Fig 1.
Richness rarefaction and Shannon index analysis of the different samples.
CK (CPV)-24(72,144)-F (M) are samples mentioned in Table 1. (a) Rarefaction curves of OTUs clustered at 97% sequence identity across difference samples. (b) Rarefaction curves of the Shannon index according to OTU. Shannon indices approached a plateau and the rarefaction curves showed it ranged from 6 to 9.
Table 1.
Bacterial community in the contents of the silkworm gut.
Table 2.
Richness and diversity index in all samples.
Fig 2.
The dominant genera percentage for all samples at each time point.
CK (CPV)-24(72,144)-F(M) are samples mentioned in Table 1. Relative read percentage of different bacterial genera within the different communities. Sequences that could not be classified into any known group were assigned as ‘Unclassified’
Fig 3.
Heatmap and sorting analysis of the different samples.
(a) Heatmap based on the hierarchical clustering solution (Bray–Curtis distance metric and complete clustering method) of the 12 samples. Rows and columns all represent the 12 samples, the similarity represented by the values in the heatmap and the heatmap of bacterial microbiota in different samples, unweighted UniFrac distance metric between samples using Unifrac was calculated to make the heatmap, the lower number represents greater similarity in bacterial microbiota between samples in the heatmap. (b) Sample sorting analysis, A PCoA plot was used to visualize the data based on β-diversity metrics of weighted UniFrac. Scatterplot of PCA-score depicting variance of fingerprints derived from different bacterial community. Principal components (PCs) 1, 2 and 3 explained 51.74%, 33.34% and 6.53% of the variance, respectively.
Fig 4.
Shared genera analysis of the different samples.
Venn diagram showing the unique and shared genera in the different samples. CK (CPV)-24(72,144)-F (M) are samples mentioned in Table 1. CK-F (M)-S was a general designation of CK-24-F (M), CK-72-F (M) and CK-144-F (M). CPV-F (M)-S was a general designation of CPV-24-F (M), CPV-72-F (M) and CPV-144-F (M). (a) for CK-24-F, CK-72-F and CK-144-F samples; (b) for CK-24-M, CK-72-M and CK-144-M samples; (c) for CPV-24-F, CPV-72-F and CPV-144-F samples; (d) for CPV-24-M, CPV-72-M and CPV-144-M samples; (e) for CK-F-S, CK-M-S, CPV-F-S and CPV-M-S samples.
Fig 5.
Phylogenetic trees of predominant genera in different samples.
The phylogenetic tree was inferred using the neighbor-joining method with MEGA6.0 and the bootstrap value was 1000 replications. Only the branch with bootstrap value >500 are shown in the tree. (a) for CK-144-F, (b) for CK-144-M, (c) for CPV-144-F, and (d) for CPV-144-M; the numbers in parentheses represented the percentage of a predominant genus. Serial numbers from 1–12 represented the Delftia, Pelomonas, Tepidimona, Ralstonia, Aspromonas, Pseudomonas, Enterococcus, Methylobacterium, Staphylococcus, Tepidimonas, Corynebacterium and Brevibacterium genera, respectively. Samples CK (CPV)-144-F (M) were mentioned in Table 1.
Fig 6.
PCA analysis of the predominant genera according to their abundance in the bacterial microbiota.
PCA analysis with linear ordination methods was used to explore the correlation between dominant genera using CANOCO 4.5 according to ter Braakand Šmilauer [13].