• Molecular architecture of tailed double-stranded DNA phages
  • Tradeoffs in bacteriophage life histories
  • Application of bacteriophages for detection of foodborne pathogens
  • Applying the ResFinder and VirulenceFinder web-services for easy identification of acquired antibiotic resistance and <i>E. coli</i> virulence genes in bacteriophage and prophage nucleotide sequences

 Molecular architecture of tailed double-stranded DNA phages

Andrei Fokine and Michael G Rossmann


The tailed double-stranded DNA bacteriophages, or Caudovirales, constitute ~96% of all the known phages. Although these phages come in a great variety of sizes and morphology, their virions are mainly constructed of similar molecular building blocks via similar assembly pathways. Here we review the structure of tailed double-stranded DNA bacteriophages at a molecular level, emphasizing the structural similarity and common evolutionary origin of proteins that constitute these virions.


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 Tradeoffs in bacteriophage life histories

Eric C Keen


Viruses are the most abundant biological entities on the planet, yet most classical principles of evolutionary biology and ecology were not developed with viruses in mind. Here, the concept of biological tradeoffs, a fundamental tenet of life history theory, is examined in the context of bacteriophage biology. Specifically, several important parameters of phage life histories—replication, persistence, host range, and adsorption—are evaluated for tradeoffs. Available data indicate that replication rate is strongly negatively correlated with both persistence and host range, suggesting that the well-documented tradeoff in macroorganisms between offspring production and offspring quality also applies to phages. The biological tradeoffs that appear to characterize viruses’ life histories have potential importance for viral evolution, ecology, and pathogenesis.


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 Application of bacteriophages for detection of foodborne pathogens

Mathias Schmelcher and Martin J Loessner


Bacterial contamination of food products presents a challenge for the food industry and poses a high risk for the consumer. Despite increasing awareness and improved hygiene measures, foodborne pathogens remain a threat for public health, and novel methods for detection of these organisms are needed. Bacteriophages represent ideal tools for diagnostic assays because of their high target cell specificity, inherent signal-amplifying properties, easy and inexpensive production, and robustness. Every stage of the phage lytic multiplication cycle, from the initial recognition of the host cell to the final lysis event, may be harnessed in several ways for the purpose of bacterial detection. Besides intact phage particles, phage-derived affinity molecules such as cell wall binding domains and receptor binding proteins can serve for this purpose. This review provides an overview of existing phage-based technologies for detection of foodborne pathogens, and highlights the most recent developments in this field, with particular emphasis on phage-based biosensors.


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 Applying the ResFinder and VirulenceFinder web-services for easy identification of acquired antibiotic resistance and E. coli virulence genes in bacteriophage and prophage nucleotide sequences

Kortine Annina Kleinheinz, Katrine Grimstrup Joensen and Mette Voldby Larsen


Extensive research is currently being conducted on the use of bacteriophages for applications in human medicine, agriculture and food manufacturing. However, phages are important vehicles of horisontal gene transfer and play a significant role in bacterial evolution. As a result, concern has been raised that this increased use and dissemination of phages could result in spread of deleterious genes, e.g., antibiotic resistance and virulence genes.

Meanwhile, in the wake of the genomic era, several tools have been developed for characterization of bacterial genomes. Here we describe how two of these tools, ResFinder and VirulenceFinder, can be used to identify acquired antibiotic resistance and virulence genes in phage genomes of interest. The general applicability of the tools is demonstrated on data sets of 1,642 phage genomes and 1,442 predicted prophages.


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