Greedy de novo motif discovery to construct motif repositories for bacterial proteomes

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

Abstract

BACKGROUND: Bacterial surfaces are complex systems, constructed from membranes, peptidoglycan and, importantly, proteins. The proteins play crucial roles as critical regulators of how the bacterium interacts with and survive in its environment. A full catalog of the motifs in protein families and their relative conservation grade is a prerequisite to target the protein-protein interaction that bacterial surface protein makes to host proteins.

RESULTS: In this paper, we propose a greedy approach to identify conserved motifs in large sequence families iteratively. Each iteration discovers a motif de novo and masks all occurrences of that motif. Remaining unmasked sequences are subjected to the next round of motif detection until no more significant motifs can be found. We demonstrate the utility of the method through the construction of a proteome-wide motif repository for Group A Streptococcus (GAS), a significant human pathogen. GAS produce numerous surface proteins that interact with over 100 human plasma proteins, helping the bacteria to evade the host immune response. We used the repository to find that proteins part of the bacterial surface has motif architectures that differ from intracellular proteins.

CONCLUSIONS: We elucidate that the M protein, a coiled-coil homodimer that extends over 500 A from the cell wall, has a motif architecture that differs between various GAS strains. As the M protein is known to bind a variety of different plasma proteins, the results indicate that the different motif architectures are responsible for the quantitative differences of plasma proteins that various strains bind. The speed and applicability of the method enable its application to all major human pathogens.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • University of Zurich
  • Swiss Institute of Bioinformatics
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Mikrobiologi inom det medicinska området
Originalspråkengelska
Artikelnummer141
TidskriftBMC Bioinformatics
Volym20
UtgivningsnummerSuppl 4
StatusPublished - 2019 apr 18
PublikationskategoriForskning
Peer review utfördJa