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Diversity and genomic determinants of the microbiomes associated with COVID-19 and non-COVID respiratory diseases.
Hoque, M Nazmul; Rahman, M Shaminur; Ahmed, Rasel; Hossain, Md Sabbir; Islam, Md Shahidul; Islam, Tofazzal; Hossain, M Anwar; Siddiki, Amam Zonaed.
  • Hoque MN; Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur 1706, Bangladesh.
  • Rahman MS; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
  • Ahmed R; Bangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
  • Hossain MS; Bangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
  • Islam MS; Bangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
  • Islam T; Institute of Biotechnology and Genetic Engineering (IBGE), BSMRAU, Gazipur 1706, Bangladesh.
  • Hossain MA; Department of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
  • Siddiki AZ; Vice-Chancellor, Jashore University of Science and Technology, Jashore 7408, Bangladesh.
Gene Rep ; 23: 101200, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1220851
Preprint
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ABSTRACT
The novel coronavirus disease 2019 (COVID-19) is a rapidly emerging and highly transmissible disease caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Understanding the microbiomes associated with the upper respiratory tract infection (URTI), chronic obstructive pulmonary disease (COPD) and COVID-19 diseases has clinical interest. We hypothesize that microbiome diversity and composition, and their genomic features are associated with different pathological conditions of these human respiratory tract diseases. To test this hypothesis, we analyzed 21 RNASeq metagenomic data including eleven COVID-19 (BD = 6 and China = 5), six COPD (UK = 6) and four URTI (USA = 4) samples to unravel the microbiome diversity and related genomic metabolic functions. The metagenomic data mapped to 534 bacterial, 60 archaeal and 61 viral genomes with distinct variation in the microbiome composition across the samples (COVID-19 > COPD > URTI). Notably, 94.57%, 80.0% and 24.59% bacterial, archaeal and viral genera shared between the COVID-19 and non-COVID samples, respectively. However, the COVID-19 related samples had sole association with 16 viral genera other than SARS-CoV-2. Strain-level virome profiling revealed 660 and 729 strains in COVID-19 and non-COVID samples, respectively, and of them 34.50% strains shared between the conditions. Functional annotation of the metagenomic data identified the association of several biochemical pathways related to basic metabolism (amino acid and energy), ABC transporters, membrane transport, virulence, disease and defense, regulation of virulence, programmed cell death, and primary immunodeficiency. We also detected 30 functional gene groups/classes associated with resistance to antibiotics and toxic compounds (RATC) in both COVID-19 and non-COVID microbiomes. Furthermore, we detected comparatively higher abundance of cobalt-zinc-cadmium resistance (CZCR) and multidrug resistance to efflux pumps (MREP) genes in COVID-19 metagenome. The profiles of microbiome diversity and associated microbial genomic features found in both COVID-19 and non-COVID (COPD and URTI) samples might be helpful in developing microbiome-based diagnostics and therapeutics for COVID-19 and non-COVID respiratory diseases. However, future studies might be carried out to explore the microbiome dynamics and the cross-talk between host and microbiomes employing larger volume of samples from different ethnic groups and geoclimatic conditions.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Gene Rep Year: 2021 Document Type: Article Affiliation country: J.genrep.2021.101200

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Randomized controlled trials Language: English Journal: Gene Rep Year: 2021 Document Type: Article Affiliation country: J.genrep.2021.101200