1. Epidemiology and Global Health
Download icon

Identification of highly-protective combinations of Plasmodium vivax recombinant proteins for vaccine development

  1. Camila Tenorio França
  2. Michael T White
  3. Wen-Qiang He
  4. Jessica B Hostetler
  5. Jessica Brewster
  6. Gabriel Frato
  7. Indu Malhotra
  8. Jakub Gruszczyk
  9. Christele Huon
  10. Enmoore Lin
  11. Benson Kiniboro
  12. Anjali Yadava
  13. Peter Siba
  14. Mary R Galinski
  15. Julie Healer
  16. Chetan Chitnis
  17. Alan F Cowman
  18. Eizo Takashima
  19. Takafumi Tsuboi
  20. Wai-Hong Tham
  21. Rick M Fairhurst
  22. Julian C Rayner
  23. Christopher L King
  24. Ivo Mueller  Is a corresponding author
  1. Walter and Eliza Hall Institute of Medical Research, Australia
  2. University of Melbourne, Australia
  3. Wellcome Trust Sanger Institute, United Kingdom
  4. Case Western Reserve University, United States
  5. Institut Pasteur, France
  6. Papua New Guinea Institute of Medical Research, Papua New Guinea
  7. Walter Reed Army Institute of Research, United States
  8. Emory University, United States
  9. Ehime University, Japan
  10. National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States
Research Article
  • Cited 19
  • Views 1,916
  • Annotations
Cite this article as: eLife 2017;6:e28673 doi: 10.7554/eLife.28673

Abstract

The study of antigenic targets of naturally-acquired immunity is essential to identify and prioritize antigens for further functional characterization. We measured total IgG antibodies to 38 P. vivax antigens, investigating their relationship with prospective risk of malaria in a cohort of 1-3 years old Papua New Guinean children. Using simulated annealing algorithms, the potential protective efficacy of antibodies to multiple antigen-combinations, and the antibody thresholds associated with protection were investigated for the first time. High antibody levels to multiple known and newly identified proteins were strongly associated with protection (IRR 0.44-0.74, P<0.001-0.041). Among five-antigen combinations with the strongest protective effect (>90%), EBP, DBPII, RBP1a, CyRPA, and PVX_081550 were most frequently identified; several of them requiring very low antibody levels to show a protective association. These data identify individual antigens that should be prioritized for further functional testing and establish a clear path to testing a multicomponent P. vivax vaccine.

Article and author information

Author details

  1. Camila Tenorio França

    Division of Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5885-4410

  2. Michael T White

    Division of Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.

  3. Wen-Qiang He

    Department of Medical Biology, University of Melbourne, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.

  4. Jessica B Hostetler

    Malaria Programme, Wellcome Trust Sanger Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  5. Jessica Brewster

    Division of Infection and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.

  6. Gabriel Frato

    Center for Global Health and Diseases, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Indu Malhotra

    Center for Global Health and Diseases, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Jakub Gruszczyk

    Division of Infection and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4536-2964

  9. Christele Huon

    Malaria Parasite Biology and Vaccines Unit, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.

  10. Enmoore Lin

    Malaria Immuno-Epidemiology Unit, Papua New Guinea Institute of Medical Research, Yagaum, Papua New Guinea
    Competing interests
    The authors declare that no competing interests exist.

  11. Benson Kiniboro

    Malaria Immuno-Epidemiology Unit, Papua New Guinea Institute of Medical Research, Yagaum, Papua New Guinea
    Competing interests
    The authors declare that no competing interests exist.

  12. Anjali Yadava

    Malaria Vaccine Branch, Walter Reed Army Institute of Research, Silver Spring, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6751-954X

  13. Peter Siba

    Malaria Immuno-Epidemiology Unit, Papua New Guinea Institute of Medical Research, Yagaum, Papua New Guinea
    Competing interests
    The authors declare that no competing interests exist.

  14. Mary R Galinski

    International Center for Malaria Research, Education, and Development, Emory University, Atlanta, United States
    Competing interests
    The authors declare that no competing interests exist.

  15. Julie Healer

    Department of Medical Biology, University of Melbourne, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.

  16. Chetan Chitnis

    Malaria Parasite Biology and Vaccines Unit, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.

  17. Alan F Cowman

    Department of Medical Biology, University of Melbourne, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5145-9004

  18. Eizo Takashima

    Division of Malaria Research, Proteo-Science Center, Ehime University, Matsuyama, Japan
    Competing interests
    The authors declare that no competing interests exist.

  19. Takafumi Tsuboi

    Division of Malaria Research, Proteo-Science Center, Ehime University, Matsuyama, Japan
    Competing interests
    The authors declare that no competing interests exist.

  20. Wai-Hong Tham

    Department of Medical Biology, University of Melbourne, Parkville, Australia
    Competing interests
    The authors declare that no competing interests exist.

  21. Rick M Fairhurst

    Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Rockville, United States
    Competing interests
    The authors declare that no competing interests exist.

  22. Julian C Rayner

    Malaria Programme, Wellcome Trust Sanger Institute, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

  23. Christopher L King

    Center for Global Health and Diseases, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.

