Front. Oral. Health Frontiers in Oral Health Front. Oral. Health 2673-4842 Frontiers Media S.A. 10.3389/froh.2024.1310334 Oral Health Systematic Review Effect of different forms of tobacco on the oral microbiome in healthy adults: a systematic review SenaratneNikitha Lalindri Mareena 1 2 Yung onCheng 3 ShettyNaresh Yedthare 4 5 GopinathDivya 5 6 * † School of Medicine, International Medical University, Kuala Lumpur, Malaysia Faculty of Medicine and Health, UNSW, Sydney, NSW, Australia Sungai Rengit Dental Clinic, Johor Health Department, Ministry of Health Malaysia, Kota Tinggi, Malaysia Clinical Sciences Department, Ajman University, Ajman, United Arab Emirates Centre of Medical and Bio-Allied Health Sciences Research, Ajman University, Ajman, United Arab Emirates Basic Medical and Dental Sciences Department, Ajman University, Ajman, United Arab Emirates

Edited by: Praveen S. Jodalli, Manipal College of Dental Sciences, India

Reviewed by: Atrey Pai Khot, King George's Medical University, India

Ramya Iyer, KM Shah Dental College and Hospital, India

 Correspondence: Divya Gopinath d.gopinath@ajman.ac.ae

ORCID Divya Gopinath orcid.org/0000-0002-4279-7420

 20022024 2024 51310334 09102023 11012024 © 2024 Senaratne, Yung on, Shetty and Gopinath. 2024Senaratne, Yung on, Shetty and Gopinath

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

 Objective

The study aimed to evaluate the impact of tobacco use on the composition and functions of the oral microbiome in healthy adult humans.

 Methods

We conducted a systematic search on PubMed, Web of Science, and Cinhal databases for literature published until 15 December 2023, to identify studies that have evaluated the oral microbiome with culture-independent next-generation techniques comparing the oral microbiome of tobacco users and non-users. The search followed the PECO format. The outcomes included changes in microbial diversity and abundance of microbial taxa. The quality assessment was performed using the Newcastle–Ottawa Scale (NOS) (PROSPERO ID CRD42022340151).

 Results

Out of 2,435 articles screened, 36 articles satisfied the eligibility criteria and were selected for full-text review. Despite differences in design, quality, and population characteristics, most studies reported an increase in bacterial diversity and richness in tobacco users. The most notable bacterial taxa enriched in users were Fusobacteria and Actinobacteria at the phylum level and Streptococcus, Prevotella, and Veillonella at the genus level. At the functional level, more similarities could be noted; amino acid metabolism and xenobiotic biodegradation pathways were increased in tobacco users compared to non-users. Most of the studies were of good quality on the NOS scale.

 Conclusion

Tobacco smoking influences oral microbial community harmony, and it shows a definitive shift towards a proinflammatory milieu. Heterogeneities were detected due to sampling and other methodological differences, emphasizing the need for greater quality research using standardized methods and reporting.

 Systematic Review Registration

CRD42022340151.

 microbiome oral tobacco smokers microbiota chewers Ajman University section-at-acceptanceOral Health Promotion Introduction

The human oral cavity harbors a diverse microbial community comprising over 700 species of bacteria or phylotypes that play a commensal role in protecting oral and systemic health (1). These diverse species have been identified by cultivation or the advancing culture in-dependent molecular approaches (1). These species attach and form biofilms on the mouth's soft and hard tissue surfaces in a structurally organized matrix, inducing a dynamic equilibrium with the immune-inflammatory response of the host (2). The human oral cavity serves as one of the major gateways to the respiratory tract, thus giving microorganisms the substantial prospect of invading these sites (3). Despite the similarities between the core microbial composition within the oral cavities, the type of species may vary depending on diet and nutrition, genetic susceptibility, antibiotic usage, hormonal factors, tobacco and alcohol exposure, and recurrent pathogenic infections of the host (4). This disturbance to the equilibrium results in oral dysbiosis altering oral and systemic health through several pathophysiological processes linked to disease (5). Dysbiosis has reportedly been involved in oral diseases such as periodontitis, gingivitis, and oral cancer (6–8).

The emergence of new genomic technology including next-generation sequencing, has led to the identification of resident bacterial populations in almost all organs and systems of the body, and has sparked an increased interest in the microbiota among researchers. These next generation sequencing helped to reveal the complex nature of the oral microbiome community, which could not be revealed by culture methods and traditional Sanger sequencing methods as less abundant and non-cultivable microbes of the population are often overlooked, which jeopardizes the accuracy of the detailed account of the microbial community (9).

Recent studies show that despite a global decline in tobacco consumption, tobacco use is exponentially rising in parts of the world, leading to a consequential public health concern (10). Tobacco smoke comprises numerous toxicants that come into direct contact with the bacteria in the oral cavity, disrupting the microbial ecology of the mouth. These toxic compounds cause cellular injury and cell death, including N-nitrosamines and polycyclic aromatic hydrocarbons blocking DNA repair and initiating tumorigenesis (11). Smoking has been shown to cause the loss of beneficial oral species, leading to pathogenic alterations by interacting with various host cells and extracellular matrix components, ultimately leading to the risk of disease development (12). This alteration increases the local density of the bacterial pathogens or decreases the prevalence of other bacteria (13, 14). Emerging evidence on the effects of smokeless tobacco on the composition of the oral microbiota in humans suggests it leads to a pro-inflammatory milieu in the oral microenvironment, further leading to diseases (15). To date, the literature on the effects of tobacco use on the oral microbiome in humans has not been systematically evaluated. Therefore, we carried out a systematic review as a first attempt to characterize the impact of tobacco use on the oral microbiome profile in healthy adults and to compare the differences in the oral microbiome profile of tobacco users with non-users. It also aims to highlight the potential effects of smoking on the host's health by analyzing the available data regarding the relationship between the human oral microbiome and tobacco use.

