Shengjiang Xiexin Decoction in the treatment of Clostridium difficile infection Related pharmacodynamic, microbiomics, and metabolomics datasets

Published: 22 March 2023| Version 1 | DOI: 10.17632/c9ng6sp4s5.1
Yutao Cui


We hypothesized that the ameliorative effect of SXD on CDI is related to the modulation of gut microbiota composition and metabolism by SXD. In the present study, we first investigated the effect of SXD on CDI mice. Then, we used 16s rDNA gene sequencing, non-targeted metabolomics, and serum pharmacochemistry to detect intestinal flora, metabolism, and blood prototype drug profiles in mice.


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Fecal 16S DNA sequencing analysis On the last day of the experiment, the mice in each group were sacrificed and the faeces were collected aseptically from the colonic area of each group in lyophilized tubes, quenched in a tank of liquid nitrogen for 30 min, and then transferred to a -80°C refrigerator for storage. Total DNA was extracted from the feces samples and the concentration and purity of DNA were measured by ultra-micro spectrophotometer and the quality of DNA extraction was measured by 1% agarose gel electrophoresis. polymerase chain reaction (PCR) amplification of the V3-V4 variable region was performed with 338F and 806R primers. The amplification procedure was: pre-denaturation at 95°C for 3 min, 27 cycles (denaturation at 95°C for 30 s, annealing at 55°C for 30 s, extension at 72°C for 30 s), and a final extension at 72°C for 10 min. The amplification system was 20ul, 4uL 5×FastPfu buffer, 2uL 2.5mM dNTPs, 0.8uL primer (5uM), 0.4uL FastPfu polymerase; 10ng DNA template. Purified amplification products were mixed and paired for sequencing on the Illumina MiSeq platform (Illumina, USA) according to standard operating protocols. The analysis was performed according to the "moving picture tutorial" and "Atacama soil microbiome tutorial" of Qiime2docs and specific program scripts. The Amplicon Sequence Variant (ASV) tables were generated by Qiime2's DADA2 plugin, which performs double-ended read splicing, quality filtering, and chimeric variant filtering. The classification of each ASV representative sequence was annotated by the Sklearn classifier algorithm against the Greengenes database version 13_8 (99% OTU dataset). UPLC-MS profiling of serum and SXD extract solution Ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze metabolites from serum and drug samples with identical chromatographic and mass spectrometric conditions. ACQUITY HSS T3 (Waters, USA) and ACQUITY UPLC HSS T3 columns (2.1 x 100 mm, 1.8 μm) (Waters, USA) were used for chromatographic separation. The column temperature was set at 35°C. A mass spectrometer detector Q-Exactive (Thermo Fisher Scientific, USA) was used for metabolite detection. 5 μl of sample solution was used for metabolite detection. The mobile phase was a mixture of solvent A (H2O, containing 0.1% formic acid) and solvent B (CH3CN). Linear gradient elution was used. The mass spectrometry conditions were set as follows: spray voltage of 3.5/-3.2 kV; 40/45 Sheath gas; 11/10 AUX gas flow; the capillary temperature of 350 °C. The mass charge ratio (M/Z) scan range was collected from 70 DA to 1000 DA in both positive and negative modes. Combined QC samples are analyzed every 10 runs when analyzing serum samples to ensure the stability and reproducibility of the operating system.


Capital Medical University Affiliated Beijing Friendship Hospital


Metabolism, Gut Microbiota