Molecular correlates of vaccine-induced protection against typhoid fever
Henderson Zhu, Irina Chelysheva, Deborah L. Cross, Luke Blackwell, Celina Jin, Malick M. Gibani, Elizabeth Jones, Jennifer Hill, Johannes Trück, Dominic F. Kelly, Christoph J. Blohmke, Andrew J. Pollard, Daniel O’Connor
Henderson Zhu, Irina Chelysheva, Deborah L. Cross, Luke Blackwell, Celina Jin, Malick M. Gibani, Elizabeth Jones, Jennifer Hill, Johannes Trück, Dominic F. Kelly, Christoph J. Blohmke, Andrew J. Pollard, Daniel O’Connor
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Clinical Research and Public Health

Molecular correlates of vaccine-induced protection against typhoid fever

Abstract

BACKGROUND Typhoid fever is caused by the Gram-negative bacterium Salmonella enterica serovar Typhi and poses a substantial public health burden worldwide. Vaccines have been developed based on the surface Vi-capsular polysaccharide of S. Typhi; these include a plain-polysaccharide-based vaccine, ViPS, and a glycoconjugate vaccine, ViTT. To understand immune responses to these vaccines and their vaccine-induced immunological protection, molecular signatures were analyzed using bioinformatic approaches.METHODS Bulk RNA-Seq data were generated from blood samples obtained from adult human volunteers enrolled in a vaccine trial, who were then challenged with S. Typhi in a controlled human infection model (CHIM). These data were used to conduct differential gene expression analyses, gene set and modular analyses, B cell repertoire analyses, and time-course analyses at various post-vaccination and post-challenge time points between participants receiving ViTT, ViPS, or a control meningococcal vaccine.RESULTS Transcriptomic responses revealed strong differential molecular signatures between the 2 typhoid vaccines, mostly driven by the upregulation in humoral immune signatures, including selective usage of immunoglobulin heavy chain variable region (IGHV) genes and more polarized clonal expansions. We describe several molecular correlates of protection against S. Typhi infection, including clusters of B cell receptor (BCR) clonotypes associated with protection, with known binders of Vi-polysaccharide among these.CONCLUSION The study reports a series of contemporary analyses that reveal the transcriptomic signatures after vaccination and infectious challenge, while identifying molecular correlates of protection that may inform future vaccine design and assessment.TRIAL REGISTRATION ClinicalTrials.gov NCT02324751.

Authors

Henderson Zhu, Irina Chelysheva, Deborah L. Cross, Luke Blackwell, Celina Jin, Malick M. Gibani, Elizabeth Jones, Jennifer Hill, Johannes Trück, Dominic F. Kelly, Christoph J. Blohmke, Andrew J. Pollard, Daniel O’Connor

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Figure 2

Global overview of blood gene expression data over the study time points.

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Global overview of blood gene expression data over the study time points...
(A) PC analysis plot and contribution plot of RNA-Seq data (13,609 genes, n = 514) from all study time points, batch corrected for the sequencing pool. (B) Contribution plot of the genes contributing to PC1 and PC2. Genes with the greatest contribution are highlighted in red. (C) Volcano plot highlighting DEGs (FDR <0.01; red = upregulated, blue = downregulated) at day 1 after vaccination compared with pre-vaccination expression (99 DEGs, n = 72). (D) Volcano plot highlighting DEGs (FDR <0.01; red = upregulated, blue = downregulated) at post-vaccination day 7 compared with pre-vaccination expression (140 DEGs, n = 67). (E) Volcano plot highlighting DEGs (FDR <0.01; red = upregulated, blue = downregulated) at 12 hours after challenge compared with pre-challenge expression (678 DEGs, n = 101). (F) Volcano plot highlighting DEGs (FDR <0.01; red = upregulated, blue = downregulated) at day 7 after challenge (in the non-diagnosed group) compared with pre-challenge expression (172 DEGs, n = 50). (G) Volcano plot highlighting DEGs (FDR <0.01; red = upregulated, blue = downregulated) at typhoid diagnosis compared with pre-challenge expression (6,854 DEGs, n = 47). P values were obtained from the moderated t statistic, after adjustment for multiple testing (Benjamini and Hochberg’s method). The top 10 genes, ranked by FDR, are labeled.