Proteome-wide subcellular topologies of E. coli polypeptides database (STEPdb).

Area of Science:

• Microbiology
• Biochemistry
• Bioinformatics

Background:

• Cellular compartmentalization is vital for isolating and specializing cell functions.
• Understanding protein localization and interactions is fundamental to comprehending cellular mechanisms.
• Surface and secreted proteins play critical roles in bacterial pathogenicity.

Purpose of the Study:

• To present the STEP database (STEPdb), a comprehensive resource for the subcellular localization and topology of the complete Escherichia coli proteome.
• To organize E. coli proteins into thirteen subcellular classes, facilitating detailed analysis.
• To provide insights into protein targeting, secretion, and interactions within E. coli.

Main Methods:

• Integration of bioinformatics predictions, proteomic, biochemical, and functional data.
• Extensive literature re-examination and manual curation of protein annotations.
• Inclusion of experimental evidence for protein localization, with support from 426 articles.

Main Results:

• STEPdb characterizes the complete proteome of E. coli (K-12 and BL21 strains) into thirteen subcellular classes.
• The database includes extensive data on peripheral inner membrane (PIM) proteins, their visualization in complexes, and interactions.
• It summarizes E. coli protein export machineries, secretomes (Sec- and TAT-utilizing), and their topological features.

Conclusions:

• STEPdb serves as a valuable resource for understanding E. coli cell biology, protein localization, and secretion pathways.
• The database facilitates research into bacterial pathogenicity by characterizing surface and secreted proteins.
• STEPdb provides integrated tools for topology prediction and homology searches, enhancing its utility for researchers.