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<p><i>Serratia marcescens</i> is a significant opportunistic pathogen that can infect hospitalized or immunocompromised patients and result in serious illnesses. This prominent human-pathogenic bacteria contains over a third of all proteins whose functions are unknown. We extended this network by leveraging data from the interactome of protein–protein interactions, which we defined as the collection of all interactions between evolutionarily conserved proteins in other bacteria. We found that these interactions dramatically improved our ability to predict the function of a protein, allowing us to propose functional hypotheses for <i>S. marcescens</i> proteins with unknown functions. The interaction network depicted here comprises 36,507 edges and 1814 nodes and features a scale-free topology. The potential networks are found to have a substantial biological bias rather than the consequence of erroneous interactions, according to an in silico sanity check. The interactome-based analysis reported 272 essential proteins from <i>S. marcescens</i> and further found that 42 proteins are non-host homologous. This study also found 21 sub-network motifs with themes related to the biosynthesis of secondary metabolites, biosynthesis of amino acids, environmental variations in microbial metabolism, a two-component system, ABC transporters, ribosomes, carbon and purine metabolism, flagellar assembly, oxidative phosphorylation, and homologous recombination, Biosynthesis of folic acid, lipopolysaccharides, aminoacyl-tRNA, RNA degradation, and DNA replication. Bottleneck proteins and proteins that straddle several sub-networks and signaling pathways are described in addition to the functional annotation of each protein in the network. The list of possible interactions between the <i>S. marcescens</i> strains offers a structure for formulating original theories and arranging experiments for wet-lab studies. The predicted core protein–protein interaction networks can be a valuable and adaptable tool for <i>S. marcescens</i> researchers.</p> Graphical Abstract <p></p>

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Genome-scale mapping of Serratia marcescens core interactome to probe essential proteins and functional modules

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Pavan Gollapalli,
  • Tamizh Selvan Gnanasekaran,
  • Santosh Kumar Hulikal Shivashankara,
  • Ballamoole Krishna Kumar

摘要

Serratia marcescens is a significant opportunistic pathogen that can infect hospitalized or immunocompromised patients and result in serious illnesses. This prominent human-pathogenic bacteria contains over a third of all proteins whose functions are unknown. We extended this network by leveraging data from the interactome of protein–protein interactions, which we defined as the collection of all interactions between evolutionarily conserved proteins in other bacteria. We found that these interactions dramatically improved our ability to predict the function of a protein, allowing us to propose functional hypotheses for S. marcescens proteins with unknown functions. The interaction network depicted here comprises 36,507 edges and 1814 nodes and features a scale-free topology. The potential networks are found to have a substantial biological bias rather than the consequence of erroneous interactions, according to an in silico sanity check. The interactome-based analysis reported 272 essential proteins from S. marcescens and further found that 42 proteins are non-host homologous. This study also found 21 sub-network motifs with themes related to the biosynthesis of secondary metabolites, biosynthesis of amino acids, environmental variations in microbial metabolism, a two-component system, ABC transporters, ribosomes, carbon and purine metabolism, flagellar assembly, oxidative phosphorylation, and homologous recombination, Biosynthesis of folic acid, lipopolysaccharides, aminoacyl-tRNA, RNA degradation, and DNA replication. Bottleneck proteins and proteins that straddle several sub-networks and signaling pathways are described in addition to the functional annotation of each protein in the network. The list of possible interactions between the S. marcescens strains offers a structure for formulating original theories and arranging experiments for wet-lab studies. The predicted core protein–protein interaction networks can be a valuable and adaptable tool for S. marcescens researchers.

Graphical Abstract