Evidence map›Paper›PMID 41039617›Full record

ArticleBMC research notes2025

Toxin data quality: a critical examination of bacterial exotoxins and animal toxins.

Tanja Krüger, Ivan Koludarov, Maria Littmann, Burkhard Rost, Luisa F Jimenez-Soto

Abstract read
In one paragraph

Article in BMC research notes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Tanja KrügerWalther-Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Goethestrasse 33, 80336, Munich, Germany.
Ivan KoludarovSchool of Computation, Information and Technology (CIT), Department of Informatics, Unit for Bioinformatics & Computational Biology - i12, TUM (Technical University of Munich, Boltzmannstr. 3, 85748, Garching/Munich, Germany.
Maria LittmannSchool of Computation, Information and Technology (CIT), Department of Informatics, Unit for Bioinformatics & Computational Biology - i12, TUM (Technical University of Munich, Boltzmannstr. 3, 85748, Garching/Munich, Germany.
Burkhard RostSchool of Computation, Information and Technology (CIT), Department of Informatics, Unit for Bioinformatics & Computational Biology - i12, TUM (Technical University of Munich, Boltzmannstr. 3, 85748, Garching/Munich, Germany.
Luisa F Jimenez-SotoWalther-Straub Institute of Pharmacology and Toxicology, Ludwig-Maximilians-Universität München, Goethestrasse 33, 80336, Munich, Germany. l.jimenez@lmu.de.ORCID http://orcid.org/0000-0001-8551-5019

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveExisting toxins datasets include a mixture of proteins and toxin peptides. In this study we present two curated datasets of toxic proteins free of associated proteins: bacterial exotoxins and animal toxins. Our stringent selection criteria resulted in two data sets with only toxins that directly target or disrupt vital molecular mechanisms of their target organism. To gain insight in their properties and differences, we compared both sets of toxins to controls, and used simple biophysical features such as protein length, and amino acid composition distinguishing between evolutionary kingdoms (phyla). This approach should reveal if there is a need to consider differences present in toxin sets depending on their origin.

resultsOur analysis revealed biophysical differences between animal and bacterial toxins that should not be ignored. Both toxin groups exhibited preferencial amino acid usage depending on their origin, together with higher cysteine content compared to their respective controls. The animal toxins set contains, on average, significantly shorter sequences than bacterial toxins, and had their isoelectric point shifted towards acidic pH values. We show that animal toxins and bacterial toxins possess intrinsic differences in general biophysical properties, which reinforce the necessity of segregating these datasets to ensure reliability of bioinformatics models aimed at understanding and predicting toxin characteristics.

Indexed as

Bacterial ToxinsData AccuracyExotoxinsToxins, BiologicalAnimalsComputational BiologyBacterial ToxinsExotoxinsToxins, BiologicalAmino acid usageAnimal toxinsBacteria toxinsExotoxins

Identifiers

PMID41039617
PMCPMC12492933

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.