Bacterial summary taxonomic composition
We analyzed buccal swab samples from 105 participants for taxonomic composition, differential abundance and functional profiling of their oral microbiota. The subjects’ characteristics in this study such as age, gender, body mass index (BMI), ethnicity, and medical history among others have been provided (Table 1).
Characteristics
|
Smokers
|
Non-smokers
|
p-value
|
(n =55)
|
(n =50)
|
Age, years
|
30.40 (9.508, 41)
|
30.30 (11.196, 39)
|
0.961 a
|
Mean (SD, range)
|
Gender (M%, F %)
|
92.7%, 7.3%
|
90.0%, 10.0%
|
0.618 b
|
Ethnicity (%)
|
|
|
|
MENA
|
78.20%
|
76.00%
|
0.798 b
|
Asians
|
20.00%
|
20.00%
|
Africans
|
1.80%
|
4.00%
|
BMI (Kg/m2)
Mean (SD, range)
|
24.97 (4.65, 16.55)
|
24.92 (3.33, 14.45)
|
0.948 a
|
Prescribed probiotics use (yes %)
|
0.00%
|
0.00%
|
-
|
Exercise (yes %)
|
61.10%
|
72.00%
|
0.24 b
|
Animal exposure (yes %)
|
14.50%
|
20.00%
|
0.459 b
|
Antibiotics use (past 3 months) (yes %)
|
0%
|
0.00%
|
-
|
Family History
|
|
|
|
Cancer
|
12.70%
|
6.00%
|
0.241 b
|
HTN
|
41.80%
|
30.00%
|
0.208 b
|
Diabetes
|
50.90%
|
30.00%
|
0.03 b
|
Asthma
|
5.50%
|
2.00%
|
0.356 b
|
Household Smoker (yes %)
|
61.80%
|
30.00%
|
0.001 b
|
Family Smoker (yes %)
|
65.50%
|
36.00%
|
0.003 b
|
Smoking Duration
Mean (SD, range)
|
11.80 (8.065, 38)
|
|
|
FTND
|
4.82 (2.427, 9)
|
|
|
Mean (SD, range)
|
Low dependence
|
18.2%
|
|
|
Low to moderate dependence
|
32.7%
|
|
|
Moderate dependence
|
32.7%
|
|
|
High dependence
|
16.4%
|
|
|
a : Independent t-test, b : Chi-squared test
|
Table 1
Demographics of Study Cohort
First, we evaluated the taxonomic composition generated from high-quality reads and classified them using the MiniKraken2_v1 database [23] as the reference database for bacteria. We aggregated taxa abundances into genera and plotted the relative abundances of the most abundant ones (Fig. S1). Furthermore, we plotted the relative abundances of the most abundant taxa within the smokers’ group based on their FTND score (nicotine dependence); 1 − 2 (low dependence), 3 − 4 (low to moderate dependence), 5 – 7 (moderate dependence), and ≥ 8 (high dependence) (Fig. S2). Nicotine dependence was further evaluated using the Short Nicotine Dependence Syndrome Scale (NDSS-S) [18, 19]. Pearson correlation suggested a significant positive correlation between FTND and NDDS-S for smokers (r=0.646) (p-value<0.01) (Data not shown). Next, we estimated alpha diversity (richness and evenness) from taxonomic profiles using Shannon’s diversity index and Chao1 richness estimator. No significant differences across different groups were found (Fig. S3). Last, to assess the overall microbial community compositional changes, PERMANOVA was used to model effects of smoking and smoking dependence on oral microbiota composition. We observed a significant taxonomy difference between smoker and non-smoker groups (p-value <0.04) and a non-significant difference based on FTND dependence among smoker group (p-value <0.09).
Bacterial differential abundance based on smoking and smoking dependence levels.
