Please wait a minute...
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

邮发代号 80-967

2019 Impact Factor: 3.421

Frontiers of Medicine  2022, Vol. 16 Issue (2): 263-275   https://doi.org/10.1007/s11684-022-0921-6
  本期目录
Integrated analysis of gut microbiome and host immune responses in COVID-19
Xiaoguang Xu1, Wei Zhang1,2, Mingquan Guo3, Chenlu Xiao4, Ziyu Fu1, Shuting Yu1, Lu Jiang1, Shengyue Wang1, Yun Ling3, Feng Liu1, Yun Tan1(), Saijuan Chen1()
1. Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
2. School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
3. Shanghai Public Health Clinical Center, Shanghai 201508, China
4. Department of Laboratory Medicine, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
 全文: PDF(2537 KB)   HTML
Abstract

Emerging evidence indicates that the gut microbiome contributes to the host immune response to infectious diseases. Here, to explore the role of the gut microbiome in the host immune responses in COVID-19, we conducted shotgun metagenomic sequencing and immune profiling of 14 severe/critical and 24 mild/moderate COVID-19 cases as well as 31 healthy control samples. We found that the diversity of the gut microbiome was reduced in severe/critical COVID-19 cases compared to mild/moderate ones. We identified the abundance of some gut microbes altered post-SARS-CoV-2 infection and related to disease severity, such as Enterococcus faecium, Coprococcus comes, Roseburia intestinalis, Akkermansia muciniphila, Bacteroides cellulosilyticus and Blautia obeum. We further analyzed the correlation between the abundance of gut microbes and host responses, and obtained a correlation map between clinical features of COVID-19 and 16 severity-related gut microbe, including Coprococcus comes that was positively correlated with CD3+/CD4+/CD8+ lymphocyte counts. In addition, an integrative analysis of gut microbiome and the transcriptome of peripheral blood mononuclear cells (PBMCs) showed that genes related to viral transcription and apoptosis were up-regulated in Coprococcus comes low samples. Moreover, a number of metabolic pathways in gut microbes were also found to be differentially enriched in severe/critical or mild/moderate COVID-19 cases, including the superpathways of polyamine biosynthesis II and sulfur oxidation that were suppressed in severe/critical COVID-19. Together, our study highlighted a potential regulatory role of severity related gut microbes in the immune response of host.

Key wordsCOVID-19    SARS-COV-2    gut microbiome    immune response
收稿日期: 2021-12-17      出版日期: 2022-04-26
Corresponding Author(s): Yun Tan,Saijuan Chen   
作者简介: Peng Lu, Renxing Wang, and Yue Xing contributed equally to this work.
 引用本文:   
. [J]. Frontiers of Medicine, 2022, 16(2): 263-275.
Xiaoguang Xu, Wei Zhang, Mingquan Guo, Chenlu Xiao, Ziyu Fu, Shuting Yu, Lu Jiang, Shengyue Wang, Yun Ling, Feng Liu, Yun Tan, Saijuan Chen. Integrated analysis of gut microbiome and host immune responses in COVID-19. Front. Med., 2022, 16(2): 263-275.
