Study on tongue coating microbes of bitter taste, sticky and greasy taste in chronic atrophic gastritis

doi:10.19852/j.cnki.jtcm.20221108.004

Abstract

Abstract:

OBJECTIVE: To objectively reveal the relationship between tongue coating microbes and bitter taste, sticky and greasy taste in chronic atrophic gastritis (CAG) patients.
METHODS: 16S rRNA high-throughput sequencing was used to detect bacterial diversity and community composition of tongue coating microbes from samples of CAG patients. LEfSe algorithm was used for discovering the different tongue coating microbes in CAG patients with or without bitter taste, also that in CAG patients with or without sticky and greasy taste.
RESULTS: We respectively compared the features of tongue coating microbes in bitter taste, sticky and greasy taste of CAG patients. At the genus level, 25 tongue coating microbes were significantly different in CAG patients with bitter taste or without bitter taste; 17 tongue coating microbes were significantly different in CAG patients with sticky and greasy taste or without sticky and greasy taste. Campylobacter and Rothia were closely related to CAG patients with bitter taste. Enterococcus, Serratia, Leptotrichia and Selenomonas were closely related to CAG patients with stick and greasy taste.
CONCLUSION: Campylobacter and Rothia possibly contribute to bitter taste of CAG patients, and Enterococcus, Serratia, Leptotrichia and Selenomonas contribute to stick and greasy taste of CAG patients, which is potential for the diagnosis and treatment of CAG.

Key words: gastritis, atrophic, taste, Campylobacter, Enterococcus, Serratia, Leptotrichia, Selenomonas

CAO Yang, GAI Xiao, ZHENG Yixin, Guo Benqiong, NIU Jingbin, QIAN Peng, LING Jianghong, LIU Guoping, ZHENG Yu. Study on tongue coating microbes of bitter taste, sticky and greasy taste in chronic atrophic gastritis[J]. Journal of Traditional Chinese Medicine, 2023, 43(1): 160-167.

Figures/Tables 6

Figure 1 Comparison on tongue coating microbes in CAG patients with or without bitter taste A: cladogram plot. Red nodes indicated significantly enriched bacterial colony with significant impact in CAG patients with bitter taste, and blue nodes indicated significantly enriched bacterial colony with significant impact in CAG patients without bitter taste. Light yellow nodes indicated bacterial colony without significant difference in both CAG patients with bitter taste and without bitter taste. B: LDA discriminant analysis. Red bar represented the bacterial colony enriched in CAG patients with bitter taste; blue bar represented the bacterial colony enriched in the CAG patients without bitter taste. CAG: chronic atrophic gastritis; LDA: linear discriminative analysis.

Figure 2 Heatmap of spearman correlation between tongue coating microbes and bitter taste A: twenty-six genera and bitter taste. The horizontal coordinates in the graph was tongue coating microbes, the vertical coordinates were the symptom of bitter taste. Red indicated positive correlation, blue indicated negative correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001). B: eleven positively correlated genera and bitter taste. The horizontal coordinates in the graph was tongue coating microbes, the vertical coordinates were the symptom of bitter taste. Red indicated a strong positive correlation, blue indicated a weak positive correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001). C: fifteen negatively correlated genera and bitter taste. The horizontal coordinates in the graph was tongue coating microbes, the vertical coordinates were the symptom of bitter taste. Red indicated weak negative correlation and blue indicated strong negative correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001).

Figure 3 Comparison on tongue coating microbes in CAG patients with or without sticky and greasy taste A: cladogram plot. red nodes indicated significantly enriched bacterial colony with significant impact in CAG patients with sticky and greasy taste, and blue nodes indicated significantly enriched bacterial colony with significant impact in CAG patients without sticky and greasy taste. light yellow nodes indicated bacterial colony without significant difference in both CAG patients with or without sticky and greasy taste. B: LDA discriminant analysis. red bar represented the bacterial colony enriched in CAG patients with sticky and greasy taste; blue bar represented the bacterial colony enriched in CAG patients with sticky and greasy taste. CAG: chronic atrophic gastritis; LDA: linear discriminative analysis.

