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Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections
A number of human infections are characterized by the presence of more than one bacterial species and are defined as polymicrobial diseases. Methods for the analysis of the complex biological interactions in mixed infections with a large number of microorganisms are limited and do not effectively de...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2566602/ https://www.ncbi.nlm.nih.gov/pubmed/18949036 http://dx.doi.org/10.1371/journal.ppat.1000184 |
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author | Sibley, Christopher D. Duan, Kangmin Fischer, Carrie Parkins, Michael D. Storey, Douglas G. Rabin, Harvey R. Surette, Michael G. |
author_facet | Sibley, Christopher D. Duan, Kangmin Fischer, Carrie Parkins, Michael D. Storey, Douglas G. Rabin, Harvey R. Surette, Michael G. |
author_sort | Sibley, Christopher D. |
collection | PubMed |
description | A number of human infections are characterized by the presence of more than one bacterial species and are defined as polymicrobial diseases. Methods for the analysis of the complex biological interactions in mixed infections with a large number of microorganisms are limited and do not effectively determine the contribution of each bacterial species to the pathogenesis of the polymicrobial community. We have developed a novel Drosophila melanogaster infection model to study microbe–microbe interactions and polymicrobe–host interactions. Using this infection model, we examined the interaction of 40 oropharyngeal isolates with Pseudomonas aeruginosa. We observe three classes of microorganisms, one of which acts synergistically with the principal pathogen, while being avirulent or even beneficial on its own. This synergy involves microbe–microbe interactions that result in the modulation of P. aeruginosa virulence factor gene expression within infected Drosophila. The host innate immune response to these natural-route polymicrobial infections is complex and characterized by additive, suppressive, and synergistic transcriptional activation of antimicrobial peptide genes. The polymicrobial infection model was used to differentiate the bacterial flora in cystic fibrosis (CF) sputum, revealing that a large proportion of the organisms in CF airways has the ability to influence the outcome of an infection when in combination with the principal CF pathogen P. aeruginosa. |
format | Text |
id | pubmed-2566602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25666022008-10-24 Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections Sibley, Christopher D. Duan, Kangmin Fischer, Carrie Parkins, Michael D. Storey, Douglas G. Rabin, Harvey R. Surette, Michael G. PLoS Pathog Research Article A number of human infections are characterized by the presence of more than one bacterial species and are defined as polymicrobial diseases. Methods for the analysis of the complex biological interactions in mixed infections with a large number of microorganisms are limited and do not effectively determine the contribution of each bacterial species to the pathogenesis of the polymicrobial community. We have developed a novel Drosophila melanogaster infection model to study microbe–microbe interactions and polymicrobe–host interactions. Using this infection model, we examined the interaction of 40 oropharyngeal isolates with Pseudomonas aeruginosa. We observe three classes of microorganisms, one of which acts synergistically with the principal pathogen, while being avirulent or even beneficial on its own. This synergy involves microbe–microbe interactions that result in the modulation of P. aeruginosa virulence factor gene expression within infected Drosophila. The host innate immune response to these natural-route polymicrobial infections is complex and characterized by additive, suppressive, and synergistic transcriptional activation of antimicrobial peptide genes. The polymicrobial infection model was used to differentiate the bacterial flora in cystic fibrosis (CF) sputum, revealing that a large proportion of the organisms in CF airways has the ability to influence the outcome of an infection when in combination with the principal CF pathogen P. aeruginosa. Public Library of Science 2008-10-24 /pmc/articles/PMC2566602/ /pubmed/18949036 http://dx.doi.org/10.1371/journal.ppat.1000184 Text en Sibley et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Sibley, Christopher D. Duan, Kangmin Fischer, Carrie Parkins, Michael D. Storey, Douglas G. Rabin, Harvey R. Surette, Michael G. Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title | Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title_full | Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title_fullStr | Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title_full_unstemmed | Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title_short | Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections |
title_sort | discerning the complexity of community interactions using a drosophila model of polymicrobial infections |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2566602/ https://www.ncbi.nlm.nih.gov/pubmed/18949036 http://dx.doi.org/10.1371/journal.ppat.1000184 |
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