Evidence map›Paper›PMID 40702306›Full record

ArticleThe Journal of antibiotics2025

Bioinformatics-driven discovery of skin microbiota bacteriocins as potential antibiotics and probiotics.

Anum Munir, Alan Janbey, Bilawal Sajjad, Kowsalya V Perumal, Hajra Qayyum, Marriam Bakhtiar

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Article in The Journal of antibiotics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Anum MunirDepartment of Health and Applied Sciences, The London College UCK, London, UK.ORCID 0000-0002-8411-0236
Alan JanbeyDepartment of Health and Applied Sciences, The London College UCK, London, UK. a.janbey@lcuck.ac.uk.
Bilawal SajjadDepartment of Health and Applied Sciences, The London College UCK, London, UK.
Kowsalya V PerumalDepartment of Health and Applied Sciences, The London College UCK, London, UK.
Hajra QayyumIntegrative Biology Laboratory, Department of Microbiology and Biotechnology, Atta UrRehman School of Applied Biosciences (ASAB), National University of Science and Technology, Islamabad, Pakistan.
Marriam BakhtiarDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology, Islamabad, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human skin microbiota, comprising a diverse range of microorganisms, including bacteria, viruses, and fungi, plays an important role in maintaining skin health and protecting against pathogenic invasions. Among these microorganisms, certain bacteria produce bacteriocins, which are ribosomal peptides with potent antimicrobial properties. This study presents a novel computational approach to identify and predict bacteriocins from microbial genomes comprising sebaceous region of the skin, aiming to explore their therapeutic potential. Through genome analysis using advanced bioinformatics tools, we identified potential genes, operons, open reading frames (ORFs), and promoter regions linked to bacteriocin production. The BAGEL4 platform was employed to detect structural bacteriocin genes, while modelling bacterial growth and bacteriocin expression under various environmental conditions was conducted using MATLAB's SimBiology application. The results revealed the optimal conditions for bacteriocin production and highlighted promising candidates for further experimental validation. These findings underscore the significance of skin microbiota as a source of novel bacteriocins, offering potential alternatives to traditional antibiotics amidst rising antimicrobial resistance.

Indexed as

Anti-Bacterial AgentsBacteriocinsComputational BiologyMicrobiotaProbioticsSkinHumansOpen Reading FramesSkin MicrobiomeAnti-Bacterial AgentsBacteriocins

Identifiers

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Registered trials

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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.