Abstract
Essential gene products carry out fundamental cellular activities in interaction with other components. However, the lack of essential gene mutants and appropriate methodologies to link essential gene functions with their partners poses significant challenges. We report here the generation in Streptococcus sanguinis strain SK36 of deletion mutants in 32 genes previously identified as essential, with 23 mutants showing extremely slow growth. The 23 genes corresponding to these mutants encode components of diverse pathways, are widely conserved among bacteria, and are essential in many other bacterial species. Whole-genome sequencing of 243 independently evolved populations of these mutants has identified >1,000 spontaneous potential suppressor mutations. Many of these mutations define new gene and pathway relationships, such as F1Fo-ATPase/V1Vo-ATPase/TrkA1-H1, which was demonstrated across multiple Streptococcus species. Our findings demonstrate that experimental evolution of slow-growing essential gene mutants provides a powerful strategy to identify compensatory mechanisms and functional interactions, offering new insights into bacterial gene networks.IMPORTANCEEssential genes are traditionally considered indispensable for bacterial survival, but how they interact with other cellular processes is not well understood. Here, we deleted essential genes from diverse pathways in Streptococcus sanguinis and found that many mutants survived, though with severely impaired growth. When allowed to evolve, these mutants repeatedly acquired spontaneous changes in other genes that restored fitness, uncovering compensatory pathways for disrupted functions. Notably, we identified gene-specific adaptations involving energy metabolism and ion transport, revealing unexpected connections between diverse cellular processes. Because many of these genes are widely conserved, our findings show that even essential functions can be bypassed through alternative routes. This work highlights the evolutionary flexibility of bacterial gene networks and provides a new approach to uncover hidden genetic interactions, offering potential insights into novel antimicrobial strategies.