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

Our 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.

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Publication Details

Journal
BMC Research Notes
Published
2025-10-02
DOI
https://doi.org/10.1186/s13104-025-07438-2
Primary Topic
Toxin Mechanisms and Immunotoxins
Type
article
Field-Weighted Citation Impact
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article

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

Maria Littmann, Tanja Krüger, Burkhard Rost, Luisa F. Jiménez‐Soto et al.
BMC Research Notes
Toxin Mechanisms and Immunotoxins
article

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

Maria Littmann, Tanja Krüger, Burkhard Rost, Luisa F. Jiménez‐Soto, Ivan Koludarov
article en

Abstract

Our 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.

BMC Research NotesVol. 18(1)
Weihenstephan-Triesdorf University of Applied Sciences (DE), Institute for Advanced Study (DE), Technical University of Munich (DE), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 71%
Toxin Mechanisms and Immunotoxins
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