 Material and methods Search strategy

A systematic review was conducted to answer the question: “Is the oral microbiome profile of tobacco users different from non-users?” The present systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) under CRD42022340151) The systematic literature search was performed to identify published studies until Dec 2023 examining the oral microbial community in tobacco users in comparison to controls using broad MeSH terms and other related keywords. The search was performed independently by two investigators (NS and CY). The electronic databases used are PubMed, Web of science and CINHAL. The search was carried out using the specific key keywords with the use of Boolean operators “OR” and “AND.” The search strategy and output for each database is provided as Supplementary Tables S1–S3. Following the elimination of duplicates, the titles and abstracts were evaluated in accordance with the preset eligibility criteria as provided below to determine whether or not they should be included for additional full-text reading. Two independent investigators (NS and CY) scanned the titles and corresponding abstracts. If the abstract clearly indicated what was included or excluded, the record was read in its entirety. In the event that the findings of the two investigators disagreed, DG, the third investigator, was consulted. We manually examined the reference lists of the included publications to find any potentially relevant articles that could be included. The systematic review follows in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines (16).

 Eligibility criteria

Inclusion criteria

Cross-sectional or prospective observational studies that compared the oral microbiome analyzed with culture-independent next-generation techniques from tobacco users, including cigarettes, water pipes, smokeless, and other forms of tobacco in comparison to healthy controls were included. The detailed PECO (Population, Exposure, Control, and Outcome) scheme followed is below:

Population: Human adults using tobacco

Exposure: Use of any form of tobacco

Control: Non-users

Outcome: Changes in microbial diversity and abundance of various microbial taxa

Type of studies: Cross-sectional or prospective observational studies that utilized culture-independent next-generation techniques without date limitation.

Exclusion criteria

The studies which did not fit into the inclusion criteria were excluded.

Studies utilizing culture techniques, studies on diseased populations like periodontitis or caries, which can have an impact on the oral microbiome, animal studies, and studies on e-cigarettes were excluded. Further narrative reviews, systematic reviews, conference reports, and letters to the editor were excluded. The literature search was limited to the English Language.

 Data Extraction

Data was extracted from the selected articles through a separate full-text review by two reviewers. The following study characteristics were extracted from each article: author name, year of publication, study design, sample size, age and gender distribution, type of tobacco, exposure assessment, and significant changes in oral microbial diversity and abundances of taxa.

 Quality assessment

The quality assessment for the included studies was performed independently by two reviewers (NS and CY) using the Newcastle–Ottawa Quality Assessment Scale (17). If there is any discrepancy, then the third author was consulted (DG) and the discrepancy was resolved. This instrument incorporates three separate domains: selection, comparability, and outcomes. The selection domain involves the assessment of four items; comparability has one item, and outcomes include three items. The selected article will receive one star in each item if acceptable, thus obtaining a maximum of four in the selection domain, one in the comparability domain, and three in the outcome domain.

 Results General study characteristics

The search yielded 2,435 records from the three databases, of which 1,109 were excluded altogether due to duplicates. Screening of articles by title and abstract and reviewing of full text resulted in 36 eligible articles for full text (Figure 1). Of the 36 articles, nine were from the United States of America (18–26), six were from India (15, 27–31), five were from the United Arab Emirates (32–36),three were from China (37–39), two from Japan (40, 41) and others including Brazil (42), Jordan (43), Hungary (44), Croatia (45), Iran (46), Germany (47), Denmark (48), Italy (49), Sudan (50), Ireland (51) and Korea (52).

The prisma flow chart.

The study design followed cross-sectional studies with a sample size ranging from 22 to 1,616. Most studies were conducted on cigarette users, except seven studies that focused on smokeless tobacco products including chewing tobacco (20, 27–30, 34, 50). The 16s rRNA gene sequencing was the most commonly used methodology except for three studies that used shotgun metagenomic gene techniques (28, 33, 44). A common trait seen in most studies was screening for antibiotic usage before sampling and for the presence of chronic or oral illnesses. Further, some studies also included decisive factors that can influence the microbiome, including alcohol consumption, BMI, and diet, into consideration for profiling of the subjects (25, 27, 31, 38). Sample collection types include saliva, oral and buccal swabs, oral rinses, supragingival, subgingival and tongue scrapes, and mouthwashes. The detailed characteristics are provided in Table 1 (42–52). All controls were deemed healthy except for one study that acquired control subjects from cancer cohorts (19).

Characteristics of the selected studies.

