烟草暴露与人类肠道菌群相关性探究
Exploring the Correlation between Tobacco Exposure and Human Intestinal Flora
DOI: 10.12677/AMB.2023.122009, PDF, HTML, XML, 下载: 232  浏览: 533 
作者: 吴 雯:江阴市第三人民医院肿瘤科,江苏 江阴;周天翔*, 怀惠英, 柳晓帅, 秦 科, 缪振丰, 赵 轶, 陈育苗:江阴市第三人民医院消化内科,江苏 江阴
关键词: 烟草暴露肠道菌群16S rDNABlautia菌属Roseburia菌属Tobacco Exposure Intestinal Flora 16S rDNA Blautia Roseburia
摘要: 目的:探究不同烟草暴露程度健康人群的肠道菌群是否存在差异,挖掘烟草暴露对肠道菌群的影响。方法:收集符合纳入标准的各组人员的粪便样本,其中烟草暴露组(>400年支) (A组) 17例、烟草暴露组(<400年支) (B组) 16例、长期二手烟暴露组(C组) 16例、戒烟组(戒烟6月以上) (D组) 14例及无烟草暴露组(E组) 17例。对上述每份粪便样本进行16S rDNA高通量测序,随后进行OTU分析及物种注释、样本复杂度分析、多样本比较分析及组间群落结构差异显著性分析。结果:A组、B组、D组在菌种组成更为接近,而C组、E组在菌种组成上更为接近。但各组间菌群丰富度、多样性、群落分布无显著异常。在门水平上,部分组间在厚壁菌门(Firmicutes)及变形菌门(Proteobacteria)存在差异(p < 0.05)。在属水平上,Agathobacter属、Blautia属、f_Lachnospiraceae_Unclassified属、Roseburia属、Subdoligranulum属在不同组间存在统计学差异(p < 0.05)。结论:不同程度的烟草暴露人群的肠道菌群多样性未发现明确的差异,但Blautia菌属及Roseburia菌属与烟草暴露程度呈负相关性,值得进一步研究。
Abstract: Objective: To investigate whether there are differences in the intestinal flora of healthy people with different levels of tobacco exposure, and explore the effects of tobacco exposure on the intestinal flora. Methods: Fecal samples were collected from 80 volunteers, including 17 cases in the tobacco exposure group (Smoking Index > 400) (group A), 16 cases in the tobacco exposure group (Smoking Index < 400) (group B), 16 cases in the long-term second-hand smoke exposure group (group C), 14 cases in the smoking cessation group (more than 6 months) (group D) and 17 cases in the non-tobacco exposure group (group E). Each of the above fecal samples was analyzed by 16SrDNA, and OTU analysis and species annotation, Alpha diversity, Beta diversity, significance analysis of community structure differences were performed between groups. Results: Groups A, B and D were closer in intestinal flora composition, while groups C and E were closer in composition. There were no significant abnormalities in the richness, diversity and community distribution of the intestinal flora between the groups. At the Phylum level,there were significantly differences between the some groups of Firmicutes and Proteobacteria (p < 0.05). At the Genus level, there were significantly differences between the different groups of Agathobacter, Blautia, f_Lachnospi- raceae_Unclassified, Roseburia, and Subdoligranulum (p < 0.05). Conclusions: Despite there were no clear differences were found in the diversity of intestinal flora in people with different levels of tobacco exposure so far, but the genus Blautia and Roseburia were inversely correlated with tobacco exposure, which is worth further exploring.
文章引用:吴雯, 周天翔, 怀惠英, 柳晓帅, 秦科, 缪振丰, 赵轶, 陈育苗. 烟草暴露与人类肠道菌群相关性探究[J]. 微生物前沿, 2023, 12(2): 71-82. https://doi.org/10.12677/AMB.2023.122009

