Impact of medical data on bacterial diversity of fractionated samples.

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Impact of medical data on bacterial diversity of fractionated samples. Impact of medical data on bacterial diversity of fractionated samples. A canonical correspondence analysis was undertaken, whereby the bacterial composition was tested to assess the fit with medical data. The analysis was performed separately for each fraction (active-F, inactive-F, IgA-pos-F, and IgA-neg-F). The numerical factors taken into account were the total dose of antibiotic treatment and the loads of toxin A and toxin B genes quantified by qPCR. The categorical medical data taken into account were the diagnosis of CDI and the type of antibiotic treatment ([i] antibiotic against CDI, [ii] antibiotics promoting CDI, and [iii] antibiotics with neutral effect on CDI onset—not associated with CDI). The bacterial species (black) and numerical variables (green boldface) with a significant influence on the ordination of samples are shown (P < 0.01). The categorical medical data (olive green boldface) are shown with asterisks corresponding to the P value (**, P < 0.01; ***, P < 0.001). The diagnosis of CDI as a categorical factor did not have a significant influence on the ordination of samples (P > 0.05); its ordination effect is shown in light gray for illustration purposes only. Samples are marked by numbers in red or blue corresponding to CDI-positive or CDI-negative patients, respectively. ud., undetermined taxon. Mária Džunková et al. mSphere 2016; doi:10.1128/mSphere.00101-16