No Author, Country, Year Study Design Sample Characteristics Type of tobacco Amount of Exposure—Assessment Methodology Statistical Adjustments
1 Thomas et al. (42), Brazil, 2014 Cross-sectional N = 226 active smokers7 smokers and drinkers9 controls Cigarette Smokers—20 cigarettes/day for past 10 years V1 region of 16s rRNA gene sequencing Subject with cancer, use of antibiotics within last 3 months, comorbidities, presence of oral lesions were excluded
2 Mason et al. (18), USA, 2015 Cross-sectional N = 200100 current smokers100 never smokers Not specified N/A 16s rRNA sequencing Diabetes, HIV, pregnancy, immunosuppressants, bisphosphonates, steroids, antibiotics, current orthodontic therapy, or professional dental cleaning within 3 months and pre-treatment using antibiotic were excluded
3 Wu et al. (19) USA, 2016 Cross-sectional N = 1,204112 current smokers471 former smokers521 never Smokers Cigarette Assessed but not specified V3 to V4 regions of 16s rRNA gene sequencing No cancer prior to samplingAge and sex was adjusted
4 Hernandez et al. (20) USA, 2017 Cross-sectional N = 12264 current chewers37 former chewers21 non chewers Chewing tobacco Long term chewers: >10 years V3 to V5 region of 16s rRNA gene sequencing No history of oral cancer
5 Yu et al. (21) USA, 2017 Cross-sectional N = 4323 current smokers20 never smokers Cigarette Smokers: >100 cigarettes in a life time V3 to V4 regions of 16s rRNA gene sequencing Age, gender, race, antibiotic usage or professional dental cleaning within the last 3 months or diagnosed with periodontal disease or cancer or losing >1 tooth were excluded
6 Rodríguez- Rabassa et al. (22) USA, 2018 Cross-sectional N = 3415 non-smokers18 current smokers Cigarette Assessed but not specified V3 to V4 regions of 16s rRNA gene sequencing Age, sex, race, education level (high school/college) was adjusted
7 Stewart et al. (23) USA, 2018 Cross-sectional N = 3010 e-cigarette users10 tobacco smokers10 controls E-cigaretteCigarette E-cigarette—daily use for at least 6 monthsTobacco smokers ≥4 and ≥10 cigarettes per day V4 region of 16s rRNA gene sequencing Sex, age, diet, height/weight and race adjusted
8 Vallès et al. (32) UAE, 2018 Cross-sectional N = 330105 smokers225 non-smokers CigaretteDokhaShisha Self-reported 16s rRNA gene sequencing Tobacco smoke exposure cut-off concentration of 200 ng/ml
9 Beghini et al. (24) USA, 2019 Cross-sectional N = 29790 current smokers45 never smokers45 former smokers38 non-smokers with second hand exposure79 alternative smokers CigaretteE-cigaretteHookahCigarCigarillo Current smokers: >100 cigarettes.Never smokers: <100 cigarettes, serum cotinine <0.05 ng/mlFormer smokers: >100 cigarettes, serum cotinine <0.05 ng/mlNon-smokers: serum cotinine 1–14 ng/ml V4 region of 16s rRNA gene sequencing Subjects who smoked in the last 5 days were excluded
10 Lin et al. (26) USA, 2019 Cross-sectional N = 6030 smokers30 non-smokers Cigarette N/A 16s rNA sequencing Subjects not treated for nicotine use, serious medical or psychiatric conditions, use of illicit drugs or on insulin or oral hypoglycaemic medications were excluded.Age and gender adjusted
11 Yang et al. (25) USA, 2019 Cross-sectional N = 1,616592 current smokers477 former smokers547 never smokers Cigarette N/A V4 region of 16s rRNA gene sequencing Age, sex, race, body mass index, alcohol consumption, total energy intake, oral and disease status adjusted.
12 Al Bataineh et al. (33) UAE, 2020 Cross sectional N = 10555 smokers50 non-smokers Cigarette Cigarette smokers: ≥5 years Shotgun metagenomic sequencing Antibiotic or prescribed probiotic use in the past three months, and those with pre-existing respiratory illness such as asthma and chronic obstructive pulmonary disease excluded
13 Al-Zyoud et al. (43) Jordan, 2020 Cross-sectional N = 10049 smokers51 non-smokers Cigarette Smokes at least 1 cigarette per day V3 to V4 regions of 16s rRNA gene sequencing Antibiotic free for the last three monthsNo chronic oral diseases
14 Halboub et al. (34) UAE, 2020 Cross-sectional N = 5229 smokers23 non-smokers Smokeless tobacco (Shammah) Daily for at least 1 year without cessation V1 to V3 regions of 16s rRNA gene sequencing Subjects with moderate to severe gingivitis or periodontitis, history of antibiotic, antifungal or steroids use and periodontal treatment, including prophylaxis in the last 3 months were excluded
15 Sato et al. (40) Japan, 2020 Cross-sectional N = 657364 never smokers129 former smokers144 current smokers Cigarette N//A V3 to V4 regions of 16s rRNA gene sequencing Subjects on oral antimicrobials or steroids, low GFR rate, on anti-hypertensive drugs, hypoglycaemic agents or probiotics were excluded
16 Wirth et al. (44) Hungary, 2020 Cross-sectional N = 2211 smokers11 non-smokers Cigarette Cigarette smokers: ≥20 cigarettes/pack year Shotgun metagenomic sequencing—real time PCR Chronic illnesses and treatment with antibiotics for at least 6 months prior to sampling were excluded
17 Bašić et al. (45) Croatia, 2021 Cross-sectional N = 6432 smokers32 non-smokers Cigarette Smokers—1 pack/day MALDI-TOF mass spectrometry Presence of periodontitis, systemic diseases, mediation, pregnancy, less than 20 teeth, use of antibiotics six months prior and periodontal or orthodontic therapy use was excluded.
18 Al Kawas et al. (35) UAE, 2021 Cross-sectional N = 4010 controls10 cigarettes smokers10 shisha smokers10 medwakh CigaretteShishaMedwakh N/A 16s rRNA gene sequencing Patients who were currently receiving orthodontic treatment and those who had any periodontal treatment, antibiotics, or steroid therapy in the last 3 months were excluded
19 Jia et al. (37) China, 2021 Cross-sectional N = 316 Cigarette Current Smokers: one cigarette every 1–3 days for 1 yearFormer Smokers: no smoking for a year 16s rRNA gene sequencing Amplicon sequence variants in fewer than three samples and with abundances less than five were excluded
20 Li et al. (38) China, 2021 Cross-sectional N = 7616 smokers60 non-smokers Cigarette Not specified V4 region of 16s rRNA gene sequencing No oesophageal cancer, low-grade dysplasia (LGD), high-grade dysplasia (HGD)Age, gender, BMI adjusted
21 Srivastava et al. (27) India, 2021 Cross-sectional N = 4020 smokers10 non-smokers Smokeless tobacco Smokers—>5 years with 25 g of SLT product intake a week V3 region of 16s rRNA gene sequencing Subjects who were alcoholic and on any medications or antibiotics were excluded
22 Wu et al. (46) Iran, 2021 Cross-sectional N = 558120 cigarette only users120 never users49 opium only users Cigarette N/A 16s rRNA gene sequencing Subjects who had a normal pancreas at the endoscopic ultrasonography exam, aged 40 years or older, no history of liver or renal failure or cancer, no consumption of a special diet, and did not develop pancreatic disease or any cancer within one year of the initial visit
23 Al-Marzooq et al. (36) UAE, 2022 Cross-sectional N = 4010 control10 cigarette smokers10 shisha smokers10 medwakh smokers CigaretteShishaMedwakh N/A 16s rRNA gene sequencing Subjects who smoked more than one type of tobacco and had less than 10 teeth were excluded
24 Gopinath et al. (15) India, 2022 Cross-sectional N = 4417 smokers14 smokeless tobacco users14 non-smokers Cigarettes/BidisSmokeless tobacco Tobacco use—1–12 years 16s rRNA gene sequencing Subjects to refrain from smoking, drinking and eating 30 min before sample collection
25 Pfeiffer et al. (47) Germany, 2022 Cross-sectional N = 5830 smokers6 ex-smokers10 never-smokers Cigarette Long term Smokers: ≥10 daily cigarettes & ≥10 pack yearsShort term smokers: ≥10 daily cigarettes & <10 pack yearsMild smokers: <10 daily cigarettes & <5 pack years 16s rRNA gene sequencing N/A
26 Poulsen et al. (48) 2022, Denmark Cross-sectional N = 746350 ex-smokers N/A N/A 16s rRNA gene sequencing N/A
27 Sharma. (28) 2022, India Cross-sectional – Chewing tobacco N/A Metagenomic sequencing N/A
28 Suzuki et al. (41) Japan, 2022 Cross-sectional N = 50 (39M, 11F)18 smokers32 non-smokers Cigarette Smokers: ≥100 cigarettes after initiation of smoking 16s rRNA gene sequencing Subjects who scored more than 0 for bleeding on probing and probing pocket depth were excluded
29 Antonello et al. (49) Italy, 2023 Cross-sectional N = 1601720 current/former smokers881 non-smokers Cigarette Current smokers—reduced daily smoking intensity one month prior V4 region of 16s rRNA sequencing Sex, age and number of teeth were adjustedUse of antibiotics for last 3 months and missing date on number of teeth were excluded
30 Bahuguna et al. (29) India, 2023 Cross-sectional N = 229 chewers9 non-chewers4 occasional/previous chewers Chewing tobacco Chewers—habitual individualsOccasional/previous chewers—once in a couple of months/previous history of chewing 16s rRNA sequencing N/A
31 Huang et al. (39) China, 2023 Cross-sectional N = 587111 smokers467 non-smokers Cigarette Pack years but not specified 16s rRNA gene sequencing Subject with disease and microbial features of cardio metabolic risk factors were excluded
32 Sami et al. (50) Sudan, 2023 Cross-sectional N = 7847 smokers32 non smokers Smokeless tobacco (toombak) N/A 16s rRNA sequencing Absence of periodontal disease and dental infection, controlled caries mouth, use of antibiotics the past 3 months
33 Sawant et al. (30) India, 2023 Cross-sectional N = 12040 controls40 long term tobacco chewers40 oral cancer patients Chewing tobacco Chewing tobacco—≥5 years 16s rRNA gene sequencing Use of antibiotic treatment for one week prior, previous oncotherapy, medically compromised and edentulous subjects were excluded
34 Galvin et al. (51) Ireland, 2023 Cross-sectional N = 322148 current smokers Cigarette N/A V1toV3 region of 16s rRNA gene Use of antibiotics or topical steroids intra-orally in the past 3 months, patients with diabetes mellitus, chron's disease, ulcerative colitis, current viral infection and history of gastrointestinal malignancy were excluded
35 Yadav et al. (31) India, 2023 Cross-sectional N = 50 Cigarette Smokers—past 5 years V3 to V4 region of 16s rRNA gene sequencing Ex-smokers and subjects who both smoked and consumed alcohol were excluded
36 Yu et al. (52) Korea, 2024 Cross-sectional N = 43 Not specified N/A 16s rRNA gene sequencing Use of antibiotics for one month and food or water intake two hours prior sample collection was restricted.
Diversity and richness analysis

