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.