Analysis of the composition and phenotypes of intestinal flora in primary bacteriologically-confirmed pulmonary tuberculosis patients based on high-throughput sequencing of 16S rRNA V4 region

doi:10.3969/j.issn.1000-6621.2021.09.014

Abstract

Abstract:

Objective To study the differences of composition and phenotypes of intestinal flora between diagnosed pulmonary tuberculosis(PTB) patients and healthy individuals by using high-throughput sequencing technology and bio-informatics analysis. Methods PE 150 (pair-end 2×150 bp) sequencing scheme was used to sequence flora 16S rRNA gene V4 region from fresh stool samples of 29 primary bacteriologically-confirmed PTB patients (PTB group)and 28 healthy volunteers (healthy controls) at Changsha Central Hospital,University of South China from April 14, to December 28, 2020. Operational taxonomic units (OTU) were annotated by aligning with Silva database (Silva 128). QIIME software was used to calculate OTU level, α diversity index, β diversity index and relative abundance at phylum and genus levels, and to generate OTU level abundance grade curve (Ranked abundance). R software package “VennDiagram” was used to generate VennDiagram. R order “ggplot” was used to draw a horizontal bubble diagram. BugBase software was used to classify and compare 7 phenotypes of intestinal flora. Results For the α diversity index, the Shannon index of intestinal flora in the PTB group and the health controls were 4.24±1.71 and 5.64±0.85 respectively (t=3.889, P<0.01), Simpson index were (0.89 (0.80,0.94)) and (0.94 (0.90,0.96)) (Z=-3.256, P<0.01), Chao1 index were 1085.35±659.99 and 1844.04±658.95 (t=4.378, P<0.01), ACE index were 1091.64±666.93 and 1857.34±657.90 (t=4.403, P<0.01). The difference of β diversity between the PTB group and the healthy control group was statistically significant (R²=0.253, P<0.01).Twelve bacterial genera with significant differences between groups were found, which were mainly concentrated in Firmicutes (PTB group: 35.44%, control group: 51.55%, Z=-3.290,P<0.01). Phenotypic analysis showed that the relative abundance of anaerobic gene, intestinal gram-positive bacteria in the intestinal flora of the PTB group were lower than that of the health controls (21.80% vs 26.50%, Z=-3.080, P<0.01; 13.86% vs 17.75%, Z=-2.283, P<0.05). The relative abundance of intestinal gram-negative bacteria, intestinal facultative bacteria, oxidative stress tolerance bacteria and the ability of biofilm formation in the intestinal flora of the PTB group was higher than the health controls (15.14% vs 10.25%, Z=-2.283, P<0.05; 5.00% vs 0.59%, Z=-3.240, P<0.01; 3.10% vs 0.35%, Z=-2.075, P<0.05; 4.94% vs 1.19%, Z=-2.267, P<0.05). Conclusion The PTB group got changes in the composition of intestinal flora and bacterial phenotypes, which were mainly manifested as decrease in the diversity of the intestinal flora. The phenotypic changes were mainly caused by changes in the intestinal oxygen environment.

Key words: Tuberculosis,lung, Bacteria, 16S rRNA sequencing, Diversity, Phenotype

YI Yi-hang, YU Rong, SHI Guo-min, MA Xiao-hua, XIAO Si-fang, SHUI Jian, FAN Ren-hua, XIANG Yan-gen. Analysis of the composition and phenotypes of intestinal flora in primary bacteriologically-confirmed pulmonary tuberculosis patients based on high-throughput sequencing of 16S rRNA V4 region[J]. Chinese Journal of Antituberculosis, 2021, 43(9): 939-946. doi: 10.3969/j.issn.1000-6621.2021.09.014