1. 引言

在全球范围内,吸烟引起的各种健康问题,已经成为人类共同面对的重大挑战。目前研究发现 [1] ,吸烟与诸多疾病存在着明确因果关系,在烟草燃烧产生的烟雾中,已经发现至少70种已知致癌物 [2] 。除了对传统认知内呼吸系统疾病、心脑血管疾病、Ⅱ型糖尿病及生殖发育等存在影响,吸烟亦显著提高食管癌、胰腺癌、胃癌、结肠癌等发病率。此外,二手烟问题日益严重,非自主吸烟者暴露于烟气中,同样面对相关疾病的发病风险,且二手烟没有安全标准,即使是短暂的接触也会造成伤害 [3] ,WHO于2019年发布报告称每年约有800余万人因烟草暴露丧生,其中超120万人属于被动暴露 [4] 。而目前,三手烟 [1] (烟草烟雾吸附在物体表面残留,可存在数月之久,持续危害健康)及电子烟的出现,更是对健康产生重大威胁,尤其是儿童、青少年及孕产妇。近年来,肠道菌群与疾病发生发展关系的研究日新月异。目前认为,肠道菌群可通过代谢产物 [5] 、内分泌系统及免疫系统 [6] 参与人体生理、病理过程。相关证据表明 [7] ,吸烟会导致肠道菌群生态失调,从而打破免疫稳态 [6] 、影响肠道抗菌作用 [8] 、诱导肠黏膜炎症或直接改变菌群组成 [8] 。本研究拟应用16S rDNA高通量测序技术,来不同程度烟草暴露人群的肠道菌群是否存在差异,为进一步明确烟草暴露–肠道菌群–疾病间关系做初步探索,为吸烟者应用益生菌减少烟草相关疾病发生提供思路。

2. 资料与方法

2.1. 一般资料

于2021年01月~2021年06月在江苏省江阴市面向社会招募志愿者80名。按烟草暴露情况分为5组,分别为:A组吸烟 > 400年支,共17人(均为男性),年龄32~57岁,平均年龄43.47 ± 8.917岁;B组吸烟 < 400年支,共16人(男性14人,女性2人),年龄29~57岁,平均年龄43.63 ± 9.493岁;C组长期二手烟暴露,共16人(男性0人,女性16人),年龄24~57岁,平均年龄44.38 ± 11.88岁;D组戒烟6月以上,共14人(均为男性),年龄28~59岁,平均年龄47.36 ± 10.49岁;E组无烟草暴露,共17人(男性8人,女性9人),年龄23~57岁,平均年龄38.06 ± 11.74岁;年龄资料为计数资料,经方差分析,各组年龄总体均数无统计学差异(F = 1.606, p = 0.181) (见表1);性别资料为定性资料,各组间经卡方检验,各组间性别存在统计学差异(χ2 = 53.23, p < 0.0001) (见表2),但众所周知,我国目前吸烟人群仍以男性群体为主,目前尚无针对不同性别健康人群肠道菌群差异的研究。纳入标准:a) 年龄18~60周岁;b) 民族:汉族;c) 18.5 ≤ BMI < 25 Kg/m2;排除标准:a) 存在明确的肠道菌群相关疾病;b) 3月内使用抗菌药物及益生菌制剂;c) 长期酗酒;d) 长期服用糖皮质激素、免疫抑制剂及滥用药物。本实验获得江阴市第三人民医院伦理委员会批准,所有受试对象均知情同意。

