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Modelling pathogen load dynamics to elucidate mechanistic determinants of host–Plasmodium falciparum interactions

Nature Microbiology volume 4, pages 1592–1602 (2019)Cite this article

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Abstract

During infection, increasing pathogen load stimulates both protective and harmful aspects of the host response. The dynamics of this interaction are hard to quantify in humans, but doing so could improve understanding of the mechanisms of disease and protection. We sought to model the contributions of the parasite multiplication rate and host response to observed parasite load in individual subjects infected with Plasmodium falciparum malaria, using only data obtained at the time of clinical presentation, and then to identify their mechanistic correlates. We predicted higher parasite multiplication rates and lower host responsiveness in cases of severe malaria, with severe anaemia being more insidious than cerebral malaria. We predicted that parasite-growth inhibition was associated with platelet consumption, lower expression of CXCL10 and type 1 interferon-associated genes, but increased cathepsin G and matrix metallopeptidase 9 expression. We found that cathepsin G and matrix metallopeptidase 9 directly inhibit parasite invasion into erythrocytes. The parasite multiplication rate was associated with host iron availability and higher complement factor H levels, lower expression of gametocyte-associated genes but higher expression of translation-associated genes in the parasite. Our findings demonstrate the potential of using explicit modelling of pathogen load dynamics to deepen understanding of host–pathogen interactions and identify mechanistic correlates of protection.

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Fig. 1: Estimating the dynamics of parasite load and host response in malaria.
Fig. 2: Contribution of parasite-load dynamics to severe malaria phenotype.
Fig. 3: The protective effect of platelets is revealed by estimating PGI.
Fig. 4: Transcriptional correlates of PGI.
Fig. 5: Effects of cathepsin G and MMP9 on parasite growth and expression of erythrocyte invasion receptors.
Fig. 6: Parasite gene-expression modules associated with predicted m.

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Data availability

Estimates of parameters determining within-host dynamics in the malariatherapy dataset were obtained from ref. 4, whose corresponding author may be contacted at klaus.dietz@uni-tuebingen.de. RNA-seq data have been deposited in the ArrayExpress database at EMBL-EBI (www.ebi.ac.uk/arrayexpress) under the accession number E-MTAB-6413. Individual subject-level data is available within the paper and its Supplementary information files. All other data that support the findings of this study are available from the corresponding author on reasonable request.

Code availability

The source code for the model simulating Gambian child subjects and examples of its use are presented as Supplementary Code library file and Supplementary Code example file.

References

  1. Plotkin, S. A. Complex correlates of protection after vaccination. Clin. Infect. Dis. 56, 1458–1465 (2013).

    Article  CAS  Google Scholar 

  2. Zumla, A. et al. Host-directed therapies for infectious diseases: current status, recent progress, and future prospects. Lancet Infect. Dis. 16, e47–e63 (2016).

    Article  Google Scholar 

  3. Cunnington, A. J. The importance of pathogen load. PLoS Pathog. 11, e1004563 (2015).

    Article  Google Scholar 

  4. Dietz, K., Raddatz, G. & Molineaux, L. Mathematical model of the first wave of Plasmodium falciparum asexual parasitemia in non-immune and vaccinated individuals. Am. J. Trop. Med. Hyg. 75, 46–55 (2006).

    Article  Google Scholar 

  5. Kumaratilake, L. M. et al. A synthetic tumor necrosis factor-α agonist peptide enhances human polymorphonuclear leukocyte-mediated killing of Plasmodium falciparum in vitro and suppresses Plasmodium chabaudi infection in mice. J. Clin. Invest. 95, 2315–2323 (1995).

    Article  CAS  Google Scholar 

  6. Kumaratilake, L. M., Ferrante, A. & Rzepczyk, C. M. Tumor necrosis factor enhances neutrophil-mediated killing of Plasmodium falciparum. Infect. Immun. 58, 788–793 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Smith, T. et al. Relationships between Plasmodium falciparum infection and morbidity in a highly endemic area. Parasitology 109, 539–549 (1994).

