Evidence map›Paper›PMID 33977168›Full record

ArticleGene reports2021

Diversity and genomic determinants of the microbiomes associated with COVID-19 and non-COVID respiratory diseases.

M Nazmul Hoque, M Shaminur Rahman, Rasel Ahmed, Md Sabbir Hossain, Md Shahidul Islam, Tofazzal Islam, M Anwar Hossain, Amam Zonaed Siddiki

Open access · greenAbstract read
In one paragraph

Article in Gene reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
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  4. Co-infection models ofFrontiers in cellular and infection microbiology · 2026
    Article
  5. The respiratory tract virome: unravelling the role of viral dark matter in respiratory health and disease.European respiratory review : an official journal of the European Respiratory Society · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

M Nazmul HoqueDepartment of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University (BSMRAU), Gazipur 1706, Bangladesh.
M Shaminur RahmanDepartment of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
Rasel AhmedBangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
Md Sabbir HossainBangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
Md Shahidul IslamBangladesh Jute Research Institute, Dhaka 1207, Bangladesh.
Tofazzal IslamInstitute of Biotechnology and Genetic Engineering (IBGE), BSMRAU, Gazipur 1706, Bangladesh.
M Anwar HossainDepartment of Microbiology, University of Dhaka, Dhaka 1000, Bangladesh.
Amam Zonaed SiddikiDepartment of Pathology and Parasitology, Chattogram Veterinary and Animal Sciences University (CVASU), Chattogram 4202, Bangladesh.
Bangladesh Jute Research Institute · BDBangabandhu Sheikh Mujibur Rahman Agricultural University · BDUniversity of Dhaka · BDChattogram Veterinary and Animal Sciences University · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COPDCOVID-19DiversityMicrobiomeNon-COVIDSARS-CoV-2URTI

Identifiers

PMID33977168
PMCPMC8102076
OpenAlexW3162087605

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.