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Related Concept Videos

Lytic Cycle of Bacteriophages01:30

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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, 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, 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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Related Experiment Video

Updated: Feb 19, 2026

Synthesis of Infectious Bacteriophages in an E. coli-based Cell-free Expression System
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Computational Modeling of Bacteriophage Production for Process Optimization.

Konrad Krysiak-Baltyn1,2, Gregory J O Martin2, Sally L Gras3,4

  • 1The Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC, 3010, Australia.

Methods in Molecular Biology (Clifton, N.J.)
|November 10, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a computational model and open-source R-script (ppSim) to optimize bacteriophage production. The model, validated with experimental data, successfully maximized production rates in a two-stage bioreactor system.

Keywords:
Bacteriophage dynamicsComputational modelingProcess optimization

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Area of Science:

  • Biotechnology
  • Microbial Engineering
  • Computational Biology

Background:

  • Bacteriophage production requires optimization for cost-effectiveness and yield.
  • Existing methods lack efficient computational tools for process optimization.

Purpose of the Study:

  • To develop and present a computational model for optimizing bacteriophage production in a two-stage self-cycling process.
  • To provide an open-source R-script (ppSim) for simulating and optimizing bacteriophage yields.

Main Methods:

  • Development of a computational model incorporating theoretical and practical considerations for bacteriophage production.
  • Experimental determination of key kinetic parameters, including variable infection rates.
  • Utilization of the ppSim R-script for simulation and optimization of a two-stage bioreactor system.

Main Results:

  • The computational model accurately simulates bacteriophage production.
  • Optimization of a level sensor and cycle time in a two-stage bioreactor system.
  • Achieved a maximum production rate of 4.46 × 1010 bacteriophage particles/hour.

Conclusions:

  • The developed model and ppSim script enable effective optimization of bacteriophage production.
  • This approach allows users to enhance yields and reduce costs for their specific bacteriophage-bacteria systems.
  • Facilitates broader application of bacteriophage modeling in biopharmaceutical manufacturing.