#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Bacterial Cooperation Causes Systematic Errors in Pathogen Risk Assessment due to the Failure of the Independent Action Hypothesis


The Independent Action Hypothesis (IAH) is a basic claim in pathogen biology that underlies risk analysis for various national and international health organizations. It states that infecting pathogens act independently of one another and has proven difficult to test directly. Here we demonstrate that cooperation between infecting bacteria causes the IAH to fail in a model host-pathogen system. As a result, standard mathematical risk-assessment models, typically based on the IAH, can overestimate mortality risk at low doses. Cooperation is widespread in micro-organisms, and our results indicate that unjustified reliance on the IAH will lead to inaccurate risk assessment. Our results suggest a re-appraisal of how we assess risk from infectious agents, and for the development of mechanistic, pathogen-specific models.


Vyšlo v časopise: Bacterial Cooperation Causes Systematic Errors in Pathogen Risk Assessment due to the Failure of the Independent Action Hypothesis. PLoS Pathog 11(4): e32767. doi:10.1371/journal.ppat.1004775
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.ppat.1004775

Souhrn

The Independent Action Hypothesis (IAH) is a basic claim in pathogen biology that underlies risk analysis for various national and international health organizations. It states that infecting pathogens act independently of one another and has proven difficult to test directly. Here we demonstrate that cooperation between infecting bacteria causes the IAH to fail in a model host-pathogen system. As a result, standard mathematical risk-assessment models, typically based on the IAH, can overestimate mortality risk at low doses. Cooperation is widespread in micro-organisms, and our results indicate that unjustified reliance on the IAH will lead to inaccurate risk assessment. Our results suggest a re-appraisal of how we assess risk from infectious agents, and for the development of mechanistic, pathogen-specific models.


Zdroje

1. Zwart MP, Hemerik L, Cory JS, de Visser JAG, Bianchi FJ, et al. (2009) An experimental test of the independent action hypothesis in virus—insect pathosystems. Proceedings of the Royal Society B: Biological Sciences: rspb. 2009.0064.

2. Zwart MP, Daròs J-A, Elena SF (2011) One is enough: in vivo effective population size is dose-dependent for a plant RNA virus. PLoS pathogens 7: e1002122. doi: 10.1371/journal.ppat.1002122 21750676

3. Fazil AM (2005) A primer on risk assessment modelling: focus on seafood products: Food & Agriculture Org.

4. Cox LA (2006) Dose-Response Modeling and Risk Characterization. Quantitative Health Risk Analysis Methods: Modeling the Human Health Impacts of Antibiotics Used in Food Animals: 169–223.

5. Buchanan† RL, Havelaar AH, Smith MA, Whiting RC, Julien* E (2009) The key events dose-response framework: its potential for application to foodborne pathogenic microorganisms. Critical reviews in food science and nutrition 49: 718–728. doi: 10.1080/10408390903116764 19690997

6. Haas CN, Rose JB, Gerba CP (2014) Quantitative microbial risk assessment: John Wiley & Sons.

7. Artiola J, Pepper IL, Brusseau ML (2004) Environmental monitoring and characterization: Academic Press.

8. World Health Organization (2003) Hazard characterization for pathogens in food and water: guidelines: Food & Agriculture Org.

9. National Research Council (2005) Reopening Public Facilities After a Biological Attack: A Decision Making Framework: National Academies Press.

10. World Health Organization (2006) Guidelines for Drinking-water Quality, FIRST ADDENDUM TO THIRD EDITION.

11. Meynell G (1957) The applicability of the hypothesis of independent action to fatal infections in mice given Salmonella typhimurium by mouth. Journal of general microbiology 16: 396–404. 13416517

12. Meynell G, Stocker B (1957) Some hypotheses on the aetiology of fatal infections in partially resistant hosts and their application to mice challenged with Salmonella paratyphi-B or Salmonella typhimurium by intraperitoneal injection. Journal of general microbiology 16: 38–58. 13406218

13. Schmidt PJ, Pintar KD, Fazil AM, Topp E (2013) Harnessing the Theoretical Foundations of the Exponential and Beta-Poisson Dose-Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo. Risk Analysis 33: 1677–1693. doi: 10.1111/risa.12006 23311599

