Cited by 1Bacterial Infections and VaccinesDiphtheria, Corynebacterium, and TetanusImmune responses and vaccinations

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Systems biology-based assessment of immune responses to whole cell and acellular pertussis vaccines

Open access
Leguia, Mariana, Vila-Sanjurjo, Antón, Juarez, Diana, Garcia-Glaessner, Alejandra, Gil, Ana I., Alvarez, Mayita, Cornejo, Rubelio, Cherikh, Sami, Gelber, Casey E., Goll, Johannes B., Howard, Leigh M., Jimenez-Truque, Natalia, Edwards, Kathryn M., Creech, C. Buddy, Lanata, Claudio F.·2025·npj Vaccines

Published version of a preprint

Abstract

Given the local and systemic adverse reactions associated with whole-cell pertussis vaccines combined with diphtheria and tetanus toxoids (DTP), acellular pertussis vaccines combined with the same toxoids (DTaP) were developed in the 1990s. In comparison to DTP, DTaP vaccines demonstrated reduced reactogenicity and equivalent or improved immunogenicity and efficacy. However, there has been a resurgence of pertussis disease, particularly in DTaP-vaccinated children, suggesting that immunity wanes more quickly with DTaP vaccination. To elucidate the differences in immune responses to DTP and DTaP vaccines, we employed a systems biology-based strategy to compare global changes in gene expression following primary vaccination with either DTP or DTaP. We used RNA-Seq and ribosome profiling (RP) to identify transcriptional and translational signatures, respectively, in peripheral blood mononuclear cells (PBMCs) collected from 50 infant recipients of DTP or DTaP at two time-points (baseline (pre-vaccination at Day 1) and either Day 2 or 8 post-vaccination). We also used standard serologic methods to assess immunogenicity, and correlated these results with transcriptional and translational signatures. Here, we provide a detailed description of the rationale, experimental design, methodology, and enrollment procedures used. Given the technical complexity of our approach, our objective is to fill knowledge gaps, describe key quality metrics, and support future publications. In brief, we recovered 4-12 million PBMCs (average 8.9 million) with 99% viability per 2.5 mL blood sample, enabling excellent nucleic acid recovery yields for the preparation of high-quality sequencing libraries. In turn, these generated RNA-Seq and RP datasets with sufficient genome coverage breadth and depth to enable differential gene expression analyses, demonstrating the validity of this approach to study pertussis vaccine immunology specifically, and its utility to characterize mechanisms of the human immune response to vaccination generally.

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Research works printed but not linked: 26