Figures/Tables 7

指标	肺结核组	对照组	统计检验值	P值
年龄(岁, $x ¯$ ±s)	42.55±10.13	43.21±10.35	t=0.244	0.808
性别			χ²=0.211	0.710
男性(例/名)	9	10
女性(例/名)	20	18
BMI( $x ¯$ ±s)	20.92±1.46	21.00±1.46	t=-0.224	0.703
TG[mmol/L,M(Q₁,Q₃)]	1.35(1.14,1.55)	1.26(0.92,1.53)	Z=1.188	0.240
TC (mmol/L, $x ¯$ ±s)	3.86±0.66	4.90±0.71	t=-5.735	0.000
HDL (mmol/L, $x ¯$ ±s)	1.07±0.32	1.57±0.35	t=-5.557	0.000
LDL (mmol/L, $x ¯$ ±s)	2.23±0.54	2.75±0.65	t=-3.234	0.002
HDL/LDL( $x ¯$ ±s)	0.53±0.24	0.61±0.25	t=-1.251	0.216

α多样性指数	肺结核组	对照组	统计检验值	P值
Shannon( $x ¯$ ±s)	4.24±1.71	5.65±0.85	t=-3.889	0.000
Simpson[M(Q₁,Q₃)]	0.89(0.80,0.94)	0.94(0.90,0.96)	Z=-3.256	0.001
Chao1( $x ¯$ ±s)	1085.35±659.99	1844.04±658.95	t=4.378	0.000
ACE( $x ¯$ ±s)	1091.64±666.93	1857.34±657.90	t=4.403	0.000