In order to further assess possible compositional differences in the bacterial community as suggested in figure S1, we conducted negative binomial models (DESEq2 R package) of the form ∼group ∼dependence and ran for differential abundance testing of taxonomic and subsystem level 3 features. P values were calculated with Likelihood Ratio Tests. First, the comparison of average relative abundance between smokers and non-smokers groups revealed that profiles obtained from smokers have a statistically significant abundance of Veillonella dispar (Log2FoldChange 2.327, P. adjusted value < 0.0000003), Leptotrichia sp000469385 (Log2FoldChange 1.913, P. adjusted value < 0.0013), and Prevotella pleuritidis (Log2FoldChange 1.896, P. adjusted value < 0.00019) among others. Whereas, we noted a statistically significant under-representation of Haemophilus_A (Log2FoldChange -2.33, P. adjusted value < 0.00007), Gemella cuniculi (Log2FoldChange -1.976, P. adjusted value < 0.00019), Neisseria subflava_B (Log2FoldChange -1.87, P. adjusted value < 0.00006), Gemella haemolysans_B (Log2FoldChange -1.75, P. adjusted value < 0.00085), Neisseria perflava (Log2FoldChange -1.73, P. adjusted value < 0.0012), Streptococcus oralis_BA (Log2FoldChange -1.56, P. adjusted value < 0.0004), and Streptococcus mitis_AT (Log2FoldChange -1.39, P. adjusted value < 0.0013) among others in smokers (Fig. 1). Next, we evaluated average relative abundance among smokers based on nicotine dependence (Fagerström score) and showed that profiles obtained from high nicotine dependence smokers have a statistically significant abundance of Streptobacillus hongkongensis (Log2FoldChange 4.78, P. adjusted value < 0.00004), Fusobacterium massiliense (Log2FoldChange 4.63, P. adjusted value < 0.00000004), Prevotella sp000163055 (Log2FoldChange 4.42, P. adjusted value < 0.00008), and Prevotella bivia (Log2FoldChange 2.46, P. adjusted value < 0.00024) among others (Fig. 2).
Functional profiling of oral microbiota in smoker vs. non-smokers
We used shotgun metagenomic sequencing to determine functional contribution of the oral microbiota in smokers vs. non-smokers using the SEED hierarchical categorization. Functional profiling showed significant enrichment of Tricarballylate utilization (Log2FoldChange 2.52, P. adjusted value < 0.0013), Aminoglycoside adenylyltransferases (Log2FoldChange 2.39, P. adjusted value < 0.002), Bacteriocins in Lactobacilli (Log2FoldChange 2.29, P. adjusted value < 0.0012), Lactate racemization (Log2FoldChange 1.003, P. adjusted value < 0.0001), and Methionine salvage (Log2FoldChange 0.7, P. adjusted value < 0.0004) among others in smokers. Whereas, we noted a significant depletion of Two-component Response Regulator of Virulence ResDE (Log2FoldChange -1.28, P. adjusted value < 0.0009), Listeria Pathogenicity Island LIPI-1 extended (Log2FoldChange -0.888, P. adjusted value < 0.00006), and CarD (Log2FoldChange -0.139, P. adjusted value < 0.0007) among others in smokers (Fig. 3).
Functional profiling of oral microbiota based on nicotine dependence severity
Finally, we examined differentially abundant gene functions based on Fagerström score for nicotine dependence among smokers. Pairwise functional differences determined significant difference between low and high nicotine dependence groups (p-value < 0.02, p-value FDR<0.05). For example, we show enrichment of Xanthosine utilization (xap region) (Log2FoldChange 3.38, P. adjusted value < 0.00007), p-Aminobenzoyl-Glutamate utilization (Log2FoldChange 1.33, P. adjusted value < 0.00056), Multidrug efflux pump in Campylobacter jejuni (CmeABC operon) (Log2FoldChange 1.14, P. adjusted value < 0.00007), Glycine biosynthesis (Log2FoldChange 1.02, P. adjusted value < 0.00062), Isoleucine degradation (Log2FoldChange 0.989, P. adjusted value < 0.00021) among others. We also noted depletion of Type VI secretion systems (Log2FoldChange -1.99, P. adjusted value < 0.00027), Rrf2 family transcriptional regulators (Log2FoldChange -0.598, P. adjusted value < 0.00067), and ABC transporter oligopeptide (TC 3.A.1.5.1) (Log2FoldChange -0.351, P. adjusted value < 0.00001) among others in the high nicotine dependence group (Fig. 4).