14. West SA, Griffin AS, Gardner A, Diggle SP (2006) Social evolution theory for microorganisms. Nature Reviews Microbiology 4: 597–607. 16845430

15. Druett H (1952) Bacterial invasion. Nature.

16. Rubin LG (1987) Bacterial colonization and infection resulting from multiplication of a single organism. Review of Infectious Diseases 9: 488–493. 3299635

17. Regoes RR, Hottinger JW, Sygnarski L, Ebert D (2003) The infection rate of Daphnia magna by Pasteuria ramosa conforms with the mass-action principle. Epidemiology and Infection 131: 957–966. 14596538

18. Ben-Ami F, Regoes RR, Ebert D (2008) A quantitative test of the relationship between parasite dose and infection probability across different host—parasite combinations. Proceedings of the Royal Society B: Biological Sciences 275: 853–859. doi: 10.1098/rspb.2007.1544 18198145

19. Moxon ER, Murphy PA (1978) Haemophilus influenzae bacteremia and meningitis resulting from survival of a single organism. Proceedings of the National Academy of Sciences 75: 1534–1536. 306628

20. Raymond B, Johnston PR, Nielsen-LeRoux C, Lereclus D, Crickmore N (2010) Bacillus thuringiensis: an impotent pathogen? Trends in microbiology 18: 189–194. doi: 10.1016/j.tim.2010.02.006 20338765

21. Schnepf E, Crickmore N, Van Rie J, Lereclus D, Baum J, et al. (1998) Bacillus thuringiensis and its pesticidal crystal proteins. Microbiology and molecular biology reviews 62: 775–806. 9729609

22. Raymond B, West SA, Griffin AS, Bonsall MB (2012) The dynamics of cooperative bacterial virulence in the field. Science 337: 85–88. doi: 10.1126/science.1218196 22767928

23. Li R, Jarrett P, Burges H (1987) Importance of spores, crystals, and δ-endotoxins in the pathogenicity of different varieties of Bacillus thuringiensis in Galleria mellonella and Pieris brassicae. Journal of Invertebrate Pathology 50: 277–284.

24. Slob W (1999) Thresholds in toxicology and risk assessment. International Journal of Toxicology 18: 259–268.

25. World Health Organization Inter-Organization Programme for the Sound Management of Chemicals (2009) Principles for modelling dose-response for the risk assessment of chemicals: World Health Organization.

26. Leggett HC, Cornwallis CK, West SA (2012) Mechanisms of pathogenesis, infective dose and virulence in human parasites. PLoS pathogens 8: e1002512. doi: 10.1371/journal.ppat.1002512 22359500

27. Gama JA, Abby SS, Vieira-Silva S, Dionisio F, Rocha EP (2012) Immune subversion and quorum-sensing shape the variation in infectious dose among bacterial pathogens. PLoS pathogens 8: e1002503. doi: 10.1371/journal.ppat.1002503 22319444

28. Joint FAO/WHO Expert Consultation on Risk Assessment of Microbiological Hazards in Foods: FAO headquarters, Rome, 17–21 July 2000. Rome: FAO. iv, 47 p. p.

29. Food and Agriculture Organization of the United Nations, World Health Organization (2011) Report of the Joint FAO/WHO Expert Consultation on the Risks and Benefits of Fish Consumption: Rome, 25–29 January 2010. Rome: Food and Agriculture Organization of the United Nations: World Health Organization. x, 50 p. p.

30. Rose JB, Haas CN, Gurian PL, Koopman JS (2008) Instruction Manual for Quantitative Microbial Risk Assessment (QMRA).

31. Teunis P, Havelaar A (2000) The Beta Poisson Dose-Response Model Is Not a Single-Hit Model. Risk Analysis 20: 513–520. 11051074

32. Ercolani G (1973) Two hypotheses on the aetiology of response of plants to phytopathogenic bacteria. Journal of General Microbiology 75: 83–95.