 链接本文:  
https://academic.hep.com.cn/fmd/CN/10.1007/s11684-022-0921-6
https://academic.hep.com.cn/fmd/CN/Y2022/V16/I2/263
Severe/critical COVID-19
?(n = 14)
Mild/moderate COVID-19
?(n = 24)
P value
Age (year) 60.5 (49.5–70.5) 51.0 (42.75–56.25) 0.19a
Gender 1.00b
?Female (n (%)) 4 (28.6%) 7 (29.2%)
?Male (n (%)) 10 (71.4%) 17 (70.8%)
Leukocyte counts (× 109/L, normal range 3.5–9.5) 3.21 (2.23–5.00) 4.86 (3.07–6.40) 0.87a
Lymphocytes (× 109/μL, normal range 1.1–3.2) 0.87 (0.64–1.15) 1.86 (1.47–2.25) <0.001a
CD3+ T cell counts (/μL, normal range 690–2540) 420 (249–546) 1204 (1089.5–1610.5) <0.001a
CD4+ T cell counts (/μL, normal range 190–1140) 240 (129.5–479.5) 680 (583.5–971.5) <0.001a
CD8+ T cell counts (/μL, normal range 410–1590) 143 (100–192.5) 380.5 (242–594) <0.001a
Platelets (× 109/L, normal range 125–350) 147 (133–200) 248.5 (225.3–277.8) <0.001a
Hemoglobin (g/L, normal range 115–150) 141 (118–145) 152 (137–154.3) 0.03a
D-dimer (μg/L, normal range 0–0.5) 0.44 (0.38–0.81) 0.22 (0.18–0.28) 0.04a
Any comorbidities
?Hypertension (n (%)) 4 (28.6%) 5 (20.8%) 0.70b
?Diabetes (n (%)) 2 (14.3%) 3 (12.5%) 1.00b
?Coronary heart disease (n (%)) 1 (7.1%) 1 (4.2%) 1.00b
?Chronic hepatitis B (n (%)) 1 (7.1%) 1 (4.2%) 1.00b
?Chronic renal diseases (n (%)) 1 (7.1%) 0 (0.0%) 0.37b
Tab.1  
Fig.1  
Fig.2  
Fig.3  
Fig.4  
Fig.5  
1 Y Shen, F Zheng, D Sun, Y Ling, J Chen, F Li, T Li, Z Qian, Y Zhang, Q Xu, L Liu, Q Huang, F Shan, L Xu, J Wu, Z Zhu, Z Song, S Li, Y Shi, J Zhang, X Wu, JB Mendelsohn, T Zhu, H Lu. Epidemiology and clinical course of COVID-19 in Shanghai, China. Emerg Microbes Infect 2020; 9(1): 1537–1545
https://doi.org/10.1080/22221751.2020.1787103 pmid: 32573353
2 N Taleghani, F Taghipour. Diagnosis of COVID-19 for controlling the pandemic: a review of the state-of-the-art. Biosens Bioelectron 2021; 174: 112830
https://doi.org/10.1016/j.bios.2020.112830 pmid: 33339696
3 M D’Arienzo, A Coniglio. Assessment of the SARS-CoV-2 basic reproduction number, R0, based on the early phase of COVID-19 outbreak in Italy. Biosaf Health 2020; 2(2): 57–59
https://doi.org/10.1016/j.bsheal.2020.03.004 pmid: 32835209
4 X Zhang, Y Tan, Y Ling, G Lu, F Liu, Z Yi, X Jia, M Wu, B Shi, S Xu, J Chen, W Wang, B Chen, L Jiang, S Yu, J Lu, J Wang, M Xu, Z Yuan, Q Zhang, X Zhang, G Zhao, S Wang, S Chen, H Lu. Viral and host factors related to the clinical outcome of COVID-19. Nature 2020; 583(7816): 437–440
https://doi.org/10.1038/s41586-020-2355-0 pmid: 32434211
5 Y Tan, W Zhang, Z Zhu, N Qiao, Y Ling, M Guo, T Yin, H Fang, X Xu, G Lu, P Zhang, S Yang, Z Fu, D Liang, Y Xie, R Zhang, L Jiang, S Yu, J Lu, F Jiang, J Chen, C Xiao, S Wang, S Chen, XW Bian, H Lu, F Liu, S Chen. Integrating longitudinal clinical laboratory tests with targeted proteomic and transcriptomic analyses reveal the landscape of host responses in COVID-19. Cell Discov 2021; 7(1): 42
https://doi.org/10.1038/s41421-021-00274-1 pmid: 34103487
