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GPA reclassification

Code and folder structure associated with our bioRxiv preprint:
Structural and evolutionary analyses support reclassification of glycopeptide antibiotics as xyclopeptides

Abstract

Glycopeptide antibiotics (GPAs) are key agents against multidrug-resistant Gram-positive pathogens, yet both the term “glycopeptide” and the current GPA type I-V classification framework have become increasingly strained as structurally and mechanistically divergent members continue to be discovered. In particular, compounds historically grouped as “type V GPAs” differ from classical GPAs in features such as glycosylation, peptide length, and reported mode of action, raising the question of whether they belong to the same natural product class. Here, a curated dataset of GPA-associated biosynthetic gene clusters (BGCs) is analysed by combining fingerprint similarity of the products with phylogenetic analysis of the BGCs. Fingerprint-based structural similarity networks and BGC similarity comparisons reveal a pronounced separation between classical lipid II-binding GPAs (types I-IV) and type V GPAs. Multi-locus phylogenetic analyses of conserved biosynthetic components further support two deeply divergent evolutionary subclasses, consistent with subclass-specific biosynthetic signatures. Together, these results motivate a revised, unambiguous framework in which the broader class is termed xyclopeptides, comprising the subclasses dalabactins (legacy GPA types I–IV) and murobactins (legacy type V).

Repository Contents

This repository contains:

  • A_dataset_creation/: predefined folder structure used for dataset organization (no data included)
  • publication_scripts/: all scripts used for data processing and analysis

Key Script

The main entry point for reproducing the dataset generation workflow is:

publication_scripts/A_gpa_dataset_generation.ipynb

This notebook contains step-by-step instructions and fully documented analysis code used to generate the dataset described in the manuscript.

Reproducibility

All computational steps described in the paper can be reproduced by following the workflow in the notebook above.

Citation

If you use this repository, please cite our preprint:

Structural and evolutionary analyses support reclassification of glycopeptide antibiotics as xyclopeptides

Athina Gavriilidou, Noel Kubach, Martina Adamek, Jens-Peter Rodler, Susanna Kremer, Daniel H. Huson, Rosa Alduina, Gerard Wright, Mohammad Seyemsayadost, Wolfgang Wohlleben, Stefano Donadio, Margherita Sosio, Min Xu, Max J. Cryle, Evi Stegmann, Nadine Ziemert

bioRxiv 2023.02.10.526856; doi: https://doi.org/10.1101/2023.02.10.526856

License

CC BY 4.0

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