SARS-CoV-2 infection alters the gut microbiome in diabetes patients: A cross-sectional study from Bangladesh

被引:8
作者
Mannan, Adnan [1 ,2 ]
Hoque, M. Nazmul [3 ]
Noyon, Sajjad Hossain [1 ,2 ]
Mehedi, H. M. Hamidullah [4 ]
Foysal, Md Javed [5 ]
Salauddin, Asma [1 ,2 ]
Islam, S. M. Rafiqul [1 ,2 ]
Sharmen, Farjana [1 ,2 ]
Tanni, Afroza Akter [1 ,2 ]
Siddiki, Amam Zonaed [6 ]
Tay, Alfred [7 ]
Siddique, Md Moradul [8 ]
Rahman, M. Shaminur [9 ]
Galib, Syed Md. [8 ]
Akter, Farhana [10 ]
机构
[1] Univ Chittagong, Dept Genet Engn & Biotechnol, Chattogram, Bangladesh
[2] Chittagong Med Coll, Dept Endocrinol, Chattogram, Bangladesh
[3] Univ Chittagong, Next Generat Sequencing Res & Innovat Lab Chittag, Biotechnol Res & Innovat Ctr BRIC, Dept Genet Engn & Biotechnol, Chittagong, Bangladesh
[4] Bangabandhu Sheikh Mujibur Rahman Agr Univ, Dept Gynecol Obstet & Reprod Hlth, Gazipur, Bangladesh
[5] 250 Bedded Gen Hosp, Dept Med, Chattogram, Bangladesh
[6] Curtin Univ, Sch Mol & Life Sci, Bentley, WA, Australia
[7] Chattogram Vet & Anim Sci Univ, Dept Pathol & Parasitol, COVID Diagnost Lab, Chattogram, Bangladesh
[8] Univ Western Australia, Marshall Ctr Infect Dis Res & Training, Sch Biomed Sci, Helicobacter Res Lab, Perth, WA, Australia
[9] Jashore Univ Sci & Technol, Dept Comp Sci & Engn, Jashore, Bangladesh
[10] Jashore Univ Sci & Technol, Dept Microbiol, Jashore, Bangladesh
关键词
Bangladesh; COVID-19; diabetes; gut microbiome; metagenome; COVID-19;
D O I
10.1002/jmv.28691
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Populations of different South Asian nations including Bangladesh reportedly have a high risk of developing diabetes in recent years. This study aimed to investigate the differences in the gut microbiome of COVID-19-positive participants with or without type 2 diabetes mellitus (T2DM) compared with healthy control subjects. Microbiome data of 30 participants with T2DM were compared with 22 age-, sex-, and body mass index (BMI)-matched individuals. Clinical features were recorded while fecal samples were collected aseptically from the participants. Amplicon-based (16S rRNA) metagenome analyses were employed to explore the dysbiosis of gut microbiota and its correlation with genomic and functional features in COVID-19 patients with or without T2DM. Comparing the detected bacterial genera across the sample groups, 98 unique genera were identified, of which 9 genera had unique association with COVID-19 T2DM patients. Among different bacterial groups, Shigella (25%), Bacteroides (23.45%), and Megamonas (15.90%) had higher mean relative abundances in COVID-19 patients with T2DM. An elevated gut microbiota dysbiosis in T2DM patients with COVID-19 was observed while some metabolic functional changes correlated with bidirectional microbiome dysbiosis between diabetes and non-diabetes humans gut were also found. These results further highlight the possible association of COVID-19 infection that might be linked with alteration of gut microbiome among T2DM patients.
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页数:14
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共 47 条
  • [1] Clinical characteristics and short term outcomes after recovery from COVID-19 in patients with and without diabetes in Bangladesh
    Akter, Farhana
    Mannan, Adnan
    Mehedi, H. M. Hamidullah
    Rob, Md. Abdur
    Ahmed, Shakeel
    Salauddin, Asma
    Hossain, Md. Shakhawat
    Hasan, Md. Mahbub
    [J]. DIABETES & METABOLIC SYNDROME-CLINICAL RESEARCH & REVIEWS, 2020, 14 (06) : 2031 - 2038
  • [2] Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes
    Al-Emran, Hassan M.
