Analysis of Gut Flora in a Mouse Model of
Esophageal Squamous Cell Carcinoma in Situ

doi:10.12114/j.issn.1007-9572.2021.01.501

Abstract

Abstract: Background

With the application and development of high-throughput sequencing-based approaches for gut flora analysis, increasing studies have confirmed that gut flora is closely related to the development of various cancers. The relationship of gut floras with esophageal squamous cell carcinoma (ESCC) , a common cancer threatening the health of Chinese people, has attracted extensive attention.

Objective

To analyze the diversity of gut floras between a rat model of ESCC in situ and normal mice, to identify the carcinoma-specific bacterial genus in ESCC.

Methods

From August 2020 to May 2021, 20 female SPF C57BL/6 mice were randomly and equally divided into control group and model group. Rice in control group were routinely fed and given ordinary drinking water for 32 weeks, and those in model group were routinely fed and received water containing 0.1 mg/ml cancer inducer 4-nitroquinoline-1-oxide for 16 weeks, and then only fed with ordinary drinking water for another 16 weeks. Stool samples of both groups were collected, and DNA in faeces was extracted and amplified by PCR, followed by high-throughput sequencing. The obtained sequencing data were divided into operational taxonomic units (OTU) based on the similarity between sequences. The α-diversity, β-diversity and species abundance were further analyzed according to species annotation.

Results

No death occurred in the experiment, and the modeling of ESCC was successfully established in model group. Compared with control group, the proportion of Bacteroidota and Firmicutes increased, while the proportion of Verrucomicrobiota and Proteobacteria decreased in model group. Analysis showed that the α-diversity measured by Shannon Diversity Index in model group was lower than that of control group (P<0.05) . As for β-diversity analysis, PCoA diagram showed that the gut floras of control and model groups clustered in different quadrants, suggesting a significant discrepancy between the groups (t=22.444, P=0.004) . At the phylum level, the abundances of unidentified bacteria, Cyanobacteria, Elusimicrobia and Campilobacterota were higher in model group than those in control group (P<0.05) . At the genus level, the abundances of Prevotellaceae_UCG-003, Bacteroides and Lachnospiraceae_NK4A136_group, Ruminococcus, Prevotellaceae_UCG-001, Prevotella, Colidextribacter, Lachnospiraceae_UCG-006 were higher while those of Romboutsia and Turicibacter were lower in model group than those in control group (P<0.05) . LEfSe analysis showed that, at the genus level, the abundances of Prevotellaceae_UCG-003, Escherichia-Shigella, Bacteroides, Lachnospiraceae_NK4A136_group were increased significantly in model group (P<0.05) , but the abundance of Romboutsia was increased significantly in control group DZ (P<0.05) .

Conclusion

By comparing the composition of gut flora, we identified the rat model of ESCC may have less diversity of species and specially differentiated bacteria, and Prevotellaceae_UCG-003, Bacteroides, Lachnospiraceae_NK4A136_group, and Romboutsia could be used as biomarkers for ESCC.

Key words: Esophageal squamous cell carcinoma, Esophageal neoplasms, Gastrointestinal microbiome, Intestinal flora, Mice, Biodiversity

摘要： 背景

随着肠道菌群高通量测序技术的应用与发展，越来越多的研究证实肠道菌群与多种肿瘤的发生、发展密切相关。食管鳞癌是威胁我国人民健康的常见肿瘤，其与肠道菌群的关系备受关注。

目的

分析比较食管鳞癌原位模型小鼠与正常小鼠肠道菌群的多样性，筛选出食管鳞癌特异性改变的菌属。

方法

2020年8月至2021年5月，将20只雌性SPF级C57BL/6小鼠适应性喂养1周后随机分为对照组（DZ组）和模型组（MX组），每组10只。DZ组小鼠常规喂养并给予普通饮用水32周，MX组小鼠按照造模方法常规喂养并给予含0.1 mg/ml诱癌剂4-硝基喹啉-1-氧化物（4NQO）的饮用水喂养16周，之后给予普通饮用水喂养至32周。收集两组小鼠粪便，提取DNA，应用聚合酶链式反应（PCR）扩增后进行高通量测序，获得的测序数据聚类成为基于序列间相似度的分类操作单元（OTU），并根据物种注释情况进一步分析Alpha多样性、Beta多样性、物种丰度。

结果

两组小鼠在实验过程中未出现死亡，MX组小鼠均造模成功。MX组与DZ组相比，拟杆菌门（Bacteroidota）及厚壁菌门（Firmicutes）比例升高，而疣微菌门（Verrucomicrobiota）及变形菌门（Proteobacteria）比例降低。Alpha多样性结果显示，MX组小鼠肠道菌群Shannon指数低于DZ组（P<0.05）。Beta多样性分析中PCoA图显示，MX组与DZ组样本分别聚集在不同的象限，相距较远，样本间多样性差异较大（t=22.444，P=0.004）。在门水平，MX组Unidentified_ Bacteria、蓝细菌（Cyanobacteria）、易感微生物（Elusimicrobia）、弯曲杆菌（Campilobacterota）丰度高于DZ组（P<0.05）。在属水平，MX组普雷沃菌科_UCG-003（Prevotellaceae_UCG-003）、拟杆菌属（Bacteroides）、毛螺菌科NK4A136组（Lachnospiraceae_NK4A136_group）、瘤胃球菌属（Ruminococcus）、普雷沃菌科_UCG-001（Prevotellaceae_UCG-001）、普雷沃菌属（Prevotella）、大肠埃希菌（Colidextribacter）、毛螺菌科_UCG-006（Lachnospiraceae_UCG-006）丰度高于DZ组，罗姆布茨菌（Romboutsia）、土杆菌属（Turicibacter）丰度低于DZ组（P<0.05）。LEfSe分析结果显示，在属水平上，Prevotellaceae_UCG-003、埃希菌-志贺菌属（Escherichia-Shigella）、Bacteroides、Lachnospiraceae_ NK4A136_group在MX组丰度增高（P<0.05）；而Romboutsia丰度在DZ组增高（P<0.05）。

结论

食管鳞癌原位模型小鼠与正常小鼠相比肠道菌群物种多样性降低，存在特异性差异菌属，其中Prevotellaceae_UCG-003、Bacteroides、Lachnospiraceae_NK4A136_group和Romboutsia可作为食管鳞癌诊断的生物标志物。

关键词: 食道鳞癌, 食管肿瘤, 胃肠道微生物组, 肠道菌群, 小鼠, 生物多样性

CLC Number:

R735.1R378.2

ZHANG Yushuang, YU Fuyang, WU Zhongbing, WANG Yiran, LI Jing.

Analysis of Gut Flora in a Mouse Model of Esophageal Squamous Cell Carcinoma in Situ [J]. Chinese General Practice, 2022, 25(08): 945-951.

张玉双,于富洋,吴忠冰等. 食管鳞癌原位模型小鼠肠道菌群分析[J]. 中国全科医学, 2022, 25(08): 945-951. DOI: 10.12114/j.issn.1007-9572.2021.01.501.

Figures/Tables 10

Figure 1 HE staining results of esophagus tissues two groups of mice

Figure 2 Venn diagram of intestinal flora between two groups of mice

Figure 3 Relative abundance of species at phylum level intestinal flora of mice between two groups

Figure 4 Rarefaction curve of intestinal flora between two groups of mice

Table 1 Shannon Diversity Index analysis of intestinal flora between two groups of mice

组别	只数	Shannon指数
DZ组	10	5.807±0.461
MX组	10	4.549±1.450
t值		2.614
P值		0.024

Figure 5 PCoA diagram of Beta diversity in intestinal flora between two groups of mice

Figure 6 Analysis of similarities （ANOSIM） of intestinal flora between two groups of mice

Figure 7 Differential species analysis of intestinal flora at the phylum level between two groups of mice

Figure 8 Differential species analysis of intestinal flora at the genus level between two groups of mice

Figure 9 Histogram of LEfSe analysis of intestinal flora between two groups of mice