Table 1. Comparison of age among groups

表1. 各组间年龄情况比较

Table 2. Comparison of gender among groups

表2. 各组间性别情况比较

2.2. 方法

a) 所有志愿者于06:00~08:00用粪便采集管收集新鲜粪便标本3 g左右,随即由专人将标本置于−80℃冰箱保存。DNA提取/QC使用DNA提取试剂盒从样本中提取DNA,使用Equalbit dsDNA HS Assay Kit检测DNA浓度。PCR扩增及文库构建 以20~30 ng DNA为模板,使用PCR引物扩增原核生物16S rDNA上包括V3及V4的2个高度可变区。然后再通过PCR向16S rDNA的PCR产物末端加上带有Index的接头,以便进行NGS测序,用磁珠进行文库纯化后通过酶标仪检测浓度和琼脂糖凝胶电泳检测片段大小。上机测序 通过酶标仪检测文库浓度。将文库定量到10 nmol/L,按Illumina MiSeq/Novaseq (Illumina, San Diego, CA, USA)仪器使用说明书进行PE250/FE300双端测序,由MiSeq/Novaseq自带的MiSeq Control Software (MCS)/Novaseq Control Software (NCS)读取序列信息。数据分析 双端测序得到的正反向reads首先进行两两拼接,过滤拼接结果中含有N的序列,保留序列长度大于200 bp的序列。经过质量过滤,去除嵌合体序列,最终得到的序列用于OTU聚类,使用VSEARCH (1.9.6)进行序列聚类(序列相似性设为97%),比对的16S rRNA参考数据库是Silva 138。然后利用RDP classifier (Ribosomal Database Program )贝叶斯算法对OTU的代表性序列进行物种分类学分析,并在不同物种分类水平下统计每个样本的群落组成。再对样本进行OTU分析、样品多样性分析、物种注释、样品组间显 著性差异分析及LEfSe分析。b) 对80位志愿者粪便样本进行Illumina MiSeq测序,得到双端序列数据,将两条序列进行比对,根据比对的末端重叠区进行拼接,拼接时保证至少有20 bp的重叠区,去除拼接结果中含有N的序列;去除引物和接头序列,去除两端质量值低于20的碱基,去除长度小于200 bp的序列;将上面拼接过滤后的序列与数据库进行比对,去除其中的嵌合体序列(chimera sequence),得到最终的有效数据。c) 对以上优化后的有效序列提取unique序列,保留各序列的重复次数,去除重复次数为1的unique序列;按照97%相似性对unique序列(重复次数 > 1)进行OTU聚类,在聚类过程中进一步去除嵌合体序列,得到OTU的代表序列。将所有优化后的序列与OTU代表序列进行比对,与OTU代表序列相似性在97%以上的序列为同一OTU,统计生成OTU丰度表。对样本进行OTU分析以及物种注释。然后通过α多样性分析比较不同组间肠道菌群多样性及丰度差异,主要从ACE、Chaos、Shannon及Simpson指数反映肠道菌群丰富度及多样性。对各组进行Kruskal-Wallis检验,分析组间物种多样性差异是否显著。利用β多样性分析方法进一步阐述烟草暴露对健康人群肠道菌群分布的影响。最后分别在门、属水平上进行各组间成分差异分析。

2.3. 统计学分析

使用R(3.6.3)进行数据统计分析及绘图。Qiime(1.9.1)采用对序列进行随机抽样,以进行OTU分析,并分别计算各α多样性指数(ACE、Chao1、Shannon、Simpson、goods Coverage),采取Kruskal-Wallis检验进行分析组间物种多样性差异是否显著;基于OTU分析结果绘制Rank-Abundance曲线;基于Brary-Curtis距离矩阵进行PCoA作图分析;基于Beta多样性距离矩阵,进行NMDS分析;借助线上工具 (http://metastats.cbcb.umd.edu/)在属水平上进行Metastats分析。p值 < 0.05认为具有统计意义。

3. 结果

3.1. 测序数据质量优化

最终共获得5,825,413条优化后有效序列,平均长度为450.21025 bp,主要集中在420~470 bp之间(见图1)。

3.2. OTU分析及物种注释

根据OTU丰度,绘制热图(丰度最高的30个OTU) (见图2)及韦恩图(见图3)。可见有烟草暴露者(A组、B组、C组、D组)特有OTU数(306个、284个、248个、230个)均较无烟草暴露者(E组) 375个减少。根据OTU丰度结果,与Silva数据库比对后可得到各水平下的菌种分布,在门及属水平上绘制物种分布柱状图及热图(见图4图5)。可见A组、B组、D组在菌种组成更为接近,而C组、E组在菌种组成上更为接近。

Figure 1. Distribution of effective sequence lengths

图1. 有效序列长度分布统计

Figure 2. Heatmap of OTU abundance clustering

图2. OTU丰度聚类热图

Figure 3. Venn diagram of OTUs

图3. OTU韦恩图

(A) (B)

Figure 4. Bar chart of species distribution ((A) Phylum level; (B) Genus level)

图4. 物种分布柱状图((A) 门水平;(B) 属水平)

(A) (B)

Figure 5. Heatmap of species distribution ((A) Phylum level; (B) Genus level)

图5. 物种分布热图((A) 门水平;(B) 属水平)

3.3. 肠道菌群多样性分析

各组间ACE、Chaos、Shannon及Simpson指数结果如图(见图6)所示。各组间肠道菌群的丰富度、多样性均无显著差异。ns,p ≥ 0.05;*,p < 0.05;**,p < 0.01;***,p < 0.001。

Figure 6. Alpha diversity analysis at the genus level (ns, p ≥ 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001)

图6. 在属水平上的α多样性分析(ns, p ≥ 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001)

3.4. 肠道菌群分布分析

利用β多样性分析方法进一步阐述烟草暴露对健康人群肠道菌群分布的影响。基于Brary-Crtis距离矩阵通过PCoA (见图7(A))和NMDS (见图7(B))对β多样性进行分析,五组间肠道菌群群落分布无显著异常。

(A) (B)

