Ribosome synthesis is one of the most energy-intensive processes in a growing cell, consuming >60% of cellular energy reserves. As such, ribosome biogenesis is highly sensitive to stress to prevent costly expenditures under adverse conditions. Moreover, successful assembly requires precise stoichiometric balance between ribosomal proteins and ribosomal RNAs (rRNA). Here, we define novel regulatory mechanisms of ribosome biogenesis under stress that reveal previously unrecognized aspects of rRNA maturation. We demonstrate that early pre-rRNA processing is particularly sensitive to stress induced by environmentally relevant heavy metals. Surprisingly, our analysis shows that 5′ and 3′ end processing can be uncoupled in human cells, with 3′ end cleavage occurring independently of 5′ end processing. We further show that classical inducers of endoplasmic reticulum stress suppress ribosomal protein synthesis without inhibiting rRNA transcription, leading to an imbalance between these essential components of ribosome assembly. This imbalance may exacerbate cellular stress and compromise proteostasis. Together, our findings uncover stress-specific checkpoints in ribosome biogenesis that link environmental exposures to disrupted nucleolar function and highlight new layers of regulation in human rRNA maturation.

All eukaryotes, including yeast, plants, animals and humans, possess linear chromosomes. The conserved eukaryotic telomere-telomerase systems, originated and evolved over 1 billion years, protect the chromosomal ends and regulate critical physiological functions through complex networks. In this study, we replace the endogenous eukaryotic telomeres in the single-chromosome yeast Saccharomyces cerevisiae with the prokaryotic telomere system TelN/tos from the Escherichia phage N15, which forms a closed hairpin structure, by interrupting the MRX/Sae2 pathway. The prokaryotic telomeres effectively protect linear chromosomal ends and prevent genetic instability. Through adaptive evolution, we identify yeast strains harboring additional mutations (TEL1 and CYR1) that restore functional MRX/Sae2 activity, thereby improving host fitness and meiotic capacity. Interestingly, the two-associated TelN/tos telomeres position deeper into chromosomes and exhibit increased interactions with their adjacent regions. The successful replacement of a complex eukaryotic chromosomal telomere with a simple bacteriophage system demonstrates functional equivalence between these divergent systems, implying possible natural origins of such stochasticity (e.g., horizontal gene transfers). Furthermore, these engineered strains facilitate development of a tos-YAC system that enabled iterative assembly and stable maintenance of megabase-level heterogeneous DNA (1.23-2.77 Mb), providing a robust platform for large-scale DNA manipulation. Telomeric systems are conserved across eukaryotes and may have originated over 1 billion years ago. Here the authors replaced yeast’s telomeres with a bacterial virus system, resulting in a stable functional assembly of DNA molecules up to 2.77 Mb, offering insights into the possible origins of telomeres.

Prokaryotic organisms have evolved unique strategies to acquire immunity against the constant threat of bacteriophage (phage) and mobile genetic elements. Hna is a broadly distributed anti-phage immune system that confers resistance against diverse phage by eliciting an abortive infection response. Using a combination of biochemistry, cryo-electron microscopy, and single-molecule fluorescence imaging, we reveal that Hna functions as a 3’—5’ single-stranded DNA exonuclease that forms an auto-inhibited dimer under physiological ATP concentrations. Biochemical and mutational analyses demonstrate that Hna catalytic outputs are governed by kinetic partitioning between ATPase and nuclease active sites. Disruption of this balance enhances DNA cleavage and causes cellular toxicity. Furthermore, we show that a phage-encoded single-stranded DNA-binding protein (5 A SSB) destabilizes the autoinhibited Hna dimer and shifts catalytic partitioning toward dysregulated nuclease activation. Conversely, phage escape mutants encode SSB variants that evade Hna surveillance by adopting higher order stoichiometries with enhanced DNA binding affinity. Our work establishes the molecular basis of Hna-mediated antiphage activity and provides insights into how phage-encoded proteins can directly stimulate a bacterial immune response. Bacteria use diverse immune systems to defend against viral infection. Here, Hooper et al. show that the Hna system is an ATP-regulated DNA nuclease activated by phage proteins. They further reveal how viruses can both trigger and evade this bacterial immune response.

Maize (Zea Mays) is one of the world’s most important staple crops, providing food for humans and feed for livestock. However, its production is threatened by a range of stresses, including crop diseases, which significantly reduce yields, particularly in smallholder farming systems. Traditional disease detection methods, such as visual inspection, are often labor-intensive, subjective, and prone to error, leading to delayed interventions and widespread crop losses. This study uses unmanned aerial vehicle (UAV) remote sensing and machine learning (ML) to investigate the feasibility of detecting maize leaf diseases in a smallholder farm located in the Mopani District of Limpopo Province, South Africa. UAV-derived vegetation indices including NDVI, GNDVI, and NDRE were combined with UAV multispectral bands and the three ML algorithms, namely – support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), to first distinguish healthy from diseased plants and then to classify specific maize diseases. The SVM algorithm achieved the highest accuracy in both, distinguishing healthy and diseased crops from other land cover classes (91.73%) and in distinguishing specific diseases (89.41%). Among the diseases identified, Southern Corn Leaf Blight was classified with the highest user’s accuracy, while phosphorus deficiency had the lowest user’s classification accuracy. The results demonstrate the potential of integrating UAV-based multispectral imaging and ML for precision agriculture by providing timely, spatially detailed disease information that enables targeted management practices, reducing crop losses and enhancing food security for smallholder farmers.