Integrating next-generation sequencing and traditional tongue diagnosis to determine tongue coating microbiome

Abstract

Tongue diagnosis is a unique method in traditional Chinese medicine (TCM). This is the first investigation on the association between traditional tongue diagnosis and the tongue coating microbiome using next-generation sequencing. The study included 19 gastritis patients with a typical white-greasy or yellow-dense tongue coating corresponding to TCM Cold or Hot Syndrome respectively, as well as eight healthy volunteers. An Illumina paired-end, double-barcode 16S rRNA sequencing protocol was designed to profile the tongue-coating microbiome, from which approximately 3.7 million V6 tags for each sample were obtained. We identified 123 and 258 species-level OTUs that were enriched in patients with Cold/Hot Syndromes, respectively, representing "Cold Microbiota" and "Hot Microbiota". We further constructed the tongue microbiota-imbalanced networks associated with Cold/Hot Syndromes. The results reveal an important connection between the tongue-coating microbiome and traditional tongue diagnosis, and illustrate the potential of the tongue-coating microbiome as a novel holistic biomarker for characterizing patient subtypes.

Figure 1. TCM tongue diagnosis and tongue-coating appearance classification.

(A) An ancient instruction for tongue diagnosis recorded in Shang-han-dian-dian-jin, a TCM book compiled in the Ming Dynasty of China (1368–1644 AD). (B) Symptoms all over human body used as features for the TCM classification of Cold and Hot Syndromes; the tongue-coating feature is highly important in clinical practice. (C) Sampling images of tongue coating from the centre of the tongue, an area regarded as reflecting conditions of the “spleen-stomach” in the traditional tongue diagnosis. (D) Typical tongue-coating appearances: normal tongue coating of healthy control examples (upper), white-greasy tongue coating of Cold Syndrome examples (middle), and yellow-dense tongue coating of Hot Syndrome examples (lower). (E) Principal Component Analysis (PCA) of the tongue-coating images. The healthy controls, Cold Syndrome patients and Hot Syndrome patients are distributed in separate regions, indicating that the three classes are distinguishable based on their tongue-coating images.

Figure 2. 16S rRNA sequencing analysis and taxonomy classification of the tongue-coating microbiome at the phylum level.

(A) The flowchart of sequence preprocessing, quality control and chimera detection. (B) Relative abundances of the dominant phyla in samples. (C) Relative abundances of the rare phyla in samples.

Figure 3. 16S rRNA diversity analysis detected significant differences in the tongue-coating microbiome between gastritis patients with Cold and Hot Syndromes.

(A) Alpha diversity rarefaction curves of all 27 samples based on species-level OTUs. (B) PCoA plot of the between-sample Jaccard matrix of all 27 samples. (C) AMOVA results of the between-sample Jaccard distance matrix of the 19 gastritis patients. The F-statistic is the ratio of the mean square among groups within the groups. (D) AMOVA results of the between-sample unweighted Unifrac distance matrix of the 19 gastritis patients.

Figure 4. Tongue microbiota-imbalanced networks of genus-classifiable OTUs in (A) the Cold Microbiota and (B) the Hot Microbiota.

OTUs as nodes are marked with the genus names (some with more precise species names), and edges with Pearson's correlation coefficient (PCC) > 0.85 are indicated.