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Cited by 5Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic NetworksGenomics and Phylogenetic Studies

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RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets

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Hemm, Luisa, Rabsch, Dominik, Ropp, Halie Rae, Reimann, Viktoria, Gerth, Philip, Bartel, Jürgen, Brenes-Álvarez, Manuel, Maaß, Sandra, Becher, Dörte, Hess, Wolfgang R., Backofen, Rolf·2025·Nature Communications
DOI 10.1038/s41467-025-64086-7PMC PMC12475003

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Abstract

The computational analysis of large proteomics datasets from gradient profiling or spatially resolved proteomics is often as crucial as experimental design. We present RAPDOR, a tool for intuitive analyzing and visualizing such datasets, based on the Jensen-Shannon distance and analysis of similarities between replicates, applied to the identification of RNA-binding proteins (RBPs) and spatial proteomics. First, we examine the in-gradient distribution profiles of protein complexes with or without RNase treatment (GradR) to identify RBPs in the cyanobacterium Synechocystis 6803. RBPs play pivotal regulatory and structural roles. Although numerous RBPs are well characterized, the complete set of RBPs remains unknown for any species. RAPDOR identifies 165 potential RBPs, including ribosomal proteins, RNA-modifying enzymes, and proteins not previously associated with RNA binding. High-ranking putative RBPs, such as ribosome hibernation factor LrtA/RaiA, phosphoglucomutase Sll0726, antitoxin Ssl2245, and preQ(1) synthase QueF predicted by RAPDOR but not the TriPepSVM algorithm, are experimentally validated, indicating the existence of uncharacterized RBP domains. These data are available online, providing a resource for RNase-sensitive protein complexes in cyanobacteria. We then show by reanalyzing existing datasets that RAPDOR effectively examines the intracellular redistribution of proteins upon growth factor stimulation. RAPDOR is a generic, non-parametric tool for analyzing highly complex datasets.

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Metadata

Authors
Hemm, L., Rabsch, D., Ropp, H. R., Reimann, V., Gerth, P., Bartel, J., Brenes-Álvarez, M., Maaß, S., Becher, D., Hess, W. R., & Backofen, R.
Affiliations
  • University of Freiburg (DE)
  • Universität Greifswald (DE)
Corresponding author
  • Hess, Wolfgang R.
  • Backofen, Rolf
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2025-09-26
Volume
16
Issue
1
Pages
8527-8527
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-025-64086-7
PMC
PMC12475003
OpenAlex
W4414534912
Cited by
5
References
5
Citations by year
2026: 3 · 2025: 2
FWCI
1.27
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (publishedVersion, cc-by)
  • FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion, cc-by)
  • HAL (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Deutsche Forschungsgemeinschaft (322977937/GRK2344, HE 2544/12-2, BA 2168/21-2, BE 3869/5-2, 390939984, CIBSS - EXC-2189 - Project ID 390939984)
  • Alexander von Humboldt-Stiftung (Alexander von Humboldt postdoctoral fellowship)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
Jensen-Shannon distance, RNA-binding proteins, spatial proteomics, Synechocystis sp. PCC 6803, cyanobacteria, protein complex identification
MeSH terms
Algorithms, Bacterial Proteins, Software, RNA-Binding Proteins, Computational Biology, Proteomics, Synechocystis

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