As displayed in Table 2 (42–52), all included studies except five assessed microbial diversity and richness (23, 28, 31, 38, 45). Five studies reported no difference in diversity difference between the smokers and control groups (34, 36, 41, 49, 52). Four studies (21, 26, 40, 42) reported lower diversity and richness in smokers. The rest of the studies concluded that the richness and phylogenetic biodiversity of smokers or tobacco users were significantly different or higher than non-users or former users.

Characteristics of oral microbiome from the selected studies.

No Author, Country, Year Sample Type Age (Range/Mean/Median) Other clinical features studied Results: Diversity and Richness Bacterial taxa associated with
1 Thomas et al. (42) Brazil, 2014 Oral swab Overall—>40 yearsSmokers—56.67 ± 2.49Smokers/drinkers—59.86 ± 3.39Control—58.11 ± 8.28 Effects of chronic alcohol use on the oral micro biome Decrease in species richness in smokers Smokers had significant increases in Prevotella and Capnocytophaga and reductions in Granulicatella, Staphylococcus, Peptostreptococcus and Gemella. Smokers/drinkers had lower abundances of Fusobacteria
2 Mason et al. (18) USA, 2015 Subgingival plaques Overall—21–40 yearsNever smokers—27.0 ± 5.3Current smokers—28.25 ± 3.5 Not assessed Higher diversity in smokers The subgingival microbiome of smokers was enriched with Fusobacterium nucleatum, S.mutans and Lactobacillus salivarius and lower levels of Streptococcus sanguinis, S.oralis and Hemophilus parainfluenzae
3 Wu et al. (19) USA, 2016 Oral rinse Current Smokers—68.82Former Smokers—70.71Never smokers—70.53 Prospective development of head and neck cancer and pancreatic cancer Current smokers had an increased diversity Current smokers had decreased abundance of phylum ProteobacteriaGenera Peptostreptococcus, Capnocytophaga, and Leptotrichia were depleted. In contrast, Atopobium and Streptococcus were enriched in current smokers compared with never smokers
4 Hernandez et al. (20) USA, 2017 Oral swabSaliva Overall—18–60 + years Body mass index Alpha diversity lower in current chewers Current chewers had elevated levels of Streptococcus infantis and lower levels Actinomyces and Streptococcus genera. Long-term chewers had reduced levels of Parascardovia and Streptococcus. Chewers with oral lesions had elevated levels of Oribacterium, Actinomyces, and Streptococcus
5 Yu et al. (21) USA, 2017 Subgingival plaque scrapes, saliva, oral swab Assessed but not specified N/A Alpha diversity was lower in smokers than in non-smokers in the buccal mucosa Streptococcus was the most abundant across all types of oral samples followed by Veillonella
6 Rodríguez- Rabassa et al. (22) USA, 2018 Saliva Smokers—54Non-smokers—34 Cytokine levels and symptoms of depression Beta diversity between smokers and non-smokers were p < 0.05 Proteobacteria, Firmicutes, Bacteroidetes, Fusobacteria and Actinobacteria dominated in smoker samples
7 Stewart et al. (23) USA, 2018 SalivaBuccal swab Control—31 (28–36)E-cigarette—29 (24–37)Tobacco smoker—35 (30–45) N/A N/A Cigarette users were associated with significantly lower abundance of Bacteroides and Prevotella compared to EC users and non-smokers
8 Vallès et al. (32) UAE, 2018 Mouthwash Smokers—32.4Non-smokers—33.1Cigarette—36.4Dokha—30.8Shisha—35.7 N/A Tobacco users had higher diversity Cyanobacteria, SR1, Cyanobacteria) and BD1–5 (GN02) were all depleted in smokersActinobacillus depletion was consistently observed across all four types of tobacco
9 Beghini et al. (24) USA, 2019 Oral rinse Overall—>18 years N/A Difference in beta diversity between current smokers and never smokers.No alpha diversity difference Streptococcus and Prevotella was the predominant genera, while proteobacteria was less abundant in smokersPhyla Actinobacteria, Firmicutes and Proteobacteria were more abundant in alternative smokers.In hookah users, Porphyromonas, Leptotrichia, Streptobacillus and Fusobacterium were depleted
10 Lin et al. (26) USA, 2019 Saliva Overall—37.2 ± 10.65 (21–56 years) Brain functional connectivity and neurological signalling in smokers, alcohol use identification and marijuana smoking Decrease of beta diversity in smokers Bacteroides, Treponema, Mycoplasma, TG5, Actinomyces spp was abundant in smokers.Depletion of Lautropia and Neisseria were also seen in smokers
11 Yang et al. (25) USA, 2019 Oral rinse Current Smokers—53.18 ± 7.90Former Smokers—59.18 ± 8.49Never Smokers—55.78 ± 8.88 Body Mass Index Current smokers had increased diversity Phylum Actinobacteria, Bifidobacterium and Lactobacillus, were enriched among current-smokersPhylum Proteobacteria was depleted in current smokers
12 Al Bataineh et al. (33) UAE, 2020 Buccal swab Smokers—30.40Non-smokers—30.30 Nicotine dependence Heavy smokers had an increase in diversity Smokers had significant abundance of Veillonella dispar, Prevotella pleuritidis and Leptotrichia spp when compared to non-smokers
13 Al-Zyoud et al. (43) Jordan, 2020 Saliva 23.9 ± 6.2027.1 ± 7.57 N/A Higher richness in smokers vs. non-smokers. Streptococcus, Prevotella, and Veillonella showed significantly elevated levels among smokers and Neisseria in non-smokers
14 Halboub et al. (34) UAE, 2020 Tongue scrapes Overall—20–40 yearsSmokers—27.34 ± 6.9 yearsNon-smokes—27.7 ± 7.19 years N/A No significant difference in richness or alpha diversity between study groups. Firmicutes, Actinobacteria, Proteobacteria, Fusobacteria, and Bacteroidetes were abundant in all samplesRothia mucilaginosa, Streptococcus sp. oral taxon 66, Actinomyces meyeri, Streptococcus vestibularis, Streptococcus sanguinis and Veilonella was abundant in smokers
15 Sato et al. (40) Japan, 2020 Tongue coating Never smokers—49.78Former smokers—48.03Current smokers—43.99 N/A The alpha diversity was lower in current smokers than in never smokers Neisseria and Capnocytophaga were less abundant and Streptococcus and Megasphaera were more abundant in current smokers
16 Wirth et al. (44) Hungary, 2020 Saliva Non-smokers—40Smokers—41.5 Level of exhaled carbon monoxide and periodontal status Increase in diversity in the smokers group Streptococcus along with Prevotella and Veillonella were abundant in both groupsPrevotella and Megasphaera was higher in saliva of current smokers whereas Neisseria, Oribacterium, Capnocytophaga and Porphyromonas were reduced
17 Bašić et al. (45) Croatia, 2021 Subgingival plaques Overall—25–35 years old N/A N/A Prevalence of Actinomyces odontolyticus was higher in smokers, while Streptococcus sanguinis was lower compared to non-smokers
