Published August 17, 2022
| Version v1
Journal article
Open
Defining hierarchical protein interaction networks from spectral analysis of bacterial proteomes
Creators
- 1. Washington University in St. Louis
- 2. University of Chicago
Description
Cellular behaviors emerge from layers of molecular interactions: proteins interact to form complexes, pathways, and phenotypes. We show that hierarchical networks of protein interactions can be defined from the statistical pattern of proteome variation measured across thousands of diverse bacteria and that these networks reflect the emergence of complex bacterial phenotypesOur results are validated through gene-set enrichment analysis and comparison to existing exper-imentally derived databases. We demonstrate the biological utility of our approach by creating a model of motility in Pseudomonas aeruginosa and using it to identify a protein that affects pilus-mediated motility. Our method, SCALES (Spectral Correlation Analysis of Layered Evolutionary Signals), may be useful for interrogating genotype-phenotype relationships in bacteria.
Data availability
All data relevant to this manuscript can be downloaded, in Table format, at https://www.github.com/arjunsraman/Zaydman_et_al copy archived at swh:1:rev:b2c1091aafb726d88a925ad16e07f617a44c8cdc. All tables are available for download in .zip format. All code used for analyses contained within the manuscript can also be found within the same github repository; please refer to Readme.m and Supplemental_Code_9_23_2020.m for relevant Matlab scripts and to reproduce results.
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Additional details
Identifiers
- DOI
- 10.7554/eLife.74104
- Other
- oai:uchicago.tind.io:9872
Related works
- Cites
- https://doi.org/10.1101/2021.09.28.462107 (URL)