Figure 7. Beta diversity analysis among groups

图7. 组间β多样性分析

3.5. 组间群落结构差异分析

在门水平上发现,部分组间在厚壁菌门(Firmicutes)及变形菌门(Proteobacteria)存在差异(见图8)。其中B组与C组、A + B混合组与C组、A + B混合组与C+E混合组、C组与A + B + D混合组、A + B + D混合组与C + E混合组间厚壁菌门丰度存在统计学差异,可见不论目前仍在吸烟或已戒烟,直接烟草暴露均会导致肠道内厚壁菌门丰度减少;在A组与C组、C组与D组、A+B混合组与C组、C组与A + B + D混合组、A + B + D混合组与C + E混合组间变形菌门丰度存在统计学差异,不论目前仍在吸烟或已戒烟,直接烟草暴露均会导致肠道内变形菌门丰度增加。ns,p ≥ 0.05;*,p < 0.05;**,p < 0.01;***,p < 0.001。

Figure 8. Comparison of microbial community composition at the phylum level (top five in terms of abundance)

图8. 门水平菌群组成比较(丰度占比前五)

在属水平上,对各组平均相对丰度大于0.01的菌属,借助Metastats进行差异性分析。相较于A组,C组中显著升高的菌属是罕见小球菌属(Subdoligranulum, p = 0.034);显著下降的菌属有f__Lachnospiraceae_Unclassified (p = 0.024)相较于A组,D组中显著升高的菌属是布劳特氏菌属(Blautia, p = 0.017);无显著下降的菌属。相较于A组,E组中显著升高的菌属是布劳特氏菌属(Blautia, p = 0.013)、Agathobacter菌属(p = 0.025);无显著下降的菌属。相较于B组,D组中显著升高的菌属是布劳特氏菌属(Blautia, p = 0.039);显著下降的菌属有罗氏菌属(Roseburia, p = 0.003)。相较于B组,E组中显著升高的菌属是布劳特氏菌属(Blautia, p = 0.034)、Agathobacter菌属(p = 0.041);无显著下降的菌属。相较于C组,D组中显著下降的菌属有罗氏菌属(Roseburia, p = 0.001)、Agathobacter菌属(p = 0.006);无显著升高的菌属。相较于D组,E组中显著升高的菌属是Agathobacter菌属(p = 0.001)、罗氏菌属(Roseburia, p = 0.012);无显著下降菌属。其中A组与B组间、B组与C组间、C组与E组间,均无显著差异菌属。

4. 讨论

越来越多的研究证明,以细菌为主的肠道微生物,在人体的生理及病理进程中发挥着至关重要的作用。本实验通过16S rDNA检测技术对不同烟草暴露程度人群的粪便进行分析,发现在肠道菌群组成上,直接烟草暴露与间接或无烟草暴露者存在差异,但在菌群的多样性及丰富度上并无显著差异,群落分布特征亦无显著差异。但在各组间,Blautia菌属及Roseburia菌属存在差异,且与烟草暴露存程度存在相关性。

4.1. 布劳特氏菌属(Blautia)

本研究发现,相较于吸烟者,戒烟者、不吸烟者的Blautia菌属丰度显著升高。Blautia属毛螺菌属科,目前研究认为其具有减轻炎症反应、改善代谢疾病及对特定微生物的抗菌活性等特性 [9] 。目前为止,共发现了20种菌种隶属于Blautia菌属 [10] 。研究表明,MRG-PMF1菌株可促进5,7-二甲氧基黄酮(5,7-DMF)和5,7,4-三甲氧基黄酮(5,7,4-TMF)分别转化为具有生物活性的蛹虫草素和芹菜素,具有抗癌、抗炎等作用 [11] ;且能够将姜黄素代谢为对HCT116结肠癌细胞具有高毒性的去甲基姜黄素 [12] 。AUH-JLD56菌株可将牛蒡子苷元特异高效的转换为(-)-3’-去甲基牛蒡子苷元,在培养约16 h后生物转化量达到最高,平均生物转化率可达96.3%,其中当底物牛蒡子苷元浓度 ≤ 2.4 mmol/L时,牛蒡子苷元的平均生物转化率为95.6%;2.4 mmol/L ≤ 浓度 < 3.6 mmol/L时,牛蒡子苷元的平均生物转化率为90.5%,后者具有良好的自由基清除活性 [13] 。但某些Blautia菌种可对初级胆汁酸进行7-α-脱羟基反应,产生次级胆汁酸,后者作为结肠癌的致癌物,在肠癌患者及溃疡性结肠炎患者粪便中浓度较高 [14] 。

