Integrative and conjugative elements (ICEs) are major drivers of horizontal gene transfer and bacterial genome evolution. Although ICE-encoded regulatory circuits have been extensively characterized, the impact of host physiology on the stability of integrated ICEs remains poorly understood. Here, we identify a host-dependent pathway that links specific host translation perturbations to loss of the ICE TnSmu1 in Streptococcus mutans. Analysis of host-gene deletion mutants revealed that disruption of fmt, rnjA, or rnjB—three translation-associated host genes—reproducibly promoted TnSmu1 loss through a mechanism that bypasses the canonical ICE-encoded metalloprotease ImmA but remains dependent on the native attachment site attR. This phenotype was selective, as mutations affecting other essential cellular functions, including protein folding, tRNA modification, cell division, and fatty acid biosynthesis, failed to destabilize TnSmu1 despite undergoing the same experimental evolution and accumulating adaptive genomic changes. Preventing TnSmu1 loss in these translation-associated mutants markedly reduced bacterial growth, whereas loss of the element improved fitness, indicating that ICE elimination alleviates the cost associated with TnSmu1 retention under these conditions. Finally, we show that the relationship between host translation and TnSmu1 stability extends to a genetically distinct S. mutans clinical isolate, although with strain-dependent penetrance. Together, these findings identify host translational state as an important physiological determinant of TnSmu1 stability and reveal that bacterial hosts can influence the maintenance of integrated mobile genetic elements through mechanisms that extend beyond element-encoded regulatory circuits.
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It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
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