2.1 Overview of the metatranscriptomes
On average, 100 million raw sequence reads were obtained from the metatranscriptome of each sample; and a total of 210.09 Gbp of high-quality sequences were generated from these 16 samples after removing the adapters and quality filtering. The Q20 and Q30 base percentages of each sample were above 98.95% and 96.30%, respectively.
A total of 1,081,814 contigs were identified after de novo assembling using MEGAHIT in these 16 samples, the length of these contigs ranged from 546 to 1,004,658 bp, with an average length of 1,623.05 bp. And 712,210 unigenes were clustered with CD-HIT (http://www.bioinformatics.org/cd-hit/) (95% identity and 90% coverage). Among these 16 samples, 19,264 core species were found in the all samples, and each sample had its own unique species (Fig. 1). In general, the PEC group had the highest numbers of specific species compared to other groups. Principal co-ordinate analysis (PCoA) based on unweighted UniFrac distances showed that the colonic luminal digesta samples in the PEC group were clustered distinctly from those in other groups (Fig. 2).
2.2 Effect of different dietary fibers on colonic microbiota composition
The distribution of dominant bacteria in each group was shown in Fig. 3. In the CON group, bacteria detected in the proximal colonic luminal digesta samples belonging to 55 different phyla, and the most abundant phylum was Bacteroidetes, followed by Firmicutes and Proteobacteria, and 1,002 bacteria genera were observed in this group, Prevotella, Bacteroides and Clostridium were the three most abundant genera. The INU group contained 968 genera belonged to 57 phyla; the RPS group had 49 phyla made up of 918 genera and the PEC group contained 60 phyla and 1131 genera.
At the phylum level, the abundance of Verrucomicrobia in the RPS group was lower (fold change >2 or < 0.5; q < 0.05) than that in the CON group, and the abundance of Verrucomicrobia in the INU group was also lower (fold change >2 or < 0.5; q < 0.05) than that in the CON group, while the abundance of Fusobacteria, Actinobacteria and Cyanobacteria were greater (fold change >2 or < 0.5; q < 0.05) than those in the CON group, then the population of Proteobacteria, Spirochaetes and Verrucomicrobia phyla were greater (fold change >2 or < 0.5; q < 0.05) in the PEC group compared with those in the CON group colonic digesta samples (Additional file 1).
At the genus level, compared with the CON group, 14 genera changed significantly in the relative abundance in the RPS group, and 17 and 25 genera in the INU and PEC groups (Table 1). The abundance of Parabacteroides, Faecalibacterium, Ruminococcus and Alloprevotella increased while Sutterella decreased in the RPS group. Inulin supplement increased the abundance of Fusobacterium and Rhodococcus while decreased the abundance of Bacillus. The abundance of Streptococcus and Bacteroidetes_norank increased, while Clostridium, Clostridioides, Intestinibacter, Ruminococcaceae_norank, Gemmiger, Muribaculum, Enterococcus and Vibrio decreased in the PEC group.
2.3 Effect of different dietary fibers on the activities of colonic CAZymes
In terms of CAZyme profiles, a total of 222 CAZymes families were detected, including 7 AAs (auxiliary activities), 36 CBMs (carbohydrate-binding modules), 15 CEs (carbohydrate esterases), 94 GHs (glycoside hydrolases), 57 GTs (glycosyl transferases) and 13 PLs (polysaccharide lyases). As shown in Fig. 4, GHs were the most abundant class in all 4 groups, but the distribution of CAZymes at class level had no significant change among four groups.
