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Deep sequencing reveals microbiota dysbiosis of tongue coat in patients with liver carcinoma

View Article: PubMed Central - PubMed

ABSTRACT

Liver carcinoma (LC) is a common malignancy worldwide, associated with high morbidity and mortality. Characterizing microbiome profiles of tongue coat may provide useful insights and potential diagnostic marker for LC patients. Herein, we are the first time to investigate tongue coat microbiome of LC patients with cirrhosis based on 16S ribosomal RNA (rRNA) gene sequencing. After strict inclusion and exclusion criteria, 35 early LC patients with cirrhosis and 25 matched healthy subjects were enrolled. Microbiome diversity of tongue coat in LC patients was significantly increased shown by Shannon, Simpson and Chao 1 indexes. Microbiome on tongue coat was significantly distinguished LC patients from healthy subjects by principal component analysis. Tongue coat microbial profiles represented 38 operational taxonomic units assigned to 23 different genera, distinguishing LC patients. Linear discriminant analysis (LDA) effect size (LEfSe) reveals significant microbial dysbiosis of tongue coats in LC patients. Strikingly, Oribacterium and Fusobacterium could distinguish LC patients from healthy subjects. LEfSe outputs show microbial gene functions related to categories of nickel/iron_transport, amino_acid_transport, energy produced system and metabolism between LC patients and healthy subjects. These findings firstly identify microbiota dysbiosis of tongue coat in LC patients, may providing novel and non-invasive potential diagnostic biomarker of LC.

No MeSH data available.


Related in: MedlinePlus

Bacterial diversity clustering by combining unweighted and weighted UniFrac PCoA of tongue coat microbiota.(a) Unweighted UniFrac (qualitative); (b) Weighted UniFrac (qualitative). Each symbol represents a sample (blue, LCT; green, HT); the variance explained by the PCs is indicated in parentheses on the axes. LCT, liver cancer patients tongue coat; HT, healthy subjects tongue coat.
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f2: Bacterial diversity clustering by combining unweighted and weighted UniFrac PCoA of tongue coat microbiota.(a) Unweighted UniFrac (qualitative); (b) Weighted UniFrac (qualitative). Each symbol represents a sample (blue, LCT; green, HT); the variance explained by the PCs is indicated in parentheses on the axes. LCT, liver cancer patients tongue coat; HT, healthy subjects tongue coat.

Mentions: The unweighted (quantitative) (Fig. 2a) and weighted (qualitative) (Fig. 2b) UniFrac PCA plots, which measure the phylogenetic similarities between microbial communities, shows that the LCT microbiota differs from that of the HT. Similar results were obtained using Principal Coordinate Analysis (PCoA) using the Hellinger distance, Jensen-Shannon Divergence (JSD) analysis, and Spearman coefficient distance methods (Fig. S1).


Deep sequencing reveals microbiota dysbiosis of tongue coat in patients with liver carcinoma
Bacterial diversity clustering by combining unweighted and weighted UniFrac PCoA of tongue coat microbiota.(a) Unweighted UniFrac (qualitative); (b) Weighted UniFrac (qualitative). Each symbol represents a sample (blue, LCT; green, HT); the variance explained by the PCs is indicated in parentheses on the axes. LCT, liver cancer patients tongue coat; HT, healthy subjects tongue coat.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5015078&req=5

f2: Bacterial diversity clustering by combining unweighted and weighted UniFrac PCoA of tongue coat microbiota.(a) Unweighted UniFrac (qualitative); (b) Weighted UniFrac (qualitative). Each symbol represents a sample (blue, LCT; green, HT); the variance explained by the PCs is indicated in parentheses on the axes. LCT, liver cancer patients tongue coat; HT, healthy subjects tongue coat.
Mentions: The unweighted (quantitative) (Fig. 2a) and weighted (qualitative) (Fig. 2b) UniFrac PCA plots, which measure the phylogenetic similarities between microbial communities, shows that the LCT microbiota differs from that of the HT. Similar results were obtained using Principal Coordinate Analysis (PCoA) using the Hellinger distance, Jensen-Shannon Divergence (JSD) analysis, and Spearman coefficient distance methods (Fig. S1).

View Article: PubMed Central - PubMed

ABSTRACT

Liver carcinoma (LC) is a common malignancy worldwide, associated with high morbidity and mortality. Characterizing microbiome profiles of tongue coat may provide useful insights and potential diagnostic marker for LC patients. Herein, we are the first time to investigate tongue coat microbiome of LC patients with cirrhosis based on 16S ribosomal RNA (rRNA) gene sequencing. After strict inclusion and exclusion criteria, 35 early LC patients with cirrhosis and 25 matched healthy subjects were enrolled. Microbiome diversity of tongue coat in LC patients was significantly increased shown by Shannon, Simpson and Chao 1 indexes. Microbiome on tongue coat was significantly distinguished LC patients from healthy subjects by principal component analysis. Tongue coat microbial profiles represented 38 operational taxonomic units assigned to 23 different genera, distinguishing LC patients. Linear discriminant analysis (LDA) effect size (LEfSe) reveals significant microbial dysbiosis of tongue coats in LC patients. Strikingly, Oribacterium and Fusobacterium could distinguish LC patients from healthy subjects. LEfSe outputs show microbial gene functions related to categories of nickel/iron_transport, amino_acid_transport, energy produced system and metabolism between LC patients and healthy subjects. These findings firstly identify microbiota dysbiosis of tongue coat in LC patients, may providing novel and non-invasive potential diagnostic biomarker of LC.

No MeSH data available.


Related in: MedlinePlus