Evidence map›Paper›PMID 42536331›Full record

ArticleFolia microbiologica2026

Investigation of the effects of ampicillin and ceftazidime on Proteus mirabilis using metabolomic approaches and bioinformatics analyses.

Kübra Tekşen, İdil Yet, Ergin Murat Altuner

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Article in Folia microbiologica, 2026. 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

3 authors.

Kübra TekşenDepartment of Biology, Faculty of Science, Kastamonu University, Kastamonu, Türkiye. kubrateksen@kastamonu.edu.tr.ORCID http://orcid.org/0009-0009-5010-4290
İdil YetDepartment of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, Ankara, Türkiye. idil.yet@hacettepe.edu.tr.ORCID http://orcid.org/0000-0002-1227-0716
Ergin Murat AltunerDepartment of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, Ankara, Türkiye. emaltuner@kastamonu.edu.tr.ORCID http://orcid.org/0000-0001-5351-8071

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance is the ability of microorganisms to survive and proliferate despite exposure to antibiotics that would normally inhibit or kill susceptible strains. This resistance can make antibiotics ineffective or diminish their ability to combat microorganisms, complicating the treatment of infections and potentially leading to serious complications. To combat antibiotic resistance, a comprehensive analysis of changes in the metabolic activities of microorganisms is crucial for understanding the underlying mechanisms. Proteus mirabilis is a critical pathogen, particularly as a common cause of urinary tract infections (UTIs), especially in women. Typically, treating P. mirabilis infections relies on antibiotic-based therapies. However, when faced with resistant strains, treatment options become limited. This research aims to simulate how antibiotic resistance develops in P. mirabilis when exposed to sub-inhibitory concentrations of ampicillin and to explore whether ampicillin-resistant strains display cross-resistance to other antibiotics through metabolomic approaches. For this purpose, P. mirabilis strains were gradually exposed to sub-inhibitory concentrations of ampicillin using the disk diffusion method, leading to the selection of resistant passages. Ampicillin and ceftazidime were then applied to both ampicillin-resistant passages and sensitive control strains, and differences in their metabolomic profiles were compared. The metabolomic data obtained from this study were supported by statistical and bioinformatics analyses to facilitate metabolic pathway mapping, comprehend metabolic alterations, and identify interactions among metabolites. Metabolomic studies in antibiotic resistance research provide valuable insights into identifying metabolic alterations in resistant microorganisms, understanding microbial responses to antibiotic exposure, clarifying the effects of antibiotics on metabolic pathways, and gaining a comprehensive perspective on the mechanisms of antibiotic resistance.

Indexed as

AmpicillinAntibiotic ResistanceBioinformaticsGC-MSMetabolomicsP. mirabilis

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.