Figure 4 Heatmap of the spearman correlation between tongue coating microbes and sticky greasy taste A: seventeen genera and sticky greasy taste: The horizontal coordinates in the graph was tongue coating microbes, the vertical coordinates were the symptom of sticky greasy taste. Red indicated positive correlation, blue indicated negative correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001). B: four positively correlated genera and sticky greasy taste. The horizontal coordinates were tongue coating microbes; the vertical coordinates were the symptom of sticky greasy taste. Red indicated a strong positive correlation, blue indicates a weak positive correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001). C: 13 negatively correlated genera and sticky greasy taste. The horizontal coordinates in the graph was tongue coating microbes, the vertical coordinates were the symptoms of sticky greasy taste. Red indicated weak negative correlation and blue indicates strong negative correlation. The darker color indicated stronger correlation. The magnitude of significant P values was marked with a, b, c (0.01 < aP ≤ 0.05, 0.001 < bP ≤ 0.01, cP ≤ 0.001).

Figure S1 Heatmap of KEGG function on the tongue coating microbes enriched in the group with or without bitter taste

Figure S2 Heatmap of KEGG function on the tongue coating microbes enriched in the group with or without sticky and greasy taste

References 34

1	Park YH, Kim N. Review of atrophic gastritis and intestinal metaplasia as a premalignant lesion of gastric cancer. J Cancer Prev 2015; 20: 25-40. DOI PMID
2	Du Y, Bai Y, Xie P, et al. Chronic gastritis in China: a national multicenter survey. BMC gastroenterology 2014; 14: 1-9.
3	Wang YQ. Diagnostics of Traditional Chinese Medicine. Beijing: Gao Deng Jiao Yu Chu Ban She, 2016: 28-9.
4	Zhu CM, Gu WJ, Yang DC, et al. Study on the characteristics of TCM tongue image in patients with chronic ttrophic gastritis. Shi Jie Ke Xue Ji Shu-Zhong Yi Yao Xian Dai Hua 2020; 22: 1595-600.
5	Jiang B, Liang X, Chen Y, et al. Erratum: integrating next-generation sequencing and traditional tongue diagnosis to determine tongue coating microbiome. Sci Rep 2012; 2: 344-67.
6	Li H, Wang WH, Guo CR, et al. Analysis of microbial community structure of tongue coating at different taxonomic levels. Zhong Hua Zhong Yi Yao Za Zhi 2020; 35: 6298-301.
7	Hu J, Han S, Chen Y, et al. Variations of tongue coating micro-biota in patients with gastric cancer. Biomed Res Int 2015; 1-7.
8	Lu H, Ren Z, Li A, et al. Tongue coating microbiome data distinguish patients with pancreatic head cancer from healthy controls. J Oral Microbiol 2019; 11: 1-12.
9	Dixon MF, Genta RM, Yardley JH, et al. Classification and grading of gastritis. The updated Sydney System. International Workshop on the Histopathology of Gastritis, Houston 1994. Am J Surg Pathol 1996; 20: 1161-81.
10	Chen S, Zhou Y, Chen Y, et al. FASTP: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018; 34: i884-90.
11	Magoč T, Salzberg SL. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 2011; 27: 2957-63. DOI PMID
12	Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 2013; 10: 996-8. DOI PMID
13	Stackebrandt E, Goebel BM. Taxonomic note: a place for DNA-DNA reassociation and 16S rRNA sequence analysis in the present species definition in bacteriology. Int J Syst Bacteriol 1994; 44: 846-9.
14	Wang Q, Garrity GM, Tiedje JM, et al. Naive bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 2007; 73: 5261-7.
15	Ye J, Cai X, Yang J, et al. Bacillus as a potential diagnostic marker for yellow tongue coating. Sci Rep 2016; 6: 1-9.
16	Wang HW, Li L, Li FF, et al. Specific bacteria of tongue coating in patients with chronic atrophic gastritis. Zhong Guo Wei Sheng Tai Xue Za Zhi 2018; 30: 497-501.
17	Wang HW, Li L, Li FF, et al. Study on the compositions of dominant bacteria and determination of E-adhesion factor and ICAM-1 in chronic atrophic gastritis. Zhong Guo Zhong Xi Yi Jie He Za Zhi 2018; 38:790-4.
18	O'Brien SJ. The consequences of campylobacter infection. Curr Opin Gastroenterol 2017; 33: 14-20.
19	Li R, Ma T, Gu J, et al. Imbalanced network biomarkers for Traditional Chinese Medicine syndrome in gastritis patients. Sci Rep 2013; 3: 1-7.
20	Cui J, Cui H, Yang M, et al. Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade. Protein Cell 2019; 10: 496-509. DOI PMID
21	Feng P, Jyotaki M, Kim A, et al. Regulation of bitter taste responses by tumor necrosis factor. Brain Behav Immunol 2015; 49: 32-42.
22	Zhang K, Kang JY, Chang RH, et al. Discussion on the pathogenesis of bitter taste in mouth. Zhejiang Zhong Yi Yao Da Xue Xue Bao 2019; 43: 653-6.
23	Si P, Fu Y, Ni S, et al. Epidemiological survey on prevalence and associated risk factors of bitter taste among inpatients from four grade 3A hospitals in Beijing. J Trad Chin Med Sci 2017; 4: 31-8.
24	Chen F, Fu YL, Zhang JJ. Experimental analysis of the correlation between bitter taste in liver disease and bile acid from oral saliva. Zhong Guo Shi Yong Nei Ke Za Zhi 2001; 21: 365-6.
25	Jiang T, Xu C, Liu H, et al. Linderae radix ethanol extract alleviates diet-induced hyperlipidemia by regulating bile acid metabolism through gut microbiota. Front Pharmacol 2021; 12: 1-13.
26	Luo JW, Lin CH, Zhu YB, et al. Association of tongue bacterial flora and subtypes of liver-fire hyperactivity syndrome in hypertensive patients. Evid Based Complement Alternat Med 2018; 2018: 1-10.
27	García-Solache M, Rice LB. The enterococcus: a model of adaptability to its environment. Clin Microbiol Rev 2019; 32: e00058-18.
28	Gupta V, Sharma S, Pal K, et al. Serratia, No longer an uncommon opportunistic pathogen - case series & review of literature. Infect Disord Drug Targets 2021; 21: e300821191666.
29	Correia PN, Carpenter GH, Osailan SM, et al. Acute salivary gland hypofunction in the duct ligation model in the absence of inflammation. Oral Dis 2008; 14: 520-8. DOI PMID
30	Tong NN. Preliminary study on saliva metabolome of dampness-heat accumulation of spleen in chronic gastritis. Guangzhou: Guangzhou TCM University, 2016: 25.
31	Eribe ERK, Paster BJ, Caugant DA, et al. Genetic diversity of Leptotrichia and description of Leptotrichia goodfellowii sp. nov. Int J Syst Evol Microbiol 2004; 54: 583-92.
32	Eribe ERK, Olsen I. Leptotrichia species in human infections II. J Oral Microbiol 2017; 9: 1-31.
33	Mcdaniel J, Mcdaniel S, Samiano B J, et al. Microbial screening reveals oral site-specific locations of the periodontal pathogen selenomonas noxia. Curr Issues Mol Biol 2021; 43: 353-64. DOI PMID
34	Melville SB, Michel TA, Macy JM. Pathway and sites for energy conservation in the metabolism of glucose by selenomonas ruminantium. J Bacteriol 1988; 170: 5298-304. PMID

Home

Online First

Author Center

Reviewer Center

Issues

Announcement

About Us