Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/60794
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dc.contributor.authorHenken, S.-
dc.contributor.authorBohling, J.-
dc.contributor.authorOgunniyi, A.-
dc.contributor.authorPaton, J.-
dc.contributor.authorSalisbury, V.-
dc.contributor.authorWelte, T.-
dc.contributor.authorMaus, U.-
dc.date.issued2010-
dc.identifier.citationAntimicrobial Agents and Chemotherapy, 2010; 54(8):3155-3160-
dc.identifier.issn0066-4804-
dc.identifier.issn1098-6596-
dc.identifier.urihttp://hdl.handle.net/2440/60794-
dc.description.abstractBioluminescence imaging is an innovative, noninvasive tool to analyze infectious disease progression under real-life conditions in small laboratory animals. However, the relevance of bioluminescence imaging to monitor invasive compared to noninvasive bacterial infections of the lung has not been examined so far. In the current study, we systematically evaluated the importance of bioluminescence imaging to monitor pneumococcal disease progression by correlating biophotonic signals with lung bacterial loads in two mouse strains (BALB/c, C57BL/6) infected with either self-glowing, bioluminescent serotype 19 Streptococcus pneumoniae causing focal pneumonia or serotype 2 S. pneumoniae causing invasive pneumococcal disease. The best correlations between bioluminescence signals and lung CFU counts were observed in BALB/c mice compared to C57BL/6 mice just on day 3 after infection with invasive serotype 2 S. pneumoniae, while excellent correlations between photon counts and bacterial loads were observed in isolated lungs of BALB/c and C57BL/6 mice, irrespective of the employed pneumococcal serotype. Moreover, good correlations between biophotonic signals and CFU counts were also observed in mice upon infection with serotype 19 S. pneumoniae causing focal pneumonia in mice, again with best correlation values obtained for BALB/c mice at day 3 postinfection. Collectively, we show that the relevance of biophotonic imaging to monitor S. pneumoniae-induced lung infections in mice is largely influenced by the disease model under investigation. The provided data may be important for studies of infectious diseases.-
dc.description.statementofresponsibilityStefanie Henken, Jennifer Bohling, A. David Ogunniyi, James C. Paton, Vyvyan C. Salisbury, Tobias Welte, and Ulrich A. Maus-
dc.language.isoen-
dc.publisherAmer Soc Microbiology-
dc.rightsCopyright © 2010, American Society for Microbiology. All Rights Reserved.-
dc.source.urihttp://dx.doi.org/10.1128/aac.00310-10-
dc.subjectLung-
dc.subjectAnimals-
dc.subjectMice, Inbred BALB C-
dc.subjectMice, Inbred C57BL-
dc.subjectHumans-
dc.subjectMice-
dc.subjectStreptococcus pneumoniae-
dc.subjectPneumonia, Pneumococcal-
dc.subjectDisease Models, Animal-
dc.subjectDiagnostic Imaging-
dc.subjectLuminescent Measurements-
dc.subjectSerotyping-
dc.subjectColony Count, Microbial-
dc.subjectVirulence-
dc.subjectPhotons-
dc.subjectImage Processing, Computer-Assisted-
dc.subjectFemale-
dc.titleEvaluation of biophotonic imaging to estimate bacterial burden in mice infected with highly virulent compared to less virulent Streptococcus pneumoniae serotypes-
dc.typeJournal article-
dc.identifier.doi10.1128/AAC.00310-10-
pubs.publication-statusPublished-
dc.identifier.orcidOgunniyi, A. [0000-0001-9308-5629]-
dc.identifier.orcidPaton, J. [0000-0001-9807-5278]-
Appears in Collections:Aurora harvest 5
Molecular and Biomedical Science publications

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