References 31

[1]	World Health Organization. Global tuberculosis report 2020. Geneva:World Health Organization, 2020.
[2]	O’Hara AM, Shanahan F. The gut flora as a forgotten organ. EMBO Rep, 2006, 7(7):688-693. doi: 10.1038/sj.embor.7400731. doi: 10.1038/sj.embor.7400731 URL
[3]	Winglee K, Eloefadrosh EA, Gupta S, et al. Aerosol Mycobacterium tuberculosis Infection Causes Rapid Loss of Diversity in Gut Microbiota. PLoS One, 2014, 9(5):e97048. doi: 10.1371/journal.pone.0097048. doi: 10.1371/journal.pone.0097048 URL
[4]	Negi S, Pahari S, Bashir H, et al. Gut Microbiota Regulates Mincle Mediated Activation of Lung Dendritic Cells to Protect Against Mycobacterium tuberculosis. Front Immunol, 2019, 10(14):1142. doi: 10.3389/fimmu.2019.01142. doi: 10.3389/fimmu.2019.01142 URL
[5]	Namasivayam S, Kauffman KD, McCulloch JA, et al. Correlation between Disease Severity and the Intestinal Microbiome in Mycobacterium tuberculosis-Infected Rhesus Macaques. mBio, 2019, 10(3):e01018-e01019. doi: 10.1128/mBio.01018-19. doi: 10.1128/mBio.01018-19
[6]	中华人民共和国国家卫生和计划生育委员会. WS 288—2017肺结核诊断. 2017-11-09.
[7]	Shi N, Li N, Duan X, et al. Interaction between the gut microbiome and mucosal immune system(Review). Mil Med Res, 2017, 4:14. doi: 10.1186/s40779-017-0122-9. doi: 10.1186/s40779-017-0122-9 pmid: 28465831
[8]	Gao X, Cao Q, Cheng Y, et al. Chronic stress promotes colitis by disturbing the gut microbiota and triggering immune system response. Proc Natl Acad Sci USA, 2018, 115(13):E2960-E2969. doi: 10.1073/pnas.1720696115. doi: 10.1073/pnas.1720696115 URL
[9]	Wu J, Liu W, He L, et al. Sputum microbiota associated with new, recurrent and treatment failure tuberculosis. PLoS One, 2013, 8(12):e83445. doi: 10.1371/journal.pone.0083445. doi: 10.1371/journal.pone.0083445 URL
[10]	Grigor’eva IN. Gallstone Disease, Obesity and the Firmicutes/Bacteroidetes Ratio as a Possible Biomarker of Gut Dysbiosis. J Pers Med, 2020, 11(1):13. doi: 10.3390/jpm11010013. doi: 10.3390/jpm11010013 URL
[11]	Zhong H, Penders J, Shi Z, et al. Impact of early events and lifestyle on the gut microbiota and metabolic phenotypes in young school-age children. Microbiome, 2019, 7(1):2. doi: 10.1186/s40168-018-0608-z. doi: 10.1186/s40168-018-0608-z URL
[12]	Liu S, Li E, Sun Z, et al. Altered gut microbiota and short chain fatty acids in Chinese children with autism spectrum disorder. Sci Rep, 2019, 9(1):287. doi: 10.1038/s41598-018-36430-z. doi: 10.1038/s41598-018-36430-z URL
[13]	Vieira AT, Rocha VM, Tavares L, et al. Control of Klebsiella pneumoniae pulmonary infection and immunomodulation by oral treatment with the commensal probiotic Bifidobacterium longum 5(1A). Microbes Infec, 2016, 18(3):180-189. doi: 10.1016/j.micinf.2015.10.008. doi: 10.1016/j.micinf.2015.10.008 URL
[14]	Mendes E, Acetturi BG, Thomas AM, et al. Prophylactic Supplementation of Bifidobacterium longum 51A Protects Mice from Ovariectomy-Induced Exacerbated Allergic Airway Inflammation and Airway Hyperresponsiveness. Front Microbiol, 2017, 8:1732. doi: 10.3389/fmicb.2017.01732. doi: 10.3389/fmicb.2017.01732 URL
[15]	Chen D, Jin D, Huang S, et al. Clostridium butyricum, a butyrate-producing probiotic, inhibits intestinal tumor deve-lopment through modulating Wnt signaling and gut microbiota. Cancer Lett, 2020, 469:456-467. doi: 10.1016/j.canlet.2019.11.019. doi: 10.1016/j.canlet.2019.11.019 URL
[16]	余今菁, 李欢, 胡邱宇, 等. 基于高通量测序技术的溃疡性结肠炎患者肠道菌群多样性研究. 华中科技大学学报(医学版), 2018, 47(4):460-465. doi: 10.3870/j.issn.1672-0741.2018. doi: 10.3870/j.issn.1672-0741.2018
[17]	Keshavarzian A, Green SJ, Engen PA, et al. Colonic bacterial composition in Parkinson’s disease. Mov Disord, 2015, 30(10):1351-1360. doi: 10.1002/mds.26307. doi: 10.1002/mds.26307 URL
[18]	Naidoo CC, Nyawo GR, Sulaiman I, et al. Anaerobe-enriched gut microbiota predicts pro-inflammatory responses in pulmonary tuberculosis. EBioMedicine, 2021, 67:103374. doi: 10.1016/j.ebiom.2021.103374. doi: 10.1016/j.ebiom.2021.103374 URL
[19]	Berni Canani R, Di Costanzo M, Leone L. The epigenetic effects of butyrate: potential therapeutic implications for clinical practice(Review). Clin Epigenetics, 2012, 4(1):4. doi: 10.1186/1868-7083-4-4. doi: 10.1186/1868-7083-4-4 URL
[20]	Vinolo MA, Rodrigues HG, Nachbar RT, et al. Regulation of inflammation by short chain fatty acids. Nutrients, 2011, 3(10):858-876. doi: 10.3390/nu3100858. doi: 10.3390/nu3100858 pmid: 22254083
[21]	Feng Q, Chen WD, Wang YD. Gut Microbiota:An Integral Moderator in Health and Disease. Front Microbiol, 2018, 9(92):151. doi: 10.3389/fmicb.2018.00151. doi: 10.3389/fmicb.2018.00151 URL
[22]	O’Keefe SJ. Diet,microorganisms and their metabolites,and colon cancer(Review). Nat Rev Gastroenterol Hepatol, 2016, 13(12):691-706. doi: 10.1038/nrgastro.2016.165. doi: 10.1038/nrgastro.2016.165 URL
[23]	Weir TL, Manter DK, Sheflin AM, et al. Stool microbiome and metabolome differences between colorectal cancer patients and healthy adults. PLoS One, 2013, 8(8):e70803. doi: 10.1371/journal.pone.0070803. doi: 10.1371/journal.pone.0070803 URL
[24]	Segal LN, Clemente JC, Li Y, et al. Anaerobic Bacterial Fermentation Products Increase Tuberculosis Risk in Antire-troviral-Drug-Treated HIV Patients. Cell Host Microbe, 2017, 21(4):530-537. doi: 10.1016/j.chom.2017.03.003. doi: 10.1016/j.chom.2017.03.003 URL
[25]	Lachmandas E, van den Heuvel CN, Damen MS, et al. Diabetes Mellitus and Increased Tuberculosis Susceptibility: The Role of Short-Chain Fatty Acids. J Diabetes Res, 2016, 2016:6014631. doi: 10.1155/2016/6014631. doi: 10.1155/2016/6014631 pmid: 27057552
[26]	Wang J, Jia H. Metagenome-wide association studies: fine-mining the microbiome. Nat Rev Microbiol, 2016, 14(8):508-522. doi: 10.1038/nrmicro.2016.83. doi: 10.1038/nrmicro.2016.83 pmid: 27396567
[27]	Singhal R, Shah YM. Oxygen battle in the gut: Hypoxia and hypoxia-inducible factors in metabolic and inflammatory responses in the intestine(Review). J Biol Chem, 2020, 295(30):10493-10505. doi: 10.1074/jbc.REV120.011188. doi: 10.1074/jbc.REV120.011188 pmid: 32503843
[28]	Ramakrishnan SK, Shah YM. Role of Intestinal HIF-2α in Health and Disease. Annu Rev Physiol, 2016, 78:301-325. doi: 10.1146/annurev-physiol-021115-105202. doi: 10.1146/annurev-physiol-021115-105202 pmid: 26667076
[29]	Gentile CL, Weir TL. The gut microbiota at the intersection of diet and human health. Science, 2018, 362:776-780. doi: 10.1126/science.aau5812. doi: 10.1126/science.aau5812 URL
[30]	Yang B, Wang Y, Qian PY. Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinformatics, 2016, 17:135. doi: 10.1186/s12859-016-0992-y. doi: 10.1186/s12859-016-0992-y pmid: 27000765
[31]	Pichler M, Coskun ÖK, Ortega-Arbulú AS, et al. A 16S rRNA gene sequencing and analysis protocol for the Illumina MiniSeq platform. Microbiologyopen, 2018, 7(6):e00611. doi: 10.1002/mbo3.611. doi: 10.1002/mbo3.611 URL

