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DNA Bacteriophages

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Bacteriophages, or phages, are viruses that specifically infect bacteria, utilizing their genetic material to hijack host cellular machinery for replication. DNA bacteriophages employ single-stranded DNA (ssDNA) or double-stranded DNA (dsDNA) genomes. These phages exhibit diverse replication strategies and host interactions, influencing their ecological roles and applications in biotechnology and medicine.ssDNA BacteriophagesssDNA phages, with their small genomes, utilize unique strategies to...
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Bacteriophages, also known as phages, are specialized viruses that infect bacteria. A key characteristic of phages is their distinctive “head-tail” morphology. A phage begins the infection process (i.e., lytic cycle) by attaching to the outside of a bacterial cell. Attachment is accomplished via proteins in the phage tail that bind to specific receptor proteins on the outer surface of the bacterium. The tail injects the phage’s DNA genome into the bacterial cytoplasm. In the...
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In contrast to the lytic cycle, phages infecting bacteria via the lysogenic cycle do not immediately kill their host cell. Instead, they combine their genome with the host genome, allowing the bacteria to replicate the phage DNA along with the bacterial genome. The incorporated copy of the phage genome is called the prophage. Some prophages can re-activate and enter the lytic cycle. This often occurs in response to a perturbation, such as DNA damage, but can also transpire in the absence of...
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Bacteriophages, or phages, are viruses that specifically infect bacteria. Among them, T-even bacteriophages, such as T4, exhibit a well-characterized lytic replication cycle in Escherichia coli (E. coli). This process ensures the rapid proliferation of the virus while ultimately leading to the destruction of the bacterial host.Attachment and DNA InjectionThe infection process begins with the recognition and binding of the T4 phage to the E. coli cell surface. Tail fibers of the phage...
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The lysogenic cycle is a crucial viral replication strategy that allows bacteriophages to persist within host cells without immediately destroying them. This process is primarily observed in temperate phages, such as bacteriophage lambda (λ), which infects Escherichia coli. The cycle allows the viral genome to persist across bacterial generations while keeping host cells viable.Integration of the Viral GenomeUpon infection, bacteriophage lambda attaches to the bacterial surface and injects...
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Bacteria and archaea are susceptible to viral infections just like eukaryotes; therefore, they have developed a unique adaptive immune system to protect themselves. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) are present in more than 45% of known bacteria and 90% of known archaea.
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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins

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Computational approaches to predict bacteriophage-host relationships.

Robert A Edwards1, Katelyn McNair2, Karoline Faust3

  • 1Department of Computer Science, San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, USA Department of Marine Biology, Institute of Biology, Federal University of Rio de Janeiro, CEP 21941-902, Brazil Division of Mathematics and Computer Science, Argonne National Laboratory, 9700 S. Cass Ave, Argonne, IL 60439, USA.

FEMS Microbiology Reviews
|December 15, 2015
PubMed
Summary

Computational tools can predict which bacteria bacteriophages (viruses that infect bacteria) infect. Analyzing phage-host signals reveals significant links, advancing our understanding of virus-host interactions for medical and industrial uses.

Keywords:
CRISPRco-occurrencemetagenomicsoligonucleotide usagephagesviruses of microbes

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Area of Science:

  • Virology
  • Bioinformatics
  • Microbial Ecology

Background:

  • Metagenomics enables virus discovery but not host identification.
  • Predicting virus-host interactions is crucial due to the vast virosphere.
  • Bacteriophages are abundant and diverse in environmental metagenomes.

Purpose of the Study:

  • To review and assess computational tools for predicting bacteriophage-host relationships.
  • To evaluate the effectiveness of in silico phage-host signals.

Main Methods:

  • Analysis of 820 phages with annotated hosts.
  • Assessment of sequence homology, compositional, and abundance-based methods.
  • Evaluation of in silico phage-host signals.

Main Results:

  • Sequence homology is most effective for known phage-host pairs.
  • Compositional and abundance methods offer significant predictive signals for novel viruses.
  • All reviewed signals demonstrate a significant link between phages and their hosts.

Conclusions:

  • Computational approaches can predict phage-host relationships.
  • Leveraging knowledge of coevolutionary mechanisms aids prediction.
  • These methods have potential applications in medicine and industry.