18 Al Kawas et al. (35) UAE, 2021 Subgingival plaques Cigarettes—31.9 ± 10.43Shisha—29.1 ± 12.05Medwakh—24.1 ± 4.33Non-smokers—38.5 ± 13.6 Periodontitis Diversity was equal in all four groups Prevotella denticola and Treponema sp. OMZ 838 increased abundance in medwakh smokersStreptococcus sanguinis and Tannerella forsythia in shisha smokersStreptococcus mutans and Veillonella in cigarette smokersFirmicutes was the most abundant phylum across all groups
19 Jia et al. (37) China, 2021 Saliva 46.98 ± 11.4746.74 ± 11.1646.17 ± 11.48 N/A Difference in alpha diversity between smokers and never smokers At the genus level, Actinomyces, Oribacterium, Atopobium, Prevotella, Veillonella and Campylobacter were increased in smokers.Haemophilus, Kingella, Neisseria, Cardiobacterium, Aggregatibacter, Lautropia, Eikenella and Moraxella were significantly depleted in smokersAt the species level, Rothia dentocariosa, Prevotella melaninogenica, Prevotella pallens, Bulleidia moorei and Veillonella dispar were increased in smokers. Rothia aeria, Neisseria oralis, Nesseria subfl ava, Haemophilus parainfluenzae and Actinobacillus parahaemolyticus were depleted in smokers
20 Li et al. (38) China, 2021 Saliva Overall—50–70 years Effect of drinking N/A for saliva samples Increase of Neisseria, Prevotella, Porphyromonas, Fusobacterium, and Rothia and a decrease of Streptococcus, Actinobacillus, and Haemophilus in subjects who smoked
21 Srivastava et al. (27) India, 2021 Oral rinse Overall—24–58 years Health Status—diabetic status, systolic BP, BMI SLT users showed higher richness diversity higher diversity SLT users had increase abundance of Fusobacteria, Porphyromonas, Enterococcus, Parvimonas and Desulfobulbus
22 Wu et al. (46) Iran, 2021 Saliva Cigarette smokers—(82.13 ± 38.55)Cigarette and opium users—(77.80 ± 42.83)Never users—(95.10 ± 44.03). Use of opium Lower alpha diversity in cigarette users Enterobacteriaceae was prevalent in cigarette smokers onlyAbundance of phyla Actinobacteria, Proteobacteria, Bacteroidetes,and Firmicutes were noted in smokers and opium users
23 Al-Marzooq et al. (36) UAE, 2022 Supragingival plaque scrapes 18–62 years Dental carries No difference Firmicutes was the most abundant phylum in the supragingival plaque samples of all types of tobacco smokingProteobacteria and Actinobacteria were significantly abundant in shisha smokers and other types of smokersOverall Streptococcus was the most abundant genus
24 Gopinath et al. (15) India, 2022 Buccal swab Smokers—33.05Chewers—32.92Controls—33.69 Levels of carbon monoxide exhaled Increase in diversity with the use of tobacco Levels of Fusobacterium spp. and Saccharibacterium spp. were increased in smokers in comparison to controls. The relative abundance of Fusobacterium spp., Catonella, and Fretibacterium spp. were significantly higher in smokeless tobacco users
25 Pfeiffer et al. (47) Germany, 2022 Nasal swabsOropharyngeal swabBronchoalveolar lavage N/A Levels of nicotine and metabolite cotinine Increase diversity with smoking Firmicutes was relatively higher in abundance in smokers compared to never-smokers Actinobacteria was significantly higher in smokers and ex-smokers comparative with never smokers and Betaproteobacteria was lower in smokers and ex-smokers in oropharyngeal samples
26 Poulsen et al. (48) 2022, Denmark Saliva Overall—68 years Effect of other lifestyle factors on salivary microbiota Difference in diversity between smokers and other variables Genera Veilonella, Streptococcus and Rothia was higher and Neisseria, Haempilus, Pophyromonas and Actinomyces in smokers compared to ex-smokers and never smokers
27 Sharma (28) 2022, India Saliva N/A Oral microbiome in oral cancer N/A Phylum Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria were abundant in tobacco users
28 Suzuki et al. (41) Japan, 2022 SalivaTongue samples Overall—25.6 ± 2.1(21–31 years)Smokers—26.8 ± 2.4Non-smokers—25.0 ± 1.6 N/A No difference Smoker's saliva was enriched with Treponema and Selenomonas. The tongue microbiota from smokers were higher in Dialister and Atopobium
29 Antonello et al. (49) Italy, 2023 Saliva Overall—45 years (18–91 years) N/A No changes in alpha diversity Firmicutes were the most abundant, followed by Bacteroidetes, Proteobacteria, Actinobacteria and FusobacteriaIncreased abundance of Atopobium, Megasphaera, Fretibacterium, and Veillonella when compared to never smokers
30 Bahuguna et al. (29) India, 2023 Oral swab N/A N/A Increased alpha diversity in chewers S. pneumoniae, S. salivarius, and S. Mutans were increased in oaccasional chewers whereas Streptococcus genus was decreased in current chewers. Prevotella and bacteriodes was increased in chewers
31 Huang et al. (39) China, 2023 Saliva Smokers—53 yearsNon-smokers—49 years Cardiometabolic risk factors Alpha diversity was higher in smokers Higher abundance of phyla Firmicutes and ActinobacteriotaMegasphaera, Anaeroglobus, Dialister, Rothia, Atopobium, Actinomyces, Howardella, and Romboutsia and lower relative abundance of the genus Johnsonella in smokers was observed
32 Sami (50) Sudan, 2023 SalivaMucosal and supragingival plaques Overall—20–70 years Oral cancer microbiome composition Alpha diversity was significantly varied between groups Staphylococcaceae and Corynebacterium_1 and Cardiobacterium was more abundant in smokersPrevotella, Lactobacillus and Bifidobacterium were prominent in non-smokers
33 Sawant et al. (30) India, 2023 Oral rinse >18 years N/A Higher alpha diversity in tobacco chewers and control populations Leptotrichia, Treponema, Lautropia, spirochaetes and Cardiobacterium was abundant in tobacco chewers
34 Galvin et al. (51) Ireland, 2023 Oral swab Overall—≤40 and ≥60 years Effect of tooth loss, plaque levels and oral hygiene on oral mucosal colonization No significant changes in alpha diversity Reduced abundance of Neisseria, H. parainfluenza, L. mirabilis, R. aeria, S. australis and S. sanguinis and Increased abundance of S. parasanguinis seen in smokersGenera Aggregatibacter, Bergeyella, Capnocytophaga, Selenomonas, Prevotella, Porphyromonas, Tannerella, Parvimonas, Filifactor, Bacteroidales [G2] and Peptostreptococcaceae was noted in smokers
35 Yadav et al. (31) India, 2023 Saliva N/A Alcoholic consumption and vegan diet N/A Smokers had higher concentrations of Streptococcus, Prevotella, Veillonella and Tannerella and lower concentrations of Fusobacterium, Selenomonas and Neisseria when compared with non-SmokersClostridium, Filifactor and Corynebacterium were only found in smokers
36 Yu et al. (52) Korea, 2024 Saliva Overall—20's to 50's Coffee consumption and Drinking No difference in alpha diversity between smokers Abundance of Oribacterium, Atopobium, and 21 Megasphaera, Eubacterium_nodatum_group, Butyrivibrio were higher in smokers
Differences in the abundance of various taxa between smokers and non-smokers