  24. Ivo Mueller

    Division of Population Health and Immunity, Walter and Eliza Hall Institute of Medical Research, Parkville, Australia
    For correspondence
    mueller@wehi.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6554-6889

Funding

National Institutes of Health (U19AI089686)

  • Ivo Mueller

Japan Society for the Promotion of Science (JP26253026)

  • Takafumi Tsuboi

Japan Society for the Promotion of Science (JP15H05276)

  • Takafumi Tsuboi

Japan Society for the Promotion of Science (JP16K15266)

  • Takafumi Tsuboi

National Health and Medical Research Council (Independent Research Institute Infrastructure Support Scheme)

  • Ivo Mueller

University of Melbourne (Melbourne International Postgraduate Scholarship)

  • Camila Tenorio França

University of Melbourne (Melbourne International Postgraduate Scholarship)

  • Wen-Qiang He

Australian Research Council (Australian Research Council Future Fellowship)

  • Wai-Hong Tham

National Health and Medical Research Council (Senior Research Fellowship 1043345)

  • Ivo Mueller

National Institute of Allergy and Infectious Diseases (Intramural Research Program)

  • Rick M Fairhurst

National Institutes of Health (AI063135)

  • Rick M Fairhurst

National Health and Medical Research Council (1021544)

  • Ivo Mueller

National Health and Medical Research Council (1092789)

  • Alan F Cowman

Malaria Elimination Science Alliance

  • Ivo Mueller

Wellcome (98051)

  • Julian C Rayner

Medical Research Council (MR/J002283/1)

  • Julian C Rayner

Medical Research Council (MR/L012170/1)

  • Julian C Rayner

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Department of Health and Human Services, Department of the Army, the Department of Defense, nor the U.S. Government.

Ethics

Human subjects: Ethical clearance for this study was obtained from the Medical Research and Advisory Committee of the Ministry of Health in PNG (MRAC 05.19), and the Walter and Eliza Hall Institute (HREC 07/07). Written informed consent was obtained from the parents or guardians of all children participating in the PNG cohort study prior to enrollment.

Reviewing Editor

  1. Urszula Krzych, Walter Reed Army Institute of Research, United States

Publication history

  1. Received: May 16, 2017
  2. Accepted: September 25, 2017
  3. Accepted Manuscript published: September 26, 2017 (version 1)
  4. Version of Record published: October 24, 2017 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Metrics

  • 1,916
    Page views
  • 412
    Downloads
  • 19
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, Scopus, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Categories and tags

Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease

    Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys

    Daniel B Larremore et al.
    Research Article

    Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies has been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions, and found that sampling schemes informed by demographics and contact networks outperform uniform sampling. The framework can be adapted to optimize serosurvey design given test characteristics and capacity, population demography, sampling strategy, and modeling approach, and can be tailored to support decision-making around introducing or removing interventions.

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease

    Viral load and contact heterogeneity predict SARS-CoV-2 transmission and super-spreading events

    Ashish Goyal et al.
    Research Article Updated

    SARS-CoV-2 is difficult to contain because many transmissions occur during pre-symptomatic infection. Unlike influenza, most SARS-CoV-2-infected people do not transmit while a small percentage infect large numbers of people. We designed mathematical models which link observed viral loads with epidemiologic features of each virus, including distribution of transmissions attributed to each infected person and duration between symptom onset in the transmitter and secondarily infected person. We identify that people infected with SARS-CoV-2 or influenza can be highly contagious for less than 1 day, congruent with peak viral load. SARS-CoV-2 super-spreader events occur when an infected person is shedding at a very high viral load and has a high number of exposed contacts. The higher predisposition of SARS-CoV-2 toward super-spreading events cannot be attributed to additional weeks of shedding relative to influenza. Rather, a person infected with SARS-CoV-2 exposes more people within equivalent physical contact networks, likely due to aerosolization.

    1. Epidemiology and Global Health
    2. Medicine

    Epidemiological transition to mortality and refracture following an initial fracture

    Thao Phuong Ho-Le et al.
    Research Article Updated

    This study sought to redefine the concept of fracture risk that includes refracture and mortality, and to transform the risk into "skeletal age". We analysed data obtained from 3521 women and men aged 60 years and older, whose fracture incidence, mortality, and bone mineral density (BMD) have been monitored since 1989. During the 20-year follow-up period, among 632 women and 184 men with a first incident fracture, the risk of sustaining a second fracture was higher in women (36%) than in men (22%), but mortality risk was higher in men (41%) than in women (25%). The increased risk of mortality was not only present with an initial fracture, but was accelerated with refractures. Key predictors of post-fracture mortality were male gender (hazard ratio [HR] 2.4; 95% CI, 1.79–3.21), advancing age (HR 1.67; 1.53–1.83), and lower femoral neck BMD (HR 1.16; 1.01–1.33). A 70-year-old man with a fracture is predicted to have a skeletal age of 75. These results were incorporated into a prediction model to aid patient-doctor discussion about fracture vulnerability and treatment decisions.