    Article  Google Scholar 

  8. Crompton, P. D. et al. Malaria immunity in man and mosquito: insights into unsolved mysteries of a deadly infectious disease. Annu. Rev. Immunol. 32, 157–187 (2014).

    Article  CAS  Google Scholar 

  9. Okebe, J. et al. School-based countrywide seroprevalence survey reveals spatial heterogeneity in malaria transmission in The Gambia. PLoS ONE 9, e110926 (2014).

    Article  Google Scholar 

  10. Cunnington, A. J., Walther, M. & Riley, E. M. Piecing together the puzzle of severe malaria. Sci. Transl. Med. 5, 211ps218 (2013).

    Article  Google Scholar 

  11. Cunnington, A. J., Bretscher, M. T., Nogaro, S. I., Riley, E. M. & Walther, M. Comparison of parasite sequestration in uncomplicated and severe childhood Plasmodium falciparum malaria. J. Infect. 67, 220–230 (2013).

    Article  Google Scholar 

  12. Hendriksen, I. C. et al. Defining falciparum-malaria-attributable severe febrile illness in moderate-to-high transmission settings on the basis of plasma PfHRP2 concentration. J. Infect. Dis. 207, 351–361 (2013).

    Article  CAS  Google Scholar 

  13. Kurtzhals, J. A. et al. Low plasma concentrations of interleukin 10 in severe malarial anaemia compared with cerebral and uncomplicated malaria. Lancet 351, 1768–1772 (1998).

    Article  CAS  Google Scholar 

  14. Perkins, D. J. et al. Severe malarial anemia: innate immunity and pathogenesis. Int. J. Biol. Sci. 7, 1427–1442 (2011).

    Article  CAS  Google Scholar 

  15. Cunnington, A. J., Riley, E. M. & Walther, M. Stuck in a rut? Reconsidering the role of parasite sequestration in severe malaria syndromes. Trends Parasitol. 29, 585–592 (2013).

    Article  Google Scholar 

  16. Kho, S. et al. Platelets kill circulating parasites of all major Plasmodium species in human malaria. Blood 132, 1332–1344 (2018).

    Article  CAS  Google Scholar 

  17. McMorran, B. J. et al. Platelets kill intraerythrocytic malarial parasites and mediate survival to infection. Science 323, 797–800 (2009).

    Article  CAS  Google Scholar 

  18. Cserti-Gazdewich, C. M. et al. Inter-relationships of cardinal features and outcomes of symptomatic pediatric Plasmodium falciparum malaria in 1,933 children in Kampala, Uganda. Am. J. Trop. Med. Hyg. 88, 747–756 (2013).

    Article  Google Scholar 

  19. Lee, H. J. et al. Integrated pathogen load and dual transcriptome analysis of systemic host-pathogen interactions in severe malaria. Sci. Transl. Med. 10, eaar3619 (2018).

    Article  Google Scholar 

  20. Arthur, J. S. & Ley, S. C. Mitogen-activated protein kinases in innate immunity. Nat. Rev. Immunol. 13, 679–692 (2013).

    Article  CAS  Google Scholar 

  21. Manning, B. D. & Toker, A. AKT/PKB signaling: navigating the network. Cell 169, 381–405 (2017).

    Article  CAS  Google Scholar 

  22. Spaulding, E. et al. STING-licensed macrophages prime type I IFN production by plasmacytoid dendritic cells in the bone marrow during severe Plasmodium yoelii malaria. PLoS Pathog. 12, e1005975 (2016).

    Article  Google Scholar 

  23. Zander, R. A. et al. Type I interferons induce T regulatory 1 responses and restrict humoral immunity during experimental malaria. PLoS Pathog. 12, e1005945 (2016).

    Article  Google Scholar 

  24. Haque, A. et al. Type I IFN signaling in CD8– DCs impairs Th1-dependent malaria immunity. J. Clin. Invest. 124, 2483–2496 (2014).

    Article  CAS  Google Scholar 

  25. Haque, A. et al. Type I interferons suppress CD4+ T-cell-dependent parasite control during blood-stage Plasmodium infection. Eur. J. Immunol. 41, 2688–2698 (2011).