Compared with the CON group at the family level, some changes were found in the dietary fiber groups (Additional file 2). 30 CAZyme families changed significantly (fold change >2 or < 0.5; q < 0.05) in the RPS group, 9 CAZymes (CBM21, CBM74, GH128, GH77, GH85, GH97, GT10, GT27, and GT3) were upregulated in the mRNA expression, while 21 CAZymes (AA7, CBM26, CBM41, GH101, GH112, GH14, GH15, GH24, GH27, GH35, GH38, GH8, GH89, GT14, GT25,GT31, GT49, GT77, GT8, GT84, and GT91) were downregulated. 14 CAZyme families were downregulated in the INU group. And 35 CAZyme families changed significantly in the PEC group, 13 CAZymes (AA12, AA3, CBM61, CBM9, CE14, GH102, GH103, GH16, GH5, GH85,GH88, GT1, and GT21) had higher abundances, while 22 CAZymes (AA1, AA2, AA6, CBM21, CBM26, CBM41, GH101, GH112, GH132, GH14, GH17, GH18, GH24,GH37, GH38, GT15, GT32, GT39, GT49, GT77, GT91, and PL4) were lower than that in the CON group. (Table 2). Among these altered CAZyme families, 4 CAZymes (AA7, GH15, GH27, and GT84) were downregulated in both INU and RPS groups; GH112 and GT91 decreased while GH85 increased in both RPS and PEC groups, and CBM21 increased in the RPS group while decreased in the PEC group. And 2 altered CAZymes (AA4 and GH26) were specific in the INU group, 14 (CBM74, GH128, GH35, GH77, GH8, GH89, GH97, GT10, GT14, GT25, GT27, GT3, GT31, and GT8) were specific in the RPS group, and 23 (AA1, AA12, AA2, AA3, AA6, CBM61, CBM9, CE14, GH102, GH103, GH132, GH16, GH17, GH18, GH37, GH5, GH88, GT1, GT15, GT21, GT32, GT39, and PL4) were specific in the PEC group.
2.4 Correlation between carbohydrate active enzymes and colonic microbiota
One of the most critical roles of the microbiota is its ability to utilize complex carbohydrate sources, the network of correlations analysis between CAZyme classes and microbiota (at the genus level) showed that Prevotella and Tannerella primarily contributed CAZyme encoding gene fragments of the GHs; GTs mainly produced by Prevotellamassilia and Prevotella; Prevotellamassilia and Roseburia primarily contributed to CBMs; Lachnotalea and Butyricimonas primarily contributed to CEs; Butyricimonas and Mediterranea primarily contributed to PLs; and AAs mainly produced by Turicibacter and Chlamydia in the growing pigs colon metatranscriptome among the significantly changed bacterial genera (Additional file 3).
Furthermore, 51 bacterial genera and 79 CAZymes families affected significantly by the dietary fiber treatment were used for the Spearman’s rank correlation analysis (Fig. 5). The production of CBM21 and GT91 were negatively correlated with the abundance of Sutterella. Parabacteroides had a negative correlation with the production of GH14, GH24, GH8, GT14, GT31, and GT77, while contributed a proportion of GT10 and GT3; Alloprevotella and Ruminococcus contributed a proportion of GH77, GH97, GT10, GT27, and GT3; and Faecalibacterium was a contributor of CBM74 and GH38. Streptococcus, Clostridioides, Intestinibacter, Vibrio, Clostridium, Gemmiger, Muribaculum and Enterococcus altered significantly specific to the PEC vs. CON group, Streptococcus had a positive correlation with the production of AA12, AA3, CBM61, GH102, GH103, GH16 and GH5; Clostridioides contributed a proportion of AA1, CBM21, and PL4, and negatively correlated with the production of AA3, CBM61, GH102, and GH103; Intestinibacter had a negative correlation with the production of AA3, CE14, and GH102; Vibrio had a negative correlation with the production of AA12, AA3, CBM61, GH102, and GH103; Clostridium was a contributor of GH18 and GT32, and negatively correlated with the production of AA3; Gemmiger contributed a proportion of GH101 and GH112, and negatively correlated with the production of AA3 and CE14; Muribaculum was a contributor of CE14 and GH37.
According to the taxonomic distribution (about top 10 genera) of predicted CAZymes identifed from the metatranscriptomes in the PEC group, Prevotella, Bacteroides, Mesorhizobium and Parabacteroides were the largest genera in the predicated AAs, GHs, GTs, CEs, PLs and CBMs, and it’s worth noting that Streptococcus was also the major microbial origin of the predicted CBMs (Fig. 6). Focus on the contributions of CAZymes from the major microbial communities in growing pigs colons in the PEC group compared to the CON group, it is noteworthy that Prevotella was the main contributor of GH5, Mesorhizobium was the main contributor of GH16, and Streptococcus was the main contributor of CBM61 in the PEC group (Fig. 7).