Firmicutes were identified as the most abundant phylum across most studies compared to other types of phyla, including Proteobacteria, Bacteroidetes, and Fusobacteria, which varied in abundance among smokers and non-smokers. Four studies reported Fusobacteria being depleted in non-smokers and higher in smokers (18, 22, 27, 49). In contrast, Fusobacteria, in particular, was lower in smokers and drinkers and more abundant in the control group (42). Studies conducted using an oral rinse and saliva of cigarette and tobacco smokers were enriched with phylum Actinobacteria in current users (25, 28, 46, 49). Similarly, an abundance of Actinobacteria in water pipe smokers was reported in another study (36). Bacteroidetes dominated smoker and chewer samples in two studies (22, 29) compared to another, which reported a lower relative abundance in cigarette smokers compared to e-cigarette users and controls (23). In terms of genera, most studies reported different types of genera in various types of samples from smokers and healthy controls. Streptococcus was relatively reported higher in abundance in smokers in several studies. Prevotella and Veillonella, mostly independently, were also found as predominant genus in tobacco users (21, 24, 31, 34, 37, 38, 42–44, 49, 51), while another data reported a significant depletion in the saliva and supragingival plaques of smokeless tobacco users (50). Neisseria was also observed to be higher among other genera in smokers in two studies conducted in China and Denmark (38, 48). The detailed findings are presented in Table 2.