    Article  CAS  Google Scholar 

  26. Montes de Oca, M. et al. Type I interferons regulate immune responses in humans with blood-stage Plasmodium falciparum infection. Cell Rep. 17, 399–412 (2016).

    Article  CAS  Google Scholar 

  27. Ioannidis, L. J. et al. Monocyte- and neutrophil-derived CXCL10 impairs efficient control of blood-stage malaria infection and promotes severe disease. J. Immunol. 196, 1227–1238 (2016).

    Article  CAS  Google Scholar 

  28. Griffin, J. T. et al. Gradual acquisition of immunity to severe malaria with increasing exposure. Proc. R. Soc. B 282, 20142657 (2015).

    Article  Google Scholar 

  29. Goncalves, B. P. et al. Parasite burden and severity of malaria in Tanzanian children. N. Engl. J. Med. 370, 1799–1808 (2014).

    Article  CAS  Google Scholar 

  30. Cowland, J. B. & Borregaard, N. Granulopoiesis and granules of human neutrophils. Immunol. Rev. 273, 11–28 (2016).

    Article  CAS  Google Scholar 

  31. Weksler, B. B., Jaffe, E. A., Brower, M. S. & Cole, O. F. Human leukocyte cathepsin G and elastase specifically suppress thrombin-induced prostacyclin production in human endothelial cells. Blood 74, 1627–1634 (1989).

    CAS  PubMed  Google Scholar 

  32. D’Alessandro, S., Basilico, N. & Prato, M. Effects of Plasmodium falciparum-infected erythrocytes on matrix metalloproteinase-9 regulation in human microvascular endothelial cells. Asian Pac. J. Trop. Med. 6, 195–199 (2013).

    Article  Google Scholar 

  33. Binks, R. H. & Conway, D. J. The major allelic dimorphisms in four Plasmodium falciparum merozoite proteins are not associated with alternative pathways of erythrocyte invasion. Mol. Biochem. Parasitol. 103, 123–127 (1999).

    Article  CAS  Google Scholar 

  34. Bykowska, K., Duk, M., Kusnierz-Alejska, G., Kopec, M. & Lisowska, E. Degradation of human erythrocyte surface components by human neutrophil elastase and cathepsin G: preferential digestion of glycophorins. Br. J. Haematol. 84, 736–742 (1993).

    Article  CAS  Google Scholar 

  35. Satchwell, T. J. Erythrocyte invasion receptors for Plasmodium falciparum: new and old. Transfus. Med. 26, 77–88 (2016).

    Article  CAS  Google Scholar 

  36. Crosnier, C. et al. Basigin is a receptor essential for erythrocyte invasion by Plasmodium falciparum. Nature 480, 534–537 (2011).

    Article  CAS  Google Scholar 

  37. Leffler, E. M. et al. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 356, eaam6393 (2017).

    Article  Google Scholar 

  38. Pasvol, G., Wainscoat, J. S. & Weatherall, D. J. Erythrocytes deficiency in glycophorin resist invasion by the malarial parasite Plasmodium falciparum. Nature 297, 64–66 (1982).

    Article  CAS  Google Scholar 

  39. Clark, M. A. et al. Host iron status and iron supplementation mediate susceptibility to erythrocytic stage Plasmodium falciparum. Nat. Commun. 5, 4446 (2014).

    Article  CAS  Google Scholar 

  40. Rosa, T. F. et al. The Plasmodium falciparum blood stages acquire factor H family proteins to evade destruction by human complement. Cell. Microbiol. 18, 573–590 (2016).

    Article  CAS  Google Scholar 

  41. Kennedy, A. T. et al. Recruitment of factor H as a novel complement evasion strategy for blood-stage Plasmodium falciparum infection. J. Immunol. 196, 1239–1248 (2016).

    Article  CAS  Google Scholar 

  42. Eriksson, U. K., van Bodegom, D., May, L., Boef, A. G. & Westendorp, R. G. Low C-reactive protein levels in a traditional West-African population living in a malaria endemic area. PLoS ONE 8, e70076 (2013).