6 A Jin, B Yan, W Hua, D Feng, B Xu, L Liang, C Guo. Clinical characteristics of patients diagnosed with COVID-19 in Beijing. Biosaf Health 2020; 2(2): 104–111
https://doi.org/10.1016/j.bsheal.2020.05.003 pmid: 32835210
7 L Kok, D Masopust, TN Schumacher. The precursors of CD8+ tissue resident memory T cells: from lymphoid organs to infected tissues. Nat Rev Immunol 2021; [Epub ahead of print] doi: 10.1038/s41577-021-00590-3
https://doi.org/10.1038/s41577-021-00590-3 pmid: 34480118
8 KA Krautkramer, J Fan, F Bäckhed. Gut microbial metabolites as multi-kingdom intermediates. Nat Rev Microbiol 2021; 19(2): 77–94
https://doi.org/10.1038/s41579-020-0438-4 pmid: 32968241
9 Y Fan, O Pedersen. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol 2021; 19(1): 55–71
https://doi.org/10.1038/s41579-020-0433-9 pmid: 32887946
10 K Martinez-Guryn, V Leone, EB Chang. Regional diversity of the gastrointestinal microbiome. Cell Host Microbe 2019; 26(3): 314–324
https://doi.org/10.1016/j.chom.2019.08.011 pmid: 31513770
11 G Falony, M Joossens, S Vieira-Silva, J Wang, Y Darzi, K Faust, A Kurilshikov, MJ Bonder, M Valles-Colomer, D Vandeputte, RY Tito, S Chaffron, L Rymenans, C Verspecht, L De Sutter, G Lima-Mendez, K D’hoe, K Jonckheere, D Homola, R Garcia, EF Tigchelaar, L Eeckhaudt, J Fu, L Henckaerts, A Zhernakova, C Wijmenga, J Raes. Population-level analysis of gut microbiome variation. Science 2016; 352(6285): 560–564
https://doi.org/10.1126/science.aad3503 pmid: 27126039
12 MC Abt, LC Osborne, LA Monticelli, TA Doering, T Alenghat, GF Sonnenberg, MA Paley, M Antenus, KL Williams, J Erikson, EJ Wherry, D Artis. Commensal bacteria calibrate the activation threshold of innate antiviral immunity. Immunity 2012; 37(1): 158–170
https://doi.org/10.1016/j.immuni.2012.04.011 pmid: 22705104
13 SC Ganal, SL Sanos, C Kallfass, K Oberle, C Johner, C Kirschning, S Lienenklaus, S Weiss, P Staeheli, P Aichele, A Diefenbach. Priming of natural killer cells by nonmucosal mononuclear phagocytes requires instructive signals from commensal microbiota. Immunity 2012; 37(1): 171–186
https://doi.org/10.1016/j.immuni.2012.05.020 pmid: 22749822
14 YK Yeoh, T Zuo, GC Lui, F Zhang, Q Liu, AY Li, AC Chung, CP Cheung, EY Tso, KS Fung, V Chan, L Ling, G Joynt, DS Hui, KM Chow, SSS Ng, TC Li, RW Ng, TC Yip, GL Wong, FK Chan, CK Wong, PK Chan, SC Ng. Gut microbiota composition reflects disease severity and dysfunctional immune responses in patients with COVID-19. Gut 2021; 70(4): 698–706
https://doi.org/10.1136/gutjnl-2020-323020 pmid: 33431578
15 Y Chen, S Gu, Y Chen, H Lu, D Shi, J Guo, WR Wu, Y Yang, Y Li, KJ Xu, C Ding, R Luo, C Huang, L Yu, M Xu, P Yi, J Liu, JJ Tao, H Zhang, L Lv, B Wang, J Sheng, L Li. Six-month follow-up of gut microbiota richness in patients with COVID-19. Gut 2022; 71(1): 222–225
pmid: 33833065
