Fecal metabolomics by LC/MS
In brief, the fecal samples were weighed for 100 mg and collected in 2 mL centrifuge tubes and added 600 μL 2-chlorophenylalanine (4 ppm) methanol (-20 °C), and then vortexed for 30 seconds. Subsequently, the mixture was sonicated at room temperature for 10 min and centrifuged at 14000 rpm at 4 °C for 10 min. The supernatant was filtered through 0.22 μm membrane to obtain the prepared samples for LC-MS.
The acquired MS data pretreatments including peak picking, peak grouping, retention time correction, second peak grouping, and annotation of isotopes and adducts was performed using XCMS software. LC−MS raw data fifiles were converted into mzXML format and then processed by the XCMS, CAMERA and metaX toolbox implemented with the R software. Each ion was identified by combining retention time (RT) and m/z data. Intensities of each peaks were recorded and a three dimensional matrix containing arbitrarily assigned peak indices (retention time-m/z pairs), sample names (observations) and ion intensity information (variables) was generated. The intensity of peak data was further preprocessed by metaX. Those features that were detected in less than 50 % of QC samples or 80 % of biological samples were removed, the remaining peaks with missing values were imputed with the k-nearest neighbor algorithm to further improve the data quality. PCA was performed for outlier detection and batch effects evaluation using the pre-processed dataset. Quality control-based robust LOESS signal correction was fitted to the QC data with respect to the order of injection to minimize signal intensity drift over time. In addition, the relative standard deviations of the metabolic features were calculated across all QC samples, and those > 30% were then removed. Student t-tests were conducted to detect differences in metabolite concentrations between 2 phenotypes. Supervised PLS-DA was conducted through metaX to discriminate the different variables between groups. The VIP value was calculated. A VIP cut-off value of 1.0 was used to select important features.
Statisticalanalysis
The analyses of chicken colibacillosis characteristics were performed using the Social Sciences (SPSS) version 19.0 (SPSS Inc., 2010 Chicago, IL, USA) and carried out in one-way analysis of variance (ANOVA) by Tukey-Kramer multiple comparison. The data were expressed as the means ± S.D. P < 0.05 was considered statistically significant.