    Article  CAS  Google Scholar 

  43. Gwamaka, M. et al. Iron deficiency protects against severe Plasmodium falciparum malaria and death in young children. Clin. Infect. Dis. 54, 1137–1144 (2012).

    Article  CAS  Google Scholar 

  44. Pasricha, S. R. et al. Expression of the iron hormone hepcidin distinguishes different types of anemia in African children. Sci. Transl. Med. 6, 235re233 (2014).

    Article  Google Scholar 

  45. Parente, R., Clark, S. J., Inforzato, A. & Day, A. J. Complement factor H in host defense and immune evasion. Cell. Mol. Life Sci. 74, 1605–1624 (2017).

    Article  CAS  Google Scholar 

  46. van Beek, A. E. et al. Complement factor H levels associate with Plasmodium falciparum malaria susceptibility and severity. Open Forum Infect. Dis. 5, ofy166 (2018).

    PubMed  PubMed Central  Google Scholar 

  47. Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform. 9, 559 (2008).

    Article  Google Scholar 

  48. Zhang, M. et al. Uncovering the essential genes of the human malaria parasite Plasmodium falciparum by saturation mutagenesis. Science 360, eaap7847 (2018).

  49. Lopez-Barragan, M. J. et al. Directional gene expression and antisense transcripts in sexual and asexual stages of Plasmodium falciparum. BMC Genom. 12, 587 (2011).

    Article  CAS  Google Scholar 

  50. Josling, G. A. & Llinas, M. Sexual development in Plasmodium parasites: knowing when it’s time to commit. Nat. Rev. Microbiol. 13, 573–587 (2015).

    Article  CAS  Google Scholar 

  51. Walther, M. et al. HMOX1 gene promoter alleles and high HO-1 levels are associated with severe malaria in Gambian children. PLoS Pathog. 8, e1002579 (2012).

    Article  CAS  Google Scholar 

  52. Walther, M. et al. Distinct roles for FOXP3+ and FOXP3− CD4+ T cells in regulating cellular immunity to uncomplicated and severe Plasmodium falciparum malaria. PLoS Pathog. 5, e1000364 (2009).

    Article  Google Scholar 

  53. Marsh, K. et al. Indicators of life-threatening malaria in African children. N. Engl. J. Med. 332, 1399–1404 (1995).

    Article  CAS  Google Scholar 

  54. R Core Development Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. http://www.R-project.org (2014).

  55. Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. B 73, 3–36 (2011).

    Article  Google Scholar 

  56. Dondorp, A. M. et al. Estimation of the total parasite biomass in acute falciparum malaria from plasma PfHRP2. PLoS Med. 2, e204 (2005).

    Article  Google Scholar 

  57. Adetifa, I. M. et al. Haematological values from a Gambian cohort–possible reference range for a West African population. Int. J. Lab. Hematol. 31, 615–622 (2009).

    Article  CAS  Google Scholar 

  58. Maier, A. G. & Rug, M. In vitro culturing Plasmodium falciparum erythrocytic stages. Methods Mol. Biol. 923, 3–15 (2013).

    Article  CAS  Google Scholar 

  59. Trager, W. & Jensen, J. B. Human malaria parasites in continuous culture. Science 193, 673–675 (1976).

    Article  CAS  Google Scholar 

  60. Dluzewski, A. R., Ling, I. T., Rangachari, K., Bates, P. A. & Wilson, R. J. A simple method for isolating viable mature parasites of Plasmodium falciparum from cultures. Trans. R. Soc. Trop. Med. Hyg. 78, 622–624 (1984).

    Article  CAS  Google Scholar 

  61. Ribaut, C. et al. Concentration and purification by magnetic separation of the erythrocytic stages of all human Plasmodium species. Malar. J. 7, 45 (2008).

    Article  Google Scholar 

  62. Malleret, B. et al. A rapid and robust tri-color flow cytometry assay for monitoring malaria parasite development. Sci. Rep. 1, 118 (2011).

