The oral microbiome of newly diagnosed tuberculosis patients; a pilot study

From BugSigDB
Needs review
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI Uniform resource identifier for web resources.
Authors
Shahzad M, Saeed M, Amin H, Binmadi N, Ullah Z, Bibi S, Andrew SC
Journal
Genomics
Year
2024
Keywords:
Bacterial diversity, Dysbiosis, Metabolic potential, Microbiota, Respiratory diseases
BACKGROUND: Changes in oral microbiota composition (dysbiosis) have long been known to play a key role in the pathogenesis of oral and systemic diseases including respiratory diseases. However, till now, no study has assessed changes in oral microbiota following tuberculosis (TB) infection in humans. AIMS: This is the first study of its kind that aimed to investigate oral microbial dysbiosis in newly diagnosed, treatment naïve, TB patients. METHODS: Oral swab samples were collected from newly diagnosed TB patients (n = 20) and age, gender and ethnicity matched healthy controls (n = 10). DNA was extracted and microbiota analyzed by sequencing the hypervariable (V3-V4) region of the bacterial 16S rRNA gene using Illumina MiSeq platform. Bioinformatics and statistical analyses were performed using QIIME and R. RESULTS: Bacterial richness, diversity and community composition were significantly different between TB patients and healthy controls. The two groups also exhibit differential abundance at phylum, class, genus and species levels. LEfSe analysis revealed enrichment (LDA scores (log10) >2, P < 0.05) of Firmicutes (especially Streptococcus) and Actinobacteriota (especially Rothia) in TB patients relative to healthy controls. Gene function prediction analysis showed upregulation of metabolic pathways related to carbohydrates (butanoate, galactose) and fatty acids metabolism, antibiotics biosynthesis, proteosome and immune system signaling. CONCLUSION: These observations suggest significant variations in diversity, relative abundance and functional potential of oral microbiota of TB patients compared to healthy controls thereby suggesting potential role of oral bacterial dysbiosis in TB pathogenesis. However, longitudinal studies using powerful metagenomic and transcriptomic approaches are crucial to more fully understand and confrim these findings.

Experiment 1


Needs review

Curated date: 2025/06/07

Curator: Nuerteye

Revision editor(s): Nuerteye

Subjects

Location of subjects
Pakistan
Host species Species from which microbiome was sampled. Contact us to have more species added.
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Oral cavity Bucca,Buccal cavity,Cavity of mouth,Oral cavity,oral cavity
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
Pulmonary tuberculosis lung TB,lung tuberculosis,pulmonary TB,pulmonary tuberculosis,Tuberculosis, Pulmonary,Pulmonary tuberculosis
Group 0 name Corresponds to the control (unexposed) group for case-control studies
Healthy controls
Group 1 name Corresponds to the case (exposed) group for case-control studies
Newly diagnosed, treatment‑naive pulmonary TB patients
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Confirmed active pulmonary TB (sputum smear microscopy and Xpert MTB/RIF assay, per national guidelines)
Group 0 sample size Number of subjects in the control (unexposed) group
10
Group 1 sample size Number of subjects in the case (exposed) group
20
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
Excluded if currently or recently receiving broad‑spectrum antibiotics or prescription mouthwashes

Lab analysis

Sequencing type
16S
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
V3-V4
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
PERMANOVA
DESeq2
LEfSe
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
Yes
LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
2
Matched on Factors on which subjects have been matched on in a case-control study
age, Matched on: "gender" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.gender
Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
socioeconomic status, education level, oral hygiene

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
increased
Simpson Estimator of species richness and species evenness: more weight on species evenness
increased
Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
increased
Richness Number of species
increased

Signature 1

Needs review

Curated date: 2025/06/07

Curator: Nuerteye

Revision editor(s): Nuerteye

Source: Figure 4A and B

Description: Linear discriminant analysis Effect Size (LEfSe) at genus and phylum level between the two groups.

Abundance in Group 1: increased abundance in Newly diagnosed, treatment‑naive pulmonary TB patients

NCBI Quality ControlLinks
Actinomyces
Bacteroides
Comamonas
Rothia mucilaginosa
Streptococcus
FirmicutesFirmicutes
ActinobacteriaActinobacteria

Revision editor(s): Nuerteye

Signature 2

Needs review

Curated date: 2025/06/07

Curator: Nuerteye

Revision editor(s): Nuerteye

Source: Figure 4A and B

Description: Linear discriminant analysis Effect Size (LEfSe) at genus and phylum level between the two groups.

Abundance in Group 1: decreased abundance in Newly diagnosed, treatment‑naive pulmonary TB patients

NCBI Quality ControlLinks
Alloprevotella
Ralstonia
Sphingomonas
Spirochaetota
Synergistota
ProteobacteriaProteobacteria

Revision editor(s): Nuerteye

Experiment 2


Needs review

Curated date: 2025/06/07

Curator: Nuerteye

Revision editor(s): Nuerteye

Differences from previous experiment shown

Subjects

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
Extrapulmonary tuberculosis Extrapulmonary tuberculosis,extrapulmonary tuberculosis
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Confirmed active pulmonary TB (sputum smear microscopy and Xpert MTB/RIF assay, per national guidelines).
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
Excluded if currently or recently receiving broad‑spectrum antibiotics or prescription mouthwashes.

Lab analysis

Statistical Analysis

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
increased
Simpson Estimator of species richness and species evenness: more weight on species evenness
increased
Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
increased
Richness Number of species
increased