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Blind Spots in Methods Based on Cultivation and Metagenomic Sequencing for Surface Microbiomes in a Medical Intensive Care Unit
- Jiaxian Shen, Alexander McFarland, Ryan Blaustein, Mary Hayden, Vincent Young, Erica Hartmann
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s141-s142
- Print publication:
- October 2020
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Background: Cultivation of targeted pathogens has been long recognized as a gold standard for healthcare surveillance. However, there is an emergent need to characterize all viable microorganisms in healthcare facilities to understand the role that both clinical and nonclinical microorganisms play in healthcare-associated infections. Metagenomic sequencing allows detection of entire microbial communities, in contrast to targeted identification by cultivation. Widespread application of metagenomic sequencing has been impeded in part because the sensitivity and specificity are unknown, which inhibits our ability to interpret results for risk assessment. To assess the impact of sample preparation methods on sensitivity and specificity, we compared several pretreatment steps followed by metagenomic sequencing, and we performed culture-based analyses. Methods: We collected 120 surface swabs from the medical intensive care unit at Rush University Medical Center, which we aggregated to create a representative microbiome sample. We then subjected aliquots to different processing methods (DNA extraction methods, internal standard addition, propidium monoazide (PMA) treatment, and whole-cell serial filtration). We evaluated the effects of these methods based on DNA yields and metagenomic sequencing outcomes. We also compared the metagenomic results to the microbial identifications obtained by cultivation using environmental microbiology methods and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Results: Our results demonstrate that bead-beating and heat lysis followed by liquid-liquid extraction is the optimal method for the identification of low-biomass surface-associated microbes, as opposed to widely used column-based and magnetic bead-based methods. For low-biomass surface-associated samples, ~590,000 reads per sample are sufficient for ≍90% coverage in metagenomic sequencing (Fig. 1). The ZymoBIOMICS microbial community standard is not appropriate for methods assessing membrane integrity. For the identification of putatively viable microorganisms, PMA treatment is promising, although elimination of signals from nonviable organisms will reduce the overall detectable signal. Combining PMA-treated metagenomic sequencing with cultivation yields the most comprehensive results, particularly for low-abundance taxa, despite high sequencing coverage (Fig. 2). To distribute more detection resources to bacteria, our target domain, we tried whole-cell filtration prior to extraction, attempting to isolate bacterial cells from eukaryotic cells and other particles. For low-biomass surface-associated samples, the sample loss and the difficulties in performing filtration outweigh the slight increase of bacterial signal. Conclusions: Despite optimization, we observed certain blind spots in both cultivation and metagenomic sequencing. This information is essential for informed risk assessment. Further research is needed to identify additional limitations to ensure that results from metagenomic sequencing can be interpreted in the context of healthcare-acquired infection prevention.
Funding: This work was supported by the Centers for Disease Control and Prevention (BAA FY2018-OADS-01 Contract 02915).
Disclosures: None
3449 Bacterial biotransformation of chemotherapeutics may promote diversity among the intestinal microbiota
- Ryan Andrew Blaustein, Patrick Casey Seed, Erica Marie Hartmann
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- Journal:
- Journal of Clinical and Translational Science / Volume 3 / Issue s1 / March 2019
- Published online by Cambridge University Press:
- 26 March 2019, p. 3
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OBJECTIVES/SPECIFIC AIMS: This study aims to test the hypothesis that bacterial biotransformation of chemotherapeutics promotes gut microbial diversity by enhancing persistence of drug-sensitive taxa. METHODS/STUDY POPULATION: The impacts of doxorubicin on a model community of gut bacteria was investigated in vitro in anaerobic batch culture. The synthetic community was composed of specific members predicted by genomic analysis to be sensitive to the therapeutic (i.e., Clostridium innocuum, Lactobacillus sp.), resistant via putative biotransformation (i.e., Escherichia coli, Klebsiella pneumoniae), or resistant via putative efflux (i.e., Enterococcus faecalis). Bacterial growth was monitored in monocultures by measuring OD600 and standard plate counts, and in mixed cultures by strain-targeted qPCR. Doxorubicin concentration was detected via absorbance assay. RESULTS/ANTICIPATED RESULTS: Strains with predicted resistance to doxorubicin by drug biotransformation significantly lowered concentrations of the drug in culture media. In contrast, E. faecalis proved resistant without evidence of drug transformation. Predicted sensitive strains were growth-repressed by the doxorubicin, but able to grow in spent media where biotransformation had occurred. However, they remained growth-repressed in spent media from E. faecalis where drug transformation had not been observed. Bacterial growth kinetics in mixed batch culture were dependent on starting bacterial concentrations and timing of drug exposure. DISCUSSION/SIGNIFICANCE OF IMPACT: This work will be extended to model microbial community responses to doxorubicin as a factor of microbial interactions and extent of drug transformation prior its exposure to sensitive strains. The resulting model will have translational implications for mitigating health risks during pediatric cancer treatment.