 Differences in metabolic pathways between smokers and non-smokers

Among the 36 studies included, only 9 of them explored the differences in metabolic pathways (15, 19, 26, 27, 30, 37, 39, 40, 49). Wu et al. reported that xenobiotic biodegradation, amino acid metabolism pathways, glycan biosynthesis, and metabolism were enriched in smokers. Further pathways related to aerobic metabolism [tricarboxylic acid (TCA) cycle, oxidative phosphorylation and nitrate reduction] were depleted in current smokers (19, 49). Similarly, Sato et al. also reported significant differences in pathways related to the TCA cycle, glyoxylate cycle, and several compound biosynthesis and degradation between smokers and non-smokers (40). Jia et al. reported that acid production, amino acid-related enzymes and amino sugar, and nucleotide sugar metabolism were all enriched in smokers (37). A recent study on cigarette smokers reported depletion of pathways related to membrane transport and lipid metabolism in smokers as well as xenobiotics biodegradation and enrichment of pathways related to the metabolism of amino acids, nucleotides, vitamins, terpenoids, polyketides, and glycans (26). In the case of smokeless tobacco users, Srivastava et al. reported an increase in amino acid metabolism, xenobiotic biodegradation, and cellular process and signaling (27). Another study also reported an increase in pathways related to amino acid metabolism, synthesis, and degradation (15). Moreover, Sawant et al, observed an increase in pathways related to reductive TCA cycle and pyrimidine biosynthesis in chewing tobacco users (30).

 Methodological quality of the studies

The quality of the studies can be found in Supplementary Table S1. Five studies were graded as very good; twenty-six articles were of good quality, whereas the rest of them were of satisfactory quality.

 Discussion

This review aimed to evaluate the available evidence on the impact of the use of tobacco in various forms on healthy humans' oral microbiomes. To our knowledge, this is the first systematic and comprehensive review that summarizes the impact of tobacco use on the oral microbiome. Although there were variations in design, quality of the studies, and characteristics, our results highlight that smoking, regardless of the form, altered the normal equilibrium of the oral microbiome. This evidence is in accordance with previous results obtained analyzing oral microbiomes in culture methods and animal models (53, 54). Despite the limited number of studies, other less-known forms of smoking also seemed to be associated with changes in the oral microbiome.

The current review of data from clinical studies emphasizes that cigarette smoking is found to cause alteration in the oral bacterial profiles. Streptococcus was notably a predominant genus in most studies. In healthy populations, streptococci are common members of the subgingival and supragingival habitats and are early commensal invaders of these environments. However, these commensals have been shown to inhibit the proinflammatory response, which is how they predominantly modulate the immune system and aid in biofilm development (55). Notably, the majority of the other bacteria that were significantly increased in smokers were anaerobes, including Prevotella and Veillonella. This could be related to the deprivation of oral oxygen due to cigarette smoking. Smoking may create a depletion of an oxygen environment in the mouth. It would reflect on the oxygen availability of microbes in the oral cavity, leading to the oral microbial ecology alteration. These were also reported to increase smokers' gut microbiome (47, 56). Veillonella and Actinomyces were the anaerobic bacteria found to be higher in smokers, and these could promote the development of biofilms in the oral cavity (37). Interestingly, Actinomyces have also been enriched in several cancers, including liver, esophagus, colorectal cancer, etc. (57–60). Actinomyces has been shown to the production of various immunological and microbial-related genes, such as TLR2, TLR4, and NF-B, which support the growth of colorectal cancer by controlling inflammation by activating the downstream TLR4/NF-B pathway (60). Actinomyces also has been shown to modulate the presence of several other gram-negative bacteria (60). It also reduces antitumor immunity by preventing CD8+ T cell invasion in colorectal cancer (60). Furthermore, nitrate in vegetables is often converted to oral nitrate, which has the potential to make the oral cavity more acidic, and anaerobic bacteria, especially Actinomyces and Veillonella, promote this conversion (61, 62). This acidic environment has been shown to encourage the growth of biofilms and is linked to oral cavity diseases (63). Decreased local oxygen tension and acidic environment are also likely to promote periodontal anaerobes Fusobacterium, Treponema, and P. gingivalis, which are implicated in the development of periodontitis (64).

The oral cavity is often the first contact with smoke and hence may play an essential role in the degradation of toxic compounds. The depletion of several biodegradation pathways in current smokers suggests potential downstream consequences. A key observation in smokers was the enriched degradation of polycyclic aromatic hydrocarbons and other constituents in cigarette smokers (19). Amino acid-related enzymes and amino sugar and nucleotide sugar metabolism were notably abundant in smokers compared to non-smokers (37). Alternatively, these toxic compounds may saturate the enzymes responsible for their degradation, thus killing the bacteria possessing these enzymes (19). The toxic components in cigarette smoke have been shown to alter the oral immune response, and it has been implicated in the pathogenesis of several oral diseases, including periodontitis and oral cancer (8, 64).

Oral epithelial cells actively participate in oral immune response by expressing specific receptors, including toll-like receptors (TLRs). TLRs are receptors in immune response expressed by cell surfaces and internal vesicles and their stimulation lead to activation multiple intracellular signaling cascades (65) One of the main downstream signaling cascades is the NF-KB, a critical transcription factor that encourages the expression of chemokines, cytokines, and co-stimulatory and adhesion molecules (66). Cigarette smoke has been shown to increase the expression of and alter the functional activation of these receptors, including TLR-2, TLR-4, and others (67, 68). Interestingly, the taxa reported to be enriched in smokers including Fusobacteria, Veillonella, Prevotella, and Actinomyces, as well as other microorganisms, also bind to TLR-2 and TLR-4 using their peptidoglycan and lipopolysaccharide cell walls, and these TLR-2 or TLR-4 mediated signaling leads to up-regulation of several proinflammatory pathways (69–74). TLRs and their signaling machinery have been subsequently implicated in a wide range of human diseases, including several cancers, especially oral cancers (75–77).

