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Scavenging Bacterial Siderophores with Engineered Lipocalin Proteins as an Alternative Antimicrobial Strategy

Authors: Martin Dauner; Arne Skerra;

Scavenging Bacterial Siderophores with Engineered Lipocalin Proteins as an Alternative Antimicrobial Strategy

Abstract

AbstractIron acquisition mediated by siderophores, high‐affinity chelators for which bacteria have evolved specific synthesis and uptake mechanisms, plays a crucial role in microbiology and in host–pathogen interactions. In the ongoing fight against bacterial infections, this area has attracted biomedical interest. Beyond several approaches to interfere with siderophore‐mediated iron uptake from medicinal and immunochemistry, the development of high‐affinity protein scavengers that tightly complex the siderophores produced by pathogenic bacteria has appeared as a novel strategy. Such binding proteins have been engineered based on siderocalin—also known as lipocalin 2—an endogenous human scavenger of enterobactin and bacillibactin that controls the systemic spreading of commensal bacteria such as Escherichia coli. By using combinatorial protein design, siderocalin was reshaped to bind several siderophores from Pseudomonas aeruginosa and, in particular, petrobactin from Bacillus anthracis, none of which is recognized by the natural protein. Such engineered versions of siderocalin effectively suppress the growth of corresponding pathogenic bacteria by depriving them of their iron supply and offer the potential to complement antibiotic therapy in situations of acute or persistent infection.

Countries
Germany, Germany
Keywords

info:eu-repo/classification/ddc/572, Bacteria, 572, Siderophores, Minireviews, Bacterial Infections, Anti-Bacterial Agents, Lipocalin-2, Host-Pathogen Interactions, Humans, Protein Binding, ddc: ddc:

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    28
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
28
Top 10%
Average
Top 10%
Green
hybrid