    Rahman, Shaminur
    Hasan, Md Shazid
    Ul Alam, Rubayet
    Islam, Ovinu Kibria
    Anwar, Ajwad
    Jahid, Md Iqbal K.
    Hossain, Anwar
    [J]. JOURNAL OF MEDICAL VIROLOGY, 2023, 95 (01)
  • [3] CONSIDERATIONS FOR GUT MICROBIOTA AND PROBIOTICS IN PATIENTS WITH DIABETES AMIDST THE COVID-19 PANDEMIC: A NARRATIVE REVIEW
    Barengolts, Elena
    Smith, Emily Daviau
    [J]. ENDOCRINE PRACTICE, 2020, 26 (10) : 1186 - 1195
  • [4] How to Determine the Role of the Microbiome in Drug Disposition
    Bisanz, Jordan E.
    Spanogiannopoulos, Peter
    Pieper, Lindsey M.
    Bustion, Annamarie E.
    Turnbaugh, Peter J.
    [J]. DRUG METABOLISM AND DISPOSITION, 2018, 46 (11) : 1588 - 1595
  • [5] Trimmomatic: a flexible trimmer for Illumina sequence data
    Bolger, Anthony M.
    Lohse, Marc
    Usadel, Bjoern
    [J]. BIOINFORMATICS, 2014, 30 (15) : 2114 - 2120
  • [6] Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
    Bolyen, Evan
    Rideout, Jai Ram
    Dillon, Matthew R.
    Bokulich, NicholasA.
    Abnet, Christian C.
    Al-Ghalith, Gabriel A.
    Alexander, Harriet
    Alm, Eric J.
    Arumugam, Manimozhiyan
    Asnicar, Francesco
    Bai, Yang
    Bisanz, Jordan E.
    Bittinger, Kyle
    Brejnrod, Asker
    Brislawn, Colin J.
    Brown, C. Titus
    Callahan, Benjamin J.
    Caraballo-Rodriguez, Andres Mauricio
    Chase, John
    Cope, Emily K.
    Da Silva, Ricardo
    Diener, Christian
    Dorrestein, Pieter C.
    Douglas, Gavin M.
    Durall, Daniel M.
    Duvallet, Claire
    Edwardson, Christian F.
    Ernst, Madeleine
    Estaki, Mehrbod
    Fouquier, Jennifer
    Gauglitz, Julia M.
    Gibbons, Sean M.
    Gibson, Deanna L.
    Gonzalez, Antonio
    Gorlick, Kestrel
    Guo, Jiarong
    Hillmann, Benjamin
    Holmes, Susan
    Holste, Hannes
    Huttenhower, Curtis
    Huttley, Gavin A.
    Janssen, Stefan
    Jarmusch, Alan K.
    Jiang, Lingjing
    Kaehler, Benjamin D.
    Bin Kang, Kyo
    Keefe, Christopher R.
    Keim, Paul
    Kelley, Scott T.
    Knights, Dan
    [J]. NATURE BIOTECHNOLOGY, 2019, 37 (08) : 852 - 857
  • [7] How human microbiome talks to health and disease
    Cong, Jing
    Zhang, Xiaochun
    [J]. EUROPEAN JOURNAL OF CLINICAL MICROBIOLOGY & INFECTIOUS DISEASES, 2018, 37 (09) : 1595 - 1601
  • [8] Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB
    DeSantis, T. Z.
    Hugenholtz, P.
    Larsen, N.
    Rojas, M.
    Brodie, E. L.
    Keller, K.
    Huber, T.
    Dalevi, D.
    Hu, P.
    Andersen, G. L.
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2006, 72 (07) : 5069 - 5072
  • [9] PICRUSt2 for prediction of metagenome functions
    Douglas, Gavin M.
    Maffei, Vincent J.
    Zaneveld, Jesse R.
    Yurgel, Svetlana N.
    Brown, James R.
    Taylor, Christopher M.
    Huttenhower, Curtis
    Langille, Morgan G. I.
    [J]. NATURE BIOTECHNOLOGY, 2020, 38 (06) : 685 - 688
  • [10] Is Gut Microbiota Dysbiosis a Predictor of Increased Susceptibility to Poor Outcome of COVID-19 Patients? An Update
    Ferreira, Carolina
    Viana, Sofia D.
    Reis, Flavio
    [J]. MICROORGANISMS, 2021, 9 (01) : 1 - 12