16 T Zuo, F Zhang, GCY Lui, YK Yeoh, AYL Li, H Zhan, Y Wan, ACK Chung, CP Cheung, N Chen, CKC Lai, Z Chen, EYK Tso, KSC Fung, V Chan, L Ling, G Joynt, DSC Hui, FKL Chan, PKS Chan, SC Ng. Alterations in gut microbiota of patients with COVID-19 during time of hospitalization. Gastroenterology 2020; 159(3): 944–955.e8
https://doi.org/10.1053/j.gastro.2020.05.048 pmid: 32442562
17 J Cao, C Wang, Y Zhang, G Lei, K Xu, N Zhao, J Lu, F Meng, L Yu, J Yan, C Bai, S Zhang, N Zhang, Y Gong, Y Bi, Y Shi, Z Chen, L Dai, J Wang, P Yang. Integrated gut virome and bacteriome dynamics in COVID-19 patients. Gut Microbes 2021; 13(1): 1–21
https://doi.org/10.1080/19490976.2021.1887722 pmid: 33678150
18 AM Bolger, M Lohse, B Usadel. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014; 30(15): 2114–2120
https://doi.org/10.1093/bioinformatics/btu170 pmid: 24695404
19 B Langmead, SL Salzberg. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9(4): 357–359
https://doi.org/10.1038/nmeth.1923 pmid: 22388286
20 DE Wood, J Lu, B Langmead. Improved metagenomic analysis with Kraken 2. Genome Biol 2019; 20(1): 257
https://doi.org/10.1186/s13059-019-1891-0 pmid: 31779668
21 MD Robinson, DJ McCarthy, GK Smyth. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010; 26(1): 139–140
https://doi.org/10.1093/bioinformatics/btp616 pmid: 19910308
22 M Hall, RG Beiko. 16S rRNA gene analysis with QIIME2. Methods Mol Biol 2018; 1849: 113–129
https://doi.org/10.1007/978-1-4939-8728-3_8 pmid: 30298251
23 N Segata, J Izard, L Waldron, D Gevers, L Miropolsky, WS Garrett, C Huttenhower. Metagenomic biomarker discovery and explanation. Genome Biol 2011; 12(6): R60
https://doi.org/10.1186/gb-2011-12-6-r60 pmid: 21702898
24 MI Love, W Huber, S Anders. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 2014; 15(12): 550
https://doi.org/10.1186/s13059-014-0550-8 pmid: 25516281
25 F Beghini, LJ McIver, A Blanco-Míguez, L Dubois, F Asnicar, S Maharjan, A Mailyan, P Manghi, M Scholz, AM Thomas, M Valles-Colomer, G Weingart, Y Zhang, M Zolfo, C Huttenhower, EA Franzosa, N Segata. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. eLife 2021; 10: e65088
https://doi.org/10.7554/eLife.65088 pmid: 33944776
26 RC Newsome, J Gauthier, MC Hernandez, GE Abraham, TO Robinson, HB Williams, M Sloan, A Owings, H Laird, T Christian, Y Pride, KJ Wilson, M Hasan, A Parker, M Senitko, SC Glover, RZ Gharaibeh, C Jobin. The gut microbiome of COVID-19 recovered patients returns to uninfected status in a minority-dominated United States cohort. Gut Microbes 2021; 13(1): 1–15
https://doi.org/10.1080/19490976.2021.1926840 pmid: 34100340
27 S Gu, Y Chen, Z Wu, Y Chen, H Gao, L Lv, F Guo, X Zhang, R Luo, C Huang, H Lu, B Zheng, J Zhang, R Yan, H Zhang, H Jiang, Q Xu, J Guo, Y Gong, L Tang, L Li. Alterations of the gut microbiota in patients with coronavirus disease 2019 or H1N1 influenza. Clin Infect Dis 2020; 71(10): 2669–2678
https://doi.org/10.1093/cid/ciaa709 pmid: 32497191