33. Grant AJ, Restif O, McKinley TJ, Sheppard M, Maskell DJ, et al. (2008) Modelling within-host spatiotemporal dynamics of invasive bacterial disease. PLoS biology 6: e74. doi: 10.1371/journal.pbio.0060074 18399718

34. van der Werf W, Hemerik L, Vlak JM, Zwart MP (2011) Heterogeneous host susceptibility enhances prevalence of mixed-genotype micro-parasite infections. PLoS computational biology 7: e1002097. doi: 10.1371/journal.pcbi.1002097 21738463

35. Höfte H, Whiteley H (1989) Insecticidal crystal proteins of Bacillus thuringiensis. Microbiological reviews 53: 242–255. 2666844

36. Raymond B, Bonsall MB (2013) Cooperation and the evolutionary ecology of bacterial virulence: The Bacillus cereus group as a novel study system. BioEssays 35: 706–716. doi: 10.1002/bies.201300028 23702950

37. Schmid-Hempel P, Frank SA (2007) Pathogenesis, virulence, and infective dose. PLoS Pathogens 3: e147.

38. Zhou L, Slamti L, Nielsen-LeRoux C, Lereclus D, Raymond B (2014) The Social Biology of Quorum Sensing in a Naturalistic Host Pathogen System. Current Biology.

39. Canter DA (2005) Addressing residual risk issues at anthrax cleanups: how clean is safe? Journal of Toxicology and Environmental Health, Part A 68: 1017–1032. 16020189

40. Coleman ME, Thran B, Morse SS, Hugh-Jones M, Massulik S (2008) Inhalation anthrax: Dose response and risk analysis. Biosecurity and bioterrorism: biodefense strategy, practice, and science 6: 147–160.

41. Regoes RR, Ebert D, Bonhoeffer S (2002) Dose—dependent infection rates of parasites produce the Allee effect in epidemiology. Proceedings of the Royal Society of London Series B: Biological Sciences 269: 271–279. 11839196

42. Cornforth DM, Sumpter DJ, Brown SP, Brännström Å (2012) Synergy and group size in microbial cooperation. The American naturalist 180: 296. doi: 10.1086/667193 22854073

43. Garbutt J, Bonsall MB, Wright DJ, Raymond B (2011) Antagonistic competition moderates virulence in Bacillus thuringiensis. Ecology letters 14: 765–772. doi: 10.1111/j.1461-0248.2011.01638.x 21635671

44. Lecadet M-M, Blondel M-O, Ribier J (1980) Generalized transduction in Bacillus thuringiensis var. berliner 1715 using bacteriophage CP-54Ber. Journal of general microbiology 121: 203–212. 7252480

45. Raymond B, Johnston PR, Wright DJ, Ellis RJ, Crickmore N, et al. (2009) A mid-gut microbiota is not required for the pathogenicity of Bacillus thuringiensis to diamondback moth larvae. Environmental microbiology 11: 2556–2563. doi: 10.1111/j.1462-2920.2009.01980.x 19555371

46. Shelton A, Cooley R, Kroening M, Wilsey W, Eigenbrode S (1991) Comparative analysis of two rearing procedures for diamond-back moth (Lepidoptera: Plutellidae). Journal of entomological science (USA).

47. Marschner IC (2011) glm2: fitting generalized linear models with convergence problems. The R journal 3: 12–15.

48. Wickham H (2009) ggplot2: elegant graphics for data analysis: Springer.

49. Bolker B (2010) bbmle: Tools for general maximum likelihood estimation. R package version 0.9.

50. Cornforth DM, Matthews A, Brown SP, Raymond B (2015) Data from: Bacterial cooperation causes systematic errors in pathogen risk assessment due to the failure of the Independent Action Hypothesis. Dryad Digital Repository. doi: 10.5061/dryad.72f4s

Štítky
Hygiena a epidemiológia Infekčné lekárstvo Laboratórium

Článok vyšiel v časopise

PLOS Pathogens


2015 Číslo 4
Najčítanejšie tento týždeň
Najčítanejšie v tomto čísle
Kurzy

Zvýšte si kvalifikáciu online z pohodlia domova

Aktuální možnosti diagnostiky a léčby litiáz
nový kurz
Autori: MUDr. Tomáš Ürge, PhD.

Všetky kurzy
Prihlásenie
Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.

Prihlásenie

Nemáte účet?  Registrujte sa

#ADS_BOTTOM_SCRIPTS#