Amplicon sequence variants estimation, taxonomic classification, and statistical analysis

The pre-processed paired-end sequences were used for further downstream analysis using various bioinformatic tools. First, the pre-processed reads were analyzed using Quantitative Insights into Microbial Ecology version 2 (QIIME2). Amplicon sequence variants (ASVs) generated using QIIME2 were used for functional interpretation of the microbiota (Bolyen et al., 2019).

To visualize the abundance of taxonomy, sample-wise stacked bar plots were constructed at phylum, family, and genus levels using the ggplot2 (3.2.1) R package. The results were further analyzed with the phyloseq (1.28.0) R package to study the alpha and beta diversity of the samples. Alpha diversity was calculated using the estimate_richness R function and visualized using the ggplot2 R package. Beta diversity was estimated using the ordinate R function and visualized using the plot_ordination R function. The clustering of the samples was presented with a non-metric multidimensional scaling (NMDS) plot based on Bray–Curtis distance. Rarefaction analyses were conducted using the rarefy (Vegan v2.6-2) R function. Permutational multivariate analysis of variance (PERMANOVA) was performed to test for significant differences between the two groups at the genus taxonomic level using the vegan (version 2.4-3) R package. The analysis compared the groups and provided the top organisms that were responsible for their differentiation (Anderson, 2017). Statistical tests were performed between NMDS1 and NMDS2 to obtain the significant coordinate, and Welch’s t-test (two) was used to calculate the p-values. Correlation between microbial taxa and periodontal clinical parameters was assessed by the Spearman rank correlation coefficient (significance level p < 0.05) using the psych v2.2.3 R package. The graphical representation of the results was done using GraphPad Prism v8.4.2, where red indicates a positive correlation and blue indicates a negative correlation.