References 26

[1]	SUNG H, FERLAY J, SIEGEL R L，et al. Global cancer statistics 2020：GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin，2021，71(3):209-249. DOI:10.3322/caac.21660.
[2]	刘宗超，李哲轩，张阳，等. 2020全球癌症统计报告解读[J]. 肿瘤综合治疗电子杂志，2021，7(2):1-13. DOI:10.12151/JMCM.2021.02-01.
[3]	GAO S G, LI S G, MA Z K，et al. Presence of Porphyromonas gingivalis in esophagus and its association with the clinicopathological characteristics and survival in patients with esophageal cancer[J]. Infect Agent Cancer，2016，11:3. DOI:10.1186/s13027-016-0049-x.
[4]	ZHAO Q F, YANG T, YAN Y F，et al. Alterations of oral microbiota in Chinese patients with esophageal cancer[J]. Front Cell Infect Microbiol，2020，10:541144. DOI:10.3389/fcimb.2020.541144.
[5]	王丽群，庞日朝，胡晓敏，等. 肠道菌群对色氨酸代谢的影响研究进展[J]. 中国比较医学杂志，2021，31(4):129-136. DOI:10.3969/j.issn.1671-7856.2021.04.019.
[6]	RAKOFF-NAHOUM S, FOSTER K R, COMSTOCK L E. The evolution of cooperation within the gut microbiota[J]. Nature，2016，533(7602):255-259. DOI:10.1038/nature17626.
[7]	YATSUNENKO T, REY F E, MANARY M J，et al. Human gut microbiome viewed across age and geography[J]. Nature，2012，486(7402):222-227. DOI:10.1038/nature11053.
[8]	MAYNARD C L, ELSON C O, HATTON R D，et al. Reciprocal interactions of the intestinal microbiota and immune system[J]. Nature，2012，489(7415):231-241. DOI:10.1038/nature11551.
[9]	WU Y L, CHEN Y N, LU Y F，et al. Structural features，interaction with the gut microbiota and anti-tumor activity of oligosaccharides[J]. RSC Adv，2020，10(28):16339-16348. DOI:10.1039/d0ra00344a.
[10]	LV J, JIA Y T, LI J，et al. Gegen Qinlian Decoction enhances the effect of PD-1 blockade in colorectal cancer with microsatellite stability by remodelling the gut microbiota and the tumour microenvironment[J]. Cell Death Dis，2019，10(6):415. DOI:10.1038/s41419-019-1638-6.
[11]	BULLMAN S, PEDAMALLU C S, SICINSKA E，et al. Analysis of Fusobacterium persistence and antibiotic response in colorectal cancer[J]. Science，2017，358(6369):1443-1448. DOI:10.1126/science.aal5240.
[12]	ROUTY B, LE CHATELIER E, DEROSA L，et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors[J]. Science，2018，359(6371):91-97. DOI:10.1126/science.aan3706.
[13]	EUN C S, KIM B K, HAN D S，et al. Differences in gastric mucosal microbiota profiling in patients with chronic gastritis，intestinal Metaplasia，and gastric cancer using pyrosequencing methods[J]. Helicobacter，2014，19(6):407-416. DOI:10.1111/hel.12145.
[14]	MA C, HAN M J, HEINRICH B，et al. Gut microbiome-mediated bile acid metabolism regulates liver cancer via NKT cells[J]. Science，2018，360(6391):eaan5931. DOI:10.1126/science.aan5931.
[15]	GOPALAKRISHNAN V, SPENCER C N, NEZI L，et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients[J]. Science，2018，359(6371):97-103. DOI:10.1126/science.aan4236.
[16]	MATSON V, FESSLER J, BAO R Y，et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients[J]. Science，2018，359(6371):104-108. DOI:10.1126/science.aao3290.
[17]	COUGNOUX A, DALMASSO G, MARTINEZ R，et al. Bacterial genotoxin colibactin promotes colon tumour growth by inducing a senescence-associated secretory phenotype[J]. Gut，2014，63(12):1932-1942. DOI:10.1136/gutjnl-2013-305257.
[18]	CHENG W T, KANTILAL H K, DAVAMANI F. The mechanism of Bacteroides fragilis toxin contributes to colon cancer formation[J]. Malays J Med Sci，2020，27(4):9-21. DOI:10.21315/mjms2020.27.4.2.
[19]	SIVAN A, CORRALES L, HUBERT N，et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy[J]. Science，2015，350(6264):1084-1089. DOI:10.1126/science.aac4255.
[20]	位俊敏，李锐锋，杨冬阳，等. 食管鳞癌患者唾液菌群的研究[J]. 中山大学学报（医学科学版），2020，41(2):313-320. DOI:10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2020.0043.
[21]	DENG Y L, TANG D R, HOU P F，et al. Dysbiosis of gut microbiota in patients with esophageal cancer[J]. Microb Pathog，2021，150:104709. DOI:10.1016/j.micpath.2020.104709.
[22]	DEJEA C M, FATHI P, CRAIG J M，et al. Patients with familial adenomatous polyposis harbor colonic biofilms containing tumorigenic bacteria[J]. Science，2018，359(6375):592-597. DOI:10.1126/science.aah3648.
[23]	KEKU T O, DULAL S, DEVEAUX A，et al. The gastrointestinal microbiota and colorectal cancer[J]. Am J Physiol Gastrointest Liver Physiol，2015，308(5):G351-363. DOI:10.1152/ajpgi.00360.2012.
[24]	WANG T T, CAI G X, QIU Y P，et al. Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers[J]. ISME J，2012，6(2):320-329. DOI:10.1038/ismej.2011.109.
[25]	ZHANG Z C, CAO H Y, SONG N，et al. Long-term hexavalent chromium exposure facilitates colorectal cancer in mice associated with changes in gut microbiota composition[J]. Food Chem Toxicol，2020，138:111237. DOI:10.1016/j.fct.2020.111237.
[26]	SEOL M, LEE Y R, KIM K M，et al. The difference of the gut microbiota of gastric cancer in relation to Helicobacter pylori negativity and positivity[J]. J Clin Oncol，2019，37(4_):10. DOI:10.1200/jco.2019.37.4_suppl.10.