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Incubations at low pH significantly modified community structure, increasing the relative abundance of Clostridiales (56.4% �� 1.2% [pH 4]), relative to the control (37.2 �� 10.0 [pH 7]; p?ERK inhibitor Clostridiales in the active and damaged subset, in addition to a higher level of Bacteroidales and Bifidobacteriales in the less active fraction (Figure?5B). Furthermore, LefSe analysis revealed that low pH and ampicillin exposure resulted in significant changes to the active and damaged gut microbiota (Table S4D), namely an increased relative abundance of members of the Bacteroidetes phylum. Digoxin also led to a significantly higher relative abundance of the Faecalibacterium genus (Firmicutes phylum) in the Pi+ subset (15.0% �� 0.9% after digoxin treatment versus 10.5% �� 1.2% in controls; Table S4D). Together, these results emphasize that, despite shared features of the active and damaged gut microbiota between healthy individuals, it can be rapidly altered following exposure to xenobiotics. In order to more comprehensively characterize the influence of xenobiotics on the active gut microbiome, we tested for changes in community-wide Cisplatin gene expression following xenobiotics exposure. RNA-seq profiles were obtained after the same 4?hr incubations with host-targeted drugs, antibiotics, vehicle controls, and low pH used for the analysis of microbial physiology and community structure (Figures S1C and S1D and Table S1B; 565 �� 142 thousand mRNA sequencing reads/sample). To obtain a high-level view of the transcriptional response to xenobiotics, we tallied the number of normalized counts assigned to each KEGG metabolic pathway and higher-level category. In general, the treatment and control samples shared a Onalespib order similar distribution of pathways (Figure?S6A; note, all correlations were >0.9) and categories (Figure?6A). Transcriptional profiles were most similar when from the same individual and the same time point. However, clear deviations from this pattern occurred after exposure to tetracycline and macrolide antibiotics that inhibit translation (Figure?6B). All three treatments resulted in an increased expression of genetic information processing genes (e.g., transcription and translation; 24.8% �� 0.4% versus 32.8% �� 0.7% of assignments in controls compared to treatments, p?