28 W Tao, G Zhang, X Wang, M Guo, W Zeng, Z Xu, D Cao, A Pan, Y Wang, K Zhang, X Ma, Z Chen, T Jin, L Liu, J Weng, S Zhu. Analysis of the intestinal microbiota in COVID-19 patients and its correlation with the inflammatory factor IL-18. Med Microecol 2020; 5: 100023
https://doi.org/10.1016/j.medmic.2020.100023 pmid: 34173452
29 T Zuo, Q Liu, F Zhang, GC Lui, EY Tso, YK Yeoh, Z Chen, SS Boon, FK Chan, PK Chan, SC Ng. Depicting SARS-CoV-2 faecal viral activity in association with gut microbiota composition in patients with COVID-19. Gut 2021; 70(2): 276–284
pmid: 32690600
30 Y Tan, F Liu, X Xu, Y Ling, W Huang, Z Zhu, M Guo, Y Lin, Z Fu, D Liang, T Zhang, J Fan, M Xu, H Lu, S Chen. Durability of neutralizing antibodies and T-cell response post SARS-CoV-2 infection. Front Med 2020; 14(6): 746–751
https://doi.org/10.1007/s11684-020-0822-5 pmid: 33017040
31 C Zhu, K Song, Z Shen, Y Quan, B Tan, W Luo, S Wu, K Tang, Z Yang, X Wang. Roseburia intestinalis inhibits interleukin17 excretion and promotes regulatory T cells differentiation in colitis. Mol Med Rep 2018; 17(6): 7567–7574
https://doi.org/10.3892/mmr.2018.8833 pmid: 29620246
32 M Schirmer, SP Smeekens, H Vlamakis, M Jaeger, M Oosting, EA Franzosa, R Ter Horst, T Jansen, L Jacobs, MJ Bonder, A Kurilshikov, J Fu, LAB Joosten, A Zhernakova, C Huttenhower, C Wijmenga, MG Netea, RJ Xavier. Linking the human gut microbiome to inflammatory cytokine production capacity. Cell 2016; 167(4): 1125–1136.e8
https://doi.org/10.1016/j.cell.2016.10.020 pmid: 27814509
33 CC Naidoo, GR Nyawo, I Sulaiman, BG Wu, CT Turner, K Bu, Z Palmer, Y Li, BWP Reeve, S Moodley, JG Jackson, J Limberis, AH Diacon, PD van Helden, JC Clemente, RM Warren, M Noursadeghi, LN Segal, G Theron. Anaerobe-enriched gut microbiota predicts pro-inflammatory responses in pulmonary tuberculosis. EBioMedicine 2021; 67: 103374
https://doi.org/10.1016/j.ebiom.2021.103374 pmid: 33975252
34 R Loomba, V Seguritan, W Li, T Long, N Klitgord, A Bhatt, PS Dulai, C Caussy, R Bettencourt, SK Highlander, MB Jones, CB Sirlin, B Schnabl, L Brinkac, N Schork, CH Chen, DA Brenner, W Biggs, S Yooseph, JC Venter, KE Nelson. Gut microbiome-based metagenomic signature for non-invasive detection of advanced fibrosis in human nonalcoholic fatty liver disease. Cell Metab 2017; 25(5): 1054–1062.e5
https://doi.org/10.1016/j.cmet.2017.04.001 pmid: 28467925
35 C Solé, S Guilly, K Da Silva, M Llopis, E Le-Chatelier, P Huelin, M Carol, R Moreira, N Fabrellas, G De Prada, L Napoleone, I Graupera, E Pose, A Juanola, N Borruel, M Berland, D Toapanta, F Casellas, F Guarner, J Doré, E Solà, SD Ehrlich, P Ginès. Alterations in gut microbiome in cirrhosis as assessed by quantitative metagenomics: relationship with acute-on-chronic liver failure and prognosis. Gastroenterology 2021; 160(1): 206–218.e13
https://doi.org/10.1053/j.gastro.2020.08.054 pmid: 32941879