作为核心菌属,Blautia对宿主的生理功能失调,如肥胖、糖尿病、癌症及各种炎症性疾病有显著相关性。Blautia菌属可产生NRPs、PKs、赛克肽类、羊毛硫肽类、细菌素、β-丙内酯等次级产物。一项日本的横断面研究显示,Blautia的丰度与内脏脂肪堆积呈明显的负相关性 [15] 。一项在肥胖人群中的研究亦显示在为期3周的低卡高蛋白饮食后,肠道中Blautia丰度显著升高 [16] 。Noriho等人研究发现,Blautia丰度在2型糖尿病患者肠道内显著降低 [17] 。研究发现,Blautia可在肠道产生醋酸,它可能通过激活GPR41和GPR43来抑制胰岛素信号和脂肪细胞中的脂肪积累,进而促进其他组织中未结合的脂质和葡萄糖的代谢,从而缓解与肥胖有关的疾病 [18] 。Blautia菌属作为一种共生的专性厌氧菌属,通过上调肠道调节T细胞和产生短链脂肪酸 [19] ,在维持肠道环境平衡和预防炎症方面发挥着重要作用。在克罗恩病及结肠癌患者的肠道菌群中,Blautia菌属丰度菌显著减少 [17] [20] 。在肠易激综合征患者中,Blautia菌属丰度通常不会增加 [21] [22] 。然而,与健康人相比,在溃疡性结肠炎患者的粪便中发现了更高丰度的Blautia菌属 [23] 。有意思的是,对于克罗恩病患者,我们都要求患者必须戒烟,而对于溃疡性结肠炎,有研究表明吸烟可能对疾病进展有保护作用,Blautia可能在同类疾病中发挥了不同作用,相关动物实验也表明,Blautia可通过调节TNF-α、claudin-1、occludin等来改善肠黏膜屏障功能,从而减轻溃疡性结肠炎模型小鼠症状 [24] ,而对于克罗恩病,目前尚无相关研究。

4.2. 罗氏菌属(Roseburia)

本研究发现,戒烟者的Roseburia菌属丰度显著低于不吸烟者、二手烟以及低剂量烟草暴露者(<400年支)。Roseburia菌属包括Roseburia intestinalis,R. hominis,R. inulinivorans,R. faecis和R. cecicola等5种革兰氏阳性杆菌。目前研究认为,其具有代谢饮食成分,产生短链脂肪酸,特别是丁酸盐,从而影响结肠运动、免疫维持以及抗炎特性。新生儿体内并无Roseburia菌属定植,人类体内的Roseburia可能源自母乳 [25] 。在肠道内,Roseburia通过分解人类无法消化的碳水化合物来生成短链脂肪酸 [26] ,尤其是能产生大量的丁酸盐以及甲酸盐、乳酸盐,而产生的短链脂肪酸通过增加促炎细胞因子来调节肠道生理和免疫稳态 [27] 。短链脂肪酸可通过调节T细胞促进肠道内和全身的抗炎反应 [28] ,其中丁酸盐可通过抑制NF-κB的激活,从而抑制结肠粘膜中促炎症细胞因子的mRNA表达,从而发挥免疫调节和抗炎作用 [29] 。已有文献报道,Roseburia菌属与炎症性肠病、肠易激综合征及结肠癌等有密切关系。在炎症性肠病患者粪便中,丁酸盐含量显著降低,对应的Roseburia菌属水平亦降低 [30] ,有报道则显示,在克罗恩病患者肠道内,Roseburia菌属丰度显著降低 [31] [32] 。对于便秘患者,肠道内Roseburia菌属丰度显著降低 [33] ,在治疗缓解后丰度则与健康人群、腹泻为主的肠易激综合征无明显差异 [34] 。对于结肠癌患者,有研究报道,在存在淋巴结转移的患者肠道内,Roseburia菌属丰度显著增加 [35] 。Roseburia菌属产生的丁酸盐可以通过减少原癌基因c-Myc来抑制miR-92a转录,从而提高抑癌基因p57水平 [36] 。此外,多项研究表明,Roseburia菌属与肝硬化、肝性脑病、肥胖、糖尿病、代谢综合征、帕金森综合征、系统性红斑狼疮等均有一定相关性。综上可见,Roseburia菌属主要通过代谢产生丁酸盐从在维持宿主肠道健康及调节免疫发挥重要作用。

于君等人研究发现 [37] ,暴露于香烟烟雾的小鼠肿瘤发病率和细胞增殖显著增增加,通过宏基因组学分析发现在暴露于烟雾的小鼠存在肠道菌群失调,表现为Eggerthella lenta的富集以及Parabacteroides distasonis和Lactobacillus spp.的耗竭,通过代谢组学分析显示,暴露于烟雾的小鼠结肠中的胆汁酸代谢物增加,尤其是牛磺脱氧胆酸(TDCA),与Eggerthella lenta呈正相关;此外,暴露于烟雾的小鼠表现出增强的致癌MAPK/ERK信号(TDCA下游靶标)以及肠粘膜屏障功能受损。在本实验中,各组Eggerthella菌属丰度均小于可检测值;无烟草暴露、戒烟组Parabacteroides菌属、Lactobacillus菌属丰度均值高于烟草暴露、二手烟暴露组,但组间差异无统计学意义。

在本实验中,通过16S rDNA检测,并未发现不同烟草暴露程度人群存在显著的肠道菌群组成差异,菌群的多样性及丰富度上亦无显著差异,但在属水平上发现,Blautia菌属及Roseburia菌属丰度在更多烟草暴露人群普遍低于更少的烟草暴露人群。Blautia菌属及Roseburia菌属均通过其代谢产物对宿主肠道及免疫系统进行干预。进一步通过多组学联合,探究Blautia及Roseburia菌属在宿主体内的代谢产物及作用机制,可以为研究烟草相关疾病发病机制、治疗手段提供新的思路。

NOTES

*通讯作者。

参考文献

[1] DeCarlo, P.F., Avery, A.M. and Waring, M.S. (2018) Thirdhand Smoke Uptake to Aerosol Particles in the Indoor Environment. Science Advances, 4, eaap8368.
https://doi.org/10.1126/sciadv.aap8368
[2] Georgiopoulos, G., Oikonomou, D., Pateras, K., et al. (2021) A Bayesian Meta-Analysis on Early Tobacco Exposure and Vascular Health: From Childhood to Early Adulthood. European Journal of Preventive Cardiology, 28, 1315-1322.
https://doi.org/10.1177/2047487319883557
[3] Office on Smoking and Health (US) (2006) The Health Consequences of Involuntary Exposure to Tobacco Smoke: A Report of the Surgeon General. Centers for Disease Control and Prevention (US), Atlanta.
[4] Zhang, K., Tartarone, A., Pérez-Ríos, M., et al. (2022) Smoking Burden, MPOWER, Future Tobacco Control and Real-World Challenges in China: Reflections on the WHO Report on the Global Tobacco Epidemic 2021. Translational Lung Cancer Research, 11, 117-121.
https://doi.org/10.21037/tlcr-22-27
[5] Lv, L.-J., Li, S.-H., Li, S.-C., et al. (2019) Early-Onset Preeclampsia Is Associated with Gut Microbial Alterations in Antepartum and Postpartum Women. Frontiers in Cellular and Infection Microbiology, 9, Article 224.
https://doi.org/10.3389/fcimb.2019.00224
[6] Nakashima, K., Kimura, S., Ogawa, Y., et al. (2018) Chitin-Based Barrier Immunity and Its Loss Predated Mucus- Colonization by Indigenous Gut Microbiota. Nature Communications, 9, Article No. 3402.
https://doi.org/10.1038/s41467-018-05884-0
[7] Lee, S.H., Yun, Y., Kim, S.J., et al. (2018) Association between Cigarette Smoking Status and Composition of Gut Microbiota: Population-Based Cross-Sectional Study. Journal of Clinical Medicine, 7, Article No. 282.
https://doi.org/10.3390/jcm7090282
[8] Shanahan, E.R., Shah, A., Koloski, N., et al. (2018) Influence of Cigarette Smoking on the Human Duodenal Mucosa-Associated Microbiota. Microbiome, 6, Article No. 150.
https://doi.org/10.1186/s40168-018-0531-3
[9] Kalyana Chakravarthy, S., Jayasudha, R., Sai Prashanthi, G., et al. (2018) Dysbiosis in the Gut Bacterial Microbiome of Patients with Uveitis, an Inflammatory Disease of the Eye. Indian Journal of Microbiology, 58, 457-469.
https://doi.org/10.1007/s12088-018-0746-9
[10] Liu, X., Mao, B., Gu, J., et al. (2021) Blautia—A New Functional Genus with Potential Probiotic Properties? Gut Microbes, 13, Article 1875796.
https://doi.org/10.1080/19490976.2021.1875796
[11] Kim, M., Kim, N. and Han, J. (2014) Metabolism of Kaempferia parviflora Polymethoxyflavones by Human Intestinal bacterium Bautia sp. MRG-PMF1. Journal of Agricultural and Food Chemistry, 62, 12377-12383.
https://doi.org/10.1021/jf504074n
[12] Burapan, S., Kim, M. and Han, J. (2017) Curcuminoid Demethylation as an Alternative Metabolism by Human Intestinal Microbiota. Journal of Agricultural and Food Chemistry, 65, 3305-3310.
https://doi.org/10.1021/acs.jafc.7b00943
[13] Liu, M.-Y., Li, M., Wang, X.-L., et al. (2013) Study on Human Intestinal Bacterium Blautia sp. AUH-JLD56 for the Conversion of Arctigenin to (-)-3’-Desmethylarctigenin. Journal of Agricultural and Food Chemistry, 61, 12060- 12065.
https://doi.org/10.1021/jf403924c
[14] Vaughn, B.P., Kaiser, T., Staley, C., et al. (2019) A Pilot Study of Fecal Bile Acid and Microbiota Profiles in Inflammatory Bowel Disease and Primary Sclerosing Cholangitis. Clinical and Experimental Gastroenterology, 12, 9-19.
https://doi.org/10.2147/CEG.S186097
[15] Ozato, N., Saito, S., Yamaguchi, T., et al. (2019) Blautia Genus Associated with Visceral Fat Accumulation in Adults 20-76 Years of Age. NPJ Biofilms and Microbiomes, 5, Article No. 28.
https://doi.org/10.1038/s41522-019-0101-x
[16] Pataky, Z., Genton, L., Spahr, L., et al. (2016) Impact of Hypocaloric Hyperproteic Diet on Gut Microbiota in Overweight or Obese Patients with Nonalcoholic Fatty Liver Disease: A Pilot Study. Digestive Diseases and Sciences, 61, 2721-2731.
https://doi.org/10.1007/s10620-016-4179-1
[17] Iida, N., Mizukoshi, E., Yamashita, T., et al. (2019) Overuse of Antianaerobic Drug Is Associated with Poor Postchemotherapy Prognosis of Patients with Hepatocellular Carcinoma. International Journal of Cancer, 145, 2701-2711.
https://doi.org/10.1002/ijc.32339
[18] Kimura, I., Ozawa, K., Inoue, D., et al. (2013) The Gut Microbiota Suppresses Insulin-Mediated Fat Accumulation via the Short-Chain Fatty Acid Receptor GPR43. Nature Communications, 4, Article No. 1829.
https://doi.org/10.1038/ncomms2852
[19] Zhernakova, D.V., Le, T.H., Kurilshikov, A., et al. (2018) Individual Variations in Cardiovascular-Disease-Related Protein Levels Are Driven by Genetics and Gut Microbiome. Nature Genetics, 50, 1524-1532.
