Employees – University of Copenhagen

Protein Engineering Reveals Mechanisms of Functional Amyloid Formation in Pseudomonas aeruginosa Biofilms

Research output: Contribution to journalJournal articleResearchpeer-review

Alissa Bleem, Gunna Christiansen, Daniel J. Madsen, Hans Maric, Kristian Strømgaard, James D. Bryers, Valerie Daggett, Rikke L. Meyer, Daniel E. Otzen

Amyloids are typically associated with neurodegenerative diseases, but recent research demonstrates that several bacteria utilize functional amyloid fibrils to fortify the biofilm extracellular matrix and thereby resist antibiotic treatments. In Pseudomonas aeruginosa, these fibrils are composed predominantly of FapC, a protein with high-sequence conservation among the genera. Previous studies established FapC as the major amyloid subunit, but its mechanism of fibril formation in P. aeruginosa remained largely unexplored. Here, we examine the FapC sequence in greater detail through a combination of bioinformatics and protein engineering, and we identify specific motifs that are implicated in amyloid formation. Sequence regions of high evolutionary conservation tend to coincide with regions of high amyloid propensity, and mutation of amyloidogenic motifs to a designed, non-amyloidogenic motif suppresses fibril formation in a pH-dependent manner. We establish the particular significance of the third repeat motif in promoting fibril formation and also demonstrate emergence of soluble oligomer species early in the aggregation pathway. The insights reported here expand our understanding of the mechanism of amyloid polymerization in P. aeruginosa, laying the foundation for development of new amyloid inhibitors to combat recalcitrant biofilm infections.

Original languageEnglish
JournalJournal of Molecular Biology
Volume430
Issue number20
Pages (from-to)3751-3763
Number of pages13
ISSN0022-2836
DOIs
Publication statusPublished - 2018

    Research areas

  • bacterial amyloid, extracellular matrix, peptide microarray, protein aggregation, protein sequence analysis

ID: 203870679