Mycotoxins exhibit several severe effects on intestinal health, but few studies have assessed mycotoxins effect on the intestinal microflora and its repercussions to humans and animals. In this study, we evaluated the effect of zearalenone (ZEA), one of the most harmful mycotoxins on the structure of caecal microbiota in rabbits. Twenty-eight male weaned rabbits were randomly divided into four groups and orally given different concentrations of ZEA (400, 800, and 1600
There is a complex population of microbes resides in the gastrointestinal tract, and these microbes are critical to the healthy development of the immune system and animal health [
Mycotoxins are secondary metabolites produced by fungal genera that are toxic, carcinogenic, and/or teratogenic, resulting in significant adverse effects food safety and public health [
There have been many reports about the toxic mechanism of mycotoxins. However, few studies have reported for mycotoxins with demonstration of effects on the intestine microbiota [
There are few reports about the effect of ZEA on intestinal microflora, especially on the intestinal flora of rabbit. Therefore, the effect of ZEA on the cecum microflora in rabbits is studied in this study. This study will expand a knowledge of the effects of mycotoxins on the intestinal microflora.
The 28 weaned New Zealand rabbits (aged 50 days, body mass 2.2kg ± 0.2kg) were bred in a room at a temperature ranging from 22 to 24°C and the rabbits were subjected to an atmosphere with a relative humidity of between 40 to 60%. Water and diet were provided
Rabbits were randomly distributed into four groups, and each group had seven rabbits and the rabbits in each group were in one cage. Animals within different treatment groups were treated daily by oral gavage at 14:00 for 28 days. The four groups are as follows: control group, administrated with control vehicle (DMSO); the low dose group (400
Total bacterial genomic DNA samples were extracted using the Fast DNA SPIN extraction kits (MPBiomedicals, Santa Ana, CA, USA), following the manufacturer’s instructions, and stored at -20°C prior to further analysis. The quantity and quality of extracted DNAs were measured using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and agarose gel electrophoresis, respectively.
PCR amplification of the bacterial 16S rRNA genes V3–V4 region was performed using the forward primer 338F (5’-ACTCCTACGGGAGGCAGCA-3’) and the reverse primer 806R
(5’-GGACTACHVGGGTWTCTAAT-3’). Sample-specific 7-bp barcodes were incorporated into the primers for multiplex sequencing. The PCR components contained 5
The Quantitative Insights into Microbial Ecology (QIIME, v1.8.0) pipeline was employed to process the sequencing data. Briefly, raw sequencing reads with exact matches to the barcodes were assigned to respective samples and identified as valid sequences. The low-quality sequences were filtered through following criteria: sequences that had a length of <150 bp, sequences that had average Phred scores of <20, sequences that contained ambiguous bases, and sequences that contained mononucleotide repeats of >8 bp. Paired-end reads were assembled using FLASH. After chimera detection, the remaining high-quality sequences were clustered into operational taxonomic units (OTUs) at 97% sequence identity by UCLUST (Edgar 2010). A representative sequence was selected from each OTU using default parameters. OTU taxonomic classification was conducted by BLAST searching the representative sequences set against the Greengenes Database using the best hit. An OTU table was further generated to record the abundance of each OTU in each sample and the taxonomy of these OTUs. OTUs containing less than 0.001% of total sequences across all samples were discarded. To minimize the difference of sequencing depth across samples, an averaged, rounded rarefied OTU table was generated by averaging 100 evenly resampled OTU subsets under the 90% of the minimum sequencing depth for further analysis.
Sequence data analyses were mainly performed using QIIME and R packages (v3.2.0). OTU-level alpha diversity indices, such as Chao1 richness estimator, ACE metric (Abundance-based Coverage Estimator), Shannon diversity index, and Simpson index, were calculated using the OTU table in QIIME. OTU-level ranked abundance curves were generated to compare the richness and evenness of OTUs among samples. Beta diversity analysis was performed to investigate the structural variation of microbial communities across samples using UniFrac distance metrics and visualized via principal coordinate analysis (PCoA), nonmetric multidimensional scaling (NMDS), and unweighted pair-group method with arithmetic means (UPGMA) hierarchical clustering. Differences in the Unifrac distances for pairwise comparisons among groups were determined using Student’s t-test and the Monte Carlo permutation test with 1000 permutations, and visualized through the box-and-whiskers plots. The taxonomy compositions and abundance were visualized using MEGAN and GraPhlAn. Venn diagram was generated to visualize the shared and unique OTUs among samples or groups using R package “VennDiagram,” based on the occurrence of OTUs across samples/groups regardless of their relative abundance. Taxa abundance at the phylum, class, order, family, genus, and species levels was statistically compared among samples or groups by Metastats and visualized as violin plots.
The one-way ANOVA method was used to analyze the data with SPSS 19.0 program, and Tukey’s post hoc test was evaluated for significance difference (p < 0.05; p < 0.05). Data were presented as the mean ± standard deviation.
The weights of rabbits in the high-dose and middle-dose groups were significantly lower than that in control group at the end of the four-week experiment (p < 0.01). We assessed the kidneys to confirm the reliability of our ZEA-induced rabbits model. The weights of liver and kidney and their indexes significantly decreased in the ZEA group compared with the control group (p < 0.05). Histopathological examination demonstrated that ZEA at high–doses caused lobulation and atrophy of the glomerulus in murine kidneys and multiple inflammatory cells with focal infiltration in the liver. These characteristics are consistent with the effects of high-dose zearalenone on animal performance and pathological damage.
