Set Phages to Stun: Reducing the Virulence of Staph Aureus in Diabetic Foot Ulcers

A recent publication from our team in the journal Diabetes describes newly identified mechanisms to manipulate virulence factors of bacteria.

Click for the open access article.

We also thought you might enjoy this figure describing the process and promise of the use of prophages.

Illuminating Viral
Illuminating Viral “Dark Matter” Illuminating viral dark matter. A: The known protein universe. Bacterial genomes are produced by cultivating bacterial isolates, extracting and sequencing DNA to produce reads, assembling the reads into contigs, and scaffolding the contigs together to produce genomes. Gene-finding algorithms identify open reading frames (or genes) that are compared with known proteins to derive functional annotation. Bacteriophage genomes are produced similarly, except that pure phages are isolated and further purified from plaques in susceptible host cultures. Phages can also integrate in their host genomes as prophages. B: Into the unknown protein universe. New metagenomic techniques to sequence DNA directly from a sample offer a glimpse into uncultured bacteria and their phages. DNA is isolated from microbial communities and enriched for either bacteria or viral-like particles. Reads are assembled as in A; however, contigs are fragmentary, generally do not represent whole genomes, and may be misassembled with reads from closely related species. Single amplified genomes provide an alternative where community samples are enriched for a single bacterial species, making uncultured genomes obtainable. Likewise, bacterial sequence inserts can be maintained in fosmid libraries and sequenced to obtain large single-species uncultured bacterial genome fragments. Phage DNA can be discovered in community metagenomes enriched for bacteria as a result of prophage or phage actively infecting bacteria. Proteins from open reading frames on assembled contigs or reads are clustered and compared with known proteins to define known and unknown protein clusters (or the “known unknown”). Reads from unassembled metagenomes can also be compared using k-mers and evaluated using social network analyses to link clinical factors with community structure.

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