Supervised Magnitude-Altitude Scoring (SMAS) methodology, a novel machine learning-based approach for analyzing gene expression data from non-human primates (NHPs) infected with Ebola virus (EBOV). By focusing on host-pathogen interactions, this research aims to enhance the understanding and identification of critical biomarkers for Ebola infection.

Methods

We utilized a comprehensive dataset of NanoString gene expression profiles from Ebola-infected NHPs. The SMAS system combines gene selection based on both statistical significance and expression changes. Employing linear classifiers such as logistic regression, the method facilitates precise differentiation between RT-qPCR positive and negative NHP samples.

Results

The application of SMAS led to the identification of IFI6 and IFI27 as key biomarkers, which demonstrated perfect predictive performance with 100% accuracy and optimal Area Under the Curve (AUC) metrics in classifying various stages of Ebola infection. Additionally, genes including MX1, OAS1, and ISG15 were significantly upregulated, underscoring their vital roles in the immune response to EBOV.

Discussion

Gene Ontology (GO) analysis further elucidated the involvement of these genes in critical biological processes and immune response pathways, reinforcing their significance in Ebola pathogenesis. Our findings highlight the efficacy of the SMAS methodology in revealing complex genetic interactions and response mechanisms, which are essential for advancing the development of diagnostic tools and therapeutic strategies.

Conclusion

This study provides valuable insights into EBOV pathogenesis, demonstrating the potential of SMAS to enhance the precision of diagnostics and interventions for Ebola and other viral infections.

Computational mining of B cell receptor repertoires reveals antigen-specific and convergent responses to Ebola vaccination

Outbreaks of Ebolaviruses, such as Sudanvirus (SUDV) in Uganda in 2022, demonstrate that species other than the Zaire ebolavirus (EBOV), which is currently the sole virus represented in current licensed vaccines, remain a major threat to global health. There is a pressing need to develop effective pan-species vaccines and novel monoclonal antibody-based therapeutics for Ebolavirus disease. In response to recent outbreaks, the two dose, heterologous Ad26.ZEBOV/MVA-BN-Filo vaccine regimen was developed and was tested in a large phase II clinical trial (EBL2001) as part of the EBOVAC2 consortium. Here, we perform bulk sequencing of the variable heavy chain (VH) of B cell receptors (BCR) in forty participants from the EBL2001 trial in order to characterize the BCR repertoire in response to vaccination with Ad26.ZEBOV/MVA-BN-Filo. We develop a comprehensive database, EBOV-AbDab, of publicly available Ebolavirus-specific antibody sequences. We then use our database to predict the antigen-specific component of the vaccinee repertoires. Our results show striking convergence in VH germline gene usage across participants following the MVA-BN-Filo dose, and provide further evidence of the role of IGHV3-15 and IGHV3-13 antibodies in the B cell response to Ebolavirus glycoprotein. Furthermore, we found that previously described Ebola-specific mAb sequences present in EBOV-AbDab were sufficient to describe at least one of the ten most expanded BCR clonotypes in more than two thirds of our cohort of vaccinees following the boost, providing proof of principle for the utility of computational mining of immune repertoires.

Refined innate plasma signature after rVSVΔG-ZEBOV-GP immunization is shared among adult cohorts in Europe and North America

Background

During the last decade Ebola virus has caused several outbreaks in Africa. The recombinant vesicular stomatitis virus-vectored Zaire Ebola (rVSVΔG-ZEBOV-GP) vaccine has proved safe and immunogenic but is reactogenic. We previously identified the first innate plasma signature response after vaccination in Geneva as composed of five monocyte-related biomarkers peaking at day 1 post-immunization that correlates with adverse events, biological outcomes (haematological changes and viremia) and antibody titers. In this follow-up study, we sought to identify additional biomarkers in the same Geneva cohort and validate those identified markers in a US cohort.

Methods

Additional biomarkers were identified using multiplexed protein biomarker platform O-link and confirmed by Luminex. Principal component analysis (PCA) evaluated if these markers could explain a higher variability of the vaccine response (and thereby refined the initial signature). Multivariable and linear regression models evaluated the correlations of the main components with adverse events, biological outcomes, and antibody titers. External validation of the refined signature was conducted in a second cohort of US vaccinees (n=142).

Results

Eleven additional biomarkers peaked at day 1 post-immunization: MCP2, MCP3, MCP4, CXCL10, OSM, CX3CL1, MCSF, CXCL11, TRAIL, RANKL and IL15. PCA analysis retained three principal components (PC) that accounted for 79% of the vaccine response variability. PC1 and PC2 were very robust and had different biomarkers that contributed to their variability. PC1 better discriminated different doses, better defined the risk of fever and myalgia, while PC2 better defined the risk of headache. We also found new biomarkers that correlated with reactogenicity, including transient arthritis (MCP-2, CXCL10, CXCL11, CX3CL1, MCSF, IL-15, OSM). Several innate biomarkers are associated with antibody levels one and six months after vaccination. Refined PC1 correlated strongly in both data sets (Geneva: r = 0.97, P < 0.001; US: r = 0.99, P< 0.001).

Conclusion

Eleven additional biomarkers refined the previously found 5-biomarker Geneva signature. The refined signature better discriminated between different doses, was strongly associated with the risk of adverse events and with antibody responses and was validated in a separate cohort.