    Article  Google Scholar 

  63. Pouw, R. B. et al. Complement factor H-related protein 3 serum levels are low compared to factor H and mainly determined by gene copy number variation in CFHR3. PLoS ONE 11, e0152164 (2016).

    Article  Google Scholar 

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Acknowledgements

We are grateful to K. Dietz for providing the original data and parameter estimates from malariatherapy patients, and his model, and to the St. Mary’s NHLI FACS core facility and Y. Guo for support and instrumentation. This work was supported by the Medical Research Council (MRC) UK via core funding to the malaria research programme at the MRC Unit, The Gambia; the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 program supported by the European Union (MR/L006529/1 to A.J.C.); a Wellcome Trust Value In People Award to A.J.C. and the European Union’s seventh Framework program under EC-GA no. 279185 (EUCLIDS; www.euclids-project.eu).

Author information

Author notes

  1. Hyun Jae Lee

    Present address: QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia

  2. Diana Wouters

    Present address: Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands

  3. Michael T. Bretscher

    Present address: F. Hoffmann-La Roche Ltd., Basel, Switzerland

  4. These authors contributed equally: Athina Georgiadou, Hyun Jae Lee.

  5. These authors jointly supervised this work: Michael T. Bretscher, Aubrey J. Cunnington.

Authors and Affiliations

  1. Section of Paediatrics, Imperial College, London, UK

    Athina Georgiadou, Fadlila Fitriani, Michael Levin & Aubrey J. Cunnington

  2. Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia

    Hyun Jae Lee & Lachlan J. Coin

  3. Medical Research Council Unit, Fajara, The Gambia at the London School of Hygiene and Tropical Medicine, Fajara, The Gambia

    Michael Walther, Davis Nwakanma & Umberto D’Alessandro

  4. Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands

    Anna E. van Beek & Diana Wouters

  5. Department of Pediatric Hematology, Immunology and Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Centre, Amsterdam, The Netherlands

    Anna E. van Beek & Taco W. Kuijpers

  6. Department of Blood Cell Research, Sanquin Research and Landsteiner Laboratory, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands

    Taco W. Kuijpers

  7. The Roslin Institute and the Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK

    Eleanor M. Riley

  8. Department of Immunology and Infection, London School of Hygiene and Tropical Medicine, London, UK

    Eleanor M. Riley

  9. Centre of Immunobiology, Institute of Infection, Immunity & Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK

    Thomas D. Otto

  10. MRC Centre for Global Infectious Disease Analysis, Imperial College, London, UK

    Azra Ghani & Michael T. Bretscher

  11. Department of Pathogen Molecular Biology, London School of Hygiene and Tropical Medicine, London, UK

    David J. Conway

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  1. Athina Georgiadou
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Contributions

A.J.C., A.G., A.E.v.B., F.F., D.J.C., D.N. and M.W. collected the data used in the study. A.J.C., E.M.R., M.T.B., M.W. and D.J.C. designed the study. A.J.C. and M.T.B. developed the mathematical model. A.J.C., M.T.B., H.J.L., F.F., T.D.O. and A.E.v.B. analysed the data. D.W., T.W.K, D.N., U.D., E.M.R., M.L., L.J.C., A.G., D.J.C. and A.J.C. supervised aspects of the project. All authors contributed to the interpretation of the results and drafting of the manuscript.

Corresponding author

Correspondence to Aubrey J. Cunnington.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–6, Supplementary Tables 1–12, Supplementary dataset legends.

Reporting Summary

Supplementary Data 1

Data from the Gambian children with malaria

Supplementary Code Example File

R example file for supplementary code for the mathematical model.

Supplementary Code Explanation File

README file explaining supplementary code.

Supplementary Code Library File

R library file with supplementary code for the mathematical model.

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Georgiadou, A., Lee, H.J., Walther, M. et al. Modelling pathogen load dynamics to elucidate mechanistic determinants of host–Plasmodium falciparum interactions. Nat Microbiol 4, 1592–1602 (2019). https://doi.org/10.1038/s41564-019-0474-x

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