属水平	相对丰度(%)		Z值	P值
属水平	肺结核组	对照组	Z值	P值
双歧杆菌属	0.08	0.09	-2.270	0.023
副拟杆菌属	0.67	0.37	-1.963	0.050
臭杆菌属	0.04	0.06	-2.149	0.032
梭状芽孢杆菌属	0.03	0.08	-4.031	0.000
Anaerostipes	0.07	0.03	-2.944	0.003
劳特氏菌属	0.15	0.21	-2.339	0.019
粪球菌属	0.08	0.32	-4.039	0.000
毛螺菌属	0.52	1.62	-4.039	0.000
罗氏菌属	0.28	1.01	-3.816	0.000
粪杆菌属	1.09	1.32	-2.235	0.025
瘤胃球菌属	0.28	0.57	-2.969	0.003
真杆菌属	0.94	0.01	-2.077	0.038

表型	基因相对丰度(%)		Z值	P值
表型	肺结核组	对照组	Z值	P值
厌氧菌	21.80	26.50	-3.080	0.002
革兰氏阳性菌	13.86	17.75	-2.283	0.022
兼性菌	5.00	0.59	-3.240	0.001
革兰氏阴性菌	15.14	10.25	-2.283	0.022
需氧菌	1.04	0.57	-1.309	0.191
生物膜形成	4.94	1.19	-2.267	0.023
氧化胁迫	3.10	0.35	-2.075	0.038
移动组件	7.24	3.42	-1.261	0.207
潜在致病性	16.83	14.76	-1.628	0.103