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

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.

Subtractive Proteomics and Immuno-informatics Approaches for Multi-peptide Vaccine Prediction Against Klebsiella oxytoca and Validation Through In Silico Expression.

Klebsiella oxytoca is a gram-negative bacterium. It is opportunistic in nature and causes hospital acquired infections. Subtractive proteomics and reverse vaccinology approaches were employed to screen out the best proteins for vaccine designing. Whole proteome of K. oxytoca strain ATCC 8724, consisting of 5483 proteins, was used for designing the vaccine. Total 1670 cytotoxic T lymphocyte (CTL) epitope were predicted through NetCTL while 1270 helper T lymphocyte (HTL) epitopes were predicted through IEDB server. The epitopes were screened for non-toxicity, allergenicity, antigenicity and water solubility. After epitope screening 300 CTL and 250 HTL epitopes were submitted to IFN-γ epitope server to predict their Interferon-γ induction response. The selected IFN-γ positive epitopes were tested for their binding affinity with MHCI-DRB1 by MHCPred. The 15 CTL and 13 HTL epitopes were joined by linkers AAY and GPGPG respectively in vaccine construct. Chain C of Pam3CSK4 (PDB ID; 2Z7X) was linked to the vaccine construct as an adjuvant. A 450aa long vaccine construct was submitted to I-TASSER server for 3D structure prediction. Thirteen Linear B cells were predicted by ABCPred server and 10 sets of discontinues epitopes for 3D vaccine structure were predicted by DiscoTope server. The modeled 3D vaccine construct was docked with human Toll-like receptor 2 (PDB ID: 6NIG) by PatchDock. The docked complexes were refined by FireDock. The selected docked complex showed five hydrogen bonds and one salt bridge. The vaccine sequence was reverse transcribed to get nucleotide sequence for In silico cloning. The reverse transcribed sequence strand was cloned in pET28a(+) expression vector. A clone containing 6586 bp was constructed including the 450 bp of query gene sequence.