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2011. Identification of Streptococcus agalactiae on Human Fetal Membrane Tissues Using Raman Microspectroscopy

BACKGROUND: Streptococcus agalactiae, also known as Group B Streptococcus (GBS), colonizes 10–40% of women during late pregnancy and is an important cause of chorioamnionitis, or infection of the fetal membranes, and neonatal sepsis. The CDC recommends third trimester rectovaginal GBS screening, and...

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Detalles Bibliográficos
Autores principales: Doster, Ryan, Ayala, Oscar, Manning, Shannon, Aronoff, David, Mahadevan-Jansen, Anita, Gaddy, Jennifer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6254601/
http://dx.doi.org/10.1093/ofid/ofy210.1667
Descripción
Sumario:BACKGROUND: Streptococcus agalactiae, also known as Group B Streptococcus (GBS), colonizes 10–40% of women during late pregnancy and is an important cause of chorioamnionitis, or infection of the fetal membranes, and neonatal sepsis. The CDC recommends third trimester rectovaginal GBS screening, and intrapartum antibiotic prophylaxis for those testing positive. A rapid GBS diagnostic test could provide opportunities to identify GBS colonized women at the time of labor and focus the use of antibiotic therapy. Raman spectroscopy (RS) is an inelastic light scattering technique that provides biochemical spectra and has been used in vitro to characterize bacteria at the genus and species level. This study evaluated RS to identify and differentiate GBS, Escherichia coli, and Staphylococcus aureus ex vivo infection of human fetal membrane tissues. METHODS: Bacterial colonies of GBS, S. aureus, and E. coli were cultured on Mueller–Hinton agar. In addition, de-identified human fetal membrane tissues (VUMC IRB Approval #131607) were isolated and infected with 10(6) bacterial cells per 12 mm tissue punch for 48–72 hours. Samples from both were characterized using a Raman microscope. Hierarchical cluster analysis was implemented to evaluate principal component scores of Raman spectra from bacterial colonies. For tissue spectra, a machine learning algorithm, sparse multinomial logistic regression (SMLR), was used to determine the ability to discriminate across tissues types and identify biochemical features important for classification. Following RS analysis, scanning electron microscopy was performed to verify the presence of bacterial cells at the site of Raman measurements. RESULTS: Unique spectral features were identified from colonies grown on agar and infected fetal membrane tissues. Analysis using SMLR accurately identified GBS-infected tissues with 92.2% sensitivity and specificity. Scanning electron microscopy evaluation confirmed the presence of bacterial cells that were structured in biofilms at the site of Raman measurements. CONCLUSION: Together, these findings support further investigation into the use of RS as an emerging microbiologic diagnostic tool and intrapartum screening test for GBS carriage. [Image: see text] [Image: see text] DISCLOSURES: All authors: No reported disclosures.