From the cecal contents of the 28 rabbits sequencing analysis through a high-throughput sequencing on the Illumina MiSeq platform, the original sequence was obtained after the quality control of a total of 1432539 valid sequences and an average of 51162 sequences per sample. Among the high-quality sequences, about 99.94% were longer than 400 bp and most were between 420 and 460 bp (Figure
Fragment length distribution of sequences from each sample after merging and trimming.
Rarefaction curves of the OTUs number at 97% similarity box plot for every sample. Green, blue, orange, and red indicate the 7 samples of control, low dose ZEA-treated group, middle dose ZEA-treated group, and high dose ZEA-treated group, respectively.
According to the OTU classification and the results classification status identification, the specific composition and bacterial flora abundance map of each sample at the level of the phylum class, order, family, genus, and species were obtained by using QIME software.
The taxon abundance of each sample was identified into 12 phyla, 19 classes, 23 orders, 39 families, 60 genera, and 68 species in our study groups. In this study, the distributions of bacterial composition at the phylum, order, and genus levels are shown in Figures
Relative abundance of the main bacterial communities found in each samples at Flylum level (a), Order level (b), and Genus level (c). C01-C07 represents the control group; 4001-4007 represent the low dose ZEA-treated group; 8001-8007 represent the middle dose ZEA-treated group; 16001-16007 represent the high dose ZEA-treated group.
The ACE, Chao1, Shannon, and Simpson indexes can indicate microbial diversity and species richness [
Microbial diversity indices in different treatment groups.
| | | | |
---|---|---|---|---|
| 0.9799±0.0086 | 8.79±0.34 | 1911.82±78.77 | 1938.26±96.64 |
| 0.9844±0.0124 | 9.17±0.40 | 2108.41±74.1 | 2120.73±88.6 |
| 0.9825±0.0056 | 8.83±0.17 | 2358.64±258.1 | 2440.92±280.9 |
| 0.9850±0.0112 | 8.80±0.64 | 2537.89±393.0 | 2605.26±399.3 |
One-way ANOVA and Tukey’s post hoc test were employed to assess the significance of differences between the four groups. The ACE and Chao 1 indexes represent the community richness of the microbiota, and the Shannon and Simpson indexes represent the community diversity of the microbiota.
Venn diagram summarizing the numbers of common and unique OTUs (3% distance level) among the four groups. Each
A beta diversity map based on PCoA Analysis with Unweighted Unifrac Distances (Figure
The principal co-ordinates analysis (PCoA) with Unweighted Unifrac Distances of the rabbits caecum microbiota. The percentage represents contribution of principal component to the difference of samples. Each symbol represents each gut microbiota. red dot, the control group; blue dot, the low dose ZEA-treated group; yellow dot, the middle dose ZEA-treated group; green dot, the high dose ZEA-treated group. The points of different colors belong to different samples (groups). Each point represents one sample. The closer of the distance between two points means that the higher of the similarity and the smaller the difference of the microbial community structure between the two samples.
Multiple samples NMDS analysis of the rabbits caecum microbiota. Red circle, the control group; green square, the low dose ZEA-treated group; pink cross; the middle dose ZEA-treated; blue triangle, the high dose ZEA-treated group. The points of different colors belong to different samples (groups). Each point represents one sample. The closer of the distance between two points means that the higher of the similarity and the smaller the difference of the microbial community structure between the two samples.
The effect of zearalenone on the microbial community structure of caecum in rabbits by using PLS-DA (Partial Least Squares Discriminant Analysis) methods. Each point represents a sample, points of the same color belong to the same group, and points of the same group are marked with ellipses. If the samples belonging to the same grouping are closer to each other and the distance between the points of different grouping is farther, the classification model is better.
As shown in Figures
As it shown in Figure
The significant different microbiota abundance in phylum level with the increase of the concentration of ZEA. The abscissa of the figure was groups and ordinate was taxa abundance. Red, the control group; green square, the low dose ZEA-treated group; blue; the middle dose ZEA-treated; purple, the high dose ZEA-treated group;
As shown in Figure
The significant different microbiota abundance in genus level with the increase of the concentration of ZEA. The abscissa of the figure was groups and ordinate was taxa abundance. Red, the control group; green square, the low dose ZEA-treated group; blue; the middle dose ZEA-treated; purple, the high dose ZEA-treated group;
Recent researches have displayed that some mycotoxins such as AFB1, OTA, DON can modulate the intestinal bacterial community compostionin in pig or rat [
In this study, we selected the weaned rabbits, because the composition of rabbit intestinal flora tended to be stabilized [
Our results showed that the main phyla were Firmicutes, followed by Bacteroidetes in caecum bacterial communities of rabbits, in which results were in accordance with previous studies on the caecum microbiota of rabbits [
Our results found that the abundance of phyla
Our results also showed that ZEA significantly increased the abundance of phyla
The abundance of genus
Studies showed that genera and
Until now, the mechanism by which ZEA affects intestinal microflora is still unclear. However, for the first time, we studied the effect of ZEA on the caecum microflora of weaned rabbits and concluded that ZEA could significantly affect the balance of caecum microflora and reduce the abundance of some bacteria with important metabolic function. We speculate that the effects of ZEA on intestinal microflora will affect the intestine digestion function and health of the rabbits, but it needs to be further confirmed.
The data used to support the findings of this study are available from the corresponding author upon request.
The authors declare no conflicts of interest.
Peng Li and Shuhua Yang contributed equally to this study.
This work was financially supported by the National Natural Science Foundation of China (Grants nos. 31772809, 31872538, 31640084, and 31302152; 31201961) and the Key Research and Development Program of Shenyang (no. 17-165-3-00).