36 Z Jie, H Xia, SL Zhong, Q Feng, S Li, S Liang, H Zhong, Z Liu, Y Gao, H Zhao, D Zhang, Z Su, Z Fang, Z Lan, J Li, L Xiao, J Li, R Li, X Li, F Li, H Ren, Y Huang, Y Peng, G Li, B Wen, B Dong, JY Chen, QS Geng, ZW Zhang, H Yang, J Wang, J Wang, X Zhang, L Madsen, S Brix, G Ning, X Xu, X Liu, Y Hou, H Jia, K He, K Kristiansen. The gut microbiome in atherosclerotic cardiovascular disease. Nat Commun 2017; 8(1): 845
https://doi.org/10.1038/s41467-017-00900-1 pmid: 29018189
37 C Depommier, A Everard, C Druart, H Plovier, M Van Hul, S Vieira-Silva, G Falony, J Raes, D Maiter, NM Delzenne, M de Barsy, A Loumaye, MP Hermans, JP Thissen, WM de Vos, PD Cani. Supplementation with Akkermansia muciniphila in overweight and obese human volunteers: a proof-of-concept exploratory study. Nat Med 2019; 25(7): 1096–1103
https://doi.org/10.1038/s41591-019-0495-2 pmid: 31263284
38 M Rasmussen, D Johansson, SK Söbirk, M Mörgelin, O Shannon. Clinical isolates of Enterococcus faecalis aggregate human platelets. Microbes Infect 2010; 12(4): 295–301
https://doi.org/10.1016/j.micinf.2010.01.005 pmid: 20109578
39 R Ahmadrajabi, MS Dalfardi, A Farsinejad, F Saffari. Distribution of Ebp pili among clinical and fecal isolates of Enterococcus faecalis and evaluation for human platelet activation. APMIS 2018; 126(4): 314–319
https://doi.org/10.1111/apm.12813 pmid: 29372575
40 W Lee, S Lim, HH Son, KS Bae. Sonicated extract of Enterococcus faecalis induces irreversible cell cycle arrest in phytohemagglutinin-activated human lymphocytes. J Endod 2004; 30(4): 209–212
https://doi.org/10.1097/00004770-200404000-00006 pmid: 15085047
41 A Nakamura, S Kurihara, D Takahashi, W Ohashi, Y Nakamura, S Kimura, M Onuki, A Kume, Y Sasazawa, Y Furusawa, Y Obata, S Fukuda, S Saiki, M Matsumoto, K Hase. Symbiotic polyamine metabolism regulates epithelial proliferation and macrophage differentiation in the colon. Nat Commun 2021; 12(1): 2105
https://doi.org/10.1038/s41467-021-22212-1 pmid: 33833232
42 E Proietti, S Rossini, U Grohmann, G Mondanelli. Polyamines and kynurenines at the intersection of immune modulation. Trends Immunol 2020; 41(11): 1037–1050
https://doi.org/10.1016/j.it.2020.09.007 pmid: 33055013
43 M Zhang, T Caragine, H Wang, PS Cohen, G Botchkina, K Soda, M Bianchi, P Ulrich, A Cerami, B Sherry, KJ Tracey. Spermine inhibits proinflammatory cytokine synthesis in human mononuclear cells: a counterregulatory mechanism that restrains the immune response. J Exp Med 1997; 185(10): 1759–1768
https://doi.org/10.1084/jem.185.10.1759 pmid: 9151701
44 Q Wang, M Zhang, Y Ding, Q Wang, W Zhang, P Song, MH Zou. Activation of NAD(P)H oxidase by tryptophan-derived 3-hydroxykynurenine accelerates endothelial apoptosis and dysfunction in vivo. Circ Res 2014; 114(3): 480–492
https://doi.org/10.1161/CIRCRESAHA.114.302113 pmid: 24281189
[1] FMD-21075-OF-TY_suppl_1 Download
[2] FMD-21075-OF-TY_suppl_2 Download
[3] FMD-21075-OF-TY_suppl_3 Download
[4] FMD-21075-OF-TY_suppl_4 Download
[5] FMD-21075-OF-TY_suppl_5 Download
[6] FMD-21075-OF-TY_suppl_6 Download
[7] FMD-21075-OF-TY_suppl_7 Download
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed