Evidence map›Paper›PMID 34966183›Full record

ArticleScientific reports2021

Sputum microbiota profiles of treatment-naïve TB patients in Uganda before and during first-line therapy.

David Patrick Kateete, Monica M Mbabazi, Faith Nakazzi, Fred A Katabazi, Edgar Kigozi, Willy Ssengooba, Lydia Nakiyingi, Sharon Namiiro, Alphonse Okwera, Moses L Joloba and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 26% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Clinical and Microbiological Characteristics ofInfection and drug resistance · 2023
    Article
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

11 authors at 3 institutions in 2 countries.

David Patrick Kateete *Department of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda. david.kateete@mak.ac.ug.
Monica M MbabaziDepartment of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Faith NakazziDepartment of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Fred A KatabaziDepartment of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Edgar KigoziDepartment of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Willy SsengoobaBSL-3 Mycobacteriology Laboratory, Department of Medical Microbiology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Lydia NakiyingiDepartment of Medicine, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
Sharon NamiiroMakerere University Lung Institute, Makerere University College of Health Sciences, Kampala, Uganda.
Alphonse OkweraTB Clinics, Mulago National Referral Hospital, Kampala, Uganda.
Moses L JolobaDepartment of Immunology and Molecular Biology, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, Uganda.
Adrian Muwonge *Division of Genetics and Genomics, The Roslin Institute, University of Edinburgh, Edinburg, UK. adrian.muwonge@roslin.ed.ac.uk.
Makerere University · UGMulago Hospital · UGRoslin Institute · GB

Funding

Biotechnology and Biological Sciences Research Council BB/P007767/1Medical Research Council MR/V034952/1Wellcome TrustWellcome Trust 107743/Z/15/Z
6 · The paper itself

Abstract

Information on microbiota dynamics in pulmonary tuberculosis (TB) in Africa is scarce. Here, we sequenced sputa from 120 treatment-naïve TB patients in Uganda, and investigated changes in microbiota of 30 patients with treatment-response follow-up samples. Overall, HIV-status and anti-TB treatment were associated with microbial structural and abundance changes. The predominant phyla were Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria and Actinobacteria, accounting for nearly 95% of the sputum microbiota composition; the predominant genera across time were Prevotella, Streptococcus, Veillonella, Haemophilus, Neisseria, Alloprevotella, Porphyromonas, Fusobacterium, Gemella, and Rothia. Treatment-response follow-up at month 2 was characterized by a reduction in abundance of Mycobacterium and Fretibacterium, and an increase in Ruminococcus and Peptococcus; month 5 was characterized by a reduction in Tannerella and Fusobacterium, and an increase in members of the family Neisseriaceae. The microbiota core comprised of 44 genera that were stable during treatment. Hierarchical clustering of this core's abundance distinctly separated baseline (month 0) samples from treatment follow-up samples (months 2/5). We also observed a reduction in microbial diversity with 9.1% (CI 6-14%) of the structural variation attributed to HIV-status and anti-TB treatment. Our findings show discernible microbiota signals associated with treatment with potential to inform anti-TB treatment response monitoring.

Indexed as

AdultAntitubercular AgentsBacteriaFemaleHumansLongitudinal StudiesMaleMicrobiotaSputumTuberculosis, PulmonaryUgandaAntitubercular Agents

Identifiers

PMID34966183
PMCPMC8716532
OpenAlexW4226205955

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.