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Updated: Apr 25, 2026

Precise Phage Mutagenesis with NgTET-Assisted CRISPR-Cas Systems
Published on: October 14, 2025
Challenges in predicting the evolutionary maintenance of a phage transgene
Matthew Schmerer1, Ian J Molineux2, Dilara Ally3
1Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, TX, USA.
Background:
In prior work, a phage engineered with a biofilm-degrading enzyme (dispersin B) cleared artificial, short-term biofilms more fully than the phage lacking the enzyme. An unresolved question is whether the transgene will be lost or maintained during phage growth - its loss would limit the utility of the engineering. Broadly supported evolutionary theory suggests that transgenes will be lost through a 'tragedy of the commons' mechanism unless the ecology of growth in biofilms meets specific requirements. We test that theory here.
Results:
Functional properties of the transgenic phage were identified. Consistent with the previous study, the dispersin phage was superior to unmodified phage at clearing short term biofilms grown in broth, shown here to be an effect attributable to free enzyme. However, the dispersin phage was only marginally better than control phages on short term biofilms in minimal media and was no better than control phages in clearing long term biofilms. There was little empirical support for the tragedy of the commons framework despite a strong theoretical foundation for its supposed relevance. The framework requires that the transgene imposes an intrinsic cost, yet the transgene was intrinsically neutral or beneficial when expressed from one part of the phage genome. Expressed from a different part of the genome, the transgene did behave as if intrinsically costly, but its maintenance did not benefit from spatially structured growth per se - violating the tragedy framework.
Conclusions:
Overall, the transgene was beneficial under many conditions, but no insight to its maintenance was attributable to the established evolutionary framework. The failure likely resides in system details that would be used to parameterize the models. Our study cautions against naive applications of evolutionary theory to synthetic biology, even qualitatively.
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