The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections
Open accessAbstract
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.
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Shaner, N. C., Campbell, R. E., Steinbach, P. A., Giepmans, B. N. G., Palmer, A. E., & Tsien, R. Y. (2004) · Nature Biotechnology · doi:10.1038/nbt1037 · Cited by 4,619
Pukatzki, S., Kessin, R. H., & Mekalanos, J. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.052704399 · Cited by 289
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Dickson, R. P., Martinez, F. J., & Huffnagle, G. B. (2014) · The Lancet · doi:10.1016/s0140-6736(14)61136-3 · Cited by 495
Quorum sensing and social networking in the microbial world
Atkinson, S., & Williams, P. (2009) · Journal of The Royal Society Interface · doi:10.1098/rsif.2009.0203 · Cited by 422
Fodor, A. A., Klem, E. R., Gilpin, D. F., Elborn, J. S., Boucher, R. C., Tunney, M. M., & Wolfgang, M. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0045001 · Cited by 353
Delhaes, L., Monchy, S., Fréalle, E., Hubans, C., Salleron, J., Leroy, S., Prevotat, A., Wallet, F., Wallaert, B., Dei-Cas, E., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036313 · Cited by 347
Metadata
- Authors
- Sibley, C. D., Duan, K., Fischer, C., Parkins, M. D., Storey, D. G., Rabin, H. R., & Surette, M. G.
- Venue
- PLoS Pathogens
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-10-24
- Volume
- 4
- Issue
- 10
- Pages
- e1000184
- ISSN
- 1553-7366 (ISSN-L)
- 1553-7374
- OpenAlex
- W1974679977
- Cited by
- 261
- References
- 2
- FWCI
- 5.34
- Type
- journal article
- Language
- en
- Open access
- gold
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- Sibley, C. D., Duan, K., Fischer, C., Parkins, M. D., Storey, D. G., Rabin, H. R., & Surette, M. G. (2008). Discerning the Complexity of Community Interactions Using a Drosophila Model of Polymicrobial Infections. PLoS Pathogens. https://doi.org/10.1371/journal.ppat.1000184
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