https://doi.org/10.1038/s41588-018-0224-7
[20] Grases-Pintó, B., Abril-Gil, M., Castell, M., et al. (2019) Influence of Leptin and Adiponectin Supplementation on Intraepithelial Lymphocyte and Microbiota Composition in Suckling Rats. Frontiers in Immunology, 10, Article 2369.
https://doi.org/10.3389/fimmu.2019.02369
[21] Liu, F., Li, J., Guan, Y., et al. (2019) Dysbiosis of the Gut Microbiome Is Associated with Tumor Biomarkers in Lung Cancer. International Journal of Biological Sciences, 15, 2381-2392.
https://doi.org/10.7150/ijbs.35980
[22] Chauhan, N.S., Pandey, R., Mondal, A.K., et al. (2018) Western Indian Rural Gut Microbial Diversity in Extreme Prakriti Endo-Phenotypes Reveals Signature Microbes. Frontiers in Microbiology, 9, Article 118.
https://doi.org/10.3389/fmicb.2018.00118
[23] Nishino, K., Nishida, A., Inoue, R., et al. (2018) Analysis of Endoscopic Brush Samples Identified Mucosa-Associated Dysbiosis in Inflammatory Bowel Disease. Journal of Gastroenterology, 53, 95-106.
https://doi.org/10.1007/s00535-017-1384-4
[24] Wang, J., Zhang, C., Guo, C. and Li, X. (2019) Chitosan Ameliorates DSS-Induced Ulcerative Colitis Mice by Enhancing Intestinal Barrier Function and Improving Microflora. International Journal of Molecular Sciences, 20, Article No. 5751.
https://doi.org/10.3390/ijms20225751
[25] Jost, T., Lacroix, C., Braegger, C.P., Rochat, F. and Chassard, C. (2014) Vertical Mother-Neonate Transfer of Maternal Gut Bacteria via Breastfeeding. Environmental Microbiology, 16, 2891-2904.
https://doi.org/10.1111/1462-2920.12238
[26] Liu, T., Liang, X., Lei, C., et al. (2020) High-Fat Diet Affects Heavy Metal Accumulation and Toxicity to Mice Liver and Kidney Probably via Gut Microbiota. Frontiers in Microbiology, 11, Article 1604.
https://doi.org/10.3389/fmicb.2020.01604
[27] Lachmandas, E., van den Heuvel, C.N., Damen, M.S., et al. (2016) Diabetes Mellitus and Increased Tuberculosis Susceptibility: The Role of Short-Chain Fatty Acids. Journal of Diabetes Research, 2016, Article ID: 6014631.
https://doi.org/10.1155/2016/6014631
[28] Nguyen, T.D., Prykhodko, O., Fåk Hållenius, F. and Nyman, M. (2019) Monovalerin and Trivalerin Increase Brain Acetic Acid, Decrease Liver Succinic Acid, and Alter Gut Microbiota in Rats Fed High-Fat Diets. European Journal of Nutrition, 58, 1545-1560.
https://doi.org/10.1007/s00394-018-1688-z
[29] Faas, M.M., Liu, Y., Borghuis, T., et al. (2019) Microbiota Induced Changes in the Immune Response in Pregnant Mice. Frontiers in Immunology, 10, Article 2976.
https://doi.org/10.3389/fimmu.2019.02976
[30] Schirmer, M., Franzosa, E.A., Lloyd-Price, J., et al. (2018) Dynamics of Metatranscription in the Inflammatory Bowel Disease Gut Microbiome. Nature Microbiology, 3, 337-346.
https://doi.org/10.1038/s41564-017-0089-z
[31] Dong, R., Bai, M., Zhao, J., et al. (2020) A Comparative Study of the Gut Microbiota Associated with Immunoglobulin a Nephropathy and Membranous Nephropathy. Frontiers in Cellular and Infection Microbiology, 10, Article 557368.
https://doi.org/10.3389/fcimb.2020.557368
[32] Harrison, C.A., Laubitz, D., Ohland, C.L., et al. (2018) Microbial Dysbiosis Associated with Impaired Intestinal Na+/H+ Exchange Accelerates and Exacerbates colitis in Ex-Germ Free Mice. Mucosal Immunology, 11, 1329-1341.
https://doi.org/10.1038/s41385-018-0035-2
[33] Strati, F., Cavalieri, D., Albanese, D., et al. (2017) New Evidences on the Altered Gut Microbiota in Autism Spectrum Disorders. Microbiome, 5, Article No. 24.
https://doi.org/10.1186/s40168-017-0242-1
[34] Gibson, G.R. (2022) Commentary on: Prebiotic Effects: Metabolic and Health Benefits. British Journal of Nutrition, 127, 554-555.
https://doi.org/10.1017/S0007114521004608
[35] Thomas, A.M., Jesus, E.C., Lopes, A., et al. (2016) Tissue-Associated Bacterial Alterations in Rectal Carcinoma Patients Revealed by 16S rRNA Community Profiling. Frontiers in Cellular and Infection Microbiology, 6, Article 179.
https://doi.org/10.3389/fcimb.2016.00179
[36] Hu, S., Liu, L., Chang, E.B., Wang, J.-Y. and Raufman, J.-P. (2015) Butyrate Inhibits Pro-Proliferative miR-92a by Diminishing c-Myc-Induced miR-17-92a Cluster Transcription in Human Colon Cancer Cells. Molecular Cancer, 14, Article No. 180.
https://doi.org/10.1186/s12943-015-0450-x
[37] Bai, X., Wei, H., Liu, W., et al. (2022) Cigarette Smoke Promotes Colorectal Cancer through Modulation of Gut Microbiota and Related Metabolites. Gut, 71, 2439-2450.
https://doi.org/10.1136/gutjnl-2021-325021