Evidence map›Paper›PMID 39915515›Full record

ArticleScientific reports2025

Comparative analysis of microbial contamination in diesel fuels using MALDI-TOF MS.

Agnieszka Ludwiczak, Tomasz Zieliński, Ewelina Sibińska, Grażyna Czeszewska-Rosiak, Michał Złoch, Joanna Rudnicka, Andrzej Tretyn, Paweł Pomastowski

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Agnieszka LudwiczakCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland. agnieszka.lud@umk.pl.
Tomasz ZielińskiCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.
Ewelina SibińskaCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.
Grażyna Czeszewska-RosiakCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.
Michał ZłochCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.
Joanna RudnickaCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.
Andrzej TretynChair of Plant Physiology and Biotechnology, Nicolaus Copernicus University in Torun, Lwowska 1 Str, Torun, 87-100, Poland.
Paweł PomastowskiCentre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Torun, Wilenska 4 Str, Torun, 87-100, Poland.

Funding

Ministry of Science and Higher Education DWD/5/0039/2021
6 · The paper itself

Abstract

Microbiological contamination in fuels poses a significant threat to fuel quality, operational safety, and the efficiency of fuel systems. Effective management of microbial risks can extend fuel systems' lifespan and minimize the environmental footprint of fuel usage. Therefore, we aimed to identify the microbiological contaminants using two MALDI-TOF MS systems (Bruker Daltonik GmbH and Zybio Inc.). Detection and characterization of microbiological contamination in fuels were performed with further validation by 16 S rRNA gene sequencing. Microorganisms collected from three types of diesel fuel were cultured, and fuel samples were analyzed. Significant differences in microbiological contamination were observed between the fuel types, with 272 isolates of bacteria and fungi identified across all fuel samples. Ekodiesel Ultra B0 had the highest number of identified microorganisms. The Zybio system identified 48% of all microorganisms at the species level, whereas the Bruker system identified only 33%. The 16 S rDNA sequencing confirmed proteomic identifications by the MALDI systems with high accuracy. Our study indicates that MALDI-TOF MS technology can effectively assess microbiological contamination in fuels. Integrating MALDI-TOF MS with other molecular techniques could provide a comprehensive view of fuel's microbial communities.

Indexed as

BacteriaFungiGasolineSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationRNA, Ribosomal, 16SGasolineRNA, Ribosomal, 16SActinomycetiaBrukerDiesel fuelMALDI-TOF MSMicrobial contaminationZybio

Identifiers

PMID39915515
PMCPMC11802864

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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.