Evidence map›Paper›PMID 38666081›Full record

ArticlePeerJ2024

Investigating antimicrobial resistance genes in Kenya, Uganda and Tanzania cattle using metagenomics.

Kauthar M Omar, George L Kitundu, Adijat O Jimoh, Dorcus N Namikelwa, Felix M Lisso, Abiola A Babajide, Seun E Olufemi, Olaitan I Awe

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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  4. TargetingFrontiers in bioinformatics · 2025
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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 6 institutions in 4 countries.

Kauthar M OmarDepartment of Biochemistry and Biotechnology, School of Pure and Applied Sciences, Pwani University, Kilifi, Kenya.
George L KitunduDepartment of Biochemistry and Biotechnology, School of Pure and Applied Sciences, Pwani University, Kilifi, Kenya.
Adijat O JimohDivision of Immunology, Department of Pathology, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.
Dorcus N NamikelwaDepartment of Data Management, Modelling and Geo-Information Unit, International Centre of Insect Physiology and Ecology, Nairobi, Kenya.
Felix M LissoDepartment of Biochemistry and Biotechnology, School of Pure and Applied Sciences, Pwani University, Kilifi, Kenya.
Abiola A BabajideSouth African National Bioinformatics Institute, University of the Western Cape, Cape Town, South Africa.
Seun E OlufemiDepartment of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.
Olaitan I AweAfrican Society for Bioinformatics and Computational Biology, Cape Town, South Africa.
Pwani University · KEAfrican Institute for Mathematical Sciences · ZAInternational Centre of Insect Physiology and Ecology · KELadoke Akintola University of Technology · NGNational Primary Health Care Development Agency · NGUniversity of the Western Cape · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antimicrobial resistance (AMR) is a growing problem in African cattle production systems, posing a threat to human and animal health and the associated economic value chain. However, there is a poor understanding of the resistomes in small-holder cattle breeds in East African countries. This study aims to examine the distribution of antimicrobial resistance genes (ARGs) in Kenya, Tanzania, and Uganda cattle using a metagenomics approach. We used the SqueezeMeta-Abricate (assembly-based) pipeline to detect ARGs and benchmarked this approach using the Centifuge-AMRplusplus (read-based) pipeline to evaluate its efficiency. Our findings reveal a significant number of ARGs of critical medical and economic importance in all three countries, including resistance to drugs of last resort such as carbapenems, suggesting the presence of highly virulent and antibiotic-resistant bacterial pathogens (ESKAPE) circulating in East Africa. Shared ARGs such as aph(6)-id (aminoglycoside phosphotransferase), tet (tetracycline resistance gene), sul2 (sulfonamide resistance gene) and cfxA_gen (betalactamase gene) were detected. Assembly-based methods revealed fewer ARGs compared to read-based methods, indicating the sensitivity and specificity of read-based methods in resistome characterization. Our findings call for further surveillance to estimate the intensity of the antibiotic resistance problem and wider resistome classification. Effective management of livestock and antibiotic consumption is crucial in minimizing antimicrobial resistance and maximizing productivity, making these findings relevant to stakeholders, agriculturists, and veterinarians in East Africa and Africa at large.

Indexed as

Drug Resistance, BacterialMetagenomicsAnimalsAnti-Bacterial AgentsCattleGenes, BacterialKenyaTanzaniaUgandaAnti-Bacterial AgentsAntimicrobial resistanceAntimicrobial Resistance Genes (ARGs)CattleEast AfricaMetagenomicsResistomes

Identifiers

PMID38666081
PMCPMC11044882
OpenAlexW4395004944

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.