  1. Edwards, K. M. Pertussis Vaccines, in Vaccines, O. W. A. Plotkin S. A., Offit P. A., Editor. Sixth edition. edn, (Elsevier Saunders, 2013).
  2. Decker, M. D. et al. Comparison of 13 acellular pertussis vaccines: adverse reactions. Pediatrics 96, 557–566 (1995). · DOI
  3. Edwards, K. M. et al. Comparison of 13 acellular pertussis vaccines: overview and serologic response. Pediatrics 96, 548–557 (1995). · DOI
  4. Klein, N. P., Bartlett, J., Rowhani-Rahbar, A., Fireman, B. & Baxter, R. Waning protection after fifth dose of acellular pertussis vaccine in children. N. Engl. J. Med. 367, 1012–1019 (2012). · DOI
  5. Witt, M. A., Katz, P. H. & Witt, D. J. Unexpectedly limited durability of immunity following acellular pertussis vaccination in preadolescents in a North American outbreak. Clin. Infect. Dis. 54, 1730–1735 (2012). · DOI
  6. Sheridan, S. L., Ware, R. S., Grimwood, K. & Lambert, S. B. Number and order of whole cell pertussis vaccines in infancy and disease protection. JAMA 308, 454–456 (2012). · DOI
  7. Liko, J., Robison, S. G. & Cieslak, P. R. Priming with whole-cell versus acellular pertussis vaccine. N. Engl. J. Med 368, 581–582 (2013). · DOI
  8. Warfel, J. M., Zimmerman, L. I. & Merkel, T. J. Acellular pertussis vaccines protect against disease but fail to prevent infection and transmission in a nonhuman primate model. Proc. Natl Acad. Sci. USA 111, 787–792 (2014). · DOI · Paper page
  9. Pulendran, B. Systems vaccinology: probing humanity’s diverse immune systems with vaccines. Proc. Natl Acad. Sci. USA 111, 12300–12306 (2014). · DOI
  10. Ingolia, N. T. Ribosome profiling: new views of translation, from single codons to genome scale. Nat. Rev. Genet. 15, 205–213 (2014). · DOI
  11. Ingolia, N. T., Brar, G. A., Rouskin, S., McGeachy, A. M. & Weissman, J. S. The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosome-protected mRNA fragments. Nat. Protoc. 7, 1534–1550 (2012). · DOI
  12. Brar, G. A. & Weissman, J. S. Ribosome profiling reveals the what, when, where and how of protein synthesis. Nat. Rev. Mol. Cell Biol. 16, 651–664 (2015). · DOI
  13. Edwards, K. M. Review of the laboratory approaches to the detection of antibody and cell-mediated immunity to pertussis disease and vaccine. Expert Rev. Vaccines 13, 1183–1190 (2014). · DOI
  14. Edwards, K. M. & Berbers, G. A. Immune responses to pertussis vaccines and disease. J. Infect. Dis. 209, S10–S15 (2014). · DOI
  15. Creech, C. B. et al. Immunologic profiling of the infant immune response to whole-cell and acellular pertussis vaccines. npj Vaccines https://doi.org/10.1038/s41541-025-01170-5 (2025). · DOI
  16. Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. & Weissman, J. S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218–223 (2009). · DOI · Paper page
  17. Ingolia, N. T., Lareau, L. F. & Weissman, J. S. Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Cell 147, 789–802 (2011). · DOI · Paper page
  18. Fagerberg, L. et al. Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics. Mol. Cell Proteom. 13, 397–406 (2014). · DOI · Paper page
  19. Prensner, J. R. et al. What Can Ribo-Seq, Immunopeptidomics, and Proteomics Tell Us About the Noncanonical Proteome? Mol. Cell Proteom. 22, 100631 (2023). · DOI
  20. Duncan, C. D. S. & Mata, J. Effects of cycloheximide on the interpretation of ribosome profiling experiments in Schizosaccharomyces pombe. Sci. Rep. 7, 10331 (2017). · DOI
  21. Sharma, P., Wu, J., Nilges, B. S. & Leidel, S. A. Humans and other commonly used model organisms are resistant to cycloheximide-mediated biases in ribosome profiling experiments. Nat. Commun. 12, 5094 (2021). · DOI
  22. Guo, H., Ingolia, N. T., Weissman, J. S. & Bartel, D. P. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466, 835–840 (2010). · DOI · Paper page
  23. Kleiveland, C. R. in The Impact of Food Bioactives on Health: in vitro and ex vivo models (eds K. Verhoeckx et al.) 161–167 (Springer Copyright 2015, The Author(s) 2015). · DOI · Paper page
  24. Slade, H. B. et al. Flow cytometric analysis of lymphocyte subpopulations in infants with congenital heart disease. J. Clin. Lab. Anal. 3, 14–20 (1989). · DOI
  25. Kutvirt, S. G., Lewis, S. L. & Simon, T. L. Lymphocyte phenotypes in infants are altered by separation of blood on density gradients. Br. J. Biomed. Sci. 50, 321–328 (1993).
  26. Vila-Sanjurjo, A., Juarez, D., Loyola, S., Torres, M. & Leguia, M. Minority gene expression profiling: probing the genetic signatures of pathogenesis using ribosome profiling. J. Infect. Dis. 221, S341–S357 (2020). · DOI

Metadata

Authors
Leguia, M., Vila-Sanjurjo, A., Juarez, D., Garcia-Glaessner, A., Gil, A. I., Alvarez, M., Cornejo, R., Cherikh, S., Gelber, C. E., Goll, J. B., Howard, L. M., Jimenez-Truque, N., Edwards, K. M., Creech, C. B., & Lanata, C. F.
Affiliations
  • Pontificia Universidad Católica del Perú (PE)
  • Instituto de Investigación Nutricional (PE)
  • Emmes (United States) (US)
  • Vanderbilt University Medical Center (US)
Venue
npj Vaccines
Published
2025-08-11
Volume
10
Issue
1
Pages
188-188
ISSN
2059-0105 (ISSN-L)
OpenAlex
W4413106949
Cited by
1
References
2
Citations by year
2025: 1
FWCI
0.55
Type
journal article
Language
en
Open access
Locations
  • npj Vaccines (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
NIH-NIAID (HSN2722001300023I, Task Order 17)
Topics
  • Life Sciences › Immunology and Microbiology › Microbiology › Bacterial Infections and Vaccines
  • Health Sciences › Medicine › Infectious Diseases › Diphtheria, Corynebacterium, and Tetanus
  • Life Sciences › Immunology and Microbiology › Immunology › Immune responses and vaccinations
Keywords
pertussis vaccine, DTaP vaccine, DTP vaccine, whole-cell pertussis vaccine, acellular pertussis vaccine, vaccine immunogenicity, vaccine response, peripheral blood mononuclear cells, gene expression signatures, ribosome profiling, infant immunization, waning immunity, pertussis resurgence

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