Tobacco components have also been shown to increase the virulence of specific periodontal pathogens, particularly for P. gingivalis, which has multiple virulence factors (64, 78, 79). Oxidative stress-related proteins in P. gingivalis are up-regulated in the presence of nicotine and other products, which helps in adaptability and survival ability in a low-oxygen environment and biofilms (78, 80). P. gingivalis biofilms have reduced proinflammatory properties, which can help enhance sustainability (80, 81). However, it was interesting to note that the upregulation of P. gingivalis was reported by two published studies only. P. gingivalis is also known to facilitate many microbial colonizers, including S. oralis, Streptococcus gordonii, Actinomyces viscosus, Fusobacterium spp & Prevotella intermedia (79, 82–84), which has been reported to be upregulated by multitude of studies included in the review.

Interestingly, one of the studies reported that the overall oral microbiome composition of former smokers did not differ in comparison to never smokers; this indicates that changes in the oral microbiome influenced by smoking are permanent (19). Such findings are encouraging and can lay the foundation for microbiome-targeted approaches for smoking cessation and disease prevention.

In our review, we noticed that only very few studies have explored the impact of use of shisha or waterpipe on the oral microbiome. It is now known that waterpipe smoke constitutes many of the same toxicants and is associated with the risk of disease (36). Relative to water pipe smoking, out of the four studies included, Streptococcus sanguinis was found to be higher in smokers (35). Overall, phyla Firmicutes was the most abundant phylum in those combined with other forms of tobacco smoking such as medwakh and cigarettes (35, 36). Few of these bacterial species are known to be a common cause of human respiratory diseases and infections, notably where tobacco consumption is a significant risk factor (85, 86). It is pretty unclear as to what specific bacteria taxa are associated with water pipes due to the scarcity of resources available; however, this could be mainly influenced by the habits of the subjects and other exposures as well.

Smokeless tobacco can also impact oral microbiota, increasing the risk for oral disease pathologies. Due to the nicotine concentration in smokeless tobacco, the growth of S.mutans places the user at an increased risk for dental caries (87). Hung et al. suggested that these tobacco products can increase caries development by fostering S.mutans formation on tooth surfaces (88). Further, streptococci species are known to produce acetaldehyde. Acetaldehyde, a carcinogenic compound, production has been proposed as a mechanism by which bacteria can contribute to oral carcinogenesis (34). This is supported by abundant levels of Streptococcus genera that indicated alterations in smokeless tobacco users compared to controls (15, 27). Furthermore, Fusobacteria abundant in smokeless tobacco users is an opportunistic pathogen and has been known to be capable of growth in acidic conditions (15). Fusobacteria has reportedly been noted in human colorectal carcinoma, suggesting it may have originated from the oral cavity. They promote tumor development by inducing inflammation and the immune response of the host to produce inflammatory factors (89). In addition, these species have reportedly been found to be abundant in head and neck cancer samples (90).

This review noted that sample collection sites in the oral cavity subsequently differed within the studies. This site variation could produce significant bias as the sites may vary in microbial composition. For instance, salivary samples may reflect the bacteria shed from the total oral cavity, whereas tissue sampling would be a deeper representation of the microbiome concerning the host (91). Hence, it wouldn't be rational to assume the impacts of smoking caused by components of tobacco smoke are similar across all microenvironments (44). Further studies are recommended to elucidate the different ecology of these environments, as interpreting the data of a mixture of sample types may obscure meaningful associations and patterns.

The current review highlights that the studies reported until now relied on genetic characterization of the microbiome using 16S sequencing methodology without adequate examination of this functionality. Only three studies employed shotgun sequencing (28, 33, 44). Given that shotgun metagenomic sequencing provides better strain level resolution and functional insights, the field should focus more on this sophisticated methodology, in combination with metabolomics and metaproteomic, in decoding host-microbiome interactions. Microbiome architecture can be highly varied among humans, with inter-individual variation presenting a substantial challenge, necessitating the development of sophisticated machine learning processes that predict the impact of microbiome and metabolites on physiological and pathological situations. Despite these constraints, understanding the ubiquitous activities of microbially regulated metabolites can open up a new avenue for enhancing oral health. One of the potential clinical implication of deciphering host-microbial interactions would be management strategies for tobacco-related illnesses, including smoking cessation strategies by altering the microbiota with probiotics, prebiotics, and other related methods. There is currently insufficient data despite the possibility that several preventive and therapeutic applications might be effective in theory. These are primarily related to the possibility of eubiosis being restored upon smoking cessation. As a matter of fact, we have uncovered a dearth of research on this aspect considering the abundance of studies on tobacco use and oral microbiota and needs to be explored further.

One of the limitations of the current review is the heterogeneity in the methods and the outcome reporting in the included studies, which hindered comparability and quantitative analysis. However, this is a common limitation reported by most of the reviews on microbiome, because of the inherent heterogeneity in the methodology. Further, we have included articles published only in the English language.

 Conclusion

In this review, it is majorly observed that smoking and smokeless tobacco influence the oral microbial community composition, and there is a definitive shift in the abundance of oral taxa favoring an anaerobic environment, thus promoting a proinflammatory milieu. It is suggested that smoking may perturb the balance of the oral microbiome by affecting the relationships between bacteria and altering their metabolic pathways. However, smokeless and smoking tobacco are a mixture of multiple toxicants, and their direct impact on the oral microbiome is yet unclear. The effect of tobacco on microbial metabolism needs to be elucidated and is critical to our understanding of the etiology of oral and systemic diseases, as oral microbial dysbiosis are associated with several systemic conditions.

 Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

 Author contributions

NSe: Data curation, Formal Analysis, Investigation, Methodology, Writing – original draft. NSh: Data curation, Methodology, Validation, Writing – review & editing. DG: Conceptualization, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. CY: Data curation, Formal Analysis, Investigation, Methodology, Writing – original draft.

 Funding

The author(s) declare no financial support was received for the research or authorship of this article.

The APC is funded by Ajman University.

 Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

 Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

 Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/froh.2024.1310334/full#supplementary-material

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